best final year project ieee 2015 by spectrum solutions pondicherry

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IEEE 2015 PROJECTS

CSE/IT/IS/ECE/E&I/EEE/MECHANICAL DEPARTMENT

SPECTRUM SOLUTIONS

COMPANY DETAIL:

SPECTRUM SOLUTIONS is a Pondicherry based R&D firm which always looks forward in the field

of science and technology to provide best technical support for the final year students. SPECTRUM has a great

team of technical experts for the design development of Electronic and software Systems using Embedded,

MATLAB, Java, Dot Net Technology.

SPECTRUM SOLUTIONS always concentrate us to provide quality products for various institutions

and students. We offer the projects in all domains for the students of Diploma, B.Tech/B.E

,M.Tech/M.E,MS,BCA,MCA etc. Our major concern is in the field of technical education to bridge the gap

between Industry and Academics. We are always in the good eyes of the Educational Institutions in India to

provide training & projects in Embedded Systems MATLAB and software technologies. We also provide

interview training for free of cost. We never stop in going that extra mile ahead in providing greater value to

own ideas of students, may it be in terms of providing adequate workforce proficient in highly application cost

oriented Embedded Systems or Software Systems.

EDUCATIONAL PARTNER:

International Journal of Research in Engineering and Advanced Technology (IJREAT)

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OUR FEATURES FOR STUDENTS:

1. 10 Days technical Project classes with practical.

2. 5 Days personality development classes.

3. Paper presentation guidance.

4. Individual Certificates.

5. Weekend Classes.

6. Students help with their job search queries.

7. Lower project cost without hampering the quality.

8. Project delivery on time.

POJECTS FOR - B.Tech/B.E, M.Tech/M.E,M.S,DIPLOMA,BCA,MCA

MAIL ID : [email protected]

WEBSITE : www.spectrumpondicherry.blogspot.in/

FACEBOOK : https://www.facebook.com/pages/Spectrum-Solutions/548721691855495?ref=hl

LANDLINE NO : 0413-2618850

MOBILE NO : 9381775781

ADDRESS : SPECTRUM SOLUTIONS

E-Mail: [email protected]

Contact: 0413-2618850, 9381775781

No-66,1st Floor

Near Rogini Nagar Govt Hospital

Poornankuppam

Pondicherry-07

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Appendix

Department Technology Page Number

1. CSE/IT/IS JAVA 5-22

2. CSE/IT/IS NS-2 22-30

3. ECE/EEE/MECHANICAL EMBEDDED 32-40

4. ECE/CSE MATLAB (Command) 42-64

5. EEE/ECE MATLAB (Simulink) 66-72

6. TRAINING PAMPHLET EMBEDDED,MATLAB,NETWORKING NETWORK SECURITY,PCB

DESIGNING

72-END

5

APPENDIX: D DotNet J Java IP Image Processing DM DataMining NS Network Security NW Networking MC Mobile Computing SC Service Computing

PD Parallel distribution

CC Cloud Computing

S.No Code Title Year Abstract 1 JCCZ-01 AuditFree

Cloud Storage

via Deniable

Attribute

based

Encryption

IEEE-2015 Cloud storage services have become increasingly popular.

Because of the importance of privacy, many cloud storage

encryption schemes have been proposed to protect data from

those who do not have access. All such schemes assumed that

cloud storage providers are safe and cannot be hacked;

however, in practice, some authorities (i.e., coercers) may

force cloud storage providers to reveal user secrets or

confidential data on the cloud, thus altogether circumventing

storage encryption schemes. In this paper, we present our

design for a new cloud storage encryption scheme that

enables cloud storage providers to create convincing fake

user secrets to protect user privacy. Since coercers cannot

tell if obtained secrets are true or not, the cloud storage

providers ensure that user privacy is still securely protected.

6

2 JCCZ-02 CHARM A

Cost efficient

Multi cloud

Data Hosting

Scheme with

High

Availability

IEEE-2015 Nowadays, more and more enterprises and organizations are

hosting their data into the cloud, in order to reduce the IT

maintenance cost and enhance the data reliability. However,

facing the numerous cloud vendors as well as their

heterogenous pricing policies, customers may well be

perplexed with which cloud(s) are suitable for storing their

data and what hosting strategy is cheaper. The general status

quo is that customers usually put their data into a single

cloud (which is subject to the vendor lock-in risk) and then

simply trust to luck. Based on comprehensive analysis of

various state-of-the-art cloud vendors, this paper proposes a

novel data hosting scheme (named CHARM) which

integrates two key functions desired. The first is selecting

several suitable clouds and an appropriate redundancy

strategy to store data with minimized monetary cost and

guaranteed availability. The second is triggering a transition

process to re-distribute data according to the variations of

data access pattern and pricing of clouds. We evaluate the

performance of CHARM using both trace-driven

simulations and prototype experiments. The results show

that compared with the major existing schemes, CHARM

not only saves around 20% of monetary cost but also

exhibits sound adaptability to data and price adjustments.

Index Terms—Multi-cloud; data hosting; cloud storage.

3 JCCZ-03 Enabling Cloud Storage Auditing with Key Exposure Resistance

IEEE-2015 Cloud storage auditing is viewed as an important service to

verify the integrity of the data in public cloud. Current

auditing protocols are all based on the assumption that the

client’s secret key for auditing is absolutely secure. However,

such assumption may not always be held, due to the possibly

weak sense of security and/or low security settings at the

client. If such a secret key for auditing is exposed, most of

the current auditing protocols would inevitably become

unable to work. In this paper, we focus on this new aspect of

cloud storage auditing. We investigate how to reduce the

damage of the client’s key exposure in cloud storage

auditing, and give the first practical solution for this new

problem setting. We formalize the definition and the security

model of auditing protocol with key-exposure resilience and

propose such a protocol. In our design, we employ the binary

tree structure and the pre-order traversal technique to

update the secret keys for the client. We also develop a novel

authenticator construction to support the forward security

and the property of blockless verifiability. The security proof

and the performance analysis show that our proposed

protocol is secure and efficient.

7

4 JCCZ-04 MobiContext_

Cloud

IEEE-2015 In recent years, recommendation systems have seen

significant evolution in the field of knowledge engineering.

Most of the existing recommendation systems based their

models on collaborative filtering approaches that make them

simple to implement. However, performance of most of the

existing collaborative filtering based recommendation system

suffers due to the challenges, such as: (a) cold start, (b) data

sparseness, and (c) scalability. Moreover, recommendation

problem is often characterized by the presence of many

conflicting objectives or decision variables, such as users’

preferences and venue closeness. In this paper, we proposed

MobiContext, a hybrid cloud based Bi Objective

Recommendation Framework (BORF) for mobile social

networks. The MobiContext utilizes multi objective

optimization techniques to generate personalized

recommendations. To address the issues pertaining to cold

start and data sparseness, the BORF performs data

preprocessing by using the Hub Average (HA) inference

model. Moreover, the Weighted Sum Approach (WSA) is

implemented for scalar optimization and an evolutionary

algorithm (NSGAII) is applied for vector optimization to

provide optimal suggestions to the users about a venue.

5 JCCZ-05 OPoR

Enabling Proof

of

Retrievability

in Cloud

Computing

with Resource

Constrained

Devices

IEEE-2015 Cloud Computing moves the application software and

databases to the centralized large data centers, where the

management of the data and services may not be fully

trustworthy. In this work, we study the problem of ensuring

the integrity of data storage in Cloud Computing. To reduce

the computational cost at user side during the integrity

verification of their data, the notion of public verifiability

has been proposed. However, the challenge is that the

computational burden is too huge for the users with

resource-constrained devices to compute the public

authentication tags of file blocks. To tackle the challenge, we

propose OPoR, a new cloud storage scheme involving a cloud

storage server and a cloud audit server, where the latter is

assumed to be semi-honest. In particular, we consider the

task of allowing the cloud audit server, on behalf of the cloud

users, to pre-process the data before uploading to the cloud

storage server and later verifying the data integrity. OPoR

outsources the heavy computation of the tag generation to

the cloud audit server and eliminates the involvement of user

in the auditing and in the preprocessing phases.

Furthermore, we strengthen the Proof of Retrievabiliy (PoR)

model to support dynamic data operations, as well as ensure

security against reset attacks launched by the cloud storage

server in the upload phase.

8

6 JCCZ-06 Privacy-

Preserving

Public

Auditing for

IEEE-2015 To protect outsourced data in cloud storage against

corruptions, adding fault tolerance to cloud storage together

with data integrity checking and failure reparation becomes

critical. Recently, regenerating codes have gained popularity

due to their lower repair bandwidth while providing fault

tolerance. Existing remote checking methods for

regenerating-coded data only provide private auditing,

requiring data owners to always stay online and handle

auditing, as well as repairing, which is sometimes

impractical. In this paper, we propose a public auditing

scheme for the regenerating-code-based cloud storage. To

solve the regeneration problem of failed authenticators in the

absence of data owners, we introduce a proxy, which is

privileged to regenerate the authenticators, into the

traditional public auditing system model. Moreover, we

design a novel public verifiable authenticator, which is

generated by a couple of keys and can be regenerated using

partial keys. Thus, our scheme can completely release data

owners from online burden. In addition, we randomize the

encode coefficients with a pseudorandom function to

preserve data privacy. Extensive security analysis shows that

our scheme is provable secure under random oracle model

and experimental evaluation indicates that our scheme is

highly efficient .

7 JCCZ-07 Profit

Maximization

Scheme

IEEE-2015 As an effective and efficient way to provide computing

resources and services to customers on demand, cloud

computing has become more and more popular. From cloud

service providers’ perspective, profit is one of the most

important considerations, and it is mainly determined by the

configuration of a cloud service platform under given

market demand. However, a single long-term renting scheme

is usually adopted to configure a cloud platform, which

cannot guarantee the service quality but leads to serious

resource waste. In this paper, a double resource renting

scheme is designed firstly in which short-term renting and

long-term renting are combined aiming at the existing issues.

This double renting scheme can effectively guarantee the

quality of service of all requests and reduce the resource

waste greatly. Secondly, a service system is considered as an

M/M/m+D queuing model and the performance indicators

that affect the profit of our double renting scheme are

analyzed, e.g., the average charge, the ratio of requests that

need temporary servers, and so forth. Thirdly, a profit

maximization problem is formulated for the double renting

scheme and the optimized configuration of a cloud platform

is obtained by solving the profit maximization problem.

9

8 JCCZ-08 Reactive

Resource

Provisioning

Heuristics for

IEEE-2015 The need for low latency analysis over high-velocity data

streams motivates the need for distributed continuous

dataflow systems. Contemporary stream processing systems

use simple techniques to scale on elastic cloud resources to

handle variable data rates. However, application QoS is also

impacted by variability in resource performance exhibited

by clouds and hence necessitates ―dynamic dataflows‖ which

utilize alternate tasks as additional control over the

dataflow’s cost and QoS. Further, we formalize an

optimization problem to represent deployment and runtime

resource provisioning that allows us to balance the

application’s QoS, value, and the resource cost. We propose

two greedy heuristics, centralized and sharded, based on the

variable-sized bin packing algorithm and compare against a

Genetic Algorithm (GA) based heuristic that gives a near-

optimal solution. A large-scale simulation study, using the

Linear Road Benchmark and VM performance traces from

the AWS public cloud, shows that while GA-based heuristic

provides a better quality schedule, the greedy heuristics are

more practical, and can intelligently utilize cloud elasticity to

mitigate the effect of variability, both in input data rates and

cloud resource performance, to meet the QoS of fast data

applications.

9 JCCZ-09 SAE Toward

Efficient Cloud

Data Analysis

IEEE-2015 Social network analysis is used to extract features of human

communities and proves to be very instrumental in a variety

of scientific domains. The dataset of a social network is often

so large that a cloud data analysis service, in which the

computation is performed on a parallel platform in the

could, becomes a good choice for researchers not

experienced in parallel programming. In the cloud, a

primary challenge to efficient data analysis is the

computation and communication skew (i.e., load imbalance)

among computers caused by humanity’s group behavior

(e.g., bandwagon effect). Traditional load balancing

techniques either require significant effort to re-balance

loads on the nodes, or cannot well cope with stragglers. In

this paper, we propose a general straggler-aware execution

approach, SAE, to support the analysis service in the cloud.

It offers a novel computational decomposition method that

factors straggling feature extraction processes into more

fine-grained sub-processes, which are then distributed over

clusters of computers for parallel execution. Experimental

results show that SAE can speed up the analysis by up to

1.77 times compared with state-of-the-art solutions.

10

10 JCCZ-10 Service

Operatorawar

e Trust

Scheme for

Resource

IEEE-2015 This paper proposes a service operator-aware trust scheme

(SOTS) for resource matchmaking across multiple clouds.

Through analyzing the built-in relationship between the

users, the broker, and the service resources, this paper

proposes a middleware framework of trust management that

can effectively reduce user burden and improve system

dependability. Based on multi-dimensional resource service

operators, we model the problem of trust evaluation as a

process of multi-attribute decision-making, and develop an

adaptive trust evaluation approach based on information

entropy theory. This adaptive approach can overcome the

limitations of traditional trust schemes, whereby the trusted

operators are weighted manually or subjectively. As a result,

using SOTS, the broker can efficiently and accurately

prepare the most trusted resources in advance, and thus

provide more dependable resources to users. Our

experiments yield interesting and meaningful observations

that can facilitate the effective utilization of SOTS in a large-

scale multi-cloud environment.

11 JCCZ-11 Towards

Optimized

Fine Grained

Pricing of

IEEE-2015 Although many pricing schemes in IaaS platform are

already proposed with pay-as-you-go and subscription/spot

market policy to guarantee service level agreement, it is still

inevitable to suffer from wasteful payment because of

coarsegrained pricing scheme. In this paper, we investigate

an optimized fine-grained and fair pricing scheme. Two

tough issues are addressed: (1) the profits of resource

providers and customers often contradict mutually; (2) VM-

maintenance overhead like startup cost is often too huge to

be neglected. Not only can we derive an optimal price in the

acceptable price range that satisfies both customers and

providers simultaneously, but we also find a best-fit billing

cycle to maximize social welfare (i.e., the sum of the cost

reductions for all customers and the revenue gained by the

provider). We carefully evaluate the proposed optimized

fine-grained pricing scheme with two large-scale real-world

production traces (one from Grid Workload Archive and the

other from Google data center). We compare the new

scheme to classic coarse-grained hourly pricing scheme in

experiments and find that customers and providers can both

benefit from our new approach. The maximum social

welfare can be increased up to 72:98% and 48:15% with

respect to DAS-2 trace and Google trace respectively.

11

12 JCCZ-12 Understanding

the

Performance

and

IEEE-2015 Commercial clouds bring a great opportunity to the

scientific computing area. Scientific applications usually

require significant resources, however not all scientists have

access to sufficien high end computing systems. Cloud

computing has gained the attention of scientists as a

competitive resource to run HPC applications at a

potentially lower cost. But as DIfferent infrastructure, it is

unclear whether clouds are capable of running scientific

applications with a reasonable performance per money

spent. This work provides a comprehensive evaluation of

EC2 cloud in different aspects. We first analyze the

potentials of the cloud by evaluating the raw performance of

different services of AWS such as compute, memory,

network and I /O. Based on the findings on the raw

performance, we then evaluate the performance of the

scientific applications running in the cloud. Finally, we

compare the performance of AWS with a private cloud, in

order to find the root cause of its limitations while running

scientific applications. This paper aims to assess the ability of

the cloud to perform well, as well as to evaluate the cost of

the cloud in terms of both raw performance and scientific

applications performance Furthermore, we evaluate other

services including S3, EBS and DynamoDB among many

AWS services in order to assess the abilities of those to be

used by scientific applications and frameworks. We also

evaluate a real scientific compng application through the

Swift parallel scripting System at scale.

13 JDMZ-13 Anonymizing

Collections of

Tree Struct

Data- Data

Engg

IEEE-2015 Collections of real-world data usually have implicit or

explicit structural relations. For example, databases link

records through foreign keys, and XML documents express

associations between different values through syntax.

Privacy preservation, until now, has focused either on data

with a very simple structure, e.g. relational tables, or on data

with very complex structure e.g. social network graphs, but

has ignored intermediate cases, which are the most frequent

in practice. In this work, we focus on tree structured data.

Such data stem from various applications, even when the

structure is not directly reflected in the syntax, e.g. XML

documents. A characteristic case is a database where

information about a single person is scattered amongst

different tables that are associated through foreign keys. The

paper defines k(m;n)-anonymity, which provides protection

against identity disclosure and proposes a greedy

anonymization heuristic that is able to sanitize large

datasets. The algorithm and the quality of the anonymization

are evaluated experimentally.

12

14 JDMZ-14 FOCS Fast

Overlapped

Community

Search

IEEE-2015 However, most of the existing algorithms that detect

overlapping communities assume that the communities are

denser than their surrounding regions and falsely identify

overlaps as communities. Further, many of these algorithms

are computationally demanding and thus, do not scale

reasonably with varying network sizes. In this article, we

propose FOCS (Fast Overlapped Community Search), an

algorithm that accounts for local connectedness in order to

identify overlapped communities. FOCS is shown to be

linear in number of edges and nodes. It additionally gains in

speed via simultaneous selection of multiple near-best

communities rather than merely the best, at each iteration.

FOCS outperforms some popular overlapped community

finding algorithms in terms of

15 JDMZ-15 Making Digital

Artifacts_Data

Engg

IEEE-2015 The current Web has no general mechanisms to make digital

artifacts — such as datasets, code, texts, and images —

verifiable and permanent. For digital artifacts that are

supposed to be immutable, there is moreover no commonly

accepted method to enforce this immutability. These

shortcomings have a serious negative impact on the ability to

reproduce the results of processes that rely onWeb

resources, which in turn heavily impacts areas such as

science where reproducibility is important. To solve this

problem, we propose trusty URIs containing cryptographic

hash values. We show how trusty URIs can be used for the

verification of digital artifacts, in a manner that is

independent of the serialization format in the case of

structured data files such as nano publications.

16 JDMZ-16 Privacy Policy

Inference of

User-Uploaded

IEEE-2015 With the increasing volume of images users share through

social sites, maintaining privacy has become a major

problem, as demonstrated by a recent wave of publicized

incidents where users inadvertently shared personal

information. In light of these incidents, the need of tools to

help users control access to their shared content is apparent.

Toward addressing this need, we propose an Adaptive

Privacy Policy Prediction (A3P) system to help users

compose privacy settings for their images. We propose a

two-level framework which according to the user’s available

history on the site, determines the best available privacy

policy for the user’s images being uploaded. Our solution

relies on an image classification framework for image

categories which may be associated with similar policies, and

on a policy prediction algorithm to automatically generate a

policy for each newly uploaded image, also according to

users’ social features.

13

17 JDMZ-17 RRW - A

Robust and

Reversible

Watermarking

IEEE-2015 Advancement in information technology is playing an

increasing role in the use of information systems comprising

relational databases. These databases are used effectively in

collaborative environments for information extraction;

consequently, they are vulnerable to security threats

concerning ownership rights and data tampering.

Watermarking is advocated to enforce ownership rights over

shared relational data and for providing a means for

tackling data tampering. When ownership rights are

enforced using watermarking, the underlying data

undergoes certain modifications; as a result of which, the

data quality gets compromised. Reversible watermarking is

employed to ensure data quality along-with data recovery.

However, such techniques are usually not robust against

malicious attacks and do not provide any mechanism to

selectively watermark a particular attribute by taking into

account its role in knowledge discovery. Therefore,

reversible watermarking is required that ensures; (i)

watermark encoding and decoding by accounting for the role

of all the features in knowledge discovery; and, (ii) original

data recovery in the presence of active malicious attacks.

18 JDMZ-18 Sparsity

Learning

Formulations

for Mining

IEEE-2015 Traditional clustering and feature selection methods

consider the data matrix as static. However, the data

matrices evolve smoothly over time in many applications. A

simple approach to learn from these time-evolving data

matrices is to analyze them separately. Such strategy ignores

the time-dependent nature of the underlying data. In this

paper, we propose two formulations for evolutionary co-

clustering and feature selection based on the fused Lasso

regularization. The evolutionary co-clustering formulation is

able to identify smoothly varying hidden block structures

embedded into the matrices along the temporal dimension.

Our formulation is very flexible and allows for imposing

smoothness constraints over only one dimension of the data

matrices. The evolutionary feature selection formulation can

uncover shared features in clustering from time-evolving

data matrices. We show that the optimization problems

involved are non-convex, non-smooth and non-separable. To

compute the solutions efficiently, we develop a two-step

procedure that optimizes the objective function iteratively.

We evaluate the proposed formulations using the Allen

Developing Mouse Brain Atlas data. Results show that our

formulations consistently outperform prior methods.

14

19 JDMZ-19 Structured

Learning_Kno

wledge

Discovery

IEEE-2015 Social identity linkage across different social media

platforms is of critical importance to business intelligence by

gaining from social data a deeper understanding and more

accurate profiling of users. In this paper, we propose a

solution framework, HYDRA, which consists of three key

steps: (I) we model heterogeneous behavior by long-term

topical distribution analysis and multi-resolution temporal

behavior matching against high noise and information

missing, and the behavior similarity are described by multi-

dimensional similarity vector for each user pair; (II) we

build structure consistency models to maximize the structure

and behavior consistency on users’ core social structure

across different platforms, thus the task of identity linkage

can be performed on groups of users, which is beyond the

individual level linkage in previous study; and (III) we

propose a normalized-margin-based linkage function

formulation, and learn the linkage function by multi-

objective optimization where both supervised pair-wise

linkage function learning and structure consistency

maximization are conducted towards a unified Pareto

optimal solution. The model is able to deal with drastic

information missing, and avoid the curse-of-dimensionality

in handling high dimensional sparse representation.

20 JDMZ-20 Subgraph

Matching with

Set Similarity

IEEE-2015 In real-world graphs such as social networks, Semantic Web

and biological networks, each vertex usually contains rich

information, which can be modeled by a set of tokens or

elements. In this paper, we study a subgraph matching with

set similarity (SMS2) query over a large graph database,

which retrieves subgraphs that are structurally isomorphic

to the query graph, and meanwhile satisfy the condition of

vertex pair matching with the (dynamic) weighted set

similarity. To efficiently process the SMS2 query, this paper

designs a novel lattice-based index for data graph, and

lightweight signatures for both query vertices and data

vertices. Based on the index and signatures, we propose an

efficient two-phase pruning strategy including set similarity

pruning and structure-based pruning, which exploits the

unique features of both (dynamic) weighted set similarity

and graph topology. We also propose an efficient

dominating-set-based subgraph matching algorithm guided

by a dominating set selection algorithm to achieve better

query performance. Extensive experiments on both real and

synthetic datasets demonstrate that our method outperforms

state-of-the-art methods by an order of magnitude.

15

21 JDMZ-21 The Impact of

View Histories

on Edit

Recommendati

ons

IEEE-2015 Recommendation systems are intended to increase developer

productivity by recommending files to edit. These systems

mine association rules in software revision histories.

However, mining coarse grained rules using only edit

histories produces recommendations with low accuracy, and

can only produce recommendations after a developer edits a

file. In this work, we explore the use of finer grained

association rules, based on the insight that view histories

help characterize the contexts of files to edit. To leverage this

additional context and fine grained association rules, we

have developed MI, a recommendation system extending

ROSE, an existing edit based recommendation system. We

then conducted a comparative simulation of ROSE and MI

using the interaction histories stored in the Eclipse Bugzilla

system. The simulation demonstrates that MI predicts the

files to edit with significantly higher recommendation

accuracy than ROSE (about 63% over 35%), and makes

recommendations earlier, often before developers begin

editing. Our results clearly demonstrate the value of

considering both views and edits in systems to recommend

files to edit, and results in more accurate, earlier, and more

flexible recommendations.

22 JDMZ-22 Towards

Effective Bug

Triage with

Software Data

Reduction

Techniques

IEEE-2015 Software companies spend over 45 percent of cost in dealing

with software bugs. An inevitable step of fixing bugs is bug

triage, which aims to correctly assign a developer to a new

bug. To decrease the time cost in manual work, text

classification techniques are applied to conduct automatic

bug triage. In this paper, we address the problem of data

reduction for bug triage, i.e., how to reduce the scale and

improve the quality of bug data. We combine instance

selection with feature selection to simultaneously reduce data

scale on the bug dimension and the word dimension. To

determine the order of applying instance selection and

feature selection, we extract attributes from historical bug

data sets and build a predictive model for a new bug data set.

We empirically investigate the performance of data

reduction on totally 600,000 bug reports of two large open

source projects, namely Eclipse and Mozilla. The results

show that our data reduction can effectively reduce the data

scale and improve the accuracy of bug triage. Our work

provides an approach to leveraging techniques on data

processing to form reduced and high-quality bug data in

software development and maintenance.

16

23 JIPZ-23 Multiview

Alignment

Hashing for

Efficient Image

IEEE-2015 Hashing is a popular and efficient method for nearest

neighbor search in large-scale data spaces, by embedding

high-dimensional feature descriptors into a similarity

preserving Hamming space with a low dimension. For most

hashing methods, the performance of retrieval heavily

depends on the choice of the high-dimensional feature

descriptor. Furthermore, a single type of feature cannot be

descriptive enough for different images when it is used for

hashing. Thus, how to combine multiple representations for

learning effective hashing functions is an imminent task. In

this paper, we present a novel unsupervised Multiview

Alignment Hashing (MAH) approach based on Regularized

Kernel Nonnegative Matrix Factorization (RKNMF),

24 JIPZ-24 YouTube

Video

Promotion by

Cross-network

IEEE-2015 The emergence and rapid proliferation of various social

media networks have reshaped the way how video contents

are generated, distributed and consumed in traditional video

sharing portals. Nowadays, online videos can be accessed

from far beyond the internal mechanisms of the video

sharing portals, such as internal search and front page

highlight. Recent studies have found that external referrers,

such as external search engines and other social media

websites, arise to be the new and important portals to Lead

users to online videos. In this paper, we introduce a novel

cross-network collaborative application to help drive the

online traffic for given videos in traditional video portal

YouTube by leveraging the high propagation efficiency of

the popular Twitter followees.

25 JMCZ-01 Modelling and

Analysis_Mob

Comp

IEEE-2015 —In opportunistic networks, direct communication between

mobile devices is used to extend the set of services accessible

through cellular or WiFi networks. Mobility patterns and

their impact in such networks have been extensively studied.

In contrast, this has not been the case with communication

traffic patterns, where homogeneous traffic between all

nodes is usually assumed. This assumption is generally not

true, as node mobility and social characteristics can

significantly affect the end-to-end traffic demand between

them. To this end, in this paper we explore the joint effect of

traffic patterns and node mobility on the performance of

popular forwarding mechanisms, both analytically and

through simulations. Among the different insights stemming

from our analysis, we identify conditions under which

heterogeneity renders the added value of using extra relays

more/less useful. Furthermore, we confirm the intuition that

an increasing amount of heterogeneity closes the

performance gap between different forwarding policies,

making endto- end routing more challenging in some cases.

17

26 JMCZ-02 Towards

Information

Diffusion in

Mobile Social

IEEE-2015 The emerging of mobile social networks opens opportunities

for viral marketing. However, before fully utilizing mobile

social networks as a platform for viral marketing, many

challenges have to be addressed. In this paper, we address

the problem of identifying a small number of individuals

through whom the information can be diffused to the

network as soon as possible, referred to as the diffusion

minimization problem. Diffusion minimization under the

probabilistic diffusion model can be formulated as an

asymmetric k- center problem which is NP-hard, and the

best known approximation algorithm for the asymmetric k-

center problem has approximation ratio of log_ n and time

complexity O(n5). Clearly, the performance and the time

complexity of the approximation algorithm are not

satisfiable in large-scale mobile social networks.

27 JMMZ-01 Color

imaging_Multi

media

IEEE-2015 Multimedia data with associated semantics is omnipresent in

today’s social online platforms in the form of keywords, user

comments, and so forth. This article presents a statistical

framework designed to infer knowledge in the imaging

domain from the semantic domain. Note that this is the

reverse direction of common computer vision applications.

The framework relates keywords to image characteristics

using a statistical significance test. It scales to millions of

images and hundreds of thousands of keywords. We

demonstrate the usefulness of the statistical framework with

three color imaging applications: 1) semantic image

enhancement: re-render an image in order to adapt it to its

semantic context; 2) color naming: find the color triplet for a

given color name; and 3) color palettes: find a palette of

colors that best represents a given arbitrary semantic

context and that satisfies established harmony constraints.

28 JPDZ-01 Secure

Distributed

Deduplication

Systems with

Improved

Reliability -01-

Secure

Distributed

Deduplication

Systems with

Improved

Reliability

IEEE-2015 Data deduplication is a technique for eliminating duplicate

copies of data, and has been widely used in cloud storage to

reduce storage space and upload bandwidth. However, there

is only one copy for each file stored in cloud even if such a

file is owned by a huge number of users. As a result,

deduplication system improves storage utilization while

reducing reliability. Furthermore, the challenge of privacy

for sensitive data also arises when they are outsourced by

users to cloud. Aiming to address the above security

challenges, this paper makes the first attempt to formalize

the notion of distributed reliable deduplication system. We

propose new distributed deduplication systems with higher

reliability in which the data chunks are distributed across

multiple cloud servers.

18

29 JPDZ-02 Service

Operatorawar

e Trust

Scheme for

Resource

IEEE-2015 This paper proposes a service operator-aware trust scheme

(SOTS) for resource matchmaking across multiple clouds.

Through analyzing the built-in relationship between the

users, the broker, and the service resources, this paper

proposes a middleware framework of trust management that

can effectively reduce user burden and improve system

dependability. Based on multi-dimensional resource service

operators, we model the problem of trust evaluation as a

process of multi-attribute decision-making, and develop an

adaptive trust evaluation approach based on information

entropy theory. This adaptive approach can overcome the

limitations of traditional trust schemes, whereby the trusted

operators are weighted manually or subjectively. As a result,

using SOTS, the broker can efficiently and accurately

prepare the most trusted resources in advance, and thus

provide more dependable resources to users. Our

experiments yield interesting and meaningful observations

that can facilitate the effective utilization of SOTS in a large-

scale multi-cloud environment.

30 JSCZ-01 A Trust-Aware

Service

Brokering

Scheme

IEEE-2015 Oriented by requirement of trust management in multiple

cloud environment, this paper presents T-broker, a

trustaware service brokering scheme for efficient matching

cloud services (or resources) to satisfy various user requests.

First, a trusted third party-based service brokering

architecture is proposed for multiple cloud environment, in

which the T-broker acts as a middleware for cloud trust

management and service matching. Then, T-broker uses a

hybrid and adaptive trust model to compute the overall trust

degree of service resources, in which trust is defined as a

fusion evaluation result from adaptively combining the

direct monitored evidence with the social feedback of the

service resources. More importantly, T-broker uses the

maximizing deviation method to compute the direct

experience based on multiple key trusted attributes of

service resources, which can overcome the limitations of

traditional trust schemes, in which the trusted attributes are

weighted manually or subjectively. Finally, T-broker uses a

lightweight feedback mechanism, which can effectively

reduce networking risk and improve system efficiency. The

experimental results show that, compared with the existing

approaches, our T-broker yields very good results in many

typical cases, and the proposed system is robust to deal with

various numbers of dynamic service behavior from multiple

cloud sites.

19

31 JSCZ-02 Collusion-

Tolerable

Privacy-

Preserving

Sum and

IEEE-2015 Much research has been conducted to securely outsource

multiple parties’ data aggregation to an untrusted

aggregator without disclosing each individual’s privately

owned data, or to enable multiple parties to jointly aggregate

their data while preserving privacy. However, those works

either require secure pair-wise communication channels or

suffer from high complexity. In this paper, we consider how

an external aggregator or multiple parties can learn some

algebraic statistics (e.g., sum, product) over participants’

privately owned data while preserving the data privacy. We

assume all channels are subject to eavesdropping attacks,

and all the communications throughout the aggregation are

open to others. We first propose several protocols that

successfully guarantee data privacy under semi-honest

model, and then present advanced protocols which tolerate

up to k passive adversaries who do not try to tamper the

computation. Under this weak assumption, we limit both the

communication and computation complexity of each

participant to a small constant. At the end, we present

applications which solve several interesting problems via our

protocols.

32 JSCZ-03 Control Cloud

Data Access

Privilege and

Anonymity

With Fully

Anonymous

Attribute-

Based

Encryption

IEEE-2015 Cloud computing is a revolutionary computing paradigm,

which enables flexible, on-demand, and low-cost usage of

computing resources, but the data is outsourced to some

cloud servers, and various privacy concerns emerge from it.

Various schemes based on the attribute-based encryption

have been proposed to secure the cloud storage. However,

most work focuses on the data contents privacy and the

access control, while less attention is paid to the privilege

control and the identity privacy. In this paper, we present a

semi anonymous privilege control scheme Anony Control to

address not only the data privacy, but also the user identity

privacy in existing access control schemes. Anony Control

decentralizes the central authority to limit the identity

leakage and thus achieves semi anonymity. Besides, it also

generalizes the file access control to the privilege control, by

which privileges of all operations on the cloud data can be

managed in a fine-grained manner. Subsequently, we present

the Anony Control-F, which fully prevents the identity

leakage and achieve the full anonymity. Our security

analysis shows that both Anony Control and Anony Control-

F are secure under the decisional bilinear Diffie–Hellman

assumption, and our performance evaluation exhibits the

feasibility of our schemes.

20

33 JSCZ-04 Data Lineage

in Malicious

Environments

IEEE-2015 Intentional or unintentional leakage of confidential data is

undoubtedly one of the most severe security threats that

organizations face in the digital era. The threat now extends

to our personal lives: a plethora of personal information is

available to social networks and smartphone providers and

is indirectly transferred to untrustworthy third party and

fourth party applications. In this work, we present a generic

data lineage framework LIME for data flow across multiple

entities that take two characteristic, principal roles (i.e.,

owner and consumer). We define the exact security

guarantees required by such a data lineage mechanism

toward identification of a guilty entity, and identify the

simplifying non-repudiation and honesty assumptions. We

then develop and analyze a novel accountable data transfer

protocol between two entities within a malicious

environment by building upon oblivious transfer, robust

watermarking, and signature primitives. Finally, we perform

an experimental evaluation to demonstrate the practicality of

our protocol and apply our framework to the important data

leakage scenarios of data outsourcing and social networks. In

general, we consider LIME , our lineage framework for data

transfer, to be an key step towards achieving accountability

by design.

34 JSCZ-05 Enabling

Cloud Storage

Auditing with

IEEE-2015 Cloud storage auditing is viewed as an important service to

verify the integrity of the data in public cloud. Current

auditing protocols are all based on the assumption that the

client’s secret key for auditing is absolutely secure. However,

such assumption may not always be held, due to the possibly

weak sense of security and/or low security settings at the

client. If such a secret key for auditing is exposed, most of

the current auditing protocols would inevitably become

unable to work. In this paper, we focus on this new aspect of

cloud storage auditing. We investigate how to reduce the

damage of the client’s key exposure in cloud storage

auditing, and give the first practical solution for this new

problem setting. We formalize the definition and the security

model of auditing protocol with key-exposure resilience and

propose such a protocol. In our design, we employ the binary

tree structure and the pre-order traversal technique to

update the secret keys for the client. We also develop a novel

authenticator construction to support the forward security

and the property of blockless verifiability. The security proof

and the performance analysis show that our proposed

protocol is secure and efficient.

21

35 JSCZ-06 Formalization

and

Verification_C

ybernetics

IEEE-2015 Group behavior interactions, such as multirobot teamwork

and group communications in social networks, are widely

seen in both natural, social, and artificial behavior related

applications. Behavior interactions in a group are often

associated with varying coupling relationships, for instance,

conjunction or disjunction. Such coupling relationships

challenge existing behavior representation methods, because

they involve multiple behaviors from different actors,

constraints on the interactions, and behavior evolution. In

addition, the quality of behavior interactions are not checked

through verification techniques. In this paper, we propose an

ontology-based behavior modeling and checking system

(OntoB for short) to explicitly represent and verify complex

behavior relationships, aggregations, and constraints. The

OntoB system provides both a visual behavior model and an

abstract behavior tuple to capture behavioral elements, as

well as building blocks. It formalizes various intra-coupled

interactions (behaviors conducted by the same actor) via

transition systems (TSs), and inter-coupled behavior

aggregations (behaviors conducted by different actors) from

temporal, inferential, and party-based perspectives.

36 JSCZ-07 Group Key

Agreement

with Local

Connectivity

IEEE-2015 In this paper, we study a group key agreement problem

where a user is only aware of his neighbors while the

connectivity graph is arbitrary. In our problem, there is no

centralized initialization for users. A group key agreement

with these features is very suitable for social networks.

Under our setting, we construct two efficient protocols with

passive security. We obtain lower bounds on the round

complexity for this type of protocol, which demonstrates that

our constructions are round efficient. Finally, we construct

an actively secure protocol from a passively secure one.

37 JSCZ-08 Privacy-

Preserving

Public

Auditing for

IEEE-2015 To protect outsourced data in cloud storage against

corruptions, adding fault tolerance to cloud storage together

with data integrity checking and failure reparation becomes

critical. Recently, regenerating codes have gained popularity

due to their lower repair bandwidth while providing fault

tolerance. Existing remote checking methods for

regenerating-coded data only provide private auditing,

requiring data owners to always stay online and handle

auditing, as well as repairing, which is sometimes impractical.

In this paper, we propose a public auditing scheme for the

regenerating-code-based cloud storage. To solve the

regeneration problem of failed authenticators in the absence

of data owners, we introduce a proxy, which is privileged to

regenerate the authenticators, into the traditional public

auditing system model.

22

38 JSEZ-01 Impact of

view_DM

IEEE-2015 Recommendation systems are intended to increase developer

productivity by recommending files to edit. These systems

mine association rules in software revision histories.

However, mining coarse-grained rules using only edit

histories produces recommendations with low accuracy, and

can only produce recommendations after a developer edits a

file. In this work, we explore the use of fine-grained

association rules, based on the insight that view histories

help characterize the contexts of files to edit. To leverage this

additional context and fine-grained association rules, we

have developed MI, a recommendation system extending

ROSE, an existing edit based recommendation system. We

then conducted a comparative simulation of ROSE and MI

using the interaction histories stored in the Eclipse Bugzilla

system. The simulation demonstrates that MI predicts the

files to edit with significantly higher recommendation

accuracy than ROSE (about 63% over 35%), and makes

recommendations earlier, often before developers begin

editing. Our results clearly demonstrate the value of

considering both views and edits in systems to recommend

files to edit, and results in more accurate, earlier, and more

flexible recommendations.

NS-2

39 NSZ-01 A Distributed

Fault-Tolerant

Topology

Control

Algorithm for

Heterogeneous

Wireless

Sensor

Networks

IEEE-2015 This paper introduces a distributed fault-tolerant topology

control algorithm, called the Disjoint Path Vector (DPV), for

heterogeneous wireless sensor networks composed of a large

number of sensor nodes with limited energy and computing

capability and several supernodes with unlimited energy

resources. The DPV algorithm addresses the k-degree

Anycast Topology Control problem where the main objective

is to assign each sensor’s transmission range such that each

has at least k-vertex-disjoint paths to supernodes and the

total power consumption is minimum. The resulting

topologies are tolerant to k _ 1 node failures in the worst

case. We prove the correctness of our approach by showing

that topologies generated by DPV are guaranteed to satisfy

k-vertex supernode connectivity. Our simulations show that

the DPV algorithm achieves up to 4-fold reduction in total

transmission power required in the network and 2-fold

reduction in maximum transmission power required in a

node compared to existing solutions.

23

40 NSZ-02 Adaptive

Algorithms for

Diagnosing

Large-Scale

Failures in

Computer

Networks

IEEE-2015 We propose a greedy algorithm, Cluster-MAX-COVERAGE

(CMC), to efficiently diagnose large-scale clustered failures.

We primarily address the challenge of determining faults

with incomplete symptoms. CMC makes novel use of both

positive and negative symptoms to output a hypothesis list

with a low number of false negatives and false positives

quickly. CMC requires reports from about half as many

nodes as other existing algorithms to determine failures with

100 percent accuracy. Moreover, CMC accomplishes this

gain significantly faster (sometimes by two orders of

magnitude) than an algorithm that matches its accuracy.

When there are fewer positive and negative symptoms at a

reporting node, CMC performs much better than existing

algorithms. We also propose an adaptive algorithm called

Adaptive-MAX-COVERAGE (AMC) that performs

efficiently during both independent and clustered failures.

During a series of failures that include both independent and

clustered, AMC results in a reduced number of false

negatives and false positives.

41 NSZ-03 Delay

Optimization

and Cross-

Layer Design

in Multihop

Wireless

Networks With

Network

Coding and

Successive

Interference

Cancelation

IEEE-2015 Network coding (NC) and multipacket reception with

successive interference cancelation (SIC) have been shown to

improve the performance of multihop wireless networks

(MWNs). However, previous work emphasized maximization

of network throughput without considering quality of service

(QoS) requirements, which may lead to high packet delays in

the network. The objective of this work is minimization of

packet delay in a TDMA-based MWN that is jointly utilizing

NC and SIC techniques for a given traffic demand matrix.

We assume conflictfree scheduling and allow multipath

routing. We formulate a cross-layer optimization that

assigns time slots to links in a way that the average packet

delay is minimized. The problem formulation results in a

difficult mixed integer nonlinear programming (MINLP)

that the state-of-art software can only solve for very small-

sized networks. For large networks, we develop a heuristic

approach that iteratively determines the optimal solution.

We present numerical results, which show that the average

packet delay and traffic handling capacity of a network,

using w/o NC+SIC, NC, SIC and NC+SIC schemes, improves

from left to right. The traffic capacity of NC+SIC is double

of the w/o NC+SIC. Thus, combined utilization of NC and

SIC techniques results in significant performance

improvement.

24

42 NSZ-04 Distributed

denial of

service attacks

in software-

defined

networking

with cloud

computing

IEEE-2015 Although software-defined networking (SDN) brings

numerous benefits by decoupling the control plane from the

data plane, there is a contradictory relationship between

SDN and distributed denial-of-service (DDoS) attacks. On

one hand, the capabilities of SDN make it easy to detect and

to react to DDoS attacks. On the other hand, the separation

of the control plane from the data plane of SDN introduces

new attacks. Consequently, SDN itself may be a target of

DDoS attacks. In this paper, we first discuss the new trends

and characteristics of DDoS attacks in cloud computing

environments. We show that SDN brings us a new chance to

defeat DDoS attacks in cloud computing environments, and

we summarize good features of SDN in defeating DDoS

attacks. Then we review the studies about launching DDoS

attacks on SDN and the methods against DDoS attacks in

SDN.In addition, we discuss a number of challenges that

need to be addressed to mitigate DDoS attached in SDN with

cloud computing. This work can help understand how to

make full use of SDN’s advantages to defeat DDoS attacks in

cloud computing environments and how to prevent SDN

itself from becoming a victim of DDoSattacks.

43 NSZ-05 Dynamic

Openflow-

Controlled

Optical Packet

Switching

Network

IEEE-2015 This paper presents and experimentally demonstrates the

generalized architecture of Open flow-controlled optical

packet switching (OPS) network. Open flow control is

enabled by introducing The Openflow/OPS agent into the

OPS network, which realizes the Openflow protocol

translation and message exchange between the Openflow

control plane and the underlying OPS nodes. With software-

defined networking (SDN) and Openflow technique, the

complex control functions of the conventional OPS network

can offloaded into a centralized and flexible control plane,

while promoted control and operations can be provided due

to centralized coordination of network resources.

Furthermore, a contentionaware routing/rerouting strategy

as well as a fast network adjustment mechanism is proposed

and demonstrated for the first time as advanced Openflow

control to route traffic and handle the network dynamics.

With centralized SDN/Openflow control, the OPS network

has the potential to have better resource utilization and

enhanced network resilience at lower cost and less node

complexity. Our work will accelerate the development of

both OPS and SDN evolution.

25

44 NSZ-06 Game-

Theoretic

Topology

Controlfor

Opportunistic

Localizationin

Sparse

Underwater

Sensor

Networks

IEEE-2015 In this paper, we propose a localization scheme named

Opportunistic Localization by Topology Control (OLTC),

specifically for sparse Underwater Sensor Networks

(UWSNs). In a UWSN, an unlocalized sensor node finds its

location by utilizing the spatio-temporal relation with the

reference nodes. Generally, UWSNs are sparsely deployed

because of the high implementation cost, and unfortunately,

the network topology experiences partitioning due to the

effect of passive node mobility. Consequently, most of the

underwater sensor nodes lack the required number of

reference nodes for localization in underwater environments.

The existing literature is deficient in addressing the problem

of node localization in the above mentioned scenario.

Antagonistically, however, we promote that even in such

sparse UWSN context, it is possible to localize the nodes by

exploiting their available opportunities.

45 NSZ-07 Improving

Physical-Layer

Security in

Wireless

Communicatio

ns Using

Diversity

Techniques

IEEE-2015 Due to the broadcast nature of radio propagation, wireless

transmission can be readily overheard by unauthorized users

for interception purposes and is thus highly vulnerable to

eavesdropping attacks. To this end, physical-layer security is

emerging as a promising paradigm to protect the wireless

communications against eavesdropping attacks by exploiting

the physical characteristics of wireless channels. This article

is focused on the investigation of diversity techniques to

improve physical-layer security differently from the

conventional artificial noise generation and beamforming

techniques, which typically consume additional power for

generating artificial noise and exhibit high implementation

complexity for beamformer design. We present several

diversity approaches to improve wireless physical-layer

security, including multiple-input multiple-output (MIMO),

multiuser diversity, and cooperative diversity. To illustrate

the security improvement through diversity, we propose a

case study

46 NSZ-08 Interference-

Based

Topology

Control

Algorithm for

Delay-

Constrained

Mobile Ad Hoc

Networks

IEEE-2015 As the foundation of routing, topology control should

minimize the interference among nodes, and increase the

network capacity. With the development of mobile ad hoc

networks (MANETs), there is a growing requirement of

quality of service (QoS) in terms of delay. In order to meet

the delay requirement, it is important to consider topology

control in delay constrained environment, which is

contradictory to the objective of minimizing interference. In

this paper, we focus on the delay-constrained topology

control problem, and take into account delay and

interference jointly.

26

47 NSZ-09 Joint Optimal

Data Rate and

Power

Allocation in

Lossy Mobile

Ad Hoc

Networks with

Delay-

Constrained

Traffics

IEEE-2015 In this paper, we consider lossy mobile ad hoc networks

where the data rate of a given flow becomes lower and lower

along its routing path. One of the main challenges in lossy

mobile ad hoc networks is how to achieve the conflicting goal

of increased network utility and reduced power

consumption, while without following the instantaneous state

of a fading channel. To address this problem, we propose a

cross-layer rate-effective network utility maximization

(RENUM) framework by taking into account the lossy

nature of wireless links and the constraints of rate outage

probability and average delay. In the proposed framework,

the utility is associated with the effective rate received at the

destination node of each flow instead of the injection rate at

the source of the flow. We then present a distributed joint

transmission rate, link power and average delay control

algorithm, in which explicit broadcast message passing is

required for power allocation algorithm.

48 NSZ-10 Max

Contribution

An Online

Approximation

of Optimal

Resource

Allocation in

Delay Tolerant

Networks

IEEE-2015 In this paper, a joint optimization of link scheduling, routing

and replication for delay-tolerant networks (DTNs) has been

studied. The optimization problems for resource allocation

in DTNs are typically solved using dynamic programming

which requires knowledge of future events such as meeting

schedules and durations. This paper defines a new notion of

approximation to the optimality for DTNs, called snapshot

approximation where nodes are not clairvoyant, i.e., not

looking ahead into future events, and thus decisions are

made using only contemporarily available knowledges.

Unfortunately, the snapshot approximation still requires

solving an NP-hard problem of maximum weighted

independent set (MWIS) and a global knowledge of who

currently owns a copy and what their delivery probabilities

are. This paper proposes an algorithm, Max-Contribution

(MC) that approximates MWIS problem with a greedy

method and its distributed online approximation algorithm,

Distributed Max-Contribution (DMC).

27

49 NSZ-11 Neighbor

Similarity

Trust against

Sybil Attack in

P2P E-

Commerce

IEEE-2015 Peer to peer (P2P) e-commerce applications exist at the edge

of the Internet with vulnerabilities to passive and active

attacks. These attacks have pushed away potential business

firms and individuals whose aim is to get the best benefit in

e-commerce with minimal losses. The attacks occur during

interactions between the trading peers as a transaction takes

place. In this paper, we propose how to address Sybil attack,

an active attack, in which peers can have bogus and multiple

identities to fake their owns. Most existing work, which

concentrates on social networks and trusted certification, has

not been able to prevent Sybil attack peers from doing

transactions. Our work exploits the neighbor similarity trust

relationship to address Sybil attack. In our approach,

duplicated Sybil attack peers can be identified as the

neighbor peers become acquainted and hence more trusted

to each other. Security and performance analysis shows that

Sybil attack can be minimized by our proposed neighbor

similarity trust.

50 NSZ-12 Power Control

and Soft

Topology

Adaptations in

Multihop

Cellular

Networks With

Multi-Point

Connectivity

IEEE-2015 The LTE standards account for the use of relays to enhance

coverage near the cell edge. In a traditional topology, a

mobile can either establish a direct link to the base station

(BS) or a link to the relay, but not both. In this paper, we

consider the benefit of multipoint connectivity in allowing

user equipment (UEs) to split their transmit power over

simultaneous links to the BS and the relay, in effect

transmitting two parallel flows. We model decisions by the

UEs as to: (i) which point of access to attach to (either a relay

or a relay and the BS or only the BS); and (ii) how to allocate

transmit power over these links so as to maximize their total

rate. We show that this flexibility in the selection of points of

access leads to substantial network capacity increase against

when nodes operate in a fixed network topology. Individual

adaptations by UEs, in terms of both point of access and

transmit power, are interdependent due to interference and

to the possibility of over-loading of the backhaul links.

28

51 NSZ-13 Privacy-

Preserving

Detection of

Privacy-

Preserving

Detection of

Sensitive Data

Exposure

IEEE-2015 Statistics from security firms, research institutions and

government organizations show that the number of data-leak

instances have grown rapidly in recent years. Among various

data-leak cases, human mistakes are one of the main causes

of data loss. There exist solutions detecting inadvertent

sensitive data leaks caused by human mistakes and to

provide alerts for organizations. A common approach is to

screen content in storage and transmission for exposed

sensitive information. Such an approach usually requires the

detection operation to be conducted in secrecy. However, this

secrecy requirement is challenging to satisfy in practice, as

detection servers may be compromised or outsourced. In this

paper, we present a privacypreserving data-leak detection

(DLD) solution to solve the issue where a special set of

sensitive data digests is used in detection. The advantage of

our method is that it enables the data owner to safely

delegate the detection operation to a semihonest provider

without revealing the sensitive data to the provider. We

describe how Internet service providers can offer their

customers DLD as an add-on service with strong privacy

guarantees. The evaluation results show that our method can

support accurate detection with very small number of false

alarms under various data-leak scenarios.

52 NSZ-14 Security-

Aware

Relaying

Scheme for

Cooperative

Networks With

Untrusted

Relay Nodes

IEEE-2015 This paper studies the problem of secure transmission in

dual-hop cooperative networks with untrusted relays, where

each relay acts as both a potential helper and an

eavesdropper. A security-aware relaying scheme is proposed,

which employs the alternate jamming and secrecy-enhanced

relay selection to prevent the confidential message from

being eavesdropped by the untrusted relays. To evaluate the

performance of the proposed strategies, we derive the lower

bound of the achievable ergodic secrecy rate (ESR), and

conduct the asymptotic analysis to examine how the ESR

scales as the number of relays increases.

29

53 NSZ-15 Self-

Organizing

Resource

Management

Framework in

OFDMA

Femtocells

IEEE-2015 Next generation wireless networks (i.e., WiMAX, LTE)

provide higher bandwidth and spectrum efficiency

leveraging smaller (femto) cells with orthogonal frequency

division multiple access (OFDMA). The uncoordinated,

dense deployments of femtocells however, pose several

unique challenges relating to interference and resource

management in OFDMA femtocell networks. Towards

addressing these challenges, we propose RADION, a

distributed resource management framework that effectively

manages interference across femtocells. RADION’s core

building blocks enable femtocells to opportunistically

determine the available resources in a completely distributed

and efficient manner. Further, RADION’s modular nature

paves the way for different resource management solutions

to be incorporated in the framework. We implement

RADION on a real WiMAX femtocell testbed deployed in a

typical indoor setting. Two distributed solutions are enabled

through RADION and their performance is studied to

highlight their quick self-organization into efficient resource

allocations.

54 NSZ-16 Statistical

Dissemination

Control in

Large

Machine-to-

Machine

Communicatio

n Networks

IEEE-2015 Cloud based machine-to-machine (M2M) communications

have emerged to achieve ubiquitous and autonomous data

transportation for future daily life in the cyber-physical

world. In light of the need of network characterizations, we

analyze the connected M2M network in the machine swarm

of geometric random graph topology, including degree

distribution, network diameter, and average distance (i.e.,

hops). Without the need of end-to-end information to escape

catastrophic complexity, information dissemination appears

an effective way in machine swarm. To fully understand

practical data transportation, G/G/1 queuing network model

is exploited to obtain average end-to-end delay and

maximum achievable system throughput. Furthermore, as

real applications may require dependable networking

performance across the swarm, quality of service (QoS)

along with large network diameter creates a new intellectual

challenge.

30

55 NSZ-17 Toward

Transparent

Coexistence for

Multihop

Secondary

Cognitive

Radio

Networks

IEEE-2015 The dominate spectrum sharing paradigm of today is

interference avoidance, where a secondary network can use

the spectrum only when such a use is not interfering with the

primary network. However, with the advances of physical-

layer technologies, the mindset of this paradigm is being

challenged. This paper explores a new paradigm called

―transparent coexistence‖ for spectrum sharing between

primary and secondary nodes in a multihop network

environment. Under this paradigm, the secondary network is

allowed to use the same spectrum simultaneously with the

primary network as long as their activities are ―transparent‖

(or ―invisible‖) to the primary network. Such transparency

is accomplished through a systematic interference

cancelation (IC) by the secondary nodes without any impact

on the primary network. Although such a paradigm has been

studied in the information theory (IT) and communications

(COMM) communities, it is not well understood in the

wireless networking community, particularly for multihop

networks.

32

S.No Code Title Year Abstract 56 EST-01 A Cooperative Train

Control Model for Energy Saving

IEEE-2015

Increasing attention is being paid to energy efficiency in subway systems to reduce operational cost and carbon emissions. Optimization of the driving strategy and efficient utilization of regenerative energy are two effective methods to reduce the energy consumption for electric subway systems. Based on a common scenario that an accelerating train can reuse the regenerative energy from a braking train on the opposite track, this paper proposes a cooperative train control model to minimize the practical energy consumption, i.e., the difference between traction energy and the reused regenerative energy. First, we design a numerical algorithm to calculate the optimal driving strategy with the given trip time, in which the variable traction force, braking force, speed limits, and gradients are considered.

57 EST-02 A High Reliability Wearable Device for Elderly Fall Detection

IEEE-2015 Falls are critical events among elderly people that requires timely rescue. In this paper we propose a fall detection system consisting of an inertial unit that includes triaxial accelerometer, gyroscope and magnetometer with efficient data fusion and fall detection algorithms. Starting from the raw data, the implemented orientation filter provides the correct orientation of the subject in terms of Yaw, Pitch and Roll angles. The system is tested according to experimental protocols, engaging volunteers who performed simulated falls, simulated falls with recovery and Activities of Daily Living (ADL). By placing our wearable sensor on the waist of the subject, the unit is able to achieve fall detection performance above those of similar systems proposed in literature.

58 EST-03 A Method for Uncertainty Assessment of Passive Sun -Induced Chlorophyll Fluorescence Retrieval by Using an Infrared Reference Light

IEEE-2015 Measurements of sun-induced chlorophyll fluorescence (SIF) over plant canopies provide a proxy for plant photosynthetic capacity and are of high interest for plant research. Together with spectral reflectance, SIF has the potential to act as a non-invasive approach to quantify photosynthetic plant traits from field to air- and spaceborne scales. But SIF is a small signal contribution to the reflected sunlight and often not distinguishable from sensor noise. SIF estimation is, therefore, affected by an unquantified uncertainty, making it difficult to estimate accurately how much SIF is truly emitted from the plant. To investigate and overcome this, we designed a device based on a spectrometer covering the visible range and equipped it with an LED emitting at the wavelength of SIF. Using this as a reference and applying thorough calibrations, we present consistent evidence of the instrument’s capability of SIF retrieval and accuracy estimations. The LED’s intensity was measured under sunlight with 1.27 ± 0.27 mW×sr-1m-2nm-1 stable over the day. The large increase of SIF due to the

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Kautsky effect was measured spectrally and temporally proving the biophysical origin of the signal. We propose rigorous tests for instruments intended to measure SIF and show ways to further improve the presented methods.

59 EST-04 A Runtime Integrity Monitoring Framework for Real-Time Relative Positioning Systems Based on GPS and DSRC

IEEE-2015 This paper provides a three-layered framework to monitor the positioning performance requirements of real-time relative positioning (RRP) systems of the Cooperative Intelligent Transport Systems that support cooperative collision warning (CCW) applications. These applications exploit state data of surrounding vehicles obtained solely from the Global Positioning System (GPS) and dedicated short-range communications (DSRC) units without using other sensors. To this end, this paper argues the need for the GPS/DSRC-based RRP systems to have an autonomous monitoring mechanism, since the operation of CCW applications is meant to augment safety on roads. The advantages of autonomous integrity monitoring are essential and integral to any safety-of-life system. The autonomous integrity monitoring framework proposed necessitates the RRP systems to detect/predict the unavailability of their subsystems and of the integrity monitoring module itself and, if available, to account for effects of data link delays and breakages of DSRC links, as well as of faulty measurement sources of GPS and/or integrated augmentation positioning systems, before the information used for safety warnings/alarms becomes unavailable, unreliable, inaccurate, or misleading.

60 EST-05 A Self-Sustainable Power Management System for Reliable Power Scaling Up of Sediment Microbial Fuel Cells

IEEE-2015 Sediment microbial fuel cells (SMFCs) are considered a promising renewable power source for remote monitoring Applications. However, existing SMFCs can only produce several mill watts of power, and the output power is not scaled linearly with the size of SMFCs. An effective alternative method to increase the output power is to independently operate multiple SMFCs, each of which has an optimal size for maximum power density. Independently operated SMFCs have electrically isolated electrodes (anodes/cathodes), which complicates the design of a suitable power management system (PMS). This paper describes the challenges in designing a PMS that can harvest energy from multiple independently operated (mio) SMFCs and accordingly proposes a design solution. From experimental results, the proposed PMS demonstrates reliable output power scaling up of mio-SMFC. The proposed PMS is self-sustainable because it is powered entirely from harvested energy without requiring additional external power sources.

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61 EST-06 A Single- Stage Photovoltaic System for a Dual-Inverter-Fed Open- End Winding Induction Motor Drive for Pumping Applications

IEEE-2015 This paper presents an integrated solution for a photovoltaic (PV)-fed water-pump drive system, which uses an openend winding induction motor (OEWIM). The dual-inverter-fed OEWIM drive achieves the functionality of a three-level inverter and requires low value dc-bus voltage. This helps in an optimal arrangement of PV modules, which could avoid large strings and Helps in improving the PV performance with wide bandwidth of operating voltage. It also reduces the voltage rating of the dc-link capacitors and switching devices used in the system. The proposed control strategy achieves an integration of both maximum power point tracking and V/f control for the efficient utilization of the PV panels and the motor. The proposed control scheme requires the sensing of PV voltage and current only. Thus, the system requires less number of sensors. All the analytical, simulation, and experimental results of this work under different environmental conditions are presented in this paper.

62 EST-07 A Smart Sensor Network for Sea Water Quality Monitoring

IEEE-2015 Measurement of chlorophyll concentration is gaining more-and-more importance in evaluating the status of the marine ecosystem. For wide areas monitoring a reliable architecture of wireless sensors network is required. In this paper, we present a network of smart sensors, based on ISO/IEC/IEEE 21451 suite of standards, for in situ and in continuous space– time monitoring of surface water bodies, in particular for seawater. The system is meant to be an important tool for evaluating water quality and a valid support to strategic decisions concerning critical environment issues. The aim of the proposed system is to capture possible extreme events and collect long-term periods of data.

63 EST-08 A Train Localization Algorithm for Train Protection Systems of the Future

IEEE-2015 This paper describes an algorithm that enables a railway vehicle to determine its position in a track network. The system is based solely on onboard sensors such as a velocity sensor and a Global Navigation Satellite System (GNSS) sensor and does not require trackside infrastructure such as axle counters or balises. The paper derives a probabilistic modeling of the localization task and develops a sensor fusion approach to fuse the inputs of the GNSS sensor and the velocity sensor with the digital track map. We describe how we can treat ambiguities and stochastic uncertainty adequately. Moreover, we introduce the concept of virtual balises that can be used to replace balises on the track and evaluate the approach experimentally. This paper focuses on an accurate modeling of sensor and estimation uncertainties, which is relevant for safety critical applications.

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64 EST-09 Alleviation of Electromagnetic Interference Noise Using a Resonant Shunt for Balanced Converters

IEEE-2015 Balanced converter is an effective way to reduce the CM noise. However, the parasitic capacitance between the switch and heat sink leads to resonant problems, resulting in high noise in certain frequency range. This paper proposes a novel coupled inductor structure based on the balanced technique for the Boost converter to further reduce the CM noise at certain frequency range. A shunt resonant path is adopted to offer a maximum suppression. The analytical estimation for shunt winding’s performance is provided for better design. Some simulation and experimental results of this new technique are presented to validate its effectiveness. The experiments about the capacitance unbalance, different load current, and reduction of the CM inductor size are also discussed for better understanding of this technique.

65 EST-10 An Approach of Reliable Data Transmission With Random Redundancy for Wireless Sensors in Structural Health Monitoring

IEEE-2015 Lossy transmission is a common problem suffered from monitoring systems based on wireless sensors. Though extensive works have been done to enhance the reliability of data communication in computer networks, few of the existing methods are well tailored for the wireless sensors for structural health monitoring (SHM). These methods are generally unsuitable for resource-limited wireless sensor nodes and intensive data SHM applications. In this paper, a new data coding and transmission method is proposed that is specifically targeted at the wireless SHM systems deployed on large civil infrastructures. The proposed method includes two coding stages: 1) a source coding stage to compress the natural redundant information inherent in SHM signals and 2) a redundant coding stage to inject artificial redundancy into wireless transmission to enhance the transmission reliability. Methods with light memory and computational overheads are adopted in the coding process to meet the resource constraints of wireless sensor nodes. In particular, the lossless entropy compression method is implemented for datacompression, and a simple random matrix projection is proposed for redundant transformation. After coding, a wireless sensor node transmits the same payload of coded data instead of the original sensor data to the base station. Some data loss may occur during the transmission of the coded data. However, the complete original data can be reconstructed losslessly on the base station from the incomplete coded data given that the data loss ratio is reasonably low. The proposed method is implemented into the Imote2 smart sensor platform and tested in a series of communication experiments on a cable-stayed bridge.

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66 EST-11 Automated Health Alerts Using In-Home Sensor Data for Embedded Health Assessment

IEEE-2015 We present an example of unobtrusive, continuous monitoring in the home for the purpose of assessing early health changes. Sensors embedded in the environment capture behavior and activity patterns. Changes in patterns are detected as potential signs of changing health. We _rst present results of a preliminary study investigating 22 features extracted from in-home sensor data. A 1-D alert algorithm was then implemented to generate health alerts to clinicians in a senior housing facility. Clinicians analyze each alert and provide a rating on the clinical relevance. These ratings are then used as ground truth for training and testing classi_ers. Here, we present the methodology for four classi_cation approaches that fuse multisensory data. Results are shown using embedded sensor data and health alert ratings collected on 21 seniors over nine months. The best results show similar performance for two techniques, where one approach uses only domain knowledge and the second uses supervised learning for training. Finally, we propose a health change detection model based on these results and clinical expertise. The system of in-home sensors and algorithms for automated health alerts provides a method for detecting health problems very early so that early treatment is possible. This method of passive in-home sensing alleviates compliance issues.

67 EST-12 Compact Personal Distributed Wearable Exposimeter

IEEE-2015 A compact wearable Personal Distributed Exposimeter is proposed, sensing the power density of incident radio-frequency (RF) fields on the body of a human. In contrast to current commercial exposimeters, our Personal Distributed Exposimeter, being composed of multiple compact personal wearable RF exposimeter sensor modules, minimizes uncertainties caused by the proximity of the body, the specific antenna used and the exact position of the exposimeter. For unobtrusive deployment inside a jacket, each individual exposimeter sensor module is specifically implemented on the feedplane of a textile patch antenna. The new wearable sensor module’s high-resolution logarithmic detector logs RF signal levels. Next, on-board flash memory records minimum, maximum and average exposure data over a time span of more than two weeks, at a one-second sample period. Sample-level synchronization of each individual exposimeter sensor module enables combining of measurements collected by different nodes. The system is first calibrated in an anechoic chamber, and then compared to a commercially available single-unit exposimeter.

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68 EST-13 Intra-Vehicle Networks: A Review

IEEE-2015 Automotive electronics is a rapidly expanding area With an increasing number of safety, driver assistance, and infotainment devices becoming standard in new vehicles. Current vehicles generally employ a number of different networking protocols to integrate these systems into the vehicle. The introduction of large numbers of sensors to provide driver assistance applications and the associated high-bandwidth requirements of these sensors have accelerated the demand for faster and more flexible network communication technologies within the vehicle. This paper Presents a comprehensive overview of current research on advanced intra-vehicle networks and identifies outstanding research questions for the future.

69 EST-14 Multirobot Control Using Time-Varying Density Functions

IEEE-2015 An approach is presented for influencing teams of robots by means of time-varying density functions, representing rough references for where the robots should be located. A continuous-time coverage algorithm is proposed and distributed approximations are given whereby the robots only need to access information from adjacent robots. Robotic experiments show that the proposed algorithms work in practice, as well as in theory.

70 EST-15 Optimization-Based Motion Planning in Joint Space for Walking Assistance With Wearable Robot

IEEE-2015 In this paper, we propose an alternative motion planning method for a wearable robot with a variable stride length and walking speed. Trajectories are planned in a joint space rather than a workspace to avoid an ill-posed problem with no solution in inverse kinematics, and to consider the joint’s range of motion, maximum velocity, foot clearance, and backward balance. The joint trajectories are represented by minimum jerk trajectories. Two via-points are assigned, and the parameters (angle and angular velocity) at the via-points are determined by applying an inverted pendulum model or optimization to satisfy the constraints. The fastest gait pattern generated by the proposed algorithm was twice as fast as the pattern generated by the workspace-based planning method. We confirmed that the fastest walking pattern of 0.36 m/s was feasible on a tread mill, and a walking pattern of 0.27 m/s was found for walking across the floor with a walker. Furthermore, the proposed method required approximately 65% of the electric power for the workspace-based method for the same walking speed and stride length. These results suggest that the proposed motion planning method is effective at generating a high-speed and efficient gait pattern for a wearable robot.

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71 EST-16 Path Following Using Dynamic Transverse Feedback Linearization for Car-Like Robots

IEEE-2015 This paper presents an approach for designing path following controllers for the kinematic model of car-like mobile robots using transverse feedback linearization with dynamic extension.This approach is applicable to a large class of paths and its effectiveness is experimentally demonstrated on a Chameleon R100 Ackermann steering robot. Transverse feedback linearization makes the desired path attractive and invariant, while the dynamic extension allows the closed-loop system to achieve the desired motion along the path.

72 EST-17 Recent Advances in Wearable Sensors for Health Monitoring

IEEE-2015 Wearable sensor technology continues to advance and provide significant opportunities for improving personalized Health care. In recent years, advances in flexible electronics, Smart materials and low-power computing and networking have reduced barriers to technology accessibility, integration, and cost, unleashing the potential for ubiquitous monitoring. This paper discusses recent advances in wearable sensors and systems that monitor movement, physiology, and environment, with a focus on applications for Parkinson’s disease, stroke, and head and neck injuries.

73 EST-18 Road Edge Recognition Using the Stripe Hough Transform From Millimeter-Wave Radar Images

IEEE-2015 Millimeter-wave (MMW) radar, which is used for road feature recognition, has performance that is superior to optical cameras in terms of robustness in different weather and lighting conditions, as well as providing ranging capabilities. However, the signatures of road features in MMW radar images are different from that of optical images, and even physically continuous features, such as road edges, will be presented as a set of bright points or spots distributed along the roadside. Therefore, discrimination of the radar features is of paramount importance in automotive imaging systems. To tackle this problem, an approach called the stripe Hough transform (HT) is introduced in this paper, allowing enhanced extraction of the geometry of the road path. The performance of the approach is demonstrated by comparison of extracted features from MMW images with the real geometry of the road and with the results of processing by classical HT.

74 EST-19 Scanning the Issue and Beyond: Transportation and Mobility Transformation for Smart Cities

IEEE-2015 THE OVERALL performance and current status of IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (T-ITS) have been reported and discussed in the first Executive Committee (ExCom) meeting of the IEEE Intelligent Transportation Systems Society (ITSS) this year, held in beautiful Saint Thomas, U.S. Virgin Islands. I am glad to inform you that the state of our journal is like the sunny blue sky, white clouds, and lovely beach of the Virgin Islands: bright and Pleasant. The ExCom has decided to establish a new platform

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for ITSS social media presence; thus, our future abstracts will be distributed through the new social media platform. This issue starts with three survey papers on technology and security for intelligent vehicles. I will go beyond smart cars and share my thinking and view on issues of transportation and mobility transformation for smart living in smart communities and cities.

75 EST-20 Smart Lighting System ISO/IEC/IEEE 21451 Compatible

IEEE-2015 Smart lighting systems go far beyond merely replacing lamps. These modern systems are now able to reproduce arbitrary spectra, color temperatures, and intensities and pivot on smart sensors and actuators incorporating information and communication technologies. This paper presents an interoperable smart lighting solution that combines heterogeneous lighting technologies enabling intelligent functions. The system can shift light intensity to increase visual comfort, and it is oriented toward human centric lighting studies. Moreover, this system follows the guidelines defined by the ISO/IEC/IEEE 21451 standards and ZigBee Light Link and also, it includes an additional transducer signal treatment service for artificial intelligence algorithms. Finally, a representational state transfer application allows us to test the interoperability and visualize energy savings in an office room.

76 EST-21 Wearable Sensors for Human Activity Monitoring: A Review

IEEE-2015 An increase in world population along with a significant aging portion is forcing rapid rises in healthcare costs. The healthcare system is going through a transformation in which continuous monitoring of inhabitants is possible even without hospitalization. The advancement of sensing technologies, embedded systems, wireless communication technologies, nano technologies, and miniaturization makes it possible to develop smart systems to monitor activities of human beings continuously. Wearable sensors detect abnormal and/or unforeseen situations by monitoring physiological parameters along with other symptoms. Therefore, necessary help can be provided in times of dire need. This paper reviews the latest reported systems on activity monitoring of humans based on wearable sensors and issues to be addressed to tackle the challenges.

77 EST-22 Design of a Mobile Charging Service for Electric Vehicles in an Urban Environment

IEEE-2015 This paper presents a novel approach to providing a service for electric-vehicle (EV) battery charge replenishment. This is an alternate system in which the charge replenishment is provided by mobile chargers (MCs). These chargers could have two possible configurations: a mobile plug-in charger (MP) or a mobile battery-swapping station (MS). A queuing-based

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analytical approach is used to determine the appropriate range of design parameters for such a mobile charging system. An analytical analysis is first developed for an idealized system with a nearest-job-next (NJN) service strategy explored for such a system. In a NJN service strategy, the MC services the next spatially closest EV when it is finished with its current request. An urban environment approximated by Singapore is then analyzed through simulation. Charging requests are simulated through a trip generation model based on Singapore. In such a realistic environment, an updated practical NJN service strategy is proposed. For an MP system in an urban environment such as Singapore, there exists an optimal battery capacity with a threshold battery charge rate. Similarly, the battery swap capacity of an MS system does not need to be large for the system to perform.

78 EST-23 Comparison of Charge Estimation Methods in Partial Discharge Cable Measurements

IEEE-2015 The aim of this paper is to compare different partial discharge (PD) charge estimation methods for PD cable measurements. The paper covers the mathematical foundation behind the different presented methods, and explores the limits of each method regarding the associated maximum charge estimation errors in PD cable measurements. The results are focused on long cables where large PD pulse distortions are present and therefore, the measured pulses differ significantly from the calibrator ones. Each proposed method is analyzed, and finally, limitations of each method are discussed.

79 EST-24 Hierarchical and Networked Vehicle Surveillance in ITS: A Survey

IEEE-2015 Traffic surveillance has become an important topic in intelligent transportation systems (ITSs), which is aimed at monitoring and managing traffic flow. With the progress in computer vision, video-based surveillance systems have made great advances on traffic surveillance in ITSs. However, the performance of most existing surveillance systems is susceptible to challenging complex traffic scenes (e.g., object occlusion, pose variation, and cluttered background). Moreover, existing related research is mainly on a single video sensor node, which is incapable of addressing the surveillance of traffic road networks. Accordingly, we present a review of the literature on the video-based vehicle surveillance systems in ITSs.We analyze the existing challenges in video-based surveillance systems for the vehicle and present a general architecture for video surveillance systems, i.e., the hierarchical and networked vehicle surveillance, to survey the different existing and potential techniques.

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M-MATLAB IP-Image Processing CM-Communication VP-Video Processing AP-Audio Processing MATLAB IMAGE PROCESSING

S.NO CODE TITLE YEAR ABSTRACT

80 MIPST-01 Bayesian Fusion of Multi-Band Images

IEEE-2015 This paper presents a Bayesian fusion technique for remotely sensed multi-band images is presented. The observed images are related to the high spectral and high spatial resolution image to be recovered through physical degradations, e.g., spatial and spectral blurring and/or subsampling defined by the sensor characteristics. The fusion problem is formulated within a Bayesian estimation framework. An appropriate prior distribution exploiting geometrical consideration is introduced. To compute the Bayesian estimator of the scene of interest from its posterior distribution, a Markov chain Monte Carlo algorithm is designed to generate samples asymptotically distributed according to the target distribution. To efficiently sample from this high-dimension distribution, a Hamiltonian Monte Carlo step is introduced in the Gibbs sampling strategy. The efficiency of the proposed fusion method is evaluated with respect to several state-of-the-art fusion techniques.

81 MIPST-02 Registration of Images With N-Fold Dihedral Blur

IEEE-2015 In this paper, we extend our recent registration method designed specifically for registering blurred images. The original method works for unknown blurs, assuming the blurring point-spread function (PSF) exhibits an N-fold rotational symmetry. Here, we also generalize the theory to the case of dihedrally symmetric blurs, which are produced by the PSFs having both rotational and axial symmetries .Such kind of blurs are often found in unfocused images acquired by digital cameras, as in out of focus shots the PSF typically mimics the shape of the shutter aperture. This makes our registration algorithm particularly well-suited in applications where blurred image registration must be used as a preprocess step of an image fusion algorithm, and where common registration methods fail, due to the amount of blur. We demonstrate that the proposed method leads to an improvement of the registration performance, and we show it to real images by providing successful examples of blurred image registration followed by depth-of-field extension and multichannel blind deconvolution.

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82 MIPST-03 A Novel SURE-Based Criterion for Parametric PSF Estimation

IEEE-2015 We propose an unbiased estimate of a filtered version of the mean squared error—the blur-SURE (Stein’s unbiased risk estimate)—as a novel criterion for estimating an unknown point spread function (PSF) from the degraded image only. The PSF is obtained by minimizing this new objective functional over a family of Wiener processing. Based on this estimated blur kernel, we then perform nonblind deconvolution using our recently developed algorithm. The SURE-based framework is exemplified with a number of parametric PSF, involving a scaling factor that controls the blur size. A typical example of such parametrization is the Gaussian kernel. The experimental results demonstrate that minimizing the blur-SURE yields highly accurate estimates of the PSF parameters, which also result in a restoration quality that is very similar to the one obtained with the exact PSF, when plugged into our recent multi-Wiener SURE-LET deconvolution algorithm. The highly competitive results obtained outline the great potential of developing more powerful blind deconvolution algorithms based on SURE-like estimates.

83 MIPST-04 Histogram-Based Locality-Preserving Contrast Enhancement

IEEE-2015 Histogram equalization (HE), a simple contrast enhancement (CE) method, tends to show excessive enhancement and gives unnatural artifacts on images with high peaks in their histograms. Histogram-based CE methods have been proposed in order to overcome the drawback of HE, however, they do not always give good enhancement results. In this letter, a histogram-based locality-preserving CE method is proposed. The proposed method is formulated as an optimization problem to preserve localities of the histogram for performing image CE. The locality-preserving property makes the histogram shape of the enhanced image to be similar to that of the original image. Experimental results show that the proposed histogram-based method gives output images with graceful CE on which existing methods give unnatural results.

84 MIPST-05 An Efficient MRF Embedded Level Set Method for Image Segmentation

IEEE-2015 This paper presents a fast and robust level set method for image segmentation. To enhance the robustness against noise, we embed a Markov random field (MRF) energy function to the conventional level set energy function. This MRF energy function builds the correlation of a pixel with its neighbors and encourages them to fall into the same region. To obtain a fast implementation of

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the MRF embedded level set model, we explore algebraic multigrid (AMG) and sparse field method (SFM) to increase the time step and decrease the computation domain ,respectively. Both AMG and SFM can be conducted in a parallel fashion, which facilitates the processing of our method for big image databases. By comparing the proposed fast and robust level set method with the standard level set method and its popular variants on noisy synthetic images, synthetic aperture radar (SAR) images, medical images, and natural images, we comprehensively demonstrate the new method is robust against various kinds of noises. In particular, the new level set method can segment an image of size 500 × 500 within 3 s on MATLAB R2010b installed in a computer with 3.30-GHz CPU and 4-GB memory.

85 MIPST-06 Robust Clutter Suppression and Moving Target Imaging Approach for Multichannel in Azimuth High-Resolution and Wide-Swath Synthetic Aperture Radar

IEEE-2015 This paper describes a clutter suppression approach and the corresponding moving target imaging algorithm for a multichannel in azimuth high-resolution and wide-swath (MC-HRWS) synthetic aperture radar (SAR) system. Incorporated with digital beaforming processing, MC-HRWS SAR systems are able to suppress the Doppler ambiguities to allow for HRWS SAR imaging and null the clutter directions to suppress clutter for ground moving target indication. In this paper, the degrees of freedom in azimuth for the multichannel SAR systems are employed to implement clutter suppression. First, the clutter and moving target echoes are transformed into the range compression and azimuth chirp Fourier transform frequency domain, i.e., coarse-focused images formation, when the clutter echoes are with azimuth Doppler ambiguity. Considering that moving targets are sparse in the imaging scene and that there is a difference between clutter and a moving target in the spatial domain, a series of spatial domain filters are constructed to extract moving target echoes. Then, using an extracted moving target echo, two groups of signals are formed, and slant-range velocity of a moving target can be estimated based on baseband Doppler centroid estimation algorithm and multilook cross-correlation Doppler centroid ambiguity number resolving approach. After the linear range cellmigration correction and azimuth focus processing, a well-focused moving target image can be obtained.

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86 MIPST-07 Optimizing Template for Lookup-Table Inverse Halftoning using Elitist Genetic Algorithm

IEEE-2015 A template optimization method based on elitist genetic algorithm was proposed for lookup-table inverse halftoning. A mathematical model with constraint conditions was built to describe the template optimization problem.We solved this optimization problem by using elitist genetic algorithm and designed the details about encoding and decoding scheme, selection and reproduce, crossover, mutation, elitist strategy and fitness function according to the proposed optimization model. In experiments, we demonstrated the performance on Floyd-Steinberg error diffusion, Jarvis-Judice error diffusion, cluster dither, Bayer disperse dither and dot diffusion halftone images. According to our experiment study, our method approaches to the optimal result closer than the greedy algorithm and simulated annealing do. We suggested on cluster dither images but on other four kinds of halftone images.

87 MIPST-08 An Improved PFA With Aperture Accommodation for Widefield Spotlight SAR Imaging

IEEE-2015 This letter presents an improved polar format algorithm for nonlinear aperture and wide field spotlight synthetic aperture radar imaging. In the proposed algorithm, the chirp z transform is used for uniform range resampling, while the fast Gaussian grid nonuniform fast Fourier transform is employed to focus the nonuniform samples in azimuth. Additionally, the space variant post filtering is incorporated for eliminating the geometric distortion and marginal defocusing effects induced by wave front curvature. The effectiveness of the proposed algorithm is validated by simulation and real large scene Gotcha data set.

88 MIPST-09 A New Framework for SAR Multitemporal Data RGB Representation: Rationale and Products

IEEE-2015 This paper presents the multitemporal adaptive processing (MAP3) framework for the treatment of multitemporal synthetic aperture radar (SAR) images. The framework is organized in three major activities dealing with calibration, adaptability,and representation. The processing chain has been designed looking at the simplicity, i.e., the minimization of the operations needed to obtain the products, and at the algorithms’ availability in the literature. Innovation has been provided in the cross calibration step, which is solved introducing the variable amplitude levels equalization (VALE) method, through which it is possible to establish a common metrics for the measurement of the amplitude levels exhibited by the images of the series.

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89 MIPST-10 Indicator Cokriging-Based Subpixel Mapping Without Prior Spatial Structure Information

IEEE-2015 Indicator cokriging (ICK) has been shown to be an effective subpixel mapping (SPM) algorithm. It is noniterative and involves few parameters. The original ICK-based SPM method,however, requires the semivariogram of land cover classes from prior information, usually in the form of fine spatial resolution training images. In reality, training images are not always available, or laborious work is needed to acquire them. This paper aims to seek spatial structure information for ICK when such prior land cover information is not obtainable. Specifically, the fine spatial resolution semivariogram of each class is estimated by the deconvolution process, taking the coarse spatial resolution semivariogram extracted fromthe class proportion image as input. The obtained fine spatial resolution semivariogram is then used to estimate class occurrence probability at each subpixel with the ICK method. Experiments demonstrated the feasibility of the proposed ICK with the deconvolution approach. It obtains comparable SPM accuracy to ICK that requires semivariogram estimated from fine spatial resolution training images. The proposed method extends ICK to cases where the prior spatial structure information is unavailable.

90 MIPST-11 Reversible Image Data Hiding with Contrast Enhancement

IEEE-2015 In this letter, a novel reversible data hiding (RDH) algorithm is proposed for digital images. Instead of trying to keep the PSNR value high, the proposed algorithm enhances the contrast of a host image to improve its visual quality. The highest two bins in the histogram are selected for data embedding so that histogram equalization can be performed by repeating the process. The side information is embedded along with the message bits into the host image so that the original image is completely recoverable. The proposed algorithm was implemented on two sets of images to demonstrate its efficiency. To our best knowledge, it is the first algorithm that achieves image contrast enhancement by RDH. Furthermore, the evaluation results show that the visual quality can be preserved after a considerable amount of message bits have been embedded into the contrast-enhanced images, even better than three specific MATLAB functions used for image contrast enhancement.

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91 MIPST-12 Features, Color Spaces, and Boosting: New Insights on Semantic Classification of Remote Sensing Images

IEEE-2015 A major yet largely unsolved problem in the semantic classification of very high resolution remote sensing images is the design and selection of appropriate features. At a ground sampling distance below half a meter, fine-grained texture details of objects emerge and lead to a large intra class variability while generally keeping the between-class variability at a low level. Usually, the user makes an educated guess on what features seem to appropriately capture characteristic object class patterns. Here, we propose to avoid manual feature selection and let a boosting classifier choose optimal features from a vast Randomized Quasi- Exhaustive (RQE) set of feature candidates directly during training. This RQE feature set consists of a multitude of very simple features that are computed efficiently via integral images inside a sliding window. This simple but comprehensive feature candidate set enables the boosting classifier to assemble the most discriminative textures at different scale levels to classify a small number of broad urban land-cover classes.

92 MIPST-13 Continuous One-Way Detection of Available Bandwidth Changes for Video Streaming Over Best-Effort Networks

IEEE-2015 Video streaming over best-effort networks, such as the Internet, is now a significant application used by most Internet users. However, best-effort networks are characterized by dynamic and unpredictable changes in the available bandwidth, which adversely affect the quality of video. As such, it is important to have real-time detection mechanisms of bandwidth changes to ensure that video is adapted to the available bandwidth and transmitted at the highest quality. In this paper, we propose a Bayesian instantaneous end-to-end bandwidth change prediction model and method to detect and predict one-way bandwidth changes at the receiver. Unlike existing congestion detection mechanisms, which use network parameters such as packet loss probability, round trip time (RTT), or jitter, our approach uses weighted inter arrival time of video packets at the receiver side. Furthermore, our approach is continuous, since it measures available bandwidth changes with each incoming video packet, and therefore detects congestion occurrence in <200 ms, on average, which is significantly faster than existing approaches. In addition, it is a one-way scheme, since it only takes into account the characteristics of the incoming path.

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93 MIPST-14 Compressed-Domain Ship Detection on Space borne Optical Image Using Deep Neural Network and Extreme Learning Machine

IEEE-2015 Ship detection on space borne images has attracted great interest in the applications of maritime security and traffic control. Optical images stand out from other remote sensing images in object detection due to their higher resolution and more visualized contents. However, most of the popular techniques for ship detection from optical space borne images have two shortcomings:1) Compared with infrared and synthetic aperture radar images, their results are affected by weather conditions, like clouds and ocean waves, and 2) the higher resolution results in larger data volume, which makes processing more difficult. Most of the previous works mainly focus on solving the first problem by improving segmentation or classification with complicated algorithms. These methods face difficulty in efficiently balancing performance and complexity. In this paper, we propose a ship detection approach to solving the a for mentioned two issues using wavelet coefficients extracted from JPEG2000 compressed domain combined with deep neural network (DNN) and extreme learning machine (ELM). Compressed domain is adopted for fast ship candidate extraction, DNN is exploited for high-level feature representation and classification, and ELM is used for efficient feature pooling and decision making.

94 MIPST-15 An Intelligent Monitoring System for Natural Gas Odorization

IEEE-2015 In this paper, we present the design of an intelligent monitoring system consisting of physical sensors and intelligent software for the automatic identification of the concentration of natural gas odorants in the environment. An optical-based sensor array was proposed comprising the hardware module. The software module employs wavelets filters and artificial neural networks to recognize the concentration of odorant in a natural gas sample. The objective is to help the natural gas odorization process by means of end point monitoring through the recognizing of the odorant concentration. The recognizing process uses a benchmark index, which measures the degrees of human perception of gas in the environment. In this way, the proposed system tries to mimic the human perception of a natural gas leak and helps one to indicate if more or less amount of odorant should be added into the gas pipeline.

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95 MIPST-16 Feature Matching With an Adaptive Optical Sensor in a Ground Target Tracking System

IEEE-2015 We consider methods to address the optical feature aided remote sensing tracking problem for vehicles in a challenging environment. Our approach is to apply the dynamic data driven application systems computing paradigm to implement control of an adaptive sensor. This adaptive sensor acquires a panchromatic image while simultaneously allowing the collection of visible-near infrared spectral data at specified pixels. This sensor holds the promise of delivering the increased accuracy of targeted spectral sensing without the enormous data volume of full spectral images. The target of interest is optimally imaged by the sensor based on the target’s forecasted location and motion relative to the extracted content of the background. Background context is both extracted from the image and created from the Open Street Map road network. We describe the implementation of the tracking framework and testing of some of the components using simulated imagery created with the digital imaging and remote sensing image generation model.

96 MIPST-17 Capabilities of BIOMASS Tomography for Investigating Tropical Forests

IEEE-2015 The objective of this paper is to provide a better understanding of the capabilities of the BIOMASS tomography concerning the retrieval of forest biomass and height in tropical areas. The analysis presented in this paper is carried out on airborne data acquired by Office National d’Etudes et de Recherches Aérospatiales (ONERA) over the site of Paracou, French Guiana, during the European Space Agency campaign TropiSAR. This high-resolution data set (125-MHz bandwidth) was reprocessed in order to generate a new data stack consistent with BIOMASS as for the bandwidth (6 MHz) and the azimuth resolution (about 12 m). To do this, two different processing approaches have been considered. One approach consisted of degrading the resolution of the airborne data through the linear filtering of raw data, followed by standard SAR processing. The other approach consisted of recovering the 3-D distribution of the scatterers at a high resolution, which was then reprojected onto the BIOMASS geometry. The latter procedure allows us to obtain a data stack that is the most realistic emulation of BIOMASS imaging capabilities. In both approaches, neither ionospheric disturbances nor temporal decorrelation has been considered.

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97 MIPST-18 Soil Moisture Estimation Under Tropical Forests Using UHF Radar Polarimetry

IEEE-2015 In this paper, we report on the performance of a semiempirical algorithm for the retrieval of soil moisture (SM) under dense tropical forests using ultrahigh frequency (UHF) polarimetric synthetic aperture radar (SAR) data. The algorithm is a simplification of a 3-D coherent model of forest canopy based on the distorted Born approximation (DBA). The simplified model reduces the number of parameters and preserves the three dominant scattering mechanisms of volume, volume–surface, and surface for three polarized backscattering coefficients, i.e., σHH, σHV, and σVV, at UHF frequencies. The inversion process uses the Levenberg–Marquardt nonlinear least squares method to estimate the three model parameters: vegetation aboveground biomass, integrated SM up to a certain depth, and surface roughness. The performance of the inversion process is examined by first using simulation data where the initial values of the inversion process vary randomly and then using airborne UHF SAR data acquired in Costa Rica over La Selva Biological Station. The results with simulated data show that the inversion process is not significantly sensitive to initial values considering they are in the range of ±50% of the true value.

98 MIPST-19 A Novel Range Grating Lobe Suppression Method Based on the Stepped-Frequency SAR Image

IEEE-2015 The magnitude error and phase error (MEPE) in the transfer function of a stepped-frequency synthetic aperture radar (SAR) system results in a periodic MEPE in the synthesized wideband waveform, which induces the grating lobes in the high-resolution range profile. In this letter, a novel grating lobe suppression method based on the SAR image is proposed. In the paired-echo theory, a single sinusoidal term of the periodic MEPE in the frequency domain induces a pair of grating lobes in the time domain. Based on the magnitudes and phases of a strong scatterer and its grating lobes in the SAR image, the sinusoidal terms in the periodic MEPE can be estimated using the proposed method. By compensating for the estimated sinusoidal terms in the spectrum reconstruction, the corresponding grating lobes can be suppressed to the background level of the SAR image. The validity of the proposed method has been demonstrated using computer simulations and experiments based on real data.

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99 MIPST-20 Multi-Task Bayesian Compressive Sensing Exploiting Intra-Task Dependency

IEEE-2015 In this letter, we propose a multi-task compressive sensing algorithm for the reconstruction of clustered sparse entries based on hierarchical Bayesian framework. By extending a paired spike-and-slab prior to a general multi-task model, the proposed algorithm has the capability of modeling both inter-task and intra-task dependencies of the observation data. The latter is achieved by imposing a clustered prior on non-zero entries and finds applications in radar where targets exhibit spatial extent. Simulation results verify that the proposed algorithm outperforms state-of-the-art group sparse Bayesian learning algorithms.

100 MIPST-21 Recognition of Genuine Smiles

IEEE-2015 Automatic distinction between genuine (spontaneous) and posed expressions is important for visual analysis of social signals. In this paper, we describe an informative set of features for the analysis of face dynamics, and propose a completely automatic system to distinguish between genuine and posed enjoyment smiles. Our system incorporates facial land marking and tracking, through which features are extracted to describe the dynamics of eyelid, cheek, and lip corner movements. By fusing features over different regions, as well as over different temporal phases of a smile, we obtain a very accurate smile classifier. We systematically investigate age and gender effects, and establish that age-specific classification significantly improves the results, even when the age is automatically estimated. We evaluate our system on the 400-subject UvA-NEMO database we have recently collected, as well as on three other smile databases from the literature.

101 MIPST-22 DietCam: Multi-View Food Recognition Using a Multi-Kernel SVM

IEEE-2015 Food recognition is a key component in evaluation of everyday food intakes, and its challenge is due to intraclass variation. In this paper, we present an automatic food classification method, DietCam, which specifically addresses the variation of food appearances. DietCam consists two major components, ingredient detection and food classification. Food ingredients are detected through a combination of a deformable part-based model and a texture verification model. From the detected ingredients,food categories are classified using a multi-view multikernel SVM. In the experiment, DietCam presents reliability and outperformance in recognition of food with complex ingredients on a database of 55 food types with 15262 food images.

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102 MIPST-23 Contributions to Automatic Target Recognition Systems for Underwater Mine Classification

IEEE-2015 This paper deals with several original contributions to an automatic target recognition (ATR) system, which is applied to underwater mine classification. The contributions concentrate on feature selection and object classification. First, a sophisticated filter method is designed for the feature selection. This filter method utilizes a novel feature relevance measure, the composite relevance measure (CRM). Feature relevance measures in the literature (e.g., mutual information and relief weight) evaluate the features only with respect to certain aspects. The CRM is a combination of several measures so that it is able to provide a more comprehensive assessment of the features. Both linear and nonlinear combinations of these measures are taken into account.

103 MIPST-24 Robust and high capacity watermarking for image based on DWT-SVD

IEEE-2015 In this paper, we propose a blind digital image water marking technique by combining Discrete Wavelet Transform (DWT) with Singular Value Decomposition (SVD) to improve the robustness and the capacity. In detail, Singular Values (SVs) of watermarks are replaced with the suitable SVs of HH sub-bands of the original images. Additionally, our method generates keys that ensures the security for the watermarks in the embedding and the extraction process. Experiments on images for digital watermarking attacked by Stirmark Benchmark 4.0 tool show that our method is more robust, imperceptible and higher capacity than others’.

104 MIPST-25 Hybrid Compression of Hyperspectral Images Based on PCA With Pre-Encoding Discriminant Information

IEEE-2015 t has been shown that image compression based on principal component analysis (PCA) provides good compression efficiency for hyperspectral images. However, PCA might fail to capture all the discriminant information of hyperspectral images, since features that are important for classification tasks may not be high in signal energy. To deal with this problem, we propose a hybrid compression method for hyperspectral images with pre-encoding discriminant information. A feature extraction method is first applied to the original images, producing a set of feature vectors that are used to generate feature images and then residual images by subtracting the feature-reconstructed images from the original ones. Both feature images and residual images are compressed and transmitted.

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105 MIPST-26 Secure Reversible Image Data Hiding over Encrypted Domain via Key Modulation

IEEE-2015 This work proposes a novel reversible image data hiding (RIDH) scheme over encrypted domain. The data embedding is achieved through a public key modulation mechanism, in which access to the secret encryption key is not needed. At the decoder side, a powerful two-class SVM classifier is designed to distinguish encrypted and non-encrypted image patches, allowing us to jointly decode the embedded message and the original image signal. Compared with the state-of-the-arts, the proposed approach provides higher embedding capacity, and is able to perfectly reconstruct the original image as well as the embedded message. Extensive experimental results are provided to validate the superior performance of our scheme.

106 MIPST-27 Context-Based Predictor Blending for Lossless Colour Image Compression

IEEE-2015 Images are typically non-stationary signals. If prediction is applied in a linear fashion, it must be combined with a technique that takes this characteristic into account. In general, images can be either regarded as piecewise two-dimensional autoregressive processes or they are handled in a block-wise manner. This paper presents a novel prediction technique, which treats the image data as an interleaved sequence generated by multiple sources. The challenge is to de-interleave the sequence and to compute prediction weights for each sub-source separately. The proposed approach adaptively determines the sub-sources based on the textures surrounding the pixels. The new linear prediction technique is combined with template-matching prediction and a blending method is proposed which considers the correlation between the predictors’ estimates.

107 MIPST-28 Reversable data hiding in encrypted image with distributed source ecncoding

IEEE-2015 This paper proposes a novel scheme of reversible data hiding (RDH) in encrypted images using distributed source coding (DSC). After the original image is encrypted by the content owner using a stream cipher, the data-hider compresses a series of selected bits taken from the encrypted image to make room for the secret data. The selected bit series is Slepian-Wolf encoded using low density parity check (LDPC) codes. On the receiver side, the secret bits can be extracted if the image receiver has the embedding key only. In case the receiver has the encryption key only, he/she can recover the original image approximately with high quality using an image estimation algorithm.

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108 MIPST-29 Nighttime Visibility Analysis and Estimation Method in the Presence of Dense Fog

IEEE-2015 Compared with daytime, a larger proportion of road accidents happens during nighttime. The altered visibility for drivers partially explains this situation. It becomes worse when dense fog is present. In this paper, we first define a standard night visibility index, which allows specifying the type of fog that an advanced driver assistance system should recognize. A methodology to detect the presence of night fog and characterize its density in images grabbed by an in-vehicle camera is then proposed. The detection method relies on the visual effects of night fog. A first approach evaluates the presence of fog around a vehicle due to the detection of the backscattered veil created by the headlamps. In this aim, a correlation index is computed between the current image and a reference image where the fog density is known. It works when the vehicle is alone on a highway without external light sources.

MATLAB-DIGITAL COMMUNICATION

109 MCMST-1 ICI Self-Cancellation with Cosine Windowing in OFDM transmitters Over Fast Time-Varying Channels

IEEE-2015 We propose the application of cosine windowing for the orthogonal frequency-division multiplexing (OFDM) systems to self-cancel inter carrier interference (ICI) in fast time-varying channels prior to receptions. With a time-domain cosine window immediately after the inverse discrete Fourier transform (IDFT) unit in OFDM transmitters, the ICI fractions from adjacent subcarriers significantly cancel one another at the expense of the orthogonally violation among subcarriers in the main lobe. As a result, the frequency-domain channel matrix reshaped by the cosine windowing can be closely approximated to a strictly banded matrix. In the complex exponential basis expansion model (CE-BEM), we present the estimation of the channel matrix with the assistance of the pilot clusters.

110 MCMST-2 Convergence Constrained Multiuser Transmitter-Receiver Optimization in Single-Carrier FDMA

IEEE-2015 Convergence constrained power allocation (CCPA)in single-carrier multiuser (MU) single-input multiple-output (SIMO) systems with turbo equalization is considered in this paper. In order to exploit the full benefit of the iterative receiver, its convergence properties need to be taken into account also at the transmitter side. The proposed scheme can guarantee that the desired quality of service (QoS) is achieved after a sufficient number of iterations. We propose two

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different successive convex approximations for solving the non-convex power minimization problem subject to user specific QoS constraints. The results of an extrinsic information transfer (EXIT) chart analysis demonstrate that the proposed CCPA scheme can achieve the design objective. Numerical results show that the proposed schemes can achieve superior performance in terms of power consumption as compared to linear receivers with and without precoding, as well as to the iterative receiver without precoding.

111 MCMST-3 Beam forming for Multiuser MIMO-OFDM Interference Channels With Multipath Diversity

IEEE-2015 This paper presents three beam forming designs for multiuser multiple-input and multiple-output with orthogonal frequency-division multiplexing, where the transmit and receive beam formers are obtained iteratively with closed-form steps. In the first case, the transmit (Tx) beam formers are set and the receive (Rx) beam formers are calculated. It works by projecting the Tx beam formers into a null space of appropriate channels .This eliminates one interference term for each user. Then the Rx beam former for each user maximizes its instantaneous signal to noise ratio (SNR) while satisfying an orthogonality condition to eliminate the remaining interferences. The second case is jointly optimizing the Tx and Rx beam formers from constrained SNR maximization. It uses the results from the first case. The third case is also for joint optimization of Tx–Rx beam formers but combines constrained SNR and signal-to-interference-plus-noise ratio maximization. The minimum number of antennas required is derived as part of the formulation.

112 MCMST-4 Quantum Spread Spectrum Multiple Access

IEEE-2015 We describe a quantum multiple access scheme that can take separate single photon channels and combine them in the same path. We propose an add-drop multiplexer that can insert or extract a single photon into an optical fiber carrying the Sub its of all the other users. The system follows the principle of code division multiple access, a spread spectrum technique widely used in cellular networks.

113 MCMST-5 New RLL Decoding Algorithm for Multiple Candidates in Visible Light Communication

IEEE-2015 In this letter, we propose a new decoding algorithm based on a soft run-length limited (RLL) decoding in visible light communication (VLC) with on-off keying modulation and Reed–Solomon codes. Conventional RLL codes are used for dimming adjustments in VLC; however, in our receiver model, the proposed RLL

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decoder produces one or multiple candidates with greater probabilities to enhance the throughput in the VLC system. We also propose a selection method based on a cyclic redundancy check among multiple candidates. A significant advantage of our proposed method is that it leads to performance enhancement without any change in the transmitter in VLC systems.

114 MCMST-6 Multi-Tap Equalization for Performance Improvement in Optical Fast OFDM Systems

IEEE-2015 We show that multi-tap equalization can significantly enhance the tolerance to laser frequency instability and phase noise in optical fast orthogonal frequency division multiplexing (OFDM) systems. We demonstrate the transmission of a 38-Gb/s 16 quadrature amplitude modulation coherent optical fast OFDM signal over 1000-km single-mode fiber using different types of lasers. It is shown that with this technique, the receiver sensitivity can be greatly improved and overhead for carrier frequency offset estimation to track the wavelength can be reduced for commercial lasers. This verifies the benefits of the technique in a continuous-mode optical communication system. We also show that the performance of multi-tap equalization in optical fast OFDM can be better than that in conventional OFDM, and an experiment using lasers with frequency modulation to emulate frequency oscillating effect during wavelength transition shows that optical fast OFDM .

115 MCMST-7 A Multistage CPE Scheme Based on Crossed Constellation Transformation for M-QAM

IEEE-2015 A multistage carrier phase estimation (CPE) scheme for any m-ary quadrature amplitude modulation (QAM) formats is proposed and analyzed in coherent optical communication systems. The scheme is based on the crossed constellation transformation algorithm that is transparent to all modulation formats whose constellations are on the square grid. Simulation results show that the hardware complexity of the proposed CPE scheme can be significantly reduced by the group factors of 6.1/8.6, 4.7/6, and 2.6/3.3 (in the form of multipliers/adders) for 32-QAM, 64-QAM, and 128-QAM compared with the single stage blind phase search algorithm. In 32-QAM, 64-QAM, and 128-QAM, coherent optical communication systems with 1-dB SNR penalty at bit error rate is 1 × 10−2, the comparable line width symbol duration can be reached with the values of 6 × 10−5, 4 × 10−5, and 8 × 10−6, respectively.

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116 MCMST-8 Efficient Chromatic Dispersion Precompensation for Coherent Optical OFDM

IEEE-2015 To reduce the guard interval, short-cyclic-prefix coherent optical orthogonal frequency division multiplexing (CO-OFDM) divides a band into two sub bands and precompensates for chromatic dispersion (CD) with timing offset. Implementation using full band inverse discrete Fourier transformations (IDFTs), however, can excessively increase hardware complexity. We propose an efficient hardware implementation of IDFT with timing offsets for short-cyclic-prefix CO-OFDM. In addition, the residual inter sub band CD induced by quantized timing offset is compensated using subcarrier-based phase rotation. By increasing the number of sub bands efficiently and compensating for the residual inter sub band CD, the transmission performance can be improved. Simulation results show 112-Gb/s single-channel transmission over a 2250-km standard single mode- fiber with polarization division multiplexing 16 quadrature amplitude modulation (PDM-16 QAM) using 128 DFT with a 16 guard interval.

117 MCMST-9 Gaussian Conditional Random Fields for Aggregation of Operational Aerosol Retrievals

IEEE-2015 We present a Gaussian conditional random field model for the aggregation of aerosol optical depth (AOD) retrievals from multiple satellite instruments into a joint retrieval. The model provides aggregated retrievals with higher accuracy and coverage than any of the individual instruments while also providing an estimation of retrieval uncertainty. The proposed model finds an optimal temporally smoothed combination of individual retrievals that minimizes the root-mean-squared error of AOD retrieval. We evaluated the model on five years (2006–2010) of satellite data over North America from five instruments (Aqua and Terra MODIS, MISR, SeaWiFS, and the Ozone Monitoring Instrument), collocated with ground-based Aerosol Robotic Network ground-truth AOD readings, clearly showing that the aggregation of different sources leads to improvements in the accuracy and coverage of AOD retrievals.

118 MCMST 10 Joint Power Splitting and Antenna Selection in Energy Harvesting Relay Channels

IEEE-2015 The simultaneous wireless transfer of information and power with the help of a relay equipped with multiple antennas is considered in this letter, where a “harvest-and-forward” strategy is proposed. In particular, the relay harvests energy and obtains information from the source with the radio-frequent signals by jointly using the antenna selection (AS) and power splitting (PS) techniques, and then the processed information is

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amplified and forwarded to the destination relying on the harvested energy. This letter jointly optimizes AS and PS to maximize the achievable rate for the proposed strategy. Considering that the joint optimization is according to the non-convex problem, a two-stage procedure is proposed to determine the optimal ratio of received signal power split for energy harvesting, and the optimized antenna set engaged in information forwarding. Simulation results confirm the accuracy of the two-stage procedure, and demonstrate that the proposed “harvest-and-forward” strategy outperforms the conventional amplify-and-forward (AF) relaying and the direct transmission.

119 MCMST 11 Compressive Sensing and Reception for MIMO-OFDM Based Cognitive Radio

IEEE-2015 This paper explores a novel receiver architecture for multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) based cognitive radio (CR) that utilizes compressive sensing (CS) technique. Assuming that a limited number of subcarriers are used simultaneously in one MIMO-OFDM channel, we show that the conventional MIMO receiver can be replaced with the proposed receiver to compressively sample signals. In the proposed reception architecture, signals from multiple antennas are mixed and sampled with less hardware by exploiting the sparsity in the OFDM channel usage. Applying the CS technology to the receiver directly reduces the power consumption in mixed signal circuit which is attributable to less number of analog-to-digital converters (ADCs). A new streamlined algorithm for digital signal processing (DSP) to recover the compressively sensed data is also devised. Besides the simplification of the signal sensing, the simulation results also show that the reception fidelity of the proposed architecture outperforms that of the conventional maximum likelihood (ML) MIMO detector when the channel is lightly loaded.

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120 MCMST 12 Spatio-Temporal Flame Modeling and Dynamic Texture Analysis for Automatic Video-Based Fire Detection

IEEE-2015 Every year, a large number of wildfires all over the world burn forested lands, causing adverse ecological, economic, and social impacts. Beyond taking precautionary measures, early warning and immediate response are the only ways to avoid great losses. To this end, in this paper we propose a computer vision approach for fire-flame detection to be used by an early warning fire monitoring system. Initially, candidate fire regions in a frame are defined using background subtraction and color analysis based on a nonparametric model. Subsequently, the fire behavior is modeled by employing various spatio-temporal features, such as color probability, flickering, spatial, and spatiotemporal energy, while dynamic texture analysis is applied in each candidate region using linear dynamical systems and a bag of systems approach. To increase the robustness of the algorithm, the spatio-temporal consistency energy of each candidate fire region is estimated by exploiting prior knowledge about the possible existence of fire in neighboring blocks from the current and previous video frames. As a final step, a two-class support vector machine classifier is used to classify the candidate regions. Experimental results have shown that the proposed method outperforms existing state-of-the-art algorithms.

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MCMST 13 Spectrum Allocation in Cognitive Radio Networks using Multi-Objective Differential Evolution Algorithm

IEEE-2015 In the existing literature the forced termination probability is analyzed after the completion of spectrum allocation (SA) process. Since the forced termination probability depends on the allocation results, it is necessary to take the termination probability into account during the allocation process. In this paper, a two dimensional Markov model is used for analyzing the spectrum access. The Markov process assumes the mean arrival time of primary and secondary users and calculates the forced termination probability. In the current work, the forced termination probability is considered as one objective function along with three network utility functions namely Max- Sum-Reward, Max-Min-Reward and Max-Proportional-Fair to improve the quality of service. Finally the spectrum allocation process is formulated as a multi-objective optimization problem consisting of the above mentioned four objective functions and solved by using multi-objective differential

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evolution (MODE) algorithm. The performance of MODE algorithm is compared with non dominated sorting genetic algorithm II (NSGA-II) for solving the SA problem. The simulation results show that MODE performs better compared to NSGA-II algorithm in terms of timing complexity and pare to optimal solutions.

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MCMST 14 Time–Frequency Joint Sparse Channel Estimation for MIMO-OFDM Systems

IEEE-2015 This letter proposes a time-frequency joint sparse channel estimation for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems under the framework of structured compressive sensing (CS). The proposed scheme first relies on a pseudorandom preamble, which is identical for all transmit antennas, to acquire the partial common support by utilizing the sparse common support property of the MIMO channels. Then, a very small amount of frequency-domain orthogonal pilots are used for the accurate channel recovery. Simulation results show that the proposed scheme demonstrates better performance and higher spectral efficiency than the conventional MIMO-OFDM schemes. Moreover, the obtained partial common support can be further utilized to reduce the complexity of the CS algorithm and improve the signal recovery probability under low signal-to-noise-ratio conditions.

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MCMST 15 Performance of OFDM Systems With Best-m Feedback, Scheduling, and Delays for Uniformly Correlated Subchannels

IEEE-2015 Contemporary cellular standards, such as Long Term Evolution (LTE) and LTE-Advanced, employ orthogonal frequency-division multiplexing (OFDM) and use frequency domain scheduling and rate adaptation. In conjunction with feedback reduction schemes, high downlink spectral efficiencies are achieved while limiting the uplink feedback overhead. One such important scheme that has been adopted by these standards is best-m feedback, in which every user feeds back its m largest subchannel (SC) power gains and their corresponding indices.We analyze the single cell average throughput of an OFDM system with uniformly correlated SC gains that employs best-mfeedback and discrete rate adaptation. Our model incorporates three schedulers that cover a wide range of the throughput versus fairness tradeoff and feedback delay. We show that, for small m, correlation significantly reduces average throughput with best-mfeedback. This result is pertinent as even in typical dispersive channels, correlation is high.

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124

MCMST 16 Power Efficient Scattered Pilot Channel Estimation for FBMC/OQAM

IEEE-2015 Filter bank multicarrier transmission with offset-QAM (FBMC/OQAM) is a promising candidate waveform for the next mobile communication systems as it is well suited for many new scenarios and challenges like improved spectral efficiency, spectrum sharing approaches or high mobility scenarios. It does not require a cyclic prefix (CP) leading to a higher spectral efficiency than orthogonal frequency division multiplexing with CP (CP-OFDM) and the flexibility of the transmit and receive filters enables higher throughput in spectral sharing and high mobility scenarios. One aspect to be considered is efficient channel estimation that is needed in order to realize these gains. As the classical channel estimation used for CP-OFDM cannot be applied directly to FBMC/OQAM, new competitive solutions are needed. One promising solution for the pilot design suited for FBMC introduces an auxiliary pilot (precoding symbol) that nullifies the intrinsic interference at the pilot position, but this leads to increased power on these auxiliary pilots.

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MCMST 17 Performance Analysis of Fast Tracking Equalization for SC-FDMA and OFDM systems under multipath fading environment

IEEE-2015 In this paper, SC-FDMA and OFDM systems with fast tracking equalizer based on RLS algorithm in multipath fading environments are proposed. In the proposed SC-FDMA and OFDM system with fast tracking equalizer, known-reference signals are allocated to the 1st slot of transmitting slots on each subcarrier at the transmitter. The transmitted signals are equalized with the reference signals on the frequency domain at the receiver. The channel information is updated by performing estimation based on RLS algorithm with the reference signals during the signal transmission, and the fast tracking equalization is performed. In order to confirm the transmission performance with fast tracking equalizer, computer simulations about BER and PAPR are carried out. As the results of computer simulation, the improvement of BER for the systems with equalizer based on LMS algorithm is about twice higher than the conventional system with only the initial equalization.

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MCMST 18 On Demand SINR based Scheduling Algorithm (ODSSA) for Mobile Uplink Communication in LTE Networks

IEEE-2015 Long Term Evolution (LTE) a Third Generation Partnership Project (3GPP) is developed for multimedia applications on mobile user equipment with very high data rates of the order 75/300 Mbps and low latency of 10msec. The high data rates are achieved by using SC-FDMA radio access mechanism for uplink communication and OFDM access mechanism for downlink. The performance can be

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further improved by scheduling the user data in an efficient manner considering channel characteristics as well as its QOS parameters, thereby allocating the resources to maximize the throughput. The Packet Scheduler helps in handling the LTE data traffic by allocating the resources both in time and frequency dimension. In this paper, we propose a novel scheduling algorithm that allocates maximum resources for the random users depending on their channel SNR condition with main focus on the data flow behavior.

MATLAB-DIGITAL SIGNAL PROCESSING

127 MSPST 1 High-Precision, Permanently Stable, Modulated Hopping Discrete Fourier Transform

IEEE-2015 A new modulated hopping Discrete Fourier Transform (mHDFT) algorithm which is characterized by its merits of high accuracy and constant stability is presented. The proposed algorithm, which is based on the circular frequency shift property of DFT, directly moves the DFT bin to the position of, and computes the DFT by incorporating the successive DFT outputs with arbitrary time hop . Compared to previous works, since the pole of mHDFT precisely settles on the unit circle in the Z-plane, the accumulated errors and potential instabilities, which are caused by the quantization of the twiddle factor, are always eliminated without increasing much computational effort. The numerical simulation results verify the effectiveness and superiority of the proposed algorithm.

128 MSPST 2 A Joint QRS Detection and Data Compression Scheme for Wearable Sensors

IEEE-2015 This paper presents a novel electrocardiogram (ECG) processing technique for joint data compression and QRS detection in awireless wearable sensor. The proposed algorithm is aimed at lowering the average complexity per task by sharing the computational load among multiple essential signal-processing tasks needed for wearable devices. The compression algorithm, which is based on an adaptive linear data prediction scheme, achieves a lossless bit compression ratio of 2.286x. The QRS detection algorithm achieves a sensitivity (Se) of 99.64% and positive prediction (+P) of 99.81% when tested with the MIT/BIH Arrhythmia database. Lower overall complexity and good performance renders the proposed technique suitable for wearable/ambulatory ECG devices.

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MATLAB-DIGITAL AUDIO-VIDEO PROCESSING

129 MVPST 1 Authenticating Using Secret Key in Digital Video Watermarking Using 3-Level DWT

IEEE-2015 Authenticating watermarking is nothing but inserting a hidden object in order to detect deceitful alteration by hackers. The object may be in terms of a secret key or password etc. There are quite few numbers of authentication methods are available for videos. Resent developers in digital video and internet technology helps the common user to easily produce illegal copies of videos. In order to solve the copyright protection problem and deceitful alteration by hackers of videos, several water marking schemes have been widely used. Very few authenticating of watermarking schemes have been produced for defining the copyrights of digital video. The process of Digital watermark embeds the data called watermark in digital media like image, video, audio file etc. so that it can be claimed for rights. The paper represents the complete software implementation of 3-Level DWT algorithms and to have more secure data a secret key is used. The secret key is given to watermark image during embedding process and while extracting the watermark image the same secret key is used. To check effectiveness of the watermark video MSE and PSNR parameters are used.

130

MAPST 1 Improved Lip Contour Extraction For Visual Speech Recognition

IEEE-2015 Automatic speech recognition systems perform on acoustic speech signals and therefore they are unreliable in noisy environments. Visual speech features such as lip movements of a speaker can make the speech recognition system robust. To track the lip movements, lip contour extraction is a necessary step and plays a crucial role in the visual speech recognition. In this paper, we propose a new method for lip contour extraction using fuzzy clustering with elliptic shape information and active contour model. In this method, we combined both image and model based methods to improve the performance of lip contour extraction. Our proposed lip contour extraction method outperforms few of existing lip contour extraction methods. We applied our lip contour extraction method on 3600 lip images from Vid Limit database and results are found better than the few existing lip contour extraction methods.

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131 IMAGE+COMMUNICA

TION PROCESSIN

G

Hybrid MIMO-OFDM System with Application to Image Transmission

IEEE-2015 In this paper performance of Image transmission with Space Time Block Coding (STBC) and Spatial Multiplexing (SM) and Hybrid MIMO with OFDM models are done. A Hybrid MIMO-OFDM is a combination of SM and STBC with OFDM. The performance of the above mentioned models are measured with respect to BER and Throughput and output image quality. The results demonstrate that Hybrid MIMO-OFDM provides low BER along with high throughput.

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S.N

O

CODE. NO PROJECT TITLES YEAR

1.POWER SYSTEMS

POWER QUALITY IMPROVEMENT, REACTIVE & HARMONIC COMPENSATION

132 001 New Control of PV Solar Farm as STATCOM (PV-STATCOM) for

Increasing Grid Power Transmission Limits During Night and Day

IEEE 2015

133 002 An Adaptive Power Oscillation Damping Controller by STATCOM With

Energy Storage

IEEE 2015

134 003 A New Control Strategy for Distributed Static Compensators Considering

Transmission Reactive Flow Constraints

IEEE 2015

135 004 A Voltage-Controlled DSTATCOM for Power-Quality Improvement IEEE 2015

136 005 An Improved Hybrid DSTATCOM Topology to Compensate Reactive and

Nonlinear Loads

IEEE 2015

137 006 The Transformerless Single-Phase Universal Active Power Filter for

Harmonic and Reactive Power Compensation

IEEE 2015

138 007 An Enhanced Voltage Sag Compensation Scheme for Dynamic Voltage

Restorer

IEEE 2015

139 008 An Improved iUPQC Controller to Provide Additional Grid-Voltage

Regulation as a STATCOM

IEEE 2015

140 009 A Grid-Connected Dual Voltage Source Inverter With Power Quality

Improvement Features

IEEE 2015

141 010 Transformerless Hybrid Power Filter Based on a Six Switch Two-Leg

Inverter for Improved Harmonic Compensation Performance

IEEE 2015

142 011 A New Railway Power Flow Control System Coupled

With Asymmetric Double LC Branches

IEEE 2015

143 012 Analysis of DC Link Operation Voltage of a Hybrid Railway Power Quality

Conditioner and its PQ Compensation Capability in High Speed Co-phase

Traction Power Supply

IEEE 2015

144 013 A Systematic Approach to Hybrid Railway Power Conditioner Design With

Harmonic Compensation for High-Speed Railway

IEEE 2015

2.RENEWABLE ENERGY

A) B) WIND ENERGY APPLICATION

145 014 High-Gain Resonant Switched-Capacitor Cell-Based DC/DC Converter for

Offshore Wind Energy Systems

IEEE 2015

146 015 DC Microgrid for Wind and Solar Power Integration

IEEE 2015

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C) D) SOLAR ENERGY APPLICATION

147 016 A Novel High Step-up DC/DC Converter Based on Integrating Coupled

Inductor and Switched-Capacitor Techniques for Renewable Energy

Applications

IEEE 2015

148 017 Hybrid Transformer ZVS/ZCS DC–DC Converter With Optimized

Magnetics and Improved Power Devices Utilization for Photovoltaic

Module Applications

IEEE 2015

149 018 Performance of Medium-Voltage DC-Bus PV System Architecture Utilizing

High-Gain DC–DC Converter

IEEE 2015

150 019 A Single Stage CCM Zeta Microinverter for Solar Photovoltaic AC Module IEEE 2015

151 020 Topology Review and Derivation Methodology of Single-Phase

Transformerless Photovoltaic Inverters for Leakage Current Suppression

IEEE 2015

152 021 A High Efficiency Flyback Micro-inverter With a New Adaptive Snubber

for Photovoltaic Applications

IEEE 2015

153 022 High Step-Up Converter With Three-Winding Coupled Inductor for Fuel

Cell Energy Source Applications

IEEE 2015

154 023 Optimized Operation of Current-Fed Dual Active Bridge DC-DC Converter

for PV Applications

IEEE 2015

155 024 Online Variable Topology-Type Photovoltaic Grid-Connected Inverter IEEE 2015

3.GRID CONNECTED SYSTEMS

156 025 An Enhanced Islanding Microgrid Reactive Power, Imbalance Power, and

Harmonic Power Sharing Scheme

IEEE 2015

157 026 A Novel Integrated Power Quality Controller for Microgrid IEEE 2015

158 027 Power Control in AC Isolated Microgrids With Renewable Energy

Sources and Energy Storage Systems

IEEE 2015

4.VEHICULAR APPLICATIONS

159 028 General Analysis and Design Guideline for a Battery Buffer System With

DC/DC Converter and EDLC for Electric Vehicles and its Influence on

Efficiency

IEEE 2015

160 029 Dual Active Bridge-Based Battery Charger for Plug-in Hybrid Electric

Vehicle with Charging Current Containing Low Frequency Ripple

IEEE 2015

161 030 Reduced-Capacity Smart Charger for Electric Vehicles on Single-Phase

Three-Wire Distribution Feeders With Reactive Power Control

IEEE 2015

162 031 A Non isolated Multi input Multi output DC–DC Boost

Converter for Electric Vehicle Applications

IEEE 2015

68

163 032 New Interleaved Current-Fed Resonant Converter With Significantly

Reduced High Current Side Output Filter for EV and HEV Applications

IEEE 2015

5.AC AND DC DRIVES

164 033 PFC Cuk Converter-Fed BLDC Motor Drive IEEE 2015

165 034 Variable-Form Carrier-Based PWM for Boost-Voltage Motor Driver With

a Charge-Pump Circuit

IEEE 2015

166 035 Sensorless Drive for High-Speed Brushless DC Motor Based on the Virtual

Neutral Voltage

IEEE 2015

167 036 Independent Control of Two Permanent-Magnet Synchronous Motors Fed

by a Four-Leg Inverter

IEEE 2015

168 037 Online Inverter Fault Diagnosis of Buck-Converter BLDC Motor

Combinations

IEEE 2015

169 038 A Unity Power Factor Bridgeless Isolated Cuk Converter-Fed Brushless DC

Motor Drive

IEEE 2015

6.BIDIRECTIONAL CONVERTER

170 039 A Zero-Voltage-Transition Bidirectional DC/DC Converter IEEE 2015

171 040 Steady-State Analysis of a ZVS Bidirectional Isolated Three Phase DC-DC

Converter Using Dual Phase-Shift Control with Variable Duty Cycle

IEEE 2015

172 041 Novel High-Conversion-Ratio High-Efficiency Isolated Bidirectional DC–

DC Converter

IEEE 2015

173 042 DC–DC Converter for Dual-Voltage Automotive Systems Based on

Bidirectional Hybrid Switched-Capacitor Architectures

IEEE 2015

174 043 A Novel PWM High Voltage Conversion Ratio Bi-Directional Three-Phase

DC/DC Converter with Y-Δ Connected Transformer

IEEE 2015

175 044 Performance Analysis of Bi-directional DC-DC Converters for Electric

Vehicles

IEEE 2015

7.LED LIGHTING APPLICATIONS

176 045 Offline Soft-Switched LED Driver Based on an Integrated Bridgeless

Boost–Asymmetrical Half-Bridge Converter

IEEE 2015

177 046 A Novel Control Scheme of Quasi-Resonant Valley-Switching for High-

Power-Factor AC-to-DC LED Drivers

IEEE 2015

178 047 A Novel Wall-Switched Step-Dimming Concept in LED Lighting

Systems using PFC Zeta Converter

IEEE 2015

179 048 Analysis and Design of Single-Switch Forward-Flyback Two-Channel LED Driver with Resonant-Blocking Capacitor

IEEE 2015

69

8.POWER FACTOR CORRECTION CONVERTER

180 049 Bridgeless PFC-Modified SEPIC Rectifier With Extended Gain for

Universal Input Voltage Applications

IEEE 2015

181 050 A Three-Level Quasi-Two-Stage Single-Phase PFC Converter with

Flexible Output Voltage and Improved Conversion Efficiency

IEEE 2015

182 051 Front-End Converter With Integrated PFC and DC–DC Functions for a

Fuel Cell UPS With DSP-Based Control

IEEE 2015

183 052 Loss-Free Resistor-Based Power Factor Correction Using a Semi-

Bridgeless Boost Rectifier in Sliding-Mode Control

IEEE 2015

184 053 Power Factor Corrected Zeta Converter Based Improved Power Quality

Switched Mode Power Supply

IEEE 2015

185 054 A New Interleaved Three-Phase Single-Stage PFC AC–DC Converter

With Flying Capacitor

IEEE 2015

9.RESONANT CONVERTER/INVERTER

186 055 Hybrid Phase-Shift-Controlled Three-Level and LLC DC–DC Converter

With Active Connection at the Secondary Side

IEEE 2015

187 056 Analysis and Design of LLC Resonant Converters With Capacitor–

Diode Clamp Current Limiting

IEEE 2015

188 057 A Secondary-Side Phase-Shift-Controlled LLC Resonant Converter

With Reduced Conduction Loss at Normal Operation for Hold-Up Time

Compensation Application

IEEE 2015

189 058 Optimal Design Methodology for LLC Resonant Converter in Battery

Charging Applications Based on Time-Weighted Average Efficiency

IEEE 2015

190 059 Analytical Model of the Half-Bridge Series Resonant

Inverter for Improved Power Conversion Efficiency and Performance

IEEE 2015

191 060 Multi-MOSFET-Based Series Resonant Inverter for Improved

Efficiency and Power Density Induction Heating Applications

IEEE 2015

10.HIGH VOLTAGE

A)INTERLEAVED CONVERTERS

192 061 A High Gain Input-Parallel Output-Series DC/DC Converter With Dual

Coupled Inductors

IEEE 2015

193 062 Bidirectional PWM Converter Integrating Cell Voltage Equalizer Using

Series-Resonant Voltage Multiplier for Series-Connected Energy

Storage Cells

IEEE 2015

194 063 Multicell Switched-Inductor/Switched-Capacitor Combined Active-

Network Converters

IEEE 2015

195 064 Reliability Evaluation of Conventional and Interleaved DC–DC Boost

Converters

IEEE 2015

70

B)SWITCHED CAPACITOR BASED CONVERTERS

196 065 A Novel Switched-Coupled-Inductor DC–DC Step-Up Converter and

Its Derivatives

IEEE 2015

197 066 Ripple Minimization Through Harmonic Elimination in Asymmetric

Interleaved Multiphase dc-dc Converters

IEEE 2015

198 067 Analysis of the Interleaved Isolated Boost Converter With Coupled

Inductors

IEEE 2015

199 068 High Step-Up Interleaved Forward-Flyback Boost Converter With

Three-Winding Coupled Inductors

IEEE 2015

200 069 A Novel Transformer-less Interleaved Four-Phase Step-down DC

Converter with Low Switch Voltage Stress and Automatic Uniform

Current Sharing Characteristics

IEEE 2015

201 070 Nonisolated High Step-Up DC–DC Converters Adopting Switched-

Capacitor Cell

IEEE 2015

202 071 A Family of High-Voltage Gain Single-Phase Hybrid

Switched-Capacitor PFC Rectifiers

IEEE 2015

203 072 A High-Efficiency Resonant Switched Capacitor Converter With

Continuous Conversion Ratio

IEEE 2015

204 073 A Cascade Point of Load DC-DC Converter with a Novel Phase Shifted

Switched Capacitor Converter Output Stage

IEEE 2015

205 074 Modeling Approaches for DC–DC Converters With Switched

Capacitors

IEEE 2015

11.ZVS, ZCS (SOFT SWITCHING) CONVERTERS

206 075 Resonance Analysis and Soft-Switching Design of Isolated Boost

Converter With Coupled Inductors for Vehicle Inverter Application

IEEE 2015

207 076 An Adaptive ZVS Full-Bridge DC–DC Converter With Reduced

Conduction Losses and Frequency Variation Range

IEEE 2015

208 077 An Integrated High-Power-Factor Converter with ZVS Transition IEEE 2015

209 078 A Novel Load Adaptive ZVS Auxiliary Circuit for PWM Three-Level

DC–DC Converters

IEEE 2015

210 079 Hybrid Modulated Extended Secondary Universal Current-Fed ZVS

Converter for Wide Voltage Range: Analysis, Design, and

Experimental Results

IEEE 2015

211 080 Two-Stage Power Conversion Architecture Suitable

for Wide Range Input Voltage

IEEE 2015

212 081 Naturally Clamped Zero-Current Commutated Soft-Switching

Current-Fed Push–Pull DC/DC Converter: Analysis, Design, and

Experimental Results

IEEE 2015

213 082 A Soft-Switched Asymmetric Flying Capacitor Boost Converter with

Synchronous Rectification

IEEE 2015

71

12.MULTIPORT CONVERTER

214 083 A Nonisolated Three-Port DC–DC Converter and Three-Domain

Control Method for PV-Battery Power Systems

IEEE 2015

215 084 A Power Decoupling Method Based on Four-Switch Three-Port

DC/DC/AC Converter in DC Microgrid

IEEE 2015

216 085 Three-Port DC–DC Converter for Stand-Alone Photovoltaic Systems IEEE 2015

217 086 A Family of Multiport Buck–Boost Converters Based on DC-Link-

Inductors (DLIs)

IEEE 2015

218 087 An Isolated Three-Port Bidirectional DC-DC Converter for

Photovoltaic Systems with Energy Storage

IEEE 2015

13.MULTIPLE OUTPUT CONVERTER

219 088 A High Step-Down Multiple Output Converter With Wide Input

Voltage Range Based on Quasi Two-Stage Architecture and Dual-

Output LLC Resonant Converter

IEEE 2015

220 089 Single-Inductor Dual-Output Buck–Boost Power Factor Correction

Converter

IEEE 2015

14.AC TO AC CONVERTER

221 090 A Bridgeless BHB ZVS-PWM AC-AC Converter for High-Frequency

Induction Heating Applications

IEEE 2015

222 091 Novel Single-Phase PWM AC–AC Converters Solving Commutation

Problem Using Switching Cell Structure and Coupled Inductor

IEEE 2015

223 092 Soft-Switching AC-Link Three-Phase AC–AC Buck–Boost Converter IEEE 2015

224 093 Ultra sparse AC-Link Converters IEEE 2015

15.INVERTER & MULTILEVEL INVERTER

225 094 Discontinuous Modulation Scheme for a Differential-Mode Cuk

Inverter

IEEE 2015

226 095 A High-Efficiency MOSFET Transformerless Inverter for Nonisolated

Microinverter Applications

IEEE 2015

227 096 A Multilevel Energy Buffer and Voltage Modulator for Grid-Interfaced

Microinverters

IEEE 2015

228 097 Extended Boost Active-Switched-Capacitor/ Switched-Inductor Quasi-

Z-Source Inverters

IEEE 2015

229 098 Grid-Connected Forward Microinverter With Primary-Parallel

Secondary-Series Transformer

IEEE 2015

230 099 Minimization of the DC Component in Transformerless Three-Phase

Grid-Connected Photovoltaic Inverters

IEEE 2015

72

231 100 Single Inductor Dual Buck Full-Bridge Inverter IEEE 2015

232 101 A Single-Phase Cascaded Multilevel Inverter Based on a New Basic

Unit With Reduced Number of Power Switches

IEEE 2015

73

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