Abstract: Establishing a secure communication of Internet
conferences for participants is very important. Before starting the
conference, all the participants establish a common conference key to
encrypt/decrypt communicated messages. It enables participants to
exchange the secure messages. Nevertheless, in the conference, if
there are any malicious participants who may try to upset the key
generation process causing other legal participants to obtain a different
conference key. In this article, we propose an improved conference
key agreement with fault-tolerant capability. The proposed scheme
can filter malicious participants at the beginning of the conference to
ensure that all participants obtain the same conference key. Compare
with other schemes, our scheme is more secure and efficient than
others.
Abstract: Image segmentation and color identification is an
important process used in various emerging fields like intelligent
robotics. A method is proposed for the manipulator to grasp and place
the color object into correct location. The existing methods such as
PSO, has problems like accelerating the convergence speed and
converging to a local minimum leading to sub optimal performance.
To improve the performance, we are using watershed algorithm and
for color identification, we are using EPSO. EPSO method is used to
reduce the probability of being stuck in the local minimum. The
proposed method offers the particles a more powerful global
exploration capability. EPSO methods can determine the particles
stuck in the local minimum and can also enhance learning speed as
the particle movement will be faster.
Abstract: One of the key aspects of power quality improvement
in power system is the mitigation of voltage sags/swells and flicker.
Custom power devices have been known as the best tools for voltage
disturbances mitigation as well as reactive power compensation.
Dynamic Voltage Restorer (DVR) which is the most efficient and
effective modern custom power device can provide the most
commercial solution to solve several problems of power quality in
distribution networks. This paper deals with analysis and simulation
technique of DVR based on instantaneous power theory which is a
quick control to detect signals. The main purpose of this work is to
remove three important disturbances including voltage sags/swells
and flicker. Simulation of the proposed method was carried out on
two sample systems by using Matlab software environment and the
results of simulation show that the proposed method is able to
provide desirable power quality in the presence of wide range of
disturbances.
Abstract: In this paper, the exergy analysis of vapor absorption
refrigeration system using LiBr-H2O as working fluid is carried out
with the modified Gouy-Stodola approach rather than the classical
Gouy-Stodola equation and effect of varying input parameters is also
studied on the performance of the system. As the modified approach
uses the concept of effective temperature, the mathematical
expressions for effective temperature have been formulated and
calculated for each component of the system. Various constraints and
equations are used to develop program in EES to solve these
equations. The main aim of this analysis is to determine the
performance of the system and the components having major
irreversible loss. Results show that exergy destruction rate is
considerable in absorber and generator followed by evaporator and
condenser. There is an increase in exergy destruction in generator,
absorber and condenser and decrease in the evaporator by the
modified approach as compared to the conventional approach. The
value of exergy determined by the modified Gouy-Stodola equation
deviates maximum i.e. 26% in the generator as compared to the
exergy calculated by the classical Gouy-Stodola method.
Abstract: Vehicular Adhoc Network (VANET) is a new
technology which aims to ensure intelligent inter-vehicle
communications, seamless internet connectivity leading to improved
road safety, essential alerts, and access to comfort and entertainment.
VANET operations are hindered by mobile node’s (vehicles)
uncertain mobility. Routing algorithms use metrics to evaluate which
path is best for packets to travel. Metrics like path length (hop count),
delay, reliability, bandwidth, and load determine optimal route. The
proposed scheme exploits link quality, traffic density, and
intersections as routing metrics to determine next hop. This study
enhances Geographical Routing Protocol (GRP) using fuzzy
controllers while rules are optimized with Bee Swarm Optimization
(BSO). Simulations results are compared to conventional GRP.
Abstract: Image search engines rely on the surrounding textual
keywords for the retrieval of images. It is a tedious work for the
search engines like Google and Bing to interpret the user’s search
intention and to provide the desired results. The recent researches
also state that the Google image search engines do not work well on
all the images. Consequently, this leads to the emergence of efficient
image retrieval technique, which interprets the user’s search intention
and shows the desired results. In order to accomplish this task, an
efficient image re-ranking framework is required. Sequentially, to
provide best image retrieval, the new image re-ranking framework is
experimented in this paper. The implemented new image re-ranking
framework provides best image retrieval from the image dataset by
making use of re-ranking of retrieved images that is based on the
user’s desired images. This is experimented in two sections. One is
offline section and other is online section. In offline section, the reranking
framework studies differently (reference classes or Semantic
Spaces) for diverse user query keywords. The semantic signatures get
generated by combining the textual and visual features of the images.
In the online section, images are re-ranked by comparing the
semantic signatures that are obtained from the reference classes with
the user specified image query keywords. This re-ranking
methodology will increases the retrieval image efficiency and the
result will be effective to the user.
Abstract: Securing the confidential data transferred via wireless
network remains a challenging problem. It is paramount to ensure
that data are accessible only by the legitimate users rather than by the
attackers. One of the most serious threats to organization is jamming,
which disrupts the communication between any two pairs of nodes.
Therefore, designing an attack-defending scheme without any packet
loss in data transmission is an important challenge. In this paper,
Dependence based Malicious Route Defending DMRD Scheme has
been proposed in multi path routing environment to prevent jamming
attack. The key idea is to defend the malicious route to ensure
perspicuous transmission. This scheme develops a two layered
architecture and it operates in two different steps. In the first step,
possible routes are captured and their agent dependence values are
marked using triple agents. In the second step, the dependence values
are compared by performing comparator filtering to detect malicious
route as well as to identify a reliable route for secured data
transmission. By simulation studies, it is observed that the proposed
scheme significantly identifies malicious route by attaining lower
delay time and route discovery time; it also achieves higher
throughput.
Abstract: In this paper, Fuzzy C-Means clustering with
Expectation Maximization-Gaussian Mixture Model based hybrid
modeling algorithm is proposed for Continuous Tamil Speech
Recognition. The speech sentences from various speakers are used
for training and testing phase and objective measures are between the
proposed and existing Continuous Speech Recognition algorithms.
From the simulated results, it is observed that the proposed algorithm
improves the recognition accuracy and F-measure up to 3% as
compared to that of the existing algorithms for the speech signal from
various speakers. In addition, it reduces the Word Error Rate, Error
Rate and Error up to 4% as compared to that of the existing
algorithms. In all aspects, the proposed hybrid modeling for Tamil
speech recognition provides the significant improvements for speechto-
text conversion in various applications.
Abstract: Wireless sensor network (WSN) is a network of many interconnected networked systems, they equipped with energy resources and they are used to detect other physical characteristics. On WSN, there are many researches are performed in past decades. WSN applicable in many security systems govern by military and in many civilian related applications. Thus, the security of WSN gets attention of researchers and gives an opportunity for many future aspects. Still, there are many other issues are related to deployment and overall coverage, scalability, size, energy efficiency, quality of service (QoS), computational power and many more. In this paper we discus about various applications and security related issue and requirements of WSN.
Abstract: Skin detection is an important task for computer
vision systems. A good method of skin detection means a good and
successful result of the system.
The colour is a good descriptor for image segmentation and
classification; it allows detecting skin colour in the images. The
lighting changes and the objects that have a colour similar than skin
colour make the operation of skin detection difficult.
In this paper, we proposed a method using the YCbCr colour space
for skin detection and lighting effects elimination, then we use the
information of texture to eliminate the false regions detected by the
YCbCr skin model.
Abstract: Key frame extraction methods select the most
representative frames of a video, which can be used in different areas
of video processing such as video retrieval, video summary, and video
indexing. In this paper we present a novel approach for extracting key
frames from video sequences. The frame is characterized uniquely by
his contours which are represented by the dominant blocks. These
dominant blocks are located on the contours and its near textures.
When the video frames have a noticeable changement, its dominant
blocks changed, then we can extracte a key frame. The dominant
blocks of every frame is computed, and then feature vectors are
extracted from the dominant blocks image of each frame and arranged
in a feature matrix. Singular Value Decomposition is used to calculate
sliding windows ranks of those matrices. Finally the computed ranks
are traced and then we are able to extract key frames of a video.
Experimental results show that the proposed approach is robust
against a large range of digital effects used during shot transition.
Abstract: Many studies have revealed the fact of the complexity
of ontology building process. Therefore there is a need for a new
approach which one of that addresses the socio-technical aspects in the
collaboration to reach a consensus. Meta-design approach is
considered applicable as a method in the methodological model of
socio-technical ontology engineering. Principles in the meta-design
framework are applied in the construction phases of the ontology. A
web portal is developed to support the meta-design principles
requirements. To validate the methodological model semantic web
applications were developed and integrated in the portal and also used
as a way to show the usefulness of the ontology. The knowledge based
system will be filled with data of Indonesian medicinal plants. By
showing the usefulness of the developed ontology in a semantic web
application, we motivate all stakeholders to participate in the
development of knowledge based system of medicinal plants in
Indonesia.
Abstract: Existing methods of data mining cannot be applied on
spatial data because they require spatial specificity consideration, as
spatial relationships.
This paper focuses on the classification with decision trees, which
are one of the data mining techniques. We propose an extension of
the C4.5 algorithm for spatial data, based on two different approaches
Join materialization and Querying on the fly the different tables.
Similar works have been done on these two main approaches, the
first - Join materialization - favors the processing time in spite of
memory space, whereas the second - Querying on the fly different
tables- promotes memory space despite of the processing time.
The modified C4.5 algorithm requires three entries tables: a target
table, a neighbor table, and a spatial index join that contains the
possible spatial relationship among the objects in the target table and
those in the neighbor table. Thus, the proposed algorithms are applied
to a spatial data pattern in the accidentology domain.
A comparative study of our approach with other works of
classification by spatial decision trees will be detailed.
Abstract: In the cloud computing hierarchy IaaS is the lowest
layer, all other layers are built over it. Thus it is the most important
layer of cloud and requisite more importance. Along with advantages
IaaS faces some serious security related issue. Mainly Security
focuses on Integrity, confidentiality and availability. Cloud
computing facilitate to share the resources inside as well as outside of
the cloud. On the other hand, cloud still not in the state to provide
surety to 100% data security. Cloud provider must ensure that end
user/client get a Quality of Service. In this report we describe
possible aspects of cloud related security.
Abstract: The operation of nuclear power plants involves
continuous monitoring of the environment in their area. This
monitoring is performed using a complex data acquisition system,
which collects status information about the system itself and values
of many important physical variables e.g. temperature, humidity,
dose rate etc. This paper describes a proposal and optimization of
communication that takes place in teledosimetric system between the
central control server responsible for the data processing and storing
and the decentralized measuring stations, which are measuring the
physical variables. Analyzes of ongoing communication were
performed and consequently the optimization of the system
architecture and communication was done.
Abstract: Assertion-Based software testing has been shown to
be a promising tool for generating test cases that reveal program
faults. Because the number of assertions may be very large for
industry-size programs, one of the main concerns to the applicability
of assertion-based testing is the amount of search time required to
explore a large number of assertions. This paper presents a new
approach for assertions exploration during the process of Assertion-
Based software testing. Our initial exterminations with the proposed
approach show that the performance of Assertion-Based testing may
be improved, therefore, making this approach more efficient when
applied on programs with large number of assertions.
Abstract: The handwriting is a physical demonstration of a
complex cognitive process learnt by man since his childhood. People
with disabilities or suffering from various neurological diseases are
facing so many difficulties resulting from problems located at the
muscle stimuli (EMG) or signals from the brain (EEG) and which
arise at the stage of writing. The handwriting velocity of the same
writer or different writers varies according to different criteria: age,
attitude, mood, writing surface, etc. Therefore, it is interesting to
reconstruct an experimental basis records taking, as primary
reference, the writing speed for different writers which would allow
studying the global system during handwriting process. This paper
deals with a new approach of the handwriting system modeling based
on the velocity criterion through the concepts of artificial neural
networks, precisely the Radial Basis Functions (RBF) neural
networks. The obtained simulation results show a satisfactory
agreement between responses of the developed neural model and the
experimental data for various letters and forms then the efficiency of
the proposed approaches.
Abstract: This paper deals with the problem of automatic rule
generation for fuzzy systems design. The proposed approach is based
on hybrid artificial bee colony (ABC) optimization and weighted least
squares (LS) method and aims to find the structure and parameters of
fuzzy systems simultaneously. More precisely, two ABC based fuzzy
modeling strategies are presented and compared. The first strategy
uses global optimization to learn fuzzy models, the second one
hybridizes ABC and weighted least squares estimate method. The
performances of the proposed ABC and ABC-LS fuzzy modeling
strategies are evaluated on complex modeling problems and compared
to other advanced modeling methods.
Abstract: Due to the large amount of information in the World
Wide Web (WWW, web) and the lengthy and usually linearly
ordered result lists of web search engines that do not indicate
semantic relationships between their entries, the search for topically
similar and related documents can become a tedious task. Especially,
the process of formulating queries with proper terms representing
specific information needs requires much effort from the user. This
problem gets even bigger when the user's knowledge on a subject and
its technical terms is not sufficient enough to do so. This article
presents the new and interactive search application DocAnalyser that
addresses this problem by enabling users to find similar and related
web documents based on automatic query formulation and state-ofthe-
art search word extraction. Additionally, this tool can be used to
track topics across semantically connected web documents.
Abstract: In this paper, we have proposed a parallel IDS and
honeypot based approach to detect and analyze the unknown and
known attack taxonomy for improving the IDS performance and
protecting the network from intruders. The main theme of our
approach is to record and analyze the intruder activities by using both
the low and high interaction honeypots. Our architecture aims to
achieve the required goals by combing signature based IDS,
honeypots and generate the new signatures. The paper describes the
basic component, design and implementation of this approach and
also demonstrates the effectiveness of this approach to reduce the
probability of network attacks.