Abstract: By introducing the concept of Oracle we propose an approach for improving the performance of genetic algorithms for large-scale asymmetric Traveling Salesman Problems. The results have shown that the proposed approach allows overcoming some traditional problems for creating efficient genetic algorithms.
Abstract: Network layer multicast, i.e. IP multicast, even after
many years of research, development and standardization, is not
deployed in large scale due to both technical (e.g. upgrading of
routers) and political (e.g. policy making and negotiation) issues.
Researchers looked for alternatives and proposed application/overlay
multicast where multicast functions are handled by end hosts, not
network layer routers. Member hosts wishing to receive multicast
data form a multicast delivery tree. The intermediate hosts in the tree
act as routers also, i.e. they forward data to the lower hosts in the
tree. Unlike IP multicast, where a router cannot leave the tree until all
members below it leave, in overlay multicast any member can leave
the tree at any time thus disjoining the tree and disrupting the data
dissemination. All the disrupted hosts have to rejoin the tree. This
characteristic of the overlay multicast causes multicast tree unstable,
data loss and rejoin overhead. In this paper, we propose that each node
sets its leaving time from the tree and sends join request to a number
of nodes in the tree. The nodes in the tree will reject the request if
their leaving time is earlier than the requesting node otherwise they
will accept the request. The node can join at one of the accepting
nodes. This makes the tree more stable as the nodes will join the tree
according to their leaving time, earliest leaving time node being at the
leaf of the tree. Some intermediate nodes may not follow their leaving
time and leave earlier than their leaving time thus disrupting the tree.
For this, we propose a proactive recovery mechanism so that disrupted
nodes can rejoin the tree at predetermined nodes immediately. We
have shown by simulation that there is less overhead when joining
the multicast tree and the recovery time of the disrupted nodes is
much less than the previous works. Keywords
Abstract: In this paper, we propose a Perceptually Optimized Foveation based Embedded ZeroTree Image Coder (POEFIC) that introduces a perceptual weighting to wavelet coefficients prior to control SPIHT encoding algorithm in order to reach a targeted bit rate with a perceptual quality improvement with respect to a given bit rate a fixation point which determines the region of interest ROI. The paper also, introduces a new objective quality metric based on a Psychovisual model that integrates the properties of the HVS that plays an important role in our POEFIC quality assessment. Our POEFIC coder is based on a vision model that incorporates various masking effects of human visual system HVS perception. Thus, our coder weights the wavelet coefficients based on that model and attempts to increase the perceptual quality for a given bit rate and observation distance. The perceptual weights for all wavelet subbands are computed based on 1) foveation masking to remove or reduce considerable high frequencies from peripheral regions 2) luminance and Contrast masking, 3) the contrast sensitivity function CSF to achieve the perceptual decomposition weighting. The new perceptually optimized codec has the same complexity as the original SPIHT techniques. However, the experiments results show that our coder demonstrates very good performance in terms of quality measurement.
Abstract: The necessity of accurate and timely field data is
shared among organizations engaged in fundamentally different
activities, public services or commercial operations. Basically, there
are three major components in the process of the qualitative research:
data collection, interpretation and organization of data, and analytic
process. Representative technological advancements in terms of
innovation have been made in mobile devices (mobile phone, PDA-s,
tablets, laptops, etc). Resources that can be potentially applied on the
data collection activity for field researches in order to improve this
process.
This paper presents and discuss the main features of a mobile
phone based solution for field data collection, composed of basically
three modules: a survey editor, a server web application and a client
mobile application. The data gathering process begins with the
survey creation module, which enables the production of tailored
questionnaires. The field workforce receives the questionnaire(s) on
their mobile phones to collect the interviews responses and sending
them back to a server for immediate analysis.
Abstract: The dynamics of User Datagram Protocol (UDP) traffic
over Ethernet between two computers are analyzed using nonlinear
dynamics which shows that there are two clear regimes in the data
flow: free flow and saturated. The two most important variables
affecting this are the packet size and packet flow rate. However,
this transition is due to a transcritical bifurcation rather than phase
transition in models such as in vehicle traffic or theorized large-scale
computer network congestion. It is hoped this model will help lay
the groundwork for further research on the dynamics of networks,
especially computer networks.
Abstract: Background: Dialign is a DNA/Protein alignment tool
for performing pairwise and multiple pairwise alignments through the
comparison of gap-free segments (fragments) between sequence
pairs. An alignment of two sequences is a chain of fragments, i.e
local gap-free pairwise alignments, with the highest total score.
METHOD: A new approach is defined in this article which relies on
the concept of using three-dimensional fragments – i.e. local threeway
alignments -- in the alignment process instead of twodimensional
ones. These three-dimensional fragments are gap-free
alignments constituting of equal-length segments belonging to three
distinct sequences. RESULTS: The obtained results showed good
improvments over the performance of DIALIGN.
Abstract: Choosing the right metadata is a critical, as good
information (metadata) attached to an image will facilitate its
visibility from a pile of other images. The image-s value is enhanced
not only by the quality of attached metadata but also by the technique
of the search. This study proposes a technique that is simple but
efficient to predict a single human image from a website using the
basic image data and the embedded metadata of the image-s content
appearing on web pages. The result is very encouraging with the
prediction accuracy of 95%. This technique may become a great
assist to librarians, researchers and many others for automatically and
efficiently identifying a set of human images out of a greater set of
images.
Abstract: Arms detection is one of the fundamental problems in
human motion analysis application. The arms are considered as the
most challenging body part to be detected since its pose and speed
varies in image sequences. Moreover, the arms are usually occluded
with other body parts such as the head and torso. In this paper,
histogram-based skin colour segmentation is proposed to detect the
arms in image sequences. Six different colour spaces namely RGB,
rgb, HSI, TSL, SCT and CIELAB are evaluated to determine the best
colour space for this segmentation procedure. The evaluation is
divided into three categories, which are single colour component,
colour without luminance and colour with luminance. The
performance is measured using True Positive (TP) and True Negative
(TN) on 250 images with manual ground truth. The best colour is
selected based on the highest TN value followed by the highest TP
value.
Abstract: In some real applications of Statistical Process Control
it is necessary to design a control chart to not detect small process
shifts, but keeping a good performance to detect moderate and large
shifts in the quality. In this work we develop a new quality control
chart, the synthetic T2 control chart, that can be designed to cope with
this objective. A multi-objective optimization is carried out employing
Genetic Algorithms, finding the Pareto-optimal front of
non-dominated solutions for this optimization problem.
Abstract: Information is increasing in volumes; companies are overloaded with information that they may lose track in getting the intended information. It is a time consuming task to scan through each of the lengthy document. A shorter version of the document which contains only the gist information is more favourable for most information seekers. Therefore, in this paper, we implement a text summarization system to produce a summary that contains gist information of oil and gas news articles. The summarization is intended to provide important information for oil and gas companies to monitor their competitor-s behaviour in enhancing them in formulating business strategies. The system integrated statistical approach with three underlying concepts: keyword occurrences, title of the news article and location of the sentence. The generated summaries were compared with human generated summaries from an oil and gas company. Precision and recall ratio are used to evaluate the accuracy of the generated summary. Based on the experimental results, the system is able to produce an effective summary with the average recall value of 83% at the compression rate of 25%.
Abstract: Mobile agent has motivated the creation of a new
methodology for parallel computing. We introduce a methodology
for the creation of parallel applications on the network. The proposed
Mobile-Agent parallel processing framework uses multiple Javamobile
Agents. Each mobile agent can travel to the specified
machine in the network to perform its tasks. We also introduce the
concept of master agent, which is Java object capable of
implementing a particular task of the target application. Master agent
is dynamically assigns the task to mobile agents. We have developed
and tested a prototype application: Mobile Agent Based Parallel
Computing. Boosted by the inherited benefits of using Java and
Mobile Agents, our proposed methodology breaks the barriers
between the environments, and could potentially exploit in a parallel
manner all the available computational resources on the network.
This paper elaborates performance issues of a mobile agent for
parallel computing.
Abstract: The main aim of this research is to investigate a novel technique for implementing a more natural and intelligent conversation system. Conversation systems are designed to converse like a human as much as their intelligent allows. Sometimes, we can think that they are the embodiment of Turing-s vision. It usually to return a predetermined answer in a predetermined order, but conversations abound with uncertainties of various kinds. This research will focus on an integrated natural language processing approach. This approach includes an integrated knowledge-base construction module, a conversation understanding and generator module, and a state manager module. We discuss effectiveness of this approach based on an experiment.
Abstract: The group mutual exclusion (GME) problem is an
interesting generalization of the mutual exclusion problem. In the
group mutual exclusion, multiple processes can enter a critical
section simultaneously if they belong to the same group. In the
extended group mutual exclusion, each process is a member of
multiple groups at the same time. As a result, after the process by
selecting a group enter critical section, other processes can select the
same group with its belonging group and can enter critical section at
the moment, so that it avoids their unnecessary blocking. This paper
presents a quorum-based distributed algorithm for the extended
group mutual exclusion problem. The message complexity of our
algorithm is O(4Q ) in the best case and O(5Q) in the worst case,
where Q is a quorum size.
Abstract: To improve the classification rate of the face
recognition, features combination and a novel non-linear kernel are
proposed. The feature vector concatenates three different radius of
local binary patterns and Gabor wavelet features. Gabor features are
the mean, standard deviation and the skew of each scaling and
orientation parameter. The aim of the new kernel is to incorporate
the power of the kernel methods with the optimal balance between
the features. To verify the effectiveness of the proposed method,
numerous methods are tested by using four datasets, which are
consisting of various emotions, orientations, configuration,
expressions and lighting conditions. Empirical results show the
superiority of the proposed technique when compared to other
methods.
Abstract: The goal of this project is to design a system to
recognition voice commands. Most of voice recognition systems
contain two main modules as follow “feature extraction" and “feature
matching". In this project, MFCC algorithm is used to simulate
feature extraction module. Using this algorithm, the cepstral
coefficients are calculated on mel frequency scale. VQ (vector
quantization) method will be used for reduction of amount of data to
decrease computation time. In the feature matching stage Euclidean
distance is applied as similarity criterion. Because of high accuracy
of used algorithms, the accuracy of this voice command system is
high. Using these algorithms, by at least 5 times repetition for each
command, in a single training session, and then twice in each testing
session zero error rate in recognition of commands is achieved.
Abstract: The users are now expecting higher level of
DSP(Digital Signal Processing) software quality than ever before.
Prevention and detection of defect are critical elements of software
quality assurance. In this paper, principles and rules for prevention and
detection of defect are suggested, which are not universal guidelines,
but are useful for both novice and experienced DSP software
developers.
Abstract: Utilities use operating reserve for frequency regulation.To ensure that the operating frequency and system security are well maintained, the operating grid codes always specify that the reserve quantity and response rate should meet some prescribed levels. This paper proposes a methodology to evaluate system's contingency reserve for an isolated power network. With the presented algorithm to estimate system's frequency response characteristic, an online allocation of contingency reserve would be feasible to meet the grid codes for contingency operation. Test results from the simulated conditions, and from the actual operating data verify the merits of the proposed methodology to system's frequency control, and security.
Abstract: In this paper, we propose an energy efficient cluster
based communication protocol for wireless sensor network. Our
protocol considers both the residual energy of sensor nodes and the
distance of each node from the BS when selecting cluster-head. This
protocol can successfully prolong the network-s lifetime by 1)
reducing the total energy dissipation on the network and 2) evenly
distributing energy consumption over all sensor nodes. In this
protocol, the nodes with more energy and less distance from the BS
are probable to be selected as cluster-head. Simulation results with
MATLAB show that proposed protocol could increase the lifetime of
network more than 94% for first node die (FND), and more than 6%
for the half of the nodes alive (HNA) factor as compared with
conventional protocols.
Abstract: In recent years there has been renewal of interest in the
relation between Green IT and Cloud Computing. The growing use of
computers in cloud platform has caused marked energy consumption,
putting negative pressure on electricity cost of cloud data center. This
paper proposes an effective mechanism to reduce energy utilization in
cloud computing environments. We present initial work on the
integration of resource and power management that aims at reducing
power consumption. Our mechanism relies on recalling virtualization
services dynamically according to user-s virtualization request and
temporarily shutting down the physical machines after finish in order
to conserve energy. Given the estimated energy consumption, this
proposed effort has the potential to positively impact power
consumption. The results from the experiment concluded that energy
indeed can be saved by powering off the idling physical machines in
cloud platforms.
Abstract: The growing influence of service industries has
prompted greater attention being paid to service operations
management. However, service managers often have difficulty
articulating the veritable effects of their service innovation. Especially,
the performance evaluation process of service innovation problems
generally involves uncertain and imprecise data. This paper presents a
2-tuple fuzzy linguistic computing approach to dealing with
heterogeneous information and information loss problems while the
processes of subjective evaluation integration. The proposed method
based on group decision-making scenario to assist business managers
in measuring performance of service innovation manipulates the
heterogeneity integration processes and avoids the information loss
effectively.