Iris-Pupil Thickness Based Method for Determining
Age Group of a Person
Asima Abbasi and Muhammad Khan
Shaheed
Zulfikar Ali Bhutto Institute of Sciences and Technology, Pakistan
Abstract: Soft
biometric attributes such as gender, ethnicity and age can be determined from
the iris images. Pupil size plays an important factor in iris template aging.
In this study, statistical experiments are performed to find out confidence
interval for Iris-Pupil thickness of different age groups such as children, youth
and senior citizen. Significant group differences have been observed by
applying statistical techniques such as Analysis of Variance (ANOVA) and the
Tukey’s pairwise comparison test. The results of the study conclude that the
proposed methodology can be employed to determine age group of a person from
the available iris images. Based on the study results, we argue that performance
of an iris recognition system can be enhanced by identifying age group of the
persons from their iris images.
Keywords: Iris recognition, feature
extraction, iris aging, iris pupil ratio.
Received July 10, 2014;
accepted April 2, 2015;
Published online December 23, 2015
Parallel Particle Filters for Multiple Target Tracking
Sebbagh Abdennour and Tebbikh
Hicham
Automatic
and Computing Laboratory of Guelma (LAIG), 8 Mai 1945 Guelma University,
Algeria
Abstract: The Multiple Targets Tracking (MTT) problem
is addressed in signal and image processing. When the state and measurement models are linear, we
can find several algorithms that yield good performances in MTT problem, among
them, the Multiple Hypotheses Tracker (MHT) and the Joint Probabilistic Data
Association Filter (JPDAF). However, if the state and measurement models are
nonlinear, these algorithms break down. In this paper we
propose a method based on particle filters bank, where the objective is to make
a contribution for estimating the trajectories of several targets using only
bearings measurements. The main idea of this algorithm is to combine the Multiple
Model approach (MM) with Sequential Monte Carlo methods (SMC). The result from
this combination is a Nonlinear Multiple Model Particle Filters algorithm
(NMMPF) able to estimate the trajectories of multiple targets.
Keywords: MM approach, MTT, particle filtering.
Received August 21, 2014; accepted December 21, 2014; Published online December 23, 2015
Face Image Super
Resolution via Adaptive-Block PCA
Lin Cao and Dan Liu
Department of
Telecommunication Engineering, Beijing Information Science
and
Technology University, China
Abstract: A novel single face image Super Resolution (SR) framework
based on adaptive-block Principal
Component Analysis (PCA)
is presented in this paper. The basic idea is the reconstruction of a High Resolution (HR) face image from a Low Resolution (LR)
observation based on a set of HR and LR training image pairs. The HR image block is generated in
the proposed method by using
the same position image blocks of each training image. The test face image and the training image
sets are divided into
many overlapping blocks, then these image blocks are classified according to
the characteristics of the image block and then PCA is operated directly on the non-flat image blocks to extract the optimal weights and the hallucinated patches are reconstructed
using the same weights. The final HR facial image is formed by integrating the
hallucinated patches. Experiments indicate that the new method produces HR faces
of higher quality and costs less computational time than some recent face image
SR techniques.
Keywords: SR, face image, adaptive-block,
PCA.
Received October 30, 2013; accepted November 20, 2014; Published online December 23, 2015
KP-Trie Algorithm for Update and Search Operations
Feras Hanandeh1, Izzat
Alsmadi2, Mohammed Akour3, and Essam Al Daoud4
1Department of Computer Information
Systems, Hashemite University, Jordan
2, 3Department of Computer Information Systems, Yarmouk University, Jordan
4Computer Science Department, Zarqa University, Jordan
Abstract: Radix-Tree is a space optimized data structure that performs data
compression by means of cluster nodes that share the same branch. Each node
with only one child is merged with its child and is considered as space
optimized. Nevertheless, it can’t be considered as speed optimized because the
root is associated with the empty string. Moreover, values are not
normally associated with every node; they are associated only with leaves and
some inner nodes that correspond to keys of interest. Therefore, it takes time
in moving bit by bit to reach the desired word. In this paper we propose the
KP-Trie which is consider as speed and space optimized data structure that is
resulted from both horizontal and vertical compression.
Keywords: Trie, radix tree, data structure, branch factor,
indexing, tree structure, information retrieval.
Received January 14, 2015;
accepted March 23, 2015; Published online
December 23, 2015
Test Case Prioritization for Regression Testing
Using Immune Operator
Angelin Gladston1, Khanna Nehemiah1,
Palanisamy Narayanasamy2, and Arputharaj Kannan2
1Ramanujan Computing Centre,
Anna University, India
2Department of Information Science and Technology, Anna
University, India
Abstract: Regression
testing is a time consuming, costly process of re-running existing test cases. As
software evolves, the regression test suite grows in size. Test case
prioritization techniques help by ordering test cases such that at least the
test cases which cover the changes made in the software are executed amidst
resource and time constraints. Genetic Algorithm (GA) has been widely used for
test case prioritization problem, however it has low convergence problem. In
this work, the Immune Genetic Algorithm (IGA) is applied for test case
prioritization, so that test case prioritization converges earlier. Our
contributions in Immune Prioritization Algorithm (IPA) include a method for
vaccine selection, zero drop function and probability selection function. The prioritized
result of IPA is evaluated against GA and the statement coverage, decision
coverage and block coverage of the test cases prioritized using IPA are found
to have improved. Further, IPA showed improved average fitness value as well as
optimal fitness value compared to genetic algorithm.
Keywords:
Immune operator, vaccine, test case
prioritization, regression testing, GA, IPA.
Received July 3, 2012; accepted April 29, 2013; Published online December 23, 2015
An Anti-Spam Filter Based on One-Class IB Method in
Small Training Sets
Chen Yang1, Shaofeng Zhao2, Dan Zhang3, and Junxia Ma1
1School of Software Engineering, Zhengzhou University of Light Industry, China
2Henan University of Economics and Law, China
3Geophysical Exploration Center of China Earthquake Administration, China
Abstract: We present an
approach to email filtering based on one-class Information Bottleneck (IB) method
in small training sets. When themes of emails are
changing continually, the available training set which is high-relevant to the
current theme will be small. Hence, we further show how to estimate the
learning algorithm and how to filter the spam in the small training sets.
First, In order to preserve classification accuracy and avoid over-fitting
while substantially reducing training set size, we consider the learning
framework as the solution of one-class centroid only averaged by highly positive emails, and second, we design
a simple binary classification model to filters spam by the comparison of
similarity between emails and centroids. Experimental results show that in
small training sets our method can significantly improve classification
accuracy compared with the currently popular methods, such as: Naive Bayes, AdaBoost
and SVM.
Keywords: IB method, one-class IB, anti-spam filter, Small training sets.
Received
September 5, 2014; accepted November 25, 2014
Metacognitive Awareness Assessment and Introductory Computer Programming Course Achievement at Unive
Metacognitive Awareness Assessment and Introductory
Computer Programming Course Achievement at University
Siti Rum and Maizatul Ismail
Faculty of Computer Science and Information Technology,
University of Malaya, Malaysia
Abstract: Computer programming is regarded as a difficult
skill to learn both by researchers and often by learners themselves.
Metacognition has been identified as an important factor to be a successful
learner in learning computer programming. Metacognitive in educational
psychology is generally described as monitoring and controlling activities of
one’s cognition. The researchers have examined the Metacognitive Awareness
Inventory (MAI) to identify how it relates to student academic achievement at
school and universities. In this research work, an empirical research is
conducted using the MAI inventory with the objective to examine the correlation
between the metacognitive awareness with the Grade Point Average (GPA) performance
of the introductory programming course at Universities in Malaysia. The
experiment result indicates a positive relationship between metacognitive
awareness with the learning success of introductory programming course at
Universities.
Keywords: Novice programmer, met cognitive, MAI, educational psychology,
introductory computer programming.
Received November 13, 2013; accepted December 16, 2014; Published online December 23, 2015
Multiple-View
Face Hallucination by a Novel Regression Analysis in Tensor Space
ParinyaSanguansat
Faculty
of Engineering and Technology,Panyapiwat Institute of Management,Thailand
Abstract:In
this paper, the novel multiple-view face hallucination method was proposed.
This method is reconstructed the high-resolution face images in various poses
(normal, up, down, left, and right) from a single low-resolution face image
within these poses. There are two steps in our proposed method. In the first
step, a high-resolution face image in the same view of the observation is
reconstructed by the position-patch face hallucination framework with the
improved Locally Linear Embedding (LLE), which the number of neighbours is
adaptive. In the second step, the reconstructed image is used to generate the
high-resolution of the other views by the novel tensor regression technique.
The experimental results on the well-known dataset show that the proposed method
can achieve the better quality image than the baseline methods.
Keywords:Face
hallucination, tensor regression, multiple views, super-resolution
Received January 6, 2014; accepted December 16, 2014; Published online December 23, 2015
The Refinement Check of Added Dynamic Diagrams
Based
on p-Calculus
Zhou Xiang1 and Shao Zhiqing2
1Qingdao
University, China
2East China University of Science and Technology,
China
Abstract: As
the semi-formal modeling
tool, UML has semantics defaults which may cause confusions or even mistakes in
refinement of models. p-calculus is a formal
specification based on process algebra, which can give strict semantics
description for system behaviors. We seek to clearly define the semantics of
refinement to a model through p- calculus and thus we are able to
propose a formal verification method of the refinement. Employing this method,
we can improve the efficiency of the consistency verification while decreasing
the mistakes in the refinement process.
Keywords: p-calculus; UML; sequence diagram;
statechart diagram; weak open bisimulation.
Received January 21, 2014; accepted December 22, 2014
A New Model for Software Inspection at the Requirements Analysis and Design Phases of Software Devel
A
New Model
for Software Inspection at the Requirements Analysis and Design Phases of
Software Development
Navid Taba and Siew Ow
Department of
Software Engineering, University of Malaya, Malaysia
Abstract: Software inspection models have been remarkable development
in over the past four decades, particularly in the field of automatic
inspection of software codes and electronic sessions. A small number of
improvements have been made in the field of system analysis and design. The
amount of using formal inspection model which is based on single check lists
and physical or electronic sessions shows the decrease in interest in it. As inspection, in
system analysis phase, is a man-cantered issue, inspectors support using
electronic tools will lead to higher efficiency of the inspection process. This
paper proposes a comprehensive web-based tool aimed to accelerating the
inspection process in the early phases of software development. In order to
evaluate the efficiency of the proposed tool, two case studies were conducted
to inspect the artifacts from six software projects of two software companies. Comparing
the statistics related to the defects detected using this tool with those
detected using the formal method shows the efficiency of the used tool.
Keywords: Software inspection, software test,
software engineering improvement, web-based solution, software inspection tool,
inspection metrics.
Received September 2, 2013; accepted September 29, 2014; Published online December 23, 2015
RPLB: A Replica Placement Algorithm in Data Grid with
Load Balancing
Kingsy Rajaretnam, Manimegalai Rajkumar, and Ranjith
Venkatesan
Department
of Computer Science and Engineering, Sri Ramakrishna Engineering College, India
Abstract: Data grid is an infrastructure
built based on internet which facilitates sharing and management of geographically
distributed data resources. Data sharing in data grids is enhanced through
dynamic data replication methodologies to reduce access latencies and bandwidth
consumption. Replica placement is to create and place duplicate copies of the
most needed file in beneficial locations in the data grid network. To reduce
the make span i.e., total job execution time, storage consumption and effective
network usage in data grids, a new method for replica placement is introduced. In
this proposed method, all the nodes in the same region are grouped together and
replica is placed in the highest degree and highest frequency node in the
region. The node to place replica should be load balanced in terms of access
and storage. The proposed dynamic Replica Placement algorithm with Load Balancing
(RPLB) is tested using OptorSim simulator, which is developed by European Data
Grid Projects. In this paper, two variants of the proposed algorithm RPLB, namely
RPLBfrequency and RPLBdegree are also presented. The
comparative analysis of all the three proposed algorithms is also presented in
this paper. A Graphical User Interface (GUI)
is designed as an interface to OptorSim to get all values for grid
configuration file, job configuration file and parameters configuration file. Simulation
results reveal that the performance of the proposed methodology is better in
terms of makespan, storage consumption and replication count when compared to the
existing algorithms in the literature.
Keywords: Replica
placement, load balancing, effective network usage, data grid, data replication.
Received June 17, 2013; accepted April 28, 2014
An Intelligent Water Drop Algorithm for
OptimizingTask Scheduling in Grid Environment
SornapandySelvarani1and
GangadharanSadhasivam2
1Department
of Information Technology, Tamilnadu College of Engineering, India
2Department
of Computer Science and Engineering, PSG College of Technology, India
Abstract: The goal of grid computing is to provide
powerful computing for complex scientific problems by utilizing and sharing
large scale resources available in the grid. Efficient scheduling algorithms
are needed to allocate suitable resources for each submitted task. So
scheduling is one of the most important issues for achieving high performance
computing in grid. This paper addresses
an approach for optimizing scheduling using a nature inspired Intelligent Water
Drops (IWD) algorithm. In the proposed approach IWD algorithm is adopted to
improve the performance of task scheduling in grid environment. The performance
of Ant Colony Optimization (ACO) algorithm for task scheduling is compared with
the proposed IWD approach and it is proved that task scheduling using IWD can
efficiently and effectively allocate tasks to suitable resources in the grid.
Keywords: grid computing, IWD, task scheduling, ACO.
Received January24, 2013; accepted March 19, 2014; Published online December 23, 2015
iHPProxy: Improving the Performance of HPProxy by
Adding Extra Hot-Points
Ponnusamy Pichamuthu1
and Karthikeyan Eswaramurthy2
1Department of Computer Science,
Bharathiar University, India
2Department of Computer Science, Government Arts
College, Udumalpet, Bharathiar University, India
Abstract: In recent years, the interest of Internet
users turned into viewing videos such as Video-on-Demand (VoD), online movies, online
sports, news, e-learning, etc., the researchers involved proxy caching with
replacement to provide immediate content delivery to the client on request. One
important aspect in the content delivery is continuous playability with random
seek even the client wants to watch the video from a new location by jumping
into that location. The continuous play is possible if the hit location is
cached already, otherwise a delay will occur. The researchers allowed a small
deviation from the desired location in the backward direction to reduce the
delay. Our earlier model, Hot-Point Proxy caching (HPPrxoy), also supports the
shift to the nearest cached Group Of Pictures (GOP) in the backward direction
to play immediately, but, in some cases the deviation was large. Hence, we
proposed a new model to provide a little deviation by adding extra hot-points
between existing sub-level hot-points. However, this mechanism additionally
consumes cache memory, it increases the byte-hit ratio, satisfies the user
requirement in random seek and provide better cache replacement.
Keywords: Proxy caching, shift distance, HPProxy, cache replacement, multimedia streaming, VoD.
Received May 9, 2013; accepted July 8, 2013; Published online December 23, 2015
Modified Bee Colony Optimization for the Selection of
Different Combination of Food Sources
Saravanamoorthi Moorthi
Department of Mathematics, Bannari Amman Institute of Technology,
India
Abstract:
There is a trend in the scientific community to model
and solve complex optimization process by employing natural metaphors. In this
area, Artificial Bee Colony optimization (ABC) tries to model natural behaviour
of real honeybees in food foraging. ABC algorithm is an optimization algorithm based
on the intelligent behaviour of honey bee swarm. In this work, ABC is used for
solving multivariable functions with different combinations of them. That is,
all the routes are identified to the bees and using all the possible
combinations, the outputs are measured. Based on the output the optimum value
is selected.
Keywords: ABC algorithm, optimization, benchmark functions.
Received February 20, 2013; accepted June 5, 2013; Published online December 23, 2015
An Adaptive Weighted Fuzzy Mean Filter
Kannan Kanagaraj
Department of
Mechanical Engineering, Kamaraj College of Engineering and Technology, India
Abstract: This research proposes an Adaptive Weighted Fuzzy Mean Filter (AWFMF) based on Cloud Model (CM) to remove the
salt and pepper noise in the digital images. Also, the performance of the
proposed filter is compared with existing variants of median and switching
filters using peak signal to noise ratio (PSNR) and quality index. The
proposed filter is able to remove salt and pepper noise even at 90% noise level
with good detail preservation.
Keywords: Image denoising, salt and pepper noise, CM.
Received January 21, 2013; accepted March 17, 2014; Published online December 23, 2015
Prediction of Part of Speech Tags for Punjabi using Support Vector
Machines
Dinesh Kumar1 and Gurpreet Josan2
1Department of Information Technology, DAV Institute of Engineering and Technology, India
2Department of Computer Science, Punjabi University, India
Abstract: Part-Of-Speech (POS) tagging
is a task of assigning the appropriate POS or lexical category to each word in
a natural language sentence. In this paper, we have worked on automated
annotation of POS tags for Punjabi. We have collected a corpus of around 27,000
words, which included the text from various stories, essays, day-to-day
conversations, poems etc., and divided these words into different size files
for training and testing purposes. In our approach, we have used Support Vector
Machine (SVM) for tagging Punjabi sentences. To the best of our knowledge, SVMs
have never been used for tagging Punjabi text. The result shows that SVM based
tagger has outperformed the existing taggers. In the existing POS taggers of
Punjabi, the accuracy of POS tagging for unknown words is less than that for
known words. But in our proposed tagger, high accuracy has been achieved for
unknown and ambiguous words. The average accuracy of our tagger is 89.86%,
which is better than the existing approaches.
Keywords: POS tagging, SVM,
feature set, vectorization, machine learning, tagger, punjabi, indian languages.
Received September 18, 2013; accepted February 28, 2014; Published online December 23, 2015
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