Original/Review Paper C.3. Software Engineering
Evaluation of Classifiers in Software Fault-Proneness Prediction

F. Karimian; S. M. Babamir

Volume 5, Issue 2 , July 2017, Pages 149-167


  Reliability of software counts on its fault-prone modules. This means that the less software consists of fault-prone units the more we may trust it. Therefore, if we are able to predict the number of fault-prone modules of software, it will be possible to judge the software reliability. In predicting ...  Read More

Original/Review Paper H.3.15.3. Evolutionary computing and genetic algorithms
Winner Determination in Combinatorial Auctions using Hybrid Ant Colony Optimization and Multi-Neighborhood Local Search

M. B. Dowlatshahi; V. Derhami

Volume 5, Issue 2 , July 2017, Pages 169-181


  A combinatorial auction is an auction where the bidders have the choice to bid on bundles of items. The WDP in combinatorial auctions is the problem of finding winning bids that maximize the auctioneer’s revenue under the constraint that each item can be allocated to at most one bidder. The WDP ...  Read More

Original/Review Paper H.3.15.3. Evolutionary computing and genetic algorithms
A Hybrid MOEA/D-TS for Solving Multi-Objective Problems

Sh. Lotfi; F. Karimi

Volume 5, Issue 2 , July 2017, Pages 183-195


  In many real-world applications, various optimization problems with conflicting objectives are very common. In this paper we employ Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), a newly developed method, beside Tabu Search (TS) accompaniment to achieve a new manner for solving ...  Read More

Original/Review Paper H.4.6. Computational Geometry and Object Modeling
A New Ontology-Based Approach for Human Activity Recognition from GPS Data

A. Mousavi; A. Sheikh Mohammad Zadeh; M. Akbari; A. Hunter

Volume 5, Issue 2 , July 2017, Pages 197-210


  Mobile technologies have deployed a variety of Internet–based services via location based services. The adoption of these services by users has led to mammoth amounts of trajectory data. To use these services effectively, analysis of these kinds of data across different application domains is required ...  Read More

Original/Review Paper H.3.15.2. Computational neuroscience
An Emotion Recognition Approach based on Wavelet Transform and Second-Order Difference Plot of ECG

A. Goshvarpour; A. Abbasi; A. Goshvarpour

Volume 5, Issue 2 , July 2017, Pages 211-221


  Emotion, as a psychophysiological state, plays an important role in human communications and daily life. Emotion studies related to the physiological signals are recently the subject of many researches. In This study a hybrid feature based approach was proposed to examine affective states. To this effect, ...  Read More

Original/Review Paper H.5.11. Image Representation
Face Recognition using an Affine Sparse Coding approach

M. Nikpour; R. Karami; R. Ghaderi

Volume 5, Issue 2 , July 2017, Pages 223-234


  Sparse coding is an unsupervised method which learns a set of over-complete bases to represent data such as image and video. Sparse coding has increasing attraction for image classification applications in recent years. But in the cases where we have some similar images from different classes, such as ...  Read More

Original/Review Paper H.3. Artificial Intelligence
Ensemble Classification and Extended Feature Selection for Credit Card Fraud Detection

F. Fadaei Noghani; M. Moattar

Volume 5, Issue 2 , July 2017, Pages 235-243


  Due to the rise of technology, the possibility of fraud in different areas such as banking has been increased. Credit card fraud is a crucial problem in banking and its danger is over increasing. This paper proposes an advanced data mining method, considering both feature selection and decision cost ...  Read More

Original/Review Paper H.3. Artificial Intelligence
A Sensor-Based Scheme for Activity Recognition in Smart Homes using Dempster-Shafer Theory of Evidence

V. Ghasemi; A. Pouyan; M. Sharifi

Volume 5, Issue 2 , July 2017, Pages 245-258


  This paper proposes a scheme for activity recognition in sensor based smart homes using Dempster-Shafer theory of evidence. In this work, opinion owners and their belief masses are constructed from sensors and employed in a single-layered inference architecture. The belief masses are calculated using ...  Read More

Original/Review Paper H.3. Artificial Intelligence
Composite Kernel Optimization in Semi-Supervised Metric

T. Zare; M. T. Sadeghi; H. R. Abutalebi; J. Kittler

Volume 5, Issue 2 , July 2017, Pages 259-273


  Machine-learning solutions to classification, clustering and matching problems critically depend on the adopted metric, which in the past was selected heuristically. In the last decade, it has been demonstrated that an appropriate metric can be learnt from data, resulting in superior performance as compared ...  Read More

Original/Review Paper Document and Text Processing
English-Persian Plagiarism Detection based on a Semantic Approach

F. Safi-Esfahani; Sh. Rakian; M.H. Nadimi-Shahraki

Volume 5, Issue 2 , July 2017, Pages 275-284


  Plagiarism which is defined as “the wrongful appropriation of other writers’ or authors’ works and ideas without citing or informing them” poses a major challenge to knowledge spread publication. Plagiarism has been placed in four categories of direct, paraphrasing (rewriting), ...  Read More

Original/Review Paper H.3.7. Learning
Distributed Incremental Least Mean-Square for Parameter Estimation using Heterogeneous Adaptive Networks in Unreliable Measurements

M. Farhid; M. Shamsi; M. H. Sedaaghi

Volume 5, Issue 2 , July 2017, Pages 285-291


  Adaptive networks include a set of nodes with adaptation and learning abilities for modeling various types of self-organized and complex activities encountered in the real world. This paper presents the effect of heterogeneously distributed incremental LMS algorithm with ideal links on the quality of ...  Read More

Original/Review Paper H.6.4. Clustering
Improved COA with Chaotic Initialization and Intelligent Migration for Data Clustering

M. Lashkari; M. Moattar

Volume 5, Issue 2 , July 2017, Pages 293-305


  A well-known clustering algorithm is K-means. This algorithm, besides advantages such as high speed and ease of employment, suffers from the problem of local optima. In order to overcome this problem, a lot of studies have been done in clustering. This paper presents a hybrid Extended Cuckoo Optimization ...  Read More

Original/Review Paper H.6.4. Clustering
A Multi-Objective Approach to Fuzzy Clustering using ITLBO Algorithm

P. Shahsamandi Esfahani; A. Saghaei

Volume 5, Issue 2 , July 2017, Pages 307-317


  Data clustering is one of the most important areas of research in data mining and knowledge discovery. Recent research in this area has shown that the best clustering results can be achieved using multi-objective methods. In other words, assuming more than one criterion as objective functions for clustering ...  Read More

Research Note D.3. Data Storage Representations
Drought Monitoring and Prediction using K-Nearest Neighbor Algorithm

E. Fadaei-Kermani; G. A Barani; M. Ghaeini-Hessaroeyeh

Volume 5, Issue 2 , July 2017, Pages 319-325


  Drought is a climate phenomenon which might occur in any climate condition and all regions on the earth. Effective drought management depends on the application of appropriate drought indices. Drought indices are variables which are used to detect and characterize drought conditions. In this study, it ...  Read More

Original/Review Paper G.3.5. Systems
Fractional Modeling and Analysis of Buck Converter in CCM Mode Peration

A. Moshar Movahhed; H. Toossian Shandiz; Syed K. Hoseini Sani

Volume 5, Issue 2 , July 2017, Pages 327-335


  In this paper fractional order averaged model for DC/DC Buck converter in continues condition mode (CCM) operation is established. DC/DC Buck converter is one of the main components in the wind turbine system which is used in this research. Due to some practical restriction there weren’t exist ...  Read More