1. QoS-Based web service composition based on genetic algorithm

Mohammad AllamehAmiri; Vali Derhami; Mohammad Ghasemzadeh

Volume 1, Issue 2 , Summer 2013, , Pages 63-73

Abstract
  Quality of service (QoS) is an important issue in the design and management of web service composition. QoS in web services consists of various non-functional factors, such as execution cost, execution time, availability, successful execution rate, and security. In recent years, the number of available ...  Read More

2. On improving APIT algorithm for better localization in WSN

Seyed M. Hosseinirad; M. Niazi; J Pourdeilami; S. K. Basu; A. A. Pouyan

Volume 2, Issue 2 , Summer 2014, , Pages 97-104

Abstract
  In Wireless Sensor Networks (WSNs), localization algorithms could be range-based or range-free. The Approximate Point in Triangle (APIT) is a range-free approach. We propose modification of the APIT algorithm and refer as modified-APIT. We select suitable triangles with appropriate distance between anchors ...  Read More

H.6.3.2. Feature evaluation and selection
3. Feature reduction of hyperspectral images: Discriminant analysis and the first principal component

Maryam Imani; Hassan Ghassemian

Volume 3, Issue 1 , Winter 2015, , Pages 1-9

Abstract
  When the number of training samples is limited, feature reduction plays an important role in classification of hyperspectral images. In this paper, we propose a supervised feature extraction method based on discriminant analysis (DA) which uses the first principal component (PC1) to weight the scatter ...  Read More

H.6. Pattern Recognition
4. IRDDS: Instance reduction based on Distance-based decision surface

J. Hamidzadeh

Volume 3, Issue 2 , Summer 2015, , Pages 121-130

Abstract
  In instance-based learning, a training set is given to a classifier for classifying new instances. In practice, not all information in the training set is useful for classifiers. Therefore, it is convenient to discard irrelevant instances from the training set. This process is known as instance reduction, ...  Read More

H.3.8. Natural Language Processing
5. An improved joint model: POS tagging and dependency parsing

A. Pakzad; B. Minaei Bidgoli

Volume 4, Issue 1 , Winter 2016, , Pages 1-8

Abstract
  Dependency parsing is a way of syntactic parsing and a natural language that automatically analyzes the dependency structure of sentences, and the input for each sentence creates a dependency graph. Part-Of-Speech (POS) tagging is a prerequisite for dependency parsing. Generally, dependency parsers do ...  Read More

H.8. Document and Text Processing
6. Plagiarism checker for Persian (PCP) texts using hash-based tree representative fingerprinting

Sh. Rafieian; A. Baraani dastjerdi

Volume 4, Issue 2 , Summer 2016, , Pages 125-133

Abstract
  With due respect to the authors’ rights, plagiarism detection, is one of the critical problems in the field of text-mining that many researchers are interested in. This issue is considered as a serious one in high academic institutions. There exist language-free tools which do not yield any reliable ...  Read More

F.2.7. Optimization
7. Optimization of fuzzy membership functions via PSO and GA with application to quad rotor

B. Safaee; S. K. Kamaleddin Mousavi Mashhadi

Volume 5, Issue 1 , Winter 2017, , Pages 1-10

Abstract
  Quad rotor is a renowned underactuated Unmanned Aerial Vehicle (UAV) with widespread military and civilian applications. Despite its simple structure, the vehicle suffers from inherent instability. Therefore, control designers always face formidable challenge in stabilization and control goal. In this ...  Read More

C.3. Software Engineering
8. Evaluation of Classifiers in Software Fault-Proneness Prediction

F. Karimian; S. M. Babamir

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

Abstract
  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

H.5. Image Processing and Computer Vision
9. Density-Based Histogram Partitioning and Local Equalization for Contrast Enhancement of Images

M. Shakeri; M.H. Dezfoulian; H. Khotanlou

Volume 6, Issue 1 , Winter 2018, , Pages 1-12

Abstract
  Histogram Equalization technique is one of the basic methods in image contrast enhancement. Using this method, in the case of images with uniform gray levels (with narrow histogram), causes loss of image detail and the natural look of the image. To overcome this problem and to have a better image contrast ...  Read More

H.5. Image Processing and Computer Vision
10. Multi-Focus Image Fusion in DCT Domain using Variance and Energy of Laplacian and Correlation Coefficient for Visual Sensor Networks

M. Amin-Naji; A. Aghagolzadeh

Volume 6, Issue 2 , Summer 2018, , Pages 233-250

Abstract
  The purpose of multi-focus image fusion is gathering the essential information and the focused parts from the input multi-focus images into a single image. These multi-focus images are captured with different depths of focus of cameras. A lot of multi-focus image fusion techniques have been introduced ...  Read More

H.5. Image Processing and Computer Vision
11. Pedestrian Detection in Infrared Outdoor Images Based on Atmospheric Situation Estimation

Seyed M. Ghazali; Y. Baleghi

Volume 7, Issue 1 , Winter 2019, , Pages 1-16

Abstract
  Observation in absolute darkness and daytime under every atmospheric situation is one of the advantages of thermal imaging systems. In spite of increasing trend of using these systems, there are still lots of difficulties in analysing thermal images due to the variable features of pedestrians and atmospheric ...  Read More

H.6.3.2. Feature evaluation and selection
12. MLIFT: Enhancing Multi-label Classifier with Ensemble Feature Selection

Sh kashef; H. Nezamabadi-pour

Volume 7, Issue 3 , Summer 2019, , Pages 355-365

Abstract
  Multi-label classification has gained significant attention during recent years, due to the increasing number of modern applications associated with multi-label data. Despite its short life, different approaches have been presented to solve the task of multi-label classification. LIFT is a multi-label ...  Read More

H.3. Artificial Intelligence
13. MEFUASN: A Helpful Method to Extract Features using Analyzing Social Network for Fraud Detection

Z. Karimi Zandian; M. R. Keyvanpour

Volume 7, Issue 2 , Spring 2019, , Pages 213-224

Abstract
  Fraud detection is one of the ways to cope with damages associated with fraudulent activities that have become common due to the rapid development of the Internet and electronic business. There is a need to propose methods to detect fraud accurately and fast. To achieve to accuracy, fraud detection methods ...  Read More

H.5. Image Processing and Computer Vision
14. Morphological Exudate Detection in Retinal Images using PCA-based Optic Disc Removal

J. Darvish; M. Ezoji

Volume 7, Issue 4 , Autumn 2019, , Pages 487-493

Abstract
  Diabetic retinopathy lesion detection such as exudate in fundus image of retina can lead to early diagnosis of the disease. Retinal image includes dark areas such as main blood vessels and retinal tissue and also bright areas such as optic disk, optical fibers and lesions e.g. exudate. In this paper, ...  Read More

H.6.5.2. Computer vision
15. Camera Arrangement in Visual 3D Systems using Iso-disparity Model to Enhance Depth Estimation Accuracy

M. Karami; A. Moosavie nia; M. Ehsanian

Volume 8, Issue 1 , Winter 2020, , Pages 1-12

Abstract
  In this paper we address the problem of automatic arrangement of cameras in a 3D system to enhance the performance of depth acquisition procedure. Lacking ground truth or a priori information, a measure of uncertainty is required to assess the quality of reconstruction. The mathematical model of iso-disparity ...  Read More

J.10.3. Financial
16. Credit Card Fraud Detection using Data mining and Statistical Methods

S. Beigi; M.R. Amin Naseri

Volume 8, Issue 2 , Spring 2020, , Pages 149-160

Abstract
  Due to today’s advancement in technology and businesses, fraud detection has become a critical component of financial transactions. Considering vast amounts of data in large datasets, it becomes more difficult to detect fraud transactions manually. In this research, we propose a combined method ...  Read More

17. Outlier Detection in Wireless Sensor Networks Using Distributed Principal Component Analysis

Mohammad Ahmadi Livani; mahdi Abadi; Meysam Alikhany; Meisam Yadollahzadeh Tabari

Volume 1, Issue 1 , Winter 2013, , Pages 1-11

Abstract
  Detecting anomalies is an important challenge for intrusion detection and fault diagnosis in wireless sensor networks (WSNs). To address the problem of outlier detection in wireless sensor networks, in this paper we present a PCA-based centralized approach and a DPCA-based distributed energy-efficient ...  Read More

18. Delay-dependent stability for transparent bilateral teleoperation system: an LMI approach

Alireza Khosravi; Alireza Alfi; Amir Roshandel

Volume 1, Issue 2 , Summer 2013, , Pages 75-87

Abstract
  There are two significant goals in teleoperation systems: Stability and performance. This paper introduces an LMI-based robust control method for bilateral transparent teleoperation systems in presence of model mismatch. The uncertainties in time delay in communication channel, task environment and model ...  Read More

19. Efficiency of a multi-objective imperialist competitive algorithm: A bi-objective location-routing-inventory problem with probabilistic routes

N. Nekooghadirli; R. Tavakkoli-Moghaddam; V.R. Ghezavati

Volume 2, Issue 2 , Summer 2014, , Pages 105-112

Abstract
  An integrated model considers all parameters and elements of different deficiencies in one problem. This paper presents a new integrated model of a supply chain that simultaneously considers facility location, vehicle routing and inventory control problems as well as their interactions in one problem, ...  Read More

20. Impact of linear dimensionality reduction methods on the performance of anomaly detection algorithms in hyperspectral images

Mohsen Zare-Baghbidi; Saeid Homayouni; Kamal Jamshidi; A. R. Naghsh-Nilchi

Volume 3, Issue 1 , Winter 2015, , Pages 11-20

Abstract
  Anomaly Detection (AD) has recently become an important application of hyperspectral images analysis. The goal of these algorithms is to find the objects in the image scene which are anomalous in comparison to their surrounding background. One way to improve the performance and runtime of these algorithms ...  Read More

F.1. General
21. Data sanitization in association rule mining based on impact factor

A. Telikani; A. Shahbahrami; R. Tavoli

Volume 3, Issue 2 , Summer 2015, , Pages 131-140

Abstract
  Data sanitization is a process that is used to promote the sharing of transactional databases among organizations and businesses, it alleviates concerns for individuals and organizations regarding the disclosure of sensitive patterns. It transforms the source database into a released database so that ...  Read More

H.3.2.2. Computer vision
22. Isolated Persian/Arabic handwriting characters: Derivative projection profile features, implemented on GPUs

M. Askari; M. Asadi; A. Asilian Bidgoli; H. Ebrahimpour

Volume 4, Issue 1 , Winter 2016, , Pages 9-17

Abstract
  For many years, researchers have studied high accuracy methods for recognizing the handwriting and achieved many significant improvements. However, an issue that has rarely been studied is the speed of these methods. Considering the computer hardware limitations, it is necessary for these methods to ...  Read More

F.4.4. Experimental design
23. Application of statistical techniques and artificial neural network to estimate force from sEMG signals

V. Khoshdel; A. R Akbarzadeh

Volume 4, Issue 2 , Summer 2016, , Pages 135-141

Abstract
  This paper presents an application of design of experiments techniques to determine the optimized parameters of artificial neural network (ANN), which are used to estimate force from Electromyogram (sEMG) signals. The accuracy of ANN model is highly dependent on the network parameters settings. There ...  Read More

A.1. General
24. Sub-transmission sub-station expansion planning based on bacterial foraging optimization algorithm

H. Kiani Rad; Z. Moravej

Volume 5, Issue 1 , Winter 2017, , Pages 11-20

Abstract
  In recent years, significant research efforts have been devoted to the optimal planning of power systems. Substation Expansion Planning (SEP) as a sub-system of power system planning consists of finding the most economical solution with the optimal location and size of future substations and/or feeders ...  Read More

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

M. B. Dowlatshahi; V. Derhami

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

Abstract
  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