H.6.3.2. Feature evaluation and selection
1. 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.3.8. Natural Language Processing
2. 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

F.2.7. Optimization
3. 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

H.5. Image Processing and Computer Vision
4. 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
5. 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.6.5.2. Computer vision
6. 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

7. 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

8. 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. Pattern Recognition
9. 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.8. Document and Text Processing
10. 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

C.3. Software Engineering
11. 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

J.10.3. Financial
12. 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

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. 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

15. Chaotic-based Particle Swarm Optimization with Inertia Weight for Optimization Tasks

N. Mobaraki; R. Boostani; M. Sabeti

Volume 8, Issue 3 , Summer 2020, , Pages 303-312

Abstract
  Among variety of meta-heuristic population-based search algorithms, particle swarm optimization (PSO) with adaptive inertia weight (AIW) has been considered as a versatile optimization tool, which incorporates the experience of the whole swarm into the movement of particles. Although the exploitation ...  Read More

H.6.3.2. Feature evaluation and selection
16. 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