H.3. Artificial Intelligence
1. 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.3.15.1. Adaptive hypermedia
2. Hybrid Adaptive Educational Hypermedia ‎Recommender Accommodating User’s Learning ‎Style and Web Page Features‎

M. Tahmasebi; F. Fotouhi; M. Esmaeili

Volume 7, Issue 2 , Spring 2019, Pages 225-238

Abstract
  Personalized recommenders have proved to be of use as a solution to reduce the information overload ‎problem. Especially in Adaptive Hypermedia System, a recommender is the main module that delivers ‎suitable learning objects to learners. Recommenders suffer from the cold-start and the sparsity ...  Read More

B.3. Communication/Networking and Information Technology
3. Behavior-Based Online Anomaly Detection for a Nationwide Short Message Service

Z. Shaeiri; J. Kazemitabar; Sh. Bijani; M. Talebi

Volume 7, Issue 2 , Spring 2019, Pages 239-247

Abstract
  As fraudsters understand the time window and act fast, real-time fraud management systems becomes necessary in Telecommunication Industry. In this work, by analyzing traces collected from a nationwide cellular network over a period of a month, an online behavior-based anomaly detection system is provided. ...  Read More

H.6.2.2. Fuzzy set
4. Developing a Course Recommender by Combining Clustering and Fuzzy Association Rules

Sh. Asadi; Seyed M. b. Jafari; Z. Shokrollahi

Volume 7, Issue 2 , Spring 2019, Pages 249-262

Abstract
  Each semester, students go through the process of selecting appropriate courses. It is difficult to find information about each course and ultimately make decisions. The objective of this paper is to design a course recommender model which takes student characteristics into account to recommend appropriate ...  Read More

H.5. Image Processing and Computer Vision
5. A Novel Face Detection Method Based on Over-complete Incoherent Dictionary Learning

S. Mavaddati

Volume 7, Issue 2 , Spring 2019, Pages 263-278

Abstract
  In this paper, face detection problem is considered using the concepts of compressive sensing technique. This technique includes dictionary learning procedure and sparse coding method to represent the structural content of input images. In the proposed method, dictionaries are learned in such a way that ...  Read More

F.2.7. Optimization
6. Optimized Design of Nanohole Array-Based Plasmonic Color Filters Integrating Genetic Algorithm with FDTD Solutions

F. Fouladi Mahani; A. Mahanipour; A. Mokhtari

Volume 7, Issue 2 , Spring 2019, Pages 279-286

Abstract
  Recently, significant interest has been attracted by the potential use of aluminum nanostructures as plasmonic color filters to be great alternatives to the commercial color filters based on dye films or pigments. These color filters offer potential applications in LCDs, LEDs, color printing, CMOS image ...  Read More

H.5. Image Processing and Computer Vision
7. Compressed Image Hashing using Minimum Magnitude CSLBP

V. Patil; T. Sarode

Volume 7, Issue 2 , Spring 2019, Pages 287-297

Abstract
  Image hashing allows compression, enhancement or other signal processing operations on digital images which are usually acceptable manipulations. Whereas, cryptographic hash functions are very sensitive to even single bit changes in image. Image hashing is a sum of important quality features in quantized ...  Read More

H.6.2.5. Statistical
8. Outlier Detection for Support Vector Machine using Minimum Covariance Determinant Estimator

M. Mohammadi; M. Sarmad

Volume 7, Issue 2 , Spring 2019, Pages 299-309

Abstract
  The purpose of this paper is to identify the effective points on the performance of one of the important algorithm of data mining namely support vector machine. The final classification decision has been made based on the small portion of data called support vectors. So, existence of the atypical observations ...  Read More

H.3.8. Natural Language Processing
9. Improvement of Chemical Named Entity Recognition through Sentence-based Random Under-sampling and Classifier Combination

A. Akkasi; E. Varoglu

Volume 7, Issue 2 , Spring 2019, Pages 311-319

Abstract
  Chemical Named Entity Recognition (NER) is the basic step for consequent information extraction tasks such as named entity resolution, drug-drug interaction discovery, extraction of the names of the molecules and their properties. Improvement in the performance of such systems may affects the quality ...  Read More

H.3.2.6. Games and infotainment
10. An Adaptive Learning Game for Autistic Children using Reinforcement Learning and Fuzzy Logic

A.H. Khabbaz; A. Pouyan; M. Fateh; V. Abolghasemi

Volume 7, Issue 2 , Spring 2019, Pages 321-329

Abstract
  This paper, presents an adapted serious game for rating social ability in children with autism spectrum disorder (ASD). The required measurements are obtained by challenges of the proposed serious game. The proposed serious game uses reinforcement learning concepts for being adaptive. It is based on ...  Read More

B.3. Communication/Networking and Information Technology
11. Analyzing Customers of South Khorasan Telecommunication Company with Expansion of RFM to LRFM Model

V. Babaiyan; Seyyede A. Sarfarazi

Volume 7, Issue 2 , Spring 2019, Pages 331-340

Abstract
  Telecommunication Companies use data mining techniques to maintain good relationships with their existing customers and attract new customers and identifying profitable/unprofitable customers. Clustering leads to better understanding of customer and its results can be used to definition and decision-making ...  Read More

12. A New Single-Display Intelligent Adaptive Interface for Controlling a Group of UAVs

M. Ilbeygi; M.R. Kangavari

Volume 7, Issue 2 , Spring 2019, Pages 341-353

Abstract
  The increasing use of unmanned aerial vehicles (UAVs) or drones in different civil and military operations has attracted attention of many researchers and science communities. One of the most notable challenges in this field is supervising and controlling a group or a team of UAVs by a single user. Thereupon, ...  Read More