H.5. Image Processing and Computer Vision
1. 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


  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.5.11. Image Representation
2. Image Restoration by Variable Splitting based on Total Variant Regularizer

E. Sahragard; H. Farsi; S. Mohammadzadeh

Volume 6, Issue 1 , Winter 2018, Pages 13-33


  The aim of image restoration is to obtain a higher quality desired image from a degraded image. In this strategy, an image inpainting method fills the degraded or lost area of the image by appropriate information. This is performed in such a way so that the obtained image is undistinguishable for a casual ...  Read More

H.5. Image Processing and Computer Vision
3. Automatic Optic Disc Center and Boundary Detection in Color Fundus Images

F. Abdali-Mohammadi; A. Poorshamam

Volume 6, Issue 1 , Winter 2018, Pages 35-46


  Accurately detection of retinal landmarks, like optic disc, is an important step in the computer aided diagnosis frameworks. This paper presents an efficient method for automatic detection of the optic disc’s center and estimating its boundary. The center and initial diameter of optic disc are ...  Read More

I. Computer Applications
4. Color Reduction in Hand-drawn Persian Carpet Cartoons before Discretization using image segmentation and finding edgy regions

M. Fateh; E. Kabir

Volume 6, Issue 1 , Winter 2018, Pages 47-58


  In this paper, we present a method for color reduction of Persian carpet cartoons that increases both speed and accuracy of editing. Carpet cartoons are in two categories: machine-printed and hand-drawn. Hand-drawn cartoons are divided into two groups: before and after discretization. The purpose of ...  Read More

F.2.7. Optimization
5. A Hybrid Meta-Heuristic Algorithm based on Imperialist Competition Algorithm

R. Roustaei; F. Yousefi Fakhr

Volume 6, Issue 1 , Winter 2018, Pages 59-67


  The human has always been to find the best in all things. This Perfectionism has led to the creation of optimization methods. The goal of optimization is to determine the variables and find the best acceptable answer Due to the limitations of the problem, So that the objective function is minimum or ...  Read More

H.3.2.5. Environment
6. Ensemble of M5 Model Tree Based Modelling of Sodium Adsorption Ratio

M. T. Sattari; M. Pal; R. Mirabbasi; J. Abraham

Volume 6, Issue 1 , Winter 2018, Pages 69-78


  This work reports the results of four ensemble approaches with the M5 model tree as the base regression model to anticipate Sodium Adsorption Ratio (SAR). Ensemble methods that combine the output of multiple regression models have been found to be more accurate than any of the individual models making ...  Read More

A.1. General
7. Competitive Intelligence Text Mining: Words Speak

A. Zarei; M. Maleki; D. Feiz; M. A. Siahsarani kojuri

Volume 6, Issue 1 , Winter 2018, Pages 79-92


  Competitive intelligence (CI) has become one of the major subjects for researchers in recent years. The present research is aimed to achieve a part of the CI by investigating the scientific articles on this field through text mining in three interrelated steps. In the first step, a total of 1143 articles ...  Read More

H.3.2.2. Computer vision
8. Camera Pose Estimation in Unknown Environments using a Sequence of Wide-Baseline Monocular Images

Seyyed A. Hoseini; P. Kabiri

Volume 6, Issue 1 , Winter 2018, Pages 93-103


  In this paper, a feature-based technique for the camera pose estimation in a sequence of wide-baseline images has been proposed. Camera pose estimation is an important issue in many computer vision and robotics applications, such as, augmented reality and visual SLAM. The proposed method can track captured ...  Read More

H.5.10. Applications
9. A case study for application of fuzzy inference and data mining in structural health monitoring

S. Shoorabi Sani

Volume 6, Issue 1 , Winter 2018, Pages 105-120


  In this study, a system for monitoring the structural health of bridge deck and predicting various possible damages to this section was designed based on measuring the temperature and humidity with the use of wireless sensor networks, and then it was implemented and investigated. A scaled model of a ...  Read More

H.3.2.5. Environment
10. Multi-Output Adaptive Neuro-Fuzzy Inference System for Prediction of Dissolved Metal Levels in Acid Rock Drainage: a Case Study

H. Fattahi; A. Agah; N. Soleimanpourmoghadam

Volume 6, Issue 1 , Winter 2018, Pages 121-132


  Pyrite oxidation, Acid Rock Drainage (ARD) generation, and associated release and transport of toxic metals are a major environmental concern for the mining industry. Estimation of the metal loading in ARD is a major task in developing an appropriate remediation strategy. In this study, an expert system, ...  Read More

H.3. Artificial Intelligence
11. BQIABC: A new Quantum-Inspired Artificial Bee Colony Algorithm for Binary Optimization Problems

F. Barani; H. Nezamabadi-pour

Volume 6, Issue 1 , Winter 2018, Pages 133-143


  Artificial bee colony (ABC) algorithm is a swarm intelligence optimization algorithm inspired by the intelligent behavior of honey bees when searching for food sources. The various versions of the ABC algorithm have been widely used to solve continuous and discrete optimization problems in different ...  Read More

H.3.11. Vision and Scene Understanding
12. Graph-based Visual Saliency Model using Background Color

Sh. Foolad; A. Maleki

Volume 6, Issue 1 , Winter 2018, Pages 145-156


  Visual saliency is a cognitive psychology concept that makes some stimuli of a scene stand out relative to their neighbors and attract our attention. Computing visual saliency is a topic of recent interest. Here, we propose a graph-based method for saliency detection, which contains three stages: pre-processing, ...  Read More

C.1. General
13. Intrusion Detection based on a Novel Hybrid Learning Approach

L. khalvati; M. Keshtgary; N. Rikhtegar

Volume 6, Issue 1 , Winter 2018, Pages 157-162


  Information security and Intrusion Detection System (IDS) plays a critical role in the Internet. IDS is an essential tool for detecting different kinds of attacks in a network and maintaining data integrity, confidentiality and system availability against possible threats. In this paper, a hybrid approach ...  Read More

H.6.4. Clustering
14. Grouping Objects to Homogeneous Classes Satisfying Requisite Mass

M. Manteqipour; A.R. Ghaffari Hadigheh; R. Mahmoodvand; A. Safari

Volume 6, Issue 1 , Winter 2018, Pages 163-175


  Grouping datasets plays an important role in many scientific researches. Depending on data features and applications, different constrains are imposed on groups, while having groups with similar members is always a main criterion. In this paper, we propose an algorithm for grouping the objects with random ...  Read More

H.3.2.15. Transportation
15. New Approaches to Analyze Gasoline Rationing

S. Mostafaei; H. Ganjavi; R. Ghodsi

Volume 6, Issue 1 , Winter 2018, Pages 177-190


  In this paper, the relation among factors in the road transportation sector from March, 2005 to March, 2011 is analyzed. Most of the previous studies have economical point of view on gasoline consumption. Here, a new approach is proposed in which different data mining techniques are used to extract meaningful ...  Read More

F.2.7. Optimization
16. Chaotic Genetic Algorithm based on Explicit Memory with a new Strategy for Updating and Retrieval of Memory in Dynamic Environments

M. Mohammadpour; H. Parvin; M. Sina

Volume 6, Issue 1 , Winter 2018, Pages 191-205


  Many of the problems considered in optimization and learning assume that solutions exist in a dynamic. Hence, algorithms are required that dynamically adapt with the problem’s conditions and search new conditions. Mostly, utilization of information from the past allows to quickly adapting changes ...  Read More

F.2.7. Optimization
17. A Gravitational Search Algorithm-Based Single-Center of Mass Flocking Control for Tracking Single and Multiple Dynamic Targets for Parabolic Trajectories in Mobile Sensor Networks

E. Khodayari; V. Sattari-Naeini; M. Mirhosseini

Volume 6, Issue 1 , Winter 2018, Pages 207-217


  Developing optimal flocking control procedure is an essential problem in mobile sensor networks (MSNs). Furthermore, finding the parameters such that the sensors can reach to the target in an appropriate time is an important issue. This paper offers an optimization approach based on metaheuristic methods ...  Read More

H.3. Artificial Intelligence
18. FDiBC: A Novel Fraud Detection Method in Bank Club based on Sliding Time and Scores Window

Seyed M. H. Hasheminejad; Z. Salimi

Volume 6, Issue 1 , Winter 2018, Pages 219-231


  One of the recent strategies for increasing the customer’s loyalty in banking industry is the use of customers’ club system. In this system, customers receive scores on the basis of financial and club activities they are performing, and due to the achieved points, they get credits from the ...  Read More