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

2. 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

H.5. Image Processing and Computer Vision
3. Image authentication using LBP-based perceptual image hashing

R. Davarzani; S. Mozaffari; Kh. Yaghmaie

Volume 3, Issue 1 , Winter 2015, Pages 21-30

Abstract
  Feature extraction is a main step in all perceptual image hashing schemes in which robust features will led to better results in perceptual robustness. Simplicity, discriminative power, computational efficiency and robustness to illumination changes are counted as distinguished properties of Local Binary ...  Read More

4. Feature selection using genetic algorithm for classification of schizophrenia using fMRI data

Hossein Shahamat; Ali A. Pouyan

Volume 3, Issue 1 , Winter 2015, Pages 30-37

Abstract
  In this paper we propose a new method for classification of subjects into schizophrenia and control groups using functional magnetic resonance imaging (fMRI) data. In the preprocessing step, the number of fMRI time points is reduced using principal component analysis (PCA). Then, independent component ...  Read More

Timing analysis
5. Fuzzy clustering of time series data: A particle swarm optimization approach

Z. Izakian; M. Mesgari

Volume 3, Issue 1 , Winter 2015, Pages 39-46

Abstract
  With rapid development in information gathering technologies and access to large amounts of data, we always require methods for data analyzing and extracting useful information from large raw dataset and data mining is an important method for solving this problem. Clustering analysis as the most commonly ...  Read More

B.3. Communication/Networking and Information Technology
6. FDMG: Fault detection method by using genetic algorithm in clustered wireless sensor networks

A. Ghaffari; S. Nobahary

Volume 3, Issue 1 , Winter 2015, Pages 47-57

Abstract
  Wireless sensor networks (WSNs) consist of a large number of sensor nodes which are capable of sensing different environmental phenomena and sending the collected data to the base station or Sink. Since sensor nodes are made of cheap components and are deployed in remote and uncontrolled environments, ...  Read More

C.3. Software Engineering
7. Method integration: An approach to develop agent oriented methodologies

E. Ghandehari; F. Saadatjoo; M. A. Zare Chahooki

Volume 3, Issue 1 , Winter 2015, Pages 59-76

Abstract
  Agent oriented software engineering (AOSE) is an emerging field in computer science  and  proposes some systematic ideas for multi agent systems analysis, implementation and maintenance. Despite the various methodologies introduced in the agent-oriented software engineering, the main challenges ...  Read More

C. Software/Software Engineering
8. Formal approach on modeling and predicting of software system security: Stochastic petri net

H. Motameni

Volume 3, Issue 1 , Winter 2015, Pages 77-83

Abstract
  To evaluate and predict component-based software security, a two-dimensional model of software security is proposed by Stochastic Petri Net in this paper. In this approach, the software security is modeled by graphical presentation ability of Petri nets, and the quantitative prediction is provided by ...  Read More

I.3.7. Engineering
9. Evaluation of liquefaction potential based on CPT results using C4.5 decision tree

A. Ardakani; V. R. Kohestani

Volume 3, Issue 1 , Winter 2015, Pages 85-92

Abstract
  The prediction of liquefaction potential of soil due to an earthquake is an essential task in Civil Engineering. The decision tree is a tree structure consisting of internal and terminal nodes which process the data to ultimately yield a classification. C4.5 is a known algorithm widely used to design ...  Read More

F.2.2. Interpolation
10. A Block-Wise random sampling approach: Compressed sensing problem

V. Abolghasemi; S. Ferdowsi; S. Sanei

Volume 3, Issue 1 , Winter 2015, Pages 93-100

Abstract
  The focus of this paper is to consider the compressed sensing problem. It is stated that the compressed sensing theory, under certain conditions, helps relax the Nyquist sampling theory and takes smaller samples. One of the important tasks in this theory is to carefully design measurement matrix (sampling ...  Read More

F.2.7. Optimization
11. Optimal adaptive leader-follower consensus of linear multi-agent systems: Known and unknown dynamics

F. Tatari; M. B. Naghibi-Sistani

Volume 3, Issue 1 , Winter 2015, Pages 101-111

Abstract
  In this paper, the optimal adaptive leader-follower consensus of linear continuous time multi-agent systems is considered. The error dynamics of each player depends on its neighbors’ information. Detailed analysis of online optimal leader-follower consensus under known and unknown dynamics is presented. ...  Read More

A.2. Control Structures and Microprogramming
12. Discrete time robust control of robot manipulators in the task space using adaptive fuzzy estimator

M. M. Fateh; S. Azargoshasb

Volume 3, Issue 1 , Winter 2015, Pages 113-120

Abstract
  This paper presents a discrete-time robust control for electrically driven robot manipulators in the task space. A novel discrete-time model-free control law is proposed by employing an adaptive fuzzy estimator for the compensation of the uncertainty including model uncertainty, external disturbances ...  Read More