1 2251-6107 ICT Research Institute(ITRC) 118 Information Technology Design Investigation of a Modified HMSIW Leaky Wave Antenna Razavi Seyed Ali H. Neshati Mohammad 1 9 2014 6 3 1 6 02 10 2018 02 10 2018 In this paper, a new leaky wave antenna (LWA) is introduced. The proposed antenna radiates through a dielectric aperture created by half mode substrate integrated waveguide (HMSIW) technique. A sample antenna is designed and simulated and its radiation characteristics are investigated. It is illustrated that half conical radiation pattern is provided by the proposed antenna. The designed antenna is also fabricated and its radiation properties are measured. Results show that the proposed antenna has the advantages of wide bandwidth, enhanced scanning angle and high gain in addition to low profile, low fabrication cost, low weight. Radiation patterns of antenna at different frequencies are theoretically calculated and compared with simulated ones. Good agreement between simulated and calculated results proves the validity of the theory presented for the calculation of radiation patterns. Moreover, its common features including high directivity and beam steering capability which make it suitable for millimeter-wave applications.
119 Information Technology An Improved Parallel Genetic Algorithm for Optimal Sensor Placement of Wireless Sensor Networks Kolangari Sara Teshnehlab Mohammad 1 9 2014 6 3 7 13 02 10 2018 02 10 2018 The wireless sensor network has recently become an intensive research focus due to its potential applications many years. Sensor placement is one of the most important issues in wireless sensor networks. An efficient placement scheme can enhance the quality of monitoring in wireless sensor networks by increasing the coverage rate of interested area. This paper presents an efficient method based on parallel genetic algorithms to solve a sensor placement optimization problem. We modify the general master-slave parallel genetic algorithm to improve the convergence rate of this optimization method. The results indicate the effectiveness of the proposed method in comparison with genetic algorithm, general parallel genetic algorithm, and some well-known evolutionary algorithms. 120 Information Technology Binaural Speech Separation Using Binary and Ratio Time-Frequency Masks Mahmoodzadeh Azar Abutalebi Hamidreza Soltanian-Zadeh Hamid Sheikhzadeh Hamid 1 9 2014 6 3 15 24 02 10 2018 02 10 2018 In many speech applications, the target signal is corrupted by highly correlated noise sources. Separating desired speaker signals from the mixture is one of the most challenging research topics in speech signal processing. This paper proposes a binaural system combined with a monaural incoherent post processor for speech segregation. The proposed binaural system is based on spatial localization cues: Interaural Time Differences (ITD) and Interaural Intensity Differences (IID). A target speech is separated from interfering sounds by estimating time–frequency binary and ratio masks. The binary mask is estimated using the multi-level extension of the Otsu thresholding algorithm used in image segmentation. ITD and IID are important features for mask estimation in low and high frequencies, respectively. The ratio mask is estimated using the incoherent monaural speech separation system as the post processing stage. Systematic evaluations show that the proposed system can separate the target signal with acceptance quality. 121 Information Technology Analyzing Content-based Heuristics for Persian Web Spam Detection Rabbani Elahe Shakery Azadeh 1 9 2014 6 3 25 39 02 10 2018 02 10 2018 The rapid growth of web spam in the World Wide Web has motivated researchers to propose algorithms for combating web spam. Despite using these techniques, the search engines do not perform well in detecting Persian spam websites. In this paper, we analyze the effectiveness of many previously proposed content-based features on detecting Persian spam websites, and also present a number of new content-based features. As another approach, we explain and examine our Bag-Of-Spam-Words (BOSW) method to do web spam detection. In this method, we represent each document as a vector of specific words selected from a spam corpus. Finally, we apply a number of feature selection methods and use various kinds of classification algorithms to classify the Persian websites. For this purpose, we have created a dataset of Persian hosts. Our results show that using the BOSW method with the SVM classifier has the best performance in detecting Persian spam websites. 122 Information Technology A Virtual Research Management Enterprise Architecture Using Axiomatic Design Sharifi Ali Asosheh Abbas Sadeghi Masoomeh Dastranj Nasrin 1 9 2014 6 3 41 51 02 10 2018 02 10 2018 Development of virtual research management enterprise architecture (EA) can provide solutions to the current challenges of research management in academic institutions and create necessary capabilities to manage and control the flow of research process among individuals, groups, and institutes. As a new approach to organizational operation, virtual enterprises (VE) introduce new business models and management techniques. The aim of this study is to provide architecture for designing and developing virtual research management based on axiomatic design method. For this purpose, first the design framework has been developed by investigating theoretical principles and using content analysis method. In the next step, the components of research management architecture have been extracted based on proposed framework and using axiomatic design method. Finally by surveying experts, the proposed architecture is validated and its application in an Iranian academic institute has been studied as a case. Proposed architecture in this paper can be used in distributed and dynamic academic research environment. Proposing new methodology for research management enterprise architecture, integrating virtual organization concepts in enterprise architecture design, introducing a methodology for identifying research management system requirements, introducing key components in designing and developing research management based on virtual enterprise are innovation aspects of this research. 123 Information Technology A Review of the Distributed Methods for Large-Scale Social Network Analysis Kahani Mohsen Abrishami Saeid Zarrinkalam Fattane 1 9 2014 6 3 53 61 02 10 2018 02 10 2018 Social Network Analysis (SNA) is aimed at studying the structure of a social network, usually represented as a graph, in order to extract the hidden knowledge about the activities and relationships of the users. With exponential increase in the volume and velocity of the data created in today's social networks like Facebook and Twitter, a main requirement for social network analysis is employing computationally efficient algorithms and methods. Since sequential and centralized approaches are far from the desired scalability, a natural solution is to distribute graph of the network on a number of processing machines and perform the execution in parallel. In this paper, existing Works on distributed large-scale graph processing are reviewed in four categories regarding their computational model. It is concluded that none of the existing categories outperforms other ones significantly, and therefore no single category addresses the requirements of all different graph algorithms. This highlights the need to research on identifying the types of algorithms for which each category of the computational models is more suitable, and also on how to customize the model for the corresponding type. 124 Information Technology Phrase Alignments in Parallel Corpus Using Bootstrapping Approach Tavakoli Leila Faili Heshaam 1 9 2014 6 3 63 76 02 10 2018 02 10 2018 Word choice and word order problems are considered as fundamental barriers in statistical machine translation (SMT). These barriers are more pronounced in deficiencies of training corpus. Phrase-Based SMT has advantages in word choice and local word ordering process; so phrase alignment is effective in improving translation quality. In this paper, an approach for automatic alignment is proposed in which boosts up the machine translation quality. Since, alignment problem is more problematic with lack of training data, so we make corpus of phrase alignment with high precision. For this purpose, a novel phrase alignment approach in a bootstrapping manner is proposed. By bootstrapping on alignment model via using a number of features, the accuracy of the phrase table is improved iteratively. These features are based on the phrase table extracted from Moses, IBM Model 3 alignment probabilities, Google translator and fertility of candidates. Our experiments on English-Persian translation show an improvement about 4.17 BLEU points over the PB-SMT as baseline system.