1 2251-6107 ICT Research Institute(ITRC) 133 Information Technology An Opportunistic Cooperative Approach for Dynamic Spectrum Leasing in Cognitive Radio Networks Ghamari Adian Mehdi Aghaeinia Hassan 1 3 2014 6 1 1 9 06 10 2018 06 10 2018 Spectrum leasing issue is investigated by an opportunistic cooperative approach. The scenario includes a multi-antenna primary user (working as a Base Station) and a number of singleantenna primary and cognitive radio users (CR users). The core aim of this paper is to maximize the data rate in the downlink, from base station (PU BS) to the desired primary user (PU RX), taking advantage of the cooperation of opportunistically selected CR users. Cooperating CR users will enjoy the benefits of transmitting to their intended CR receivers in a portion of time, allocated by PU BS. The main contribution of this work is proposing the opportunistic cooperative approach. Meanwhile the interference imposed on other PUs, due to cooperation of selected CR users, is removed. Moreover, as the opportunistically selected CR users form a virtual antenna array, it becomes feasible to utilize zero-forcing beamforming to remove the interference on other PUs.
134 Information Technology A Cross Layer Method for Efficient Video Delivery Based on TPGF Routing in WMSN Sheikh Bagheri Arjmand Mehdi Khansari Mohammad 1 3 2014 6 1 11 22 06 10 2018 06 10 2018 In this paper, we propose a QoS-aware method for multimedia streaming that uses cross-layer information (application layer and physical layer) in Wireless Multimedia Sensor Networks (WMSNs). Our goal is to use cross­layer information to route video packets efficiently and deliver a higher quality video in streaming applications. Our QoS-Aware Multi-Path Selection (QAMPS) method is hased on multi-path multi-priority selection algorithm that uses Two-Phase geographic Greedy forwarding (TPGF) as a routing algorithm. The proposed method improves QoS by splitting video streams into I-frames, P-frames and B-frames in the application layer and passes them to the network layer for routing packets in three different classes. The differentiation is based on Bit Error Rate (BER) and delay of the paths. These parameters determine the best paths for sending I, P and B-frame streams separately. Finally, the comparison of QAMPS with Context-Aware Multi-path Selection (CAMS) scheme that sends video stream without classification of frames shows a better quality. The proposed method has better PSNR and decreases the frame loss ratio by about 20 percent in average compared to CAMS. 135 Information Technology A Survey of Advanced Search Techniques in Unstructured P2P Networks Sharifkhani Fatemeh Pakravan Mohammad Reza 1 3 2014 6 1 23 31 06 10 2018 06 10 2018 In unstructured peer to peer networks, any peer might share any file with other nodes. This uncertainty of where a specific file is located, makes the search problem in unstructured networks complicated. So far, many search algorithms have been proposed which try to maximize the success rate of an initiated query and minimize the imposed cost of search. In this paper, we survey newly introduced approaches to overcome search process problems. By reviewing these strategies and comparing them with previous search methods, we propose a new classification of informed search algorithms and we conclude that regarding this classification, informed search algorithms should be applied in less dynamic networks while blind search algorithms can be used in small networks. We believe that this taxonomy and the new classification can be useful as a guide for future search algorithm design. 136 Information Technology Improved Mapping Algorithms Performance in NoCs Design Based on Cellular Learning Automata Keley Mohammad Bagher Khademzadeh Ahmad Hosseinzadeh Mehdi 1 3 2014 6 1 33 42 06 10 2018 06 10 2018 NOC technology is a solution to cover the communication challenges of complex systems. The important note in the matter of application mapping for those of NoCs who are based on mesh architecture is their NP-hard problem. Also some methods have been proposed trying to overcome the mentioned problem. A low complexity mapping algorithm cannot present the optimal mapping for all applications. Then, adding an optimization phase to mapping algorithms can have an impact on their performance. This study presents an optimization phase based on Cellular Learning Automata to achieve this goal. To evaluate the proposed algorithm, we compare mapping algorithm of Nmap, CastNet, and Onyx before and after optimization. Mathematical analysis and simulation of mapping algorithms for five real applications shows that using the proposed algorithm optimizes efficiency in mapping algorithms. 137 Information Technology Web Page Streams and Relevance Propagation for Topic Distillation Golshani Mohammad Amin Zareh Bidoki Ali Mohammad 1 3 2014 6 1 43 54 06 10 2018 06 10 2018 Over the past decade, several studies in field of relevance propagation models have been proposed to improve quality of web search, which include hyperlink-based score propagation, hyperlinkbased term propagation and popularity-based relevance propagation models; however, all of them have used low precision content similarity functions in the propagation process and their throughputs are not entirely satisfactory. In this paper, two stream-based content similarity functions that could be used to derive new relevance propagation models were introduced. In the proposed content similarity functions, the web page was split to different streams with different degrees of importance and the text of each web page was divided between these streams. To evaluate the proposed relevance propagation models, Letor 3.0 (including two standard web test collections) was used in the experiments. It was concluded that splitting web pages as different streams could provide significant improvement in relevance propagation models. 138 Information Technology Learning to Exploit Different Translation Resources for Cross Language Information Retrieval Azarbonyad Hosein Shakery Azadeh Faili Heshaam 1 3 2014 6 1 55 68 06 10 2018 06 10 2018 One of the important factors that affects the performance of Cross Language Information Retrieval(CLIR) is the quality of translations being employed in CLIR. In order to improve the quality of translations, it is important to exploit available resources efficiently. Employing different translation resources with different characteristics has many challenges. In this paper, we propose a method for exploiting available translation resources simultaneously. This method employs Learning to Rank(LTR) for exploiting different translation resources. To apply LTR methods for query translation, we define different translation relation based features in addition to context based features. We use the contextual information contained in translation resources for extracting context based features.The proposed method uses LTR to construct a translation ranking model based on defined features. The constructed model is used for ranking translation candidates of query words. To evaluate the proposed method we do English-Persian CLIR, in which we employ the translation ranking model to find translations of English queries and employ the translations to retrieve Persian documents. Experimental results show that our approach significantly outperforms single resource based CLR methods. 139 Information Technology A Semantic Domain-Specific Framework to Assist Researchers in Screening Contents Tayefeh Mahmoudi Maryam Taghiyareh Fattaneh 1 3 2014 6 1 69 78 06 10 2018 06 10 2018 Screening and selecting appropriate research documents out of enormous existing contents, has drawn a wide range of research activities these days. Some researchers focus on developing automatic content assessment systems, while the others propose and expand some semantic rules and structures to facilitate the assessment process. There exist various content assessment methods which usually consider at least one of syntactic, semantic and structural perspectives through information retrieval or machine learning algorithms. In this paper, a semantic domain-specific framework is presented to assist researchers in their screening, selecting and recommending activities. The proposed framework is equipped with the ontology of key segments to assess various parts of research content, as well as WordNet and domain ontology, to reinforce semantic rules. The proposed framework is examined on a dataset of contents, and is also compared to the experts assessment of the same research materials. The comparison results reveal that the proposed semantic researcher-assisting framework has been successful in almost 70% of cases.