@article{ author = {Monemizadeh, Mostafa and Seyedin, Seyed Alireza and AbedHodtani, Ghosheh}, title = {Capacity Region of the Compound Multiple Access Channels with Common Message and in the Presence of Intersymbol Interference}, abstract ={The capacity region of a two-user linear Gaussian compound Multiple Access Channel with common message (CMACC) and intersymbol interference (ISI) under an input power constraint is derived. To obtain the capacity region we first convert the channel to its equivalent memoryless one by defining an n-block memoryless circular Gaussian CMACC model. We then make use of the discrete Fourier transform (DFT) to decompose the nblock circular Gaussian CMACC into a set of independent parallel channels whose individual capacities can be found easily. Finally we derive the capacity of this n-block memoryless circular Gaussian CMACC (n-CGCMACC) based on the DFT decomposition. Since our channel is a special case of a synchronous multi-terminal channel, the capacity region of the Gaussian CMACC with ISI is the same as the capacity region of the n-CGCMACC in the limit of infinite block length. We also investigate the capacity regions for some special cases of the Gaussian CMACC with ISI using the obtained capacity region, and finally, provide some numerical results to show the loss in the rate caused by ISI.}, Keywords = { Capacity region, compound multiple access channels, Gaussian channels, intersymbol interference (ISI) }, volume = {6}, Number = {2}, pages = {1-9}, publisher = {ICT Research Institute(ITRC)}, url = {http://ijict.itrc.ac.ir/article-1-126-en.html}, eprint = {http://ijict.itrc.ac.ir/article-1-126-en.pdf}, journal = {International Journal of Information and Communication Technology Research}, issn = {2251-6107}, eissn = {2783-4425}, year = {2014} } @article{ author = {Mazoochi, Mojtaba and Pourmina, Mohammad Ali and Bakhshi, Hamidreza and Navidi, Hamidrez}, title = {A Novel Strategy-Proof Auction Mechanism for Hybrid Spectrum Allocation}, abstract ={Auctions have been widely studied as an efficient approach of allocating spectrum among secondary users in recent years. On the other side, a wide range of frequency bands could be available in a spectrum auction considering the current trend of deregulating wireless resources, therefore, channels provided by the primary users may reside in widely separated frequency bands, and due to the difference in propagation profile, would show significant heterogeneity in transmission range, channel error rate, path-loss, etc. Also, we can consider the channels with similar propagation and quality characteristics, for example, channels located in the same frequency band, are homogeneous and can be located in one spectrum type. Therefore, in this paper, we propose a novel double auction mechanism for both homogeneous and heterogeneous spectrums, called hybrid spectrums. The hybrid auction design has its own challenges, especially it also inherits the challenges related to heterogeneity. We prove that our auction design can not only solve the challenges caused by hybrid spectrums but also preserve three important economic aspects including truthfulness, budget balance and individual rationality.}, Keywords = {Spectrum Allocation, Double Auction, Heterogeneity, Strategy-Proofness, Hybrid Spectrum}, volume = {6}, Number = {2}, pages = {11-18}, publisher = {ICT Research Institute(ITRC)}, url = {http://ijict.itrc.ac.ir/article-1-127-en.html}, eprint = {http://ijict.itrc.ac.ir/article-1-127-en.pdf}, journal = {International Journal of Information and Communication Technology Research}, issn = {2251-6107}, eissn = {2783-4425}, year = {2014} } @article{ author = {GhasemiKomishani, Elahe and Abadi, Mahdi}, title = {TrPLS: Preserving Privacy in Trajectory Data Publishing by Personalized Local Suppression}, abstract ={Trajectory data are becoming more popular due to the rapid development of mobile devices and the widespread use of location-based services. They often provide useful information that can be used for data mining tasks. However, a trajectory database may contain sensitive attributes, such as disease, job, and salary, which are associated with trajectory data. Hence, improper publishing of the trajectory database can put the privacy of moving objects at risk. Removing identifiers from the trajectory database before the public release, is not effective against privacy attacks, especially, when an adversary uses some partial trajectory information as its background knowledge. The existing approaches for preserving privacy in trajectory data publishing apply the same amount of privacy protection for all moving objects without considering their privacy requirements. The consequence is that some moving objects with high privacy requirements may be offered low privacy protection, and vice versa. In this paper, we address this challenge and present TrPLS, a novel approach for preserving privacy in trajectory data publishing. It combines local suppression with the concept of personalization to achieve the conflicting goals of data utility and data privacy in accordance with the privacy requirements of moving objects. The results of experiments on a trajectory dataset show that TrPLS can be successfully used for preserving personalized privacy in trajectory data publishing.}, Keywords = {trajectory data, privacy preservation, personalized privacy, quasi-identifier, local suppression, information loss, disclosure risk }, volume = {6}, Number = {2}, pages = {19-28}, publisher = {ICT Research Institute(ITRC)}, url = {http://ijict.itrc.ac.ir/article-1-128-en.html}, eprint = {http://ijict.itrc.ac.ir/article-1-128-en.pdf}, journal = {International Journal of Information and Communication Technology Research}, issn = {2251-6107}, eissn = {2783-4425}, year = {2014} } @article{ author = {Keyvanpour, Mohammad Reza and Homayouni, Hajar}, title = {Automatic Test Case Generation for Modern Web Applications Using Population-Based Automatic Fuzzy Neural Network}, abstract ={Automatic test case generation is an approach to decrease cost and time in software testing. Although there have been lots of proposed methods for automatic test case generation of web applications, there still exists some challenges which needs more researches. The most important problem in this area is the lack of a complete descriptive model which indicates the whole behaviors of web application as guidance for the generation of test cases with high software coverage. In this paper, test cases are generated automatically to test web applications using a machine learning method. The proposed method called RTCGW (Rule-based Test Case Generator for Web Applications) generates test cases based on a set of fuzzy rules that try to indicate the whole software behaviors to reach to a high level of software coverage. For this purpose a novel machine learning approach based on fuzzy neural networks is proposed to extract fuzzy rules from a set of data and then used to generate a set of fuzzy rules representing software behaviors. The fuzzy rule set is then used to generate software test cases and the generated test cases are optimized using an optimization algorithm based on combination of genetic and simulated annealing algorithms. Two benchmark problems are tested using the optimized test cases. The results show a high level of coverage and performance for the proposed method in comparison with other methods.}, Keywords = {Automatic Test case generation, web applications, population-based Fuzzy Neural Network }, volume = {6}, Number = {2}, pages = {29-40}, publisher = {ICT Research Institute(ITRC)}, url = {http://ijict.itrc.ac.ir/article-1-129-en.html}, eprint = {http://ijict.itrc.ac.ir/article-1-129-en.pdf}, journal = {International Journal of Information and Communication Technology Research}, issn = {2251-6107}, eissn = {2783-4425}, year = {2014} } @article{ author = {Gohari, Faezeh Sadat and Tarokh, Mohammad Jafar}, title = {A Cluster-Based Similarity Fusion Approach for Scaling-Up Collaborative Filtering Recommender System}, abstract ={Collaborative Filtering (CF) recommenders work by collecting user ratings for items in a given domain and computing similarities between users or items to produce recommendations. The user-item rating database is extremely sparse. This means the number of ratings obtained is very small compared with the number of ratings that need to be predicted. CF suffers from the sparsity problem, resulting in poor quality recommendations and reduced coverage. Further, a CF algorithm needs calculations that are very expensive and grow non-linearly with the number of users and items in a database. Incited by these challenges, we present Cluster-Based Similarity Fusion (CBSF), a new hybrid collaborative filtering algorithm which can deal with the sparsity and scalability issues simultaneously. By the use of carefully selected clusters of users and items, CBSF reduces the computational cost of traditional CF, while retaining high accuracy. Experimental results demonstrate that apart from being scalable, CBSF leads to a better precision and coverage for the recommendation engine.}, Keywords = {recommender systems, collaborative filtering, similarity fusion, clustering }, volume = {6}, Number = {2}, pages = {41-52}, publisher = {ICT Research Institute(ITRC)}, url = {http://ijict.itrc.ac.ir/article-1-130-en.html}, eprint = {http://ijict.itrc.ac.ir/article-1-130-en.pdf}, journal = {International Journal of Information and Communication Technology Research}, issn = {2251-6107}, eissn = {2783-4425}, year = {2014} } @article{ author = {Rahmaninia, Maryam and Bigdeli, Elnaz and Afsharchi, Mohse}, title = {A Scalable Algorithm to Solve Distributed Constraint Optimization}, abstract ={Recently, Distributed Constraint Optimization Problems (DCOP) have been drawing a growing body of attention as an important research area in multi agent systems as a large body of real problems can be modeled by them. The primary goal of this research is to design a distributed and effective algorithm to solve DCOP. There are various criteria that measure the efficiency of DCOP algorithms, but the most efficient algorithm for DCOP is the one by which the computation and communication cost is as low as possible and the quality of the solution is high. In this paper, we focus on an approximate DCOP algorithm called DALO (Distributed Asynchronous Local Optimization). Using the main idea of the DALO algorithm, we propose a new algorithm to solve DCOP, which exhibits two important improvements over the DALO algorithm. First we use a sequential partial approach to select a coefficient of leaders to compute the best assignment for agents by which the computation and communication cost decrease in the whole DCOP. The second improvement is an evolutionary approach by which the computation and communication burden for each agent decreases. We present some empirical evidences that show our algorithm performs better than the DALO algorithm.}, Keywords = {distributed constraint optimization, multi agent system }, volume = {6}, Number = {2}, pages = {53-65}, publisher = {ICT Research Institute(ITRC)}, url = {http://ijict.itrc.ac.ir/article-1-131-en.html}, eprint = {http://ijict.itrc.ac.ir/article-1-131-en.pdf}, journal = {International Journal of Information and Communication Technology Research}, issn = {2251-6107}, eissn = {2783-4425}, year = {2014} } @article{ author = {Amrollahi, Alireza and Khansari, Mohammad and Manian, Amir}, title = {How Open Source Software Succeeds? A Review of Research on Success of Open Source Software}, abstract ={Different aspects of Open Source Software (OSS) have been subject of many research in last decades. Among them many researchers have tried to adopt the pervasive literature of information systems success with this special kind of system development and its specific dimensions. On the other hand the question of success in the OSS development may cover all different aspects of OSS development and help managers and sponsors of OSS projects to evaluate and increase effectiveness of these projects. So drawing a full picture of related research may be beneficial in different ways. In this paper we try to make a systematic review of related literature in the field and specially pay attention to the measures of success, factors affecting the OSS success and research methods used in previous research. We discussed measures of success and determinants that affect success of OSS as well as methods used in related research and conclude with some points that may strengthen the quality of further work in the topic.}, Keywords = {Open Source Software, Open Source Success, Systematic literature review }, volume = {6}, Number = {2}, pages = {67-77}, publisher = {ICT Research Institute(ITRC)}, url = {http://ijict.itrc.ac.ir/article-1-132-en.html}, eprint = {http://ijict.itrc.ac.ir/article-1-132-en.pdf}, journal = {International Journal of Information and Communication Technology Research}, issn = {2251-6107}, eissn = {2783-4425}, year = {2014} }