• List of Articles


      • Open Access Article

        1 - Selecting Enterprise Resource Planning System Using Fuzzy Analytic Hierarchy Process Approach
        hojatallah hamidi
        To select an enterprise resource planning (ERP) system is time consuming due to the resource constraints, the software complexity, and the different of alternatives. A comprehensively systematic selection policy for ERP system is very important to the success of ERP pro Full Text
        To select an enterprise resource planning (ERP) system is time consuming due to the resource constraints, the software complexity, and the different of alternatives. A comprehensively systematic selection policy for ERP system is very important to the success of ERP project. In this paper, we propose a fuzzy analytic hierarchy process (FAHP) method to evaluate the alternatives of ERP system. The selection criteria of ERP system are numerous and fuzzy, so how to select an adequate ERP system is crucial in the early phase of an ERP project. The framework decomposes ERP system selection into four main factors. The goal of this paper is to select the best alternative that meets the requirements with respect to product factors, system factors, management factors and vendor factors. The sub-attributes (sub-factors) related to ERP selection have been classified into thirteen main categories of Functionality, Reliability¬, Usability¬, Efficiency¬, Maintainability¬, Portability¬, Cost, Implementation time, User friendliness¬, Flexibility¬, Vendor Reputation¬, Consultancy Services, and R&D Capability¬ and arranged in a hierarchy structure. These criteria and factors are weighted and prioritized and finally a framework is provided for ERP selection with the fuzzy AHP method. Also, a real case study from Iran (PARDIS-LO Company) is also presented to demonstrate efficiency of this method in practice. Manuscript Document
      • Open Access Article

        2 - A fuzzy approach for ambiguity reducing in text similarity estimation (case study: Persian web contents)
        Hamid Ahangarbahan gholamali montazer
        Finding similar web contents have great efficiency in academic community and software systems. There are many methods and metrics in literature to measure the extent of text similarity among various documents and some its application especially in plagiarism detection s Full Text
        Finding similar web contents have great efficiency in academic community and software systems. There are many methods and metrics in literature to measure the extent of text similarity among various documents and some its application especially in plagiarism detection systems. However, most of them do not take ambiguity inherent in word or text pair’s comparison as well as structural features into account. As a result, pervious methods did not have enough accuracy to deal vague information. So using structural features and considering ambiguity inherent word improve the identification of similar contents. In this paper, a new method has been proposed that taking lexical and structural features in text similarity measures into consideration. After preprocessing and removing stopwords, each text was divided into general words and domain-specific knowledge words. Then, the two lexical and structural fuzzy inference systems were designed to assess lexical and structural text similarity. The proposed method has been evaluated on Persian paper abstracts of International Conference on e-Learning and e-Teaching (ICELET) Corpus. The results shows that the proposed method can achieve a rate of 75% in terms of precision and can detect 81% of the similar cases. Manuscript Document
      • Open Access Article

        3 - Scalable Community Detection through Content and Link Analysis in Social Networks
        Zahra  Arefian Mohammad Reza  Khayyam Bashi
        Social network analysis is an important problem that has been attracting a great deal of attention in recent years. Such networks provide users many different applications and features; as a result, they have been mentioned as the most important event of recent decades. Full Text
        Social network analysis is an important problem that has been attracting a great deal of attention in recent years. Such networks provide users many different applications and features; as a result, they have been mentioned as the most important event of recent decades. Using features that are available in the social networks, first discovering a complete and comprehensive communication should be done. Many methods have been proposed to explore the community, which are community detections through link analysis and nodes content. Most of the research exploring the social communication network only focuses on the one method, while attention to only one of the methods would be a confusion and incomplete exploration. Community detections is generally associated with graph clustering, most clustering methods rely on analyzing links, and no attention to regarding the content that improves the clustering quality. In this paper, to scalable community detections, an integral algorithm is proposed to cluster graphs according to link structure and nodes content, and it aims finding clusters in the groups with similar features. To implement the Integral Algorithm, first a graph is weighted by the algorithm according to the node content, and then network graph is analyzed using Markov Clustering Algorithm, in other word, strong relationships are distinguished from weak ones. Markov Clustering Algorithm is proposed as a Multi-Level one to be scalable. The proposed Integral Algorithm was tested on real datasets, and the effectiveness of the proposed method is evaluated. Manuscript Document
      • Open Access Article

        4 - On-road Vehicle detection based on hierarchical clustering using adaptive vehicle localization
        Moslem  Mohammadi Jenghara Hossein Ebrahimpour Komleh
        Vehicle detection is one of the important tasks in automatic driving. It is a hard problem that many researchers focused on it. Most commercial vehicle detection systems are based on radar. But these methods have some problems such as have problem in zigzag motions. Im Full Text
        Vehicle detection is one of the important tasks in automatic driving. It is a hard problem that many researchers focused on it. Most commercial vehicle detection systems are based on radar. But these methods have some problems such as have problem in zigzag motions. Image processing techniques can overcome these problems.This paper introduces a method based on hierarchical clustering using low-level image features for on-road vehicle detection. Each vehicle assumed as a cluster. In traditional clustering methods, the threshold distance for each cluster is fixed, but in this paper, the adaptive threshold varies according to the position of each cluster. The threshold measure is computed with bivariate normal distribution. Sampling and teammate selection for each cluster is applied by the members-based weighted average. For this purpose, unlike other methods that use only horizontal or vertical lines, a fully edge detection algorithm was utilized. Corner is an important feature of video images that commonly were used in vehicle detection systems. In this paper, Harris features are applied to detect the corners. LISA data set is used to evaluate the proposed method. Several experiments are applied to investigate the performance of proposed algorithm. Experimental results show good performance compared to other algorithms . Manuscript Document
      • Open Access Article

        5 - A New Architecture for Intrusion-Tolerant Web Services Based on Design Diversity Techniques
        Sadegh Bejani Mohammad  Abdollahi Azgomi
        Web services are the realization of service-oriented architecture (SOA). Security is an important challenge of SOAP-based Web services. So far, several security techniques and standards based on traditional security mechanisms, such as encryption and digital signature, Full Text
        Web services are the realization of service-oriented architecture (SOA). Security is an important challenge of SOAP-based Web services. So far, several security techniques and standards based on traditional security mechanisms, such as encryption and digital signature, have been proposed to enhance the security of Web services. The aim has been to employ the concepts and techniques of fault-tolerant computing to make Web services more secure, which is called intrusion-tolerance. Intrusion-tolerance means the continuous delivery of services in presence of security attacks, which can be used as a fundamental approach for enhancing the security of Web services. In this paper, we propose a novel architecture for intrusion-tolerant Web services with emphasis on intrusion-tolerance concepts and composite Web service techniques. The proposed architecture, which is called design-diverse intrusion-tolerant Web service (DDITWS), takes the advantages of design diversity techniques. For Web service composition, BPEL4WS is used. Formal modeling and verification of the proposed architecture is performed using colored Petri nets (CPNs) and CPN Tools. We have checked the behavioral properties of the model to ensure its correctness. The reliability and security evaluation of the proposed architecture is also performed using a stochastic Petri net (SPN) model and the SHARPE tool. The results show that the reliability and mean-time-to-security-failure (MTTSF) in the proposed architecture are improved. Manuscript Document
      • Open Access Article

        6 - Automatic Construction of Domain Ontology Using Wikipedia and Enhancing it by Google Search Engine
        Sedigheh  Khalatbari
        The foundation of the Semantic Web are ontologies. Ontologies play the main role in the exchange of information and development of the Lexical Web to the Semantic Web. Manual construction of ontologies is time-consuming, expensive, and dependent on the knowledge of doma Full Text
        The foundation of the Semantic Web are ontologies. Ontologies play the main role in the exchange of information and development of the Lexical Web to the Semantic Web. Manual construction of ontologies is time-consuming, expensive, and dependent on the knowledge of domain engineers. Also, Ontologies that have been extracted automatically from corpus on the Web might have incomplete information. The main objective of this study is describing a method to improve and expand the information of the ontologies. Therefore, this study first discusses the automatic construction of prototype ontology in animals’ domain from Wikipedia and then a method is presented to improve the built ontology. The proposed method of improving ontology expands ontology concepts through Bootstrapping methods using a set of concepts and relations in initial ontology and with the help of the Google search engine. A confidence measure was considered to choose the best option from the returned results by Google. Finally, the experiments showed the information that was obtained using the proposed method is twice more than the information that was obtained at the stage of automatic construction of ontology from Wikipedia. Manuscript Document
      • Open Access Article

        7 - A Linear Model for Energy-Aware Scheduling Problem Considering Interference in Real-time Wireless Sensor Networks
        Maryam  Hamidanvar rafeh rafeh
        An important factor in increasing quality of service in real-time wireless networks is minimizing energy consumption, which contradicts with increasing message delivery rate because of associating a time deadline to each message. In these networks, every message has a t Full Text
        An important factor in increasing quality of service in real-time wireless networks is minimizing energy consumption, which contradicts with increasing message delivery rate because of associating a time deadline to each message. In these networks, every message has a time deadline constraint and when the message is not delivered to its destination before its deadline constraint, it will drop. Therefore, scheduling methods that simultaneously consider both energy consumption and time deadline constraint are needed. An effective method for reducing energy consumption is multi-hop transmission of packets. However, this method takes longer time for transmission as compared to single-hop transmission. Parallel transmission is another approach which on one hand reduces the transmission time and on the other hand increases the network throughput. However, a main issue with parallel transmission is the presence of interference among nearby nodes. In this paper, we propose a linear model (ILP formulation) for energy aware scheduling problem in real-time wireless sensor networks using parallel transmission. The main objective of the model is to reduce energy consumption and packet loss using multi-hop routing and parallel transmission. Experimental results show that the proposed model finds the optimum solution for the problem and outperforms the sequential scheduling based on the TDMA protocol. Manuscript Document
      • Open Access Article

        8 - A Hybrid Object Tracking for Hand Gesture (HOTHG) Approach based on MS-MD and its Application
        Amir Hooshang  Mazinan Jalal  Hassanian
        In the research proposed here, a hybrid object tracking approach, namely HOTHG, with its application to hand gesture recognition in American Sign Language; ASL, is realized. This is in fact proposed to track and recognize the hand gesture, in an effective manner, in lin Full Text
        In the research proposed here, a hybrid object tracking approach, namely HOTHG, with its application to hand gesture recognition in American Sign Language; ASL, is realized. This is in fact proposed to track and recognize the hand gesture, in an effective manner, in line with the mean shift; MS, and the motion detection; MD, entitled MS/MD-based approach. The results are synchronously investigated based on these two well-known techniques in the area of object tracking to modify those obtained from the traditional ones. The MS algorithm can track the objects based on its detailed targets, so we have to specify ones, as long as the MD algorithm is not realized. In the proposed approach, the advantages of two algorithms are efficiently used to upgrade the hand tracking performance. In the first step, the MD algorithm is applied to remove a number of parts without area motion, and subsequently the MS algorithm is accurately realized for hand tracking. Finally, the present approach is carried out to eliminate the weakness of the traditional methods, which are only organized in association with the MS algorithm. The results are all carried out on Boston-104 database, where the hand gesture is tracked in better form with respect to the previous existing approaches. Manuscript Document