• About Journal

     The Journal of Information Systems and Telecommunication (JIST) accepts and publishes papers containing original researches and/or development results, representing an effective and novel contribution for knowledge in the area of information systems and Telecommunication. Contributions are accepted in the form of Regular papers or Correspondence. Regular papers are the ones with a well-rounded treatment of a problem area, whereas Correspondence focus on a point of a defined problem area. Under the permission of the editorial board, other kinds of papers may be published if they are found to be relevant or of interest to the readers. Responsibility for the content of the papers rests upon the Authors only. The Journal is aimed at not only a national target community, but also international audiences is taken into consideration. For this reason, authors are supposed to write in English.

    This Journal is Published under scientific support of Advanced Information Systems (AIS) Research Group and Digital & Signal Processing Group, ICTRC

    APC charge update for ONLY Iranian authors, effective 22th December, 2021.

    For further information on Article Processing Charges (APCs) policies, please visit our APC page or contact us infojist@gmail.com. 


    Latest published articles

    • Open Access Article

      1 - Measurement and Analysis of Radiation Levels from Base Transceiver Station in Sambas
      Fitri Imansyah Leonardus Sandy Ade Putra Eka  Kusumawardhani
      Volume 9 , Special Issue
      The development of telecommunications in Indonesia until now has experienced a very significant increase and has become a significant need in communication. Many people use communication tools daily, causing many providers to set up Base Transceiver Stations (BTS) to re Full Text
      The development of telecommunications in Indonesia until now has experienced a very significant increase and has become a significant need in communication. Many people use communication tools daily, causing many providers to set up Base Transceiver Stations (BTS) to reach their users to remote areas. BTS has a transmit power that can reach the destination area, but most people still do not know the level of radiation emitted and the health effects on the body. Therefore the International Commission for Non-Ionizing Radiation Protection (ICNIRP) has set a threshold level of safe radiation for the human body. Sambas is one of the cities in West Kalimantan which is the target for the development of BTS establishments by operators. This makes the surrounding community feel afraid of the health caused by radiation from the BTS. So it is necessary to do some research, socialize, measuring, and evaluate the level of radiation emitted from BTS, especially in residential areas. The research was conducted through several stages, including; data collection, data collection methods on variations in distance from BTS, results of radiation level measurements, and comparisons to the safe threshold value for radiation intensity that has been set by ICNIRP. The measurement results from 20 BTS in Sambas show that the radiation level from the BTS measured is still far from the safe radiation threshold that has been set by ICNIRP. Manuscript Document

    • Open Access Article

      2 - Analytical Model to Create Proxy Server Sessions in Multimedia Networks
      Mehdi Khazaei
      Volume 9 , Special Issue
      One of the most popular and widely applied protocols on multimedia networks is the Session Initiation Protocol (SIP) to create, modify, and terminate the sessions. SIP is the platform of Next Generation Networks (NGN). In this way, SIP should be able to respond to the n Full Text
      One of the most popular and widely applied protocols on multimedia networks is the Session Initiation Protocol (SIP) to create, modify, and terminate the sessions. SIP is the platform of Next Generation Networks (NGN). In this way, SIP should be able to respond to the needs of such a largely-used network. One of the major problems in SIP networks is overload. This challenge creates a sharp drop in quality of service for NGN users. In this regard, many studies have been conducted on the effectiveness of this protocol, especially under overload. A new analytical model is developed that prioritizes the SIP message processing. An analytical approach is proposed based on the Mean Value Analysis (MVA) algorithm in queue theory. Considering some appropriate assumptions customizing MVA as to implement this proposed model and to cope with the limitations of the MVA is highly essential. The output of the analytical model is compared with the standard SIP model obtained from the simulator and the results confirm that prioritizing original messages would enhance the SIP performance at different load conditions. Prioritization of original messages is advantageous, and outperforms the normal SIP. Nevertheless, prioritizing the repeated messages not only has no advantage, but also its performance is less than the normal SIP. Manuscript Document

    • Open Access Article

      3 - SQP-based Power Allocation Strategy for Target Tracking in MIMO Radar Network with Widely Separated Antennas
      Mohammad  Akhondi Darzikolaei Mohammad Reza Karami-Mollaei Maryam Najimi
      Volume 9 , Special Issue
      MIMO radar with widely separated antennas enhances detection and estimation resolution by utilizing the diversity of the propagation path. Each antenna of this type of radar can steer its beam independently towards any direction as an independent transmitter. However, t Full Text
      MIMO radar with widely separated antennas enhances detection and estimation resolution by utilizing the diversity of the propagation path. Each antenna of this type of radar can steer its beam independently towards any direction as an independent transmitter. However, the joint processing of signals for transmission and reception differs this radar from the multistatic radar. There are many resource optimization problems which improve the performance of MIMO radar. But power allocation is one of the most interesting resource optimization problems. The power allocation finds an optimum strategy to assign power to transmit antennas with the aim of minimizing the target tracking errors under specified transmit power constraints. In this study, the performance of power allocation for target tracking in MIMO radar with widely separated antennas is investigated. Therefore, a MIMO radar with distributed antennas is configured and a target motion model using the constant velocity (CV) method is modeled. Then Joint Cramer Rao bound (CRB) for target parameters (joint target position and velocity) estimation error is calculated. This is utilized as a power allocation problem objective function. Since the proposed power allocation problem is nonconvex. Therefore, a SQP-based power allocation algorithm is proposed to solve it. In simulation results, the performance of the proposed algorithm in various conditions such as a different number of antennas and antenna geometry configurations is examined. Results affirm the accuracy of the proposed algorithm. Manuscript Document

    • Open Access Article

      4 - Reliability Analysis of the Joint LDPC Decoding Algorithms over the Multiple Access Channels
      Mahdi Nangir
      Volume 9 , Special Issue
      The joint Low Density Parity-Check (LDPC) decoding schemes iteratively decode the received data from multiple channels. Mostly, the available data in different channels are correlated and there is kind of dependency between the links or channels. In recent decades, the Full Text
      The joint Low Density Parity-Check (LDPC) decoding schemes iteratively decode the received data from multiple channels. Mostly, the available data in different channels are correlated and there is kind of dependency between the links or channels. In recent decades, the graph-based codes have been considered for the communication network scenarios. The performance of these codes is close to the existing theoretical bounds and their complexity is not high which cause the possibility of real world implementation and exploitation. The Multiple Access Channel (MAC) scenario with multiple senders which aim to send correlated data to a single receiver is considered. An analysis on the reliability of the Bit Error Rate (BER) performance of the Joint Sum-Product (JSP) decoding algorithm is presented for a two-link case, which can be extended to higher number of links. The effect of parameter variations on the BER performance is studied. These parameters include: the total number of iterations, the codeword length, the total number of rounds, and the coding rate in the JSP algorithm. An optimal value of the parameters is selected during the design procedure of a communication network by considering its limitations and complexity criterion. The JSP algorithm is a reliable scheme for jointly decoding of noisy binary data from different origins. Manuscript Document

    • Open Access Article

      5 - Remote Sensing Image Registration based on a Geometrical Model Matching
      Zahra Hossein-Nejad Hamed Agahi Azar Mahmoodzadeh
      Volume 9 , Special Issue
      Remote sensing image registration is the method of aligning two images from the same scene taken under different imaging circumstances containing different times, angles, or sensors. Scale-invariant feature transform (SIFT) is one of the most common matching methods pre Full Text
      Remote sensing image registration is the method of aligning two images from the same scene taken under different imaging circumstances containing different times, angles, or sensors. Scale-invariant feature transform (SIFT) is one of the most common matching methods previously used in the remote sensing image registration. The defects of SIFT are the large number of mismatches and high execution time due to the high dimensions of classical SIFT descriptor. These drawbacks reduce the efficiency of the SIFT algorithm. To enhance the performance of the remote sensing image registration, this paper proposes an approach consisting of three different steps. At first, the keypoints of both reference and second images are extracted using SIFT algorithm. Then, to increase the speed of the algorithm and accuracy of the matching, the SIFT descriptor with the vector length of 64 is used for keypoints description. Finally, a new method has been proposed for the image matching. The proposed matching method is based on calculating the distances of keypoints and their transformed points. Simulation results of applying the proposed method to some standard databases demonstrated the superiority of this approach compared with some other existing methods, according to the root mean square error (RMSE), precision and running time criteria. Manuscript Document

    • Open Access Article

      6 - Error Reconciliation based on Integer Linear Programming in Quantum Key Distribution
      zahra eskandari mohammad  rezaee
      Volume 9 , Special Issue
      Quantum telecommunication has received a lot of attention today by providing unconditional security because of the inherent nature of quantum channels based on the no-cloning theorem. In this mode of communication, first, the key is sent through a quantum channel that i Full Text
      Quantum telecommunication has received a lot of attention today by providing unconditional security because of the inherent nature of quantum channels based on the no-cloning theorem. In this mode of communication, first, the key is sent through a quantum channel that is resistant to eavesdropping, and then secure communication is established using the exchanged key. Due to the inevitability of noise, the received key needs to be distilled. One of the vital steps in key distillation is named key reconciliation which corrects the occurred errors in the key. Different solutions have been presented for this issue, with different efficiency and success rate. One of the most notable works is LDPC decoding which has higher efficiency compared to the others, but unfortunately, this method does not work well in the codes with a high rate. In this paper, we present an approach to correct the errors in the high rate LDPC code-based reconciliation algorithm. The proposed algorithm utilizes Integer Linear Programming to model the error correction problem to an optimization problem and solve it. Testing the proposed approach through simulation, we show it has high efficiency in high rate LDPC codes as well as a higher success rate compared with the LDPC decoding method - belief propagation – in a reasonable time. Manuscript Document
    Most Viewed Articles

    • Open Access Article

      1 - Privacy Preserving Big Data Mining: Association Rule Hiding
      Golnar Assadat  Afzali shahriyar mohammadi
      Issue 14 , Volume 4 , Spring 2016
      Data repositories contain sensitive information which must be protected from unauthorized access. Existing data mining techniques can be considered as a privacy threat to sensitive data. Association rule mining is one of the utmost data mining techniques which tries to Full Text
      Data repositories contain sensitive information which must be protected from unauthorized access. Existing data mining techniques can be considered as a privacy threat to sensitive data. Association rule mining is one of the utmost data mining techniques which tries to cover relationships between seemingly unrelated data in a data base.. Association rule hiding is a research area in privacy preserving data mining (PPDM) which addresses a solution for hiding sensitive rules within the data problem. Many researches have be done in this area, but most of them focus on reducing undesired side effect of deleting sensitive association rules in static databases. However, in the age of big data, we confront with dynamic data bases with new data entrance at any time. So, most of existing techniques would not be practical and must be updated in order to be appropriate for these huge volume data bases. In this paper, data anonymization technique is used for association rule hiding, while parallelization and scalability features are also embedded in the proposed model, in order to speed up big data mining process. In this way, instead of removing some instances of an existing important association rule, generalization is used to anonymize items in appropriate level. So, if necessary, we can update important association rules based on the new data entrances. We have conducted some experiments using three datasets in order to evaluate performance of the proposed model in comparison with Max-Min2 and HSCRIL. Experimental results show that the information loss of the proposed model is less than existing researches in this area and this model can be executed in a parallel manner for less execution time Manuscript Document

    • Open Access Article

      2 - Instance Based Sparse Classifier Fusion for Speaker Verification
      Mohammad Hasheminejad Hassan Farsi
      Issue 15 , Volume 4 , Summer 2016
      This paper focuses on the problem of ensemble classification for text-independent speaker verification. Ensemble classification is an efficient method to improve the performance of the classification system. This method gains the advantage of a set of expert classifiers Full Text
      This paper focuses on the problem of ensemble classification for text-independent speaker verification. Ensemble classification is an efficient method to improve the performance of the classification system. This method gains the advantage of a set of expert classifiers. A speaker verification system gets an input utterance and an identity claim, then verifies the claim in terms of a matching score. This score determines the resemblance of the input utterance and pre-enrolled target speakers. Since there is a variety of information in a speech signal, state-of-the-art speaker verification systems use a set of complementary classifiers to provide a reliable decision about the verification. Such a system receives some scores as input and takes a binary decision: accept or reject the claimed identity. Most of the recent studies on the classifier fusion for speaker verification used a weighted linear combination of the base classifiers. The corresponding weights are estimated using logistic regression. Additional researches have been performed on ensemble classification by adding different regularization terms to the logistic regression formulae. However, there are missing points in this type of ensemble classification, which are the correlation of the base classifiers and the superiority of some base classifiers for each test instance. We address both problems, by an instance based classifier ensemble selection and weight determination method. Our extensive studies on NIST 2004 speaker recognition evaluation (SRE) corpus in terms of EER, minDCF and minCLLR show the effectiveness of the proposed method. Manuscript Document

    • Open Access Article

      3 - COGNISON: A Novel Dynamic Community Detection Algorithm in Social Network
      Hamideh Sadat Cheraghchi Ali Zakerolhossieni
      Issue 14 , Volume 4 , Spring 2016
      The problem of community detection has a long tradition in data mining area and has many challenging facet, especially when it comes to community detection in time-varying context. While recent studies argue the usability of social science disciplines for modern social Full Text
      The problem of community detection has a long tradition in data mining area and has many challenging facet, especially when it comes to community detection in time-varying context. While recent studies argue the usability of social science disciplines for modern social network analysis, we present a novel dynamic community detection algorithm called COGNISON inspired mainly by social theories. To be specific, we take inspiration from prototype theory and cognitive consistency theory to recognize the best community for each member by formulating community detection algorithm by human analogy disciplines. COGNISON is placed in representative based algorithm category and hints to further fortify the pure mathematical approach to community detection with stabilized social science disciplines. The proposed model is able to determine the proper number of communities by high accuracy in both weighted and binary networks. Comparison with the state of art algorithms proposed for dynamic community discovery in real datasets shows higher performance of this method in different measures of Accuracy, NMI, and Entropy for detecting communities over times. Finally our approach motivates the application of human inspired models in dynamic community detection context and suggest the fruitfulness of the connection of community detection field and social science theories to each other. Manuscript Document

    • Open Access Article

      4 - Node Classification in Social Network by Distributed Learning Automata
      Ahmad Rahnama Zadeh meybodi meybodi Masoud Taheri Kadkhoda
      Issue 18 , Volume 5 , Spring 2017
      The aim of this article is improving the accuracy of node classification in social network using Distributed Learning Automata (DLA). In the proposed algorithm using a local similarity measure, new relations between nodes are created, then the supposed graph is partitio Full Text
      The aim of this article is improving the accuracy of node classification in social network using Distributed Learning Automata (DLA). In the proposed algorithm using a local similarity measure, new relations between nodes are created, then the supposed graph is partitioned according to the labeled nodes and a network of Distributed Learning Automata is corresponded on each partition. In each partition the maximal spanning tree is determined using DLA. Finally nodes are labeled according to the rewards of DLA. We have tested this algorithm on three real social network datasets, and results show that the expected accuracy of presented algorithm is achieved. Manuscript Document

    • Open Access Article

      5 - A Bio-Inspired Self-configuring Observer/ Controller for Organic Computing Systems
      Ali Tarihi haghighi haghighi feridon Shams
      Issue 15 , Volume 4 , Summer 2016
      The increase in the complexity of computer systems has led to a vision of systems that can react and adapt to changes. Organic computing is a bio-inspired computing paradigm that applies ideas from nature as solutions to such concerns. This bio-inspiration leads to the Full Text
      The increase in the complexity of computer systems has led to a vision of systems that can react and adapt to changes. Organic computing is a bio-inspired computing paradigm that applies ideas from nature as solutions to such concerns. This bio-inspiration leads to the emergence of life-like properties, called self-* in general which suits them well for pervasive computing. Achievement of these properties in organic computing systems is closely related to a proposed general feedback architecture, called the observer/controller architecture, which supports the mentioned properties through interacting with the system components and keeping their behavior under control. As one of these properties, self-configuration is desirable in the application of organic computing systems as it enables by enabling the adaptation to environmental changes. However, the adaptation in the level of architecture itself has not yet been studied in the literature of organic computing systems. This limits the achievable level of adaptation. In this paper, a self-configuring observer/controller architecture is presented that takes the self-configuration to the architecture level. It enables the system to choose the proper architecture from a variety of possible observer/controller variants available for a specific environment. The validity of the proposed architecture is formally demonstrated. We also show the applicability of this architecture through a known case study. Manuscript Document

    • Open Access Article

      6 - Publication Venue Recommendation Based on Paper’s Title and Co-authors Network
      Ramin Safa Seyed Abolghassem Mirroshandel Soroush Javadi Mohammad Azizi
      Issue 21 , Volume 6 , Winter 2018
      Information overload has always been a remarkable topic in scientific researches, and one of the available approaches in this field is employing recommender systems. With the spread of these systems in various fields, studies show the need for more attention to applying Full Text
      Information overload has always been a remarkable topic in scientific researches, and one of the available approaches in this field is employing recommender systems. With the spread of these systems in various fields, studies show the need for more attention to applying them in scientific applications. Applying recommender systems to scientific domain, such as paper recommendation, expert recommendation, citation recommendation and reviewer recommendation, are new and developing topics. With the significant growth of the number of scientific events and journals, one of the most important issues is choosing the most suitable venue for publishing papers, and the existence of a tool to accelerate this process is necessary for researchers. Despite the importance of these systems in accelerating the publication process and decreasing possible errors, this problem has been less studied in related works. So in this paper, an efficient approach will be suggested for recommending related conferences or journals for a researcher’s specific paper. In other words, our system will be able to recommend the most suitable venues for publishing a written paper, by means of social network analysis and content-based filtering, according to the researcher’s preferences and the co-authors’ publication history. The results of evaluation using real-world data show acceptable accuracy in venue recommendations. Manuscript Document

    • Open Access Article

      7 - DBCACF: A Multidimensional Method for Tourist Recommendation Based on Users’ Demographic, Context and Feedback
      Maral Kolahkaj Ali Harounabadi Alireza Nikravan shalmani Rahim Chinipardaz
      Issue 24 , Volume 6 , Autumn 2018
      By the advent of some applications in the web 2.0 such as social networks which allow the users to share media, many opportunities have been provided for the tourists to recognize and visit attractive and unfamiliar Areas-of-Interest (AOIs). However, finding the appropr Full Text
      By the advent of some applications in the web 2.0 such as social networks which allow the users to share media, many opportunities have been provided for the tourists to recognize and visit attractive and unfamiliar Areas-of-Interest (AOIs). However, finding the appropriate areas based on user’s preferences is very difficult due to some issues such as huge amount of tourist areas, the limitation of the visiting time, and etc. In addition, the available methods have yet failed to provide accurate tourist’s recommendations based on geo-tagged media because of some problems such as data sparsity, cold start problem, considering two users with different habits as the same (symmetric similarity), and ignoring user’s personal and context information. Therefore, in this paper, a method called “Demographic-Based Context-Aware Collaborative Filtering” (DBCACF) is proposed to investigate the mentioned problems and to develop the Collaborative Filtering (CF) method with providing personalized tourist’s recommendations without users’ explicit requests. DBCACF considers demographic and contextual information in combination with the users' historical visits to overcome the limitations of CF methods in dealing with multi- dimensional data. In addition, a new asymmetric similarity measure is proposed in order to overcome the limitations of symmetric similarity methods. The experimental results on Flickr dataset indicated that the use of demographic and contextual information and the addition of proposed asymmetric scheme to the similarity measure could significantly improve the obtained results compared to other methods which used only user-item ratings and symmetric measures. Manuscript Document

    • Open Access Article

      8 - The Surfer Model with a Hybrid Approach to Ranking the Web Pages
      Javad Paksima - -
      Issue 15 , Volume 4 , Summer 2016
      Users who seek results pertaining to their queries are at the first place. To meet users’ needs, thousands of webpages must be ranked. This requires an efficient algorithm to place the relevant webpages at first ranks. Regarding information retrieval, it is highly impor Full Text
      Users who seek results pertaining to their queries are at the first place. To meet users’ needs, thousands of webpages must be ranked. This requires an efficient algorithm to place the relevant webpages at first ranks. Regarding information retrieval, it is highly important to design a ranking algorithm to provide the results pertaining to user’s query due to the great deal of information on the World Wide Web. In this paper, a ranking method is proposed with a hybrid approach, which considers the content and connections of pages. The proposed model is a smart surfer that passes or hops from the current page to one of the externally linked pages with respect to their content. A probability, which is obtained using the learning automata along with content and links to pages, is used to select a webpage to hop. For a transition to another page, the content of pages linked to it are used. As the surfer moves about the pages, the PageRank score of a page is recursively calculated. Two standard datasets named TD2003 and TD2004 were used to evaluate and investigate the proposed method. They are the subsets of dataset LETOR3. The results indicated the superior performance of the proposed approach over other methods introduced in this area. Manuscript Document

    • Open Access Article

      9 - Short Time Price Forecasting for Electricity Market Based on Hybrid Fuzzy Wavelet Transform and Bacteria Foraging Algorithm
      keyvan borna Sepideh Palizdar
      Issue 16 , Volume 4 , Autumn 2016
      Predicting the price of electricity is very important because electricity can not be stored. To this end, parallel methods and adaptive regression have been used in the past. But because dependence on the ambient temperature, there was no good result. In this study, lin Full Text
      Predicting the price of electricity is very important because electricity can not be stored. To this end, parallel methods and adaptive regression have been used in the past. But because dependence on the ambient temperature, there was no good result. In this study, linear prediction methods and neural networks and fuzzy logic have been studied and emulated. An optimized fuzzy-wavelet prediction method is proposed to predict the price of electricity. In this method, in order to have a better prediction, the membership functions of the fuzzy regression along with the type of the wavelet transform filter have been optimized using the E.Coli Bacterial Foraging Optimization Algorithm. Then, to better compare this optimal method with other prediction methods including conventional linear prediction and neural network methods, they were analyzed with the same electricity price data. In fact, our fuzzy-wavelet method has a more desirable solution than previous methods. More precisely by choosing a suitable filter and a multiresolution processing method, the maximum error has improved by 13.6%, and the mean squared error has improved about 17.9%. In comparison with the fuzzy prediction method, our proposed method has a higher computational volume due to the use of wavelet transform as well as double use of fuzzy prediction. Due to the large number of layers and neurons used in it, the neural network method has a much higher computational volume than our fuzzy-wavelet method. Manuscript Document

    • Open Access Article

      10 - Promote Mobile Banking Services by using National Smart Card Capabilities and NFC Technology
      Reza Vahedi Sayed Esmaeail Najafi Farhad Hosseinzadeh Lotfi
      Issue 15 , Volume 4 , Summer 2016
      By the mobile banking system and install an application on the mobile phone can be done without visiting the bank and at any hour of the day, get some banking operations such as account balance, transfer funds and pay bills did limited. The second password bank account Full Text
      By the mobile banking system and install an application on the mobile phone can be done without visiting the bank and at any hour of the day, get some banking operations such as account balance, transfer funds and pay bills did limited. The second password bank account card, the only security facility predicted for use mobile banking systems and financial transactions. That this alone cannot create reasonable security and the reason for greater protection and prevent the theft and misuse of citizens’ bank accounts is provide banking services by the service limits. That by using NFC (Near Field Communication) technology can identity and biometric information and Key pair stored on the smart card chip be exchanged with mobile phone and mobile banking system. And possibility of identification and authentication and also a digital signature created documents. And thus to enhance the security and promote mobile banking services. This research, the application and tool library studies and the opinion of seminary experts of information technology and electronic banking and analysis method Dematel is examined. And aim to investigate possibility Promote mobile banking services by using national smart card capabilities and NFC technology to overcome obstacles and risks that are mentioned above. Obtained Results, confirmed the hypothesis of the research and show that by implementing the so-called solutions in the banking system of Iran. Manuscript Document
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    Number of Issues 9
    Count of Volumes 36
    Printed Articles 264
    Number of Authors 2127
    Article Views 624451
    Article Downloads 130818
    Number of Submitted Articles 1187
    Number of Rejected Articles 710
    Number of Accepted Articles 296
    Acceptance 24 %
    Admission Time(Day) 168
    Reviewer Count 780
    Last Update 1/19/2022