فهرست مطالب

International Journal Information and Communication Technology Research
Volume:14 Issue: 3, Summer 2022

  • تاریخ انتشار: 1401/09/20
  • تعداد عناوین: 6
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  • Roghayeh Doost*, Pedram Hajipour, Saber Shahidzadeh, Roghieh Roghieh Karimzadeh Baee Pages 1-9

    Determining and observing the minimum allowable distance of the marine earth station in motion (M-ESIM) from the shore prevents its destructive interference on the co-frequency shore fixed station. ESIMs are providing broadband Fixed Satellite Services (FSS). This paper studies the parameters involved in determining the minimum allowable distance of the ship from the shore by the interference simulation. The results show that with decreasing the carrier frequency, decreasing latitude or increasing the number of annual passing vessels, this minimum distance increases. In this paper a methodology is presented and simulated to keep constant the minimum allowed distance by adjusting the values of the frequency dependent rejection (FDR). FDR is caused by shifting the M-ESIM frequency band. The minimum distance of 100, 105 and 110Km is evaluated in this paper. In this way, the M-ESIM can be close to the shore as near as the desired distance using the FDR adjustment.

    Keywords: Marine ESIM, broadband Fixed Satellite Service, Frequency Interference, FDR
  • Abdolrasoul Sakhaei Gharagezlou*, Mahdi Nangir, Nima Imani Pages 10-18

    In this paper, the performance of a system in terms of the energy efficiency (EE) is studied. To check the EE performance, an appropriate power is allocated to each user. The system in question in this paper is a multiple-input multiple-output (MIMO) system with non-orthogonal multiple access (NOMA) method. Precoding in this system is considered to be the zero forcing (ZF). It is also assumed that the channel state information (CSI) mode is perfect. First, all the parameters that affect the channel, such as path loss and beam forming are investigated, and then the channel matrix is obtained. To improve system performance, better conditions are provided for users with poor channel conditions. These conditions are created by allocating more appropriate power to these users, or in other words, the total transmission power is divided according to the distance of users from the base station (BS) and the channel conditions of each user. The problem of maximizing the EE is formulated with two constraints of the minimum user rate and the maximum transmission power. This is a non-convex problem that becomes a convex problem using optimization properties, and because the problem is constrained it becomes an unconstrained problem using the Lagrange dual function. Numerical and simulation results are presented to prove the mathematical relationships which show that the performance of the proposed scheme is improved compared to the existing methods. The simulation results are related to two different algorithms with a same objective function. Furthermore, to comparison with performance of other methods, output of these two algorithms are also compared with each other.

    Keywords: Multiple-Input Multiple-Output (MIMO), Energy Efficiency (EE), Power Allocation, Zero Forcing (ZF) Precoding, Non-Orthogonal Multiple Access (NOMA), Cell Division Technique
  • Samira Rafiee Samira Rafiee, Alireza Abdollahpouri* Pages 19-26

    In a multiplex network, there exists different types of relationships between the same set of nodes such as people which have different accounts in online social networks. Previous researches have proved that in a multiplex network the structural features of different layers are interrelated. Therefore, effective use of information from other layers can improve link prediction accuracy in a specific layer. In this paper, we propose a new inter-layer similarity metric DSMN, for predicting missing links in multiplex networks. We then combine this metric with a strong intra-layer similarity metric to enhance the performance of link prediction. The efficiency of our proposed method has been evaluated on both real-world and synthetic networks and the experimental results indicate the outperformance of the proposed method in terms of prediction accuracy in comparison with similar methods.

    Keywords: Link prediction, Multilayer networks, Inter-layer similarity metric, structural information
  • Ebrahim Mahdipour*, Ali Aghamohammadpour, Iman Attarzadeh Pages 27-36

    Ransomware attacks are taking advantage of the ongoing coronavirus pandemics and attacking the vulnerable systems in the health sector. Modeling ransomware attacks help to identify and simulate attacks against security environments, using likely adversary techniques. Process Mining (PM) is a field of study that focuses on analyzing process logs linked with the execution of the processes of a system to acquire insight into the variety of characteristics of how the functions behave. This paper presents a PM conformance-based approach to determining ransomware processes. First, frequent ransomware techniques were identified using state-of-the-art MITRE ATT&CK. Then, a model was developed to gather ransomware techniques using a process-based approach. The PM-based Prom tool is used to check the conformance of malware processes alongside the presented model to illustrate its efficiency. The model can identify chain processes associated with ransom-related behaviors. In this study, the presented model was evaluated using thirty common malwares in the healthcare industry. The approach demonstrates that this model could successfully classify ninety percent of malware instances as ransomware and non-ransomware. Finally, guidelines for future research are provided. We believe the proposed method will uncover behavioral models that will enable us to hunt ransomware threats.

    Keywords: Process Mining, Ransomware Hunting, Threat Modeling, Threat Intelligence, Threat Hunting
  • Maryam Hourali*, Mansoureh Hourali Pages 37-47

    Today we live in a period that is known to an area of communication. By increasing the information on the internet, the extra news are published on news agencies websites or other resources, the users are confused more with the problems of finding their desired information and related news. Among these are recommended systems they can automatically finding the news and information of their favorite’s users and suggesting to them too. This article attempts to improve the user’s interests and user’s satisfactions by refining the content based recommendation system to suggest better sources to their users. A clustering approach has been used to carry out this improvement. An attempt has been made to define a cluster threshold for clustering the same news and information in the K-means clustering algorithm. By detecting best resemblance criterion value and using an external knowledge base (ontology), we could generalize words into a set of related words (instead of using them alone). This approach is promoted the accuracy of news clustering and use the provided cluster to find user’s favorite news and also could have suggest the news to the user. Since the dataset has an important and influential role in advisory recommended systems, the standard Persian dataset is not provided and not published yet. In this research, an attempted has been made to connect and publish the dataset to finish the effect of this vacuum. The data are collected and crawl 8 periods of days from the Tabnak news agency website. The profile of each volunteers has been created and also saved at the same time as they read the favorite news on that period of time. An analysis shows that the proposed clustering approach provided by the NMI criterion has reached 70.2%  on our the dataset. Also, using the suggested clustering recommendation system yield 89.2% performance based on the accuracy criterion, which shows an improvement of 8.5% in a standardized way.

    Keywords: Recommender system, Persian news, Hierarchical clustering, Ontology
  • Mahmoud Naghibzadeh, Samira Babaei, Behshid Behkmal*, Mojtaba Hatami Pages 48-56

    discovering mutations in DNA sequences is the most common approach to diagnosing many genome-related diseases. The optimal alignment of DNA sequences is a reliable approach to discover mutations in one sequence in comparison to the reference sequence. Needleman-Wunsch is the most applicable software for optimal alignment of the sequences and Smith-Waterman is the most applicable one for local optimal alignment of sequences. Their performances are excellent with short sequences, but as the sequences become long their performance degeneration grows exponentially to the point that it is practically impossible to align the sequences such as compete human DNAs. Therefore, many researches are done or being conducted to find ways of performing the alignment with tolerable time and memory consumptions. One such effort is breaking the sequences into same number of parts and align corresponding parts together to produce the overall alignment. With this, there are three achievements simultaneously: run time reduction, main memory utilization reduction, and the possibility to better utilize multiprocessors, multicores and General-Purpose Graphic Processing Units (GPGPUs).  In this research, the method for breaking long sequences into smaller parts is based on the divide and conquer approach. The breaking points are selected along the longest common subsequence of the current sequences. The method is evaluated to be very efficient with respect to both time and main memory utilization which are the two confining factors.

    Keywords: DNA sequence alignment, divide, conquer approach, longest common subsequence, big genome data, desease diagnosis