فهرست مطالب

Advances in Computer Research - Volume:8 Issue: 2, Spring 2017

Journal of Advances in Computer Research
Volume:8 Issue: 2, Spring 2017

  • 130 صفحه،
  • تاریخ انتشار: 1396/03/08
  • تعداد عناوین: 9
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  • Hamed Nikookar *, Ahmad Patooghy Pages 1-11
    Due to employ of embedded systems for safety-critical applications and high probability of occurrence transient faults in them as well as increasing popularity of COTS (commercial off the shelf) components, techniques of control flow checking to improve reliability processors are of particular importance. Among all the problems of software-based technique for control flow error detection can be pointed to the performance overhead because of software redundancy and lack of proper solution for detecting Intra-block control-flow jump errors. In this article we have proposed a generic software-based technique for control flow error detection that can add instructions redundant on a basic block to detect a large number of errors as well as reduced overhead by identifying S-NODE in control flow graph and placed check instruction in these nodes. Overall, combining CFCSS (Control Flow Checking by Software Signatures) with our proposed technique has an average of 96% fault coverage in comparison to 92% fault coverage of previously proposed signature based techniques while maintaining the performance overhead has nearly SCFC.
    Keywords: COTS (Commercial-Off-The-Shelf), Control-Flow Checking, Embedded Systems, Transient Fault
  • Mostafa Boroumandzadeh * Pages 13-19
    It's important and necessary to detect and prove the ownership of a digital work in the communication technology era. The purpose of this paper is to propose a digital watermarking scheme for images. In this scheme, first, a watermark signal is produced by a chaotic sequence. Then the watermark is placed in the cosine transform coefficients of a host image. Next, the watermarked image is exposed to some attacks such as filtering, compression, rotation and addition of noise. The simulation results show the ability of the proposed method in maintaining the watermark after conducting these attacks. In the following, in addition to comparing the propose method with other similar methods, the superiority of this scheme over other methods will be remarkable and confirm able. In the following, in addition to comparing the propose method with other similar methods, the superiority of this scheme over other methods will be remarkable and confirm able.
    Keywords: Security, discrete cosines transform (DCT), robustness, watermarking, chaotic sequence
  • Sosan Sarbazfard, Ahmad Jafarian * Pages 21-38
    In this paper, a new and an e ective combination of two metaheuristic algorithms, namely Fire y Algorithm and the Di erential evolution, has been proposed. This hybridization called as HFADE, consists of two phases of Di erential Evolution (DE) and Fire y Algorithm (FA). Fire y algorithm is the nature- inspired algorithm which has its roots in the light intensity attraction process of re y in the nature. Di erential evolution is an Evolutionary Algorithm that uses the evolutionary operators like selection, recombination and mutation. FA and DE together are e ective and powerful algorithms but FA algorithm depends on random directions for search which led into retardation in nding the best solution and DE needs more iteration to nd proper solution. As a result, this proposed method has been designed to cover each algorithm de ciencies so as to make them more suitable for optimization in real world domain. To obtain the required results, the experiment on a set of benchmark functions was performed and ndings showed that HFADE is a more preferable and e ective method in solving the high-dimensional functions.
    Keywords: Differential Evolution, Firefly Algorithm, Global Optimization, Hybrid Algorithm
  • Farhad Rad *, Zahra Moghtaderinasab, Hamid Parvin Pages 39-51
    Energy is one of the most important criteria in wireless sensor networks. To extend the lifetime and coverage in these networks, researchers are always looking for ways that they can reduce the energy consumption of sensor nodes. Clustering methods sensor nodes is one of the best ways that can significantly increase the lifetime of the network. The hierarchical clustering protocols will have a more effective role. In this protocols, how to build a cluster, the cluster and data transmission methods, including issues that have a significant role in energy consumption. Hence, this paper, we study the reduction of energy consumption Wireless Sensor Networks one of the following methods called W-LEACH focused and to improve the algorithm equation suggests that the density of nodes in each round clustering is used in a more effective way. Simulation of MATLAB environment, shows that the proposed method than other methods such as LEACH, DE-LEACH, LEACH-C, L-LEACH, W-LEACH is able to increase network lifetime and energy consumption of sensor nodes be less.
    Keywords: Network lifetime, Clustering, W-LEACH, Energy consumption
  • Saeed Jafari, Sedigheh Ghofrani * Pages 53-66
    For any coherent imaging systems including ultrasound, synthetic aperture radar and optical laser, the multiplicative speckle noise degrades both the spatial and contrast resolution of the image. So, speckle suppression or despeckling is necessary before processing like image segmentation, edge detection, and in general any medical diagnosis. It is quite a mind-numbing task to analyze the corrupted images. Among many methods that have been proposed to perform this task either in spatial domain or in transformed domain, there exists a class of approaches that use coefficient modelling in transform domain. In this paper, we proposed a novel despeckling method in the nonsubsampled shearlet transform (NSST) domain with coefficient modelling. We used Bayesian maximum a posteriori (MAP) estimator with the priori assumption as heavy-tailed Lévy (HTL) distribution for estimating the noise-free NSST coefficients. Finally, experiments show that the proposed method outperforms others in terms of visual evaluation and image assessment parameters.
    Keywords: nonsubsampled shearlet transform, heavy-tailed Lévy distribution, medical ultrasound images despeckling
  • Leila Pourabdi *, Ali Harounabadi Pages 67-77
    Money-Laundering causes a higher prevalence of crime and reduces the desire tending to invest in productive activities. Also, it leads to weaken the integrity of financial markets and decrease government control over economic policy. Banks are able to prevent theft, fraud, money laundering conducted by customers through identification of their clients’ behavioral characteristics. This leads to reduce the banking and credit risks. So there are some systems in order to identify unusual users’ behavior in banking industry that can help different societies. In present study, effective variables are used to determine suspicious behavior in terms of money-laundering from users’ account transactions in an Iranian private bank. Users’ membership degree to clusters is determined using fuzzy clustering method and maximum membership degree is considered as a label for users; also, back propagation neural network is used to identify the model. The results show that the proposed method can detect money-laundering accurately at the bank up to 97%.
    Keywords: Money-Laundering, Fuzzy Clustering, Membership Degree, Neural Network
  • Somayeh Taherian Dehkordi *, Vahid Khatibi Bardsiri Pages 79-93
    The need for calculating actions has been emerged everywhere and in any time, by advancing of information technology. Cloud computing is the latest response to such needs. Prominent popularity has recently been created for Cloud computing systems. Increasing cloud efficiency is an important subject of consideration. Heterogeneity and diversity among different resources and requests of users in the Cloud computing environment creates complexities and problems in task scheduling in the cloud environment. Scheduling consists of selecting the most appropriate resource with the aim to distribute load in resources, and maximum productivity from them, while it should minimize the response time and the time of completion of each task, as well as minimizing the service costs. In addition to analyzing the Cloud computing system and scheduling aspects in it, it has been tried in this article to provide a combined algorithm for appropriate mapping of tasks to the existing virtual machines for reducing the completing times and increasing the productivity of virtual machines. According to the scheduling parameters, the presented method improves the load balancing according to the Sufferage and genetic algorithm as compared to previous algorithms, while it also reduces the total time of requests. The results of simulating the proposed algorithm in CloudSim environment and comparing it with the studied methods show that the proposed algorithm has reached a more optimized response, both for the load balancing and also for the total completion time.
    Keywords: Cloud Computing, Task scheduling, Genetic, Sufferage
  • Zeynab Sasan *, Majid Salehi Pages 95-102
    In the field of computer networks, the introduction of SDN has been associated with new concepts. In SDN networks, control plane is separated from the data palne. Traditional networks suffer from difficult configuration and management. In other words, a change in the network needs to be configured on the whole equipment. With the introduction of SDN, various modules can be designed and run in controller in order to perform expected policies and rules on all switches. One of the areas of network management is to deal with cyber-attacks. In SDN networks, security modules can be designed to run in the controller and generate rules on switches. Due to the importance of intranets, this paper aimed to detect and prevent ARP poisoning attack on LAN. The tests in a LAN showed that the module can detect the ARP poisoning attack and block the attacker operation.
    Keywords: Software Defined Networking, ARP Poisioning Attack, Network Security, Mininet, POX
  • Khadijeh Mirzaei Talarposhti *, Mehrzad Khaki Jamei Pages 103-124
    Automatic lip-reading plays an important role in human computer interaction in noisy environments where audio speech recognition may be difficult. However, similar to speech recognition, lip-reading systems also face several challenges due to variances in the inputs, such as with facial features, skin colors, speaking speeds, and intensities. In this study a new method has been proposed for extracting features from a video containing a certain Persian words without any audio signal. The method is based on the fast furrier transform combined with the color specification of the frames in the recorded video of the spoken word. To improve the system performance visual word has been used as the shortest element of visual speech. Five speaker, three men and two women, have participated for capturing the videos of the spoken words. After obtaining features from the videos an artificial neural network has been employed as classifier. The experimental results show the average accuracy about 86.8% in recognition 31 Persian words.
    Keywords: Automatic Lip-Reading, Fast Furrier Transform, Visual Word, Artificial Neural Network