Accepted Papers


  • COMPARING THE CUCKOO ALGORITHM WITH OTHER ALGORITHMS FOR ESTIMATING TWO GLSD PARAMETERS
    Dr. Jane Jaleel Stephan, Dr. Haitham Sabah Hasan and Alaa Hamza Omran,University of Information Technology & Communications, Iraq
    ABSTRACT

    This study introduces and compares different methods for estimating the two parameters of generalized logarithmic series distribution. These methods are the cuckoo search optimization, maximum likelihood estimation, and method of moments algorithms. All the required derivations and basic steps of each algorithm are explained. The applications for these algorithms are implemented through simulations using different sample sizes (n = 15, 25, 50, 100). Results are compared using the statistical measure mean square error.

  • A Strategy of Dynamic Error Correction Code for Defect Tolerance Improvement on Flash Memory
    Yi-Cheng Chung and Chung-Ho Chen Department of Electrical Engineering and Institute of Computer and Communication Engineering National Cheng-Kung University,Taiwan
    ABSTRACT

    Conventional flash controller uses static error correction code (ECC) to recover limited bits of data from erroneous flash pages. The performance is not quite satisfactory because the error correction capability is limited by the static ECC field within the flash page. In order to utilize the spare area used for storing ECC field among each flash page more efficiently, this work proposes a dynamic ECC strategy that conceptually regards most of the ECC fields within a flash block as a single pool and adaptively allocates the ECC fields to each flash page in accordance with the emerging defects on the flash page. Two defect distribution models are introduced to the dynamic ECC strategy and the conventional error correcting method for comparison. The result shows the proposed method can greatly improve the defect tolerance if the defects occur densely within a region of a few data pages.

  • A Cohesion Based Friend Recommendation System
    ShamsuShehu,Al-qalam University Katsina,Nigeria
    ABSTRACT

    Social network sites have attracted millions of users with the social revolution in Web2.0. A social network is composed by communities of individuals or organizations that are connected by a common interest. Online social networking sites like Twitter, Facebook and Orkut are among the most visited sites in the Internet. In the social network sites, a user can register other users as friends and enjoy communication. However, the large amount of online users and their diverse and dynamic interests possess great challenges to support such a novel feature in online social networks. In this work, we design a general friend recommendation framework based on cohesion after analyzing the current method of friend recommendation. The main idea of the proposed method is consisted of the following stages- measuring the link strength in a network and find out possible link on this network that is yet to be established; detecting communities among the network using modularity and recommending friends. Considering the noticeable attraction of users to social networking sites, lots of research has been carried out to take advantage of the users ‘information available in these sites. Knowledge mining techniques have been developed in order to extract valuable pieces of information from the users’ activities. This paper deals with a methodology to generate a social graph of users’ actions and predict the future social activities of the users based upon the existing relationships. This graph is updated dynamically based on the changes in the selected social network. The forecasting performed is based upon some predefined rules applied on the graph elaborated.

  • A COMPARATIVE EVALUATION OF DATA LEAKAGE/LOSS PREVENTION SYSTEMS (DLPS)
    Kamaljeet Kaur1, Ishu Gupta2 and Ashutosh Kumar Singh2 1 Govt. Sr. Sec. School, Ambala, Haryana, India,2Department of Computer Applications, National Institute of Technology, Kurukshetra, Haryana, India
    ABSTRACT

    Data is the most valuable assets of an organization that need to be secured. Due to limited computational resources, Customers outsource their workload to cloud and economically enjoy the massive computational power, bandwidth, storage, and even appropriate software that can be shared in a pay-per-use manner. Despite of tremendous benefits of cloud computing, protection of customers’ confidential data is a major concern. Data leakage involves the intentional or unintentional release of secure or confidential information to non-trusted environment. Data leakage poses a serious issue for companies as the number of incidents and the cost to those experiencing them continue to increase. Data leakage is enhanced by the fact that transmitted data (both inbound and outbound); including emails, instant messaging, website forms and file transfers. Data leakage prevention system (DLPS) is a strategy for making sure that end users do not send the confidential data or information outside the corporate network. This review paper aims to study data leakage prevention through some challenges and data protection approaches as well as considering some limitations. This survey of DLPS can benefit academics as well as professionals.

  • A SECURITY PERIOD UPDATE METHOD USING EVALUATION FUNCTION FOR IMPROVING ENERGY EFFICIENCY OF STATISTICAL EN-ROUTE FILTERING BASED WSNs
    Jung-Sub Ahn and Tae-Ho Cho,Sungkyunkwan University,Republic of Korea
    ABSTRACT

    In recent years, WSN research is being carried out to obtain high security and energy efficiency. In WSN, sensor nodes are vulnerable to physical attacks because they are deployed in an open environment. An attacker can inject false report into networks using these vulnerabilities. F. Ye et al proposed Statistical En-route Filtering to prevent false report injection attacks. And in order to effectively use that scheme, that techniques for determining thresholds using fuzzy logic have been studied. So as to effectively apply these techniques to the network, an appropriate update period should be set according to the network environments. In this paper, we proposed a security period update method in order to improve the lifetime of the network in the Statistical En-route Filtering based on wireless sensor network of the cluster environment. Experimental results show up to 11.96 % improvement in energy efficiency is achieved when security threshold setting to the optimum period.

  • INVESTIGATION THE EFFECT OF USING GRAY LEVEL AND RGB CHANNELS ON BRAIN TUMOR IMAGE
    Ahmed B Salem Salamh,Department of Computer, Zawia University, Libya
    ABSTRACT

    Analysis the effect of using gray level on the Brain tumor image for improving speed of object detection in the field of Medical Image using image processing technique. Specific areas of interest are image binarization method, Image segmentation. Experiments will be performed by image processing using Matlab. This paper presents a strategy for decreasing the calculation time by using gray level and just one channel Red or Green or Blue in medical Image and analysis its impact in order to improve detection time and the main goal is to reduce time complexity.

  • ELASTIC SOFTWARE DESIGN PATTERNS
    Nazanin Fardroo 1 and Shohre Kazemi 2, 1Department of Computer Engineering, Islamic Azad University, Iran and 2Department of Computer Engineering, Islamic Azad University, Iran
    ABSTRACT

    Nowadays Cloud computing is becoming more and more popular. This because of its elastic behavior: users can acquire and release resources on-demand, which enables web application enabled to change the resources provisioned and de-provisioning resources to emerge their applications under dynamic workload in order to minimize resource cost and satisfying Quality of Service (QoS) requirements and pay only for the resources they need (pay-per-use or pay-as-you-go model). Application can adapt the resources that assigned to the application to the incoming user demand. However, best amount of resources are achieved by the required Service Level Agreement, while keeping the total cost low, is not an easy job. Many patterns and techniques have been done for auto scaling application.The main purpose of this article is an up-to-date review of the latest elasticity works and a detailed classification scheme, focusing on the elastic design patterns

  • ALUMNI TRACKING SYSTEM WITH DATA ANALYTICS FOR PANPACIFIC UNIVERISITY NORTH PHILIPPINES – TAYUG CAMPUS
    Joey Aviles,Panapcific University North Philippines Tayug Campus
    ABSTRACT

    Tracer studies help educational institutions formulate strategic plans in creating sustainable quality education or improvement. This study focused on developing a web-based alumni tracking system for Panpacific University North Philippines – Tayug Campus. The objectives of the study are to: identify the problems encountered in tracking the alumni of the university, incorporate and identify necessary features and security measures of the proposed system.

  • BLOCKCHAIN-BASED SMART CONTRACTS: A SYSTEMATIC MAPPING STUDY
    Maher Alharby and Aad van Moorsel School of Computing Science, Newcastle University, Newcastle, UK and College of Computer Science and Engineering, Taibah University, Medina, KSA
    ABSTRACT

    An appealing feature of blockchain technology is smart contracts. A smart contract is executable code that runs on top of the blockchain to facilitate, execute and enforce an agreement between untrusted parties without the involvement of a trusted third party. In this paper, we conduct a systematic mapping study to collect all research that is relevant to smart contracts from a technical perspective. The aim of doing so is to identify current research topics and open challenges for future studies in smart contract research. We extract 24 papers from different scientific databases. The results show that about two thirds of the papers focus on identifying and tackling smart contract issues. Four key issues are identified, namely, codifying, security, privacy and performance issues. The rest of the papers focuses on smart contract applications or other smart contract related topics. Research gaps that need to be addressed in future studies are provided.

  • INVESTIGATION OF COVERAGE TIME AND THE IMPACT OF HELLO PACKET IN OPEN SHORTEST PATH FIRST NETWORK
    Ahmed B Salem Salamh and Nuredeen abdullah abujela matoug University of Zawia,Zawia, libya
    ABSTRACT

    In today’s world the internet are growing up dramatically and become the major facilities to reach our resources and to communicate with other people, this increase the desired to speed up the connection of the internet which depend on different subjective, one of them delay that related to the internet components, such as a router and its elements. In this paper, we present total coverage time and how to analysis the OSPF network by using hello protocol which is the main objective to reduce the time that is taken by hello packet in point to point network.

  • IMPROVED OPTIMUM DYNAMIC TIME SLICING ROUND ROBIN ALGORITHM
    Md. Shihab Ullah1 ,1Department of Computer Science and Engineering, BRAC University, Dhaka, Bangladesh
    ABSTRACT

    In time-shared systems, selection of the time quantum plays a pivotal role in performance of CPU. In this paper, the static use of dynamic time quantum as CPU Time Slice is reviewed and a new algorithm for CPU scheduling named Improved Optimum Dynamic Time Slicing Round Robin Algorithm (IODTSRR) is proposed for process and thread scheduling. Proposed algorithm is based upon dynamic nature of allocation, calculation of the value of time quantum which varies according to the state of queue along with the capability of executing ready processes arriving at the same or different time. The performance is compared with Optimum Dynamic Time Slicing Using Round Robin (ODTSRR) and the results revealed that the proposed algorithm is better specifically in response time and turnaround time. As process gets fully or partially executed while others arrive simultaneously, context switch rates, waiting time and throughput improves hence resulting in optimized CPU performance.

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