Venue : Coral Deira - April 23 ~ 24, 2016, Dubai, UAE

Accepted Papers

  • Combination of Context-role and Perimeter Protection Paradigms for Modelling the Information Systems Security
    Hein Tun, Sergey Lupin and Aleksandr Gureev, National Research University of Electronic Technology, Russia
    The paper analysis a possibility of Hybrid Modelling using for the estimation of information systems ability to prevent the unauthorized access. We proposed approach which combines two paradigms of information security – context-role and protection of perimeter. AnyLogic was used for modelling and simulation the experimental model. It allows using agent and discrete event methods for description of information systems security. According to the context-role model the permission of agents determines its placement in information security hierarchy. In our approach it depends also from agent position in protected environment. Presented the structure of Anylogic model and set of data which provide the definition of agent’s behaviour and bound’s functionality. Produced simulations confirm the ease and accuracy the combined method for estimation the level of information security. The Experiments confirmed the functionality of the model and the possibility of its using for analysis of information system security.
  • Applying Genetic Algorithm to Reduce Response Time in ETL Service Composition
    Nazila Taghvaei and Fereidoon Shams, Shahid Beheshti University, Iran
    Data ETL tools, through the creation of workflow (including graphs of data conversion tasks), make it possible to process high volume of data. This workflow includes set of activities that extract data from various sources, transform and load it into a data warehouse. ETL development constitutes the most costly in both time and resources. It can take up as much as 80% of development time in a data warehouse project. Any error in designing of ETL, leads to increase data volume and then rising data access in data warehouse so that impacts on business decisions. Currently ETL workflows are designed manually, which is time consuming and sometimes with errors. Having more Complex workflows, users who can design and make them, must have a lot of knowledge to produce solutions tailored to the business objectives of the working groups. Also available ETL workflows, depend largely on a platform where they have been implemented and it is not possible to reuse them between ETL tools. In service Oriented ETL, we are following the adoption of service oriented ETL capabilities in BI systems, as can be reused ETL workflows turnover, establish interoperability between ETL tools and perform these workflows independent of the platform. Why the existing ETL tools designed and implemented by designer once, do not use any techniques to automatically optimize ETL workflow at runtime.

    Our goal in this study is optimizing ETL workflow dynamically which we implemented as a web service. To do this, we applied genetic algorithm, as an evolutionary approach to service oriented ETL, so it can be considered as an algorithm in designing of ETL tools.
  • Speaker Recognition Method Based on Feature Extraction Using Linear Dynamic Systems
    Peixian Hu and Xi Chen, Center for Intelligent and Networked Systems (CFINS), China
    In this paper, we propose a new approach to extract spectral information from voice signals as a feature denoted as signal response coefficients (SRC) for speaker recognition.The new proposed feature is based on the complex network that represents voice signal. And in our approach, the temporal/spatial conversion is used twice and the new feature is eventually calculated using the mathematical theory of linear dynamic systems. We implement our approach and carry out some experiments on TIMIT database. The preliminary results show that the proposed feature performs well in speaker recognition. The results also illustrate that the performance of recognition could be improved by combining the traditional features like Mel frequency cepstrum coefficients (MFCC) and linear prediction coefficient (LPC) with the proposed feature.
  • First-order Mathematical Fuzzy Logic with Hedges
    Van-Hung Le, Hanoi University of Mining and Geology, Vietnam
    In this paper, we consider rst-order mathematical fuzzy logic expanded by many hedges. This is based on the fact that, in the real world, many hedges can be used simultaneously, and some hedge modi es truth (or meaning of sentences) more than another hedge. Moreover, each hedge may or may not have a dual one. We expand the axiomatizations for propositional mathematical fuzzy logic with many hedges to the rst-order level and prove a number of completeness results for the resulting logics.
  • Hardware Acceleration of Smith-Waterman Algorithm for Short Read DNA Alignment Using FPGA
    Wael Abou El-Wafa, Asmaa G.Seliem and Hesham F.A.Hamed, Minia University, Egypt
    The Field Programmable Gate Arrays (FPGAs) are highly attractive options for hardware implementations of Bioinformatics algorithms as they provide physical security and potentially higher performance than software solutions. The Smith-Waterman algorithm, based on dynamic programming, is the most accurate local alignment algorithm for DNA and protein sequencing. However the existing parallel Smith-Waterman algorithm needs extra memory space and this limits the size of a sequence to be aligned. As the data of biological banks expands exponentially, so we develop a new hardware parallel bi-sequence and tri-sequence alignment algorithm, using the strategy of divide and extend. This paper suggests a hardware architecture for the Smith Waterman algorithm using Xilinx ZYNQ-7000 FPGA. Then we present the efficiency and utilization of our Parallel Smith Waterman over sequential Smith Waterman algorithm. After that the simulated implementations of the algorithm presented to perform the most suitable hardware architecture within Xilinx ZYNQ-7000 FPGA which speeds up the algorithm by 28.4x with less Utilization and 29.4 more efficiency.