Browsing by Author "Yildiz, Zehra"

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    Citation Count: 3
    Evaluation of Student Performance in Laboratory Applications using Fuzzy Decision Support System Model
    (Ieee, 2014) Yildiz, Zehra; Baba, A. Fevzi
    In recent years, the importance of laboratory applications in engineering education has increased because, there is need for transferring the theoretical knowledge to empirical research and practice, which is particularly significant for the development of students in their career. Therefore, the evaluation of these laboratory applications should be effective. In this study, we propose a new approach to this assessment system. Our approach uses fuzzy decision support system and proposes a new approach that is called 'refinement process' on student grades. Fuzzy helps more reliable decision making and evaluation of applications using a pre-determined list of criteria. This model based on fuzzy multi criteria method, is developed for evaluating student performances in laboratory activities which consolidate theoretical knowledge with practical applications. In our approach, we use peer assessment, group assessment and personal assessment methods. This study shows that fuzzy system can provide a better evaluation system than classical systems.
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    Citation Count: 7
    PARALLELIZATION OF BITONIC SORT AND RADIX SORT ALGORITHMS ON MANY CORE GPUS
    (Ieee, 2013) Yildiz, Zehra; Aydin, Musa; Yilmaz, Guray
    Data sorting is used in many fields and plays an important role in defining the overall speed and performance. There are many sorting categories. In this study, two of these sorting algorithms that are bitonic sort and radix sort are dealt with. We have designed and developed Radix Sort and Bitonic Sort algorithms for many core Graphics Processing Units (GPUs). Although bitonic sort is a concurrent sorting algorithm, radix sort is a distribution sorting algorithm, i.e. both of these algorithms are not usual sorting algorithms. They can be parallelized on GPUs easily to get better performance than other sorting algorithms. We parallelized these sorting algorithms on many core GPUs using the Compute Unified Device Architecture (CUDA) platform, developed by NVIDIA Corporation and got some performance measurements.