Search Results - (( java implementation graph algorithm ) OR ( program learning mode algorithm ))
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…In the benchmark paper, the result of implementation of LACE algorithm in 400, 600, 800 and 1000 servers were plotted at different graphs. …”
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Fostering motivation in TVET students: the role of learner-paced segments and computational thinking in digital video learning
Published 2024“…In recent years, digital video courseware has emerged as an effective tool for enhancing learning experiences, particularly in Technical and Vocational Education and Training (TVET) programs. …”
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Priority and dynamic quantum time algorithms for central processing unit scheduling
Published 2018“…The proposed algorithms (Priority Dynamic Quantum Time and Multi Priority Dynamic Quantum Time Algorithms) are implemented using JAVA programming language and validated using Key Performance Indicators equations. …”
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Spiking Neural Network For Energy Efficient Learning And Recognition
Published 2020“…The use of applications consumes energy and hard to perform through standard programmed algorithms. Spiking neural networks have emerged that achieve favourable advantages in terms of energy and time efficiency by using spikes for computation and communication as well as solving different problems such as pattern classification and image processing. …”
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs
Published 2019“…Therefore, this study proposed a cost-cognizant TCP approach for object-oriented software that uses path-based integration testing to identify the possible execution path extracted from the Java System Dependence Graph (JSDG) model of the source code using forward slicing technique. …”
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Dynamic and adaptive execution models for data stream mining applications in mobile edge cloud computing systems / Muhammad Habib Ur Rehman
Published 2016“…The critical factors of complexity at application level include data size and data rate of continuously streaming data, the selection of data fusion and data preprocessing methods, the choice of learning models, learning rates and learning modes, and the adoption of data mining algorithms. …”
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