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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”

Batch mode heuristic approaches for efficient task scheduling in grid computing system by Maipan-Uku, Jamilu Yahaya

“…Many algorithms have been implemented to solve the grid scheduling problem. …”
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

“…Traditional schema theory does not support Lamatckian learning, i.e, forcing the genetic representation to match the solution found by the learning algorithm. …”
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Implementation of hashed cryptography algorithm based on cryptography message syntax by Ali, Mohammed Ahnaf

“…By the end of the research, the animation and animation system will be introduced to show the basic process of network enhancement with the automated learning system.…”
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Simulation on Emotion Recognition for Autism Therapy by Adzmi, Muhammad Azrin

“…This paper mainly focusing on the simulation of emotion recognition software based on the Local Binary Pattern (LBP) algorithm to extract the features from the image. The program will be used by the therapist during therapy session with the autism child in order to create more exciting environment for them to learn about the classification of basic human emotions with the help of human-computer interaction. …”
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The basics of multi-layer feedforward neural networks / Nurul Aityqah Yaccob and Farizuwana Akma Zulkifle by Yaccob, Nurul Aityqah, Zulkifle, Farizuwana Akma

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SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment by Murad, Saydul Akbar, Zafril Rizal, M. Azmi, Muzahid, Abu Jafar Md, Bhuiyan, Md Khairul Bashar, Saib, Md, Rahimi, Nick, Prottasha, Nusrat Jahan, Bairagi, Anupam Kumar

“…To conduct this experiment, we employed the CloudSim simulator, which is implemented using the Java programming language.…”
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A new modern scheme for solving fractal–fractional differential equations based on deep feedforward neural network with multiple hidden layer by Admon, Mohd Rashid, Senu, Norazak, Ahmadian, Ali, Majid, Zanariah Abdul, Salahshour, Soheil

“…During the initial stage of the method development, the basic framework on solving FFDEs is designed. To minimize the burden of computational time, the vectorized algorithm is constructed at the next stage for method to be performed efficiently. …”
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Adaptive security architecture for protecting RESTful web services in enterprise computing environment by Beer, M.I., Hassan, M.F.

“…The proposed security architecture is constructed as an adaptive way-forward Internet-of-Things (IoT) friendly security solution that is comprised of three cyclic parts: learn, predict and prevent. A novel security component named â��intelligent security engineâ�� is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. …”
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Adaptive security architecture for protecting RESTful web services in enterprise computing environment by Beer, M.I., Hassan, M.F.

“…The proposed security architecture is constructed as an adaptive way-forward Internet-of-Things (IoT) friendly security solution that is comprised of three cyclic parts: learn, predict and prevent. A novel security component named â��intelligent security engineâ�� is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. …”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

“…The RSNN implements a novel approximation transform. The basic design for the network is provided together with the learning rules. …”
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