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Assessment of cognitive load using multimedia learning and resting states with deep learning perspective by Qayyum, A., Faye, I., Malik, A.S., Mazher, M.

“…It is a well-understood fact that the brain activity increases with the increased demand of cognition. The deep learning algorithm based on Pre-trained convolutional neural network (CNN) networks have been used as a transfer learning for the classification of rest and cognitive states and also assessed the cognitive load using brain waves particularly alpha wave. …”
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Detection and classification of conflict flows in SDN using machine learning algorithms by Mutaz Hamed Hussien Khairi, Sharifah Hafizah Syed Ariffin, Nurul Mu'azzah Abdul Latiff, Kamaludin Mohamad Yusof, Mohamed Khalafalla Hassan, Fahad Taha Al-Dhief, Mosab Hamda, Suleman Khan, Muzaffar Hamzah

“…Moreover, applying machine learning algorithms in the identification and classification of conflicting flows has limitations. …”
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

“…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

“…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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Daily maximum load forecasting of consecutive national holidays using OSELM-based multi-agents system with weighted average strategy by Yap K.S., Yap H.J.

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Fault classification in smart distribution network using support vector machine by Chuan O.W., Ab Aziz N.F., Yasin Z.M., Salim N.A., Wahab N.A.

“…In this paper, a machine-learning algorithm known as Support Vector Machine (SVM) for fault type classification in distribution system has been developed. …”

A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem by Lee, Wei Wen, Hashim, Mohd Ruzaini

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Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification by Abdul Wahit, Mohamad Aizat

“…Furthermore, the Support vector machine (SVM) and Linear discriminant analysis (LDA) machine learning for the hand posture classification based on the EMG signal pattern were investigated and compared in term of classification performance. …”
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

“…Several variants of PSO have been proposed for solving discrete optimization problems like TSP. Among them, the basic algorithm is the Swap Sequence based PSO (SSPSO), however, it does not perform well in providing high quality solutions. …”
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Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

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An algorithm for the selection of planting lining technique towards optimizing land area: an algorithm for planting lining technique selection by Md Badarudin, Ismadi, Md Sultan, Abu Bakar, Sulaiman, Md. Nasir, Mamat, Ali, Tengku Muda Mohamed, Mahmud

“…This algorithm solution generated the dataset based coordinates areas to analyze the techniques. …”
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Cyberbullying detection: a machine learning approach by Yeong, Su Yen

“…Those algorithms are used in the classification or regression model to predict an input. …”
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Synthesis of transistor chaining algorithm for CMOS cell layout using euler path / Sukri Hanafiah by Hanafiah, Sukri

“…After discussing about the introduction (the basic of CMOS transistor ), we will discuss how to create the Optimal layout of CMOS Functional Array with the minimum separation based on euler path method. …”
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Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators by Abed I.A., Sahari K.S.M., Koh S.P., Tiong S.K., Jagadeesh P.

“…A method based on Electromagnetism-Like algorithm (EM) and Genetic Algorithm (GA) is proposed to determine the time-optimal task scheduling for dual robot manipulators. …”

Algorithm development for optimization of a refrigeration system by Izzat, Mohamad Adnan

“…This thesis deals with algorithm development for optimization of a refrigeration system. …”
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Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques by Mas Ira Syafila, Mohd Hilmi Tan, Mohd Faizal, Jamlos, Ahmad Fairuz, Omar, Kamarulzaman, Kamarudin, Mohd Aminudin, Jamlos

“…However, a few overlapped NIRs’ spectral data between healthy and infected samples require for further validation which chemometric and machine learning (ML) classification technique are chosen. …”
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The design and applications of the african buffalo algorithm for general optimization problems by Odili, Julius Beneoluchi

“…Optimization, basically, is the economics of science. …”
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Gender Classification: A Convolutional Neural Network Approach by Shan, Sung Liew, Mohamed, Khalil-Hani, Syafeeza, Ahmad Radzi, Rabia, Bakhteri

“…Unlike in conventional CNNs, we replace the convolution operation with cross-correlation, hence reducing the computational load. The network is trained using a second-order backpropagation learning algorithm with annealed global learning rates. …”
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