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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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Hybrid multilayered perceptron network for classification of bundle branch blocks by Megat Syahirul Amin, Megat Ali, Ahmad Nasrul, Norali, Aisyah Hartini, Jahidin

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Development of learning algorithm of passive joint for 3R under-actuated robot / Mohd Amiruddin Fikri Yaakob by Yaakob, Mohd Amiruddin Fikri

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Algorithm animation for cryptanalysis of caesar and hill ciphers / Sapiee Haji Jamel and Giuseppina Sherry Sayan by Jamel, Shafie, Sayan, Giuseppina Sherry

“…Each of the steps involved in the cryptanalysis is shown using animation technique developed using Macromedia Flash. This application is suitable for e-learning activities for students interested in the cryptanalysis of block cipher.…”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

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The development and implementation of web content adaptation and negotiation based on user, device and network profiles / Harizah Sazali by Sazali, Harizah

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Optimization of Motion Compensated Block-Based DCT Video Compression for Software Implementation by Chen, Soong Der

“…This thesis focuses on ways to improve the existing solutions in the algorithmic and implementation aspects. For the algorithmic aspect, the basic principles of motion compensated DCT block-based compression scheme was studied. …”
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A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network by Mohammad Azmi Ridwan, Dr.

“…This thesis proposes a hybrid ML-based intrusion detection system (ML-IDS) and ML-based intelligent routing algorithm (ML-RA) for MPLS network. The research is divided into three parts, which are (1) dataset development, (2) algorithm development, and (3) algorithm performance evaluation. …”

Accident Prevention Block to Move an Automobile From Traffic Collision by Rajiv, Charles Samuel

“…This proposed solution is fueled by recent technological advancements like IoT (Internet of Things) and Machine Learning. In the present work, an attempt has been made to propose an accident prevention block in automobiles that can sense the tired/sleepy driver via a camera and algorithms, to maneuver the vehicle to safety. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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Video Surveillance Image Enhancement Using Deep Learning by Aminudin, Muhamad Faris Che

“…To achieve the goal, Deep Learning Image Enhancement (DLIE) is proposed. There are two deep learning blocks which are Deep Learning Block 1 and Deep Learning Block2 (DLB1 and DLB2) and image fusion in the proposed DLIE model. …”
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BIOLOGICAL INSPIRED INTRUSION PREVENTION AND SELF-HEALING SYSTEM FOR CRITICAL SERVICES NETWORK by MOHAMED AHMED ELSHEIK, MUNA ELSADIG

“…The design features of the proposed system are inspired by the human immune system, integrated with pattern recognition nonlinear classification algorithm and machine learning. Firstly, the current intrusions preventions systems, biological innate and adaptive immune systems, autonomic computing and self-healing mechanisms are studied and analyzed. …”
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Development of unconstrained handwritten digit extraction, segmentation and recognition on bank cheques using artificial neural network by Francis, Adam

“…The third objective is to perform Vertical Splitting Algorithm technique for digit segmentation. And lastly, to develop an Artificial Neural Network for digit recognition. …”
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Spiking Neural Network For Energy Efficient Learning And Recognition by Wong, Yan Chiew, Wang, Ning Lo

“…This work presents essential properties of a spiking feedforward computing system that emulates the behaviour of biological neural networks, showing the potential for learning and classification in significantly reduced energy resources…”
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Blood cell classification using deep learning by Liaw, Mun Kin

“…The motivation was gotten from the literature review section where various researchers developed their own methods manually through experimenting such as ensemble methods, learning algorithms, combined methodologies, etc. …”
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An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications. by S. Ahmed, Bestoun, Enoiu, Eduard, Afzal, Wasif, Kamal Z., Zamli

“…We applied Q-EMCQ on 37 real-world industrial programs written in Function Block Diagram (FBD) language, which is used for developing a train control management system at Bombardier Transportation Sweden AB. …”
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Raspberry Pi-Based Finger Vein Recognition System Using PCANet by Quek, Ee Wen

“…PCA is employed for learning multistage filter banks. Binary hashing and block histograms are the steps for indexing and pooling. …”
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Human hearing disorder recognition model using eeg-aep based signal by Md Nahidul, Islam

“…This study investigated two conventional machine learning algorithms: support vector machine (SVM) and k-nearest neighbors (KNN), and two deep learning techniques: convolutional neural network (CNN) and improved-VGG16 model. …”
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An enhanced synthetic oversampling framework with self-supervised contrastive learning for multi-class image imbalance by Xiaoling, Gao

“…Class imbalance significantly affects the performance of machine learning and deep learning classifiers, especially in image recognition tasks where certain classes are underrepresented. …”
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