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Prediction of COVID-19 outbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman by Mohd Azman, Muhammad Qayyum

“…A prototype architecture and a user-friendly graphical interface tailored for SVM-based outbreak predictions are developed, accompanied by detailed code snippets elucidating essential steps in data loading, encoding, scaling, and SVM model training. …”
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BLAZEBREAKER: GAMIFY THE FLAMES by SAID MOHD NAJIB, ELIAS

“…The project addresses the critical need for effective training methods to ensure occupants are well-equipped to respond to fire emergencies. …”
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A new mobile botnet classification based on permission and API calls by Yusof M., Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan

Extended development of a Computer Aided Detection (CAD) system for brain bleed in CT / Muhammad Illyas Abdul Muhji by Muhammad Illyas, Abdul Muhji

“…In this study, 227 volumes of brain CT images were used to develop and validate the CAD. The new develop algorithm is set to register image of brain patient in order to determine the rotation angle for brain realignment. …”
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Direct neuro-AVC modelling and control strategy for vibration suppression of a flexible plate structure by Mat Darus, Intan Zaurah, Tokhi, M. O.

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Steady state security analysis using artificial neural network by Mohd Nor, Nurul Huda

“…The performance of the developed model is compared with the unified neural network trained with the full feature set. …”
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Enhanced kiosks mapping on traditional market using Apriori Algorithm / Ardiansyah Dores, and Tazkiyah Herdi by Dores, Ardiansyah, Hasani, Rifqi, Herdi, Tazkiyah

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A New Mobile Botnet Classification based on Permission and API Calls by Yusof, M, Saudi, MM, Ridzuan, F

Implementing Aproiri Algorithm for Predicting Result Analysis by Abdul Aziz, Azwa, Hassan, Hasni, Wan Idris, Wan Mohd Rizhan, Jusoh, Julaily Aida

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Integration of spectroscopy and chemometric analysis for food authentication: a review by Basri, Katrul Nadia

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An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

“…The research implements stock prediction analysis as a case study for training the neural network by adopting MGWO algorithm. …”
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Development of airbag suit system for motorcyclist by Zainal Abidin, Zulkifli, Razali, Fakhruddin

“…The calibration involved a sizable collection of samples, analysis and training to set the threshold in the algorithm which decides the emergency events. …”
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Implementing Aproiri Algorithm for Predicting Result Analysis by Nurul A., Emran, Aziz, A. A., Jusoh, J. A, Idris, W. M. R. W., Hassan, H.

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An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection by Shing, Chiang Tan, Mohammed Al-Andoli, Mohammed Nasser, Kok, Swee Lim, Pey, Yun Goh, Chee, Peng Lim

“…However, most ML models have limitations in performance since the training depth is usually limited. The emergence of Deep Learning (DL) models allow more training possibilities and improvement in performance. …”
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Implementation of convolutional neural network (CNN) algorithm for autonomous robot / Tiara Kusuma Dewi ... [et al.] by Dewi, Tiara Kusuma, Saptaji, Kushendarsyah, Simarmata, Adven, Fikri, Muhamad Rausyan

“…In Indonesia, the development of autonomous robots has emerged intensively since the last coronavirus pandemic, especially the autonomous UV disinfection (A-UV) robot. …”
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Development of deep reinforcement learning based resource allocation techniques in cloud radio access network by Amjad, Iqbal

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PV fault classification: Impact on accuracy performance using feature extraction in random-forest cross validation algorithm by Muhamad Zahim, Sujod, Siti Nor Azlina, Mohd Ghazali, Mohd Fadzil, Abdul Kadir, Al-Shetwi, Ali Qasem

“…In this process, each simulated fault that are line-line faults (LLF), open-circuit faults (OCF), ground faults (GF) and partial shading (PS) dataset was divided, with 80% allocated for training and 20% for testing purposes. As the results, all SFDC models (small, medium, large-scale) developed have achieved 100% accuracy for all fault types in training simulations. …”
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SVM modelling of agarwood oil quality grading using radial basis function (RBF) and sequential minimal optimization (SMO) learning algorithms by Muhammad Haziq Haikal, Hisham, Nurlaila, Ismail, Nor Azah, Mohd Ali, Saiful Nizam, Tajuddin, Mohd Nasir, Taib

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QR factorization equalisation scheme for mode devision multiplexing transmission in fibre optics by Abbas, Sharafal-Deen Abdulkadhum

“…This is done by trying to avoid the issues accompanied with the development of the previous algorithms that have been utilized for the same goal. …”
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License plate detection using deep learning object detection models by Leong, Kar Wan

“…For example, they can be slow in detection speed, not as accurate, and is difficult to develop. Since 2012, deep learning has become an emerging technology that can solve object detection with relatively better performance. …”
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