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Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

“…There exist several types of classification algorithms, and these are based on various bases. The classification performance varies based on the dataset velocity and the algorithm selection. …”
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A New Mobile Botnet Classification based on Permission and API Calls by Yusof, M, Saudi, MM, Ridzuan, F

“…As a result, 16 permissions and 31 API calls that are most related with mobile botnet have been extracted using feature selection and later classified and tested using machine learning algorithms. The experimental result shows that the Random Forest Algorithm has achieved the highest detection accuracy of 99.4% with the lowest false positive rate of 16.1% as compared to other machine learning algorithms. …”

A new mobile botnet classification based on permission and API calls by Yusof M., Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan

The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Optimal energy management strategies for hybrid electric vehicles : A recent survey of machine learning approaches by Jui, Julakha Jahan, Mohd Ashraf, Ahmad, Molla, Md Mamun, Muhammad Ikram, Mohd Rashid

“…This article presents a current analysis of various EMSs proposed in the literature. It highlights the shift towards integrating machine learning and artificial intelligence (AI) breakthroughs in EMSs development. …”
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Benchmarking Robust Machine Learning Models Under Data Imperfections in Real-World Data Science Scenarios by Marlindawati, ., Mohammad, Azhar, Esha, Sabir

“…Multiple classical machine learning algorithms and deep learning models were assessed across diverse benchmark datasets. …”
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Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning by Lim, Wai Ping, Goh, Ching Pang

“…Focusing on clustering algorithms, the study employs popular methods like K-Means Clustering, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Agglomerative Hierarchical Clustering, and Mean Shift Clustering to understand customer characteristics and behaviors. …”
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A conceptual Malaysian private healthcare university-of-the-future business model: staying relevant in the digital and post-covid era by Saiid, Muhammad, Bah, Ahmadou Pathe, Ahmad Dahlan, Abdul Rahman

“…The results from the analysis and design of the BMC and SC indicate that the principal changes required to digitally transform the university to a UotF include: the adoption of an open learning system for flexible and lifelong learning; transitioning the campus to a more 'smart', eco-friendly and sustainable campus; incorporating the latest artificial intelligence, machine learning algorithms, and data analytics to improve the university‘s management systems and enhance delivery mechanisms for teaching and learning; and to improve community engagement relationships and partnerships to deliver value to the economic, health and safety of the society, as well as to leverage the open learning system to provide curated courses to niche categories of students locally and globally.…”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system by Islam N.N., Hannan M.A., Shareef H., Mohamed A.

Classification of chest radiographs using novel anomalous saliency map and deep convolutional neural network by Md. Ali, Mohd. Adli, Abidin, Mohd Radhwan, Nik Muhamad Affendi, Nik Arsyad, Abdullah, Hafidzul, Rosman, Daaniyal Reesha, Badrud'din, Nu'man, Kemi, Faiz, Hayati, Farid

“…The rapid advancement in pattern recognition via the deep learning method has made it possible to develop an autonomous medical image classification system. …”
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Ethical Considerations in the Use of AI in Learning and Teaching for Special Education. by Noor Aida, Md Noor, Siti Noor Aneeis, Hashim, Juereanor, Mat Jusoh, Leha, Saliman, Shazali, Johari, NorHamidah, Ibrahim, Zaim Azizi, Abu Bakar, Mohd Norazmi, Nordin

“…The paper concludes by proposing a set of normative guidelines for educators, developers, and policymakers to foster an inclusive and ethically sound AI-augmented learning ecosystem.…”
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Computer vision that can ‘see’ in the dark by Wong, Yan Chiew, Ahmad Radzi, Syafeeza, Goh, Shi Yong, Sarban Singh, Ranjit Singh

“…Insufficient lighting environment has raised challenges for night shift workers’ safety monitoring. Thus, we have developed a computer vision-based algorithm recognizing 11 actions based on action recognition in dark (ARID) dataset. …”
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Enhanced recognition methods for text and slider CAPTCHA vulnerability assessment by Xing, Wan

“…To address the limitation of traditional color enhancement algorithms that lack adaptive learning capabilities, three types of Variation Color Shift (VCS) algorithms have also been proposed for data augmentation. …”
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Developing students' mathematical thinking: how far have we came? by Md. Yunus, Aida Suraya

“…Several findings from studies that focused on students' ability to provide reasoning and give meanings to concepts and algorithms are highlighted. Students' development in geometric thinking based van Hiele's levels of geometric thinking in learning, shapes and spaces is also discussed. van Hiele's levels of geometric thinking includes higher order thinking and decision making skills and acquisition of mathematical concepts to enable learners to operate at higher levels in van Hiele's theory. …”
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Future trends in auditing: preparing for a technology-driven landscape by Muhammad Arnim, Nur Afiqah Najwa, Abd Razak, Siti Noor Azmawaty

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Operational matrix based on orthogonal polynomials and artificial neural networks methods for solving fractal-fractional differential equations by Shloof, Aml Melad Asan

“…We also investigated numerical illustrations by varying the values of fractional and fractal parameters as well as the number of terms from truncated shifted Legendre polynomials (SLPs) and shifted Jacobi polynomials (SJPs). …”
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Mapping of oil palm land cover using integration of cloud computing, machine learning and big data by Shaharum, Nur Shafira Nisa

“…Random Forest (RF) machine learning algorithm was utilised to produce and classify the land cover maps covering the Peninsular Malaysia. …”
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Postal address handwritten recognition using convolutional neural network / Nur Hasyimah Abd Aziz by Abd Aziz, Nur Hasyimah

“…Next, the system was successfully developed by implementing the best CNN model as a classifier. …”
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Sound quality classification of wood used for Sarawak traditional musical instrument- Sape / Wong Tee Hao by Wong , Tee Hao

“…To address dataset imbalances, Synthetic Minority Oversampling Technique was used, enhancing dataset quality before training 40 machine learning classification algorithms. Among these, the Gaussian-kernel Support Vector Machine stood out, achieving remarkable performance with 88.18% validation and 93.37% test accuracies. …”
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