Search Results - (( java implication based algorithm ) OR ( progress monitoring learning algorithm ))

Development of hippocampus MRI image segmentation algorithm for progression detection of alzheimer’s disease (AD) by Gilani Mohamed, Mohamed Ahmed

“…This study indicates developing an algorithm for detecting and progressing through the hippocampus of patients with Alzheimer's disease in MRI images. …”
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An artificial intelligence approach to monitor student performance and devise preventive measures by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

“…This research evaluates the effectiveness of machine learning algorithms to monitor students� academic progress and informs the instructor about the students at the risk of ending up with unsatisfactory result in a course. …”

Student project monitoring system (SPMS) using text recognition / Muhammad Firdaus Mustapha ...[et al.] by Mustapha, Muhammad Firdaus, Ahmad, Marina, Ab Hamid, Siti Haslini, Mohamad, Roslim, Mohd Zin, Nor Asma, Nik Wan, Nik Zam

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A Systematic Approach to Transform Machine Learning Students� Performance Prediction Model into Preventive Procedures by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

“…This research evaluates the effectiveness of machine learning classifiers to monitor students� academic progress and informs the instructor about the students at the risk of producing unsatisfactory final result in a course. …”

Smart site monitoring system / Muhammad Azmi and Muhammad Naim Mahyuddin by Azmi, Muhammad, Mahyuddin, Muhammad Naim

“…Advanced data analytics and machine learning algorithms process this data, enabling the system to detect potential safety hazards, monitor construction progress, and predict resource requirements. …”
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Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit by Shah N.N.H., Razak N.N.A., Razak A.A., Abu-Samah A., Suhaimi F.M., Jamaluddin U.

“…This study demonstrates the performances of different machine learning algorithms in the classification of multiple organ failures. …”

Machine learning classifications of multiple organ failures in a malaysian intensive care unit by Norliyana, Nor Hisham Shah, Normy Norfiza, Abdul Razak, Athirah, Abdul Razak, Asma’, Abu-Samah, Fatanah, M. Suhaimi, Ummu Kulthum, Jamaludin

“…This study demonstrates the performances of different machine learning algorithms in the classification of multiple organ failures. …”
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Lower Form Grade System (LF-Grade Sys) / Norhanisha Yusof ... [et al.] by Yusof, Norhanisha, A. Sanggar, Logineey, Kalidason, Tiivashkkar, Saravanan, Puvithra

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State-of-the-art ensemble learning and unsupervised learning in fatigue crack recognition of glass fiber reinforced polyester composite (GFRP) using acoustic emission by Gholizadeh, S., Leman, Z., Baharudin, B.T.H.T.

“…This study evaluates the damage progression on glass fiber reinforced polyester composite specimens using different approaches of machine learning. …”
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Microalgae biomass and biomolecule quantification: Optical techniques, challenges and prospects by Thiviyanathan V.A., Ker P.J., Hoon Tang S.G., Amin E.P., Yee W., Hannan M.A., Jamaludin Z., Nghiem L.D., Indra Mahlia T.M.

“…Potential approaches to improve the efficiency of optical methods in monitoring microalgae culture are also emphasized. This review also elucidates the potential of machine learning and big data analytics algorithms in understanding the growth and interaction of microalgae strains as well as to aid in decision making, which can possibly encourage the participation of small-scale and large-scale farmers in microalgae cultivation. …”

My little learner : E-learning wonderland by Teoh, Wei En

“…Creating an analytic dashboard, which offers information on the child's learning, is a crucial component of the project. This feature will make it easier for kindergarten kids and parents to monitor the learning progress and identify areas for improvement, which will improve the learning process overall. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Prediction of oil and gas pipeline failures through machine learning approaches: A systematic review by Al-Sabaeei, A.M., Alhussian, H., Abdulkadir, S.J., Jagadeesh, A.

“…This review article mainly focuses on the novelty of using machine and deep learning techniques, specifically artificial neural networks (ANNs), support vector machines (SVMs) and hybrid machine learning (HML) algorithms, for predicting different pipeline failures in the oil and gas industry. …”
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My little learner: E-learning wonderland by Teoh, Wei En

“…Creating an analytic dashboard, which offers information on the child's learning, is a crucial component of the project. This feature will make it easier for kindergarten kids and parents to monitor the learning progress and identify areas for improvement, which will improve the learning process overall. …”
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Transparent insights into alzheimer’s progression: a time-aware approach with explainable by Abraham Varghese, Ben George, Vinu Sherimon, Prashanth Gouda

“…Thus, this paper contributes to the creation of a clinically relevant and practical model for monitoring Alzheimer’s disease progression that holds the potential for a deeper understanding of the evolving nature of the disease and paving the way for personalized and timely interventions.…”
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An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection by Ayodele Nojeem, Lasisi

“…The V-Detectors algorithm depends greatly on the random detectors generated in monitoring the status of a system. …”
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STeM: a web-based system for managing test artifacts in software testing course / Nor Shahida Mohamad Yusop, Adib Suhaimi Mohd Fikri and Nursyuhaila Yahaya by Yusop, Nor Shahida Mohamad, Mohd Fikri, Adib Suhaimi, Yahaya, Nursyuhaila

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Remote sensing technologies for unlocking new groundwater insights: a comprehensive review by Ibrahim, Abba, Wayayok, Aimrun, Mohd Shafri, Helmi Zulhaidi, Toridi, Noorellimia Mat

“…The evolution of the techniques analyses spans from empirical reliance on sparse point data to the assimilation of multi-platform satellite measurements using sophisticated machine learning algorithms. Key developments reveal enhanced characterisation of localised groundwater measurement by integrating coarse-resolution gravity data with high-resolution ground motion observations from radar imagery. …”
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Design and implementation of a deep learning based hand gesture recognition system for Rehabilitation Internet-Of-Things (RIOT) environments using MediaPipe by Mohd Dhuzuki, Nurul Hanis, Zainuddin, Ahmad Anwar, Kamarul Zaman, Nur Anis Sofea, Ahmad Razmi, Alin Nur Maisarah, Kaitane, Wonderful Shammah, Ahmad Puzi, Asmarani, Johar, Mohd Naqiuddin, Yazid, Maslina, Mohd Nordin, Nor Azlin, Sidek, Shahrul Naim, Mohd Zaki, Hasan Firdaus

“…The system's objective is to provide precise, real-time tracking of hand movements, enabling patients to perform exercises at home by maintaining an optimal distance between the camera and hand placement, ensuring ideal room lighting conditions across IoT devices such as mobile phones' front cameras and webcams, while healthcare professionals remotely monitor their progress. The methodology involves the integration of MediaPipe for detecting hand landmarks and adaptive sensitivity algorithms to ensure reliable recognition across different environments, such as varying lighting and hand positions. …”
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Critical review of object detection techniques for traffic light detection in intelligent transportation systems by Muhammad Adhwa, Mohd Salemi, Muhammad Arif, Mohamad

“…Despite progress in deep learning and optimization algorithms, traffic light detection still faces persistent challenges under varying conditions such as illumination changes, occlusions, and visual clutter. …”
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