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E4ML: Educational Tool for Machine Learning by Sainin, Mohd Shamrie, Siraj, Fadzilah

“…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
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Developing A Prediction Tool To Improve The Shading Efficiency Of The Pedestrian Zones by Khudhayer, Wael A.

“…The development of the prediction tool was conducted base on integrating three sequenced algorithms, which are sun position algorithm, shadow length and position algorithm, and expansion limit algorithm. …”
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A conceptual framework for multi-objective optimization of building performance: Integrating intelligent algorithms, simulation tools, and climate adaptation by Rong, Li, Shari, Zalina, Ab Kadir, Mohd Zainal Abidin

“…This study systematically examined recent research trends in multi-objective optimization (MOO) for building performance from 2020 to 2024 and proposed a conceptual framework integrating intelligent algorithms, simulation tools, and climate adaptation strategies. …”
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Enhanced dynamic security assessment for power system under normal and fake tripping contingencies. by A. Salih, Qusay

“…The hybrid logistic model tree (hybrid LMT) approach proposed in this study combines the symmetrical uncertainties (SU) algorithm and the logistic model tree (LMT) algorithm. …”
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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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Random forest algorithm for co2 water alternating gas incremental recovery factor prediction by Belazreg, L., Mahmood, S.M., Aulia, A.

“…RF develops multiple decision trees based on the random selection of the input data and random selection of the variables. …”
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Enhancing a cluster-based TDMA MAC protocol for vehicle-to-vehicle communications / Abubakar Bello Tambawal by Abubakar Bello , Tambawal

“…The proposed EC-TMAC protocol was evaluated through simulation and validated using a statistical analysis tool. …”
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Enhancement of medical image compression algorithm in noisy WLANS transmission by Algaet, Mustafa Almahdi

“…For image reconstruction,decoding steps based the developed quantization architecture are examined.The EICA is particularly useful where the size of the transmitted data needs to be reduced to minimize the image transmission time.For data compression with suitable and effective performance,enhanced independent components analysis (EICA) is proposed as an algorithm for compression and decompression of medical data.A comparative analysis is performed based on existing data compression techniques:discrete cosine transform (DCT), set partitioning in hierarchical trees (SPIHT),and Joint Photographic Experts Group (JPEG 2000).Three main modules,namely,compression segment (CS),transceiver segment (TRS),and outcome segment (OTS) modules,are developed to realize a fully computerized simulation tool for medical data compression with suitable and effective performance.To compress medical data using algorithms,CS module involves four different approaches which are DCT, SPIHT,JPEG 2000 and EICA.TRS module is processed by low-cost WLANs with low-bandwidth transmission.Finally,OTS is used for data decompression and visualization result.In terms of compression module,results show the benefits of applying EICA in medical data compression and transmission.While for system design,the developed system displays favorable outcomes in compressing and transmitting medical data.In conclusion,all three modules (CS,TRS,and OTS) are integrated to yield a computerized prototype named as Medical Data Simulation System(Medata-SIM) computerized system that includes medical data compression and transceiver for visualization to aid medical practitioners in carrying out rapid diagnoses.…”
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Insomnia audio therapy mobile application with music recommender system / Nur Azmina Mohamad Zamani, Nasiroh Omar and Nur Damira Huda Azmi by Mohamad Zamani, Nur Azmina, Omar, Nasiroh, Azmi, Nur Damira Huda

“…The research focused on investigating the performances of three machine learning algorithms namely Random Forest, Decision Tree and Support Vector Machine to be selected as the music recommendation tool. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Machine learning techniques for flood forecasting by Hadi F.A.A., Sidek L.M., Salih G.H.A., Basri H., Sammen S.Sh., Dom N.M., Ali Z.M., Ahmed A.N.

“…Simulations were run in the Colab software tool. The results revealed that between 1986 and 2000, there would be an average of (18?…”

An Accurate and Efficient Shooting-and-bouncing-polygon Ray Tracer For Radio Propagation Modelling by Teh, Chin Hui

“…Traversal of the CCP graph is also simpler than the binary tree. To improve CCP usability, we have developed and implemented a tool to automatically construct the CCP graph from a given set of 3D walls. …”
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Industrial datasets with ICS testbed and attack detection using machine learning techniques by Mubarak, Sinil, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Balla, Asaad, Tahir, Mohammad, Elsheikh, Elfatih A A, Suliman, F M

“…The performance metrics such as accuracy, precision, recall, F1 score are evaluated and cross validated for different ML algorithms for anomaly detection. The decision tree (DT) ML technique is optimized with pruning method which provides an attack detection accuracy of 96.5%. …”
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