Search Results - (( learning implementation based algorithm ) OR ( program implementation level algorithm ))

Students’ attitude towards video-based learning: machine learning analysis with rapid software / Abdullah Sani Abd Rahman ... [et al.] by Abd Rahman, Abdullah Sani, Meutia, Rita, Hamid, Yusnaliza, Abdul Rahman, Rahayu

“…The goals of this paper are to: 1) provide fundamental experimental works of the machine learning implementation based on a new rapid software framework and 2) present the ability of machine learning in classifying students’ attitude towards video-based learning. …”
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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

“…The results show the Q-EMCQ is also capable of outperforming the original EMCQ as well as several recent meta/hyper-heuristic including modified choice function, Tabu high-level hyperheuristic, teaching learning-based optimization, sine cosine algorithm, and symbiotic optimization search in clustering quality within comparable execution time.…”
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Impact of Computational Thinking and Computer Science (CTCS) Teaching Technique at Seleceted Schools in Sarawak : A Qualitative Analysis by Nor Iqbal, Mohd Sait, Noor'ain, Aini, Kartinah, Zen

“…This paper aimed to explore the impact of the implementation of CTCS in the teaching-learning process by obtaining descriptive information through interviews with selected teachers and students. …”
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Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi, Al-Habshi, Mohammed Mustafa

“…Objectives: The main objective of the study is to classify the severity level of FLS disease in soybean using hyperspectral reflectance data and machine learning algorithms. …”
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Investigating computational thinking among primary school students in Terengganu using visual programming by Osmanullrazi, Abdullah

“…This study had implemented a two-hours per week experiment for eight weeks which had been conducted through the subject of Information Technology and Communication. …”
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Computational Thinking : Experiences of Rural Pupils in Sarawak Primary School by Nur Hasheena, Anuar

“…The study employed embedded mixed methods design using a quasi-experimental approach which aims to provide an in-depth understanding of how pupils in remote rural area adapt and process to learning Computational Thinking skills (i.e., abstraction, algorithmic thinking, and decomposition) as well as their attitudes towards computational thinking practices by engaging in an unplugged game-based, art-based, Scratch programming and robotic activities through a revised Computational Thinking pedagogical model. …”
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Development of water surface robot system for lake sanitation and sampling / Ahmed Abdullah Omar by Ahmed Abdullah , Omar

“…Case study 1 tests the robot’s APIs in implementing a genetic algorithm for wayfinding with RTK-based localization. …”
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

“…The main objective of this paper is to propose and implement an intelligent framework documentation approach that integrates case-based learning (CBL) with genetic algorithm (GA) and Knuth-Morris-Pratt (KMP) pattern matching algorithm with the intention of making learning a framework more effective. …”

Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches by Al Mahmud, Suaib, Kamarulariffin, Abdurrahman, Mohd Ibrahim, Azhar, Haja Mohideen, Ahmad Jazlan

“…With the goal of enhancing the autonomy in mobile robot navigation, numerous algorithms (traditional AI-based, swarm intelligence-based, self-learning-based) have been built and implemented independently, and also in blended manners. …”
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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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DEEP LEARNING ALGORITHM IMPLEMENTATION FOR SHIP DETECTION IN SPOT SATELLITE IMAGES by HANIZAM, MOHD HAZIQ NAZMI

“…The deep-learning algorithm to be deployed is Faster R-CNN and to be implemented using MATLAB. …”
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Control algorithm for two-tank system using multiparametric programming by Zakaria, A., Mid, E.C., Mohamed, M.F., Hussin, M.H.M., Shaari, A.S., Ruslan, Eliyana, Hadi, Dayanasari, Masri, M.

“…In conclusion, the implementation of multiparametric programming is able to estimate the value of the output for the control algorithm of the two-tank system.…”
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Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.] by Mohd, Thuraiya, Jamil, Syafiqah, Masrom, Suraya, Ab Rahim, Norbaya

“…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

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Implementation of AES algorithm into information investigation autopsy (IIA) / Ahmad Wafiy Hamad Zaki by Hamad Zaki, Ahmad Wafiy Hamad Zaki

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Implementation of machine learning algorithm in preventing network congestion by Noorazimah binti Ali Sabri

Needleman wunsch implementation for SPAM/UCE inline filter by Tamil E.M., Idris M.Y.I., Thong C.M., Jali M.Z., Madihah Mohd Saudi

Low-level hybridization scripting language with dynamic parameterization in PSO-GA / Suraya Masrom by Masrom, Suraya

“…However, in many cases, implementing the suitable hybrid algorithms for a given optimization problem is a considerably difficult, which in most cases, is time consuming. …”
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Mobile machine vision for railway surveillance system using deep learning algorithm by Kit, Guan Lim, Daniel Siruno, Min, Keng Tan, Chung, Fan Liau, Sha, Huang, Tze, Kenneth Kin Teo

“…In this paper, object detection model is developed and implemented with deep learning algorithm. Object classification model is produced through the model training with Deep Neural Networks (DNN). …”
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Low-level hybridization scripting language with dynamic parameterization in PSO-GA / Suraya Masrom by Masrom, Suraya

“…However, in many cases, implementing the suitable hybrid algorithms for a given optimization problem is a considerably difficult, which in most cases, is time consuming. …”
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