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Data mining techniques for disease risk prediction model: A systematic literature review
Published 2023Conference Paper -
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Mobile Learning: An Application Prototype for AVL Tree Learning Object
Published 2010“…Our approach is to incorporate video clips in presenting the algorithm systematically. With this mobile learning application, student could learn at his or her own pace, anywhere anytime. …”
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Prime-based method for interactive mining of frequent patterns
Published 2010“…The PC-tree is a well-organized tree structure, which is systematically built based on descendant making introduced in this study. …”
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Mobile Learning: An Application Prototype for AVL Tree Learning Object
Published 2010“…Our approach is to incorporate video clips in presenting the algorithm systematically. With this mobile learning application, student could learn at his or her own pace, anywhere anytime. …”
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Reverse migration prediction model based on machine learning / Azreen Anuar
Published 2024“…For this purpose, three (3) algorithms have been assessed, namely, the Random Forest, Decision Tree, and Gradient Boosted Tree. …”
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An object-based approach to detect tree stumps in a selective logging area using Unmanned Aerial Vehicle imagery
Published 2021“…This research implemented a technique for detecting, segmenting, classifying, and measuring tree stumps by using the Multiresolution Segmentation Algorithm method. …”
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A conceptual framework for multi-objective optimization of building performance: Integrating intelligent algorithms, simulation tools, and climate adaptation
Published 2025“…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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Developing A Prediction Tool To Improve The Shading Efficiency Of The Pedestrian Zones
Published 2020“…Moreover, the study provided systematic solutions based on reconfiguring the pedestrian zone by the trees. …”
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Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination
Published 2025“…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
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Enhancing obfuscation technique for protecting source code against software reverse engineering
Published 2019“…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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Recovery of tree community composition across different types of anthropogenic disturbances and characterization of their effect using Landsat time series in Bornean tropical monta...
Published 2022“…This approach provides an efficient means for developing systematic conservation strategies for high-elevation regions in the tropics, where human-modified landscapes are expanding.…”
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Classification models for higher learning scholarship award decisions
Published 2018“…A dataset of successful and unsuccessful applicants was taken and processed as training data and testing data used in the modelling process. Five algorithms were employed to develop a classification model in determining the award of the scholarship, namely J48, SVM, NB, ANN and RT algorithms. …”
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An artificial intelligence approach to monitor student performance and devise preventive measures
Published 2023“…In addition, the prediction model is transformed into a clear shape to make it easy for the instructor to prepare the necessary precautionary procedures. We developed a set of prediction models with distinct machine learning algorithms. …”
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Anomaly detection in network traffic using machine learning
Published 2026“…The study objective is to analyze the effectiveness and reliability of implementing machine learning techniques in identifying anomalies in network traffic. Five (5) algorithms, which are Adaptive Boosting (AdaBoost), K-Nearest Neighbor (KNN), Random Forest (RF), Multi-Layer Perceptron (MLP), and Decision Trees (ID3) are systematically evaluated using the dataset CICIDS2017, a comprehensive and widely adopted benchmark for network traffic detection research. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…Then, the classifier (support vector machine (SVM) and data mining (DM) algorithm, decision tree (DT) were applied on each fusion image and their accuracy were evaluated. …”
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DurianCare: optimising trunk disease detection and precision farming in a mobile application / Muhammad Haziq Azmi
Published 2025“…This could include for instance a systematic literature review on theories available to understand the current problem and its possible solution, analysis of the users need gathered from interviews, and of course the application development using Flutter within Visual Studio Code. …”
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