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1
Sentiment analysis regarding marital issues using Naive Bayes algorithm / Farah Nabila Mohd Razali
Published 2025“…This study explores the application of sentiment analysis using the Naive Bayes algorithm to understand public perceptions of marital issues, particularly factors contributing to the rising divorce rate. …”
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2
Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…Therefore, this study aims to develop a new health monitoring system for communication towers based on AdaBoost, Bagging, and RUSBoost algorithms as hybrid algorithm, which can predict the damage by using noisy, random, unstable, and skewed frequency data with high accuracy. …”
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3
Wearable based-sensor fall detection system using machine learning algorithm
Published 2021“…In this project, a wearable sensor-based fall detection system using a machine-learning algorithm had been developed. …”
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Proceeding Paper -
4
Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques
Published 2011“…The proposed algorithm employs a combined model that uses two different measures (nonconformity metric measures and Local Distance-based Outlier Factor (LDOF)) to improve its detection ability. …”
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5
Predicting motorcycle customization preferences using machine learning
Published 2025“…The classification model was developed using the Random Forest algorithm, Support Vector Machine and Logistic Regression with 5-fold Cross validation. …”
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6
IOT-based fertigation system / Mohamad Amir Furqan Darus
Published 2024“…It integrates the MDD3A Cytron motor driver for water pump control and the Ph sensor to monitor soil acidity or alkalinity. Using advanced algorithms and machine learning techniques, the system nalyses the collected data to determine optimal irrigation and fertilization requirements. …”
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Student Project -
7
A Multi-Criteria Recommendation Technique for Personalized Tourism Experiences
Published 2025“…Using ResNet, the algorithm can learn more complex and nuanced patterns in the data, leading to more accurate recommendations. …”
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8
The determinant factors for the issuance of Central Bank Digital Currency (CBDC) in Malaysia using machine learning framework
Published 2024“…Eventually, the factors identified will be used to develop a framework for the implementation of CBDC in Malaysia.…”
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Detection of Malaysian sign language with single shot detector algorithm/ Nurfarah Idayu Mohamad Fauzi, Shahirah Mohamed Hatim and Zalikha Zulkifli
Published 2023“…Single Shot Detector (SSD) algorithm was implemented to perform the Malaysian Sign Language object detection in the application. …”
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10
An Improved Grey Wolf Optimization-based Learning of Artificial Neural Network for Medical Data Classification
Published 2021“…An adequate equilibrium among exploration and exploitation is a key factor to the success of meta-heuristic algorithms especially for optimization task. …”
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11
Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi
Published 2015“…An electronic board, transistor relay driver circuit, is designed for the purpose of establishing communication interface between the computer, adaptive learning algorithm and the actuator mechanism. …”
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12
Analysis of online CSR message authenticity on consumer purchase intention in social media on Internet platform via PSO-1DCNN algorithm
Published 2024“…Secondly, this work designs optimization measures from inertia weight and learning factor to build an improved particle swarm optimization algorithm (IPSO). …”
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13
A Novel Path Prediction Strategy for Tracking Intelligent Travelers
Published 2009“…The FCM nodes are a novel selection of kinematical factors. Genetic algorithm (GA) is then used to train the FCM to be able to replicate the decisional behaviors of the intelligent traveler. …”
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14
Logic Mining Approach: Shoppers’ Purchasing Data Extraction via Evolutionary Algorithm
Published 2023“…In reducing the learning complexity, a genetic algorithm was implemented to optimize the logical rule throughout the learning phase in performing a 2-satisfiability-based reverse analysis method, implemented during the learning phase as this method was compared. …”
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15
Prediction of sleep pattern for university students using machine learning
Published 2026“…These results demonstrate the potential of machine learning in identifying key behavioral and demographic factors influencing sleep patterns, which can be used to support targeted health and academic interventions for students.…”
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16
User interface and interactivity design guidelines of algorithm visualization on mobile platform
Published 2019“…Moreover, the evaluation of the effectiveness of the AVOMP prototype from 35 participants through laboratory experiments based on the bloom taxonomy test shows that there is a significant difference between students learning sorting algorithms using the manual approach (Pre-Test) and the AVOMP app (Post-Test). …”
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17
A COMPARATIVE STUDY OF MACHINE LEARNING MODELS FOR PREDICTION OF AUTISM SPECTRUM DISORDER USING SCREENING DATA
Published 2023“…Finally, the best classification model for ASD prediction was a model trained using the Support Vector Machine (SVM) algorithm…”
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Final Year Project Report / IMRAD -
18
A modified group authentication scheme for machine type communication in LTE/LTE-a networks
Published 2018“…Machine-Type Communication (MTC), as one of the essential advancements of wireless communication, has become a new business development in mobile communication. …”
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19
A stable energy balancing based clustering routing protocol for IoUT using meta-heuristic technique
Published 2024“…The proposed method enable to optimization the IoUT energy efficiency by balancing strategy that uses the Q-learning algorithm to ensure more balanced distribution of tasks across UNs and CHs. …”
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Proceeding Paper -
20
Dynamic and adaptive execution models for data stream mining applications in mobile edge cloud computing systems / Muhammad Habib Ur Rehman
Published 2016“…However, the execution of MDSM applications in MECC systems becomes hard due to multiple factors. The critical factors of complexity at application level include data size and data rate of continuously streaming data, the selection of data fusion and data preprocessing methods, the choice of learning models, learning rates and learning modes, and the adoption of data mining algorithms. …”
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