Search Results - (( java implementation learning algorithm ) OR ( program mobile learning algorithm ))*

Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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A new mobile botnet classification based on permission and API calls by Yusof M., Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan

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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

“…These proves that without prior knowledge, the hybrid AI algorithm can self-learn. In the future the research on improving the algorithm learning will be studied and the implementation in other types of autonomous system other mobile robot obstacle avoidance will be considered.…”
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A New Mobile Botnet Classification based on Permission and API Calls by Yusof, M, Saudi, MM, Ridzuan, F

“…As a result, 16 permissions and 31 API calls that are most related with mobile botnet have been extracted using feature selection and later classified and tested using machine learning algorithms. …”

An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

“…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Mobile Learning: An Application Prototype for AVL Tree Learning Object by Ibrahim, Mohammad Noor, Mahamad, Saipunidzam, Chua, Edrea Ning Wei

“…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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Collision prediction based genetic network programming-reinforcement learning for mobile robot navigation in unknown dynamic environments by Findi, Ahmed H. M., Marhaban, Mohammad Hamiruce, Raja Ahmad, Raja Mohd Kamil, Hassan, Mohd Khair

“…Genetic Network Programming with Reinforcement Learning (GNP-RL) has several important features over other evolutionary algorithms such as it combines offline and online learning on the one hand, and it combines diversified and intensified search on the other hand, but it was used in solving the problem of MR navigation in static environment only. …”
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Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir by Amir, Nur Hazirah

“…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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Mobile Learning: An Application Prototype for AVL Tree Learning Object by Ibrahim, Mohammad Noor, Mahamad, Saipunidzam, Chua, Edrea Ning Wei

“…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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A mobile application system for parking validation based on deep learning image processing / Alias Deraman and Muhammad Izz Kamaruddin by Deraman, Alias, Kamaruddin, Muhammad Izz

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Utilizing autonomous mobile robot to increase interest in STEM by Tay T.T., Lim Z.Z., Chua Y.L.

Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Development of a Wireless PC-Controlled Mobile Robot System and Multimedia Based Learning Module by Mujber, Tariq Saad

“…The code has been developed using Object-Oriented Programming Language and Graphic User Interface. The developed control algorithms enable the user to control the mobile robot manually, automatically or by voice recognition commands. …”
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Self learning module on securing IPV6 deployment / Muhamad Nazif Shahaimi Zaha by Zaha, Muhamad Nazif Shahaimi

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Campus study buddy : collaborative learning and resource sharing app by Huang, Yifan

“…This project is aiming to create a mobile application based on Android. Higher education institutions can use this program to provide students with a platform to collaborate and support each other's learning, creating a collaborative learning environment, promoting knowledge sharing, and improving student academic success. …”
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Parking finder mobile application by Tham, Chee Ming

“…In this system, computer vision and deep learning models such as YOLOv8 will be utilized for parking spaces and vehicle detection while the DeepSORT algorithm is implemented to track vehicle movement in real-time. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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BFEDroid: A Feature Selection Technique to Detect Malware in Android Apps Using Machine Learning by Chimeleze C., Jamil N., Ismail R., Lam K.-Y., Teh J.S., Samual J., Akachukwu Okeke C.