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Age And Gender Recognition Mobile App by Wee, Quo Lung

“…Through reviewing and evaluate the existing age and gender recognition mobile apps and their deep learning algorithm, the study found the number of existing age and gender recognition mobile app is very less. …”
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My little learner : E-learning wonderland by Teoh, Wei En

“…The emphasis will be on providing an exciting and inspiring experience through interactive games, storytelling, and multimedia activities. The app will also use adaptive learning algorithms to tailor the instructional material to each child's unique learning style and speed. …”
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My little learner: E-learning wonderland by Teoh, Wei En

“…The emphasis will be on providing an exciting and inspiring experience through interactive games, storytelling, and multimedia activities. The app will also use adaptive learning algorithms to tailor the instructional material to each child's unique learning style and speed. …”
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Machine Learning Approach Regarding The Classification And Prediction Of Dog Sounds: A Case Study Of South Indian Breeds by Prabu Mohandas, Jerline Sheebha Anni, Khairunnisa Hasikin, Dhayalan Velauthapillai, Veena Raj, Thanihaichelvan Murugathas, Rajkumar Thanasekaran, Muhammad Mokhzaini Azizan

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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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.

“…Android (operating system); Android malware; Classification (of information); Feature Selection; Learning systems; Mobile security; Android apps; Classification models; Feature weight; Features selection; Machine learning algorithms; Machine-learning; Malware detection; Malwares; Memory usage; Selection techniques; Learning algorithms…”

GuitarApprentice: A Mobile Application for Acoustic Guitar Learning using Fast Fourier Transform algorithm by Lau , Jason Kim Wee

“…The results of the project are the suitable algorithm for chords detection and prototype of the mobile app. …”
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Mobility, Residual Energy, and Link Quality Aware Multipath Routing in MANETs with Q-learning Algorithm by Tilwari, Valmik, Dimyati, Kaharudin, Hindia, Mhd Nour, Fattouh, Anas, Amiri, Iraj

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AI powered asthma prediction towards treatment formulation : An android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Muzahid, Abu Jafar Md, Sarker, Md. Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md.

“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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AI powered asthma prediction towards treatment formulation: an android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Md Muzahid, Abu Jafar, Sarker, Md Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md

“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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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. The experimental result shows that the Random Forest Algorithm has achieved the highest detection accuracy of 99.4% with the lowest false positive rate of 16.1% as compared to other machine learning algorithms. …”

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

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Malware visualizer: A web apps malware family classification with machine learning by Mohd Zamri, Osman, Ahmad Firdaus, Zainal Abidin, Rahiwan Nazar, Romli

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Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin by Husam , N. S. Yasin

“…The computation time complexity of the Q-Learning-based test coverage algorithm was also analyzed. …”
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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

Comparative study of machine learning algorithms in data classification by Tan, Kai Jun

“…This research conducts a comparative study of various machine learning algorithms for dataset classification to identify the most accurate and reliable classifier. …”
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Nutrilife: Empowering health with diet and nutrition app by Tan, Yuki Lok Yee

“…Using MediaPipe and deep learning algorithms, the app track and analyses users' movements during exercises such as squats and bicep curls, providing corrections to improve technique. …”
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

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Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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NLP- based for providing mental health support in mobile application / Muhammad Amirul Roslan by Roslan, Muhammad Amirul

“…Performance testing confirmed the app's responsiveness and efficiency. Future enhancements, such as advanced machine learning algorithms and user interface improvements, are proposed to further enhance functionality. …”
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