Search Results - (( mobile application learning algorithm ) OR ( _ application tree algorithm ))*

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 new mobile botnet classification based on permission and API calls by Yusof M., Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan

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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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Context-Aware Recommender System based on machine learning in tourist mobile application / Nor Liza Saad … [et al.] by Saad, Nor Liza, Khairudin, Nurkhairizan, Azizan, Azilawati, Abd Rahman, Abdullah Sani, Ibrahim, Roslina

“…Furthermore, data were collected simulated based on the mobile application prototype to be used for finding the suitable machine learning algorithms in the recommendation system module. …”
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Insomnia audio therapy mobile application with music recommender system / Nur Azmina Mohamad Zamani, Nasiroh Omar and Nur Damira Huda Azmi by Mohamad Zamani, Nur Azmina, Omar, Nasiroh, Azmi, Nur Damira Huda

“…This paper presents the research design and implementation of music recommendation system that possible to be used as an insomnia audio therapy in a mobile application platform. The research focused on investigating the performances of three machine learning algorithms namely Random Forest, Decision Tree and Support Vector Machine to be selected as the music recommendation tool. …”
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Reverse migration prediction model based on machine learning / Azreen Anuar by Anuar, Azreen

“…And the third objective is to evaluate reverse migration prediction model based on machine learning analysis. For this purpose, three (3) algorithms have been assessed, namely, the Random Forest, Decision Tree, and Gradient Boosted Tree. …”
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A wheelchair sitting posture detection system using pressure sensors by Mohamad Yusoff, Muhammad Annuar Alhadi, Azmi, Nur Liyana, Nordin, Nor Hidayati Diyana

“…Three classification algorithms based on the supervised learning of machine learning, such as support vector machine (SVM), random forest (RF),and decision tree (DT) were used to classify the postures which produced an accuracy of 95.44%, 98.72%,and 98.80%, respectively. …”
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Identification Of Flow Blockage Levels In Centrifugal Pump By Machine Learning by Ng, Woon Li

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Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models by Bakar M.A.A.A., Ker P.J., Tang S.G.H., Baharuddin M.Z., Lee H.J., Omar A.R.

“…The development of the algorithms shows that Logistic Regression, SVM with Linear and Polynomial kernels performed the best with 95% accuracy, followed by SVM-RBF kernel, and KNN with 93% accuracy, Decision Tree with 90% accuracy, and lastly, SVM-Sigmoidal kernel with 83% accuracy. …”

Empirical study on intelligent android malware detection based on supervised machine learning by Abdullah, Talal A.A., Ali, Waleed, Abdulghafor, Rawad Abdulkhaleq Abdulmolla

“…The increasing number of mobile devices using the Android operating system in the market makes these devices the first target for malicious applications. …”
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Design of Predictive Model for TCM Tongue Diagnosis In Malaysia Using Machine Learning by Koe, Jia Chi

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Optimising acoustic features for source mobile device identification using spectral analysis techniques / Mehdi Jahanirad by Mehdi , Jahanirad

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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

“…In this review paper, a comprehensive review of mobile robot navigation algorithms has been conducted. …”
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GuitarApprentice: A Mobile Application for Acoustic Guitar Learning using Fast Fourier Transform algorithm by Lau , Jason Kim Wee

“…The objective of the project is to create a learning-based mobile application for learning to play an acoustic guitar. …”
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Machine Learning Applications in Multiplayer Online Battle Arena Esports—A Systematic Review by Ahmad Alif, Kamal, Mohd. Asyraf, Mansor, Liyana, Truna, Norhunaini, Mohd. Shaipullah, Nor Hafizie, Habib Sultan

“…The applications of ML in MOBA are an interesting field of study as the esports genre is enriched by a plethora of data. …”
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Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models by Bakar, Mohd Anif A. A., Ker, Pin Jern, Tang, Shirley G. H., Baharuddin, Mohd Zafri, Lee, Hui Jing, Omar, Abdul Rahman

“…The development of the algorithms shows that Logistic Regression, SVM with Linear and Polynomial kernels performed the best with 95 accuracy, followed by SVM-RBF kernel, and KNN with 93 accuracy, Decision Tree with 90 accuracy, and lastly, SVM-Sigmoidal kernel with 83 accuracy. …”
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Algorithm visualization design guidelines for mobile leaning by Supli, Ahmad Affandi, Shiratuddin, Norshuhada

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Object Detection and Movement Tracking Using Tubelets and Faster RCNN Algorithm with Anchor Generation by Prabu Mohandas, Jerline Sheebha Anni, Rajkumar Thanasekaran, Khairunnisa Hasikin, Muhammad Mokhzaini Azizan

Review on ubiquitous education system with multi-agent synchronization on mobile learning application environment by Mwinyi, Amir Kombo, Syed Mohamed, Syed Abdul Rahman Al Haddad, Abdullah, Rusli, Hashim, Shaiful Jahari

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State of charge estimation for electric vehicles using random forest by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…Previous methods, including the Extreme Learning Machine (ELM), have exhibited limitations in providing the accuracy and robustness required for practical EV applications. …”
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