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

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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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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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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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

“…For the machine learning training and testing purposes, data was collected based on the simulated run of the proposed insomnia audio therapy mobile application. …”
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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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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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Identification Of Flow Blockage Levels In Centrifugal Pump By Machine Learning by Ng, Woon Li

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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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Design of Predictive Model for TCM Tongue Diagnosis In Malaysia Using Machine Learning by Koe, Jia Chi

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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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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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Machine learning approach for tenaga nasional berhad (tnb) overhead powerline and electricity pole inventory using mobile laser scanning data by Mohd Rapheal M.S.A., Farhana A., Mohd Salleh M.R., Abd Rahman M.Z., Majid Z., Musliman I.A., Abdullah A.F., Abd Latif Z.

“…Decision trees; Laser applications; Learning algorithms; Machine learning; Mean square error; Scanning; Classifieds; Electricity assets; Electricity pole; Laser scanner data; Laserscanners; Machine-learning; Mobile laser scanner; Overhead powerline; Point-clouds; Power lines; Poles…”

Content-based indexing of low resolution documents by Md Nor, Danial

“…This approach, which is signature-based are considered for fast and efficient matching to fulfil the needs of real-time applications. …”
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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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Determination of tree height based on tree crown using algorithm derived from UAV imagery / Suzanah Abdullah ... [et al.] by Abdullah, Suzanah, Tahar, Khairul Nizam, Abdul Rashid, Mohd Fadzil, Osoman, Muhammad Ariffin

“…In this study, UAV technology has been taking a look at several algorithms for estimating tree height value of a single tree crown. …”
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Algorithm visualization design guidelines for mobile leaning by Supli, Ahmad Affandi, Shiratuddin, Norshuhada

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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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A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets by Mohd Razali, Muhamad Hasbullah, Saian, Rizauddin, Yap, Bee Wah, Ku-Mahamud, Ku Ruhana

“…Ant-tree-miner (ATM) has an advantage over the conventional decision tree algorithm in terms of feature selection. …”
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