Search Results - (( learning program end algorithm ) OR ( java application customization algorithm ))

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    A New Mobile Botnet Classification based on Permission and API Calls by Yusof, M, Saudi, MM, Ridzuan, F

    Published 2024
    “…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. …”
    Proceedings Paper
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    Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak by Ishak, Najihah Salsabila

    Published 2021
    “…A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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    Thesis
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    Implementation of hashed cryptography algorithm based on cryptography message syntax by Ali, Mohammed Ahnaf

    Published 2019
    “…The system will automatically protect data and thus retrieve data at the end of the system. The important study in this research is an automated learning system for deep learning to enhance security. …”
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    Optimal water supply reservoir operation by leveraging the meta-heuristic Harris Hawks algorithms and opposite based learning technique by Lai V., Huang Y.F., Koo C.H., Ahmed A.N., Sherif M., El-Shafie A.

    Published 2024
    “…To ease water scarcity, dynamic programming, stochastic dynamic programming, and heuristic algorithms have been applied to solve problem matters related to water resources. …”
    Article
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    Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

    Published 2019
    “…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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    Lightning fault classification for transmission line using support vector machine by Asman, Saidatul Habsah, Ab Aziz, Nur Fadilah, Ab Kadir, Mohd Zainal Abidin, Ungku Amirulddin, Ungku Anisa, Roslan, Nurzanariah, Elsanabary, Ahmed

    Published 2023
    “…In this study, two machine learning algorithms, Support Vector Machine (SVM) and k-Nearest Neighbor (kNN), were used and compared to classify faults due to lightning strikes, insulator failure, tree and crane encroachment. …”
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    Conference or Workshop Item
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    Lightning Fault Classification for Transmission Line Using Support Vector Machine by Asman S.H., Aziz N.F.A., Kadir M.Z.A.A., Amirulddin U.A.U., Roslan N., Elsanabary A.

    Published 2024
    “…In this study, two machine learning algorithms, Support Vector Machine (SVM) and k-Nearest Neighbor (kNN), were used and compared to classify faults due to lightning strikes, insulator failure, tree and crane encroachment. …”
    Conference Paper
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    Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar by Abu Bakar, Nordin

    Published 2016
    “…The end product of learning that could establish the relationships between knowledge and intelligence. …”
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    Design & Development of a Robotic System Using LEGO Mindstorm by Abd Manap, Nurulfajar, Md Salim, Sani Irwan, Haron, Nor Zaidi

    Published 2006
    “…Since the model is built using LEGO bricks, the model is fully customized, in term of its applications, to perform any relevant tasks. …”
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    Conference or Workshop Item
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    Enhancing predictive crime mapping model using association rule mining for geographical and demographic structure by Asmai, S. A.

    Published 2014
    “…Apriori is a popular algorithm in finding frequent set of items in data and association rule. …”
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    Dynamic and adaptive execution models for data stream mining applications in mobile edge cloud computing systems / Muhammad Habib Ur Rehman by Muhammad Habib , Ur Rehman

    Published 2016
    “…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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