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A lightweight graph-based pattern recognition scheme in mobile ad hoc networks. by Raja Mahmood, Raja Azlina, Muhamad Amin, Anang Hudaya, Amir, Amiza, Khan, Asad I.

“…Its one-cycle learning and divide and distribute recognition task approach allows DHGN to detect similar patterns in short of time. …”
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iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems by Azad, Saiful, Mahmud, Mufti, Kamal Zuhairi, Zamli, Kaiser, M. Shamim, Jahan, Sobhana, Razzaque, Md Abdur

“…These threats can largely be tackled by employing a Trust Management Model (TMM) by exploiting the behavioural patterns of nodes to identify their trust class. In this context, ML-based models are best suited due to their ability to capture hidden patterns in data, learning and improving the pattern detection accuracy over time to counteract and tackle threats of a dynamic nature, which is absent in most of the conventional models. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Multi resident complex activity recognition in smart home: a literature review by Mohamed, Raihani, Perumal, Thinagaran, Sulaiman, Md. Nasir, Mustapha, Norwati

“…We highlighted the multi resident activity recognition including concurrent, interleave and cooperative interaction activity. We present methods behind the main stream of multi resident activity recognition models and algorithms that deploys machine learning as the core subject. …”
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Artificial intelligence-driven vehicle fault diagnosis to revolutionize automotive maintenance: A review by Hossain, Md Naeem, Rahman, Md Mustafizur, D., Ramasamy

“…We focus on reviewing relevant literature in the field of machine learning as well as deep learning algorithms for fault diagnosis in engines, lifting systems (suspensions and tires), gearboxes, and brakes, among other vehicular subsystems. …”
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