Search Results - (( model validation learning algorithm ) OR ( _ information security algorithm ))*

Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

“…The total work is completed by the selection, assessment, and implementation of the Machine Learning (ML) model, and finally, proposed the crime prediction. …”
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Detection of DDoS attacks in IoT networks using machine learning algorithms by Abdulrahman Alwan, Alwan Ahmed, Shah, Asadullah, Abdulrahman Alwan, Alwan Abdullah, Laghari, Shams Ul Arfeen

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BIOLOGICAL INSPIRED INTRUSION PREVENTION AND SELF-HEALING SYSTEM FOR CRITICAL SERVICES NETWORK by MOHAMED AHMED ELSHEIK, MUNA ELSADIG

“…This thesis presents new intrusion prevention and self-healing system (SH) for critical services network security. The design features of the proposed system are inspired by the human immune system, integrated with pattern recognition nonlinear classification algorithm and machine learning. …”
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Social engineering exploitation detection (SEED) in Malaysia's SMEs using machine learning by Sia, Ken Yen

“…The project will use natural language processing in extracting certain features as the input of an algorithm to generate a reputation score that will be trained using machine learning to build the detection model. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…Despite attempts to solve the data clustering issues, there are also many variants of modified algorithms in traditional information clustering that attempt to solve issues such as clustering algorithms based on condensation. …”
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Intelligent deep machine learning cyber phishing URL detection based on BERT features extraction by Muna Elsadig, Ashraf Osman Ibrahim Elsayed, Shakila Basheer, Manal Abdullah Alohali, Sara Alshunaifi, Haya Alqahtani, Nihal Alharbi, Wamda Nagmeldin

“…Then, the natural language processing (NLP) algorithm was applied to the unique data column and extracted a huge number of useful data features in terms of meaningful text information. …”
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Machine Learning based Predictive Modelling of Cybersecurity Threats Utilising Behavioural Data by Ting, Tin Tin, Khiew, Jie Xin, Ali Aitizaz, Lee, Kuok Tiung, Teoh, Chong Keat, Hasan Sarwar

“…The algorithms are used to construct, test, and validate three categories of cybercrime threat (Malware, Social Engineering, and Password Attack) predictive models. …”
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ReSTiNet: An efficient deep learning approach to improve human detection accuracy by Shahriar Shakir, Sumi, Dayang Rohaya, Awang Rambli, Mirjalili, Seyedali, Miah, M. Saef Ullah, Muhammad Mudassir, Ejaz

“…It is one of the most important tasks in global security and safety monitoring. In recent days, Deep Learning has improved human detection technology. …”
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ReSTiNet: An Efficient Deep Learning Approach to Improve Human Detection Accuracy by Sumit, S.S., Rambli, D.R.A., Mirjalili, S., Miah, M.S.U., Ejaz, M.M.

“…It is one of the most important tasks in global security and safety monitoring. In recent days, Deep Learning has improved human detection technology. …”
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ReSTiNet : An efficient deep learning approach to improve human detection accuracy by Sumit, Shahriar Shakir, Dayang Rohaya, Awang Rambli, Seyedali, Mirjalili, Miah, Md Saef Ullah, Muhammad Mudassir, Ejaz

“…It is one of the most important tasks in global security and safety monitoring. In recent days, Deep Learning has improved human detection technology. …”
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EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique by Liew, Siaw Hong

“…High level security has nurtured the arisen of Electroencephalograms (EEG) signals as a noteworthy biometrics modality for person authentication modelling. …”
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A conceptual framework for a lightweight AI system for skin disease risk prediction using epidemiological data in rural Bangladesh by Islam, Mohammad Raihanul, Abdul Kadir, Andi Fitriah, Ismail, Syazwan Aizat

“…The framework incorporates environmental, occupational, hygiene-related, and living-condition factors to model individual risk profiles. Preliminary experiments conducted on an existing dataset demonstrate that conventional machine learning algorithms, particularly K-Nearest Neighbors (KNN) and Random Forest, achieve strong predictive performance, with accuracy reaching up to 88% in train–test evaluations and 80% in 10-fold cross-validation. …”
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Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models by Quadros, Jaimon Dennis, Khan, Sher Afghan, Aabid, Abdul, Baig, Muneer

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Machine learning techniques validation using experimental average surface temperature and output power of photovoltaic panel cooled by porous media under indoor condition by Al-Masalha, Ismail, Masuri, Siti Ujila, Badran, Omar Othman, Alsabagh, Abdel Salam, Alawin, Aiman Al, Abu-Rahmeh, Taiseer M., Al-Khawaldeh, Mustafa A.

“…Therefore, the algorithm AdaBoost model prediction results proved one of the best machine learning models for analytical studies on photovoltaic panel cooling performance predictions. …”
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A deep reinforcement learning hybrid algorithm for the computational discovery and characterization of small proteins utilizing mycobacterium tuberculosis as a model by Ouwabunmi, Babalola AbdulHafeez

“…This study presents the development and evaluation of a novel hybrid machine learning algorithm that integrates the strengths of Random Forest and Gradient Boosting models to enhance the prediction of smORFs. …”
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Prediction of Machine Failure by Using Machine Learning Algorithm by Fakhrurazi, Nur Amalina

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Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

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Approach For Optimizing Course Recommendation Based On Integrating Modified Felder-Silverman Learning Style Model With Meta-Heuristics Algorithm by Ashraf, Erum

“…It involves identifying potential courses learning style, validated through genetic and surrogate meta-heuristics optimization algorithms, and employing Felder-Silverman model for learning style identification. …”
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Lane detection in autonomous vehicles : A systematic review by Noor Jannah, Zakaria, Mohd Ibrahim, Shapiai, Rasli, Abd Ghani, Mohd Najib, Mohd Yassin, Mohd Zamri, Ibrahim, Nurbaiti, Wahid

“…In the meantime, the methodologies include geometric modeling and traditional methods, while AI includes deep learning and machine learning. …”
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Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.] by Mohd, Thuraiya, Jamil, Syafiqah, Masrom, Suraya, Ab Rahim, Norbaya

“…In the cycle of Industrial Revolution 4.0 (IR 4.0), many issues in the industries can be solved with implementation of artificial intelligence approaches, including machine learning models. Designing an effective machine learning model for prediction and classification problems is a continuous effort. …”
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