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Evaluating Machine Learning Algorithms for Fake Currency Detection by Keerthana, S.N, Chitra, K.

“…In this study, we evaluate the effectiveness of six supervised machine learning algorithms—K-Nearest Neighbor, Decision Trees, Support Vector Machine, Random Forests, Logistic Regression, and Naive Bayes—in detecting the authenticity of banknotes. …”
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Application of Recently Developed Boosting Ensemble Machine Learning Algorithms in Carbon Capture and Storage Feasibility Assessment to Predict Subsurface Porosity by Sandunil, Kushan, Bennour, Ziad, Sivakumar, Saaveethya, Mahmud, Hisham Ben, Giwelli, Ausama A.

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The AGEB Algorithm for Solving Heat Equation in Two Space Dimensions and Its Parallelization on a Distributed Memory Machine by Alias, Norma, Sahimi, Mohamed Salleh, Abdullah, Abdul Rahman

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Induction machine diagnostic using adaptive neuro fuzzy inferencing system by Shukri, Mohamad, Khalid, Marzuki, Yusuf, Rubiyah, Shafawi, Mohd.

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Enhanced notes capture using super resolution technique on tecogan by Lee, Theresa Wen Yan

“…The concept is similar to documents scanning using mobile devices which users are able to capture the messages on the whiteboard, screen and notebook, then images can be further saved as enhanced notes in a softcopy file. The study areas included machine learning as well as generative adversarial network (GAN). …”
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Transfer Learning for Lung Nodules Classification with CNN and Random Forest by Abdulrazak, Saleh, Chee, Ka Chin, Ros Ameera, Rosdi

“…This research aims include preprocessing lung nodular data, developing the proposed algorithm, and comparing its effectiveness with other methods. …”
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Prediction of Rheological and Filtration Loss Properties of Nano-Zirconium-Dioxide Drilling Fluids via Machine Learning Techniques for Energy Exploration by Jason, Cheah, Ilyas, Suhaib Umer, Ridha, Syahrir, Sehar, Umara, Alsaady, Mustafa, Krishna, Shwetank

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3D LiDAR Vehicle Perception and Classification Using 3D Machine Learning Algorithm by Yong, Ericsson, Muhammad Aizzat, Zakaria, Mohamad Heerwan, Peeie, M. Izhar, Ishak

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Transfer Learning for Lung Nodules Classification with CNN and Random Forest by Abdulrazak Yahya, Saleh, Chee, Ka Chin, Ros Ameera, Rosdi

“…This research aims include preprocessing lung nodular data, developing the proposed algorithm, and comparing its effectiveness with other methods. …”
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Decision Support Tools: Machine Learning Application in Smart Planner by Baharom, M.A.A., Rahman, M.S.A., Sabudin, A.R., Nor, M.F.M.

“…Immaculate Project Planning and Execution (PPE) is capital to edge over competitors, decrease costs and honour delivery dates.Project Management Information System (PMIS) is necessary towards an improved and efficient quality of any project.Machine Learning (ML) Algorithms enabled learned the date of experience to develop insights into various associations between data and outcomes.A defined set of rules prescribed by the analysts makes the probability of the fault possible.In this paper, Regression Model compute across all viable sectors expending the tool for Downstream Business and other Facilities Upstream, including Resource Estimation Schedule Generation.Extending structured information into a reliable database allows super users to define the data structures and completely configurable the settingâ��s dynamics.The model used to decrease the approximation error and measure the closest possible outcome.This subset of artificial intelligence has tremendous potential in improving schedule generation configuration to develop Project Planning timely and financially smartly.This paper aims to share standard protocols and methods applied in ML-aided as a tool in PPE decision making.Additionally, the abundant used data resources devoted to implementing ML are outlined.Finally, ML success as a Decision Support tool in project management by having a Smart Planner in supporting project recommendation accelerates the decision process, increases stakeholder confidence, and minimizes uncertainty; results are reviewed and analyzed where gaps and potential improvement for future projects are being noted and highlighted. …”
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Prediction of abrasive waterjet machining of sheet metals using artificial neural network by Nur Khadijah, Mazlan, Nazrin, Mokhtar, Asmelash, Mebrahitom Asmelash, Azmir, Azhari

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Prediction of abrasive waterjet machining of sheet metals using artificial neural network by Nur Khadijah, Mazlan, Nazrin, Mokhtar, Gebremariam, Mebrahitom Asmelash, Azmir, Azhari

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Prediction of lattice constant of pyrochlore compounds using optimized machine learning model by Mohamad Zamri, Isma Uzayr, Abd Rahman, Mohd Amiruddin, Bundak, Caceja Elyca

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Bio-inspired for Features Optimization and Malware Detection by Razak, Mohd Faizal Ab, Anuar, Nor Badrul, Othman, Fazidah, Firdaus, Ahmad, Afifi, Firdaus, Salleh, Rosli

“…A static analysis technique with machine learning classifier is developed from the permission features noted in the Android mobile device for detecting the malware applications. …”
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Bio-inspired for Features Optimization and Malware Detection by Mohd Faizal, Ab Razak, Nor Badrul, Anuar, Fazidah, Othman, Ahmad, Firdaus, Firdaus, Afifi, Rosli, Salleh

“…A static analysis technique with machine learning classifier is developed from the permission features noted in the Android mobile device for detecting the malware applications. …”
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Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

“…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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Lung Nodules Classification Using Convolutional Neural Network with Transfer Learning by Abdulrazak Yahya, Saleh, Ros Ameera, Rosdi

“…Agriculture, healthcare, machinery, aviation, management, and even education have all benefited from the development and implementation of machine learning. …”
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Rain classification for autonomous vehicle navigation : A support vector machine approach by Abdul Haleem, Habeeb Mohamed, Muhammad Aizzat, Zakaria, Mohd Azraai, Mohd Razman, Anwar P. P., Abdul Majeed, Mohamad Heerwan, Peeie

“…Noting that, the proposed method has the potential to evaluate weather classification.…”
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Imputation Analysis of Time-Series Data Using a Random Forest Algorithm by Nur Najmiyah, Jaafar, Muhammad Nur Ajmal, Rosdi, Khairur Rijal, Jamaludin, Faizir, Ramlie, Habibah, Abdul Talib

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Developing flood mapping procedure through optimized machine learning techniques. Case study: Prahova river basin, Romania by Diaconu D.C., Costache R., Towfiqul Islam A.R.M., Pandey M., Pal S.C., Mishra A.P., Pande C.B.