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Artificial neural network model for predicting windstorm intensity and the potential damages / Mohd Fatruz Bachok by Bachok, Mohd Fatruz

“…A predictive model was developed to provide a mechanism that can be regionally simulated, and predict low or high risk windstorm, its possible location, time, duration of the risk, intensity as well as potential damages. …”
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Stereolithography 3D printing development of 3D printing machine controller using the predefined closest-distance volume interpolator system by -, -

“…Generation of the layers are computationally intensive. Existing contour generation algorithm requires long computational time to generate the contour layers especially for high polygon models. …”
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Machine learning-based risk prediction model for medication administration errors in neonatal intensive care units: a prospective direct observational study by Henry Basil, Josephine, Lim, Wern Han, Syed Ahmad, Sharifah M., Menon Premakumar, Chandini, Mohd Tahir, Nurul Ain, Mhd Ali, Adliah, Seman, Zamtira, Ishak, Shareena, Mohamed Shah, Noraida

“…Conclusions: This study developed and validated an ML-based model to predict the presence of MAEs among neonates in NICUs. …”
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Jogging activity recognition using k-NN algorithm by Afifah Ismail

“…To recognize and classify the level of jogging intensity, k-Nearest Neighbours (k-NN) algorithms will be considered as a machine learning method. …”
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System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

“…System identification is getting more intensive from researcher to develop an algorithm with work efficiently and more accurate. …”
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Target heart rate zone detector during exercise based on real-time facial expression using single shot detection algorithm / Muhammad Azziq Shamsudin, Raihah Aminuddin and Ummu Mar... by Shamsudin, Muhammad Azziq, Aminuddin, Raihah, Abdul Jalil, Ummu Mardhiah

“…The object detection machine learning model used in this project is Single Shot Detector (SSD) algorithm. …”
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Modified spectral clustering algorithm for semisupervised face annotation modeling by Sheng, Gao You

“…The research streamlines annotation, reduces manual work, boosts facial recognition performance (98.97% purity), and contributes to computer vision and AI with efficient large-scale face annotation solutions, developing two models.…”
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Contour generation for mask projection stereolithography 3D printing by Faeiz Azizi, Adnan

“…Generation of the layers are computationally intensive. Existing contour generation algorithm requires long computational time to generate the contour layers especially for high polygon models. …”
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Developing and validating a simulation model for counting and classification of vehicles by Ali Emad Jehad, Riza Atiq O.K. Rahmat

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State of charge estimation for lithium-ion battery based on random forests technique with gravitational search algorithm by Lipu M.S.H., Ayob A., Saad M.H.M., Hussain A., Hannan M.A., Faisal M.

DC motor control using LQR algorithm by Adezeno, Sagoli Olid

“…Hence it is essential for complex algorithm to control real time process system. Programmable Logic Controller (PLC) is known as process models by industries for several years. …”
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Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

EEG-based brain source localization using visual stimuli by Jatoi, M.A., Kamel, N., Malik, A.S., Faye, I., Bornot, J.M., Begum, T.

“…Various source localization algorithms have been developed to determine the exact locations of the active brain sources due to which electromagnetic activity is generated in brain. …”
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Modelling and Optimization of Asymmetric Vehicle Routing Problem Using Particle Swarm Optimization Algorithm by Muhamad Rozikin, Kamaluddin, M. F. F., Ab Rashid

“…Specific optimization model and algorithm were developed to solve the problem. …”
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Dynamic replication algorithm in data grid: Survey by K. Madi, Mohammed, Hassan, Suhaidi

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Data discovery algorithm for scientific data grid environment by Abdullah, Azizol, Othman, Mohamed, Sulaiman, Md. Nasir, Ibrahim, Hamidah, Othman, Abu Talib

“…We investigate these algorithms using our Grid Simulator developed using PARSEC. …”
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Early bacterial detection in bloodstream infection using deep transfer learning algorithm by Son Ali, Akbar, Kamarul Hawari, Ghazali, Habsah, Hasan, Wahyu Sapto, Aji, Yudhana, Anton

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Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

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Classification of chest radiographs using novel anomalous saliency map and deep convolutional neural network by Md. Ali, Mohd. Adli, Abidin, Mohd Radhwan, Nik Muhamad Affendi, Nik Arsyad, Abdullah, Hafidzul, Rosman, Daaniyal Reesha, Badrud'din, Nu'man, Kemi, Faiz, Hayati, Farid

“…Therefore, we also introduce the Xenafas algorithm in this paper. The algorithm creates a new kind of anomalous saliency map called the Intensity Probability Mapping and Weighted Intensity Probability Mapping. …”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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