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Teaching and learning via chatbots with immersive and machine learning capabilities by Nantha Kumar Subramaniam

“…These chatbots support learning of Java via problem-solving steps through “learning by doing”. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

“…However, its precision affected by numerous factors like data set type, spatial resolution, number of variables, etc. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

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A machine learning approach of predicting high potential archers by means of physical fitness indicators by Muazu Musa, Rabiu, Abdul Majeed, Anwar P.P., Taha, Zahari, Chang, Siow Wee, Ab. Nasir, Ahmad Fakhri, Abdullah, Mohamad Razali

“…The present study classified and predicted high and low potential archers from a set of physical fitness variables trained on a variation of k-NN algorithms and logistic regression. 50 youth archers with the mean age and standard deviation of (17.0 ± 0.56) years drawn from various archery programmes completed a one end archery shooting score test. …”
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A machine learning approach of predicting high potential archers by means of physical fitness indicators by Musa, Rabiu Muazu, Anwar, P. P. Abdul Majeed, Zahari, Taha

“…The present study classified and predicted high and low potential archers from a set of physical fitness variables trained on a variation of k-NN algorithms and logistic regression. 50 youth archers with the mean age and standard deviation of (17.0 ± 0.56) years drawn from various archery programmes completed a one end archery shooting score test. …”
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Detection of mental disorders based on the analysis of emotion, facial expressions and facial movements in a video stream by Nurzhanova, Aizhan, Mussabek, Miras, Ince, Gokhan, Mustaffa, Mas Rina, Zhumadillayeva, Ainur

“…Using machine learning techniques and deep learning algorithms, we aim to create an algorithm for emotion recognition using a personalized approach. …”
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Classifying corporates default and non-default using machine learning Artificial Neural Network: multilayer perceptron / Nur Insyirah Mohamad Radzi, Murni Salina Rosidi and Nur Asy... by Mohamad Radzi, Nur Insyirah, Rosidi, Murni Salina, Zailand, Nur Asyura Izzati

“…Asset volatility is found to be the most significant independent variable. Therefore, ANN is a machine learning algorithm that uses multiple layers perceptron to solve complex problems and predict analytics.…”
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Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models by Hilal, Yousif Yakoub

“…Finally, this research concluded that a genetic algorithm is useful for selecting input variables in oil palm production. …”
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Multi-horizon ternary time series forecasting by Htike@Muhammad Yusof, Zaw Zaw

“…Because of the fact that these time series are affected by a multitude of interrelating macroscopic and microscopic variables, the underlying models that generate these time series are nonlinear and extremely complex. …”
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Optimization of operational conditions for adipate ester synthesis in a stirred tank reactor by Chaibakhsh, Naz, Abdul Rahman, Mohd Basyaruddin, Vahabzadeh, Farzaneh, Abd. Aziz, Suraini, Basri, Mahiran, Salleh, Abu Bakar

“…The process was carried out using an artificial neural network (ANN) trained by the Levenberg-Marquardt (LM) algorithm. …”
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Rank-based optimal neural network architecture for dissolved oxygen prediction in a 200L bioreactor by Mamat, Nor Hana, Mohd Noor, Samsul Bahari, Che Soh, Azura, Taip, Farah Saleena, Ab Rashid, Ahmad Hazri, Jufika Ahmad, Nur Liyana, Mohd Yusuff, Ishak

“…In a fermentation process, dissolved oxygen (DO) concentration is mostly affected by aeration rate, and agitation speed and temperature. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

“…Based on the mentioned criteria several scenarios were defined and compared which resulted to a structure of 8-10-1 with the Levenberg-Marquardt (LM) as the training algorithm and logistic sigmoid function in the output layer. …”
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Price prediction model of green building based on machine learning algorithms / Nur Syafiqah Jamil by Jamil, Nur Syafiqah

“…Meanwhile, experiments using five common algorithms, Random Forest Regressor Model outperforms four (4) other algorithms in predicting the price of green building condominium, by training and validating the data-set using Split approach. …”
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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.

“…To achieve this goal, we employed ten flood-related variables as independent variables in our machine learning models. …”

Production quantity estimation using an improved artificial neural network by Dzakiyullah, Raden Nur Rachman

“…This model is designed based on input variables that affect the determination of production quantity which include demand, setup costs, production, material costs, holding costs, transportation costs. …”
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Advanced neural networking and classification techniques for human brain tissues diagnoses: segmenting healthy, cancer affected and edema brain tissues by Falah Ali, Wadah

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A Performance Comparison of Various Artificial Intelligence Approaches for Estimation of Sediment of River Systems by Hayder G., Solihin M.I., Kushiar K.F.B.

“…Sediment is a universal issue that is generated in the river catchment and affects the river flow, reservoir capacity, hydropower generation and dam structure. …”

An artificial neural network approach in service life prediction of building components in Malaysia based on local environment and building service load by Tapsir, Siti Hamisah, Mohd. Yatim, Jamaludin, Usman, Fathoni

“…The back-propagation learning algorithm is used as learning model. The environment load factors, workmanship, design, usage and level of maintenance are used as input variables in training process of the neural network model. …”
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Identification of debris flow initiation zones using topographic model and airborne laser scanning data by Lay, Usman Salihu, Pradhan, Biswajeet

“…In addition to this, the resolution of the terrain dataset also affects the results of the detection of source areas. …”
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A comprehensive model for determining technological innovation level in supply chains using green investment, eco-friendly design and customer collaborations factors by Beigizadeh, Razieh, Delgoshaei, Aidin, Ariffin, Mohd Khairol Anuar, Hanjani, Sepehr Esmaeili, Ali, Ahad

“…Then, in the 2nd phase, a comprehensive model will be developed and trained. Using the data of supply chains that were gathered in the first phase, the train and test data would be selected. …”
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