Search Results - (( based stimulated learning algorithm ) OR ( java application optimisation algorithm ))

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Autonomous Person-following Telepresence Robot Using Monocular Camera And Deep Learning Yolo by Ahmad Amin Firdaus Sakri, Noor Hanis Izzuddin Mat Lazim, Suffian At-Tsauri Mauzi, Mus’ab Sahrim, Liyana Ramli, Aminurrashid Noordin

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Machine learning in botda fibre sensor for distributed temperature measurement by Nur Dalilla binti Nordin

“…The results obtained in these experiments would provide some overview in deploying machine learning algorithm for characterizing the Brillouin-based fibre sensor signals.…”

Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm by Mohamed, M. E, Samir, B. B., Azween, Abdullah

“…A new non classification algorithm was developed based on the danger theory model of human immune system (HIS).The abstract model of system algorithm is inspired from HIS cell mechanism mainly, the Dendritic cell behavior and T-cell mechanisms. …”
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Arithmetic optimization algorithm with deep learning enabled airborne particle-bound metals size prediction model by Almalawi, A., Khan, A.I., Alsolami, F., Alkhathlan, A., Fahad, A., Irshad, K., Alfakeeh, A.S., Qaiyum, S.

“…In this view, this paper presents a novel arithmetic optimization algorithm (AOA) with multi-head attention based bidirectional long short-term memory (MABLSTM) model for predicting the size fractionated airborne particle bound metals. …”
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Arithmetic optimization algorithm with deep learning enabled airborne particle-bound metals size prediction model by Almalawi, A., Khan, A.I., Alsolami, F., Alkhathlan, A., Fahad, A., Irshad, K., Alfakeeh, A.S., Qaiyum, S.

“…In this view, this paper presents a novel arithmetic optimization algorithm (AOA) with multi-head attention based bidirectional long short-term memory (MABLSTM) model for predicting the size fractionated airborne particle bound metals. …”
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Arithmetic optimization algorithm with deep learning enabled airborne particle-bound metals size prediction model by Almalawi, A., Khan, A.I., Alsolami, F., Alkhathlan, A., Fahad, A., Irshad, K., Alfakeeh, A.S., Qaiyum, S.

“…In this view, this paper presents a novel arithmetic optimization algorithm (AOA) with multi-head attention based bidirectional long short-term memory (MABLSTM) model for predicting the size fractionated airborne particle bound metals. …”
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Empirical Analysis of Intra vs. Inter-Subject Variability in VR EEG-Based Emotion Modelling by N.S. Suhaimi, J. Teo, J. Mountstephens

“…These methods showed highly promising results and will be further enhanced using other machine learning approaches such as deep learning in VR stimulus.…”
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A review of classification techniques for electromyography signals by Mohd Saad, Norhashimah, Omar, Siti Nashayu, Abdullah, Abdul Rahim, Shair, Ezreen Farina, H.Rashid

“…All of the ML classifiers have their own algorithm, special specification, pros and cons based on the available input. …”
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Computational design, synthesis and evaluation of caffeine imprinted molecular imprint polymer (MIP) by Nurul Maisyarah, Samsudin

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Ensemble learning using multi-objective optimisation for arabic handwritten words by Ghadhban, Haitham Qutaiba

“…Most ensemble learning approaches are based on the assumption of linear combination, which is not valid due to differences in data types. …”
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Computational analysis of biological data: Where are we? by Soreq, Lilach, Mohamed, Wael Mohamed Yousef

“…Computer modeling allows such electrical stimulations using statistics, bioinformatics and advanced machine-learning algorithms. …”
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A Neural Network Mobile Learning Application For Autonomous Improvement In A Flexible Manufacturing Environment by Siew , Jit Ping

“…Given the standing work environment of the machine operators who are continuously on the move, the challenge is therefore, to empower them with knowledge on their performances relative to defects with a mobile learning application, and to stimulate an autonomous process improvement. …”
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Modeling of Functional Electrical Stimulation (FES): Powered Knee Orthosis (PKO) assisted gait exercise in post-stroke rehabilitation / Adi Izhar Che Ani by Che Ani, Adi Izhar

“…In the human gait model, three Machine Learning algorithms were used: Gaussian Process Regression, Support Vector Machine, and Decision Tree. …”
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Hybrid Soft Computing Approach for Determining Water Quality Indicator: Euphrates River by Jing, Li, Husam Ali , Abdulmohsin, Samer Sami , Hasan, Li , Kaiming, Belal , Al-Khateeb, Mazen Ismaeel, Ghareb, Mohammed, Muamer N.

“…In this research, the implementation of hybrid evolutionary model based on integrated support vector regression (SVR) with firefly algorithm (FFA) was investigated for water quality indicator prediction. …”
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Developing students' mathematical thinking: how far have we came? by Md. Yunus, Aida Suraya

“…To provide support for learning school textbooks need to be greatly improved as the current contents, contexts and examples do not stimulate students' thinking. …”
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In silico approaches for unearthing bacterial quorum-sensing inhibitors against pathogenic bacteria by Pawar, Shrikant, Bramha Chari, P. V., Lahiri, Chandrajit *

“…Thus, certain group of researchers also developed machine learning tools based on support vector machine (SVM) and hidden Markov models (HMM) for the identification of novel and effective biofilm inhibitory peptides (BIPs), while others used in silico approaches for predicting and designing of antibiofilm peptides usingbidirectional recursive neural network (BRNN) and Random Forest (RF) algorithms. …”
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