Search Results - (( developing gender selection 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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Gender classification on skeletal remains: efficiency of metaheuristic algorithm method and optimized back propagation neural network by Hairuddin, Nurul Liyana, Yusuf, Lizawati Mi, Othman, Mohd Shahizan

“…Thus, this paper proposed metaheuristic algorithms such as Particle Swarm Optimization, Ant Colony Algorithm and Harmony Search Algorithm based feature selection to identify the most significant features of skeleton remains. …”
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Age And Gender Recognition Mobile App by Wee, Quo Lung

“…Therefore, this study aimed to develop age and gender recognition mobile application using deep learning algorithm. …”
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First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms by Azwa, Abdul Aziz, Fadhilah, Ahmad

“…From the experiment, the models develop using Rule Based and Decision Tree algorithm shows the best result compared to the model develop from the Naïve Bayes algorithm. …”
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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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Google autocomplete search algorithms and the Arabs' perspectives on gender: a case study of Google Egypt by Al-Abbas, Linda S., Haider, Ahmad S., Hussein, Riyad F.

“…The study concludes that since such generalizations may entail exaggerations and are not evidently right all the time, one must be careful about adopting such stereotypes and making them part of each gender's views of the other. Bearing in mind the perpetuating function that technology may have of existing stereotypes and social norms, users and developers of Google alike must pay more attention to gender biases that algorithms may establish and disseminate.…”
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Finding an effective classification technique to develop a software team composition model by Gilal, A.R., Jaafar, J., Capretz, L.F., Omar, M., Basri, S., Aziz, I.A.

“…The model developed was composed of 3 predictors: team role, personality types, and gender variables; it also contained 1 outcome: team performance variable. …”
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Finding an effective classification technique to develop a software team composition model by Gilal, A.R., Jaafar, J., Capretz, L.F., Omar, M., Basri, S., Aziz, I.A.

“…The model developed was composed of 3 predictors: team role, personality types, and gender variables; it also contained 1 outcome: team performance variable. …”
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Development Of Human Skin Detection Algorithm Using Multilayer Perceptron Neural Network And Clustering Method by Al-Mohair, Hani Kaid Saif

“…The Differential Evolution Algorithm (DE) is used in this work to select the optimum color and texture information to achieve the optimum response. …”
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Finding an effective classification technique to develop a software team composition model by Gilal, Abdul Rehman, Jaafar, Jafreezal, Capretz, Luiz Fernando, Omar, Mazni, Basri, Shuib, Abdul Aziz, Izzatdin

“…Ineffective software team composition has become recognized as a prominent aspect of software project failures.Reports from results extracted from different theoretical personality models have produced contradicting fits, validity challenges, and missing guidance during software development personnel selection.It is also believed that the technique/s used while developing a model can impact the overall results.Thus, this study aims to: 1) discover an effective classification technique to solve the problem, and 2) develop a model for composition of the software development team.The model developed was composed of three predictors: team role, personality types, and gender variables; it also contained one outcome: team performance variable.The techniques used for model development were logistic regression, decision tree, and Rough Sets Theory (RST).Higher prediction accuracy and reduced patte rn complexity were the two parameters forselecting the effective technique.Based on the results, the Johnson Algorithm (JA) of RST appeared to be an effective technique for a team composition model.The study has proposed a set of 24 decision rules for finding effective team members.These rules involve gender classification to highlight the appropriate personality profile for software developers.In the end, this study concludes that selecting an appropriate classification technique is one of the most important factors in developing effective models.…”
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Customer analysis with machine vision by Tiong, Wei Jie

“…To address the issue, the latest algorithms, such as YOLOv5, YOLOv8 and mobilenet ssd, were selected for retraining. …”
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Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control by Mohd Hanafi, Muhammad Sidik

“…This method would be a control method to activate power assist system and selected based on conditions set in the algorithm. …”
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Nonlinear identification for dengue fever / Herlina Abdul Rahim. by Abdul Rahim, Herlina

“…The best parameters' settings for the NARMAX model can be found using the Lipschitz number criterion for the model order selection with artificial neural network structure of 5-2-1 trained using the Levenberg Marquardt algorithm.…”
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A study of graduate on time (GOT) for Ph.D students using decision tree model by Chin, Wan Yung, Ch’ng, Chee Keong, Mohd Jamil, Jastini

“…Historical data that related to all Ph.D students in a public university in Malaysia has been obtained directly from the database of Graduate Academic Information System (GAIS) in order to develop and compare the performance of decision tree models (Chi-square algorithm, Gini index algorithm, Entropy algorithm and an interactive decision tree). …”
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Artificial Neural Network in Predicting Risk Exposure in Malaysian Shipyard Industry by David Chua, Sing Ngie, Calvin Chin, Yen Chih, Lim, Soh Fong

“…Several network architectures were developed and the best model was selected for the risk exposure prediction of workers in the shipyard industry. …”
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Development of an explainable machine learning model for predicting depression in adults with type 2 diabetes mellitus: a cross-sectional SHAP-based analysis of NHANES 2009-2023 by Tang, Yan, Jia, Lei, Zhou, Junjun, Dou, Jin, Qian, Jingjuan, Yi, Xin, Soh, Kim Lam

“…Twenty-eight candidate predictors encompassing demographic characteristics, clinical and biochemical measurements, and lifestyle factors were initially included. Variable selection was performed using least absolute shrinkage and selection operator regression. …”
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An acquisition and a modulated recognition system for driver profiling in Malaysia / Ward Ahmed Alaulddin Al-Hussein by Ward Ahmed Alaulddin , Al-Hussein

“…The results have shown that CNN outperformed the other two classification algorithms in terms of accuracy, precision, recall, and f-measure and was therefore selected for a recognition system that, in combination with the acquisition system, would assist traffic police and insurance firms in detecting unsafe driving behaviors. …”
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Investigating computational thinking among primary school students in Terengganu using visual programming by Osmanullrazi, Abdullah

“…The experiment was divided into three phases namely, the introduction of algorithm and Scratch interface, the creation of animation and games and in the final phase, participants were allowed to choose either to develop animation or games as their final project. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

“…Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
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Enhanced extreme learning machine for general regression and classification tasks by Mahmood, Saif F

“…The first challenge is to select the optimal number of hidden nodes for ELM in different application. …”
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