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Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis by Kabir Ahmad, Farzana, Kamaruddin, Siti Sakira, Yusof, Yuhanis, Yusoff, Nooraini

“…Thus, this study proposed a Bat Algorithm (BA) to address the complex learning structure of DBN in detecting sentiment patterns. …”
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Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar by Ja'afar, Nur Shahirah

“…To overcome these limitations, this research has proposed five machine learning algorithms namely Linear Regression, Lasso, Ridge, Random Forest and Decision Tree. …”
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Integrating of web 2.0 technologies for interactive courseware : data structure and algorithm as case study by Mohd Nurhafeezi, Nordin

“…It also has a greater potential for teaching and learning activities and how these technologies impact the education sector. …”
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Predicting machine failure using recurrent neural network-gated recurrent unit (RNN-GRU) through time series data by Zainuddin, Z., P. Akhir, E.A., Hasan, M.H.

“…Thus, this paper offers a deep learning algorithm named recurrent neural network-gated recurrent unit (RNN-GRU) to forecast the state of machines producing the time series data in an oil and gas sector. …”
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Gamification of Regional Tourism Engagement: Analysis and Design of a Web-Based Information System by Johannes Hamonangan, Siregar, Rufman Iman, Akbar, Augury, El Rayeb, Chaerul, Anwar, Suriati Khartini, Jali, Mohamad Imran, Bandan, Phei Chin, Lim, Abby Lian, Hendrick

“…The system integrates a structured gamification algorithm with a scalable relational database model, built using React.js and Firebase, to ensure responsive and consistent user experiences. …”
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Artificial intelligence revolutionising the automotive sector: A comprehensive review of current insights, challenges, and future scope by Hossain, Md Naeem, Rahim, Md. Abdur, Rahman, Md Mustafizur, D., Ramasamy

“…The review highlights that AI has significantly expedited the development of autonomous vehicles regarding navigation, decision-making, and safety features through the use of advanced algorithms and deep learning structures. Furthermore, it identifies advanced driver assistance systems, vehicle health monitoring, and predictive maintenance as the most impactful AI applications, transforming operational safety and maintenance efficiency in modern automotive technologies. …”
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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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Deep learning-based vehicular engine health monitoring system utilising a hybrid convolutional neural network/bidirectional gated recurrent unit by Rahim, Md. Abdur, Rahman, Md Mustafizur, Islam, Md. Shofiqul, Md. Muzahid, Abu Jafar, Rahman, Md. Arafatur, D., Ramasamy

“…To date, hybrid deep learning approaches to vehicle engine diagnostics have been limited, and none have used engine health monitoring and categorisation based on vulnerability assessment and vehicle structural information. …”
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The integration between strategic cost management techniques to improve the performance of Iraqi manufacturing companies by Al-Naser, Khalis Hasan Yousif, Mohamed, Rapiah

“…Data were collected by means of structured questionnaire survey using simple random sampling and a Partial Least Squares (PLS) algorithm and bootstrap techniques were used to test the hypothesis of the paper.The result revealed that TQM had a significant positive effect on BSC through the measurement of customer perspective, financial perspective, innovation and learning perspective, and internal business process perspective.The finding implies that Iraqi manufacturing industries can attain the performance of their companies in the different perspective of BSC by proper implementation of TQM technique.…”
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The interrelations between artificial intelligence (AI) usage and academic performance by Chin, Wie Jane

“…Previous studies have mostly concentrated on technology tools, algorithms, validation, and utilisation rather than their impact on student performance. …”
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الضوابط الشرعية والمهنية للعملات الافتراضية في ظل الرقمنة المالية by Mahmoud Mohamed Ali Mahmoud Edris, Mohamed Sharif Bashir, Muneer Ali Abdul Rab, Ahmad Zaki Salleh

Bayesian network of influence of sociodemographic variables on dengue related knowledge, attitude, and practices in selected areas in Selangor, Malaysia by Ajibola, Lamidi-Sarumoh Alaba

“…Data of socio-demographic variables, medical history about dengue, knowledge about dengue fever and its vectors, attitude towards dengue incidence, elimination of dengue vectors and practices to eradicate the dengue infection and vectors was collected using a structured validated bilingual questionnaire. The data collected was used to learn the structure of BN via some known algorithms using R programming language. …”
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