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Full-Text Articles in Engineering
Machine Learning-Based Prediction Of International Roughness Index For Continuous Reinforced Concrete Pavements, Ragaa T. Abd El-Hakim, Ahmed N. Awaad, Sherif M. El-Badawy
Machine Learning-Based Prediction Of International Roughness Index For Continuous Reinforced Concrete Pavements, Ragaa T. Abd El-Hakim, Ahmed N. Awaad, Sherif M. El-Badawy
Mansoura Engineering Journal
The International Roughness Index (IRI) serves as a crucial indicator for ride quality and user comfort. As road roughness escalates, road serviceability diminishes, resulting in reduced vehicle speed and increased travel time, and consequently higher carbon dioxide emissions. Predicting the IRI is of utmost importance for Pavement Management Systems and sustainable development overall. While numerous studies have forecasted the IRI of flexible pavements, there is a notable scarcity of research focusing on rigid pavement performance prediction. This study addresses the gap in predicting IRI for Continuous Reinforced Concrete Pavements (CRCP), an understudied aspect of pavement engineering. Leveraging the Long-Term Pavement …
Equipment Performance Cost Optimization Using Machine Learning (A Surface Condenser Case Study), Firdaus Basheer, Mohamed Saleem Haja Nazmudeen, Fadzliwati Mohiddin, Elango Natrajan
Equipment Performance Cost Optimization Using Machine Learning (A Surface Condenser Case Study), Firdaus Basheer, Mohamed Saleem Haja Nazmudeen, Fadzliwati Mohiddin, Elango Natrajan
ASEAN Journal on Science and Technology for Development
Equipment performance assessment or prediction has usually been done using the conventional approach. Organization is often too busy to focus on improvement opportunities for equipment performance. Opportunities identifications are heavily reliant on expert opinion and the methods used often vary from one person to another depending on the knowledge they possess. The benefits of simplistic and realistic equipment performance prediction would significantly improve maintenance costs and hence could help to reduce the total operating cost of the asset. In this research work, a surface condenser was used as a case study. The solution proposed in this research work is to …
Word Prediction Using Dynamic Skip Connections Along With Arabert And Lstm In Arabic Language, Ahad Almalki, Faris Kateb, Rayan Mosli
Word Prediction Using Dynamic Skip Connections Along With Arabert And Lstm In Arabic Language, Ahad Almalki, Faris Kateb, Rayan Mosli
ASEAN Journal on Science and Technology for Development
Natural Language Generation (NLG) plays a crucial role in modern digital tools, including chatbots, virtual support, content suggestions, and tailored marketing, making bots more responsive and reducing the need for human staff. While there's much research on NLG for languages like English, languages like Arabic, Urdu, and Chinese still face challenges. This study examines Arabic NLG's unique aspects, dialects, and word variations. With around 420 million Arabic speakers globally, it's crucial to advance NLG for this language. We compared three models: Long Short-Term Memory (LSTM), a mix of Bidirectional Encoder Representations from Transformers (BERT) and LSTM, and a version that …