Special Issue on Computing, Engineering and Sciences (SI-CES 2024-25) - 4 Articles
Software Development and Application for Sound Wave Analysis
by Eunsung Jekal, Juhyun Ku and Hyoeun Park
Journal of Engineering Research and Sciences, Volume 4, Issue 3, Page # 8-21, 2025; DOI: 10.55708/js0403002
Abstract: In this paper, we developed our own software that can analyze piano performance by using short-time Fourier transform, non-negative matrix decomposition, and root mean square. Additionally, we provided results that reflected the characteristics and signal analysis of various performers for the reliability of the developed software. The software was coded through Python, and it actively… Read More
(This article belongs to the Special Issue on Special Issue on Computing, Engineering and Sciences (SI-CES 2024-25) and the Section Acoustics (ACO))
Water Potability Prediction Using Neural Networks
by Ranyah Taha, Fuad Musleh and Abdel Rahman Musleh
Journal of Engineering Research and Sciences, Volume 4, Issue 5, Page # 1-9, 2025; DOI: 10.55708/js0405001
Abstract: The crucial need for maintaining specific water potability levels depending on the sector of utilization, this is becoming increasingly challenging due to the increased pollution. It is therefore important to have fast and reliable water potability assessment techniques. A subset of Machine Learning (ML); being Deep Learning (DL), can be utilized to develop models capable… Read More
(This article belongs to the Special Issue on Special Issue on Computing, Engineering and Sciences (SI-CES 2024-25) and the Section Artificial Intelligence – Computer Science (AIC))
Cavity Sensing for Defect Prevention in Injection Molding
by Oumayma Haberchad and Yassine Salih-Alj
Journal of Engineering Research and Sciences, Volume 4, Issue 5, Page # 10-19, 2025; DOI: 10.55708/js0405002
Abstract: Real-time monitoring of injection molding parameters plays a pivotal role in enhancing product quality, reducing defects and improving production. This study presents a cavity data acquisition system for real time monitoring of process parameters inside the mold. The system consists of non-destructive in-mold sensors that monitor the status of the melt within the cavities. Furthermore,… Read More
(This article belongs to the Special Issue on Special Issue on Computing, Engineering and Sciences (SI-CES 2024-25) and the Section Manufacturing Engineering (MNE))
Fire Type Classification in the USA Using Supervised Machine Learning Techniques
by Ranyah Taha, Fuad Musleh and Abdel Rahman Musleh
Journal of Engineering Research and Sciences, Volume 4, Issue 6, Page # 1-8, 2025; DOI: 10.55708/js0406001
Abstract: Wildfires are a growing global concern, causing widespread environmental, economic, and health impacts. In the USA, fire incidents have become more frequent and intense due to factors such as climate change, prolonged droughts, and human activities. Machine learning plays a vital role in predicting and classifying fires by analyzing vast satellite and environmental datasets with… Read More
(This article belongs to the Special Issue on Special Issue on Computing, Engineering and Sciences (SI-CES 2024-25) and the Section Remote Sensing (RMS))