Modeling And Detection of Cracks in Earthenware Water Jugs Using Artificial Neural Networks and Image Processing Techniques
Department of Management Information System, Batman University, Batman, Turkiye

Published: December 28, 2025
This issue of the International Journal of Applied Methods in Electronics and Computers (Vol. 13, No. 4, 2025) presents innovative research contributions focused on power electronics, intelligent inspection systems, and biomedical measurement applications. Featured studies include a bidirectional PUC converter–based battery storage system designed for active and reactive power control, and an artificial neural network–driven approach combined with image processing techniques for modeling and detecting cracks in earthenware water jugs. The issue also explores microwave dielectric measurement methods to determine sensitive frequency bands for cytotoxicity analysis, offering valuable insights into advanced sensing and analysis techniques in applied engineering research.
Department of Management Information System, Batman University, Batman, Turkiye
Department of Electronics and Automation, Vocational School of Trade and Industry, KTO Karatay University, Konya, Turkiye; Electrical and Electronics Engineering Department, Necmettin Erbakan University, Konya, Turkiye
Sakarya University of Applied Sciences, School of Information Technologies, Department of Software, Application Development and Analysis, Sakarya, Turkiye.; Selçuk University, Faculty of Technology, Department of Computer Engineering, Konya, Turkiye.
Seydisehir Ilica Vocational and Technical Anatolian High School, Konya, Türkiye; Selçuk University, Faculty of Technology, Department of Electrical and Electronics Engineering, Konya, Türkiye.
Electrical and Electronics Engineering, Faculty of Engineering, Gaziantep University, Gaziantep, Türkiye