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Articles by Erdal Akin
Real time VBNE and leakage current monitoring in hospital electrical systems: a low cost approach
Abstract Neutral to earth voltage (VBNE) in hospital electrical installations can reveal grounding issues or leakage currents that threaten patient safety and sensitive medical equipment. Patients with varying electrical resistances are particularly at risk, highlighting the need for continuous monitoring. This study presents a low cost, Arduino based relay system programmed in C + + for real time VBNE measurement, providing visual and audible alerts when thresholds are exceeded.
CalFireSegNet: a lightweight hybrid attention–transformer network for post-wildfire building footprint change analysis using high-resolution satellite imagery
Abstract Natural disasters, particularly wildfires, cause severe human, environmental, and economic losses worldwide. Rapid and accurate identification of building footprints and potential potential structural changes is essential for effective emergency response, search-and-rescue operations, and post-disaster recovery planning.
Optimal control of a heat flow system via novel enhanced quadratic interpolation optimization tuned 2DOF-PID controller
Abstract This study addresses the optimal temperature regulation problem of a laboratory-scale heat flow system using a two-degree-of-freedom proportional–integral–derivative (2DOF-PID) controller tuned by a newly developed enhanced quadratic interpolation optimization (eQIO) algorithm.
Temperature regulation of a nonlinear CSTR using a global-guided optimization-based PID framework
Abstract Accurate temperature regulation in nonlinear continuous stirred tank reactors (CSTRs) remains a challenging task due to strong nonlinearities and operating-point sensitivity. Although numerous proportional-integral-derivative (PID) tuning approaches have been proposed, most existing studies primarily focus on nominal operating conditions, often resulting in degraded performance under varying process dynamics.
A Comprehensive Survey: Evaluating the Efficiency of Artificial Intelligence and Machine Learning Techniques on Cyber Security Solutions
Abstract: Given the continually rising frequency of cyberattacks, the adoption of artificial intelligence methods, particularly Machine Learning (ML), Deep Learning (DL), and Reinforcement Learning (RL), has become essential in the realm of cybersecurity. These techniques have proven to be effective in detecting and mitigating cyberattacks, which can cause significant harm to individuals, organizations, and even countries.
A Novel Blockchain-Based Scientific Publishing System
Open AccessArticle by Mansur Beştaş 1, Ruhi Taş 2, Erdal Akin 3, Merve Ozkan-Okay 4,*, Ömer Aslan 5 and Semih Serkant Aktug 6 1 IT Department, Siirt University, Siirt 56000, Turkey 2 Department of Computer Engineering, Faculty of Engineering, Ostim Technical University, Ankara 06374, Turkey 3 Department of Computer Engineering, Faculty of Engineering, Bitlis Eren University, Bitlis 13100, Turkey 4 Department of Computer Engineering, Faculty of Engineering, Ankara University, Ankara 06830,...
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