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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics
Karam Mazin Zeki Othman
Northern Technical University
Computer Science & IT Electrical & Electronics Engineering

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Scaled conjugate gradient ANN for industrial sensors calibration Karam Mazin Zeki Othman; Abdulkreem M Salih
Bulletin of Electrical Engineering and Informatics Vol 10, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i2.2738

Abstract

In this paper, artificial neural network is used to calibrate sensors that are commonly used in industry. Usually, such sensors have nonlinear input output characteristic that makes their calibration process rather inaccurate and unsatisfied. Artificial neural network is utilized in an inverse model learning mode to precisely calibrate such sensors. The scaled conjugate gradient (SCG) algorithm is used in the learning process. Three types of industrial sensors which are gas concentration sensor, force sensors and humidity sensors are considered in this work. It is found that the proposed calibration technique gives fast, robust and satisfactory results.
Therapeutic management of diseases based on fuzzy logic system- hypertriglyceridemia as a case study Karam Mazin Zeki Othman; Nameer Mazin Zeki
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 2: April 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i2.23564

Abstract

The support systems for assisting clinical decision highly improve the quality and efficiency of the therapeutic and diagnostic treatment in medicine. The proper implementation of such systems can emulate the reasoning of health care professionals in such a way that suggest reasonable decisions on patient treatment. The fuzzy logic system can be considered as one of the efficient techniques for converting a complex decision tree that usually facing the physician into artificial intelligent procedure embedded in a computer program. So many properties in fuzzy logic system that can facilitate the process of medical diagnosis and therapeutic management. In this paper, a system for therapeutic management of hypertriglyceridemia was efficiently realized using a fuzzy logic technique. The obtained results had shown that the proposed fuzzy logic contributes a reliable managing procedure for assisting the physicians and pharmacist in treating the hypertriglyceridemia. Many different hypertriglyceridemia treatment cases showed a perfect matching decision between the standard guidelines and that given by the proposed system.
Co-Authors Abdulkreem M Salih Nameer Mazin Zeki