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In this study, using the fuzzy logic method, a stress detection tool was created with body temperature and blood pressure parameters as indicators to determine a person's stress level. This tool uses the LM35DZ sensor to detect body temperature, the MPX5100GP sensor to read blood pressure values, and Arduino Uno as a data processor from sensor readings which are then calculated using the fuzzy logic method as a stress level decisionmaker. The resulting output measures blood pressure, body temperature, and the stress level experienced by a person, which will be displayed on the liquid crystal display. Based on the results of testing the body temperature parameter, the highest error generated was 1.17%, and for the blood pressure parameter, the highest error was 2.5% for systole and 0.93% for diastole. Furthermore, testing the stress level displayed on the tool is compared to the depression, anxiety, and stress scales 42 (DASS 42), a psychological stress measuring instrument. From the results of testing the tool with the questionnaire, the average conformity level is 74%.

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8th International Conference on Soft Computing, Mathematics and Control (SMC 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications impacts and challenges of Soft Computing, Mathematics and Control. The conference documents practical and theoretical results which make a fundamental contribution for the development of Soft Computing, Mathematics and Control. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.

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At the forefront of technological innovation and scholarly discourse, the Journal of Electrical Systems (JES) is a peer-reviewed publication dedicated to advancing the understanding and application of electrical systems, communication systems and information science. With a commitment to excellence, we provide a platform for researchers, academics, and professionals to contribute to the ever-evolving field of electrical engineering, communication technology and Information Systems. The mission of JES is to foster the exchange of knowledge and ideas in electrical and communication systems, promoting cutting-edge research and facilitating discussions that drive progress in the field. We aim to be a beacon for those seeking to explore, challenge, and revolutionize the way we harness, distribute, and utilize electrical energy and information systems..

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Exploring AI's Impact: Key Features in Due Diligence In the realm of due diligence, AI emerges as a game-changer, revolutionizing traditional methods with its advanced features. AI-powered algorithms excel in data analysis, swiftly sifting through vast amounts of information for crucial insights. Automation streamlines document review processes, ensuring accuracy and efficiency. Moreover, AI enables predictive analytics, forecasting potential risks and opportunities with precision. With machine learning capabilities, AI continuously improves its performance, adapting to evolving trends and patterns. By integrating AI into due diligence practices, businesses gain a competitive edge, maximizing efficiency and making informed decisions swiftly. AI in due diligence is not just a tool; it's a transformational force driving businesses into the future. https://www.leewayhertz.com/ai-in-due-diligence/

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