The main objective of this study was to look for the electromagnetic interference produced by medical devices in hospitals and to evaluate its impacts on the proper functions of such devices. However, the present study encountered other important problems with regard to CT scanner and X-ray Imaging systems. Such problems demand fast responses in order to secure health safety for the patients and the operators of such systems.

Identifying the psychological instability in mental health assessment through the application of ML techniques, using the principally the RFA (Random Forest Algorithm). This research investigates the application of machine learning techniques to detect psychological instability in individuals. By employing a variety of algorithms, including both supervised and unsupervised learning methods, this study aims to predict psychological states based on diverse data inputs such as behavioural patterns, physiological signals, and social interactions. The models are developed and validated using datasets from clinical studies, social media activity, and wearable health devices. The results illustrate the capability of ML to provide accurate and timely predictions of psychological instability, offering valuable insights for early diagnosis and intervention in mental health care. This study advances the field by demonstrating a data-driven approach to understanding and managing psychological health.

A significant issue in the application of simulation tools in production processes is the difficulty in effectively integrating these tools into existing logistics systems, which often leads to underutilization and suboptimal performance. According to a study by McKinsey & Company (2017), only 17% of companies have successfully integrated advanced simulation tools into their logistics processes, resulting in considerable inefficiencies. Additionally, a report by Gartner (2020) highlighted that 55% of organizations face significant challenges in aligning simulation technologies with their operational workflows, often due to a lack of expertise and inadequate technological infrastructure. This document provides a qualitative analysis to present a current overview of the application areas and benefits of simulation tools in intralogistics processes through a systematic literature review of 108 articles published between 2011 and 2023. The primary focus to explore is about operational warehouses processes, examining applications by country, knowledge area, simulation tool type, practical or theoretical application and implementation challenges of simulation.