https://journals.tultech.eu/index.php/jtse <p><strong>Journal of Transactions in Systems Engineering (JTSE)</strong> is an open-access and peer-reviewed journal that provides the latest research and developments in all theoretical and practical aspects and fields of engineering applications, informatics, and engineering systems design. The journal publishes three times a year (January, June, and October). All the content is freely available without charge to the user or his/her institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, without asking prior permission from the publisher or the author. This is in accordance with the DOAJ and BOAI definition of open access..</p> TULTECH en-US Journal of Transactions in Systems Engineering 2806-2973 https://journals.tultech.eu/index.php/jtse/article/view/235 <p style="font-weight: 400;">The growing amount of e-waste has become a major problem, especially in industrialized areas like the Czech Republic, where 15.7 kg of e-waste was produced annually per person in 2019. This study responds by offering a motivating e-waste management program targeted at the Technical University of Liberec (TUL), the CXI, and the surrounding area. The program predicts significant economic gains through the use of metal recovery techniques, particularly electrolysis: roughly 165,000 CZK per year at CXI, more than 5 million CZK at TUL, 85 million CZK in Liberec, and up to 8.6 billion CZK nationwide. These figures take into account the profits from metal recovery, and they might be improved even more by include the costs of trash management services. The suggested approach, which offers a range of incentives to employees and community members, has the potential to create a circular economy, increase financial returns, and promote environmental sustainability. In order to increase exposure and awareness, the initiative also involves local schools and integrates public participation. The goal of this community driven strategy is to establish TUL as a leader in environmentally friendly operations.</p> Mohammad Gheibi Seyyed Roohollah Masoomi Mahad Uzairu Magala Diana Nalugo Aisha Twahir Hussein Kassim Copyright (c) 2024 https://creativecommons.org/licenses/by/4.0 2024-12-14 2024-12-14 3 1 325 339 10.15157/JTSE.2025.3.1.325-339 https://journals.tultech.eu/index.php/jtse/article/view/247 <div class="page" title="Page 1"> <div class="layoutArea"> <div class="column"> <p>Applications of image processing in radiology and radiation are critical for the development of models, simulations, and computational tools. 3D Slicer is a widely used platform for processing, segmenting, visualizing, registering, and analyzing medical images, as well as for image-guided treatments. Image segmentation, which focuses on identifying specific regions in the image such as tumors or lesions, is one of the most common challenges in medical image processing. In this research work we have utilized 3D Slicer to implement simulation techniques and automation for imaging diagnostics, computation, and prediction. This paper expands on the HD Brain Extraction module in 3D Slicer to autonomously segment brain MRI images using artificial intelligence. To optimize the brain extraction process, various adjustable parameters including segmentation techniques, threshold values, and smoothing factors are fine-tuned. The brain is then extracted from MRI images for further analysis and visualization.</p> </div> </div> </div> Elda Spahiu Dafina Xhako Niko Hyka Suela Hoxhaj Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0 2025-02-05 2025-02-05 3 1 340 348 10.15157/JTSE.2025.3.1.340-348