Pakistan Journal of Engineering and Technology <p>Pakistan Journal of Engineering and Technology (PakJET)<em>&nbsp;</em>is a peer-reviewed, scientific, and technical journal owned and published by the Faculty of Engineering and Technology, The University of Lahore, Lahore, Pakistan<em>.&nbsp;</em>PakJET&nbsp;publishes high-quality original scientific articles dealing with the use of analytic and quantitative tools for the modeling, analysis, design and engineering management in the Engineering and technology disciplines. The <strong>scope</strong> of the journal falls in all fields of&nbsp;<strong>Electrical, Electronics, Civil, Mechanical, Biomedical, Software and Computer Engineering</strong>.&nbsp; <strong>The journal does not charge any Article Processing Charges (APCs)/fee for the publication and submission of the articles.</strong></p> en-US <h3>COPYRIGHT POLICY</h3> <p>UOL journals follow an <strong>open-access</strong> publishing policy and full text of all articles is available free, immediately upon acceptance. Articles are published and distributed under the terms of the CC BY-SA 4.0 International License. Thus, work submitted to UOL Journals implies that it is original, unpublished work of the authors; neither published previously nor accepted/under consideration for publication elsewhere.&nbsp;</p> <p>Authors will be responsible for any information written/informed/reported in the submitted manuscript. Although we do not require authors to submit the data collection documents and coded sheets used to do quantitative or qualitative analysis, we may request it at any time during the publication process, including after the article has been published. It is author's responsibility to obtain signed permission from the copyright holder to use and reproduce text, illustrations, tables, etc., published previously in other journals, electronic or print media.</p> <p>Conflict of interest statements will be published at the end of the article. If no conflict of interest exists, the following sentence will be used: "The authors declare no conflict of interest." Authors are required to disclose any sponsorship or funding received from any institution relating to their research. 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After publication of the article, it may be posted anywhere with full journal citation included.</p> <p>All articles published in UOL journals are <strong>open-access</strong> articles, published and distributed under the terms of the Creative Commons Attribution-ShareAlike 4.0 International License which permits remixing, transformation, or building upon the material, provided the original work is appropriately cited mentioning the authors and the publisher, as well as the produced work is distributed under the same license as the original.</p> <p>In the future, UOL may reproduce printed copies of articles in any form. Without prejudice to the terms of the license given below, we retain the right to reproduce author's articles in this way.</p> <h3>Brief Summary Of The License Agreement</h3> <p>By submitting your research article(s) to UOL Journal(s), you agree to Creative Commons Attribution-ShareAlike 4.0 International License which states that:</p> <p>Anyone is free:</p> <p>o To copy and redistribute the material in any medium or format<br>o To remix, transform, or build upon the material for any purpose, even commercially</p> <p>Provided:</p> <p>o The author and the publisher have been appropriately credited<br>o The link to license is provided<br>o Indicated if any changes were made<br>o The material produced is distributed under the same license as the original</p> <p>&nbsp;</p> (PakJET) (Dr. Muhammad Rashad) Thu, 21 Sep 2023 09:13:19 +0500 OJS 60 Graphical User Interface-Based Detection of Kidney Stones Using Image Segmentation Techniques <p>The exponential increase in detrimental surroundings and unhealthy nourishments is causing various health issues in humans. The most destructive effect of such lifestyles is on the kidneys, which cause many kidney diseases, and the most common among them are kidney stones. Kidney stones are a regular but life-threatening disease as they mostly remain unrecognized at the initial stages, leading to an increased threat of end-stage kidney failure. Due to the high recurring rate, Medical Imaging technologies are of paramount importance in detecting this serious public health threat worldwide. This research paper provides a Graphical User Interface for the detection of kidney stones that enables ease of understanding and point-and-click control of the algorithm in MATLAB. The proposed work uses CT scan images to explore image processing techniques due to their reliability and regularity. The algorithm enhances kidney stone screening by improving image quality and focusing on the region of interest. This study highlights the best solutions of imaging techniques to resolve problems like grainy pixels, low-resolution images, and the inaccurate detection of kidney stones due to size and resemblance with nearby parts. All this begins with examining the medical imaging slices from the body area, which later undergoes preprocessing, segmentation, and boundary detection techniques. To check the accuracy of the algorithm, 12 features were extracted using GLCM. Finally, the obtained features were classified using the Classification Designer App in MATLAB. An accuracy of 99.2% was acquired using Ensemble Classifiers. Also, for further progress in the detection of kidney stones in the future, an AI model can be trained so that it can deal with images having different thresholds for better management of the disease.</p> Khadijah Ali Shah, Zohaib Mushtaq, Syed Muddasir Hussain, Muhammad Haris Aziz ##submission.copyrightStatement## Mon, 18 Sep 2023 11:41:46 +0500 A Review of Real-Time Monitoring of Hybrid Energy Systems by Using Artificial Intelligence and IoT <p>This research focuses on the invention of real-time monitoring of hybrid energy systems using artificial intelligence (AI) and the Internet of Things (IoT). The study aims to develop a monitoring system that provides real-time insights, anomaly detection, fault diagnosis, and energy optimization. The research methodology involves the integration of AI algorithms and IoT devices to collect, analyze, and visualize system data. The results demonstrate the effectiveness of the developed monitoring system in improving system performance, sustainability, and cost savings. The practical implementation and scalability of the system are also addressed, along with future research opportunities. This research contributes to the advancement of monitoring systems for hybrid energy applications, promoting efficiency and sustainability in energy management. This research provides significant contributions to the field of real-time monitoring of hybrid energy systems. The article focuses on addressing key problems related to the real-time monitoring of hybrid energy systems using AI and IoT technologies. The lack of real-time insights provided by conventional methods also limits timely decision-making and responsiveness to dynamic changes in the system.</p> Zuhaib Nishtar, Jamil Afzal ##submission.copyrightStatement## Thu, 21 Sep 2023 10:54:39 +0500