https://journals.cspc.edu.ph/index.php/jeet/issue/feed Journal of Engineering and Emerging Technologies 2023-12-01T00:00:00+08:00 CSPC-CRD Research Publication Management [email protected] Open Journal Systems <p><span style="font-size: 0.875rem; -webkit-text-size-adjust: 100%;">The <strong>Journal of Engineering and Emerging Technologies (JEET)</strong> is a high-quality, open access, and international refereed journal which aims to publish original research papers in areas of engineering and technology, including Civil Engineering, Mechanical Engineering, Electrical Engineering, Electronics Engineering, Computer Science and Engineering, Information Systems, and Technologies. This also covers multidisciplinary and interdisciplinary studies in engineering and technology education, management, and development.</span></p> <p><strong>Print ISSN:</strong> 2782-9421<br /><strong>Online ISSN:</strong> 2984-8172<br /><strong>Frequency:</strong> Annually<br /><strong>Review Type:</strong> Double-blind Review<br /><strong>Submission Link:</strong><a href="https://jeet.cspc.edu.ph"> https://jeet.cspc.edu.ph</a></p> https://journals.cspc.edu.ph/index.php/jeet/article/view/188 From ChatGPT-3 to GPT-4: A Significant Advancement in AI-Driven NLP Tools 2023-05-11T14:22:42+08:00 Md. Saidur Rahaman [email protected] M. M. Tahmid Ahsan [email protected] Nishath Anjum [email protected] Harold Jan R. Terano [email protected] Md. Mizanur Rahman [email protected] <p>Recent improvements in Natural Language Processing (NLP) have led to the creation of powerful language models like Chat Generative Pre-training Transformer (ChatGPT), Google’s BARD, Ernie which has shown to be very good at many different language tasks. But as language tasks get more complicated, having even more advanced NLP tool is essential nowadays. In this study, researchers look at how the latest versions of the GPT language model(GPT-4 &amp; 5) can help with these advancements. The research method for this paper is based on a narrative analysis of the literature, which makes use of secondary data gathered from previously published studies including articles, websites, blogs, and visual and numerical facts etc. Findings of this study revealed that GPT-4 improves the model's training data, the speed with which it can be computed, the flawless answers that it provides with, and its overall performance. This study also shows that GPT-4 does much better than GPT-3.5 at translating languages, answering questions, and figuring out how people feel about things. The study provides a solid basis for building even more advanced NLP tools and programmes like GPT-5. The study will help the AI &amp; LLM researchers, NLP developers and academicians in exploring more into this particular field of study. As this is the first kind of research comparing two NLP tools, therefore researchers suggested going for a quantitative research in the near future to validate the findings of this research.</p> 2023-05-11T00:00:00+08:00 Copyright (c) 2023 Journal of Engineering and Emerging Technologies https://journals.cspc.edu.ph/index.php/jeet/article/view/211 Development and Evaluation of an Onion Bulb Size Grading Machine: A Promising Solution to Enhance Efficiency and Reduce Costs for Local Onion Farmers 2023-07-30T20:52:54+08:00 Marjun Caguay [email protected] Angelica Mae Magboo [email protected] <p>Grading is vital in food processing, ensuring adherence to commercial standards and facilitating marketing. Unfortunately, the Philippine Onion industry lacks a suitable onion grader for field-level operations. Consequently, farmers still resort to manual grading, leading to labor scarcity during peak seasons, increased time and financial costs, and physical strain on the workers. Thus, the study aimed to develop a suitable onion (Allium cepa L.) bulb-size grading machine for farm-level operations. The device comprised six significant parts: input chute, cylindrical grader, discharge unit for onion bulbs, frame assembly, cover of the grading machine, and power transmission assembly. To evaluate the grader's performance, tests assessed grading efficiency, grading capacity, and energy demand at different shaft speeds (10 rpm, 20 rpm, 30 rpm). The experimental layout followed a Completely Randomized Design (CRD) and was analyzed using the Analysis of Variance test. The mean comparison was carried out using the Least Significant Difference (LSD) method, with a significance level set at 5\%. The results revealed that the most effective shaft speed was 10rpm, yielding an impressive 95.45\% grading efficiency and a notable grading capacity of 583.23 kg/hr. The cost analysis indicated that the grader could generate an additional income of at least 82,301.52 Php/year for onion farmers, with a payback period of 0.32 years and a remarkable rate of return of 204.85\%. These findings highlight the grader's cost efficiency, making it a valuable device for onion farmers.</p> 2023-05-23T00:00:00+08:00 Copyright (c) 2023 Journal of Engineering and Emerging Technologies