Journal of Engineering and Emerging Technologies

From ChatGPT-3 to GPT-4: A Significant Advancement in AI-Driven NLP Tools

Md. Saidur Rahaman — 2023-05-11

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 & 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 & 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.

Development and Evaluation of an Onion Bulb Size Grading Machine: A Promising Solution to Enhance Efficiency and Reduce Costs for Local Onion Farmers

Marjun Caguay — 2023-12-01

The developed Red Onion (Allium cepa L.) Stem Cutting Machine is a trolley-type cutting machine designed and fabricated to reduce production costs, labor, and time required for cutting onion stems. A single person can operate it. The machine weighs 64.8 kg and has overall dimensions of 1050 mm in height, 1010 mm in length, and 525 mm in width. The machine’s major components include counter-rotating blades, counter-rotating gears, frame assembly, collecting bin, wheels, and power transmission assembly. Onions are fed into the input chute where the counter-rotating blades are located. The cut onions are collected in the bin below the machine. Three treatments were used to evaluate the study: 440 rpm, 660 rpm, and 990 rpm. The experimental layout followed a Completely Randomized Design (CRD) and was ana- lyzed using the Analysis of Variance test. The mean comparison was carried out using the Least Significant Difference (LSD) method, with a 5% significance level. The machine’s performance was evaluated in terms of machine cutting capacity, efficiency, and energy demand. The results indicate that at 660 rpm, the machine achieved a Capacity of 57.91 kg/h, efficiency of 95.51%, and Energy demand of 4.3 W-h/kg. Cost analysis revealed that the machine needs to cut a total of 7,513.67 kg of onions to break even, assuming a custom rate of Php 1.30/kg. The payback period is approximately two and a half harvesting seasons. This machine is recommended for local onion farmers to help them streamline their post-harvest onion processing

Development Of Red Onion (Allium Cepa L.) Stem Cutting Machine

Marjun Caguay — 2023-12-01

The developed Red Onion (Allium cepa L.) Stem Cutting Machine is a trolley-type cutting machine designed and fabricated to reduce production costs, labor, and time required for cutting onion stems. A single person can operate it. The machine weighs 64.8 kg and has overall dimensions of 1050 mm in height, 1010 mm in length, and 525 mm in width. The machine's major components include counter-rotating blades, counter-rotating gears, frame assembly, collecting bin, wheels, and power transmission assembly. Onions are fed into the input chute where the counter-rotating blades are located. The cut onions are collected in the bin below the machine. Three treatments were used to evaluate the study: 440 rpm, 660 rpm, and 990 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 5\% significance level. The machine's performance was evaluated in terms of machine cutting capacity, efficiency, and energy demand. The results indicate that at 660 rpm, the machine achieved a Capacity of 57.91 kg/h, efficiency of 95.51\%, and Energy demand of 4.3 W-h/kg. Cost analysis revealed that the machine needs to cut a total of 7,513.67 kg of onions to break even, assuming a custom rate of Php 1.30/kg. The payback period is approximately two and a half harvesting seasons. This machine is recommended for local onion farmers to help them streamline their post-harvest onion processing.