Open Artificial Intelligence (AI) published an AI chatbot tool called ChatGPT at the end of November 2022. Generative Pre-trained Transformer (GPT) architecture is the foundation of ChatGPT. On the internet, ChatGPT has been rapidly growing. This chatbot enables users to discuss with the AI by inputting prompts, and it is based on OpenAI’s language model. Although ChatGPT is fantastic and produces exciting results for writing tales, poetry, songs, essays, and other things, it has certain restrictions. Users may ask the bot questions, and it will reply with pertinent, convincing subjects and replies. ChatGPT has now risen to the top of several academic agendas. Administrators create task teams and hold institution-wide meetings to react to the tools, with most of the advice being to adopt this technology. This paper briefs about the ChatGPT and its need. Further, various Progressive Work Flow Processes of the ChatGPT Tool are stated diagrammatically. Specific features and capabilities of the ChatGPT Support System are studied in this paper. Finally, we identified and discussed the significant roles of ChatGPT in the current scenario. The neural language models that form the foundation of character AI have been developed from the bottom up with talks in mind. This technology implies that the programme uses deep learning methods to analyse and produce text. The model “understands” the subtleties of human-produced natural language using vast amounts of data from the internet. 

An era of ChatGPT as a significant futuristic support tool: A study on features, abilities, and challenges

Electronic commerce or e-commerce includes the service and good exchange through electronic support like the Internet It plays a crucial role in today's business and users' experience Also, e-commerce platforms produce a vast amount of information So, Recommender Systems (RSs) are a solution to overcome the information overload problem They provide personalized recommendations to improve user satisfaction The present article illustrates a comprehensive and Systematic Literature Review (SLR) regarding the papers published in the field of e-commerce recommender systems We reviewed the selected papers to identify the gaps and significant issues of the RSs' traditional methods, which guide the researchers to do future work So, we provided the traditional techniques, challenges, and open issues concerning traditional methods of the field of review based on the selected papers This review includes five categories of the RSs' algorithms, including Content-Based Filtering (CBF), Collaborative Filtering (CF), Demographic-Based Filtering (DBF), hybrid filtering, and Knowledge-Based Filtering (KBF) Also, the salient points of each selected paper are briefly reported The publication time of the selected papers ranged from 2008 to 2019 Also, we provided a comparison table of important issues of the selected papers as well as the tables of advantages and disadvantages Moreover, we provided a comparative table of metrics and review issues for the selected papers And finally, the conclusions can, to a great extent, provide valuable guidelines for future studies

/pdf/a-systematic-study-on-the-recommender-systems-in-the-e-24eg8g97m8.pdf

A Systematic Study on the Recommender Systems in the E-Commerce

This research aims to explore the potential impact of the ChatGPT on b-learning methodologies in engineering education, specifically in mathematics. The study focuses on how the use of these artificial intelligence tools can affect the acquisition of critical thinking, problem-solving, and group work skills among students. The research also analyzes the students’ perception of the reliability, usefulness, and importance of these tools in academia. The study collected data through a survey of 110 students enrolled in a Mathematics I course in BEng Aerospace Engineering where a blended methodology, including flipped teaching, escape room gamification, problem-solving, and laboratory sessions and exams with a computer algebraic system were used. The data collected were analyzed using statistical methods and tests for significance. Results indicate students have quickly adopted ChatGPT tool, exhibiting high confidence in their responses (3.4/5) and general usage in the learning process (3.61/5), alongside a positive evaluation. However, concerns arose regarding the potential impact on developing lateral competencies essential for future engineers (2.8/5). The study concludes that the use of ChatGPT in blended learning methodologies poses new challenges for education in engineering, which requires the adaptation of teaching strategies and methodologies to ensure the development of essential skills for future engineers.

/pdf/chatgpt-challenges-blended-learning-methodologies-in-3d03z6go.pdf

ChatGPT Challenges Blended Learning Methodologies in Engineering Education: A Case Study in Mathematics

Computer science has been revolutionized by artificial intelligence (AI), which has opened up new paths for data analysis, modelling, and prediction. ChatGPT, a language model based on deep neural networks, has shown promise in natural language processing, picture identification, and data analysis. However, integrating ChatGPT and other AI models into scientific research presents obstacles and constraints. This study aims to analyze the limitations of ChatGPT and AI in computer science research and provide methods to address these shortcomings. Specifically, we concentrate on two primary goals: first, Domain expertise restrictions: There may be a lack of specialized subject expertise in ChatGPT and comparable language models, providing difficulties for researchers in particular domains. We investigate techniques to improve domain knowledge integration into AI models, allowing for more precise and contextually relevant predictions. Second, interpretability difficulties: The interpretability of AI models continues to be a significant challenge, impeding researchers' ability to comprehend how algorithms create predictions. We address this issue by suggesting strategies for enhancing interpretability, giving researchers insights into the decision-making processes of AI models. We hope to promote AI's ethical and responsible use in scientific research by addressing these objectives. We examine various strategies to improve the representation of domain knowledge within AI models and its interpretability, enabling researchers to utilize the benefits of ChatGPT and AI while limiting their limitations.

Pushing the Envelope: Investigating the Potential and Limitations of ChatGPT and Artificial Intelligence in Advancing Computer Science Research

The influence of the moon cycles on the ichthyofauna has been little studied in the surf zone. In this study, the number of species, density and biomass were evaluated as a function of the moon. A total of 49 species distributed in 24 families were captured in two areas of Miramar beach. The mean density was significant high in the weaning and low in the new moon, while density and biomass together showed differences for areas. The most abundant species were Anchoa tricolor and Trachinotus falcatus (new moon), and Anchovia clupeoides showed significant differences in the waning moon. The RDA indicates that turbidity influenced significantly the presence of two species group. The group I were represented by Stellifer brasiliensis, Trachinotus goodei, A. clupeoides, Chilomycterus spinosus and Conodon nobilis that occurred on the waning and new phases in both areas, while the group II were represented by Polydactylus virginicus and Haemulopsis corvinaeformis in the full moon. The surf zones may also be strongly governed by the lunar phases. Therefore, the results found in this study, showed that the biological interactions between the species with turbidity and moon might explain the density and biomass variations for some species in the surf zone.

/pdf/composition-density-and-biomass-of-fish-community-from-the-4dq08fjbh9.pdf

Composition, density and biomass of fish community from the surf zone as a function of the lunar cycle at Miramar Beach in Cabedelo, Paraíba

PurposeIn 2014, real estate investment trust (REIT) emerged as a new alternative investment option in India. This research aims to give an empirical authentication of the Indian REITs performance from April 2019 to July 2022 across a range of investment variables.Design/methodology/approachUsing monthly total returns in Indian Rupee, risk-adjusted Indian REIT performance and investment portfolio characteristics are examined. Indian REITs' potential in a diversified multi-asset portfolio is analysed using the mean-variance analysis, asset allocation diagram and efficient frontier.FindingsDuring April 2019–July 2022, Indian REITs provided a lower return than stocks but outperformed bonds despite coronavirus disease 2019 (COVID-19) lockdowns, which hurt the traditional working from office concept. The study also examined REIT allocation to an Indian mixed-asset portfolio and the benefits of a diversified portfolio.Practical implicationsIndian REITs provide a liquid, transparent alternative to direct property for investors seeking exposure to Indian real estate markets. Indian REITs gave real estate companies an extra funding source and investors an alternate asset. This paper explores Indian REITs' potential opportunities, given that domestic and foreign investors' demand for transparent property investment in India. The analysis found a positive early performance despite a challenging environment.Originality/valueThis paper offers the first empirical performance validation of Indian REITs as a way to obtain exposure to commercial property in India and the REITs' role in a diversified asset portfolio. The authors' study improves investors' decision-making abilities by providing empirically validated, valuable and practicable property investing insights.

Analysis of the emergence and initial performance of REITs in India

OpenAI created ChatGPT, an Artificial Intelligence based Chatbot that responds conversationally to lengthy, complicated enquiries. The present paper is a guide to how the potential of ChatGPT can be used fully to perform effective research studies in the shortest possible time. 

Performing Effective Research Using ChatGPT

A research study found that fish and prawn prefer light whereas shrimp may not. There is a vertical movement of fish movement is found owing to light as on moon lit days when the fish catch may become more considering the fact the fishing efforts and gear remaining similar in all days of lunar periodicity. Estuarine fishes in Sundarban Rivers are caught more during such dates. Optimum fishing days may also determined by the intensity and duration of moon lit in total night hours.

https://www.fisheriesjournal.com/archives/2015/vol2issue4/PartF/2-4-88-162.pdf

The optimum fishing day is based on moon

This paper is an initial attempt towards the direction of analysis of performances of Indian public and private non-life insurance companies and towards forecasting of future growth potential of the sector. This paper also presents future prospects and growth potentiality of the non-life insurance sector in India along with the current state of the underwriting cycle prevalent in the Indian non-life insurance industry. This paper presents a detailed analysis of the underwriting performance of the non-life insurance sector as a whole during the post-liberalization period of 2000-2001 to 2014-2015. It depicts a colorful prospect for the Indian non-life insurance industry in the next 10 years. This paper has also been devoted to the determination of the presence of an underwriting cycle (pattern) that exists in the performances of the non-life insurance companies (public and private) during the last 15 years.

https://archive.aessweb.com/index.php/5004/article/download/3961/6237

Forecasting performance of Indian non-life insurance industry - an analysis of underwriting experience of public and private insurance companies

Recommender System in E-Commerce : Bringing Revolution in Marine Product Industry

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Analysis of the emergence and initial performance of REITs in India

Performing Effective Research Using ChatGPT

The optimum fishing day is based on moon

Forecasting performance of Indian non-life insurance industry - an analysis of underwriting experience of public and private insurance companies

Recommender System in E-Commerce : Bringing Revolution in Marine Product Industry