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This paper aims to describe several artificial intelligence (AI)-based applications that librarians can use to serve and design virtual library instruction, so it will be more effective and efficient.

The approach involves a comprehensive review of AI-based applications that bring benefits to librarian to enhance the virtual instructional services (AI). This study explores the existing papers to reveal the potential use of AI for research consultation, designing the instructional services and conducting evaluation of the program.

There are some AI-based applications that are available for free that will help instructional librarian jobs. Librarians use the AI to increase effectiveness of the services. The AI-based applications that can be used to support instructional services on research inquiries include virtual assistance, knowledge mapping and note making, and to support designing virtual instruction, librarians can use design apps, image generators, voice generator, grammar checker and paraphrasing.

There are many studies on AI at the library; however, it’s still rare a paper studied AI-based application that potentially will bring benefit for virtual instructional services. This paper will give overview of AI application that will help instructional librarian on transactions with users and help librarians to create innovative instructional media.

This study sought to analyze the correlation between artificial intelligence (AI) and libraries and examine whether there were any shifts in research trends related to these two topics during the coronavirus pandemic.

The study gathered secondary data from the Scopus website using the keywords “AI,” “library” and “repository,” from 1993 to 2022. Data were re-analyzed using the bibliometric software VOSviewer to examine the trending country's keyword relations and appearance and Biblioshiny to study the publication metadata.

Index keywords, such as “human,” “deep learning,” “machine learning,” “surveys” and “open-source software,” became popular during 2020, being closely related to digital libraries. Additionally, the annual scientific production of papers increased significantly in 2021. Words related to data mining also had the most significant growth from 2019 to 2022 because of the importance of data mining for library services during the pandemic.

This study provides insight for librarians for the implementation of AI to support repositories during the pandemic. Librarians can learn how to maximize the AI-based repository services in academic libraries during the pandemic. Furthermore, academic libraries can create policies for repository services using AI.

This study can lead researchers, academicians and practitioners in conducting research on AI in library repositories.

As research on AI and digital repositories remains limited, the study identifies themes and highlights the knowledge gap existing in the field.

Deployment of health and safety standards in extremely hazardous work environments such as oil and gas sector, is essential to minimise accidents leaving employees permanently or temporarily incapacitated. The purpose of this research, is to understand why there are frequent accidents in case country's oil and gas sector, with a view to recommend solutions to mitigate problems.

Research methodology involved extensive review of the literature to appreciate background, and current research on typical accidents and safety measures taken at oil and gas construction sites to minimise accidents in a middle east country. Interviews, questionnaires and case stidies were deployed to acquire data which highlighted major reasons for accidents occurrence at oil and gas construction sites, and safety tools and techniques that could reduce accident rate if adopted by companies.

Findings, showed that oil and gas construction projects in case country were prone to health and safety related risks, challenges and accidents due to failure to comply with standards and legislation. Construction site teams and shop floor staff were rarely involved in development of safety policies, and some had no understanding of requirements and procedures underpinning safety during operations. Research recommended rapid application/adoption of international standards underpinned by ISO 45000 series and staff training at all levels. Deployment of robots and use of machine learning technology were suggested to implement risky tasks in the sector.

Research was based on rampant accidents occurring in hazardous oil and gas sector in country studied. Enforcement of health and safety standards, and use of modern tools and techniques were recommended to minimise accident rate.