Research Article
Knowledge and Utilization of Digital Applications for Effective Service Delivery in Academic Libraries in South-South Universities, Nigeria
Comfort Nwuju Owate*
Issue:
Volume 13, Issue 3, June 2024
Pages:
43-52
Received:
11 April 2024
Accepted:
8 May 2024
Published:
30 May 2024
Abstract: This study investigated knowledge and utilization of digital applications for effective service delivery in academic libraries in South-South universities, Nigeria. 3 research questions and 3 hypotheses were raised. The population included 181 selected Librarians in the twelve (12) selected universities in South-South, Nigeria as a case study. A sample size of 119 Librarians representing 66% of the population served as respondents. Convenience sampling technique was used for the study. A 25-item questionnaire was used for data collection. Cronbach alpha statistics was used to obtain 0.73 reliability. Mean/standard deviation were used for research questions and z-test statistics was used to test the hypotheses at 0.05 level of significance. The result amongst others revealed that, Librarian in both federal and state universities are knowledgeable about Library Catalogue Apps, Library Card and Account Management Apps, Digital Preservation and Archives Apps and others. Meanwhile, Librarians in both federal and state universities poorly utilize Digital Citation Management Apps, Digital Library Card and Account Management Apps and Digital Preservation and Archives Apps. The analysis also shows that, Librarians do not utilize Digital Augmented and Virtual Reality Apps, Digital Library Events and Notifications Apps, Reading and E-Book Apps, Digital Study and Collaboration Apps and Quick Response (QR) Codes scanners. The challenges academic libraries face in promoting digital applications are inadequate skilled staff to operate digital libraries, difficulty in the enforcement of intellectual property rights, non-utilization of digital library Apps.
Abstract: This study investigated knowledge and utilization of digital applications for effective service delivery in academic libraries in South-South universities, Nigeria. 3 research questions and 3 hypotheses were raised. The population included 181 selected Librarians in the twelve (12) selected universities in South-South, Nigeria as a case study. A sa...
Show More
Research Article
Enhancing Electronic Design Automation Tools with an ML-Based Information Retrieval System
Vikash Kumar,
Shideh Yavary Mehr*
Issue:
Volume 13, Issue 3, June 2024
Pages:
53-58
Received:
17 May 2024
Accepted:
4 June 2024
Published:
19 June 2024
DOI:
10.11648/j.ijiis.20241303.12
Downloads:
Views:
Abstract: Over the past fifty years, Electronic Design Automation (EDA) tools have played a crucial role in the semiconductor industry, assisting in the design, simulation, and manufacturing of integrated circuits (ICs). However, the sophisticated nature of these tools often demands extensive expertise, which can be a barrier for many users. Mastery of these tools necessitates specialized knowledge and skills, including comprehension of complex algorithms, design methodologies, and tool-specific workflows. To address this challenge, this paper introduces a machine learning (ML) based information retrieval system designed to enhance the usability of EDA tools. The objective of this system is to simplify user interactions and make EDA tools more accessible to designers, regardless of their expertise level. The main idea of this ML-driven system is to provide a chatbot-like interface that facilitates efficient, context-aware searches and offers interactive, step-by-step guidance on using various tool functionalities. By integrating natural language processing and machine learning techniques, the system can understand user queries, extract relevant information from the tool's documentation, and provide context-specific guidance. This approach helps to mitigate the steep learning curve associated with advanced EDA applications and enhances tool accessibility. Consequently, it promotes a more intuitive interaction with sophisticated EDA software, thus fostering enhanced usability of complex tools in the semiconductor industry. This work exemplifies the transformative potential of integrating machine learning with conversational user interfaces in making sophisticated software applications more user-friendly.
Abstract: Over the past fifty years, Electronic Design Automation (EDA) tools have played a crucial role in the semiconductor industry, assisting in the design, simulation, and manufacturing of integrated circuits (ICs). However, the sophisticated nature of these tools often demands extensive expertise, which can be a barrier for many users. Mastery of these...
Show More
