Volume 8, Issue 1

Over the past decades, blended learning using a flipped classroom approach has become an increasingly important part of global learning development and has gradually revolutionized educational environments. However, in the online part, individual differences of learners are often not considered and treated in an equipollent way, neglecting their needs and personal characteristics, which results in a poor quality of the learning service. Thus the need to improve both the content of e-learning systems and their adaptability requires a careful examination of the direct behavior of students in distance learning platforms. Our study is based on a dataset from the FOAD_FSBM e-learning platform involved in the learning of Moroccan university students. This work is motivated by the fact that professors seek to better understand students’ learning styles, which are founded on the Felder and Silverman Learning Style Model (FSLSM) so that they can offer them adaptive and personalized courses. In this article, we first describe the basic environment of this study and the reasons that led us to choose the Moodle e-learning platform. We also present the format of the courses created to conduct our experiments, and its advantage in e-learning. Then, we highlight the development tools that we used to conduct our studies. Finally, we present the results of our statistical analyses in relation to the performance of the students.

This study explores the perspectives of Indian library professionals on the use of artificial intelligence (AI) in libraries. It aims to understand their knowledge, awareness, and views on AI and its challenges and opportunities. The research adopts a quantitative approach, using a closed-ended survey to collect data from 386 library professionals in academic institutions across India. The survey covers various aspects, including socio-demographic information, AI knowledge, perspectives on AI in libraries, ethical considerations, and adopting AI tools and services. The findings indicate that Indian library professionals are generally aware of AI and its potential benefits in libraries. They believe that AI can enhance library activities, improve accessibility, and support decision-making. However, there are concerns about AI replacing human intelligence within libraries. Factors such as user privacy, funding, staff expertise, and alignment with institutional goals are essential when implementing AI applications. Ethical considerations, including bias and discrimination, intellectual freedom, and transparency, are also significant concerns. AI tools like smart shelving and optical character recognition are among the technologies already adopted in Indian libraries.

The security landscape of Internet of Things (IoT) networks continues to draw significant attention from recent networks; the Version Number Attack (VNA) stands out as a prominent threat to IoT network resources. Routing Protocol for Low-Power and Lossy Network structures low-power and lossy networks through one or more Destination Oriented Directed Acyclic Graphs (DODAGs). Each DODAG is assigned a version number, serving the purpose of ensuring the existence of loop-free paths to the root node. In the event of any inconsistency detected by the root node, the version number is incremented, triggering a global repair process and the reconstruction of the Directed Acyclic Graph. A potential security concern arises when a malicious node advertises a false version number in its control message, compelling the initiation of a global repair process. This study conducts a comprehensive analysis of the VNA’s impact, considering various parameters that have not been explored in previous research articles. These parameters include an examination of the additional forwarding tasks introduced by the attack and an exploration of factors contributing to node hyperactivity (such as loops, local and global repairs, etc.). The article delves into the specific control messages that result in the detrimental effects of the attack, offering a detailed analysis of control overhead, energy consumption, Packet Delivery Ratio, and latency. The obtained results show that the DAO (Destination Advertisement Object) messages dominate the total control overhead and are the main contributor to the total consumer energy, where the closest the malicious node to the sink the more damaging is the attack.

This study delves into artificial intelligence (AI) literacy within Zambian academic libraries, focusing on librarians’ perceptions and applications of AI. The research aims to gauge the AI literacy level among Library and Information Science Professionals in Zambia, identify their awareness and knowledge of AI applications in libraries, and explore their perceptions regarding the advantages and challenges of implementing AI technologies in library services. Data from 82 diverse participants were gathered using purposive and convenience sampling methods. The findings indicate a solid understanding of AI fundamentals among Zambian librarians and positive attitudes towards AI’s potential benefits in library services. However, challenges such as the need for enhanced AI expertise, resistance to change, and budgetary constraints are acknowledged.

This study aimed to investigate students’ awareness and perception toward the execution of Internet of Things (IoT) in library services of Indian Institute Technologies (IITs) of Northern India. This study consists of a quantitative research design in which a survey was conducted utilizing a stratified random sampling technique to survey 813 students from five IITs. A total of 780 correctly filled-out surveys were received, yielding a response rate of 95.94%. Statistical tools, including Microsoft Excel and the Statistical Package for the Social Sciences, were used to analyze the data. To assess the significance of the results at the 0.05% level, statistical analysis was carried out utilizing percentages and analysis of variance. This study will communicate the attitude, awareness, and perception of students regarding the implementation of IoT in libraries of IITs. It is conducted to understand the motive behind new technology acceptance in academic libraries. The findings reveal that most of the students got familiar with IoT from browsing on the Web/Internet, social networking sites, research projects, conferences, workshops, webinars and faculty development programs, professional discussions, and meetings, as part of the curriculum. Respondents were in favor of implementing IoT in library services. They believed that IoT will ensure better and more efficient utilization of library resources, followed by real-time information accessibility, recommend IoT-based library services, system content quality will be updated, and will increase the quality of the library; the efficiency of library services will increase with implementation of IoT. It will increase the productivity of library services, be useful in an emergency, and promote information literacy. The study’s findings would be beneficial to libraries and academic institutions interested in implementing IoT applications in their libraries.

Software-defined networking offers a flexible and programmatically efficient network design. Security in today’s ad hoc mobile wireless network is paramount and incredibly challenging. Software-defined network is used to automatically and dynamically manage and control large network devices, network services, traffic paths, network topology, and packet management (quality of service). Recently different attackers are attacking our data when forwarding from one device to another. Therefore, software-defined networking and a Hybrid Rivest, Shamir, and Adelman (RSA)–Advanced Encryption Standard (AES) cryptography algorithm are needed to establish the concept of software-defined networking in mobile ad hoc networks to improve security and routing efficiency. The proposed Hybrid Cryptography Algorithm (HCA)-Based SDN mainly creates strong detection, prevention, and authentication mechanisms for MANET. The proposed secure data channel throughput increased by 0.4%, and the suggested system latency was 3.6% lower than the Normal MANET. It is already proved that the Hybrid cryptography algorithm also generates a key for security faster than RSA (Rivest, Shamir, and Adelman). The performance of the RSA–AES (hybrid) approach for encrypting and decrypting broad data significantly beats the RSA-Blowfish algorithm. In decrypting files, the hybrid approach (RSA–AES) outperforms the RSA-Blowfish method 11.2 times more efficiently when the file size is 32 kB; however, efficiency is increased by 77.1 times when the file size exceeds 4,096 kB. The experimental result shows that as the file size increases the hybrid RSA–AES solution outperforms RSA when the file is only 145 bytes; however, when the file is 6,460 bytes in size, the efficiency is multiplied by 61.3. As file size increases, RSA is less efficient than the hybrid encryption method. This is more preferred to be implemented for different parts of wireless networks like MANET.

Malware has become one of the biggest risks to security due to its rapid expansion. Therefore, it must be quickly detected and removed. While convolutional neural network (CNN) models have expanded to include ensemble and transfer learning approach from previous individual CNN architectures, relatively few studies have compared how well these approaches perform when it comes to malware family detection. A small number of malware varieties have been the focus of several research efforts’ studies. In this study, both of these issues were resolved. We present our own ensemble model for the classification of malware diseases into 34 types. We merge the Microsoft malware dataset with the Malimg dataset to increase the number of malware families identified by the model. To reduce training time and resource consumption, the suggested model utilized the most significant malware features, which are chosen based on the Least Absolute Shrinkage and Selection Operator method, for the purpose of classifying the malware classes. The experimental findings demonstrate that the ensemble model’s accuracy is 99.78%. Based on the experimental results, we conclude that the model will help with real-world malware classification tasks.

The open-access (OA) discourse is shrouded in controversy and is actively discussed on forums like social media, where scholars engage in professional conversations. The mining of the conversations of the Twitter (X) scholarly community with an open-source intelligence tool for a 7-day time frame yielded a cleaned dataset of 67 posts, which were analyzed and coded into seven major themes. Most Twitter users who participated in the #openaccess discussion were scholars (64%), but (institutions) libraries and publishers, universities, and repositories were also part of the participants in the discourse. The major themes that were identified in the corpus of posts retrieved were article processing charges (25%), repositories (16%), paywalls (15%), support initiatives for OA (15%), definitions of OA (12%), benefits of OA (10%), and OA policies (10%). These themes were found to be of high interest to scholars and in line with contemporary research, based on the volume and tone of the peer-reviewed literature that supports the study. While Twitter (X) can be accepted as an authentic platform for exploring scholarly discourse, such studies can also lean on other forums for scholarly communication such as LinkedIn, Facebook, focus groups, peer-reviewed literature, and institutional policies for a well-rounded exploration of the evolving perspectives and practices of OA publishing.

This study explores Indian library and information science (LIS) professionals’ perspectives on the integration of artificial intelligence (AI) in academic libraries in India. It aims to evaluate their comprehension of AI, determine their perspectives, investigate AI utilization, assess advantages, identify influencing factors, and examine attitudes towards AI adoption. A quantitative research approach was employed, utilizing a structured questionnaire designed based on study objectives and reviewed by subject matter experts. Purposive sampling targeted individuals with relevant LIS knowledge. Data were collected through Google Forms from 259 respondents and analysed using descriptive and inferential statistics. Respondents generally exhibited positive perceptions towards AI integration in libraries. High mean scores were observed for statements such as “AI can bridge librarian performance gaps” and “AI does not make library staff lazy.” Librarians expressed willingness to learn about AI, interest in its ethical implications, and confidence in its potential to improve library services. The study highlights a cautious optimism towards AI adoption in Indian academic libraries, with recognition of its potential benefits tempered by concerns about employment and resource allocation. Librarians demonstrate proactive attitudes towards engaging with AI technology and understanding its implications for library services, indicating a readiness to embrace AI within the profession.

Power outages have become pervasive in many Global South countries causing serious disruption to economies, psycho-social well-being, and industries including libraries. Occasionally, these power outages and their implications are felt in Global North countries too, mainly as a result of natural disasters whose occurrence has become too common due to global warming. This study sought to assess the impact of power outages on library services. The method employed was desk research which relied on a literature review and the lived experiences of the researcher who is based in South Africa, one of the countries that experienced almost daily periodic power outages as a result of the imposition of load shedding. The results show that power outages disrupt daily services of libraries resulting in difficulties in accessing electronic resources and services causing library hours to be adjusted and even closures. Power outages often lead to great frustration and anger from clients and librarians alike. Based on the available literature, some remedies are suggested to cushion the blow to clients and libraries. However, these remedies can only be temporary solutions. Ultimately, it is recommended that libraries should tackle the issue of load shedding collectively by either negotiating favourable deals with alternative energy providers and/or in negotiations with governments to, as far as possible, exempt and prioritise libraries in cases of power outages. This will aid in stemming the negative effects on education, access to information, and other efforts to actualise sustainable development.

With the growth of open educational resources (OERs), academic libraries have an opportunity to play a vital role in facilitating access, use, and development of OERs. This study explored the management practices of OER initiatives in Nigerian public university libraries. A sequential mixed method was adopted for this study using the sequential explanatory strategy. Quantitative method was used to gather data to inform the study population for the qualitative part of the study. The quantitative data was analysed descriptively, while the qualitative data was analysed thematically; both data were integrated into the discussion of findings to provide robustness and complementarity. The study revealed variability across institutions in the completeness of OER projects. It also found key drivers and challenges of integrating OERs in these institutions. While this study provided recommendations based on the findings, it also made suggestions for librarians seeking to expand their role in OER adoption through strategic leadership, faculty partnerships, and advocacy. The findings of this research contribute to the on-going discourse on OER adoption, offering insights into the challenges and opportunities facing academic libraries in sustaining OER initiatives.

This study presents a comprehensive bibliometric analysis of the scientific literature about artificial intelligence (AI), automation, and job displacement from 1984 to 2024. Utilizing the Scopus database, 225 relevant documents were retrieved and analysed using R Studio and VOSviewer. The analysis reveals significant trends in publication growth, citation metrics, and collaborative networks among researchers and institutions. Notable findings indicate a marked increase in research output during key technological advancements, highlighting the evolving discourse surrounding the implications of AI and automation on the workforce. This study identifies prevailing themes within the literature through keyword analysis and explores the interconnectedness of research contributions across various domains. This bibliometric review aims to provide a foundational understanding of the current landscape and future directions in studying AI, automation, and job displacement.

The primary objective of this article is to provide a comprehensive analysis of the open network for digital commerce (ONDC), an innovative initiative by the Indian government. The study aims to explore the potential impact of ONDC on India’s digital commerce sector, focusing on how it seeks to democratize digital commerce and create an environment characterized by fair competition, innovation, and inclusivity. Our methodology involves an extensive review and thematic analysis of relevant literature. This approach includes a detailed examination of ONDC’s core objectives, its technological underpinnings, and the role of the government in facilitating its growth and adoption. The study is designed to provide a holistic view of ONDC, considering various aspects such as technology, policy, and market dynamics. The analysis suggests that ONDC could revolutionize India’s digital commerce ecosystem. Key findings indicate that ONDC can enhance interoperability, empower small businesses and local retailers, and diversify consumer choices. The initiative’s reliance on existing digital frameworks like the Unified Payments Interface and the Data Empowerment and Protection Architecture is crucial in streamlining transactions and bolstering data security. However, the realization of ONDC’s full potential is contingent upon its effective implementation and widespread acceptance among stakeholders. This study contributes to the existing body of knowledge by comprehensively analysing ONDC, a relatively new and underexplored area in digital commerce research. It offers original insights into the initiative’s potential to transform India’s digital commerce landscape. The article also identifies gaps in current research, such as the limited scope of existing studies, the absence of primary data, and the influence of external variables. It suggests avenues for future research, including longitudinal studies, international comparisons, and primary data collection, to understand ONDC better and its long-term impact on India’s digital commerce sector.

This commentary abridges three closely related aspects of scholarly publishing, copyright transfer to publishers in the subscription-based model, posting of author-accepted versions to preprint servers, and publishing embargoes, to appreciate how each might impact the dissemination of information. We found no direct evidence showing that either copyright transfer or the posting of early (i.e., author-submitted or journal-accepted) versions of works to preprint servers stifle academics’ ability to share their papers openly. However, some key structural issues and incompatibilities in policies may dampen the wider adoption of preprints despite their widely promoted advantages for scientists. We found a 6- to 36-month embargo period in place by 10 of the world’s top largest publishers, depending on the version of the record. These embargoes may constrain the dissemination of knowledge.

A recent disruptive innovation to scientific publishing is OpenAI’s ChatGPT, a large language model. The International Committee of Medical Journal Editors and COPE, and COPE member journals or publishers, set limitations to ChatGPT’s involvement in academic writing, requesting authors to declare its use. Those guidelines are practically useless because they ignore two fundamentals: first, academics who cheat to achieve success will not declare the use of ChatGPT; second, they fail to explicitly assign the responsibility of detection to editors, journals, and publishers. Using two primers, i.e., residual text that may reflect traces of ChatGPT’s output but that authors may have forgotten to remove from their articles, this commentary draws readers’ attention to 46 open-access examples sourced from PubPeer. Even though editors should be obliged to investigate such cases, a primer-based detection of ChatGPT’s textual crumb trails is only a temporary measure and not a sustainable solution because it relies on the detection of carelessness.