Current Research Papers Research Articles

Leadership development through self-upskilling: role of generative artificial intelligence

PurposeThis viewpoint paper investigates the changing role of leadership in a dynamic, technologically driven society, and the vital requirement for leaders to engage in continuous self-upskilling to remain effective. It emphasizes the importance of generative artificial intelligence (GAI) in transforming personalized learning experiences for leaders and allowing them to adapt to an ever-changing world.Design/methodology/approachA review of current research papers, articles, and case studies is conducted to evaluate the integration of generative AI in leadership self-upskilling. It examines the possibilities and possible benefits of generative AI, and the issues it offers regarding data privacy, algorithmic bias, and learning requirements.FindingsThe findings highlight the transformational potential of GAI in self-upskilling for leaders. It demonstrates how GAI can build personalized learning materials, provide real-time feedback, and adapt content to individual learning styles. It identifies notable executives who have effectively embraced GAI for their self-upskilling journeys, resulting in increased productivity and competitiveness.Practical implicationsThe paper investigates the application of GAI for self-improvement, addressing challenges such as data privacy and algorithmic bias while suggesting responsible AI use tactics.Originality/valueThis study investigates the relationship between leadership and AI, emphasizing the importance of leaders in self-improvement as well as the possibility of AI-powered self-upskilling to democratize leadership development while also promoting ethical use.

Utility of Large Language Models for Health Care Professionals and Patients in Navigating Hematopoietic Stem Cell Transplantation: Comparison of the Performance of ChatGPT-3.5, ChatGPT-4, and Bard.

Artificial intelligence is increasingly being applied to many workflows. Large language models (LLMs) are publicly accessible platforms trained to understand, interact with, and produce human-readable text; their ability to deliver relevant and reliable information is also of particular interest for the health care providers and the patients. Hematopoietic stem cell transplantation (HSCT) is a complex medical field requiring extensive knowledge, background, and training to practice successfully and can be challenging for the nonspecialist audience to comprehend. We aimed to test the applicability of 3 prominent LLMs, namely ChatGPT-3.5 (OpenAI), ChatGPT-4 (OpenAI), and Bard (Google AI), in guiding nonspecialist health care professionals and advising patients seeking information regarding HSCT. We submitted 72 open-ended HSCT-related questions of variable difficulty to the LLMs and rated their responses based on consistency-defined as replicability of the response-response veracity, language comprehensibility, specificity to the topic, and the presence of hallucinations. We then rechallenged the 2 best performing chatbots by resubmitting the most difficult questions and prompting to respond as if communicating with either a health care professional or a patient and to provide verifiable sources of information. Responses were then rerated with the additional criterion of language appropriateness, defined as language adaptation for the intended audience. ChatGPT-4 outperformed both ChatGPT-3.5 and Bard in terms of response consistency (66/72, 92%; 54/72, 75%; and 63/69, 91%, respectively; P=.007), response veracity (58/66, 88%; 40/54, 74%; and 16/63, 25%, respectively; P<.001), and specificity to the topic (60/66, 91%; 43/54, 80%; and 27/63, 43%, respectively; P<.001). Both ChatGPT-4 and ChatGPT-3.5 outperformed Bard in terms of language comprehensibility (64/66, 97%; 53/54, 98%; and 52/63, 83%, respectively; P=.002). All displayed episodes of hallucinations. ChatGPT-3.5 and ChatGPT-4 were then rechallenged with a prompt to adapt their language to the audience and to provide source of information, and responses were rated. ChatGPT-3.5 showed better ability to adapt its language to nonmedical audience than ChatGPT-4 (17/21, 81% and 10/22, 46%, respectively; P=.03); however, both failed to consistently provide correct and up-to-date information resources, reporting either out-of-date materials, incorrect URLs, or unfocused references, making their output not verifiable by the reader. In conclusion, despite LLMs' potential capability in confronting challenging medical topics such as HSCT, the presence of mistakes and lack of clear references make them not yet appropriate for routine, unsupervised clinical use, or patient counseling. Implementation of LLMs' ability to access and to reference current and updated websites and research papers, as well as development of LLMs trained in specialized domain knowledge data sets, may offer potential solutions for their future clinical application.

Strategic Key Elements in Big Data Analytics as Driving Forces of IoT Manufacturing Value Creation: A Challenge for Research Framework

Big Data (BD)-driven business intelligence (BI) is considered to be a new development stage within industrial engineering management to achieve higher business value creation. The article provides extensive research of BD-driven approaches to identify strategic knowledge and value-creating components within Internet of Things (IoT) manufacturing. Due to previous research studies focused mostly on partial solutions and lack a holistic view, this article topic is still far from being sufficiently explored and resolved. The article presents the results of an extensive research study of contemporary professional literature with a specific aim to provide a more holistic and systematical view on the current state and future trends in this issue. To solve this high complex research problem, both quantitative and qualitative research methodology approaches are used. The article is primarily based on a systematic literature review covering 187 essential and 36 additional current research papers within the Web of Science and Scopus database from 2012 to the present. Research findings identify the seven key strategic elements determining that Big Data analytics (BDA) can become a real and tremendous business value creation driver within IoT intelligent manufacturing. These research results provide important conclusions and implications for challenging future investigations into BDA and BI systems in the context of advancing the Industry 4.0 revolution. In conclusion, we propose a final suggestion in the form of a strategic future research chain from IoT through BDA to value creation based on BD intelligence within IoT manufacturing, whereas seven strategic elements might play a crucial.

Enhancement of Cloud Computing Environment Using Machine Learning Algorithms MLCE

Cloud computing is an evolving and high-demand research field at the forefront of technological advancements. It aims to provide software resources and operates based on service-oriented delivery. Within the infrastructure as a service (IaaS) framework, the cloud offers end customers access to crucial infrastructure resources, including CPU, bandwidth, and memory. When a cloud system fails to deliver as expected, it is referred to as an event, signifying a deviation from the anticipated service. To meet their service-level agreement (SLA) obligations, cloud service providers (CSPs) must ensure continuous access to fault-tolerant, on-demand resources for their clients, particularly during outages. Consequently, finding the most efficient ways to accomplish tasks while considering the rapid depletion of resources has become an urgent concern. Researchers are actively working to develop optimal strategies tailored to the cloud environment. Machine learning plays a critical role in these endeavors, serving as a key component in various cloud computing platforms. This study presents a comprehensive literature review of current research papers that employ machine learning algorithms to propose strategies for optimizing cloud computing environments. Additionally, the survey provides authors with invaluable resources by extensively exploring a diverse range of machine learning techniques and their applications in the field of cloud computing. By examining these areas, researchers aim to enhance their understanding of efficient resource allocation and scheduling, addressing the challenges posed by resource scarcity while meeting SLA obligations. Index Terms— Cloud computing, Resource allocation Prediction, Energy-efficient resource management, Task Scheduling, Machine Learning.

SOFT POWER PROJECTION OF ASPIRING MIDDLE EASTERN POWERS TOWARDS YEMEN: THE CASE OF THE KINGDOM OF SAUDI ARABIA AND IRAN

The multiple hard power engagements of the aspiring Middle East powers (the Kingdom of Saudi Arabia and Iran) in Yemen are self-evident. However, the disposition of foreign interference in Yemen is multifaced. Current research papers have primarily focused on using hard power military or economic tools, but soft power tools were left behind. Therefore, this article explores soft power’s nature influencing the countries above assert towards the Yemeni population. It focused on three ostensibly distinct areas of soft power – education, religion, and media – within each particular analysis since those three areas are key elements of the Saudi and Iranian soft-power toolkit. Multiple religious, educational, and media tools towards Yemen were detected in each case.

Cyclodextrin based nanoparticles for smart drug delivery in colorectal cancer.

The advancement of colorectal cancer (CRC) prevention, detection, and treatment is essential to ensure that survivors live longer and higher-quality lives. The field of cancer detection and therapy has undergone a revolution with the development of nanotechnology for targeted drug delivery. The significant problems with the delivery of cancer drugs are their solubility, stability, and nonspecific distribution. There is a challenge that the acidic and enzymatic environment in the digestive tract will modify or destroy the medication or the active pharmaceutical ingredient. To overcome the problems, nanoparticles have been widely employed during the past several years to increase the specificity, selectivity, and controlled release of drug delivery systems. The site-specific and targeted delivery leads to reduce toxicity and side effects. With respect to the capability and utilization of cyclodextrin-based nanoparticles in different aspects of the tumour microenvironment and gut microbiota, a survey of current research papers was conducted via looking through databases including GoogleScholar, PubMed, Web of Science, and Scopus. This review aims to summarize cutting-edge nanoparticulate-based technologies and therapies for CRC.

The history of the oil industry in the Fergana Valley during the period of the Kokand Khanate and the colonial era of the Russian Empire

The article examines the history of oil production by primitive methods and by drilling oil wells in the Fergana Valley during the period of the Kokand Khanate and the era of colonialism of the Russian Empire, the development of the oil refining industry in conjunction with all sectors of the national economy. The article is devoted to the history of the development of the oil industry in the Ferghana Valley, the processes of oil production by drilling on the basis of archival documents from the funds of the National State Archives of Uzbekistan, scientific research by foreign and domestic researchers. The formation of the oil industry in the Fergana Valley was carried out in the middle of the 19th century under the Kokand Khanate. By the beginning of the 20th century, oil drilling began. As a result of the introduction of foreign capital into the oil industry, the introduction of new methods, technologies and means of oil production, the use of advanced experience in this industry, this industry has succeeded, reaching a high industrial scale. But during the First World War, the rate of oil production in the Ferghana Valley declined, as in the entire territory of the empire. This was due to the closure of foreign trade routes due to the war, the reduction in the amount of capital invested in this sector, the involvement of skilled oil workers in the war, and the result of the nationalization process after the coup d'état. In the study of the process of formation and formation of the oil industry in the region, comparative, historical and factor analysis was used for a detailed approach to the topic. The conclusions and proposals in the article are developed using current research papers, unique archival materials, and also include the relevant chronology, statistics, periodization and conclusions on the topic.

Effects of Digital Presence on Business Development: A Study from the Perspectives of Pandemic Situation in Bangladesh

Covid 19’s effect is very severe on this community where the lives of many people have been dangerously affected resulting in superfluous infections as well as death tolls. In consequence, business activities of the various industries have been adversely affected which is exhibited by the statistics of the lower amount of revenue, profitability, export, investment, etc. But the timely decision of the global policy maker to move towards the digital platform from conventional physical establishment seems to be a very significant issue. Because of the digital presence on one hand enables the business entities to sustain well. On the other hand, develop their business into electronic platform-centric leadership. Bangladesh has also not been an exception to this because the industry leaders of the country prioritized digital transformation with immediate effect. The justification for such a decision is exhibited by the regular flow of business and positive growth of her economy even in this pandemic crisis. With this end of view, the present study is an endeavor to investigate the effect of digital presence on the business development of Bangladesh. Both primary and secondary data were collected for this study. Here, secondary information has been gathered from current research papers and articles related to the study's topic that have been published in refereed journals. Inferential statistical methods are operated in this work to test the main data obtained using a structured, self-administered questionnaire-based lengthy survey that includes open-ended, non-forced, balanced itemized questions utilizing a 5 Likert scale (strongly disagree to strongly agree). This current study has found the feasibility of the effects of digital presence because of its diversified uses in the pandemic situation which include government support to use digital platforms as the best alternative to physical work environment both in the public and private sectors during the pandemic and after the pandemic, Organizations should increase digital presence to reduce fixes cost related with construction and maintenance, the government must ensure IT training facilities to employees so that they can smoothly execute their official activities through digital platforms for facilitating "Digital Bangladesh Vision 2021" and many more. Thus, digital presence can be predicted as effective for business development by which a country can achieve more growth and prosperity.

Advancements in 5G Technology: Enhancing Connectivity and Performance in Communication Engineering

The present research delves into how 5G technology developments can improve communication engineering performance and connectivity. The primary goals are to assess 5G's technical viability, performance potential, and real-world obstacles while offering recommendations for best practices in implementation and use. The study synthesizes current literature, research papers, and industry reports using a secondary data-based review technique to examine the technological underpinnings, performance improvements, real-world applications, and future directions of 5G. According to key findings, 5G dramatically improves data rates, lowers latency, and allows for ample device connectivity, opening up new possibilities for revolutionary applications in industries like industrial automation, smart cities, and healthcare. Strategic policy interventions are necessary to address cybersecurity risks, coverage restrictions, interoperability issues, and expensive infrastructure costs. To overcome these issues, provide fair access, and optimize the socioeconomic benefits of 5G, policymakers are encouraged to prioritize spectrum allocation, simplify regulatory frameworks, and provide incentives for investments. Future studies and developments in Edge Computing and AI-driven network optimization are emphasized as essential to improving 5G networks even more. The potential of 5G to alter communication engineering and accelerate inclusive digital transformation is shown by this thorough examination.

Study on performance of Indian bank

A financial institution is a business that engages in financial transactions such as investing, lending, and depositing money. Almost everyone has regular interactions with financial institutions. All must be done through financial institutions, from depositing money to taking out loans and exchanging currencies. Here's a rundown of some of the most important forms of financial institutions and their positions in financial systems. The banking system is an essential component of any economy's growth, and this sector is critical to the country's modern economic development. Indian bank is a nationalized bank among the public sector banks, and its success has an impact on the country's economy. Economists have expressed a wide range of views on the efficacy of banking systems in fostering economic development by facilitating large amounts of financial assistance. The Indian Bank, a premier bank owned by the Indian government, was established on March 5, 1907 as Indian Bank Limited and began operations on August 15, 1907. Current research papers provide opportunities to know about profitability and performance of Indian Bank from 2008-09 to 2017-2018.

Critical Decision-Making Issues in Disaster Relief Supply Management: A Review.

This paper comprehensively reviews the literature related to disaster relief supply management in recent years by taking the perspectives of three critical decision-making issues, i.e., coordination issues, facility location decisions, and inventory decisions. For each decision-making issue discussed, we clarify the barriers of current research papers and identify the major challenges and critical factors that should be considered. In the following, we present the perspectives on the road of coordination between multiple relief actors, characterize the location decisions of relief facilities with a variety of optimization objectives, and emphasize the importance of relief supply varieties and critical factors in the decisions of disaster relief inventories. Future research directions are recommended for further discussions.

Textbooks and Learning Materials in Physical Education in the International Context: Literature Review

This paper presents a review of the research carried out internationally in recent years regarding textbooks, teaching materials, and the field of physical education. The objectives to which this article aims are as follows: To offer a compilation of current research papers published in the Scopus, Web of Science, and Dialnet databases and to provide a classification of the research lines undertaken on the subject. The information used is based on a review of studies listed in Scopus, Web of Science, and Dialnet. For this, a systematic review was carried out with the terms: “curricular resources”, “didactic materials”, “digital resources”, “educational resource”, “physical education”, and “textbooks”, allowing the selection of original articles, which included information on this line of research. For the literature review, only articles that presented scientific evidence were used, discarding merely descriptive articles or didactic experiences that were not investigated with the scientific protocol. A total of 589 articles were found, although after applying the review’s inclusion criteria, they were reduced to 54 articles. The investigations do not follow a common protocol and the researchers address multiple objectives in them, highlighting the studies on the implicit ideological discourse in the images of physical education textbooks. The results reveal a diversity of research, in particular, studies involving ideological discourse. Insofar as methodology, content analysis of textbooks and materials was the most common approach.

Analytical review on deep learning and IoT for smart healthcare monitoring system

PurposeSelecting and using the same health monitoring devices for a particular problem is a tedious task. This paper aims to provide a comprehensive review of 40 research papers giving the Smart health monitoring system using Internet of things (IoT) and Deep learning.Design/methodology/approachHealth Monitoring Systems play a significant role in the healthcare sector. The development and testing of health monitoring devices using IoT and deep learning dominate the healthcare sector.FindingsIn addition, the detailed conversation and investigation are finished by techniques and development framework. Authors have identified the research gap and presented future research directions in IoT, edge computing and deep learning.Originality/valueThe gathered research articles are examined, and the gaps and issues that the current research papers confront are discussed. In addition, based on various research gaps, this assessment proposes the primary future scope for deep learning and IoT health monitoring model.

Analysing Show Cause Notices based on Applied Genre Analysis: a Multi- perspective Model

The current research papers targets to investigate the genre of Show Cause notices (SCNs) based on theoretical approaches of genre analysis (Bhatia, 1999) and applied genre analysis (Bhatia, 2002). The reason to carry the said study is to identify the correlation among the textual, generic and social perspectives of Show cause notices. The corpus of ninety show cause notices was gathered and analyzed by applying applied genre analysis: a multi-perspective model of Bhatia (2002). The theoretical concerns (1999) directed towards the language use in four categories; purpose, products, process and players which are affirmed through the analytical analysis. The findings through qualitative and quantitative paradigms of research represented that purpose of the SCNs and lexico-grammatical features are the mainstreams to suggest the structure patterning in the text to shape such genre as highly formal, objective and professional. The social perspective reflected the participants in no personal terms, clear separate power zones and the addresser's cognitive understanding of communicative event and purpose.

AI-Based Personalized E-Learning Systems: Issues, Challenges, and Solutions

A personalized e-learning system is effective in imparting enhanced learning to its users. As compared to a conventional e-learning system, which provides similar contents to each learner, a personalized learning system provides specific learning contents and assessments to the learners. Personalization is based on Artificial Intelligence (AI) based techniques in which appropriate contents for each learner are determined using the level of comprehension of the learner and the preferred modes of learning. This paper presents requirements and challenges for a personalized e-learning system. The paper is focused in elaborating four research questions, which are related to identifying key factors of personalized education, elaborating on state of the art research in the domain, utilizing benefits of AI in personalized education, and determining future research directions. The paper utilizes an extensive survey of current research papers in answering these questions. It provides a comprehensive review of existing solutions in offering personalized e-learning solutions. It also elaborates on different learning models and learning theories, which are significant in providing personalized education. It proposes an efficient framework, which can offer personalized e-learning to each learner and identifies significant directions for future research. The paper is beneficial for academicians and researchers in understanding the requirements of such a system, comprehending its methodologies, and identifying challenges which are needed to be addressed.

Framework for assessing innovation capacity and business efficiency in Romanian SMEs

Abstract The purpose of this paper is to provide a new framework for assessing the innovation capacity and efficiency in Romanian small enterprises and start-ups. In this sense, a systematic literature review has been employed in order to obtain a clear understanding of the existing knowledge and to critically evaluate the existing solutions. In addition, considering the European Union objectives regarding innovation and sustainable development, this paper investigates the present situation of Romania by interpreting the official European Commission reports and current research papers. Considering the importance of regional innovation advancement and that of creating economic growth through competitiveness, this paper scrutinizes several concepts from the scientific literature, including regional innovation governance, entrepreneurship and innovation efficiency with the final purpose of developing a framework applicable for Romania. Taking into consideration the relatively low scores of Romanian regions regarding innovativeness and technological advancement, this paper attempts to provide a clearer understanding of the applicable factors that can be used for measuring innovation performance. The proposed framework focuses on the importance of entrepreneurship and the development of new business models in order to efficiently assess the innovative endeavors of enterprises. All things considered, this paper provides both theoretical and managerial contributions and possibility for further investigations addressed at specific Romanian regions and business sectors.

Exploring Reasons on Lexical Borrowing from English Language (L2) to Sindhi Language (L1)

The term lexical borrowing is often used to express the system through which one language borrows words from another language to renew its linguistic system. The current research papers focuses to explore the reasons of borrowing words from English language (L1) into Sindhi language (L1). The current study employs qualitative research methodology to explore the reasons of borrowing words from English language. Research tool used to collect data was semi structured interviews and convenient sampling was taken as a source. Participants were (n=5) from a public sector university of Sindh. Data was examined and analyzed through thematic analysis. The major reasons behind lexical borrowing discovered were; code switching and code mixing result in borrowing, importance and exposure of English and lack of vocabulary in Sindhi (L1). Keywords: Lexical borrowing, reasons, Sindhi language, English language. DOI: 10.7176/JLLL/83-03 Publication date: November 30 th 2021

The Learning Styles Neuromyth Is Still Thriving in Medical Education.

Learning Styles theory promises improved academic performance based on the identification of a personal, sensory preference for informational processing. This promise is not supported by evidence, and is in contrast to our current understanding of the neuroscience of learning. Despite this lack of evidence, prior research shows that that belief in the Learning Styles “neuromyth” remains high amongst educators of all levels, around the world. This perspective article is a follow up on prior research aimed at understanding why belief in the neuromyth of Learning Styles remains so high. We evaluated current research papers from the field of health professions education, to characterize the perspective that an educator would be given, should they search for evidence on Learning Styles. As in earlier research on Higher Education, we found that the use of Learning Style frameworks persist in education research for the health professions; 91% of 112 recent research papers published on Learning Styles are based upon the premise that Learning Styles are a useful approach to education. This is in sharp contrast to the fundamental principle of evidence-based practice within these professions. Thus any educator who sought out the research evidence on Learning Styles would be given a consistent but inaccurate endorsement of the value of a teaching technique that is not evidence based, possibly then propagating the belief in Learning Styles. Here we offer perspectives from both research and student about this apparent mismatch between educational practice and clinical practice, along with recommendations and considerations for the future.

UWB-MAC: MAC protocol for UWB localization using ultra-low power anchor nodes

Indoor localization systems allow for innovative Industry 4.0 applications such as tracking of assets, people, or robots. Due to its cm-level accuracy, the Ultra Wide Band (UWB) technology seems to be a perfect fit as an enabler for these advanced use cases. Most current UWB research papers and commercial offerings assume that battery-powered mobile tags communicate with non-energy constrained infrastructure devices. However, in many deployments it is not possible to offer the required power cabling at the correct locations to provide energy to all infrastructure nodes. To this end, this paper proposes a novel power-aware Medium Access Control (MAC) protocol that uses a probed, secondary wake-up radio to maximize the battery lifetime on the anchor nodes. In order to show that battery powered infrastructure nodes are feasible, our solution accurately analyzes the long-term energy consumption of the infrastructure devices. Depending on the update rate and using a high capacity battery (10.4 Ah), it is possible to achieve a battery lifetime between 1 to 16 years, which is comparatively up to four times better compared to the current state-of-the-art TDMA-based solutions.

Sustainable Construction Investment, Real Estate Development, and COVID-19: A Review of Literature in the Field

Aspects of sustainable construction investment and real estate development (CIRED) and their interrelations during the period pre-, intra-, and post-COVID-19, are presented in the research. Applications of the topic model, environmental psychology theory, building life cycle method, and certain elements of bibliometrics, webometrics, article level metrics, altmetrics, and scientometrics make it possible to perform a quantitative analysis on CIRED. The CIRED topic model was developed in seven steps. This paper aims to present a literature review on CIRED throughout the pandemic and to look at the responses from the real estate and construction sector. This sector is a field that appears to be rapidly expanding, judging from the volume of current research papers. This review focuses on last year’s leading peer-reviewed journals. A combination of various keywords was applied for the review and the criteria for paper selections included construction investment, real estate development, civil engineering, COVID-19, and sustainability, as well as residential, industrial, commercial, land, and special purpose real estate, along with their risks, strategies, and trends. The articles reviewed for this paper, which analyzes three hypotheses, look at pre-, intra-, and post-pandemic CIRED. The three hypotheses were validated by analyzing scientific publications from around the world. Two innovative elements make this study stand out among the most advanced research on pre-, intra-, and post-pandemic CIRED. The first of the two innovations is the integrated analysis of the COVID-19 pandemic, COVID-19-related national policies, and business investment strategies relevant to CIRED and the interests of investors as well as on the impact a CIRED policy and investors make on the spread of COVID-19. In addition, this research demonstrates a marked increase in the effectiveness of a CIRED analysis, when the life cycle of a CIRED, the involved stakeholders with their own individual interests, the COVID-19 situation, and the external micro-, meso-, and macro-environments are covered comprehensively as a single entity.