KANGA Koffi1, KAMAGATE Béman Hamidja2, BROU Aguie Pacome Bertrand3, OUMTANAGA Souleymane4, 2Doctor in Computer Science: Software Engineering and Database: INPHB Doctoral School Teacher – Researcher, at ESATIC (African Higher School of ICT: Republic of Côte d'Ivoire) Laboratory of Information and Communication Sciences and Technologies, African Higher School of ICT, LASTIC-ESATIC, Abidjan, Ivory Coast, 18bp 1501 Abidjan 18. https://orcid.org/0000-0002-5246-4304, 2Doctor in Computer Science: Networks and Security: INPHB Doctoral School Teacher – researcher, at ESATIC (African Higher School of ICT: Republic of Côte d’Ivoire) Laboratory of Information, Communication Sciences and Technologies, African Higher School of ICT, LASTIC-ESATIC, Abidjan, Ivory Coast, 18bp 1501 Abidjan 18, 3Doctor of Computer Science at the Laboratory of Information, Communication Sciences and Technologies, African Higher School of ICT, LASTIC-ESATIC, Abidjan, Ivory Coast, 18bp 1501 Abidjan 18. orcid.org/0000-0002- 2584-3325, 4Lecturer in computer science at the Houphouët Boigny National Polytechnic Institute in Yamoussoukro Computer science and telecommunications research laboratory
In this work, the main objective is to provide a contribution of resources adaptation to consumption demand in IOT environments. To do this, we have proposed a data model including the entities " resource ", " load ", " event ", " policy " and " device " as well as the different relationships between IOT devices and others. 0 This data model, an adaptation process is proposed as well as a mathematical model based on the optimization of resource consumption on requests while, taking into account certain constraints including the Maximum Capacity of resources, the Satisfaction of user or IOT device requests and the Energy Constraints have been proposed. The simulation results regarding the optimization of resource consumption show that our model could be beneficial for smart city management, industry 4.0 and e-health.
Resource adaptation – data model – IOT resource.
KUSHTRIM UKADR. AGIM KRASNIQI, Training and Development ManagerMinistry of Education, Science, Technology, and "INTEREX" Prishtina – Kosova
This study explores the integration of knowledge management and digital technology as a strategic approach to enhancing organizational performance. In an era of rapid digital transformation, organizations are increasingly leveraging advanced technologies such as artificial intelligence, cloud computing, and data analytics to optimize knowledge management processes. This paper examines the theoretical underpinnings of knowledge management, the practical challenges of adapting these theories in modern organizational contexts, and the role of digital tools in bridging these gaps. Using a mixed-methods approach, the research combines quantitative surveys and qualitative interviews with professionals in the field, supported by case studies and a comprehensive literature review. The findings reveal that the integration of digital technologies enhances innovation, operational efficiency, and decision-making processes, contributing significantly to organizational competitiveness. However, challenges such as resistance to change, technological complexity, and skill gaps among staff remain significant barriers. This paper concludes with actionable recommendations for organizations to effectively align knowledge management practices with digital tools to foster sustainable growth and improve performance. By addressing the identified challenges and leveraging digital advancements, organizations can unlock the full potential of knowledge management to achieve long-term success.
Knowledge management, digital technology, organizational performance, innovation, operational efficiency.
Drita Shaqiri Dr. Agim Krasniqi, Ministry of Education, Science, Technology, and Innovation, Republic of Kosovo
This paper explores the impact of information management on enhancing the quality of scientific research by analyzing contemporary techniques and tools that assist researchers in searching, selecting, and managing academic resources. With advancements in information technology and the exponential growth of scientific resources, researchers face the challenge of effectively organizing data to improve the accuracy and efficiency of their studies. The paper examines modern practices such as the use of artificial intelligence, recommendation algorithms, and academic search platforms like Google Scholar and Scopus, highlighting their benefits and limitations. Furthermore, key challenges in information management, including data overload and resource fragmentation, are addressed, with recommendations for optimizing these processes. This study contributes to the understanding of effective information management practices, aiming to assist researchers in better selecting and organizing literature for successful and sustainable research.
Information management, scientific research, research quality, information technology, search algorithms.
