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A Systematic Literature Review: Big Data Maturity Model in the Telecommunication Industry
No full textThis paper presents a systematic literature review focused on Big Data Maturity Model, with a specific emphasis on its application within the telecommunications sector. It addresses two primary research questions: the models currently available for assessing Big Data Maturity and the models predominantly used within the telecommunications industry. The review reveals that several models, such as Gartner\u27s Data Maturity Model (GDMM), IBM\u27s Big Data & Analytics Maturity Model, The Data Warehousing Institute (TDWI\u27s) Big Data Maturity Model, the Data Management Maturity (DMM) Model, and the Big Data Maturity Model (BDMM), are widely recognized. However, no single model has been predominantly adopted and suitable within the telecommunications sector. The paper thus identifies a need for a telecommunications-specific Big Data maturity model, and suggests further research to develop a model that addresses the unique needs and challenges of this industry
14th International Conference on Business, Technology and Innovation 2025
No full textWelcome to IC – UBT 2025
UBT Annual International Conference is the 14th international interdisciplinary peer reviewed conference which publishes works of the scientists as well as practitioners in the area where UBT is active in Education, Research and Development. The UBT aims to implement an integrated strategy to establish itself as an internationally competitive, research-intensive university, committed to the transfer of knowledge and the provision of a world-class education to the most talented students from all background. The main perspective of the conference is to connect the scientists and practitioners from different disciplines in the same place and make them be aware of the recent advancements in different research fields, and provide them with a unique forum to share their experiences. It is also the place to support the new academic staff for doing research and publish their work in international standard level.
This conference consists of sub conferences in different fields like: Architecture and Spatial Planning Art and Digital Media Civil Engineering, Infrastructure and Environment Computer Science and Communication Engineering Dentistry Education and Development Energy Efficiency Engineering Food Science, Nutrition and Agriculture Integrated Design Information Systems and Security Journalism, Media and Communication Law Language and Culture Management, Business and Economics Modern Music, Digital Production and Management Medicine and Nursing Mechatronics, System Engineering and Robotics Pharmaceutical and Natural Sciences Political Science Performing Arts Psychology Security Studies Sport, Health and Society
This conference is the major scientific event of the UBT. It is organizing annually and always in cooperation with the partner universities from the region and Europe. We have to thank all Authors, partners, sponsors and also the conference organizing team making this event a real international scientific event.
Edmond Hajrizi, President of UBT UBT – Higher Education Institutio
Lecture Notes in Architecture: The Impact of AI (Artificial Intelligence) on Education: Opportunities and Challenges in Modern Schools
No full textThis paper explores the growing role of Artificial Intelligence (AI) in educational environments and its potential impact on learning, teaching methodologies, and school administration. AI technologies, such as intelligent tutoring systems, personalized learning platforms, and automated grading, are becoming integral components of modern classrooms. This research investigates how AI can enhance student engagement, improve academic performance, and support teachers in managing diverse classrooms by providing tailored learning experiences. In this paper also examines the ethical concerns and challenges associated with AI in education, including data privacy, algorithmic bias, and the digital divide. Through a combination of literature research, case studies and survey this study seeks to provide a comprehensive analysis of AI\u27s current and future implications in schools
Architectural heritage, sustainability, innovation, spatial planning
No full textThis paper will address the process and procedures for the development of the drafting, financing and management of the Affordable and Social Housing Program in Kosovo. The implementation of this program will be a key initiative for improving living conditions and ensuring access to housing for low-, middle- and vulnerable categories of Kosovar society. It aims to create sustainable and affordable housing solutions for low-, middle- and social-income families, based on needs analysis, comparison with innovative financing models and effective management mechanisms. Cooperation between central and local public institutions, the private sector and international donors. Increasing the stock of affordable housing and social housing will have an impact on sustainable urban development and improve the quality of life of communities that will be stakeholders in this Program. The document includes an analysis of existing challenges, recommendations for improvement and strategies for the efficient implementation of the progra
Assessment of Water Losses Using ILI and ALI Performance Indicators: A Case Study from Urban and Rural DMAs in the Prishtina Regional Water Company
No full textWater loss management is a critical component of sustainable water utility operations, particularly in regions where both technical and commercial losses threaten service reliability and financial viability. This study investigates water losses through two key performance indicators: the Infrastructure Leakage Index (ILI), which measures real (physical) losses, and the Apparent Loss Index (ALI), which quantifies non-physical losses such as meter inaccuracies, data errors, and unauthorized consumption. The research was conducted within the Regional Water Company Prishtina in Kosovo, using a comparative analysis of two District Metered Areas (DMAs)—one urban zone located in Prishtina, and one rural zone in the municipality of Podujeva. Data collection involved field measurements, flow analysis, and consumption data over a representative period. The calculated ILI and ALI values highlight significant differences between the two zones, reflecting the impact of infrastructure age, population density, and operational practices on water loss performance
An Insight into Prefabricated Composite Wall Design That Dissipates Blast Energy Through Fracture of Confined Concrete Within Steel Enclosure
No full textBuildings for civilian use are not ordinarily expected to resist blast pressures due to explosions. However, blast resistance is required of certain civil engineering structures that are under the threat of terrorism. Ever increasing conflicts between states and state sponsored terrorism require a paradigm shift that can include design for blast resistance for civilian buildings where needed. Design for blast pressures require new approaches that take into consideration for structural behavior following the detonation. The structural element that is designed to resist an explosion should not transform into a projectile weapon itself due to uncontrolled high-speed fragmentation. Design for blast pressures includes sacrificial post elastic behavior that can absorb blast energy and design measures for easy replacement following an attack. This study presents design approaches against blast pressures and presents the results of blast pressure tests conducted on a conceptual design for blast pressures named as “Design for Multiple Intrinsic Resistance (DeMIR)”. The study concludes with proposals for future studies
Precast Concrete Panels in Fire
No full textPrecast concrete panels are widely used as compartmentation or cladding systems in buildings with fire safety requirements. Although the live loads acting on such panels under service conditions are generally negligible, in fire conditions failures often arise from the malfunction or collapse of their connection systems. When exposed to fire, panels undergo significant thermal deformation, including elongation and deflection, which may compromise structural integrity and lead to connection failure. This study investigates the deformative behaviour of monolithic solid precast panels under fire exposure through non-linear heat transfer and thermomechanical analyses. Based on the results, a practical nomogram is proposed to support design decisions aimed at preventing unintended contact either between the panel and the supporting frame or adjacent panels, thus reducing the risk of collapse. The proposed design criteria provide designers with a simplified yet reliable approach for evaluating the performance of the panel under fire conditions, contributing to improve fire safety and structural resilience
High-Performance SHA-256-Based Request Signing: A Comparative Study of Standard and Custom Implementations
No full textEnsuring data integrity in modern software integrations with third-party providers is critical for secure communication and reliable transaction processing. This study focuses on implementing SHA-256 hashing for verifying the authenticity and integrity of HTTP requests. Two approaches are analyzed: the built-in .NET SHA-256 implementation and a fully custom SHA-256 algorithm implemented from first principles. Both methods are evaluated for correctness, security, and performance. Experimental results demonstrate that the custom implementation achieves comparable security guarantees while offering improved execution speed and minimal memory usage. The findings highlight the relevance of SHA-256 in protecting data against tampering and its suitability for high-performance, security-sensitive applications. This research provides a practical reference for developers and researchers seeking reliable data integrity verification mechanisms in networked systems
Computational Analysis of GDP, Inflation, and Unemployment Trends in the Western Balkans
No full textUsing computational econometric techniques, this study examines three important macroeconomic indicators over a multi-year period: GDP growth, inflation, and unemployment. The study uses a Python-based analytical pipeline for data processing, visualization, and interpretation by integrating cross-sectional and time-series data from trustworthy sources. The methodology evaluates indicator behavior under different economic conditions by using statis- tical learning and segmentation across multiple temporal phases. Based on the research outcomes, traditional macroeconomic frameworks, such as Okun\u27s Law and the Phillips Curve, exhibit limited predictive accuracy across heterogeneous economic environments, particularly when incorporating the effects of global disruptions. The research presents a modular analytical framework for real-time monitoring of macroeconomic dynamics, emphasizing the necessity for flexible, data-driven policy approaches. By integrating economic theory with computa- tional modeling, the study advances the development of scalable decision-sup- port systems, enhancing resilient governance in environments characterized by uncertainty, structural heterogeneity, and exogenous volatility
Audio Signal Compression Using Wavelet Transform: A MATLAB Implementation
No full textIn modern signal processing, the need to efficiently analyze and store non- stationary signals has become increasingly important, particularly for audio applications where both time and frequency localization are essential. Traditional Fourier-based methods provide global frequency information but fail to indicate when these frequencies occur, making them suboptimal for real-world, time-var- ying signals. This paper investigates the use of wavelet transforms, specifically the Daubechies wavelet for audio signal compression. A practical implementa- tion is developed in MATLAB, where the discrete wavelet transform (DWT) is applied to decompose audio signals into approximation and detail coefficients. Thresholding techniques are employed to remove insignificant coefficients, re- ducing data size while preserving perceptual quality. Results include coefficient visualization, compressed signal reconstruction, and Power Spectrum Density (PSD) analysis comparing original and compressed signals. The method achieves significant compression ratios without perceptible quality loss, demonstrating wavelet transform’s potential for audio data reduction