CONTENTS
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A Practical Framework for Generating and Validating Synthetic
Databases: Application to Freight Transport Liviu-Ioan ZECHERU, Cristian-Eugen CIUREA 5 Synthetic databases are increasingly used in research and industry to support testing, training, and analysis without exposing sensitive information. This paper proposes a practical frame-work for generating and validating synthetic databases, structured around a pipeline that en-sures structural consistency, business relevance, and reproducibility. The framework is illus-trated through a case study on freight transport in Romania, where a relational model was de-signed to capture entities such as clients, trains, conductors, and transported goods. A Python-based generator was developed to populate the database with realistic values under domain-specific constraints (e.g., valid national identifiers, capacity limits, distinct departure/arrival sta-tions). Validation is focused on structural integrity, query performance, and privacy preserva-tion. The results show that the generated dataset is both realistic and safe for academic or en-terprise use, while the methodology is transferable to other economic and business contexts. Keywords: Synthetic Databases, Data Generation, Freight Transport, Data Validation Business Process Engineering through Artificial Intelligence Algorithms and Chaos Theory: A Conceptual Framework Marian STOICA, Andreea-Iuliana GHIMICIU 21 Today's business environments are characterized by increasing complexity and volatility, which highlights the limitations of traditional process engineering models. Faced with nonlinear and unpredictable organizational phenomena, classical methods of analysis and optimization become insufficient, making it necessary to integrate more advanced theoretical and technological frameworks. Chaos theory provides a conceptual tool for describing these dynamics, and artificial intelligence brings the ability to identify hidden patterns and generate robust predictions in seemingly unstable systems. This paper examines the synergy between chaos theory and artificial intelligence in business process engineering, focusing on how machine learning algorithms and neural networks can support managerial decisions, optimize processes, and strengthen organizational resilience. The main contribution is the formulation of a conceptual and methodological framework through which chaotic models, augmented with artificial intelligence, can support the digital transformation of organizations. Although the integration of these paradigms raises challenges related to complexity, transparency, and data access, the research findings highlight the real potential for building adaptive, intelligent, and future-oriented business systems. Keywords: Business process engineering, Artificial intelligence, Chaos theory, Machine learning algorithms, Neural networks, Organizational resilience, Digital transformation Arrival Time Prediction for Public Transport Using LSTM-Based Neural Networks Cristian DINU, Mihai DOINEA 33 Neural networks have recently found widespread application across various domains within IT software infrastructure. This study focuses on specific neural network architectures incorporating Long Short-Term Memory (LSTM) layers and their variations, aiming to effectively capture the dynamic, nonlinear nature of traffic data. LSTM networks are well-suited for learning long-term dependencies in sequential data, making them particularly effective for time series prediction tasks. To evaluate the performance of different LSTM-based architectures, we utilize a dataset comprising bus logs from New York City collected over a four-month period. The experimental results indicate that LSTM architectures demonstrate strong predictive capabilities and are well-suited for modeling complex temporal patterns in traffic data. Keywords: LSTM, Neural Networks, Machine Learning, Time estimation Sustainable Quantum Computing: Analyzing Costs and Carbon Emissions Teodor CERVINSKI, Cristian-Valeriu TOMA, Claudiu BRANDAȘ, Marius POPA 41 As quantum computing progresses from theory to practical systems, its environmental and eco-nomic sustainability remains underexplored. This paper analyzes both the carbon footprint and cost implications of quantum computing technologies, with attention to their alignment with global sustainability goals. Key contributors to energy consumption, emissions, and operational costs are identified across the quantum computing lifecycle: hardware manufacturing, cryogen-ic cooling, runtime power demands, and quantum circuit simulation. The study employs a qual-itative methodology, integrating a comprehensive review of scientific literature, environmental assessments, cost analysis reports, and benchmarking frameworks. It further presents a com-parative analysis of quantum and classical high-performance computing (HPC), evaluating en-ergy efficiency, environmental impact, and cost-effectiveness across realistic scenarios. By ad-dressing both sustainability and economic dimensions, this research provides new insights for developers and policymakers, supporting the advancement of greener and more cost-effective quantum technologies. Keywords: Quantum computing, Sustainability, Carbon footprint, Operational costs, Energy consumption, Environmental impact Towards the Smart Digital Circular Economy – Integrating Internet of Things and Digital Product Passports for Sustainability Innovation Sorin-Daniel GHEORGHE 50 This study explores the convergence of Internet of Things and Digital Product Passport technologies as a catalyst for achieving a Smart Digital Circular Economy. Anchored in a systematic literature review, the research identifies key IoT-driven use cases that enhance sustainability practices within Circular Economy context. The study also proposes a conceptual framework for integrating IoT data, interoperability standards, and circular metrics into DPP systems. By transforming static product information into dynamic, real-time data, the study demonstrates how IoT–DPP integration enables circular value creation, resource efficiency, and digital transparency across all stages of the product lifecycle. The findings offer both theoretical insights and practical guidance for industry stakeholders, policymakers, and researchers seeking to implement the digital transformation of circular economy practices and the circular transformation of the digital economy. Keywords: Circular economy, Digital Product Passports, Internet of Things, Sustainability The Power of Words in The Digital Era: The Impact of Terminology on Responses and Security Mechanisms in Combating Phishing Costinel-Valeriu GONCIULEA 76 In the digital era, words have a significant influence on how cyber threats are defined and perceived. This article examines the impact of framing phishing and other cybercrimes as „cyberattacks” on user responses and the legal and security mechanisms triggered. Confusing these concepts may discourage reporting incidents to authorities, leading users to delete messages and destroy evidence, which allows criminals to continue undisturbed. The study emphasizes the need for a clear distinction between cyberattacks, which threaten national security, and common cybercrimes, to ensure appropriate responses and effective protection measures. Moreover, this article seeks to clarify the essential differences between cyberattacks and cybercrime, highlighting their legal and strategic implications. Through a comparative analysis and a review of recent legislation, the study underscores the challenges and opportunities in managing these complex and dynamic threats. Keywords: Cyberattacks, Cybercrime, Computer fraud, National security, Cyber legislation, Cyber warfare, Computer offense, Phishing, Cybersecurity, Authorities, Digital era Publishing Guide for Authors 93 INFOREC Association 95 |
