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Data Privacy and Compliance in Information Security
No full textIn today’s digital age, protecting sensitive data is a paramount concern. This chapter explores the intricate relationship between data privacy and compliance in information security, discussing the challenges, regulations, and best practices involved. Data privacy is crucial in a world where personal information is constantly collected, stored, and shared. The chapter highlights the potential risks and consequences of data breaches and unauthorized access, emphasizing the importance of implementing robust security measures. Compliance in information security is a complex landscape. The chapter examines legal frameworks like the GDPR and CCPA, which aim to safeguard privacy rights. It discusses the challenges that organizations face in achieving compliance and the potential repercussions of non-compliance. To ensure data privacy and compliance, the chapter outlines best practices. It emphasizes a comprehensive approach, including encryption techniques, access controls, security audits, and fostering privacy awareness within organizations. The chapter concludes by emphasizing the evolving nature of data privacy and compliance. It highlights the need for continuous learning and adaptation to keep pace with emerging technologies, changing regulations, and ever-changing threats. Overall, this chapter provides a comprehensive overview of the critical issues surrounding data privacy and compliance in information security. It serves as a valuable resource for individuals, organizations, and policymakers navigating the complex landscape of data protection and ensuring the privacy and security of sensitive information.</p
Defining Intent-Based Service Management Automation for 6G Multi-Stakeholders Scenarios
No full textThis article aims to explore the requirements and challenges that Intent-Based Management (IBM) systems should look towards to deliver proper automation management in multi-stakeholder 6G scenarios. To do so, the evolution of the telecommunications actors is presented to identify how they will interact with the use of intents and what IBM systems must face to fulfil with the tenants expectations while interacting among other IBM domains (aggregation vs. federation models). In a second step, this article presents how the IBM systems functionalities should be organized (based on standards research and comparative) and a set of enablers using them to properly deliver the automation needed to accomplish the requests done by the tenants. On a third step, a set of End-to-End (E2E) intent-based services are described to illustrate how the different enablers (and the functionalities they use) may work to reach the E2E service goal. Finally, a set of experimental results related to how intent conflicts should be manage is presented, followed by the conclusions
Delay minimization in NTNs:Deployment and caching optimization for satellite- and cache-aided UAV
No full textThis paper explores satellite- and cache-aided UAV communications for content delivery in non-terrestrial networks, demonstrating significant potential to offer widespread connectivity and high capacity. Specifically, the UAV provides caching to alleviate backhaul congestion, while the satellite supports the UAV's backhaul link. A problem is formulated to minimize content transmission delay. To address this problem, we design a user clustering and UAV deployment method based on an improved K-means algorithm, which determines the minimum number of UAVs and their deployment locations while ensuring QoS of users. Then, using linear programming relaxation and interior point methods, we obtain the optimal cache placement strategy. Simulations analyze the effects of Zipf parameter, backhaul bandwidth, and UAV altitude on system performance. The results and analysis can provide guidance for real-world network deployment.</p
Forecasting Green Energy Production in Latin American Countries and Canada via Temporal Fusion Transformer
No full textForecasting green energy is crucial in diminishing dependence on fossil fuels and fostering sustainable development. However, it encounters notable challenges, such as variable demand, restricted data availability, the integration of various datasets, and the necessity for precise long-term projections. This study thoughtfully examines these issues using the temporal fusion transformer (TFT) model to project green energy production across five Latin American nations (Argentina, Brazil, Chile, Colombia, and Mexico) and Canada, drawing on data from 1965 to 2023. The performance of the proposed TFT is more authentic as compared with the gated recurrent unit (GRU), the long short-term memory (LSTM), deep autoregression (DeepAR), and the meta graph-based convolutional recurrent network (MegaCRN). The TFT has a mean square error (MSE) of 0.0003, root mean square error (RMSE) of 0.0173, mean absolute error (MAE) of 0.0112 and mean absolute percentage error (MAPE) of 1.76%. From the preceding results, it is clear that the proposed TFT model can identify dynamic energy patterns that will contribute towards achieving sustainable development goals by the end of 2040.</p
Biological contaminants analysis in microalgae culture by UV–vis spectroscopy and machine learning
Get PDFThis study elucidates the utility and efficacy of UV–visible spectroscopy for the detection and characterization of biological contaminants within microalgae cultures, augmented by machine learning algorithms. Biological contamination, exemplified by flagellates and rotifers, poses a significant concern due to its potential to rapidly devastate entire cultures, thus jeopardizing commercial viability. Conventional analytical methods for monitoring contamination, such as microscopy and cytometry, are often labor-intensive, reliant on specialized expertise for microorganism identification, and may lack specificity in discerning the nature of contamination, impeding timely intervention. UV–visible spectroscopy offers a compelling solution by overcoming many of these challenges, affording specificity in analysis, real-time monitoring capabilities, and automation, owing to the intricate pigment chemistry inherent in the microalgae realm, which generates distinct UV–visible spectra. Through the measuring of contaminated and uncontaminated samples, coupled with machine learning analysis of their respective spectra, this study explores the underlying biochemical principles driving spectral data, thereby justifying the efficacy of the technique. The findings underscore the wealth of information encapsulated within UV–visible spectral data, which can be effectively harnessed through classification algorithms for early-stage identification of contamination in real-time applications.</p
Corrigendum to “A life cycle assessment model to evaluate the environmental sustainability of lignin-based polyols” [Sustain. Prod. Consump. 52 (2024) 624–639, (S2352550924003312), (10.1016/j.spc.2024.11.019)]
No full textThe authors regret missing the Acknowledgement.</p
Design of a Solar-Wind Hybrid Renewable Energy System for Power Quality Enhancement:A Case Study of 2.5 MW Real Time Domestic Grid
No full textThe increasing global energy demand driven by climate change, technological advancements, and population growth necessitates the development of sustainable solutions. This research investigates the design, modeling, and simulation of a 2.5 MW solar-wind hybrid renewable energy system (SWH-RES) optimized for domestic grid applications. A survey conducted across 450 households identified a total energy demand of 2.3 MW, with distinct day and night usage profiles. In response, a hybrid system consisting of a 1.5 MW solar park and a 1 MW wind energy unit was designed to ensure continuous power supply. The system was modeled and simulated using MATLAB, and its performance was evaluated through a detailed Total Harmonic Distortion (THD) analysis. This research addresses the critical need for a sustainable and high-quality power supply by designing, modeling, and simulating a 2.5 MW solar-wind hybrid renewable energy system (SWH-RES) optimized to meet the energy demand of a surveyed 2.3 MW domestic load, while also reducing THD to acceptable levels for improved power quality and grid stability. The results demonstrated a significant reduction in THD, with voltage THD decreasing from 45.48% to 26.20% and current THD from 8.32% to 2.88% after implementing filtering components. These findings underscore the effectiveness of the proposed SWH-RES in providing stable, high-quality power while addressing the growing demand for sustainable energy solutions.</p
Future Energy Technology for Nonroad Mobile Machines
Get PDFGreenhouse gases emissions reduction in the energy and transportation systems is extremely important. Nonroad mobile machines (NRMMs) are a key factor of production in many industrial and transportation systems with high-energy intensity. NRMM cover a wide range of application sectors and operate often in harsh environments. This study presents a literature review for NRMM on agriculture and forestry, mining and earth-moving, construction, and ports. It provides an overview of future energy technology and energy-related business factors for NRMM, considering different geographical areas, various energy sources, energy delivery solutions, and different types of powertrains. The best solutions for the case combinations and projected market environments are derived for several case regions. This study also contains a detailed example of an off-grid mining with renewable energy supply. The analysis of the off-grid mining cases clearly reveals the differences between the Nordic conditions and southern conditions. The importance of the wind power as a source for the renewable energy is emphasized in Nordic conditions, but the solar power can augment it during the summer months. Also, the seasonal storage becomes important in the case of Nordic conditions.</p
Integrating “nature” in the water-energy-food Nexus: Current perspectives and future directions
No full textIntegrated approaches for managing natural resources are said to meet increasing demand for water, energy, and food, while maintaining the integrity of ecosystems, and ensuring equitable access to resources. The Water-Energy-Food (WEF) Nexus has been proposed as a cross-sectoral approach to manage trade-offs and exploit synergies that arise among these sectors. Although not initially included as a component of the Nexus, the role of nature in sustaining the water, energy, and food sectors and in regulating their interrelationships is increasingly recognised by Nexus researchers and practitioners. To converge existing approaches that integrate nature into the WEF Nexus and suggest a common framework, we – an interdisciplinary group of natural resources management researchers and systems thinkers from the European research network NEXUSNET COST Action – followed a collaborative process of knowledge creation combining literature review, elicitation of expert opinion and collaborative writing. Our results reveal a multiplicity of concepts utilised in the literature to represent, partially or fully, “nature” in the Nexus, such as “environment”, “ecosystems”, “ecosystem services”, “social-ecological systems”, and “biodiversity”. Disparity was also found in the role attributed to nature, represented by three key paradigms: (1) ecosystems as the fourth component of an expanded Nexus, i.e., the WEF-Ecosystems (WEFE) Nexus; (2) ecosystems as a foundational layer to the Nexus; and (3) the WEF Nexus as a central component of social-ecological systems (SES). By creating a hybrid approach that brings together the benefits of the respective paradigms, we present a forward-looking WEFE Nexus conceptualisation. This paradigm expands the mutual interlinkages among water, energy and food to the entirety of SES, thus acknowledging the social-ecological processes that are affected by and affect the WEF Nexus. The results of this collaborative research effort intend to provide researchers and stakeholders with means to better understand and ultimately manage Nexus issues towards a transformative change.<br/
Self-Sovereign Identity Adoption: Antecedents and Potential Outcomes
Get PDFSelf-Sovereign Identity (SSI) technology is transforming digital identity management by enabling individuals and organizations to control personal data securely. Its adoption promises enhanced privacy, data security, and trust in digital ecosystems. However, despite its rising importance, the key drivers and broader impacts of SSI adoption remain unclear. Understanding these factors is essential to support informed decision-making by organizations and policymakers, ensuring successful implementation and widespread adoption. This study addresses this critical research gap. We employed a qualitative field study, gathering data through interviews with senior SSI practitioners, participatory observations, and document analysis. This multi-method approach facilitated a comprehensive exploration of factors shaping SSI adoption. Our findings identify four categories of adoption antecedents. Organizational factors include leadership attitudes and financial stability. Societal and environmental drivers involve regulatory frameworks and public sector involvement. Ecosystem dynamics cover governance models and technological readiness. Individual traits such as risk tolerance and technical expertise also play a central role. We also highlight significant outcomes of SSI adoption. These include enhanced organizational efficiency, strengthened data privacy, and expanded ecosystem collaboration. Additionally, SSI adoption improves trust and scalability within digital ecosystems. Theoretically, this study advances technology adoption research by integrating ecosystem governance and individual-level factors into established frameworks. Practically, it provides actionable insights for organizational leaders and policymakers