Search Results (298)

Secure Digital Evidence Management Systems (DEMSs) ae crucial for law enforcement agencies, because traditional systems are prone to tampering and unauthorised access. Blockchain technology, particularly private blockchains, offers a solution by providing a centralised and tamper-proof system. This study proposes a private blockchain using Proof of Work (PoW) to securely manage digital evidence. Miners are assigned specific nonce ranges to accelerate the mining process, called collaborative mining, to enhance the scalability challenges in DEMSs. Transaction data includes digital evidence to generate a Non-Fungible Token (NFT). Miners use NFTs to solve the puzzle according to the assigned difficulty level d, so as to generate a hash using SHA-256 and add it to the ledger. Users can verify the integrity and authenticity of records by re-generating the hash and comparing it with the one stored in the ledger. Our results show that the data was verified with 100% precision. The mining time was $2.5$ s, and the nonce iterations were as high as $80\times {10}^3$ for $d=5$. This approach improves the scalability and integrity of digital evidence management by reducing the overall mining time. Full article

The increasing penetration of renewable energy sources (RESs) has significantly altered the operational characteristics of modern power systems, resulting in reduced system inertia and fault current capacity. These developments introduce new challenges for maintaining frequency and voltage stability, particularly in low-inertia grids that are dominated by inverter-based resources (IBRs). This paper presents a hierarchical control framework that integrates synchronous condensers (SCs) and grid-forming (GFM) inverters through a leader–follower consensus control architecture to address these issues. In this approach, selected GFMs act as leaders to restore nominal voltage and frequency, while follower GFMs and SCs collaboratively share active and reactive power. The primary control employs droop-based regulation, and a distributed secondary layer enables proportional power sharing via peer-to-peer communication. A modified IEEE 14-bus test system is implemented in PSCAD to validate the proposed strategy under scenarios including load disturbances, reactive demand variations, and plug-and-play operations. Compared to conventional droop-based control, the proposed framework reduces frequency nadir by up to 0.3 Hz and voltage deviation by 1.1%, achieving optimised sharing indices. Results demonstrate that consensus-based coordination enhances dynamic stability and power-sharing fairness and supports the flexible integration of heterogeneous assets without requiring centralised control. Full article

The increased uptake of Electric Vehicles (EVs) requires the installation of charging stations in parking lots, both to facilitate charging while running daily errands and to support EV owners with no access to home charging. Photovoltaic (PV) generation is ideal for powering up EVs, both for environmental reasons and for the benefit it creates for Charging Point Operators (CPOs). In this paper, we propose a centralised V1G Smart Charging (SC) algorithm for EV parking lots, considering real EV charging dynamics, which minimises both the EV charging costs for their owners and the CPO electricity provision costs or the related CO₂ emissions. We also introduce an innovative SC benefit-splitting algorithm that makes sure SC savings are fairly split between EV owners. Eight scenarios are described, considering costs or emissions minimisation, with and without a PV system. The centralised algorithm is benchmarked against a decentralised one, and tested in an exemplary workplace parking lot in Denmark, that includes includes 12 charging stations and one PV system, owned by the same entity. Reductions of up to 11% in EV charging costs, 67% in electricity provision costs for the CPO, and 8% in CO₂ emissions are achieved by making smart use of a 35 kWp rooftop PV system. Additionally, the SC benefit-splitting algorithm successfully ensures that EV owners save money when adopting SC. Full article

Marble votive reliefs from rural sanctuary contexts have seldom undergone archaeometric investigation, despite their potential to illuminate regional trade and production networks. This study focuses on such reliefs from Philippopolis and its hinterland, with particular emphasis on cult sites in Roman Thrace. Using a stable isotope (δ¹³C and δ¹⁸O) and trace element analysis via ICP-MS, integrated with petrography, the provenance of marble used in these artefacts was determined. The results identify Asenovgrad marble—prevalent in the Rhodope Mountains—as the primary material, with a minority of examples sourced from Prokonnesos and the southeastern Rhodopes. The predominantly fine-to-medium-grained nature of Asenovgrad marble may have facilitated the execution of small, detailed iconography. The consistent use of this local stone across votive types and deities implies centralised production, likely by one or more local workshops. These findings contribute to our understanding of marble selection, workshop localisation, and regional connectivity during the Roman period. They also highlight the importance of combining geochemical and petrographic methods for reliable marble provenance. This research demonstrates that even modest sanctuaries can yield critical data on raw material distribution and artisanal practices within broader economic and cultural frameworks. Full article

Nowadays, when battery-powered electric vehicles (EVs) travel along motorways, their drivers decide where to recharge their cars’ batteries with no or scarce information on the occupancy status of the next charging stations. While this may still be acceptable in most countries, due to the limited number of EVs on motorways, long queues may build-up in the coming years with increased electric mobility, unless smart allocation strategies are designed and implemented. For instance, as we shall investigate in this manuscript, a centralised coordination of the charging strategies of individual EVs has the potential to significantly reduce the queuing time at charging stations. In particular, in this paper we explain how the charging problem on motorways can be modelled as an optimisation problem, we propose some strategies based on dynamic optimisation to solve it, and we explain how this may be implemented in practice using a centralised charge manager that exchanges information with the EVs and solves the optimisation problems. Finally, we compare in a realistic scenario the current decentralised recharging strategies with a centralised one, and we show that, under simplifying assumptions, queueing times can be reduced by more than 50%. Such a significant reduction allows one to greatly improve vehicular flows and general journey durations without requiring building new infrastructure. Reducing queuing times has a positive impact on traffic congestion and emissions, and the more geographically balanced energy demand of the proposed methodology mitigates energy consumption peaks. Full article

This study examines the relationship between K-Pop and education migration to South Korea in the context of the global internet and the COVID-19 pandemic. It focuses on the phenomenon in which local Asian territories have been widely influenced by the Korean Wave, particularly K-Pop, even during the era of global communication and health risks. This research illuminates some intriguing aspects of the distinctive reception patterns of Korean Wave audiences, as well as their unique characteristics, such as innocence, transgression, and the nuanced dynamics of the fandom during that period. Furthermore, this research engages critically with controversial aspects of cultural politics, such as the transmission of the legacy of K-Pop and the centralisation of femininity more actively. This study concludes that K-Pop has recently been relocated to the conjunctures of mediated and overdetermined influences on students’ education migration to South Korea rather than acting as a direct power and reason for it, particularly in the context of the COVID-19 pandemic and the rapid digitalisation of education. Full article

Background: The global number of operatively treated proximal femoral fractures is steadily growing, driven by the demographic shift toward an increasingly elderly, frail, and comorbid population. This clinical condition profoundly impacts not only patient health but also the finances of healthcare systems. The aim of this economic analysis was to investigate the impact on direct costs of orthogeriatric co-management (OGCM) compared to standard of care (SOC). Methods: A retrospective analysis was conducted investigating two comparable cohorts of patients aged 75 and above, originating from the exact same geographic area, who underwent surgical treatment for proximal femoral fractures in 2023. The two cohorts differed in their perioperative care protocols: one followed an OGCM (n = 143) protocol, while the other adhered to a SOC protocol (n = 141). Economic data were retrieved from the centralised finance department managing the two hospital sites under investigation. Results: The findings revealed that the OGCM protocol was associated with direct costs that were not higher (CHF 16,019 vs. CHF 16,713, p = 0.78) compared to SOC, despite higher daily costs in the OGCM cohort (CHF 2504 vs. CHF 2202, p < 0.0001). This difference was largely driven by a significantly shorter length of stay in the OGCM group (6 days vs. 7 days, p = 0.002). Conclusions: Optimising resource allocation through tailored geriatric care protocols suggests not only an improvement in clinical outcomes but also a reduction in economic burden, thereby alleviating pressure on the healthcare system. Full article

The integration of renewable energy into residential microgrids presents significant challenges due to solar generation intermittency and variability in household electricity demand. Traditional forecasting methods, reliant on historical data, fail to adapt effectively in dynamic scenarios, leading to inefficient energy management. This paper introduces a novel adaptive energy management framework that integrates streaming machine learning (SML) with a hierarchical fractal microgrid architecture to deliver precise real-time electricity demand forecasts for a residential community. Leveraging incremental learning capabilities, the proposed model continuously updates, achieving robust predictive performance with mean absolute errors (MAE) across individual households and the community of less than 10% of typical hourly consumption values. Three battery-sizing scenarios are analytically evaluated: centralised battery, uniformly distributed batteries, and a hybrid model of uniformly distributed batteries plus an optimised central battery. Predictive adaptive management significantly reduced cumulative grid usage compared to traditional methods, with a 20% reduction in energy deficit events, and optimised battery cycling frequency extending battery lifecycle. Furthermore, the adaptive framework conceptually aligns with digital twin methodologies, facilitating real-time operational adjustments. The findings provide critical insights into sustainable, decentralised microgrid management, emphasising improved operational efficiency, enhanced battery longevity, reduced grid dependence, and robust renewable energy utilisation. Full article

Background: Strategies are needed to address the elevated prevalence of chronic kidney disease (CKD) in socioeconomically disadvantaged regions where obesity, smoking, and type 2 diabetes rates are high. Methods: Recognising the inadequacy of generic health approaches in complex contexts, this study employed a participatory action research (PAR) framework to design and deliver five co-design community workshops in two stages over one year. Stage one workshops identified key matters of concern and stage two focussed on problem solving and co-creating solutions. The goal was to inform health service delivery in a region with high CKD prevalence and explore strategies to overcome barriers to individualised, collaborative care, and promote self-management. Results: The workshops identified three themes: 1. achieving person/family-centred care; 2. multimorbidity and siloed care (stage one); and 3. a kidney wellness framework (stage two). Conclusions: The findings reinforce the need for enhanced care coordination, and highlight the importance of consistent information sources, clear referral pathways, and centralised data sharing among health professionals. The proposed kidney healthcare framework aims to support various professionals, fostering linkages between primary and tertiary care, with an emphasis on professional development, especially in communicating complex information to individuals with multimorbidities. While co-designed healthcare models show promise, challenges persist in effective self-management amidst complex disease information and multimorbidity. Full article

Timely detection of organophosphates in outdoor environments remains a critical challenge for forensic and environmental monitoring. Traditional methods often require transporting samples to centralised laboratories, delaying essential response actions. In this study, we present a novel mobile analytical chemistry workstation that integrates capillary electrophoresis (CE) with capacitively coupled contactless conductivity detection (C4D) on low-cost polydimethylsiloxane (PDMS) microfluidic chips, enabling rapid and accurate on-site analysis of organophosphates. The system features a streamlined workflow that includes in-field sample collection, microfluidic analysis, and the wireless transmission of data to a central command centre for immediate decision-making. The detection system demonstrates a linear range of 2.5 mM to 20 mM for dimethyl methylphosphonate (DMMP), with an estimated limit of detection (LOD) of 2.5 mM. We evaluate the feasibility of combining CE and C4D under field conditions, highlighting both the strengths and limitations of this integrated platform. Full article

Agricultural supply chains face growing scrutiny due to rising concerns over food authenticity, safety, and sustainability. These challenges stem from issues such as contamination risks, fraudulent labelling, and the absence of reliable, real-time tracking systems. Existing systems often rely on centralised databases and fragmented data flows, limiting traceability, data integrity, and end-to-end visibility. While blockchain technology offers potential, most research focuses narrowly on traceability, overlooking its role in establishing secure product identity and its integration with emerging tools. This review investigates how Decentralised Identifiers (DIDs), digital twins, and smart contracts—in conjunction with blockchain—can create verifiable digital representations of agricultural products and automate trust mechanisms. Through an analysis of over sixty recent sources and leading standards (e.g., W3C DIDs, Hyperledger Aries), the study identifies key gaps in interoperability, governance, and system maturity. A layered system architecture is proposed, and its application is demonstrated in a cold-chain case scenario. The paper concludes with a roadmap for empirical validation and policy alignment, contributing a practical and scalable framework for researchers, practitioners, and regulators advancing blockchain-enabled traceability systems. Full article

Technological evolution has driven the integration of computing devices in various domains, giving rise to heterogeneous and dynamic intelligent environments; together with market pressure, these pose challenges in formulating an architecture that takes advantage of contextual knowledge. In terms of architectural design, we are witnessing a transition from a centralised, monolithic view of systems to a decentralised view that incorporates the vertical and horizontal dimensions of the production environment. Therefore, this review aimed to (i) identify the requirements, (ii) find out about the representation models and context inference techniques, and (iii) identify architectural technologies, norms, models, and standards. The results observed in 25 articles made it possible to identify interoperability, automation, and decision-making as convergence points and observe the adoption of ontologies as a research area for context representation. In contrast, the discussion of context inference techniques remains open. Finally, this study presents recommendations for the design of a context-aware systems architecture that incorporates the principles of Industry 4.0 and facilitates the development of applications. Full article

It is anticipated that by 2028 there will be a significant increase in the use of HWHP systems in Great Britain (GB). Such systems are considered a better, energy-efficient alternative to fossil fuel-based burners and furnaces, as they use electricity. There are concerns that these systems are susceptible to microbial contamination because they hold water at lower temperatures. In particular, the concern is regarding Legionella contamination, as it can potentially cause disease in the general public and those who are maintaining and replacing these systems. Therefore, this review was focused on understanding the potential risk posed by their increased use and maintenance requirements. This review was approached systematically but was not a full systematic review. There were 61 papers that were considered potentially relevant to the research questions. Of these, 40 papers were considered relevant to the topic of Legionella in HWHP and underwent full article assessment and data extraction. The remaining papers were considered useful for background information. The scope of this review established that Legionella are a known risk in hot water systems that can be carried over to HWHP systems, yet there is minimal evidence to suggest that the current control measures are being appropriately applied to reduce the risk of exposure. When considering countrywide legislation and guidance, it appears that the risk is considered lower in single- or multi-family homes that do not require a centralised system. This review included the assessment of information regarding the safety of working with HWHP systems with regards to maintenance and replacement. The authors found a lack of information regarding these safety concerns. This review is among the first to systematically evaluate the risks of Legionella contamination in HWHP systems. Full article

Effective anomaly detection is essential for realizing modern and secure industrial control systems. However, the direct integration of anomaly detection within such a system is complex due to the wide variety of hardware used, different communication protocols, and given industrial requirements. Many components of an industrial control system allow direct integration, while others are designed as closed systems or do not have the required performance. At the same time, the effective usage of available resources and the sustainable use of energy are more important than ever for modern industry. Therefore, in this paper, we present a modular and hybrid concept that enables the integration of efficient and effective anomaly detection while optimising the use of available resources under consideration of industrial requirements. Because of the modular and hybrid properties, many functionalities can be outsourced to the respective devices, and at the same time, additional hardware can be integrated where required. The resulting flexibility allows the seamless integration of complete anomaly detection into existing and legacy systems without the need for expensive centralised or cloud-based solutions. Through a detailed evaluation within an industrial unit, we demonstrate the performance and versatility of our concept. Full article

The COVID-19 pandemic highlighted the urgent need for sustainable and scalable air disinfection technologies in HVAC systems, addressing the limitations of energy-intensive and chemically intensive conventional methods. This study developed and evaluated a pilot experimental installation integrating plasma chemistry and photocatalysis for airborne pathogen and pollutant mitigation. The installation, designed with a modular architecture to simulate real-world HVAC dynamics, employed a bipolar plasma ioniser, a TiO₂ photocatalytic module, and an adsorption-catalytic module for ozone abatement. Characterization techniques, including SEM and BET analysis, were used to evaluate the morphology and surface properties of the catalytic materials. Field tests in a production room demonstrated a 60% reduction in airborne microflora in three days, along with effective decomposition of ozone. The research also determined the optimal electrode geometry and interelectrode distance for stable corona discharge, which is essential for efficient plasma generation. Energy-efficient design considerations, which incorporate heat recovery and heat pump integration, achieved a 7–8-fold reduction in air heating energy consumption. These results demonstrate the potential of integrated plasma photocatalysis as a sustainable and scalable approach to enhance indoor air quality in centralised HVAC systems, contributing to both public health and energy efficiency. Full article