Search Results (83)

To address the impact of insulation medium degradation in the arc quenching chambers of ultra-high-voltage SF₆ circuit breakers on phase-controlled switching accuracy caused by multiple operations throughout the service life, this paper proposes an adaptive switching algorithm. First, a modified formula for the breakdown voltage of mixed gases is derived based on the synergistic effect. Considering the influence of contact gap on electric field distortion, an adaptive switching strategy is designed to quantify the dynamic relationship among operation times, insulation strength degradation, and electric field distortion. Then, multi-round switching-on and switching-off tests are carried out under the condition of fixed single-arc ablation amount, and the laws of voltage–current, gas decomposition products, and pre-breakdown time are obtained. The test data are processed by the least squares method, adaptive switching algorithm, and machine learning method. The results show that the coincidence degree of the pre-breakdown time obtained by the adaptive switching algorithm and the test value reaches 90%. Compared with the least squares fitting, this algorithm achieves a reasonable balance between goodness of fit and complexity, with prediction deviations tending to be randomly distributed, no obvious systematic offset, and low dispersion degree. It can also explain the physical mechanism of the decay of insulation degradation rate with the number of operations. Compared with the machine learning method, this algorithm has stronger generalization ability, effectively overcoming the defects of difficult interpretation of physical causes and the poor engineering adaptability of the black box model. Full article

This study proposes a Fuzzy-Based Control System (FBCS) for a Bulk Service Queueing Model with Vacation, designed to optimize service performance by dynamically adjusting system parameters. The queueing model is categorized into three service levels: (A) High Bulk Service, where a large number of arrivals are processed simultaneously; (B) Medium Single Service, where individual packets are handled at a moderate rate; and (C) Low Vacation, where the server takes minimal breaks to maintain efficiency. The Mamdani Inference System (MIS) is implemented to regulate key parameters, such as service rate, bulk size, and vacation duration, based on input variables including queue length, arrival rate, and server utilization. The Mamdani-based fuzzy control mechanism utilizes rule-based reasoning to ensure adaptive decision-making, effectively balancing system performance under varying conditions. By integrating bulk service with a controlled vacation policy, the model achieves an optimal trade-off between processing efficiency and resource utilization. This study examines the effects of fuzzy-based control on key performance metrics, including queue stability, waiting time, and system utilization. The results indicate that the proposed approach enhances operational efficiency and service continuity compared to traditional queueing models. Full article

The technological growth in the automation of manufacturing processes, as seen in Industry 4.0, is characterized by a constant revolution and evolution in small- and medium-sized factories. As basic and advanced technologies from the pillars of Industry 4.0 are gradually incorporated into their value chain, these factories can achieve adaptive technological transformation. This article presents a practical solution for companies seeking to evolve their production processes during the expansion phase of their manufacturing, starting from a base architecture with Industry 4.0 features which then integrate and implement specific tools that facilitate the duplication of installed capacity; this creates a situation that allows for the development of manufacturing execution systems (MESs) for each production line and a fog computing node, which is responsible for optimizing the load balance of order requests coming from the cloud and also acts as an intermediary between MESs and the cloud. On the other hand, legacy Machine Learning (ML) inference acceleration modules were integrated into the single-board computers of MESs to improve workflow across the new architecture. These improvements and integrations enabled the value chain of this expanded architecture to have lower latency, greater scalability, optimized resource utilization, and improved resistance to network service failures compared to the initial one. Full article

Housing retrofit plays a pivotal role in achieving sustainability goals. The fragmented nature of the retrofit industry has been identified as a barrier to driving retrofit at scale. The study aims to analyse how to strategically improve the concept of the one-stop-shop model to drive housing retrofit at scale with the help of existing literature. The concept of a one-stop-shop model provides all the retrofit services with a single contact to the client. A systematic literature review approach was used. Only peer-reviewed journal articles, book chapters and conference articles published from 2016 to 2025 in English were selected. There are 12 shortlisted journal and conference proceedings articles critically evaluated under three themes: delivery method, ownership structure and level of responsibility. The findings highlight the different characteristics of the one-stop-shop model under these themes. Considering the existing case studies, starting a one-stop shop under a hybrid delivery method and a medium level of responsibility is recommended for retrofit at scale. The ownership structure shall be context-specific. Limitations could be given as the researcher bias and the missed articles in databases not considered for this review. Further research is suggested on how the characteristics of a one-stop shop can be customised, considering the context-specific resources and purposes. Full article

Gonghe Basin is an important frontier of resource and energy development and environmental protection on the Qinghai–Tibetan Plateau and upper sections of the Yellow River. As a characteristic ecotone, this area exhibits complex and diverse ecosystem types while demonstrating marked ecological vulnerability. The response of ecosystem services (ESs) to human activities (HAs) is directly related to the sustainable construction of an ecological civilization highland and the decision-making and implementation of high-quality development. However, this response relationship is unclear in the Gonghe Basin. Based on remote sensing data, land use, meteorological, soil, and digital elevation model data, the current research determined the human activity intensity (HAI) in the Gonghe Basin by reclassifying HAs and modifying the intensity coefficient. Employing the InVEST model and bivariate spatial autocorrelation methods, the spatiotemporal evolution characteristics of HAI and ESs and responses of ESs to HAs in Gonghe Basin from 2000 to 2020 were quantitatively analyzed. The results demonstrate that: From 2000 to 2020, the HAI in the Gonghe Basin mainly reflected low-intensity HA, although the spatial range of HAI continued to expand. Single plantation and town construction activities exhibited high-intensity areas that spread along the northwest-southeast axis; composite activities such as tourism services and energy development showed medium-intensity areas of local growth, while the environmental supervision activity maintained a low-intensity wide-area distribution pattern. Over the past two decades, the four key ESs of water yield, soil conservation, carbon sequestration, and habitat quality exhibited distinct yet interconnected characteristics. From 2000 to 2020, HAs were significantly negatively correlated with ESs in Gonghe Basin. The spatial aggregation of HAs and ESs was mainly low-high and high-low, while the aggregation of HAs and individual services differed. These findings offer valuable insights for balancing and coordinating socio-economic development with resource exploitation in Gonghe Basin. Full article

We investigate what drives small and medium-sized enterprises (SMEs) in the Alps–Adriatic macro-region to offer green products and services. A sample of 2305 SMEs from Flash Eurobarometer 498 is analyzed with a multinomial logit model that distinguishes firms that already offer green products/services, those planning to do so within two years, and those with no such intention. SMEs implementing ≥ 5 resource-efficiency actions are 75% more likely to offer green products/services (RRR = 1.75, p < 0.05). An increase in the share of green jobs to >30% of staff triples that likelihood (RRR = 3.65, p < 0.01). Selling only services reduces the probability by 17%. Country dummies show Austria and Slovenia as early movers, while Croatia lags. This is the first study to apply a three-outcome model to green market activity in this macroregion, thus revealing nonlinear and country-specific patterns that a binary approach would mask. This study has multiple implications for entrepreneurial practice: (i) entrepreneurs should focus on high-leverage resource-efficiency bundles (energy, waste, circular design) rather than single actions; (ii) policymakers should combine financial incentives with green-skills vouchers to accelerate adoption in service-oriented SMEs. Full article

Public service facilities are the cornerstone of urban development and further expansion, and their spatial distribution fairness is closely related to the quality of life of urban residents. Existing research tends to focus on coverage analysis of a single city or a single type of public service facility, lacking a macro perspective at a medium-to-large scale and consideration of residents’ public service needs. To improve the monitoring of urban public service facility coverage and supply–demand patterns, this paper adopts an urban diagnostic perspective, using 14 megacities from nine urban agglomerations in China as the study area. By integrating spatial and temporal social sensing big data, including road networks, population, and points of interest (POI) data, and employing spatial analysis methods including coverage rate calculation, supply–demand matching efficiency, spatial heterogeneity, and sp{atial stability analysis, this study reveals the spatial distribution patterns of various facilities within cities, as well as the heterogeneity, balance, and equity of supply–demand matching efficiency between different cities. The results show that the spatial distribution of public service facilities in different cities generally tends to concentrate in the central areas, although there are some variations due to local topographical influences. The coverage rate of transportation and education facilities is relatively high, while that of healthcare facilities is generally lower. This study provides information support for urban planning and the optimization of public service facility allocation, contributing to the achievement of sustainable urban development through the comprehensive analysis and comparison of 14 megacities. Full article

Driven by the path of ecological transition, municipal solid waste management is now more than ever at the center of debates on the most efficient delivery methods. Although competition policy advocates subdivision into lots to facilitate medium-sized enterprise participation, in some cases—notably when substantial investments are required to achieve circular economy and sustainable development goals—a single-operator model may prove more efficient. Using a mixed research approach that integrates empirical evidence and market analysis, this study examines the relevance of cost curves, transaction costs, and market structure in determining the optimal service delivery model. The findings indicate that for large cities, consolidating MSW management services under a single contract yields significant cost advantages due to economies of scale and scope and is better suited to supporting the investments necessary for circular economy objectives. Practical implications for local policymakers highlight the need to assess utility sector policies carefully. Decisions at the local level should account for the interplay between the economic environment and the role of industrialization and economies of scale in fostering sustainable development. We suggest policymakers design policies that balance market efficiency with equitable access to services while also considering the scale of service provision, as it influences sustainability and economic resilience. Full article

With the rise in patients traveling worldwide for medical treatment in recent years, the importance of patient care continuum has become increasingly evident. We aimed to analyze the role of video consultations in facilitating medical care for patients traveling internationally for medical care in South Korea. In this retrospective study, data were gathered on video consultations for international medical travelers conducted between January 2021 and December 2023 at a single tertiary hospital. We analyzed information on patient demographics, the content of video consultation, and how these factors were associated with the patient’s decision to travel for treatment. A total of 16.5% of international medical travel patients who underwent video consultation subsequently traveled for treatment. Patients who engaged directly with the institution were more likely (aOR 5.74, [95% CI 1.20–27.33]) to travel for treatment compared to those who relied on domestic or international travel services. Additionally, patients who participated in follow-up video consultations were more likely (aOR 4.06, [95% CI 1.04–15.92]) to travel compared to those who underwent their first video consultation. International medical travel patients utilized video consultations for a range of medical conditions, with the likelihood of subsequent treatment travel being associated with both the medium through which consultations were initiated and prior experience with the institution. Full article

Previous studies have focused on the fact that government policies are the key factors in promoting the development of intelligent construction in construction enterprises. However, how to select different forms of policy support and quantify the intensity of policy support, as well as the impact on the behavioral strategies of construction enterprises and the government, still needs in-depth exploration. This paper constructs an evolutionary game model between construction companies and the government, using the system dynamics simulation software Vensim to analyze the model under three different government policy support scenarios. The study explores how varying levels of policy support and key factors influence the strategic choices of the game participants, providing valuable insights for promoting the development of intelligent construction. The key findings are as follows: (1) The willingness to adopt intelligent construction is heavily dependent on policy incentives. The incentive effect of the three single policies is much lower than that of the combined policies, and only high-intensity special fund support (more than 8 CNY/m²) significantly promotes widespread adoption. Among combinations of policies, tax incentives coupled with special funds prove most effective. (2) The government’s decision to actively promote intelligent construction hinges on a cost–benefit analysis. Under medium to high levels of special fund support, medium to low levels of service support are more beneficial for reaching a stable state of intelligent construction implementation. (3) Reducing the incremental costs of intelligent construction transformation is the primary key factor in promoting construction. The findings contribute to a deeper understanding of how both the government and construction companies can adjust their strategies in response to policy changes, ultimately leading to more effective policy implementation and strategic decision-making. Full article

Positioning information greatly enhances the convenience of people’s lives and the efficiency of societal operations. However, due to the impact of complex indoor environments, GNSS signals suffer from multipath effects, blockages, and attenuation, making it difficult to provide reliable positioning services indoors. Smartphone indoor positioning and navigation is a crucial technology for enabling indoor location services. Nevertheless, relying solely on a single positioning technique can hardly achieve accurate indoor localization. We reviewed several main methods for indoor positioning using smartphone sensors, including Wi-Fi, Bluetooth, cameras, microphones, inertial sensors, and others. Among these, wireless medium-based positioning methods are prone to interference from signals and obstacles in the indoor environment, while inertial sensors are limited by error accumulation. The fusion of multi-source sensors in complex indoor scenarios benefits from the complementary advantages of various sensors and has become a research hotspot in the field of pervasive indoor localization applications for smartphones. In this paper, we extensively review the current mainstream sensors and indoor positioning methods for smartphone multi-source sensor fusion. We summarize the recent research progress in this domain along with the characteristics of the relevant techniques and applicable scenarios. Finally, we collate and organize the key issues and technological outlooks of this field. Full article

Mobility-as-a-service (MaaS) apps provide a single platform for journey planning, booking, payment and ticketing, and are proposed as a medium for encouraging sustainable travel behaviour. Generating sustainable-vehicle-based journey alternatives can be formulated as a multi-modal multi-objective journey-planning problem, one that is known to have a prohibitively large solution space. Building on prior insights, we develop a scalable decomposition-based solution strategy. A Pareto set of journey profiles is generated based on inter-transfer-zone objective criteria contributions. Then, guided by neural-network predictions, extended versions of existing shortest-path algorithms for open and public transport networks are used to optimise the paths and transfers of journey profiles. A novel hybrid k-means and Dijkstra’s algorithm is introduced for generating transfer-zone samples while accounting for transport network connectivity. The resulting modularised algorithm knits together and extends the most effective existing shortest-path algorithms using neural networks as a look-ahead mechanism. In experiments based on a large-scale transport network, query response times are shown to be suitable for real-time applications and are found to be independent of transfer-zone sample size, despite smaller transfer-zone samples, leading to higher quality and more diverse Pareto sets of journeys: a win-win scenario. Full article

The importance of the electronics sector in the modern world is unquestionable, as it demonstrates clean technology, dry processes, and efficient design, which favor Industry 4.0 and sustainability. Nonetheless, the large number of instruments developed, and their correspondent quick obsolescence, imply an increment in electronic waste. Therefore, in this work, with the aim of diminishing obsolescence, we developed and customized one application that runs independently of systems and takes advantage of the existing computing structures. The application is a new edge computing structure (the AIFC) that is based on an enterprise service bus (ESB) developed in decentralized microservices. In this study, we conducted action research involving the collaboration of researchers and practitioners, and the tests involved six different scenarios; they used existing low-cost, basic computing environments and ranged from the proof of concept, prototype, minimum viable product, and scalability to the roadmap for the structure implementation. The six scenarios emulated sections of a small and medium-sized enterprise (SME), and all the developed microservices communicate with each other to perform data filtering, processing, storage, query, and sensor data acquisition. The results show that it is possible to carry out these functions with low latency and without any decrement or even increase in performance when compared with more conventional cloud computing structures, and it is also possible to manipulate different products that do not have single, consolidated structures. Moreover, there is no need to update machines or communication structures, which are the main factors of rapid obsolescence. Therefore, following the steps of the AIFC development, the results from the proof of concept to the minimum viable product and scalability tests correspond to a roadmap for a sustainable solution and are an important tool for both Industry 4.0 and SMEs. Full article

Urban park green spaces have the functions of improving the urban ecological environment and providing recreational services, and at the same time, they have a certain effect on the value of the surrounding residential property. To quantitatively assess the value of the landscape premium function of park green space, many scholars have carried out research exploration and adopted a variety of methods (such as the contingent valuation method (CVM), travel cost method (TCM) and hedonic price method (HPM)), which have developed from simple theoretical models with single factors to complex empirical models with multiple factors. Among them, the hedonic price method has become the mainstream research method, and in recent years, it has been widely adopted in combination with GIS technology. In terms of research objects, single park green space or multiple park green spaces in large cities are the main focus, while there are fewer studies on park green spaces in built-up areas of small and medium-sized cities. In terms of research content, there are more studies on the value-added coefficient of landscape premium and influence distance, and there are fewer studies on the total value of landscape premium. This article aims to calculate the total landscape premium value of all park green spaces in the built-up areas of small and medium-sized cities, proposing a complete and operable accounting system for the functional value of park green space landscape premiums by combining GIS with a hedonic pricing model and remote sensing image interpretation methods. For the first time, a method for interpreting the height of residential buildings within the benefit range of landscape premium through remote sensing images is proposed, and then the floor area ratio of residential plots is estimated, so as to estimate the total area of actual beneficial buildings. Therefore, this paper takes Chifeng City, a small and medium-sized city, as a case study, and empirically demonstrates the assessment of the landscape premium function of parks and green spaces in the built-up area of Chifeng City by using this accounting system. Research shows that this method has certain feasibility, not only calculating the total value of landscape premium but also addressing the issue in existing studies where all areas within the potential range of landscape premium function are counted as appreciated areas, leading to an overestimation of the premium. It further advances the accuracy of accounting for the value of landscape premium function of urban park green space and provides theoretical reference for the planning and construction of urban park green space. Full article

Background: Pickleball is an exponentially growing sport with a lack of notation-based studies. Consequently, this research aimed to conduct a match analysis in men’s singles to enhance the understanding of the game and optimize training practices. Methods: Using observational methodology, a total of 1145 points were analyzed from the semifinal and final rounds of five Professional Pickleball Association Tour tournaments. Data were recorded with LINCE PLUS V.2.1.0 software using the OI-PICKLEBALL-S23 observational instrument. Descriptive statistical analyses were conducted with IBM-SPSS version 25.0, and gameplay patterns were detected using Theme 6.0 Edu. Statistical significance was set at p < 0.05. Results: The data indicated that service faults at the start of the game were minimal (2.4%). The server won fewer points than the returner in the overall set of analyzed points (46.6%). Most points were concluded in short rallies (1–4 shots; 43%) or medium-length rallies (5–8 shots; 44%), with the final shot predominantly occurring from striking zone 2, the area closest to the non-volley line (50.7%). Ground strokes (55.1%) and volleys (38.4%) were the most common final shots. Conclusions: The insights gained from this study can benefit high-performance players and coaches and provide a foundation for future notation-based research in pickleball. Full article