Search Results (368)

The last kilometer connection problem of metro transit stations is the core factor to measure the connection efficiency and service quality. Establishing the spatiotemporal distribution pattern of the connection distance is conducive to clarifying the interaction mechanism between bike-sharing connections and urban space. This study focuses on the travel behavior of shared bicycle users accessing metro stations, aiming to reveal the access distance decay patterns and their relationship with influence factors. Finally, the random forest algorithm was used to explore the nonlinear relationship between the influencing factors and the connection decay distance, and to clarify the importance of the factors. Multiple linear regression was applied to examine the linear correlation between the distance decay coefficient and the factors influence. The geographically weighted regression was further employed to explore spatial variations in their effects. Finally, the random forest algorithm was used to rank the importance of the impact factors. The results indicate that proximity distance to metro stations, proximity distance to bus stops, and the number of bus routes serving the station area have significant negative correlations with the distance decay coefficient. Significant spatial heterogeneity was observed in the influence of each factor on the distance decay coefficient, based on the geographically weighted regression analysis. With a high goodness-of-fit (R² = 0.8032), the Random Forest regression model furthermore quantified the relative importance of each factor influencing the distance decay coefficient. The findings can be directly applied to optimize the layout of shared bicycle parking, metro access facilities planning, and multi-modal transportation system design. Full article

With the global trend towards “carbon neutrality,” the use of electric vehicles is becoming increasingly widespread, leading to new impacts on urban spaces. In the process of allocating resources for urban charging stations, there are widespread issues such as a singular planning approach and inadequate adaptation to actual travel demands. Therefore, this study adopts a method of integrating multi-source data to optimize the planning and layout of public electric vehicle charging facilities in Macau, striving to achieve breakthroughs in theoretical methods and key technologies. The study obtained a determination coefficient of R² = 0.43 through quantitative analysis, which is within a reasonable range of fitting spatial syntax and charging facility layout. This indicates that there is a moderate positive correlation between the distribution of charging facilities and core indicators such as road network integration and accessibility—about 43% of layout differences can be explained by spatial syntax indicators, and the remaining 57% of differences reserve space for optimizing multiple factors such as population density and parking lot distribution. On this basis, this study compares the layout experience of medium to high-density cities such as Hong Kong and Singapore, and combines the common characteristics of old parishes on Macau Island and new urban areas on outlying islands to explore innovative sustainable development technology paths that are suitable for Macau. This study not only summarizes the key factors and optimization breakthroughs that affect the spatial distribution of charging facilities in Macau, providing basic data and methodological strategies for charging facility planning, but also helps Macau save energy and reduce emissions, build a green city through layout optimization, provide practical reference for the development of land reclamation areas, and provide reference for carbon neutrality and smart city construction in the Guangdong Hong Kong Macau Greater Bay Area. Full article

Urban vitality is an important evaluation indicator for enhancing urban spatial efficiency and promoting sustainable development. However, few studies have systematically integrated steady-state and dynamic vitality perspectives. To address this gap, we integrate steady-state vitality and dynamic vitality indicators, and use geographically weighted regression (GWR) and geographically weighted logistic regression (GWLR) to quantify how the built environment, natural elements, and travel purposes influence urban vitality. The results reveal that: (1) From the steady-state perspective, urban vitality exhibits a distinct polycentric structure, with transportation POI and catering facilities serving as core driving factors; (2) From the dynamic perspective, areas where citizens are always highly concentrated are mainly influenced by floor area ratio and transportation POI. Green space coverage and building density significantly correspond to patterns of persistently low vitality, while periodic population fluctuations are associated with subway accessibility and proximity to waterfronts. This study provides a comprehensive analysis of the stable spatial distribution and dynamic changes in population aggregation, offering a theoretical and empirical basis for optimizing urban spatial layout and meeting citizens’ activity needs. Full article

Indoor positioning using commodity WiFi has gained significant attention; however, achieving sub-meter accuracy across diverse layouts remains challenging due to multipath fading and Non-Line-Of-Sight (NLOS) effects. In this work, we propose a hybrid Graph–Temporal Convolutional Network (GTCN) model that incorporates Access Point (AP) geometry through graph convolutions while capturing temporal signal dynamics via dilated temporal convolutional networks. The proposed model adaptively learns per-AP importance using a lightweight gating mechanism and jointly exploits WiFi Received Signal Strength (RSS) and Round-Trip Time (RTT) features for enhanced robustness. The model is evaluated across four experimental areas such as lecture theatre, office, corridor, and building floor covering areas from 15 m × 14.5 m to 92 m × 15 m. We further analyze the sensitivity of the model to AP density under both LOS and NLOS conditions, demonstrating that positioning accuracy systematically improves with denser AP deployment, especially in large-scale mixed environments. Despite its high accuracy, the proposed GTCN remains computationally lightweight, requiring fewer than ${10}^5$ trainable parameters and only tens of MFLOPs per inference, enabling real-time operation on embedded and edge devices. Full article

The topic of archaeological apothekes, i.e., storage areas not intended for display and not accessible to the public (depositi in Italian), has only recently received the attention it deserves, for reasons related to the history of research methodology. The archiving of archaeological material poses specific problems compared to other categories of material with which the process is generally associated, such as artistic artefacts. Excavation finds consist mainly (and increasingly) of a mass of anonymous, repetitive pottery fragments, not destined to be accessible to the public. The management of these storage facilities poses two sets of problems linked with its archiving: on one hand, its (digital) documentation; on the other hand, its physical arrangement. Both aspects have often been contemplated, but as separate entities by different specialists (archaeologists, conservators, etc.). An adequate approach requires however both aspects to be considered together, for archaeological material only achieves its full value when its context of origin is secure. Only proper management of digital and physical archives can ensure a full understanding of the historical significance of archaeological material. These challenges also apply to the Archaeological Mission of Phaistos, in Crete, where Italian have been active since 1900. The reorganisation of the warehouses in 2024–2025 provided an opportunity to adequately address both the digital archiving of the material and the layout of the warehouses, tackling at the same time the particularly pressing issue in this case of the reuse of ‘legacy data’, which poses problems of standardization. This led also to a new perspective, using old labels and boxes as metadata to reconstruct the methods of archaeological research. The main results however were the creation of a holistic approach to the management of archaeological material and its (written, graphic, photographic, and topographic) documentation through the adoption and implementation of PyArchInit (version 4.9.5), a plug-in of QGIS (version 3.40.7 Bratislava). Full article

Monitoring the complex, three-dimensional flow within centrifugal compressor diffusers remains a major challenge due to geometric confinement, high rotational speeds, and strong unsteadiness near surge and stall. This review provides a comprehensive assessment of contemporary instrumentation strategies for diffuser flow characterization, spanning pressure, temperature, velocity, vibration, and acoustic measurements. The article outlines the standards governing compressor instrumentation, compares conventional probes with emerging high-resolution and high-bandwidth sensor technologies, and evaluates the effectiveness of pressure- and temperature-based diagnostics, optical methods, and advanced dynamic sensing in capturing diffuser behavior. Case studies from industrial compressors, research rigs, and high-speed experimental facilities illustrate how sensor layout, bandwidth, and synchronization influence the interpretation of flow stability, performance degradation, and surge onset. Collectively, these examples demonstrate that high-frequency pressure and temperature probes remain indispensable for instability detection, while optical techniques such as PIV, LDV, and PSP/TSP offer unprecedented spatial resolution for understanding flow structures. The findings highlight the growing integration of hybrid sensing architectures, digital acquisition systems, and data-driven analysis in diffuser research. Overall, the review identifies current limitations in measurement fidelity and accessibility while outlining promising paths toward more robust, real-time monitoring solutions for reliable centrifugal compressor operation. Full article

The accessibility of rural tourism attractions is a key factor affecting their tourism development potential. Although forest land is the primary land cover type, the mechanism by which forest land influences accessibility has not been fully elucidated. This study takes Yongchun County in Fujian China as an example to explore the spatial relationship between forest land and the accessibility of rural tourism attractions. Based on multi-source spatial data and using a GIS cost raster analysis method, the study incorporates the road network, transportation modes, and land cover characteristics. Specifically, forest land was assigned a resistance coefficient of 1.5 to quantitatively assess the spatial pattern of attraction accessibility. In addition, spatial autocorrelation analysis was applied to reveal the spatial correlation characteristics between forest land distribution and attraction accessibility. The results indicate that: (1) There is a significant spatial complementarity between forest land distribution and attraction accessibility, which needs to be considered when building tourism networks. (2) The spatial pattern of forest land directly affects the layout of regional transportation networks, so planning for regional transportation network layouts should prioritize the impact of forest land. (3) By altering surface cover characteristics, forest land increases regional traversal resistance, thereby further affecting the spatial distribution pattern of attraction accessibility. This study provides empirical evidence for understanding the spatial relationship between forest land and rural tourism attraction accessibility and offers valuable reference for optimizing rural spatial structure and promoting tourism development. Full article

With the acceleration of urbanization, urban renewal and the renovation of old residential communities have become important measures to enhance the quality of cities and improve the living conditions of residents. How to scientifically identify and evaluate the environmental factors of public spaces and their impacts from the perspective of residents’ demands and satisfaction remains an important issue that urgently needs to be addressed in the current research field. This research takes the urban renewal project in Tiantuo Area, Nankai District, Tianjin, as an example by using questionnaire surveys, PLS-SEM and IPMA, and other multivariate statistical analysis methods to systematically explore the influence mechanism factors such as space accessibility, spatial usability, spatial maintainability, environmental comfort, and site safety on residents’ satisfaction. These findings reveal the following: (1) Space Accessibility has a significant direct positive impact on residents’ satisfaction. (2) Emotional Perception plays a complete mediating role in the relationship between Site Safety and residents’ satisfaction. (3) Emotional Perception has a complementary mediating effect in the relationship between Space Usability, Space Maintainability, Environmental Comfort, and Resident Satisfaction. (4) The renovation of old urban residential communities should give priority to improving space maintainability, especially focusing on the green landscape maintenance status, life-supporting infrastructure maintenance degree, and the maintenance status of entertainment and fitness facilities. Secondly, the space accessibility should be optimized and improved. In the future, in terms of the Physical Space, we should focus on the rationality of road network layout and strengthen the maintenance and management of public facilities. In terms of the Perceptional Space, the flatness of pavement should be optimized and the construction of security systems should be strengthened. In terms of the Psychological Status, a multi-party resident participation mechanism can be established to encourage residents to participate in the decision-making and construction of community public affair. As has been noted, this research quantitatively analyzed the key factors influencing residents’ satisfaction and their respective impact intensities and proposed prioritized and targeted optimization strategies for the existing situation. The research results are expected to provide a theoretical basis and practical decision-making reference for the optimization of public space environmental quality. Full article

Our study introduces a surface electromyography (sEMG)-based Cheonjiin speller system developed to assist individuals with restricted hand mobility. The interface incorporates a directional control framework—comprising up, down, left, right, and select commands—integrated with a Korean keyboard layout to enable efficient and accessible text input. Two-channel surface EMG signals were recorded from the rectus femoris and gastrocnemius muscles at a sampling rate of 200 Hz using an EMG acquisition module. The signals were processed in real time using notch and bandpass filtering, followed by full-wave rectification. To decode user intent, three physiologically interpretable time-domain features—root mean square (RMS), slope sign change (SSC), and peak amplitude—were extracted and subsequently used for classification. The Cheonjiin speller was implemented in Python 3.10.8 and operated through directional cursor navigation. System performance was quantitatively evaluated in two experiments: in Experiment 1, recognition accuracy for five discrete commands reached an average of 90.0%, while Experiment 2, involving continuous Korean word and sentence input, achieved an average accuracy of 88.65%. Across both experimental conditions, the system attained an average information transfer rate (ITR) of 96.19 bits/min, confirming efficient real-time communication capability. The results demonstrate that high recognition performance can be achieved using simple, low-computation features without deep learning models, confirming the feasibility of real-time implementation in resource-limited environments. Overall, the proposed speller system exhibits high operability, accessibility, and practical usability in constrained conditions and holds potential for integration into augmentative and alternative communication (AAC) systems for users with motor impairments. Moreover, its lightweight architecture, minimal computational load, and flexible directional control structure make it adaptable to a wide range of assistive and wearable technology applications. Full article

Background/Objectives: As the world becomes more connected, it is becoming critical for clinicians to understand other cultures, races, and ethnicities to provide the most effective therapy. A comprehensive understanding of all communities necessitates an examination of the social determinants of health (SDH). Eye diseases and many other conditions are influenced by SDH. To elucidate the impact of SDH on eye health, a comparative ecological analysis of Monroe and Erie Counties in New York State was conducted to identify any differences in SDH and glaucoma, age-related macular degeneration (AMD), and diabetic retinopathy prevalence. Methods: The CDC Vision and Eye Health Surveillance System (VEHSS) was utilized to collect glaucoma, AMD, and diabetic retinopathy data in Monroe and Erie Counties, New York State, and the USA for 2019. The American Community Survey, County Health Rankings, and Neighborhood Atlas data portals were used to collect the county socioeconomic demographics, along with other health statistics. Results: Overall, Erie County had a higher prevalence of AMD (9.56% vs. 6.61%, p < 0.0001) and glaucoma (13.05% vs. 11.71%, p < 0.0001) compared to Monroe County. Erie County also had a higher prevalence of AMD and glaucoma across all races, aside from North American Natives. Erie County also had a greater primary care shortage, with only 1 primary care physician for every 1230 individuals. Although income inequality and poverty were similar between Erie and Monroe Counties, Erie County also has more racial segregation regarding the residential layout (ranked 74 on a scale of 0 to 100, with 100 being the most segregated). Conclusions: The results indicate that Erie County had an increased prevalence of AMD and glaucoma compared to Monroe County in 2019, along with a greater primary care shortage. Although this analysis targeted Western New York, disparities such as lack of primary care access and segregation are prevalent across the US, necessitating widespread action to address these problems. Full article

The Unbroken Rehabilitation Center in Lviv illustrates how architectural design can support recovery in post-conflict conditions. Drawing on concepts of healing environments, evidence-based design, and trauma-informed architecture, this study aimed to identify architectural strategies that enhance physical and psychological rehabilitation in war-affected populations. A mixed-method approach was applied, combining field observations, architectural analysis, and user surveys triangulated with interviews and documentation review. Results show that decentralised layouts, daylight access, barrier-free circulation, and cross-laminated timber (CLT)-based vertical expansion contribute to therapeutic effectiveness. Survey data from 45 respondents confirmed very high ratings for accessibility (9–10/10) and strong appreciation of group therapy rooms (9.0), art therapy (8.8), and music therapy (8.7). These findings highlight the value of sensory and symbolic elements, including natural materials and culturally embedded art. While the exploratory character and uneven respondent distribution limit generalisability, the triangulated methodology enhanced reliability and revealed clear user trends. The study demonstrates that architectural design can actively support resilience and rehabilitation in war-affected contexts, offering transferable insights for future post-conflict reconstruction. Full article

Equitable accessibility to elderly canteens is critical for addressing the challenges of an aging population. Using Nanjing as a case study, this paper constructed an integrated framework that fuses GIS spatial analysis with interpretable machine learning to diagnose, evaluate, and optimize the service network’s spatial layout. The study found that the existing design is a direct manifestation of the conflict between “market logic” and “social demand.” First, Nanjing’s elderly canteen service suffers from a severe spatial mismatch and inequality of opportunity. Approximately 80% of the elderly population resides in areas that share less than 15% of the canteen resources. Second, a multi-modal accessibility analysis revealed the phenomenon of “false equity.” The high service coverage under the car accessibility model masks the systemic service deprivation faced by the majority of seniors who rely on walking and micromobility. Third, this study proposed and validated a data-driven “stock activation” strategy. An XGBoost model, guided by a “demand-oriented and spatially efficient” decision-making logic, identified 161 high-potential optimization sites. At the same time, the framework also diagnosed its own strategic boundaries by identifying “resource vacuums” where a lack of convertible stock necessitates alternative solutions, such as new builds. Full article

This study explores how outdoor environments in cold-region university campuses influence students’ physical and mental health, addressing the lack of research on health-oriented campus design under cold climatic conditions. Drawing on Evidence-Based Design (EBD) theory and the Socio-Ecological Model (SEM), a Multi-Factor Analysis (MFA) framework integrating theoretical analysis, data mining, and empirical validation was developed to reveal the mechanisms linking campus environmental factors and student health. Through a systematic literature review and Latent Dirichlet Allocation (LDA) topic modeling, six key factors—climate adaptability, architectural layout, infrastructure, natural landscape, safety, and transportation accessibility—were identified and further verified through questionnaire data (N = 480) for reliability and validity. The Delphi method was then used to refine the indicator system and determine factor weights, while case studies of representative cold-region universities proposed optimization strategies from the dimensions of built environment, climatic adaptation, and perceived environment. The findings enrich the application of socio-ecological theory in health-oriented campus research and provide scientific and practical guidance for planning and promoting healthy university environments in cold regions. Full article

Campus buildings often present hidden safety risks such as falls and wheelchair instabilities, which are closely related to architectural layout, material selection, and accessibility design. This study develops YOLOv11-Safe, an attention-enhanced and geometry-aware framework that functions as both a detection model and a spatial diagnostic tool for building safety assessment. The framework integrates a modified SimAM attention mechanism and a normalized Wasserstein distance (NWD) loss to improve detection accuracy in complex indoor environments, trained on a dataset of 1000 annotated images covering fall and wheelchair accident scenarios. To interpret spatial risk patterns, a Random Forest classifier combined with SHAP analysis was applied to quantify the contribution of five architectural–behavioral variables: body–ground contact ratio (BGCR), accessibility index (AI), event duration (D), body posture angle (PA), and spatial density (SD). Results show that BGCR and AI dominate the risk-level prediction, while D, PA, and SD refine boundary conditions. Scene-based verification further demonstrated that the framework accurately localized unsafe features—such as uneven drainage edges and discontinuous handrails—and translated them into actionable design feedback. The proposed approach thus links deep-learning detection with interpretable spatial analysis, offering a quantitative foundation for evidence-based architectural safety optimization in university campuses. Full article

As a key indicator for measuring urban green visibility, the Green View Index (GVI) reflects actual visible greenery from a human perspective, playing a vital role in assessing urban greening levels and optimizing green space layouts. Existing studies predominantly rely on single-source remote sensing image analysis or traditional statistical regression methods such as Ordinary Least Squares and Geographically Weighted Regression. These approaches struggle to capture spatial variations in human-perceived greenery at the street level and fail to identify the non-stationary effects of different drivers within localized areas. This study focuses on the Luolong District in the central urban area of Luoyang City, China. Utilizing Baidu Street View imagery and semantic segmentation technology, an automated GVI extraction model was developed to reveal its spatial differentiation characteristics. Spearman correlation analysis and Multiscale Geographically Weighted Regression were employed to identify the dominant drivers of GVI across four dimensions: landscape pattern, vegetation cover, built environment, and accessibility. Field surveys were conducted to validate the findings. The Multiscale Geographically Weighted Regression method allows different variables to have distinct spatial scales of influence in parameter estimation. This approach overcomes the limitations of traditional models in revealing spatial non-stationarity, thereby more accurately characterizing the spatial response mechanism of the Global Vulnerability Index (GVI). Results indicate the following: (1) The study area’s average GVI is 15.24%, reflecting a low overall level with significant spatial variation, exhibiting a “polar core” distribution pattern. (2) Fractal dimension, normalized vegetation index (NDVI), enclosure index, road density, population density, and green space accessibility positively influence GVI, while connectivity index, Euclidean nearest neighbor distance, building density, residential density, and water body accessibility negatively affect it. Among these, NDVI and enclosure index are the most critical factors. (3) Spatial influence scales vary significantly across factors. Euclidean nearest neighbor distance, building density, population density, green space accessibility, and water body accessibility exert global effects on GVI, while fractal dimension, connectivity index, normalized vegetation index, enclosure index, road density, and residential density demonstrate regional dependence. Field survey results confirm that the analytical conclusions align closely with actual greening conditions and socioeconomic characteristics. This study provides data support and decision-making references for green space planning and human habitat optimization in Luoyang City while also offering methodological insights for evaluating urban street green view index and researching ecological spatial equity. Full article