Search Results (350)

Traditional pedestrian routing algorithms typically minimize physical distance or travel time, often overlooking contextual factors that influence route choice in digitally connected environments. As public WiFi infrastructure becomes increasingly prevalent in smart-city districts and university campuses, digital connectivity may influence pedestrian mobility decisions. This study introduces P-WARP, a multi-factor routing and inference framework that reconstructs latent pedestrian preferences by integrating physical effort, environmental walkability, and WiFi connectivity within a unified semantic graph. The empirical analysis is conducted on the Chiang Mai University campus, a digitally connected environment serving as a smart campus testbed. The framework integrates heterogeneous spatial datasets, including OpenStreetMap topology, Shuttle Radar Topography Mission elevation data, environmental walkability grids, and WiFi roaming logs collected via a custom mobile sensing application from 21 volunteers across 71 verified walking trips. Two routing strategies are evaluated: a Global Static Model, representing infrastructure-based connectivity assumptions, and a Trip-Centric Dynamic Model, incorporating realized connectivity histories. Model parameters are calibrated using Bayesian Optimization with five-fold cross-validation. Results show that incorporating realized connectivity reduces trajectory reconstruction error by 6.84% relative to the baseline. The learned parameters reveal a notable detour tolerance, suggesting that stable digital connectivity can influence pedestrian route choice in digitally instrumented environments. Full article

This paper proposes a novel method for measuring music similarity. Existing music similarity measurements have often been used for music appreciation, but this paper proposes a method for measuring the similarity between music samples which are used for music production. Conventional music recommendation approaches often rely on either metadata-based similarity or audio-based feature similarity in isolation, which limits their effectiveness in sample-based recommendation scenarios where both compositional context and acoustic characteristics are important. To address this limitation, the proposed framework combines a hypergraph-based information similarity module with a feature-based similarity module learned using Siamese networks and triplet loss. In the information-based module, metadata attributes such as beats per minute (BPM), genre, chord, key, and instrument are modeled as vertices in a hypergraph, and Random Walk–Word2Vec embeddings are learned to capture structural relationships between music samples and their attributes. In parallel, the feature-based module employs vertex-specific Siamese networks trained on instrument and key classification tasks to learn perceptual similarity directly from audio signals. The two modules are trained independently and jointly utilized at the recommendation stage to provide attribute-specific similarity results for a given query sample. Results show that the proposed system achieves high Precision@k across multiple attributes and forms stable similarity structures in the embedding space, even without relying on user interaction data. These results reflect embedding consistency evaluated over the entire dataset where training and retrieval are performed on the same sample pool, rather than generalization to unseen samples. These results demonstrate that the proposed hybrid framework effectively captures both structural and perceptual similarity among music samples and is well suited for sample-based music recommendation in music production environments. Full article

Accurate forecasting of equity returns remains fundamentally constrained by weak short-horizon predictability, pronounced noise, and structural non-stationarity. While deep learning models have been widely applied to financial time series, most studies prioritize point prediction and provide limited guidance on reliable uncertainty quantification, particularly in emerging markets. This study developed an uncertainty-aware forecasting framework for the South African equity market by integrating variational mode decomposition (VMD), gated recurrent units (GRUs), and temporal conformal prediction (TCP) to construct distribution-free prediction intervals with finite-sample coverage guarantees. Using daily returns from the FTSE/JSE All Share Index, we first confirmed that baseline recurrent models applied directly to raw returns exhibited negligible out-of-sample explanatory power, consistent with weak-form market efficiency. Incorporating VMD enhanced representation learning and improved point forecast accuracy by isolating latent frequency components. However, model-based predictive variance alone proved insufficient for reliable calibration. Embedding the models within a rolling conformal prediction framework restored near-nominal coverage across multiple confidence levels while allowing interval widths to adapt dynamically to changing volatility regimes. Robustness analyses, including walk-forward validation, stress-regime evaluation, and block permutation negative control experiments, indicated that the observed performance was not driven by temporal leakage or alignment artifacts. The results further highlight a trade-off between interval sharpness and tail-risk protection, particularly during extreme market events. Overall, the findings support a shift from return-level prediction toward calibrated uncertainty estimation as a more stable and economically meaningful objective in non-stationary financial environments. Full article

The Green Oasis (GRO) Project is a targeted urban greening intervention designed to evaluate the environmental and health impacts of compact, high-density plantings in dense built environments. Initiated in downtown Louisville, the project transformed Founders Square, a 0.64-acre sparsely planted park, into a microforest (“Trager Microforest”), a multilayered planting of 119 trees and more than 200 shrubs. The impact of this intervention is being assessed through a randomized crossover study in which participants walk in the microforest and a nearby impervious parking lot. Physiological outcomes include heart rate, heart rate variability, arterial stiffness, and stress biomarkers measured in saliva, urine, and sweat. Environmental conditions are continuously monitored by fixed and mobile weather stations, air pollution sensors, and biodiversity surveys. Baseline assessments were conducted in 2023 and 2024, with post-planting evaluations now underway (2025–). Power calculations indicate adequate sensitivity (n ≈ 40–50) to detect changes in cardiovascular stress responses in participants. Complementary ecological measurements include soil microbiome composition, greenhouse gas fluxes, and avian diversity. This study addresses critical gaps in understanding how small-scale, high-density greening interventions affect cardiovascular resilience, stress physiology, and microclimatic regulation. By integrating environmental, biological, and human health data, GRO establishes a comprehensive framework for evaluating the efficacy of urban microforests as nature-based solutions. The results are expected to inform urban planning, public health strategies, and climate adaptation policies, demonstrating how compact greening interventions can simultaneously mitigate heat, reduce pollution, enhance biodiversity, and promote human wellbeing in dense urban cores. Full article

Against the backdrop of accelerating urbanization and population aging, urban parks have emerged as significant venues for enhancing the physical and mental well-being of older adults. The age-friendly quality of these spaces is directly linked to health equity and urban inclusiveness. Using the high-density historic district of Beilin in Xi’an as a case study, we developed an innovative assessment tool to evaluate the age-friendliness of park walking environments. Guided by the Health Impact Assessment (HIA) framework, this tool integrates subjective perceptions and objective data to diagnose environmental strengths and weaknesses across four dimensions: accessibility, safety, comfort, and health-related interactivity. Based on multi-source data and quantitative analysis, the study revealed key variations in the age-friendly attributes of different parks. Our field assessment focused on three representative park types: urban comprehensive, historic–cultural, and community leisure parks. The key findings are: (1) Safety was perceived by experts as the most critical dimension for older adults’ health experience, with a weight of 0.49, accounting for nearly half of the total. However, significant variations exist in safety quality across different types of parks. (2) Age-friendly performance differed profoundly among park types. Benefiting from systematic management, the urban comprehensive park achieved balanced performance and a total score of 84.87. In contrast, the historic–cultural park, constrained by its linear morphology and historical functions, scored the lowest at 66.03, exhibiting notable deficits in safety and comfort. The community leisure park, while vibrant in community activity, attained an intermediate score of 74.76 due to insufficient attention to safety details. (3) The assessment outcomes highlight the association of park typology, site selection, and design sophistication with the lived experience and potential health benefits for older adults. This study provides a refined evaluation tool and tailored optimization strategies for the age-friendly renovation of diverse park types. Full article

Wearable systems based on inertial measurement units (IMUs) have attracted considerable interest in recent years in the field of gait analysis. However, most gait studies using such devices have been conducted in laboratory rather than clinical settings. This study evaluated a commercially available IMU-based insole system in two cohorts: a clinical group (59 ± 18, years) recruited from podiatry clinics and a non-clinical group (28 ± 7, years) recruited from a university with no reported complaints. Participants wore the IMU-based device and performed treadmill walking (clinical group) and overground walking (non-clinical group). Spatiotemporal parameters were compared between groups using statistical analyses included the Shapiro–Wilk test, Mann–Whitney test, and Welch’s t-tests for non-bilateral data, and a two-factor linear mixed-effects model estimated by restricted maximum likelihood (REML) for bilateral spatiotemporal parameters to evaluate group, foot-side, and interaction effects. Ten of the twenty-two spatiotemporal parameters showed significant group differences, with statistical significance observed in at least one foot for parameters measured bilaterally. The observed differences may reflect a combination of clinical characteristics, age-related effects, and walking environment influences. Findings are discussed in relation to potential biomechanical mechanisms, factors influencing results and the clinical utility of IMU systems. Future research should investigate specific foot conditions under standardized walking conditions with age-matched cohorts. Full article

Integrating health-oriented physical activity into community-scale walking environments is a key strategy for promoting healthy aging within sustainable urban development. However, community walking environments are often planned and managed without systematic evaluation frameworks to determine whether daily walking conditions effectively support health-oriented physical activity. To address this gap, this study proposes a planning-oriented health effectiveness assessment framework that translates exercise prescription principles into spatial, functional, and managerial performance indicators. Based on the Frequency, Intensity, Time, Type, Volume, and Progression (FITT-VP) exercise prescription framework, a multi-method approach was adopted. Evaluation indicators were identified through a structured literature review and refined using the Delphi method. User perception differences were incorporated using the Kano model, and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) was applied to quantitatively evaluate and rank the health effectiveness of community walking environments. The framework was empirically tested through a case study of Binshui communities in the Jimei District of Xiamen, China. The outcomes imply that priority indicators include progression route planning integrity, interval training feasibility, multifunctional training area match, monthly maintenance frequency, nighttime illumination uniformity. Community walking environments can function as effective everyday planning instruments for promoting physical activity among aging populations when exercise science principles are systematically embedded into urban design and management. By operationalizing exercise prescription principles as planning performance criteria, this study advances sustainable urban planning research and provides an evidence-based assessment tool for age-friendly neighborhood regeneration and community health governance. Full article

Evaluating pedestrian comfort in high-density cities requires methods integrating subjective experience with urban morphology. This study develops an integrated framework combining pairwise comparison scoring, semantic segmentation (DeepLabv3+), ensemble learning (Random Forest), and SHAP-based interpretability. EfficientNet-B7 is used to expand pairwise datasets and derive continuous comfort scores across Macau’s street network. Four experiential street types are identified: historical–cultural districts, urban lifestyle areas, natural corridors, and leisure zones. SHAP analysis illustrates stable associations between predicted comfort scores and multi-layered spatial configurations, including cultural legibility and sequencing in historic cores, moderate greenery with functional anchoring in residential areas, and scene coherence in tourism zones. Semantic features serve as effective morphological proxies within the modeling framework. Methodologically, the framework demonstrates how explainable machine learning can be applied to dense Asian cities under observational conditions. Design implications emphasize interface continuity, microclimate adaptation, and functional enrichment, suggesting that pedestrian comfort is closely related to coherent spatial–experiential structures rather than isolated environmental upgrades. Full article

Two major global trends shaping 21st-century society are population aging and urbanization. Consequently, the living conditions of older adults have become an increasing focus of societal attention. Social–Emotional Responses play a crucial role in the mental health, emotional well-being, and social identity of older adults. Urban streets, as key sites for walking and social activity among older adults, can be seen as extensions of their homes—places where they regularly interact with neighbors and build new connections. Compared to built environments often termed “gray spaces,” exposure to green spaces has been shown to offer greater benefits to residents’ well-being. Among streetscape features, the Spatial Openness Level is closely associated with the psychological well-being of elderly individuals. Visual-spatial features correlate with an EEG-derived proxy for emotional state during exposure to street scenes. The Gray-Green space Exposure Ratio (GER) and Spatial Openness Level (SOL) serve as key indicators for evaluating streetscape quality. Designing age-friendly streets requires evidence-based tools that link visual features to emotional well-being. This study provides such a tool by combining EEG measurements with configurational analysis of street visual dimensions: SOL and GER. In this study, conducted in Wuhan City, objective physiological monitoring of brainwave activity was employed to examine the responses of older adults to variations in GER and SOL. The results indicate that SOL significantly influences the emotional states of older adults (correlation coefficient R² = 0.7262, p < 0.01). The results indicate that the effect of GER on the emotional states of older adults was moderated by gender. Specifically, GER exerted a significant effect on the emotional states of females (correlation coefficient R² = 0.6262, p < 0.01), whereas no significant effect was observed in males (p > 0.01). These results allow us to rank the nine tested scenes. For example, Scene L-3 (open space with abundant vegetation) scored highest on emotional well-being, while Scene H-1 (enclosed gray space) scored lowest. The difference is explained by the configurational logic: greenery delivers emotional benefits only when combined with sufficient openness. The findings will enable EEG data to extend beyond serving as a unique standalone outcome and integrate into a more comprehensive explanatory model. This model aims to elucidate how urban morphology influences the micro-foundations of social activity in later life. Furthermore, it seeks to equip urban designers and policymakers with an evidence-based tool for creating age-friendly environments, facilitating a shift from intuition-driven to evidence-based design. Future research should incorporate additional environmental factors to establish a more comprehensive assessment framework for age-friendly urban spaces. Full article

Background/Objectives: Stroke frequently leads to balance deficits. Vestibular physical therapy (VPT) may enhance postural control through neuroplastic mechanisms. Virtual reality (VR) can provide ecologically valid environments for rehabilitation, increasing patient engagement. Methods: In this randomized feasibility study, nine individuals with chronic stroke were randomized to either a Real visuo–vestibular rehabilitation group (n = 6) or a Sham VR group (n = 3) to explore the feasibility of the protocol and randomization procedures rather than to compare clinical efficacy. Both groups were trained in immersive VR environments for 12 sessions. The Real group experienced visuo–vestibular stimuli requiring sensorimotor integration; the Sham group trained in the same environments without such stimuli. Feasibility was assessed through attendance, participation (Pittsburgh Rehabilitation Participation Scale, PRPS), and user satisfaction (USEQ). Safety and acceptability were monitored through adverse event reporting. Secondary exploratory outcomes included measures of balance—the Mini Balance Evaluation Systems Test (MiniBESTest), the Berg Balance Scale (BBS), and the Performance-Oriented Mobility Assessment (POMA)—as well as functional independence (Barthel Index), health-related quality of life (Stroke-Specific Quality of Life Scale, SSQoL), and a set of spatiotemporal and gait quality parameters derived from inertial measurement unit (IMU) data collected during the 10-Meter Walk Test and the Figure of 8 Walk Test. Results: All participants completed the protocol without adverse events. Participation, as measured by the PRPS, remained consistently high across sessions (mean ≥5.7/6), while USEQ scores indicated excellent user satisfaction (mean ≥28/30). Exploratory analyses revealed improvements in MiniBESTest and BBS scores for the Real group. Instrumental measures derived from IMUs demonstrated improvements across groups. Conclusions: Exploratory outcomes suggested positive trends in balance improvements, and the integration of clinical scales with wearable sensors proved feasible and informative. Full article

Background and aim: Traditional marker-based optical motion capture systems are costly, time-consuming to operate, and constrained by laboratory environments, limiting their broader adoption in clinical practice and naturalistic settings. Markerless motion capture based on a sums-of-Gaussians (SoG) body model is a potential alternative; however, its metrological properties for kinematic assessment during walking and slow running remain insufficiently validated. Using a conventional marker-based Vicon system as the reference, this study evaluated the reliability and concurrent validity of an SoG-based markerless system (MocapGS) for bilateral lower-limb joint range of motion (ROM) during gait. Methods: Thirty-six healthy adults completed self-selected-pace speed walking and slow running tasks while both systems synchronously acquired bilateral lower-limb kinematics. The intraclass correlation coefficient (ICC), standard error of measurement (SEM), SEM percentage (SEM%), minimal detectable change (MDC), MDC percentage (MDC%), and root mean square error (RMSE) were used to assess reliability. Concurrent validity was evaluated using the Pearson correlation coefficient, paired-sample t-tests, and the concordance correlation coefficient (CCC) to compare the ROM. Results: Vicon showed moderate-to-high reliability for ROM in most joints across both tasks. By contrast, the MocapGS achieved acceptable ICC values mainly for the sagittal-plane ROM at the hip and knee. The CCC analysis showed no significant agreement between the two systems. Bland–Altman plots showed systematic biases with spatially heterogeneous random errors. During walking, MocapGS systematically overestimated ROM relative to Vicon at several joint axes; the widest limits of agreement (LOA) occurred at the left knee X-axis and right hip Z-axis. During running, overestimation was consistent across all bilateral joints at the X-axis and the right hip at the Y-axis, while the widest LOA were found at the bilateral hip X-axes. These specific discrepancies highlighted the joint–axis combinations with the greatest measurement variance. In walking, the test–retest reliability of the knee flexion–extension ROM measured by the MocapGS approached that of Vicon; however, the SEM% and MDC% were generally larger for MocapGS than for Vicon. The RMSE exceeded 5 degrees for ROM in most joint planes, especially in the frontal and transverse planes and at distal joints; errors increased further during slow running. Conclusions: MocapGS may be used for coarse monitoring of large-magnitude changes in sagittal-plane kinematics during gait; however, it is currently unlikely to replace Vicon for clinical decision-making or detecting subtle gait changes, and its outputs should be interpreted with caution, particularly for ankle kinematics and non-sagittal-plane motion. Full article

Background: Research on vibrations induced by running has gained significant attention due to its implications for athletes’ performance, injury prevention, and overall well-being. Distance running exposes the body to repetitive impulsive forces, causing significant vibrations to travel through physiological systems and biomechanical structures. These vibrations increase fatigue and the risk of injury. Although it has gained importance, research on induced vibration during running and wearable equipment for monitoring is scarce. This study aims to evaluate the performance of a measurement system for monitoring the acceleration levels of induced vibrations during long-distance running, exploring the capability of non-invasive wearable devices to characterise vibration transmissibility and exposure. Moreover, a preliminary quantitative assessment of induced vibration levels for an indoor testing scenario is given. Methods: Metrological characterisation of Xsens Motion Trackers Awinda (MTw), off-the-shelf inertial magnetic motion trackers, was performed by measuring the sensors’ frequency bandwidth in a controlled environment, providing logarithmic sweep sine excitations at different levels (2 g, 5 g, 7 g, where g is meant to be the gravitational acceleration). A testing protocol for indoor testing was derived from the literature, allowing characterisation of the sensors’ behaviour in terms of vibration transmissibility and exposure detection in the intended application. Time domain and frequency domain analyses were conducted by following the ISO 2631 standard guideline for vibration exposure assessment, and measurement uncertainty was defined, either for the dynamic correction of the sensors’ frequency behaviour or for the computed time and frequency domain metrics. In this framework, a treadmill-based test was conducted. The aim was to evaluate the Xsens sensors’ performance in measuring vibration dose exposure and transmissibility. Three MTws were placed on the subject’s right tibia, back, and forehead using elastic bands. A 25-year-old female amateur runner completed a series of tests consisting of walking for 1 min at 3.5 km/h (instrumentation setup), followed by running at two speeds (8 km/h and 11 km/h) for 2–4 min per trial, with 5 min rest periods between tests. Conclusions: The tested measurement system showed promising results due to its capability to assess vibration exposure during sports activities, but dynamic correction was found to be mandatory for accurate vibration level assessment. The main outcome of this study is a method for characterising the accelerometers embedded in the proposed devices, along with an analysis strategy for future testing campaigns. Thanks to the portability of IMUs (inertial measurement units), this approach enables the evaluation of induced vibrations during in-field running measurements. Full article

Introduction: Exercise has proven to be an excellent tool for improving health in individuals with hypertension. A particularly interesting environment for performing exercise is the aquatic medium, whose unique properties have shown effectiveness in reducing blood pressure values. Objective: Our objective was to provide an update on the available scientific evidence regarding the effects of aquatic exercise on individuals with hypertension. Methods: A systematic search was conducted in the databases PubMed, Web of Science, CINAHL, Sport Discus, Medline, Scopus, and PEDro. Methodological quality was assessed using the PEDro scale, and the risk of bias was evaluated using the RoB 2 tool. Results: Eleven studies were included, with a total of 402 participants, obtaining a mean score of 5.7 on the PEDro scale. Five studies presented a high risk of bias, four showed a low risk, and in two, the risk was unclear. The most used therapeutic exercises in the analyzed interventions were water walking, aquatic mobility and strength exercises, aquatic high-intensity interval training, and aquatic calisthenics. Notably, none of the interventions included swimming. Conclusions: Aquatic exercise appears to be associated with reductions in blood pressure in individuals with hypertension; however, these findings should be interpreted cautiously due to the methodological limitations and heterogeneity of the included studies. Full article

This paper investigates an algorithmic redesign tailored to cost minimization with degradation awareness EV charging under an uncertainty framework for coordinated grid-to-vehicle (G2V) and vehicle-to-grid (V2G) scheduling. An improved variant of the Polar Lights Optimizer (IPLO) is developed through the integration of Random Walk Exploitation (RWE) to enhance local refinement and Periodic Random Parameter Tuning (PRPT) to improve adaptability under uncertainty. In addition, an adaptive control mechanism is incorporated to adjust charging and discharging actions based on battery capacity degradation and dynamic electricity price signals. The presented framework is evaluated through simulation-based case studies and compared with several recent metaheuristic algorithms. The results demonstrate cost reductions of up to 25.42% over the original PLO and 80.78% relative to a non-optimized baseline, faster convergence, and improved robustness to price uncertainty, while mitigating adverse battery degradation effects. A statistical analysis over multiple independent runs confirms the reliability and consistency of the presented approach, highlighting its suitability for smart EV charging optimization in dynamic operating environments. Full article

Inequity in urban walking resources has been garnering increasing scholarly attention. However, there is still no widely accepted tool for assessing walkability, making results difficult to compare across studies. In addition, the ways in which walkability equity is typically defined and measured often overlook China’s local context. Therefore, this study develops a comprehensive walkability evaluation framework for Kunming’s main urban area using open-source data and census information, synthesizing 15 indicators across five dimensions (connectivity, accessibility, suitability, sociability, and aesthetics) analyzed through the Catastrophe Theory models (CT models). Furthermore, spatial autocorrelation, the Concentration Index (CI), and an interpretable machine learning framework (Random Forest-SHAP) are employed to examine the relationships between community walkability disparities and socio-economic factors for a spatial justice assessment. The results show the following: (1) Community walkability in the main urban area of Kunming exhibits a “core–periphery” spatial distribution pattern, where connectivity, accessibility, and sociability follow the general pattern, while suitability and aesthetics display heterogeneous spatial distributions. (2) The social differentiation characteristics of community walkability in Kunming’s main urban area correlate significantly with age structure, hukou registration, and social status, but show limited association with ethnicity and economic status. These findings challenge Western-centric social differentiation paradigms and underscore the context-specific nature of walkability equity in China, thus providing new perspectives for the understanding of built environment justice in the context of Chinese cities. Full article