Search Results (180)

Aquatic recreation significantly enhances well-being; however, individuals experiencing functional limitations remain frequently marginalized from this form of tourism due to infrastructural and environmental barriers. This study investigates the perceived operational risks and apprehensions encountered by users with specific accessibility needs during yacht sailing, aiming to inform inclusive vessel design aligned with the social dimension of sustainable development. A survey of 277 participants with diverse, officially certified functional limitations was conducted to evaluate their maritime experiences and safety concerns. Participants identified a mean of 11 pre-voyage apprehensions out of 19 distinct risk categories. The most prevalent concerns included stumbling, slipping, or falling on board (79%), the risk of falling overboard (73%), and seasickness (70%), with an overall moderate severity ($\overline{X}$ = 2.2 on a 4-point scale). Crucially, severe safety concerns (e.g., vessel sinking or falling overboard) were significantly mitigated following practical sailing experience. Conversely, everyday functional and ergonomic challenges—such as moving between the deck and crew quarters ($\overline{X}$ = 2.6), operating rigging ($\overline{X}$ = 2.7), embarkation ($\overline{X}$ = 2.6), and utilizing sanitary facilities ($\overline{X}$ = 2.1)—persisted irrespective of experience level. Statistical analysis revealed that gender and age had negligible effects on concern levels. Extensive maritime experience reduced apprehensions regarding balance and swimming competencies, while concurrently increasing awareness of communication and comfort-related operational challenges. This study highlights a distinct divergence between initial psychological anxiety—which is largely mitigated by experience—and persistent architectural barriers inherent in standard yacht design. The results underscore that achieving meaningful inclusivity in water tourism requires prioritizing interior spatial layouts, accessible sanitary facilities, and barrier-free vertical circulation in naval architecture, rather than focusing exclusively on emergency safety systems. These insights directly support the advancement of Sustainable Development Goal 10 and the integration of universal and human-centered design principles within the maritime recreation sector. Full article

Traditional evaluation indicators, including average air temperature, flow field distribution, and breathing-zone temperature, fail to fully characterize the actual effect of solar radiation on passenger thermal comfort. Therefore, based on the Fiala human physiological thermoregulation model and the Berkeley–Zhang thermal comfort evaluation criterion, this study develops a coupled simulation method for the objective evaluation of passenger thermal comfort. On this basis, the influence of front windshield solar radiation transmittance on passenger thermal comfort is preliminarily investigated. The results reveal that when the glass transmittance decreases from 0.52 to 0.37, the steady-state average cabin air temperature declines by approximately 0.5 °C, and the overall thermal comfort value increases from 0.67 to 1.2. In addition, the left crus receives the maximum solar radiation intensity, resulting in the poorest local thermal comfort. This verifies the feasibility and effectiveness of the method and provides a basis for the thermal comfort research of the vehicle cabin. Full article

Flexible pressure sensors with a porous architecture are highly desirable for wearable health monitoring and intelligent human–machine interaction, owing to their excellent comfort and conformability to human motion. However, conventional porous sensors often suffer from poor signal accuracy and unstable output, which limit their capability for precision sensing. To address these challenges, we designed and fabricated a flexible pressure sensor with exceptional linearity by mimicking the unique surface structure of Iron Cross Begonia (Begonia masoniana) leaves. The sensor is constructed using a readily available melamine foam as the backbone: a porous sensing scaffold is first obtained via a simple dip-coating process, and a film featuring bioinspired protrusions is fabricated by repeated replica molding. Lamination of these two components yields a stacked sensor device. Characterization demonstrates that the sensor achieves a broad pressure detection range of up to 350 kPa, with a minimum resolvable pressure of 250 Pa, and exhibits an excellent linearity of 0.999 over its entire working range (0–350 kPa). Moreover, the sensor shows stable responses under varying loading frequencies, is capable of detecting low-frequency signals, and retains its performance without notable degradation even after 5000 repeated loading-unloading cycles. In practical applications, the sensor accurately monitors flexion and extension movements of the wrist, finger, neck, and knee, capturing human motion signals with high fidelity. Furthermore, it enables information encoding and transmission through finger gestures. The proposed bioinspired structural design strategy effectively enhances the overall performance of porous pressure sensors, offering a new paradigm for the development of flexible sensing devices with promising applications in wearable health monitoring, human motion detection, and human–machine interaction. Full article

Indoor lighting systems are a significant contributor to building energy consumption while also directly affecting occupant comfort and circadian regulation. Recent advances in smart lighting have introduced adaptive and human-centric approaches; however, the integration of optimization-oriented control strategies with interoperable automation frameworks remains only partially articulated in the literature. This study presents a systematic bibliometric review of smart indoor lighting research, with particular attention to the roles of hyper-heuristics (HH), Internet of Things (IoT) platforms, and IFTTT/Event–Condition–Action (ECA) automation. A PRISMA-based methodology was applied across Scopus, Web of Science, and IEEE Xplore for the period 2010–2025. A total of 5529 records were identified, with 5229 screened after duplicate removal, and 27 core studies included following eligibility assessment. To reduce the risk of over-interpreting null intersections, the review also incorporated a search-sensitivity analysis based on expanded query formulations and title–abstract screening. Bibliometric analysis was conducted using MATLAB and VOSviewer to identify publication trends, technological clusters, and patterns of fragmentation across the literature. The results indicate rapid growth in IoT-based and energy-aware lighting systems, alongside mature research in circadian and comfort-driven lighting. However, explicit indexed evidence connecting hyper-heuristics with IoT platforms and IFTTT/ECA frameworks remains sparse and fragmented in the available literature. Co-occurrence analysis further reveals weak metadata-level connections between optimization techniques and IoT protocols, while the sensitivity analysis confirms that broadened retrieval improves recall but still yields only limited directly relevant evidence. Overall, the review identifies a gap in the explicit convergence of optimization, interoperable IoT infrastructure, and event-driven automation for human-centric indoor lighting. On this basis, it outlines a conceptual integration framework combining hyper-heuristics, IoT middleware, and event-driven control. The findings provide a structured roadmap for future research and implementation-oriented studies aimed at improving both energy efficiency and human-centric comfort in smart indoor environments. Full article

Indoor environmental quality (IEQ) is increasingly recognized as a critical factor in shaping employee well-being, satisfaction, and work performance, particularly in hybrid workplace settings. This mixed-methods study examined how integrated IEQ conditions influence employee experience in a public-sector hybrid workplace through a case study of the WorkHub, a technology-enabled flexible workspace embedded within a large municipal utility. Quantitative data were collected from 93 valid survey responses using the Workplace Environment Satisfaction and Performance Questionnaire (WESP-Q™), and qualitative insights were obtained from a 90-min participatory think tank session with 24 employees. Results showed that WorkHub users reported significantly higher satisfaction across 15 of 18 environmental and spatial dimensions, including layout, thermal comfort, air quality, lighting, furnishings, cleanliness, and overall building experience. They also reported significantly stronger outcomes in collaboration access, work transition, focus support, work efficiency, workspace productivity, pride in work, and job satisfaction. Qualitative findings reinforced these results, highlighting technology integration, daylight, and spatial flexibility as key strengths, while identifying acoustics, thermal discomfort, and limited privacy as persistent challenges. These findings support a systems-oriented, human-centered approach to workplace design, demonstrating that integrated IEQ can enhance employee experience, collaboration, and organizational performance in hybrid public-sector environments. Full article

This study evaluated whether membrane structures can enhance thermal comfort and reduce heat- and cold-related health risks in privately owned public spaces (POPS) under representative seasonal peak conditions. Based on previous in situ measurements revealing severe summer heat stress and winter cold discomfort in two POPS in Tokyo’s Minato-ku Shibaura district, a membrane-based shelter solution is proposed and systematically assessed. Their thermal environmental effects were numerically simulated using a coupled surface energy balance (SEB) and computational fluid dynamics (CFD) model, with evaluations focusing on human health risks and thermal comfort. Results demonstrated that in summer, membrane structures effectively improved thermal comfort by reducing the standard effective temperature (SET*) by 1.9–3.9 °C, although these SET* values still remained above the thermal comfort range. Notably, heat stress-related health risks were significantly mitigated, as deep body temperature (DBT) decreased by 1.2–1.6 °C, falling below the 38 °C heatstroke risk threshold. In winter, although the overall improvement was limited, the membrane structures still reduced cold-related health risks and extended allowable exposure duration (AED). Furthermore, auxiliary measures (e.g., mist sprays for summer and supplementary heating for winter) are recommended to further enhance thermal comfort in POPS. Full article

Indoor environmental quality (IEQ) significantly impacts people’s comfort, health, and productivity in buildings, and modern green rating systems are primarily focused on energy efficiency rather than the direct user experience. This paper analyses the relationship between IEQ and the perceived quality of life (QoL) of certified and conventional office buildings in Malaysia using a mixed-methods design. The questionnaires were completed by 162 employees working in four open-plan offices: two were certified under the Green Building Index (GBI) established in Malaysia, and two were traditional. This was supplemented by 14 semi-structured interviews and 2 focus groups. The factors of IEQ were divided into ambient, designed, and behavioral environments. It was statistically determined that behavioral factors, such as visual privacy, personalization, ergonomics, and control, exhibited the strongest correlations with overall QoL, compared to ambient factors such as air quality or thermal comfort. Green buildings performed better in terms of daylighting and esthetics than conventional buildings, though they did not always deliver higher occupant satisfaction. The results indicate that current green certification frameworks pay insufficient attention to occupant-centered aspects. The proposed research adds a validated IEQ-QoL framework that predicts the incorporation of subjective user experience into building performance indicators, which can be important for certification reform, post-occupancy evaluation (POE), and human-centered sustainable design approaches. Full article

Ride comfort is a critical issue in vehicle dynamics, as excessive vibrations adversely affect passenger comfort and human health. This paper presents a comparative performance analysis of a passive suspension system, fuzzy logic control (FLC), and a newly designed adaptive robust control (ARC) strategy applied to a nonlinear quarter-car suspension–seat–driver model. The primary objective is to improve ride comfort while maintaining vibration levels within accepted health criteria. First, the nonlinear dynamic model of the suspension–seat–driver system is established. The FLC structure and rule base are determined based on heuristic knowledge. Passive and FLC-based systems, while effective to some extent, suffer from limited adaptability to external disturbances and modeling uncertainties, slower convergence, and suboptimal vibration attenuation. The main contribution of this study is the design and implementation of a novel adaptive robust controller that effectively handles modeling uncertainties, external disturbances, and parameter variations. Different controller placement approaches within the system are also investigated. Numerical simulations are conducted under identical operating conditions for the uncontrolled system and all control strategies. The results demonstrate that although the FLC improves ride comfort compared to the passive system, the proposed ARC achieves the best overall performance, providing superior vibration attenuation, faster convergence, and enhanced robustness for nonlinear vehicle suspension systems. Quantitatively, the ARC reduces head acceleration RMS from 0.1693 m/s² (passive) and 0.1422 m/s² (FLC) to 0.0705 m/s², and upper torso RMS from 0.1689 m/s² (passive) and 0.1417 m/s² (FLC) to 0.0703 m/s², corresponding to approximately 58% reduction relative to passive and 50% improvement over FLC. Full article

Heatwaves are among the most significant climate extremes affecting Egypt, with direct impacts on human health, energy demand, water resources, and overall thermal comfort. Although several previous studies have examined heatwave characteristics in Egypt, most have relied on station-based or localized analyses, limiting the understanding of national-scale patterns and recurrence behavior. To address this gap, this study provides a comprehensive national-scale assessment of the spatiotemporal characteristics of heatwave occurrences across Egypt from 1990 to 2023 using daily maximum and minimum temperatures derived from the ERA5 reanalysis dataset. Daytime and nighttime heatwaves were defined using the 90th percentile temperature thresholds and a minimum duration of three consecutive days. This made it possible to study their frequency, duration, severity, seasonal distribution, and how often they happened again. The results demonstrate that heatwaves happen more often and with more severity in late July and August. This is especially true for nighttime heatwaves. These findings indicate that daily baseline temperatures in Egypt have been rising steadily since 2010. Nighttime heatwaves show a notable increase in frequency and persistence, indicating a sustained rise in baseline temperatures and reduced nocturnal cooling. By providing the first long-term, spatially consistent national-scale heatwave assessment over Egypt, this study contributes to a more comprehensive understanding of extreme temperature behavior under ongoing climate change. Full article

In intermittent convective cooling environments created by split air conditioners, the dynamic nature of the environment poses challenges to traditional steady-state thermal comfort models in predicting human thermal comfort. Therefore, this study proposes an alliesthesia-informed machine learning framework that encodes alliesthesia theory into explicit mathematical features for predicting dynamic overall thermal comfort. Data were obtained through controlled experiments under intermittent cooling conditions, and a theory-driven feature set incorporating dynamic set points and physio-psycho gap was constructed. The results demonstrate that the gradient boosting model achieved optimal performance under rigorous subject-level cross-validation (test set R² = 0.71). Interpretability analysis confirmed that model decisions are highly dependent on exposure time and alliesthesia features, whose importance far exceeds that of conventional environmental parameters, revealing that the core of thermal comfort perception lies in the dynamic interplay between physiological states and psychological expectations. Furthermore, the proposed few-shot personalized calibration strategy can effectively accommodate individual differences with minimal user data. This study demonstrates that the framework not only enhances prediction accuracy but also improves model interpretability and generalizability by incorporating alliesthesia-inspired feature representations, offering a new perspective for developing next-generation human-centric intelligent environmental control systems. Full article

To address the critical need for accurate human thermal comfort prediction in winter heating environments, this study established a comprehensive thermal comfort dataset containing 2089 valid samples through experiments. On this basis, thermal comfort prediction models were constructed using three multi-class machine learning algorithms: Support Vector Classification, K-Nearest Neighbors, and Random Forest. The predictive performance of 63 different feature combinations was systematically evaluated. The results indicate that the feature subset comprising indoor air temperature, forehead temperature, cheek temperature, dorsal hand temperature, heart rate, and systolic blood pressure yields the optimal prediction performance. Among the evaluated models, the Random Forest model demonstrated superior overall performance, achieving an accuracy exceeding 90% and an AUC ranging from 96% to 99%, significantly outperforming the SVC and KNN models. Compared with the traditional Predicted Mean Vote (PMV) model, the machine learning models developed in this study showed a substantial improvement in prediction accuracy under identical conditions; notably, the Random Forest model improved accuracy by approximately 40% over the PMV model. Based on these findings, a smart heating system framework integrating environmental sensors, wearable devices, and intelligent control valves is proposed, providing a theoretical basis and technical approach for realizing personalized and energy-efficient heating control. Full article

Aim: This systematic review compared erbium lasers (Er:YAG/Er,Cr:YSGG) with conventional rotary instruments (dental turbine/high-speed handpiece) for caries removal and cavity preparation in pediatric dentistry, focusing on patient-centered outcomes and short-term restorative performance. Methods: Following PRISMA guidance, PubMed, Scopus, and Web of Science were searched for studies published between January 2010 and November 2025. Eligible studies were in vivo/human investigations in children with carious primary teeth comparing erbium laser versus rotary instrumentation. Results: Eleven studies met the inclusion criteria. Across the included trials, erbium laser treatment was consistently associated with reduced intraoperative pain and improved comfort, often accompanied by lower anxiety indicators and higher child acceptance compared with rotary preparation. Several studies also reported a reduced need for local anesthesia in the laser group. In contrast, operative time was generally longer with erbium lasers than with turbines. When restorations were evaluated, clinical performance and short-term success (up to 12 months) were comparable between laser- and bur-prepared cavities, with no consistent disadvantages observed for laser preparation. Conclusions: Overall, erbium lasers appear to be a clinically effective and child-friendly alternative to conventional turbines, offering superior patient comfort while maintaining comparable short-term restorative outcomes, albeit at the cost of longer procedure duration. Full article

Whole-body vibration (WBV) remains a critical factor influencing ride comfort, driver performance and occupational health in vehicle applications. Despite the widespread use of standardized indicators, assessing WBV exposure and its perceptual implications remains challenging due to the complex interaction between road excitation, vehicle dynamics, seat transmissibility and human biodynamic response. This review provides a comprehensive synthesis of contemporary methods for WBV assessment, emphasizing their theoretical foundations, practical implementation and inherent limitations. The paper examines classical evaluation metrics, including frequency-weighted root mean square acceleration and vibration dose value, alongside complementary approaches such as overall vibration total value, absorbed power and motion sickness indicators. Biodynamic modeling strategies for the human–seat–vehicle system are critically reviewed, highlighting trade-offs between model simplicity and physiological realism. Particular attention is given to road surface representation and excitation modeling, discussing the implications of ISO 8608-based stochastic profiles versus measured, time-domain inputs on WBV assessment outcomes. Simulation frameworks, experimental platforms and driving simulators are reviewed as complementary tools for evaluating vibration exposure and validating predictive models. Emerging methods, including time–frequency analysis and data-driven approaches, are discussed with a focus on interpretability, validation and integration with established standards such as ISO 2631. The review consolidates recent advances in integrated evaluation approaches, including the role of driving simulators and simulation-, hardware- and driver-in-the-loop (SiL/HiL/DiL) frameworks as enabling tools for repeatable testing, objective–subjective comfort correlation and early-stage vibration-control development. By critically examining both established and emerging methodologies, this review aims to support informed selection and interpretation of WBV assessment tools in vehicle design and evaluation. The findings underscore the need for integrated, transparent and application-oriented approaches to advance vibration comfort assessment and guide future research and standardization efforts. Full article

Spatio-temporal planning has emerged as a robust methodology for solving trajectory planning challenges in complex autonomous driving scenarios. By integrating both spatial and temporal variables, this approach facilitates the generation of highly accurate, human-like, and interpretable trajectory decisions. This paper presents a novel learned planning model-based spatio-temporal behavior decider, engineered to produce optimal and explainable driving trajectories with enhanced efficiency and passenger comfort. The proposed decider systematically evaluates the action space of the ego-vehicle, selecting the trajectory that optimizes overall driving performance. This method is particularly significant for autonomous driving systems, as it ensures the generation of human-like trajectories while maintaining high driving efficiency. The efficacy of the proposed framework has been comprehensively validated through rigorous simulations and real-world experimental trials on a commercial passenger vehicle platform, demonstrating its practical utility and performance advantages. Full article

This study investigated how illuminance and spectrum in office lighting affect psychological fatigue, preference, visual comfort, and cognitive performance. Forty adults participated in a repeated-measures experiment under four conditions with two illuminance levels (500, 1000 lx) and two LED types (full-spectrum, conventional). For each condition, Karolinska Sleepiness Scale scores (fatigue), Office Lighting Survey ratings (preference, visual comfort), and Alphanumeric Verification Task performance (work speed, accuracy) were collected. Linear mixed-effects modeling was applied alongside correlation and regression analyses to examine condition effects and associations between variables. Compared to 500 lx, ΔKSS significantly decreased under 1000 lx, confirming that increased illuminance is associated with reduced psychological fatigue. At the same illuminance level, full-spectrum LEDs showed benefits, including lower fatigue and faster responses. Preference and visual comfort showed minimal direct sensitivity to lighting conditions but were moderately and positively correlated, while fatigue exhibited significant negative correlations with both preference and response speed. An interaction between illuminance and spectrum on accuracy suggested a speed–accuracy trade-off under high-illuminance full-spectrum lighting. Overall, the findings indicate that office lighting, particularly illuminance and spectral quality, acts as a human-centered factor shaping an interconnected response network linking fatigue, affective appraisal, and task performance. Full article