Search Results (3,957)

Conventional furniture design predominantly hinges on empirical expertise and subjective appraisal, absent systematic quantitative validation of users’ visual cognition. This research establishes a multimodal quantitative evaluation framework for round-back armchairs that integrates subjective weighting via AHP and objective eye tracking measurements. Four ocular physiological metrics are aggregated using the CRITIC–entropy composite weighting approach to characterize visual attention allocation. PCA distills three core perceptual dimensions, and Quantification Theory Type I constructs a mapping function linking component morphology to perceptual responses. Notable systematic divergence is identified between expert aesthetic preferences and users’ fixation patterns. Backrests govern volume perception, chair rings dominate concise shape perception, and foot stretchers determine stylistic elegance. Low-relief backrests, three-segment curved chair rings and inward horse hoof stretchers yield superior perceptual performance, whereas gooseneck front posts and connecting balusters exhibit trivial marginal optimization gains. A model-derived candidate morphological configuration, A2-B3-C1-D1-E2-F2, is identified with corresponding effect size estimation. This study provides an exploratory analytical framework and methodological reference for promoting the transition from experience-oriented to data-driven traditional furniture design. Full article

Virtual reality (VR) applications are often designed as episodic experiences, with limited support for persistence, longitudinal revisitation, and structured integration of interaction data across sessions. This paper presents a persistent multi-user VR garden architecture that combines snapshot-based state restoration, structured event, movement, and transcript records, an asymmetric owner–visitor workflow, cloud-mediated speech transcription, and deferred AI-supported synthesis. The architecture separates the current spatial configuration of the environment from the interaction traces through which it evolves, supporting repeated access, state restoration, historical consultation, and post-hoc processing. A controlled technical validation using synthetic or researcher-generated inputs was conducted through Unity Editor/backend tests and on Meta Quest 3 hardware. Persistence was evaluated at 20, 100, and 250 objects in the Editor and at 1, 50, and 100 objects on Quest, with two Quest replicas per load. Application-level visitor restrictions were verified across nine prohibited write operations. A frozen production speech-to-text corpus completed 40/40 requests with a micro-averaged word error rate of 9.50% and a median end-to-end latency of 1.619 s. The deferred AI pipeline was additionally verified as a functioning technical integration, while limitations in semantic-detail preservation were observed. The results support the implementation-level feasibility of the proposed persistent and traceable VR architecture. The present evaluation does not establish backend-level authorization guarantees, general AI or NPC-grounding performance, user outcomes, or clinical effectiveness. Full article

As China’s urbanization shifts toward quality-oriented development, urban regeneration increasingly prioritizes the perceived quality of public spaces to enhance urban vitality and advance sustainable urban living. This study takes Zhengzhou’s Dongfeng Canal, a revitalized urban core waterfront, as a case to develop a human–machine collaborative analytical framework for exploring nonlinear relationships between visual environmental features and human spatial quality perception. By integrating 779 geolocated panoramic images with volunteers’ subjective rating data, this study adopts deep learning-based semantic segmentation to quantify eight objective visual indicators (e.g., greenness, color diversity, spatial structure). A random forest (RF) model links these indicators to three perceptual dimensions: scenic beauty, safety, and recreational value. Adopting explainable artificial intelligence (SHAP and PDPs), the results indicate that: (1) greenness is positively associated with positive perceptions but exhibits a significant threshold effect; (2) color diversity and waterfront accessibility substantially improve user experience, while excessive uniformity and extreme openness negatively affect perceived spatial quality. These findings challenge the simplistic linear “more-is-better” assumption in urban design and highlight the value of balanced, context-sensitive spatial interventions. This study provides evidence-based, segment-specific strategies for urban waterfront regeneration, advancing people-centered planning that integrates ecological functionality, social inclusivity, and long-term sustainability via Geospatial Artificial Intelligence (GeoAI) and geospatial analytics. Full article

Public parks support health, wellbeing, and social inclusion, yet conventional wayfinding approaches remain largely focused on physical mobility and directional navigation, often overlooking the cognitive and sensory experiences of neurodivergent users. This study develops a theory-informed framework for neuroinclusive wayfinding design through an integrative literature review. Using a Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA)-informed protocol, 106 core sources were synthesized from landscape architecture, environmental psychology, public health, and neurodiversity research. A qualitative theory-building approach combining thematic analysis, theoretical mapping, and abductive synthesis identified four themes: Cognitive Navigation and Environmental Legibility, Sensory Processing and Environmental Regulation, Restorative Landscapes and Nature-Based Wellbeing, and Inclusive, Adaptive, and Neurodiverse Design. These themes were subsequently translated into eight environmental challenges and operationalized into eight neuroinclusive wayfinding design criteria organized within four support domains. The resulting framework conceptualizes wayfinding as a cognitive–sensory support system rather than a purely navigational function, linking interdisciplinary evidence to practical landscape architectural design strategies. By integrating fragmented knowledge across multiple disciplines, the study provides a foundation for future validation and the advancement of neuroinclusive public park design. Full article

With increasing interest in nature-based and biophilic built environments, understanding how users perceive natural characteristics embedded in sports venues and how these perceptions are associated with psychological experiences and behavioural intentions has become an important research topic. However, limited studies have examined the psychological mechanisms through which perceived nature-based characteristics of sports venue design are related to users’ revisit intention. Based on restorative environment theory and place attachment theory, this study investigates the relationship between nature-based sports venue design and revisit intention from a user-perceived built environment perspective, with a particular focus on the mediating roles of perceived restorativeness and place attachment. A questionnaire survey was conducted among university students in Shandong Province, China, and 623 valid responses were obtained. Structural equation modelling and bootstrap analysis were employed to examine the proposed relationships. The results showed that perceived nature-based sports venue design characteristics were positively associated with revisit intention, perceived restorativeness, and place attachment. Perceived restorativeness was positively associated with both place attachment and revisit intention, while place attachment was positively associated with revisit intention. Furthermore, mediation analysis indicated that perceived restorativeness and place attachment separately mediated the relationship between perceived nature-based sports venue design characteristics and revisit intention, and together formed a sequential mediation pathway. These findings suggest that nature-based characteristics embedded within sports venues may support users’ restorative experiences and emotional connections with places, which are associated with continued engagement with sports spaces. This study provides user-centred evidence for built environment design and sports venue planning by highlighting the potential importance of natural lighting, spatial openness, visual connections with nature, and restorative spatial experiences. Full article

As China’s dominant urban housing form, gated residential communities deploy layered spatial access controls governing who may enter and move through neighbourhood space. While neighbourhood social sustainability has attracted substantial scholarly attention, how micro-spatial governance arrangements affect the inclusiveness of residential built environments toward essential service workers remains underexplored. Drawing on Lefebvre’s theory of the production of space, this study uses food delivery riders—who navigate gated community access controls dozens of times daily—as an analytical lens to evaluate how neighbourhood spatial governance shapes social inclusiveness. Vignette-based survey data from 445 riders across 157 cities in 27 Chinese provinces were analysed using structural equation modeling. Results show that cumulative anxiety from procedural delays, detours, and elevator waiting is the dominant pathway through which spatial governance undermines riders’ perceived spatial inclusion—operationalised through occupational dignity indicators—with elevator-based spatial stratification identified as a concrete, low-cost intervention target within the spatial-channeling mechanism. Technology-mediated access partially mitigates face-to-face exclusion but leaves underlying spatial inequalities intact. Demographic invariance across all tested variables confirms that diminished inclusion arises from the governance regime itself. The findings position neighbourhood spatial governance as a measurable dimension of urban social sustainability—one concretely testable through the experience of essential service workers—and identify low-cost built-environment interventions for inclusive residential design. While the study focuses on riders as a single user group, the analytical framework is transferable to evaluating how residential built environments accommodate diverse non-resident populations. Full article

Ambient Assisted Living (AAL) environments aim to enable older people to remain active and lead an autonomous and independent life for as long as possible. Among the technologies that can be incorporated into these settings, socially assistive robots (SAR) seek to establish a more natural and intuitive means of interaction with people, whilst helping them to carry out everyday tasks. One of the main challenges facing the design of these robots is how to enable them to undertake more complex tasks. Recent advances in Large Language Models (LLMs) have opened new avenues for flexible robot deliberation, yet their integration into real-time robotic systems remains challenging due to latency constraints, reasoning reliability, and the complexity of coordinating multi-step tasks. This paper proposes a hierarchical multi-agent architecture for robot deliberation that addresses these challenges by combining LLM-based planning with structured execution mechanisms within the ROS 2 ecosystem. The proposed architecture employs a supervisor agent that decomposes high-level natural language instructions into prioritised subtasks, enabling a priority-driven execution model that dynamically adapts to task relevance, temporal constraints, and environmental feedback. Subtasks are delegated to a set of Single-Purpose Agents (SPAs), orchestrated via LangGraph state machines and coordinated through a priority-aware scheduling mechanism. A key design principle is the use of Behaviour Trees (BTs) as high-level callable tools through the Model Context Protocol (MCP), encapsulating closed-loop control strategies while enabling preemptive and priority-consistent execution. This reduces the number of LLM inference steps required per task and improves robustness under dynamic conditions. A further contribution concerns the deployment of fine-tuned, lightweight LLMs—on the order of 0.6 billion parameters—specifically adapted for both the supervisor and the individual SPA roles through parameter-efficient low-rank adaptation (LoRA). These models are trained on role-specific tool-calling datasets to specialise in constrained reasoning patterns and task-specific decision-making, enabling efficient, low-latency inference directly on edge hardware. The combination of fine-tuning and hierarchical priority control enhances both the determinism and responsiveness of the system while mitigating error propagation across agent interactions. The paper presents the full software architecture, a formal characterisation of the system as a priority-aware hierarchical policy over a graph of agent workflows, and an experimental evaluation in an Ambient Assisted Living scenario assessing task success rate, inference efficiency, responsiveness under competing priorities, and overall user experience. Because SPA execution is decoupled from the supervisor’s own reasoning loop, the architecture is designed to keep accepting, processing, and queuing new user queries while previously dispatched SPAs are still executing their tasks. Full article

Sustainable web development focuses on designing web pages that minimize their environmental impact by reducing digital carbon emissions while maintaining optimal website performance and user experience. This study emphasizes the necessity of adopting sustainable web development practices in the Balkan region, highlighting the role of institutional education and web developers in encouraging environmentally responsible web practices within a Technology-Enhanced Education context. A descriptive cross-country analysis was conducted on a total of 8976 websites across five Balkan countries—Albania, Greece, Serbia, Montenegro, and North Macedonia—selected from public domain registries and categorized by sector (education, organization, government, and commercial domains). Data were collected during December 2025. DNS verification was conducted to identify active domains, and hosting sustainability was determined through the Green Web Foundation API. “Green hosting” is operationally defined as hosting that is completely powered by renewable energy sources. Overall, the findings suggest that the prevalence of green hosting in the region is very low, at approximately 27.77%, with substantial variation across sectors. Educational institutions (.edu) and non-profit organizations (.org) have higher adoption rates, while public administrations (.gov) and small commercial websites generally fall behind. The country with the highest percentage of green hosting is Greece (64.07%), while the lowest is Albania, with less than 1%. These findings reveal significant gaps in knowledge and practices among developers and institutions, indicating an urgent need for targeted educational interventions. Crucially, this study connects empirical evidence directly to education. Recognized knowledge gaps guide curriculum development and the design of practical training modules to equip developers and institutional personnel with the skills to adopt sustainable web practices. This research establishes a regional comparative baseline and offers practical recommendations for incorporating sustainability into web development education. The findings endorse strategies and policies aimed at promoting environmentally sustainable digital infrastructure in the Balkan area. Full article

Background/Objectives: The integration of artificial intelligence (AI) into pharmaceutical sciences and industry can accelerate the design and optimization of drug delivery systems and biotechnological processes and operations. Methodology: In this work, we present a novel application (a platform) developed using Google AI Studio, a web-based environment for prototyping generative AI solutions powered by highly capable models such as Gemini. The application enables rapid design of experiments (DoE), drug formulations and processes through structured prompting and automated workflows using a simple, user-friendly interface. Results: The platform could integrate formulation material attributes and critical process parameters to assist in the rational design of conventional and advanced delivery systems or any industrial process. Conclusions: This study highlights the potential of generative AI to accelerate pharmaceutical and biotechnological innovation, reduce experimental burden, and support pharmaceutical industry strategies. Full article

Self-checkout (SCO) systems have become an integral part of modern retail, yet their increasing popularity has also revealed a number of technical and usability challenges that influence customer experience and technology acceptance. This paper investigates human–machine interaction in self-checkout systems based on a survey conducted among 419 young adults in Poland. The study combines quantitative and qualitative analyses to identify the most commonly reported technical difficulties, users’ attitudes toward current self-checkout systems, and their expectations regarding future technological developments. The results indicate that although self-checkout systems are generally perceived as intuitive, convenient, and time-saving, their broader acceptance is limited by recurring self-reported problems related to age verification, weighing scales, product recognition, and the need for employee intervention. Respondents consistently emphasized that future technological innovations should build upon reliable and user-centered existing systems by addressing current usability limitations before introducing entirely new functionalities. At the same time, they expressed a positive attitude toward AI-assisted solutions, including automated product recognition and intelligent age verification, provided that these technologies increase perceived reliability and preserve users’ sense of control. The findings highlight that successful technological innovation in self-checkout systems should be driven by human-centered design, with improvements in usability forming the foundation for the adoption of future AI-assisted solutions. Full article

The growing demand for virtual reality and immersive applications has increased interest in 360° video streaming. When viewing omnidirectional content through a head-mounted display, users observe only a limited portion of the content, i.e., the viewport, at any given time. Consequently, transmitting the complete panoramic frame at uniformly high quality is bandwidth-inefficient. This review presents a system-level analysis of viewport-adaptive three-degree-of-freedom (3DoF) 360° video streaming, focusing on the coupled roles of viewport prediction, tile-based multi-rate encoding and bitrate allocation, transport mechanisms, and edge-assisted processing. The reviewed literature is examined to identify the design dependencies and trade-offs among these components. Viewport-adaptive approaches seek to reduce the bandwidth allocated to regions outside the instantaneous viewport while preserving the quality of the visible region. The analysis shows that their effectiveness cannot be attributed to prediction accuracy alone: the resulting Quality of Experience (QoE) depends jointly on tile granularity, bitrate allocation, buffer occupancy, transport delay, and whether prioritized tiles arrive before their playback deadlines. Finer tiling can improve spatial selectivity but increases coding, signaling, and request overhead. Moreover, HTTP/2, HTTP/3/QUIC, RTP/RTSP, and WebRTC present different reliability, latency, congestion-control, and scalability trade-offs across buffered video-on-demand, low-latency live streaming, and interactive immersive applications. Based on this synthesis, the review formulates a unified closed-loop cross-layer framework that coordinates prediction, tiling, bitrate allocation, request timing, transport configuration, buffering, and edge processing under bandwidth, latency, and resource constraints. Full article

The integration of Generative AI (GenAI) into non-STEM education introduces cognitive demands that challenge static interpretations of technology acceptance. Evidence on GenAI acceptance is drawn largely from cross-sectional designs applied to general-purpose academic tasks and for computing students who already hold prior technical knowledge, leaving unresolved how acceptance perceptions evolve when non-technical students confront sustained high-load programming work. To address this gap, a pre-test/post-test randomized field experiment with repeated measures was conducted with 117 Chilean Accounting and Auditing undergraduates assigned to a control group (instructional videos; n = 57) or an experimental group (Google Gemini 1.5; n = 60). Participants completed Java programming exercises that increased in cognitive complexity, ranging from basic conditionals to vector operations. The study did not assess objective learning outcomes; instead, it tracked changes in user perceptions through a hybrid motivational framework integrating Perceived Ease of Use and Behavioral Intention with Perceived Enjoyment and Value/Usefulness. Baseline results showed lower initial Perceived Ease of Use in the GenAI group, consistent with initial cognitive friction. Post-intervention analyses indicated that the control group showed a significant increase only in Behavioral Intention, whereas the experimental group showed statistically significant within-group gains across all measured dimensions. These findings suggest that, for non-STEM students, the perceived ease and value of GenAI are not necessarily immediate but may develop through sustained interaction with cognitively demanding tasks. The study contributes to technology acceptance research by framing ease of use as an acquired proficiency in high-friction GenAI learning environments. Full article

Fake news often manipulates fine-grained knowledge elements such as entities, events, claims, temporal expressions, attributes, and source credibility. Existing information extraction methods usually require task-specific annotations or focus on generic named entities, making them less effective for open-domain fake news scenarios where labeled data are scarce and logical inconsistencies are subtle. This paper proposes HPDO-KEE, a hierarchical prompting framework with dynamic optimization for knowledge element extraction and feature enhancement in fake news detection. The method first defines a fake-news-oriented schema covering entities, events, claims, attribute–value pairs, relations, contradictions, and user authority. It then designs a four-layer prompt consisting of task description, core information, structure awareness, and demonstration assistance. The revised implementation distinguishes offline prompt-template rewriting from input-adaptive demonstration retrieval and automatic schema-validation retries during inference. Domain-aware demonstration selection, strict JSON constraints, redundancy removal, contradiction-candidate verification, and type correction are incorporated to improve extraction accuracy, format compliance, and stability. Experiments on CoNLL03, ACE2005, and DuEE2.0 show that HPDO-KEE achieves F1 scores of 88.9%, 82.6%, 80.3%, and 78.6% on named entity, entity, event, and Chinese event extraction tasks, respectively. Full article

Thai Buddhist funeral services constitute a substantial multi-actor service ecosystem that remains largely dependent on conventional, fragmented coordination among bereaved families, temples, service providers, and administrative actors, with limited digital integration. This study reports a pre-deployment acceptance evaluation of a conceptually specified GenAI-assisted funeral-coordination service and proposes an Evidence-to-Design Translation Framework (EDTF) for translating acceptance evidence into initial design and governance requirements. Using non-probability convenience sampling through online recruitment, 342 screened adults with prior funeral-arrangement experience in the Bangkok Metropolitan Area evaluated a standardized vignette and representative interface mockups rather than an operational platform. PLS-SEM was used to examine prospective acceptance under five predefined safeguards: traceability, auditability, contestability and redress, verification, and risk-based human review. Perceived usefulness was the strongest predictor of intention to use, while attitude toward use provided a secondary pathway. The EDTF maps empirically supported user-evaluation signals to candidate workflow features, accountability controls, required records, monitoring indicators, and escalation rules. The findings provide bounded pre-deployment evidence for subsequent prototyping and pilot validation; they do not demonstrate actual adoption, live-system effectiveness, safeguard causality, or realized industry transformation. Full article

Small-scale fisheries are socio-ecological systems in which resource users interact with environmental conditions, fishing regulations, community initiatives, and institutional actors. Understanding how fishers perceive and report these interactions provides information on the social context of fisheries management, although such perceptions cannot substitute for independent assessments of ecological sustainability, behavioural compliance, or governance effectiveness. This study characterized fishers’ environmental perceptions, self-reported fishing practices, participation in environmental education and conservation activities, and perceptions of community and institutional involvement in fisheries management in Tecomate Lagoon, Guerrero, Mexico. A cross-sectional quantitative design was used, and structured questionnaires were administered to 120 active artisanal fishers selected through simple random sampling. Data were analyzed descriptively using frequencies and percentages. Respondents primarily associated the lagoon with economic (49.17%) and food-related (25.83%) functions. Declining water levels (60.00%) and reduced species abundance (40.00%) were the environmental changes reported by respondents. Regarding fishing practices, 94.17% stated that they complied with fishing regulations, and 100% reported releasing organisms below the minimum legal catch size. Environmental training was reported by 95.00% of respondents, while 94.17% reported participation in conservation-related activities. CONAPESCA (80.83%) and UAGro (19.17%) were identified as institutions involved in fisheries-related initiatives. These findings characterize the perceptions and self-reported experiences of surveyed fishers and should not be interpreted as evidence of ecological sustainability, actual behavioural compliance, educational effectiveness, or governance performance. The contribution of the study lies in systematically documenting the resource-user perspective as a component of the social dimension of the fishery. This information provides a descriptive baseline that can complement future ecological, behavioural, institutional, and longitudinal assessments of small-scale fisheries in coastal lagoon systems. Full article