Search Results (651)

Blind image quality assessment (BIQA) without reference images remains significantly challenging due to the fact that perceptual quality is largely determined by subtle, spatially localized distortions. However, existing Contrastive Language–Image Pre-training (CLIP)-based methods exhibit limited sensitivity to fine-grained degradations such as local blur, noise, compression artifacts, and exposure inconsistencies, since they are optimized for global semantic alignment. To overcome these limitations, we propose a fine-grained vision–language framework that enhances distortion-aware representation by considering both fine-grained visual and detailed textual domains. Specially, our method employs a fine-grained CLIP architecture in conjunction with explicit textual descriptions to enable the effective identification of subtle regional degradations. Furthermore, a parameter-efficient prompt-tuning strategy is utilized to facilitate the learning of task-adaptive prompt representations tailored to image quality assessment (IQA). Extensive experiments on three widely used in-the-wild IQA benchmarks show that the proposed method achieves strong consistency with human subjective judgments: our training-free FGCLIP-IQA reaches a maximum SROCC of 0.732 on KonIQ-10k, outperforming the vanilla CLIP-IQA baseline, while the prompt-tuned FGCLIP-IQA+ further achieves a maximum SROCC of 0.909 on KonIQ-10k with only a small number of learnable parameters and exhibits robust cross-dataset generalization capabilities. These results demonstrate that the fine-grained vision–language alignment shows great potential for future development, and provides an efficient and accurate solution for the BIQA task. Full article

Background: Sensorimotor differences have frequently been reported in children with developmental dyslexia, but are often considered secondary or comorbid to phonological deficits. Within an embodied cognition perspective, reading acquisition emerges from dynamic interactions between bodily regulation, multisensory integration, and learning-related neural plasticity. Proprioception contributes to spatial orientation, motor coordination, and perceptual stabilization, while sleep-dependent processes play a critical role in the consolidation and automatization of cognitive and motor skills. Objectives: Building on early clinical observations, including the hypothesis proposed by Martins da Cunha, this review explores whether variations in proprioceptive processing and sensorimotor regulation may influence multisensory stability and the conditions under which reading skills develop in some individuals with dyslexia. Methods: This narrative synthesis integrates clinical observations and experimental paradigms examining proprioceptive function in children with dyslexia, including studies conducted in our laboratory over the past two decades. These investigations address postural regulation under varying attentional demands, laboratory measures of proprioceptive acuity, visuospatial localization tasks, multisensory interactions, and exploratory observations concerning sleep–wake regulation. Results: Across studies, children with dyslexia often show differences in proprioceptive processing associated with variations in postural regulation, visuospatial stability, and multisensory tasks. Laboratory measurements suggest reduced proprioceptive acuity in some individuals, with moderate correlations observed between proprioceptive sensitivity and reading-related measures. Additional observations suggest that nocturnal physiological regulation—including respiratory dynamics and sleep architecture—may interact with daytime sensorimotor stability and attentional functioning. Conclusions: Taken together, these findings support the hypothesis that variations in sensorimotor regulation across the sleep–wake cycle may influence the stability of multisensory processing and attentional conditions relevant for reading acquisition. Within this perspective, proprioception is not proposed as an alternative explanation for dyslexia but as a complementary dimension that may contribute to the heterogeneity of dyslexic profiles. Further longitudinal and controlled studies are required to clarify the relationships between sensorimotor regulation, sleep-dependent plasticity, and learning processes. Full article

Children gifted for music are often described as possessing heightened perceptual and sensory abilities, yet little is known about how these abilities are understood within different family contexts or how giftedness is experienced as an identity. This mixed-methods study examined alignment between gifted children’s and parents’ perceptions of children’s mental–perceptual abilities, the role of parental musical background, and how giftedness is explained and emotionally negotiated. Twenty-two children identified as gifted for music and 25 parents completed a survey based on Gagné’s Differentiated Model of Giftedness and Talent assessing six mental–perceptual abilities, followed by semi-structured interviews. Quantitative analyses revealed a strong positive association between child and parent ratings, alongside a consistent tendency for parents to provide higher evaluations. Parental professional musical background did not significantly moderate alignment but was associated with greater variability in both children’s and parents’ ratings. Qualitative findings indicated shared experiential understandings of ability across families, alongside systematic differences in evaluative frameworks: musician parents more frequently drew on technical, comparative, and training-based standards, whereas non-musician parents relied on affective and everyday observations. Children across contexts often expressed modesty or ambivalence toward being labeled gifted, while parents balanced pride with concern about pressure. Overall, perceptions of mental–perceptual ability emerged as relationally constructed within family environments that shape how musical giftedness is recognized and supported. Full article

Formative assessment is widely seen as a key teaching strategy to support student learning; however, evidence about its connection with self-regulated learning and the alignment between teachers’ and students’ perceptions remains mixed. This study explored the role of formative assessment in promoting self-regulated learning in lower secondary mathematics by incorporating both students’ and teachers’ viewpoints. From a co-regulatory perspective, formative assessment is considered a process developed through ongoing interactions between teachers and students and shared views of assessment practices. The sample included 305 students from Grades 5–9 and 39 mathematics teachers. Students reported their perceptions of formative assessment practices and self-regulated learning, while teachers reported their own practices. Analyses included Pearson correlation and multiple regression at the student level, along with class-level comparisons of teacher–student perceptions and analyses of perceptual agreement. Results revealed that students’ perceptions of formative assessment were positively linked to cognitive, metacognitive, behavioral, and motivational dimensions of self-regulated learning. Multiple regression results showed that different aspects of formative assessment significantly predicted students’ self-regulation, with the greatest explained variance in behavioral self-regulation. Teachers believed they used more formative assessment practices than students perceived. Additionally, higher levels of perceptual agreement between teachers and students, especially in clarifying learning goals and gathering evidence of learning, were associated with increased behavioral regulation and motivational independence among students. These findings emphasize formative assessment in mathematics as a relational and co-regulatory process that relies on shared understanding between teachers and students. Full article

In (colloquial) Italian, the fixed expression mi sa functions as an evidential/epistemic marker, requiring the dative 1SG clitic experiencer and the 3SG default form of the verb sapere. Mi sa diachronically develops from the verb for taste/smell, sapere, which is still productive in contemporary Italian, and the structure that it projects. This comprises an obligatory PP introduced by di encoding the type/quality of taste/smell (often metaphorically extended); a subject expressing the perceived entity; and an optional dative experiencer. We systematically analyzed data from the KIParla corpus, comparing the distribution of mi sa to the distribution of one of the most frequent Italian epistemic verb forms, namely, credo ‘I believe’. This study aimed to establish how the original perceptual meaning of mi sa influences its epistemic meaning. The results suggest that the persistence of the original object-oriented perception verb makes mi sa more likely to appear in particular contexts, i.e., events/situations that are known by the speaker through an inferential-like process. Furthermore, mi sa can only rarely be uttered out of the blue and seems to need a situative context (a stage), often containing an explicit QUD. Full article

Aircraft noise monitoring systems deployed at major airports typically rely on scalar energy-based indicators, which primarily describe integrated sound energy but provide limited representation of the spectral–temporal structure and perceptual attributes of aircraft noise. To address this limitation, this study proposes a sensor-based psychoacoustic feature extraction and spatiotemporal analysis framework for continuous aircraft noise monitoring under high-density operational conditions. An automatic noise monitoring system compliant with ISO 20906 was deployed to synchronously acquire acoustic waveforms and ADS-B trajectory data. A cascaded spatiotemporal fusion algorithm was developed to associate noise events with aircraft flight paths, followed by a model-stratified multidimensional IQR-based data cleaning strategy to suppress environmental interference and non-stationary outliers. Based on the cleaned dataset, a suite of psychoacoustic features—including loudness, sharpness, roughness, fluctuation strength, and tonality—was extracted to characterize the perceptual structure of aircraft noise beyond conventional energy metrics. Experimental results demonstrate that, under equivalent sound exposure levels, psychoacoustic features retain substantial discriminative information that is lost in scalar energy indicators. The coefficients of variation for fluctuation strength and tonality reach 43.2% and 22.1%, respectively, corresponding to 15–69 times higher sensitivity compared to traditional energy-based metrics. Furthermore, nonlinear manifold mapping using UMAP reveals clear topological separation between new-generation and legacy aircraft models in the psychoacoustic feature space, whereas severe overlap persists in energy-based representations. Correlation analysis further indicates decoupling between macro-level physical design parameters (e.g., bypass ratio, thrust) and perceptual feature dimensions, highlighting the limitations of energy-centric monitoring schemes. The proposed framework demonstrates the feasibility of integrating psychoacoustic feature extraction into continuous sensor-based aircraft noise monitoring systems. It provides a scalable signal processing pipeline for enhancing the resolution and interpretability of aircraft noise measurements in complex operational environments. Full article

Environmental perception is a cornerstone for autonomous underwater vehicles (AUVs) to achieve robust self-localization and scene understanding, which are pivotal for the intelligent management of marine ranching. However, underwater image degradation and weak-textured scenes significantly hinder reliable self-localization and fine-grained environmental perception. To address the perceptual asymmetry arising from these challenges, this paper proposes a robust visual–inertial simultaneous localization and mapping (SLAM) and biomass assessment scheme for marine ranching. Specifically, we first propose a robust tightly coupled underwater visual–inertial localization scheme, which leverages a multi-sensor fusion strategy to solve the image degradation problem of localization in complex underwater environments. Furthermore, we propose a novel underwater scene perception method, which enables the simultaneous visual reconstruction of aquaculture species and the quantitative mapping of their spatial distribution in marine ranching. Finally, we develop a low-cost, agile, and portable multisensor-integrated system that consolidates autonomous localization and aquaculture biomass assessment modules, with its performance validated through extensive real-world underwater experiments. The experimental results demonstrate that the proposed methods can effectively overcome the interference of complex underwater environments and provide high-precision perception support for both AUV state estimation and aquaculture asset management. Full article

While objective street metrics derived from imagery or GIS have become standard in urban analytics, they remain insufficient to capture subjective perceptions essential to inclusive urban design. This study introduces a novel Multimodal Street Evaluation Framework (MSEF) that fuses a vision transformer (VisualGLM-6B) with a large language model (GPT-4), enabling interpretable dual-output assessment of streetscapes. Leveraging over 15,000 annotated street-view images from Harbin, China, we fine-tune the framework using Low-Rank Adaptation(LoRA) and P-Tuning v2 for parameter-efficient adaptation. The model achieves an F1 score of 0.863 on objective features and 89.3% agreement with aggregated resident perceptions, validated across stratified socioeconomic geographies. Beyond classification accuracy, MSEF captures context-dependent contradictions: for instance, informal commerce boosts perceived vibrancy while simultaneously reducing pedestrian comfort. It also identifies nonlinear and semantically contingent patterns—such as the divergent perceptual effects of architectural transparency across residential and commercial zones—revealing the limits of universal spatial heuristics. By generating natural-language rationales grounded in attention mechanisms, the framework bridges sensory data with socio-affective inference, enabling transparent diagnostics aligned with Sustainable Development Goal 11(SDG 11). This work offers both methodological innovation in urban perception modeling and practical utility for planning systems seeking to reconcile infrastructural precision with lived experience. Full article

The ISO 12913 series represents a paradigm shift in environmental acoustics by introducing a human-centered and perceptual framework for soundscape assessment. Although conceived as globally applicable, questions remain regarding its implementation in Global South contexts. This study evaluates how ISO 12913 is perceived, interpreted, and applied in Brazil, with the aim of identifying its strengths, limitations, and contextual adaptation needs in relation to soundscape standardization and sustainability. A mixed-methods approach was employed, combining an online survey with Brazilian soundscape researchers and practitioners and a virtual focus group with domain experts. Quantitative data were analyzed descriptively, while qualitative responses were examined through thematic analysis structured under a Societal Research Impact Assessment framework. The results indicate broad recognition of the conceptual relevance of ISO 12913, especially its interdisciplinary and human-centered approach. However, several challenges were identified, including linguistic and semantic inconsistencies in perceptual attributes, limited guidance for indoor soundscape assessment, conceptual ambiguities, and socioeconomic constraints affecting implementation. Participants highlighted the need for cultural, linguistic, and methodological adaptations to enable meaningful application within heterogeneous and resource-constrained contexts. By foregrounding the Brazilian experience, the study contributes to global debates on soundscape standardization, by demonstrating how international frameworks such as ISO 12913 can be refined through meaningful engagement with Global South contexts. The study supports the development of complementary national guidelines aimed at enhancing contextual adequacy, operational feasibility, and long-term societal impact, thereby fostering more inclusive and socially sustainable soundscape assessment practices. Full article

This study examines the perceived impact of sensory and interactive architectural design in inclusive learning environments on the sensory–emotional responses and behavioral–academic outcomes of children with neurodevelopmental disorders—namely Autism Spectrum Disorder, Down Syndrome, and Attention-Deficit/Hyperactivity Disorder—during early childhood within the Egyptian educational context. Adopting a perception-based, non-causal analytical perspective, a descriptive–analytical, survey-based design was implemented using a validated questionnaire developed from an architectural–educational conceptual framework grounded in relevant literature. The study involved (N = 202) parents, teachers, therapists, and caregivers who evaluated the perceived influence of environmental design elements on children’s sensory responses, behavior, social interaction, and academic performance, based on observational and experiential assessments rather than objective environmental performance measurements. The results indicated high perceived impacts on sensory–emotional responses (84.8%) and behavioral–academic outcomes (82.0%). Movement–spatial attributes showed the strongest influence, followed by balanced natural lighting, calming colors, natural materials, and low-noise acoustic conditions, while natural elements and sensory gardens played a regulatory role in supporting emotional stability and social interaction. The study concludes that sensory- and emotionally responsive architectural design, when understood as a supportive component of the educational experience rather than an independent causal factor, and integrated with appropriate pedagogical practices, contributes to inclusive learning environments accommodating neurodevelopmental diversity, while informing the development of an applied, evidence-informed architectural design framework that translates perceptual–correlational findings into structured and operational design guidelines adaptable to the Egyptian educational context. Full article

University campus green spaces function as critical microcosms of urban building environments, directly advancing Sustainable Development Goals 3 (Good Health and Well-being) and 11 (Sustainable Cities and Communities) through evidence-based landscape design. Taking a large university in China as the research object, this study integrates virtual reality (VR) simulations with synchronized psychophysiological measurements and perceptual scales to quantify how three planting modes—clustered, scattered, and regular—influence restorative experiences across teaching, living, and administrative areas. Rigorous data processing ensured robustness. The results revealed functional-area-specific restoration pathways: clustered planting enhanced relaxation in living zones, scattered planting elevated vitality in teaching areas, and regular planting reinforced security perception in administrative spaces. A path model was used to elucidate how four-dimensional (4D) landscape indicators (openness, pleasantness, diversity, focus) mediate psychological and physiological responses. Theoretically, this 4D framework translates abstract restorative experiences into operable design dimensions; methodologically, VR-based multi-source measurement offers a replicable technical pathway for scheme verification; practically, it serves as a quantitative tool for planting optimization. Critically, these campus-derived insights offer transferable design principles for enhancing well-being across urban building environments, delivering a replicable VR-assisted framework that directly contributes to sustainable cities through human-centered, evidence-based landscape solutions. Full article

In the context of rapid urbanization and the pursuit of the United Nations Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities and Communities), cities face multifaceted challenges such as high population density, limited green space, ecosystem degradation, and an insufficient supply of ecological products, all of which undermine urban sustainability. As crucial ecological units, urban park green spaces (UPGS) play a vital role in alleviating environmental pressures and providing cultural ecosystem services (CES) that are essential for human well-being and social sustainability. However, systematic insight into how residents perceive and value CES, along with the underlying drivers, remains underdeveloped, impeding the advancement of refined park management practices. Based on 12,083 social media texts, this study employed BERTopic topic modeling to identify five core dimensions of CES perception: recreational services (RS), aesthetic experiences (AE), health-promoting activities (HA), social interactions (SI), and educational services (ES). Additionally, four underlying drivers with corresponding measurable indicators were also identified: residents’ socioeconomic backgrounds (RSB), external built environment of parks (EBE), internal landscape composition (ILC), and quality of services management (QSM). Subsequently, using 313 valid questionnaires and geographic park data, a Partial Least Squares Structural Equation Modeling (PLS-SEM) framework was constructed to analyze the influence mechanisms of EBE, ILC, and QSM on CES perception differences, with residents’ satisfaction with CES serving as the measure of their perceived CES levels. Hierarchical regression analysis was further employed to examine the moderating effects of RSB on these driving pathways. The findings reveal the following: (1) Significant synergies and heterogeneities existed among CES dimensions, with notable synergistic effects observed between AE and SI, as well as between HA and RS. (2) EBE, ILC, and QSM significantly influenced CES perception differences (p < 0.05). EBE affected these differences through pathways such as EBE → ILC → QSM → CES and EBE → QSM → CES. Notably, QSM was identified as the most critical mediating factor affecting CES perception differences. (3) Age exerted a significant positive moderating effect on the QSM → CES pathway, while monthly income showed a marginally significant negative moderating trend on the ILC → QSM pathway. This study elucidates the multi-level driving mechanisms underlying differences in residents’ perceptions of CES in UPGS. A key innovation lies in the integration of large-scale social media text data with questionnaire surveys, combined with the application of the BERTopic model and PLS-SEM to analyze these perceptual differences. The findings offer both theoretical foundations and practical insights for landscape optimization and service enhancement in park planning and management, contributing to the development of more equitable, resilient, and sustainable urban environments. Full article

In the context of rapid urban tourism expansion and the growing emphasis on equitable and sustainable transport development, understanding how transport systems support different types of attractions has become increasingly important. This study investigates how attraction hierarchy and functional type interact with public transport accessibility to shape urban tourism patterns and equity. Whereas prior work emphasizes objective metrics, the alignment between perceived accessibility and actual transport conditions remains understudied. Using Wuhan’s A-rated and popular unrated attractions as a case, we have developed an innovative “ objective–perceived coupling framework that integrates GIS network analysis, travel cost matrix, non-parametric testing, and online comment text mining methods to examine how scenic spot levels (A-level and unrated popular scenic spots) and functional types interact with the public transportation system from both objective and perceptual dimensions. Results show: (1) A-rated attractions cluster in suburbs with low accessibility, while unrated sites concentrate centrally with high rail-bus connectivity, revealing a “high-grade–low-accessibility” mismatch. (2) Accessibility varies by type: natural sites are lowest, cultural/leisure venues intermediate, and comprehensive sites highest due to multimodal hub proximity. (3) Sentiment and topic analyses based on transport-related review content suggest that some A-rated attractions receive less favorable evaluations of access conditions (e.g., transfers, waiting, last-mile walking, wayfinding, and parking), whereas many popular unrated sites are evaluated more positively in these transport-specific aspects. (4) Quadrant analysis shows many highly rated attractions fall into a “low objective–low perceived” disadvantage, while most unrated ones exhibit strong objective–perceived coupling. These findings underscore structural imbalances among administrative grading, attraction function, and transit provision, offering evidence for optimizing public transport service to tourist attractions. They help optimize the spatial structure of urban tourism, improve resource allocation efficiency, guide differentiated scenic spot development strategies, and promote sustainable and experience-oriented urban tourism governance. Full article

In soundscape studies, several models of perceived affective quality have been developed for specific indoor spaces to help characterize comfortable and satisfying environments. However, no model has been developed so far for dining spaces and the validity of existing models proposed for other indoor contexts, like residential buildings and offices, in dining spaces settings remains uncertain. Therefore, this sequential mixed-method study was conducted to establish a list of attributes that researchers may use to describe dining space soundscapes, which will help in developing an indoor soundscape model for dining spaces. A total of 505 potential attributes were identified and collected through multiple approaches including a Large Language Model-driven synthesis and a systematic review of literature related to dining space soundscapes. Subsequently, the original attributes were refined using qualitative analysis methods in several steps, resulting in a final set of 129 single-word attributes, clustered into 53 semantically coherent groups. This set of attributes will contribute to identifying the main perceptual dimensions of dining space soundscapes and constructing a principal components model through quantitative analyses, while the proposed methodology integrates an LLM-driven synthesis with iterative qualitative expert refinement and offers a more efficient and scalable alternative to conventional labor-intensive manual descriptor extraction for attribute collection, therefore supporting efficient and scalable attribute compilation. Full article

This paper examines students’ perceptions of factors influencing normative support for the integration of AI Chatbots in universities, providing an empirical basis for developing institutional policies and implementation strategies in higher education. Framed within the sustainability perspective, the study examines how ethical, cognitive, and perceptual factors shape the long-term adoption of AI technologies in academic environments. Our study employs a structural model comprising 10 constructs, 46 items, and 9 hypotheses, tested on a sample of 408 economics students from Timisoara. The research identifies AI literacy as the most influential factor in the formal integration of these technologies in universities. The following factors have a direct impact: teacher perception, student perception, and cognitive risks (reliance on AI Chatbots and avoidance of intellectual effort). Use for personalized learning is a factor with a significant direct effect on positive perceptions and intentions to use AI Chatbots among students. Academic integrity risks, as well as limitations on accuracy and reliability, have no significant impact. AI Chatbots represent an essential opportunity to transform higher education. However, their positive impact is realized only through responsible formal integration, grounded in ethical policies, adequate digital education, and the adaptation of pedagogical practices. Universities must regard AI as a strategic ally for teachers and students, while keeping human interaction, critical thinking, and academic integrity at the centre of the educational process. The study argues that students’ perceptions are that universities must approach AI Integration as a strategic component of sustainable educational ecosystems, aligning innovation with long-term academic integrity and the objectives of sustainable development, particularly Sustainable Development Goal 4 (Quality Education). Full article