To enhance the online education service experience, the emotional valence of the user was studied as an evaluation variable, and both qualitative and quantitative research were used to find how to evaluate online education service touchpoints. First, deconstruct the system service interface with the interactive touchpoint matrix, set service evaluation indicators from four aspects, visual guidance, learning resources, after-class evaluation, and interactive feedback, and build an online education service touchpoint evaluation system. Secondly, using Tencent Classroom as the target of research, an online education service rating experiment is created based on the two dimensions of emotional valence and perceptual cognition. With the aid of a questionnaire survey and analytic hierarchy process (AHP), a multidimensional evaluation of online education service touchpoints is accomplished using the learners’ emotional enjoyment, activation, dominance, touchpoint satisfaction, and importance as measuring indicators. Finally, concluding the assessment and optimization of online education service touchpoints, the evaluation data for the service are combined, and the evaluation results are generated using visual design. This study includes successful strategies and practical recommendations for boosting interest in e-learning services, user initiative, and excitement for learning.

This study aims to address the research gap in the digital analysis of traditional patterns by proposing an image-processing-driven parametric modeling method that combines graphic primitive function modeling with topological reconstruction. The image is processed using a dual-channel image processing algorithm (Canny edge detection and grayscale mapping) to extract and vectorize graphic primitives. These primitives are uniformly represented using B-spline curves, with variations generated through parametric control. A topological reconstruction approach is introduced, incorporating mapped geometric parameters, topological combination rules, and geometric adjustments to output topological configurations. The generated patterns are evaluated using fractal dimension analysis for complexity quantification and applied in cultural heritage imaging practice. The proposed image processing pipeline enables flexible parametric control and continuous structural integration of the graphic primitives and demonstrates high reproducibility and expandability. This study establishes a novel computational framework for traditional patterns, offering a replicable technical pathway that integrates image processing, parametric modeling, and topological reconstruction for digital expression, stylistic innovation, and heritage conservation.

Colored glaze on a black background and monochrome glaze are representative porcelain glazes from the Duandian kiln. Differences between the two types of glazes were studied by colorimetry, XRF, UV-Vis-NIR, XPS, Raman, XRD, and SEM-EDS. The results showed that the monochrome glaze contained more SiO₂, bubbles, and crystal phases than the colored glaze on a black background, giving it a higher brightness. The production method of the monochrome glaze was more mature, and the atmosphere was more strongly reducing. Rayleigh scattering within the sky-blue and sky-green glazes on a black background deepened their blue tone. Mie scattering produced by the moon-white glaze on a black background enhanced its opacity. However, the amorphous photonic crystal structural color produced by the monochrome glaze was weak. The Fe²⁺/Fe³⁺ ratio of the sky-blue, sky-green, and moon-white glazes of the two types of glazes decreased successively.

As core architectural environments for cultural heritage preservation and public education, museums are evolving from static exhibition spaces into immersive, multisensory interactive environments. The sensory attributes of the architectural environment—including multimodal information such as light, sound, and touch—exhibit a dynamic coupling with visitors’ emotional states. Responding to visitors’ growing emphasis on emotional enhancement, this study aims to improve the emotional experience of museum tours through multisensory compensation strategies. First, we conducted an experiment at the Shaanxi Archaeology Museum, capturing facial videos of participants during their tours and utilizing a facial expression analysis system for continuous emotion recognition. Subsequently, drawing on theories of multisensory interaction and emotion regulation, we constructed a multisensory emotion regulation model to guide the sensory compensation experiment. Visualization analysis of the results confirmed that multisensory compensation strategies within the architectural environment significantly increased positive emotions (from 48.23% to 60.78%). This study focuses on the mechanisms by which sensory compensation strategies in the architectural environment influence visitors’ emotional experiences, aiming to promote the transformation of cultural heritage spaces from “function-oriented” to “emotion-oriented” environments.

With the continuous expansion of urban metro systems, balancing passenger experience and operational efficiency has become a central concern in contemporary public transportation design. However, most existing metro service studies continue to focus on perceptual comfort or isolated usability tasks and lack an integrated, behavior-centered perspective that accounts for the full travel chain and diverse user groups. This study develops the Bi-directional Service Behavioral Experience Model (BSBEM), which systematically integrates one-way navigation behaviors and interactive operational behaviors within a unified dual-path framework to identify behavioral patterns and experiential disparities across user groups. Based on the People–Touchpoints–Environments–Messages–Services–Time–Emotion (POEMSTI) behavioral observation framework, this study employs a mixed-method approach combining video-based behavioral coding, usability testing, and subjective evaluation. An empirical study conducted at Beidajie Station on Xi’an Metro Line 2 involved three representative passenger groups: high-frequency commuters, urban leisure travelers, and special-care passengers. Multi-source data were collected to capture temporal, spatial, and interactional dynamics throughout the travel process. Results show that high-frequency commuters demonstrate the highest operational fluency, urban leisure travelers exhibit greater visual dependency and exploratory pauses, and special-care passengers are most affected by accessibility and feedback latency. Further analysis reveals a positive correlation between route complexity and interaction delay, highlighting discontinuous information feedback as a key experiential bottleneck. By jointly modeling one-way and interactive behaviors and linking group-specific patterns to concrete metro touchpoints, this research extends behavioral evaluation in metro systems and offers a novel behavior-based perspective along with empirical evidence for inclusive, adaptive, and human-centered service design.