The role of privacy design in office environments: Implications for stress level, spatial perception, and work performance using Hybrid immersive Virtual Environment

The expansion of digital commerce in Indonesia has reshaped the way local creative brands compete in online marketplaces. Although platforms such as Tokopedia enable sellers to reach a wider audience, maintaining customer satisfaction has become increasingly challenging due to market saturation. KORIGENGI is a local brand specializing in otaku-themed merchandise that operates through Tokopedia, yet its competitive position remains weaker than that of several rival stores. This study aims to analyze how product quality, price perception, and distribution performance influence customer satisfaction with KORIGENGI products on Tokopedia. This research applies a quantitative approach using survey data collected from customers who have previously purchased KORIGENGI products. Structured questionnaires were distributed online and measured using a Likert scale. The collected data were examined through instrument testing, classical assumption testing, and multiple linear regression analysis. The findings indicate that product quality, price, and distribution exert positive and statistically significant effects on customer satisfaction. When examined simultaneously, these variables collectively explain the variations in customer satisfaction. Product quality was the most influential factor, followed by price and distribution. The results highlight the importance of delivering high-quality products, applying appropriate pricing strategies, and ensuring reliable distribution processes to enhance customer satisfaction in competitive e-commerce environments.

Inspired by human skin, electronic skin (e-skin) integrates multidisciplinary technologies from materials engineering to microelectronics. It aims to replicate the skin's ability to perceive pressure, temperature, and humidity while also exhibiting excellent biocompatibility. As an emerging technology, e-skin holds significant promise across diverse fields, including industry, medicine, the military, and robotics. This review summarizes recent progress in the structural design of e-skin, which is a pivotal factor enabling breakthroughs in its functionality and performance. The e-skin structural design strategies are classified into three categories: skin-like perception regulation and performance enhancement, conformal interface stabilization design, and beyond-skin functionality design. These strategies facilitate skin-like multimodal sensing, stable human-machine interfaces, and capabilities exceeding those of biological skin, respectively. Current challenges and future prospects for e-skin development are also discussed.

This paper proposes E-MOTE (Emotion-aware Teacher Education Framework), an ethically grounded conceptual model aimed at enhancing teacher education through the integrated use of the Facial Action Coding System (FACS), Artificial Intelligence (AI), and Virtual Reality (VR). As a conceptual and design-oriented proposal, E-MOTE is presented as a structured blueprint for future development and empirical validation, not as an implemented or evaluated system. Grounded in neuroscientific and educational research, E-MOTE seeks to strengthen teachers’ emotional awareness, teacher noticing, and social–emotional learning competencies. Rather than reporting empirical findings, this article offers a theoretically structured framework and an operational blueprint for the design of emotion-aware teacher training environments, establishing a structured foundation for future empirical validation. E-MOTE articulates three core contributions: (1) it clarifies the multi-layered construct of emotion-aware teaching by distinguishing between emotion detection, perception, awareness, and regulation; (2) it proposes an integrated AI–FACS–VR architecture for real-time and post hoc feedback on teachers’ perceptual performance; and (3) it outlines a staged experimental blueprint for future empirical validation under ethically governed conditions. As a design-oriented proposal, E-MOTE provides a structured foundation for cultivating emotionally responsive pedagogy and inclusive classroom management, supporting the development of perceptual micro-skills in teacher practice. Its distinctive contribution lies in proposing a shift from predominantly macro-behavioral simulation toward the deliberate cultivation of perceptual micro-skills through FACS-informed analytics integrated with AI-driven simulations.

Vibration, as one of the most prevalent environmental factors in human-machine interfaces, has been shown to adversely affect interaction efficiency and human behavior. How to alleviate the negative impact of vibration environment by design deserve to explore. We employed an icon visual search task and an interactive tap task to investigate the effects of graphical user interface, including icon border shape, line width, and complexity on users’ visual perception and touch interaction performance under different levels of vibration intensity. Results indicated that vibration intensity significantly impaired accuracy in both tasks and increased response time in the tap task, but not in visual search. Borderless icons significantly outperformed those with borders, and simpler icons showed better performance than complex ones. However, icon line width had no significant effect. These findings offer valuable guidance for designing graphical user interfaces in vibration-prone environments.

Abstract In response to the low detection accuracy and limited adaptability of algorithms caused by significant differences in target characteristics in multi-source dynamic target detection tasks for coal mine conveyors, this paper proposes a Lite-DSP-YOLO-P2 lightweight intelligent detection algorithm. Firstly, considering the differences in image quality and target properties between coal flow states and personnel unsafety scenarios, a differentiated data augmentation strategy is adopted. For personnel unsafety images, a combination of classical augmentation and GridMask is employed to enhance the detection of occluded targets. For coal flow images, an improved DeblurGAN-v2 is used for deblurring prior to classical augmentation, thereby improving structural clarity and detection accuracy. Secondly, to enhance the algorithm's perception of small targets and complex backgrounds, a P2 detection layer is constructed based on the Dynamic Multi-scale Fusion and Triple Feature Encoder (DyMsF-TFE), which integrates shallow and deep features to improve multi-scale representation capability. Meanwhile, a Lightweight Shared Detail Enhanced-convolutional Detection Head (LSDEcDH) is designed, incorporating Group Normalization (GN) and Detail-enhanced Convolution (DeC) to reduce parameters while improving localization accuracy. Finally, the Layer-Adaptive Magnitude-based Pruning (LAMP) method is applied to compress the model structure, achieving a better balance between detection performance and computational complexity, thus enhancing its applicability and efficiency in resource-constrained environments. Experimental results show the differentiated data augmentation strategy significantly improves the quality and diversity of training samples, and enhances the algorithm's perception and detection performance for multi-source dynamic targets in complex scenarios. The proposed Lite-DSP-YOLO-P2 achieves a precision of 95.2%, recall of 90.9%, mAP0.5 of 95.1%, and mAP0.5:0.95 of 67.0%, which represents improvements of 3.5%, 1.1%, 2.7%, and 1.5%, respectively, compared to the YOLOv8n baseline. Furthermore, the algorithm's parameters are reduced by 24.6%, and after applying LAMP pruning, both the parameters and model size are reduced by 51.9% and 39.7%, respectively, while maintaining detection accuracy.

This study investigates how optical information and dynamical constraints influence movement production and perception. In Experiment 1, 16 volunteers walked or performed a Y-balance movement with and without sight on sturdy or foam-padded floors. The optical information and force environment affected the participants’ kinematics, such as stride duration, stride length, stride width, gait speed, joint ranges of motion for walking, total movement duration, and joint ranges of motion for Y-balance. Naïve observers then watched these movements on a point-light display and distinguished movements executed under different optical information (Experiment 2) and force environment (Experiment 3) conditions. They were able to pick out movements performed without sight, especially for those performed on a padded floor; they were also able to discriminate movements performed on different supporting surfaces, especially when the actors were blindfolded. Thus, discriminating movement conditions from point-light displays was possible, and better with higher kinematic variability. Logistic regressions showed discriminating movements relied on the movement kinematics that varied the most between conditions. This information was valid and useful regardless of viewing perspective; that is, whether the walking and Y-balance were displayed in the frontal or side view, the perceptual performance was equivalent. Thus, both optical information and dynamical constraints shape movement patterns in ways that are perceptible through the kinematic variations.

Motion speed is a salient cue for visual segmentation, yet how the visual system represents and differentiates multiple speeds remains unclear. Here, we investigated the encoding and decoding of multiple speeds. We first characterized the perceptual capacity of human and macaque subjects to segment overlapping stimuli moving at different speeds. We then determined how neurons in area MT of macaque monkeys represent multiple speeds. We found that the responses of MT neurons to two speeds showed a robust bias toward the faster speed component. This faster-speed bias occurred when both speeds were slow (≤20°/s) and diminished as stimulus speed increased. Our findings can be explained by a modified divisive normalization model, in which the weights for the speed components are proportional to the responses of a population of neurons (the weighting pool) with a broad range of speed preferences, elicited by the individual speeds. Regarding decoding, a classifier could distinguish MT responses to two speeds from those to a corresponding log-mean speed. We further found that it was possible to decode two speeds from the MT population response, supporting the theoretical framework of coding multiplicity in neuronal populations. The decoded speeds can account for perceptual performance in segmenting two speeds with a large (4x) but not a small (2x) separation. Our findings help define the neural coding rule of multiple speeds. The faster-speed bias in MT could benefit important behavioral tasks, such as figure-ground segregation, as figural objects tend to move faster than the background in the natural environment.

Motion speed is a salient cue for visual segmentation, yet how the visual system represents and differentiates multiple speeds remains unclear. Here, we investigated the encoding and decoding of multiple speeds. We first characterized the perceptual capacity of human and macaque subjects to segment overlapping stimuli moving at different speeds. We then determined how neurons in area MT of macaque monkeys represent multiple speeds. We found that the responses of MT neurons to two speeds showed a robust bias toward the faster speed component. This faster-speed bias occurred when both speeds were slow (≤20°/s) and diminished as stimulus speed increased. Our findings can be explained by a modified divisive normalization model, in which the weights for the speed components are proportional to the responses of a population of neurons (the weighting pool) with a broad range of speed preferences, elicited by the individual speeds. Regarding decoding, a classifier could distinguish MT responses to two speeds from those to a corresponding log-mean speed. We further found that it was possible to decode two speeds from the MT population response, supporting the theoretical framework of coding multiplicity in neuronal populations. The decoded speeds can account for perceptual performance in segmenting two speeds with a large (4x) but not a small (2x) separation. Our findings help define the neural coding rule of multiple speeds. The faster-speed bias in MT could benefit important behavioral tasks, such as figure-ground segregation, as figural objects tend to move faster than the background in the natural environment.

Motion speed is a salient cue for visual segmentation, yet how the visual system represents and differentiates multiple speeds remains unclear. Here, we investigated the encoding and decoding of multiple speeds. We first characterized the perceptual capacity of human and macaque subjects to segment overlapping stimuli moving at different speeds. We then determined how neurons in area MT of macaque monkeys represent multiple speeds. We found that the responses of MT neurons to two speeds showed a robust bias toward the faster speed component. This faster-speed bias occurred when both speeds were slow (≤20°/s) and diminished as stimulus speed increased. Our findings can be explained by a modified divisive normalization model, in which the weights for the speed components are proportional to the responses of a population of neurons (the weighting pool) with a broad range of speed preferences, elicited by the individual speeds. Regarding decoding, a classifier could distinguish MT responses to two speeds from those to a corresponding log-mean speed. We further found that it was possible to decode two speeds from the MT population response, supporting the theoretical framework of coding multiplicity in neuronal populations. The decoded speeds can account for perceptual performance in segmenting two speeds with a large (4x) but not a small (2x) separation. Our findings help define the neural coding rule of multiple speeds. The faster-speed bias in MT could benefit important behavioral tasks, such as figure-ground segregation, as figural objects tend to move faster than the background in the natural environment.

This study explores the possible effects of incorporating Polya's Problem-Solving Method on Bukidnon State University Secondary Laboratory School (SLS) students' academic performance in Mathematics. This intervention study is intended to untangle significant information that will inform the educational field to understand SLS students' academic performance. This study aims to analyze whether incorporating Polya's Problem-Solving Method improves the students' academic performance in mathematics and perception towards problem solving. A quantitative one-group pretest-posttest research design approach was employed using survey questionnaires. The results show that incorporating Polya's Problem-Solving Method significantly improved students' academic performance and demonstrated increased Higher Order Thinking Skills in solving mathematical problems. The findings suggest that integrating Polya's Problem-Solving Method into the curriculum can promote autonomous learning and enhance higher-order thinking Skills in Grade 7 students. Further research is recommended to explore the effectiveness of combining this method with other instructional strategies to improve students’ problem-solving skills and academic achievement.

Relationships between interoceptive accuracy/attention and well-being: Insights from heartbeat and temperature perception.

This study examines the impact of rainfall on the perception performance of a LiDAR-based cooperative driving infrastructure system and presents a weather-aware performance evaluation methodology. Controlled rainfall experiments were conducted at the SOC Demonstration Center in Yeoncheon, where combinations of rainfall intensity and vehicle approach speed were configured to create nine test scenarios. Each scenario was executed repeatedly under both clear and rainfall conditions. The evaluation focused on key performance indicators (KPIs) including object detection rate, tracking continuity, distance estimation accuracy, and position accuracy. Under clear conditions, the LiDAR infrastructure system exhibited stable perception performance, achieving an average object detection rate above 98% across all scenarios and maintaining consistent tracking continuity. In contrast, rainfall conditions caused substantial degradation: detection rates dropped to approximately 40%, ID continuity was reduced by more than 90% relative to clear-weather baselines, and position accuracy deteriorated from a mean error of 0.22 m to 0.55 m, with a maximum error of 0.83 m. These degradations were primarily driven by rainfall-induced laser attenuation, back-scattering, reduced point-cloud density, and the resulting deformation of object clusters that led to centroid estimation instability. The results demonstrate that rainfall imposes significant adverse effects on roadside LiDAR perception, triggering cascading performance degradation in detection reliability, tracking stability, and spatial accuracy. Existing C-ITS and cooperative perception standards predominantly emphasize communication and interoperability layers, and therefore lack systematic sensor-level evaluation procedures that account for adverse weather. The methodology proposed in this study provides foundational guidance for developing standardized, weather-robust performance evaluation protocols for cooperative perception infrastructure in real-world operating environments.

This study investigates the usability and user experience of integrating 3D visualizations and short 3D animations into the website interface of a marketing agency. The research evaluates how computer-generated 3D elements influence user interaction, perception, and overall website performance. The experimental phase documents the design process, including software selection, web interface development, and the creation of 3D assets. Target user groups were defined and represented through personas, which informed the specification of website functionality, content structure, and information architecture. Wireframes were designed to determine the spatial organization of interface components, while parallel development focused on producing 3D models and animations intended for web deployment. Usability testing was conducted using the standardized User Experience Questionnaire (UEQ) supplemented with domain-specific questions. Participants interacted with a functional prototype to assess system usability, visual engagement, and navigational efficiency. The findings provide an analysis of user experience outcomes associated with the incorporation of 3D elements into web interfaces. The results offer practical guidance and best-practice recommendations for designers, developers, and content creators seeking to implement 3D visual content as a functional and aesthetic component of modern website design.

PurposeVisual function testing in retinal prosthesis users relies on repetitive psychophysical tasks that are cognitively demanding and fatiguing. Gamification may increase engagement, but its effects on perceptual performance in implanted users remain unclear.MethodsThree Argus II users completed circle localization and motion direction discrimination in clinical and gamified versions. Visual stimuli, trial structure, and response requirements were matched within each participant; gamified versions added scoring, background music, and affectively framed end-of-trial auditory feedback. Difficulty and response format were calibrated to individual abilities (8AFC for two participants; 4AFC restricted to cardinal directions for one participant).ResultsGamification improved accuracy and reduced angular error in localization but did not improve motion discrimination. Effects were task-dependent and varied across participants, with reduced precision in the gamified motion task for one user. Participants preferred gamified localization and reported higher enjoyment and sustained attention; responses to gamified motion were mixed.ConclusionsGamification can influence measured performance and user experience in prosthetic vision testing, but benefits are not universal and depend on task demands and cognitive load, indicating that engagement can affect outcomes in tests often treated as objective.Translational relevancePersonalized, engagement-aware gamified tools with adaptive difficulty may improve the usability and scalability of prosthetic vision assessment and rehabilitation, including at-home training.

The Panchayati Raj system plays a vital role in strengthening grassroots democracy and rural development in India. Sarpanch and Deputy Sarpanch, as key functionaries of Gram Panchayats, are central to planning and implementing various development initiatives. The present study was conducted in Navsari district of South Gujarat to assess the role perception and performance of these leaders. A total of 120 respondents, comprising 60 sarpanch and 60 deputy sarpanch from 60 randomly selected Gram Panchayats across six talukas, were interviewed using a structured schedule. Data were statistically analyzed by working out frequency, percentage, mean, standard deviation and correlation. Results revealed that a majority of respondents (sarpanch and deputy sarpanch) were female (55, 56.57 %) belonged to the middle age group (48.33, 58.33 %), had secondary-level education (58.33, 61.66 %) and engaged primarily in farming and allied occupations (45, 40 %). Both sarpanch and deputy sarpanch exhibited moderate levels of role perception (58.33, 65 %) and role performance (51.66 % for both). Education, mass media exposure, cosmo-politeness, self-confidence, social participation and participation in extension activities were significantly associated with role perception and performance of sarpanch (r = 0.40–0.59**) and deputy sarpanch (r = 0.36–0.72**). The findings highlight the importance of capacity building and training for enhancing leadership effectiveness at the village level. Strengthening these attributes among elected representatives can lead to more effective governance and holistic rural development.

This study investigated the effects of daily hot water immersion after exercise in cool conditions on the physiological, perceptual, and endurance performance responses of well-trained cyclists in warm and hot conditions. Sixteen male cyclists completed a six-day intervention involving daily cycling exercise for 40min at 50% of their peak power output at 13.9 ± 0.1°C, 43.9 ± 5.9% RH followed immediately by either hot water immersion (HWI; n = 8) or thermoneutral water immersion (CON; n = 8) for 40min. At baseline and post-intervention, participants completed two 30-min continuous cycling tests followed by 20-km time-trial tests on two different days (first at 27.0 ± 0.2°C, 42.2 ± 3.3% RH and 48h later at 35.0 ± 1.2°C, 35.5 ± 3.4% RH). Hot water immersion decreased peak heart rate (p = 0.03), peak thermal sensation (p < 0.01), and peak rating of perceived exertion (p = 0.02) during the 30-min continuous test at 27°C, and also decreased peak thermal sensation (p = 0.03) and peak rating of perceived exertion (p = 0.01) during the same test at 35°C. None of these variables was altered in the CON group. The HWI intervention did not affect the time-trial performance in either condition. The findings that post-exercise hot water immersion for six consecutive days had no significant impact on the functioning of the cardiovascular and thermoregulatory systems or endurance performance in the heat suggest that this heat acclimation protocol cannot serve as an effective alternative to active heat acclimation in endurance-trained male individuals.

Abstract Situational awareness is critical to maritime safety, particularly with the rise of autonomous ships, which pose risks such as automation bias and complacency. Traditional assessment methods using ships or simulators are resource-intensive and hinder research progress. To address this, this paper introduces and demonstrates a conceptual method that integrates ship operational videos, eye-tracking technology, and image processing to analyze seafarers’ gaze behavior. This approach enables both qualitative and quantitative assessment of perception, a key component of situational awareness. Its utility is demonstrated through a proof-of-concept comparison of three seafarers with varying expertise during entering and leaving port operations. The results show that the method effectively captures and quantifies gaze differences between the seafarers, offering a practical, scalable way to assess perceptual performance in maritime contexts.

This paper is dedicated to solving the environmental perception system problem of unmanned surface vehicles (USVs) experiencing adverse sea conditions and complex mission scenarios. First, the functionalities and characteristics of each subsystem in the USV environmental perception system under different mission scenarios are analyzed, and an efficient and stable environmental perception system is designed. Second, the static and dynamic characteristics of the sea–sky line are investigated, along with the impacts on each subsystem of the environmental perception system when the USV experiences six-degree-of-freedom motion on the sea surface. Based on the above analysis, a sea–sky line detection method based on the radar–electro-optical system is designed. This method utilizes the features of the radar and electro-optical subsystems to redefine the region of interest, effectively suppressing interference from non-sea–sky line edges, thereby improving detection efficiency and accuracy. Furthermore, a sea–sky line-based target detection algorithm is proposed, which confines the search area to the vicinity of the detected sea–sky line, significantly reducing false detections caused by sea clutter and noise. Sea trials demonstrate that the proposed method enhances the accuracy and real-time performance of USV environmental perception. The proposed systematic approach offers a practical solution for improving the robustness of USV environmental perception in complex marine environments. Sea trials have shown that the method improves the effectiveness of target information by 3.61%.

ABSTRACT The purpose of this study was to examine the effects of sleep inertia following naps of two durations on cognitive performance (reaction time and decision making), physical performance (countermovement jump (CMJ) and handgrip strength (HG)), and perceptual responses (i.e. sleepiness, fatigue, and readiness to perform). In a randomized, counterbalanced, crossover design, 17 physically active participants (9 males, 8 females, age: 23 ± 2 y) completed three conditions: no-nap (NN), a 25-min nap opportunity (N25), and a 90-min nap opportunity (N90). Naps were conducted in a controlled laboratory setting using a sleep pod. Nighttime sleep prior to each session was tracked using a wrist-worn actigraph, and sleep during naps was assessed using a forehead mounted EEG device. Following each condition, participants completed four 30-min test batteries within the first two post-nap hours (T1: 0–30 min post-nap, T2: 30–60 min post-nap, T3: 60–90 min post-nap, and T4: 90–120 min post-nap), starting at 15:00 h. Each session included assessments of sleepiness, fatigue, readiness to perform, cognitive function (psychomotor vigilance task and Simon task (ST)), and physical performance (HG and CMJ). All performance markers were impaired at T1 compared to the subsequent time points (p < 0.05) for both nap durations, with more pronounced sleep inertia after N90 (p < 0.05) for sleepiness, readiness to perform, HG, and accuracy during ST. However, most performance markers improved after both N25 and N90 at T3 (p < 0.05), with more improvement observed after N90 at T4 compared to NN and N25 in sleepiness, fatigue, reaction time during ST, and HG (p < 0.05). In conclusion, at least one hour is required for sleep inertia to dissipate following N25 and N90, with significant improvements in perceptual, cognitive, and physical performance observed at 1–2 h post napping.