Search Results (118)

Biometric authentication using human physiological and behavioral characteristics has been widely adopted, with speaker verification attracting attention due to its convenience and noncontact nature. Conventional speaker verification systems remain vulnerable to spoofing attacks, however, often requiring integration with separate spoofed speech detection models. In this work, the authors propose an emotion-dependent speaker verification system that integrates speaker characteristics with emotional speech characteristics, enhancing robustness against spoofed speech without relying on additional classification models. By comparing acoustic characteristics of emotions between registered and verification speech using pretrained models, the proposed method reduces the equal error rate compared to conventional speaker verification systems, achieving an average equal error rate of 1.13% for speaker verification and 17.7% for the anti-spoofing task. Researchers additionally conducted a user evaluation experiment to assess the usability of emotion-dependent speaker verification. The results indicate that although emotion-dependent authentication was initially cognitively stressful, participants adapted over time, and the burden was significantly reduced after three sessions. Among the tested emotions (anger, joy, sadness, and neutral), sadness proved most effective, with stable scores, a low error rate, and minimal user strain. These findings suggest that neutral speech is not always the optimal choice for speaker verification and that well-designed emotion-dependent authentication can offer a practical and robust security solution. Full article

Background: Undergraduate nursing students (UNSs) often enter clinical training just as they are still mastering the emotional labor of the profession. In Nepal, where teaching hierarchies discourage upward dialogue and hospitals routinely struggle with overcrowding, supply shortages, and outward nurse migration, these learners confront a distinct, under-documented burden of psychological distress. Objective: This study examines how UNSs interpret, negotiate, and cope with the mental health challenges that arise at the intersection of cultural deference, resource scarcity, and migration-fueled uncertainty. Methods: A qualitative design employing reflexive thematic analysis (RTA), guided by the Reflexive Thematic Analysis Reporting Guidelines (RTARG), was used. Fifteen second-, third-, and fourth-year Bachelor of Science in Nursing students at a major urban tertiary institution in Nepal were purposively recruited via on-campus digital flyers and brief in-class announcements that directed students (by QR code) to a secure sign-up form. Participants then completed semi-structured interviews; audio files were transcribed verbatim and iteratively analyzed through an inductive, reflexive coding process to ensure methodological rigor. Results: Four themes portray a continuum from silenced struggle to systemic constraint. First, Shrouded Voices, Quiet Connections captures how students confide only in trusted peers, fearing that formal disclosure could be perceived as weakness or incompetence. Second, Performing Resilience: Masking Authentic Struggles describes the institutional narratives of “strong nurses” that drive students to suppress anxiety, adopting scripted positivity to satisfy assessment expectations. Third, Power, Hierarchy, and the Weight of Tradition reveals that strict authority gradients inhibit questions in classrooms and clinical placements, leaving stress unvoiced and unaddressed. Finally, Overshadowed by Systemic Realities shows how chronic understaffing, equipment shortages, and patient poverty compel students to prioritize patients’ hardships, normalizing self-neglect. Conclusions: Psychological distress among Nepalese UNSs is not an individual failing but a product of structural silence and resource poverty. Educators and policymakers must move beyond resilience-only rhetoric toward concrete reforms that dismantle punitive hierarchies, create confidential support avenues, and embed collaborative pedagogy. Institutional accountability—through regulated workloads, faculty-endorsed wellbeing forums, and systematic mentoring—can shift mental health care from a private struggle to a shared professional responsibility. Multi-site studies across low- and middle-income countries are now essential for testing such system-level interventions and building a globally resilient, compassionate nursing workforce. Full article

The scientific study of emotion remains fraught with conceptual ambiguity, methodological limitations, and epistemological blind spots. This theoretical paper argues that existing paradigms frequently capture synthetic rather than natural emotional states—those shaped by social expectations, cognitive scripting, and performance under observation. We propose a conceptual framework that distinguishes natural emotion—spontaneous, embodied, and interoceptively grounded—from synthetic forms that are adaptive, context-driven, and often unconsciously rehearsed. These reactions often involve emotional scripts rather than genuine, spontaneous affective experiences. Drawing on insights from affective neuroscience, psychological measurement, artificial intelligence, and neurodiversity, we examine how widely used tools such as EEG, polygraphy, and self-report instruments may capture emotional conformity rather than authenticity. We further explore how affective AI systems trained on socially filtered datasets risk replicating emotional performance rather than emotional truth. By recognizing neurodivergent expression as a potential site of emotional transparency, we challenge dominant models of emotional normalcy and propose a five-step agenda for reorienting emotion research toward authenticity, ecological validity, and inclusivity. This post-synthetic framework invites a redefinition of emotion that is conceptually rigorous, methodologically nuanced, and ethically inclusive of human affective diversity. Full article

Accurately discerning the authenticity of facial expressions is crucial for inferring others’ psychological states and behavioral intentions, particularly in shaping interpersonal trust dynamics among elementary school children. While existing literature remains inconclusive regarding school-aged children’s capability to differentiate between genuine and posed facial expressions, this study employed happy and sad facial stimuli to systematically evaluate their discrimination accuracy. Parallel to behavioral measures, children’s gaze patterns during authenticity judgments were recorded using eye-tracking technology. Results revealed that participants demonstrated higher accuracy in identifying genuine versus posed happy expressions, whereas discrimination of sad expressions proved more challenging, especially among lower-grade students. Overall, facial expression recognition accuracy exhibited a positive correlation with grade progression, with visual attention predominantly allocated to the Eye-region. Notably, no grade-dependent differences emerged in region-specific gaze preferences. These findings suggest that school-aged children display emotion-specific recognition competencies, while improvements in accuracy operate independently of gaze strategy development. Full article

This study explores the psychological and social impacts of the forced use of self-service technologies (SSTs) in South Korea’s hospitality and tourism sectors, focusing on perceptions of service dehumanization among different age groups. Grounded in symbolic interactionism theory, the research aims to uncover how reduced interpersonal interaction affects perceived service quality and emotional response. A quantitative approach was employed using data collected from 300 Korean adults (150 older adults and 150 young adults). The study utilized the PROCESS Macro to test mediation effects of reduced human contact, empathy, and authenticity, as well as the moderating role of employee presence in shaping dehumanization perceptions. The results indicate that the mandatory use of SSTs significantly diminishes the perceived social value of service encounters, thereby increasing feelings of dehumanization. This effect is mediated by a reduction in human contact, empathy, and authenticity. Moreover, the presence of employees moderates this relationship, particularly intensifying dehumanization perceptions among older adult participants. Gender was not a significant factor in these perceptions. These findings suggest that while SSTs may improve operational efficiency, their forced implementation can negatively impact customer experience, especially for older adults. Hospitality and tourism providers should consider hybrid service models that maintain optional human interaction to mitigate adverse psychological effects. This study contributes to the limited research on SSTs and service dehumanization by integrating symbolic interactionism theory and highlighting the moderating role of employee presence. It offers novel insights into age-related differences in SST acceptance and the socio-emotional costs of automation in service contexts. Full article

As an introductory core course in computer science and related fields, “Fundamentals of Programming” has always faced many challenges in stimulating students’ interest in learning and cultivating their practical coding abilities. The traditional teaching model often fails to effectively connect theoretical knowledge with practical applications, resulting in a low retention rate of students’ learning and a weak ability to solve practical problems. Digital twin (DT) technology offers a novel approach to addressing these challenges by creating dynamic, virtual replicas of physical systems with real-time, interactive capabilities. This study explores DT integration in programming teaching and its impact on learning engagement (behavioral, cognitive, emotional) and skill acquisition (syntax, algorithm design, debugging). A quasi-experimental design was employed to study 135 first-year undergraduate students, divided into an experimental group (n = 90) using a DT-based learning environment and a control group (n = 45) receiving traditional instruction. Quantitative data analysis was conducted on participation surveys, planning evaluations, and qualitative feedback. The results showed that, compared with the control group, the DT group exhibited a higher level of sustained participation (p < 0.01) and achieved better results in actual coding tasks (p < 0.05). Students with limited coding experience showed the most significant progress in algorithmic thinking. The findings highlight that digital twin technology significantly enhances engagement and skill acquisition in introductory programming, particularly benefiting novice learners through immersive, theory-aligned experiences. This study establishes a new paradigm for introductory programming education by addressing two critical gaps in digital twin applications: (1) differential effects on students with varying prior knowledge (engagement/skill acquisition) and (2) pedagogical mechanisms in conceptual visualization and authentic context creation. Full article

The presence of Internet of Things (IoT) devices in modern working and living environments is growing rapidly. The data collected in such environments enable us to model users’ behaviour and consequently identify and authenticate them. However, these data may contain information about the user’s current activity, emotional state, or other aspects that are not relevant for authentication. In this work, we employ adversarial deep learning techniques to remove privacy-revealing information from the data while keeping the authentication performance levels almost intact. Furthermore, we develop and apply various techniques to offload the computationally weak edge devices that are part of the machine learning pipeline at training and inference time. Our experiments, conducted on two multimodal IoT datasets, show that P²ESA can be efficiently deployed and trained, and with user identification rates of between 75.85% and 93.31% (c.f. 6.67% baseline), can represent a promising support solution for authentication, while simultaneously fully obfuscating sensitive information. Full article

In today’s competitive environment of online service industries, particularly e-commerce, meeting consumer expectations is essential for service providers to ensure service quality. However, service failures are unavoidable, leading to unfavorable consequences for businesses. Understanding the mechanisms for customer recovery after negative service experiences is crucial. Using cognitive–emotional personality systems theory and benign violation theory, this study constructed a theoretical model. A total of 351 samples were collected through a situational simulation experiment for a linear regression analysis. A self-mocking response strategy positively influenced brand trust through perceived brand authenticity regarding the dimensions of credibility, integrity, and symbolism. Simultaneously, brand trust was identified as a key driver of post-recovery satisfaction. This study proposes a chain mediation model, which incorporates perceived authenticity and brand trust, to fully comprehend the mechanisms underlying consumers’ satisfaction after service recovery. Our findings provide empirical evidence for the effects of self-mockery on post-recovery satisfaction, as well as suggestions for marketers seeking efficient means to meet consumers’ emotional and cognitive demands during service recovery situations. Full article

Templestay programs in South Korea represent a unique convergence of Buddhist ritual, cultural immersion, and wellness tourism. While often treated as niche cultural experiences, their broader significance within sustainable wellness tourism remains underexplored. This study examines participant reflections from the Beomeosa Templestay program through thematic analysis of over 600 reviews sourced from TripAdvisor, Google Reviews, and handwritten guestbooks. Using a triangulated framework combining Grounded Theory, Symbolic Interactionism, and the Wellness Tourism Model, the research identifies four recurring experiential themes: spiritual development, emotional healing, cultural immersion, and conscious consumption. Findings reveal cross-cultural variations: non-Korean participants emphasized spiritual exploration and cultural learning, while Korean participants prioritized emotional renewal and reconnection with heritage. Yet, across all groups, participants reported transformative outcomes, including heightened clarity, inner calm, and enhanced self-awareness. These results suggest that Templestays serve as accessible, culturally grounded wellness retreats that align with rising global demand for intentional, mindful travel. This study contributes to sustainable tourism scholarship by framing Templestays as low-impact, spiritually resonant alternatives to commercialized wellness retreats. Practical recommendations are offered to expand participation while maintaining program authenticity and safeguarding the spiritual and cultural integrity of monastic hosts in an increasingly globalized wellness landscape. Full article

This study examines the psychological mechanisms through which BTS’s perceived star attributes—expertise, authenticity, likability, and similarity—influence fan loyalty within fandom-driven tourism. Anchored in activity theory and content theory of motivation, the proposed model identifies psychological need fulfillment and emotional satisfaction as sequential mediators linking celebrity perception to loyalty behaviors. Data were obtained from 916 BTS fans across six English-speaking countries via a structured online survey. To test the hypothesized relationships, Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed. Results demonstrate that perceived star attributes significantly enhance psychological need fulfillment, which subsequently predicts emotional satisfaction and loyalty. Additionally, the attributes exert direct effects on emotional satisfaction, supporting both reflective and intuitive engagement pathways. All hypothesized paths were statistically significant, and the model exhibited strong overall fit (SRMR = 0.039; NFI = 0.875). Theoretically, this study advances loyalty research by foregrounding the roles of symbolic consumption, emotional resonance, and identity-based alignment in global fandom contexts. Practically, the findings offer insights for tourism marketers, destination planners, and entertainment brands seeking to design emotionally immersive, narrative-rich tourism experiences. Recommendations are provided for developing BTS-themed content aligned with fans’ identity motivations to foster sustained emotional engagement and destination loyalty. Full article

Masstige fashion brands present a promising alternative to both luxury and fast fashion in the context of sustainability, offering an affordable yet prestigious option. However, these brands face the challenge of leveraging digital transformation tools while balancing prestige and accessibility. With its visual appeal, interactive features, and daily usage, Instagram Stories is a highly engaging communication tool for masstige brands. Despite its importance, ephemeral brand communication remains an underexplored area. This study investigates how young consumers interpret and decode Instagram Stories featuring human models from masstige fashion brands that represent identitary values Sexuality and Seduction, Seasonality, and Renewal. Using mind mapping and focus group discussions with 75 frequent Instagram users, findings reveal that audiences actively reinterpret brand messages, sometimes reshaping their intended meaning. Highly stylized celebrities led to skepticism or disengagement, while authentic, everyday portrayals fostered positive engagement. Sexualized imagery was often reframed as functional rather than aspirational. The study reveals that while brands aim to communicate identitary values such as Sexuality and Seduction, these are usually reinterpreted or even rejected by users in favor of values like comfort, simplicity, or emotional authenticity. Conversely, values like Seasonality, Renewal, and Quality were more consistently recognized and positively decoded, suggesting a more substantial alignment between brand encoding and audience perception in those domains. Full article

Recent advancements in urban vitality space design reflect increasing academic attention to emotional experience dimensions, paralleled by the emergence of AI-based generative technology as a transformative tool for systematically exploring the emotional attachment potential in preliminary designs. To effectively utilize AI-generative design results for spatial vitality creation and evaluation, exploring whether generated spaces respond to people’s emotional demands is necessary. This study establishes a comparative framework analyzing emotional attachment characteristics between LoRA-generated spatial designs and the real urban vitality space, using the representative case of THE BOX in Chaoyang, Beijing. Empirical data were collected through structured on-site surveys with 115 validated participants, enabling a comprehensive emotional attachment evaluation. SPSS 26.0 was employed for multi-dimensional analyses, encompassing aggregate attachment intensity, dimensional differentiation, and correlation mapping. Key findings reveal that while both generative and original spatial representations elicit measurable positive responses, AI-generated designs demonstrate a limited capacity to replicate the authentic three-dimensional experiential qualities inherent to physical environments, particularly regarding structural articulation and material tactility. Furthermore, significant deficiencies persist in the generative design’s cultural semiotic expression and visual-interactive spatial legibility, resulting in diminished user satisfaction. The analysis reveals that LoRA-generated spatial solutions require strategic enhancements in dynamic visual hierarchy, interactive integration, chromatic optimization, and material fidelity to bridge this experiential gap. These insights suggest viable pathways for integrating generative AI methodologies with conventional urban design practices, potentially enabling more sophisticated hybrid approaches that synergize digital innovation with built environment realities to cultivate enriched multisensory spatial experiences. Full article

Rural agricultural markets face unique challenges, yet neuromarketing applications in this sector are understudied. This systematic review investigates how neuroscience has been applied to shape marketing narratives for rural agricultural producers. The objectives were to catalog relevant studies, identify key themes using inductive thematic synthesis, and derive practical implications for rural marketing strategy and future research. We systematically searched English-language, peer-reviewed studies published between 2016 and 2024 across multiple academic databases, following PRISMA guidelines. Two independent reviewers screened the records, resulting in the inclusion of 20 studies. Key data from each study were extracted and synthesized using an inductive thematic analysis approach. The synthesis revealed several recurrent findings. First, in terms of social and community context, farmers showed greater trust and engagement with familiar local buyers than with distant corporations, indicating that local relationships strongly influence producer behavior. Second, regarding product and narrative attributes, marketing narratives that emphasized local provenance, organic or sustainable production, and ethical values such as animal welfare and environmental sustainability resonated strongly with rural consumers. Third, sensory and emotional cues particularly visual elements and storytelling techniques including color, imagery, and packaging design consistently enhanced consumer attention and engagement. Overall, these neuroscience-informed themes suggest that marketing narratives emphasizing authenticity, trust-building, and community values can effectively strengthen rural agricultural marketing. This review provides neuroscience-informed interpretations of key rural marketing challenges, drawing on dual-process theory and consumer decision models for applying neuromarketing insights in this context. Practically, rural producers can leverage these findings by designing marketing messages and packaging that highlight local identity and ethical values, thereby building consumer trust and loyalty. The review also highlights gaps such as the need for more field-based neuromarketing studies and suggests directions for future research, offering guidance for both scholars and practitioners working at the intersection of neuroscience and rural consumer behavior. Full article

As a crucial component of cultural heritage, industrial heritage possesses considerable cultural, historical, and economic significance. The key challenge for industrial heritage sites is to foster eco-conscious actions among visitors while boosting tourism spending. Based on the S-O-R theory, we constructed a relationship model between authenticity, place attachment and environmental responsibility behavior through structural equation modeling and tested it with the survey data of tourists in Maoming open-pit mine ecological park. Findings reveal that both the object-related authenticity and the existential authenticity of the experience enhance the sense of reliance and belonging to the place, with the former also directly promoting visitors’ eco-conscious actions. In contrast, experiential authenticity does not exert a direct effect on eco-conscious actions. The sense of place reliance and identity are found to be significantly and positively linked to eco-conscious behavior. Furthermore, place reliance and identity act as intermediaries in the relationship between object authenticity, experiential authenticity, and eco-conscious behavior, serving as a sequential mediating factor. The study suggests strategies such as augmenting financial support to preserve the authenticity of the site, prioritizing the enhancement of infrastructure and the creation of cultural offerings to elicit emotional responses, and reinforcing emotional bonds to encourage eco-conscious actions. Full article

Access control systems protect homes and businesses in the continually evolving security industry. This paper designs and implements a Raspberry Pi-based facial recognition door lock system using artificial intelligence and computer vision for reliability, efficiency, and usability. With the Raspberry Pi as its CPU, the system uses facial recognition for authentication. A camera module for real-time image capturing, a relay module for solenoid lock control, and OpenCV for image processing are essential. The system uses the DeepFace library to detect user emotions and adaptive learning to improve recognition accuracy for approved users. The device also adapts to poor lighting and distances, and it sends real-time remote monitoring messages. Some of the most important things that have been achieved include adaptive facial recognition, ensuring that the system changes as it is used, and integrating real-time notifications and emotion detection without any problems. Face recognition worked well in many settings. Modular architecture facilitated hardware–software integration and scalability for various applications. In conclusion, this study created an intelligent facial recognition door lock system using Raspberry Pi hardware and open-source software libraries. The system addresses traditional access control limits and is practical, scalable, and inexpensive, demonstrating biometric technology’s potential in modern security systems. Full article