Search Results (81)

Advances in technology and changes in the way people entertain themselves have made video games a cultural agent on a par with more traditional games, including language learning. In addition, the use of video games in education is becoming increasingly common and numerous benefits associated with their use have been discovered. The aim of this article is to analyze the search trends in studies dealing with the use of video games in language learning. To this end, a bibliometric analysis was carried out by applying the traditional laws of bibliometrics (Price’s law, Bradford’s law of concentration, Lotka’s law, Zipf’s law and h-index) to documents published in journals indexed in the Core Collection of the Web of Science (WoS). Annual publications between 2009 and 2022 show an exponential growth R2 = 86%. The journals with the most publications are Computer assisted language learning (Taylor & Francis) and Computers and Education (Elsevier). Jie Chi-Yang and Gwo Jen-Hwan were the most cited authors. The United States and Taiwan were the countries with the highest scientific output. The use of video games in language learning has been of particular interest in recent years, with benefits found for students who use them in their classes, although more research is needed to establish criteria and requirements for each video game for its intended purpose. Full article

Once marketed as smoking cessation tools, e-cigarettes are used by adolescents mainly for entertainment, driven by aggressive marketing, appealing flavors, and safer alternatives to smoking. This study analyzes data from the National Youth Tobacco Survey (NYTS) to explore trends in adolescent perceptions and usage patterns of e-cigarettes from 2011 to 2023, focusing on their dual roles as cessation aids and recreational products. Cross-sectional data from the NYTS over four years (2011: N = 18,866; 2015: N = 17,711; 2019: N = 19,018; 2023: N = 22,069) formed the foundation of this study. This study investigated demographic trends, usage frequency, initial and future use patterns, and quitting behavior. Descriptive statistics and latent class analysis (LCA) were employed to examine adolescent e-cigarette use patterns, with statistical significance determined at p < 0.05. The reasons for using e-cigarettes have changed significantly over the years because of family or friends. In all years (2015–2023), use for smoking cessation dropped significantly (2.33% in 2023 vs. 6.95% in 2015). In 2023, 38% wanted to quit using e-cigarettes within 30 days, and 25% attempted to quit at least 10 times. Flavored e-cigarette users were more than twice as likely to consider quitting compared to those not interested in flavors (OR = 2.64). Our findings highlight a significant decrease in the use of e-cigarettes for cessation, with a corresponding increase in recreational use over time. These trends emphasize the urgency of implementing interventions to mitigate nicotine addiction and its associated health risks among adolescents. Adolescent e-cigarette use has transitioned from being primarily driven by cessation efforts to recreational purposes, largely influenced by appealing flavors and social factors such as peer influence, showing the need for stricter marketing regulations and targeted educational campaigns. Full article

This study investigates the influence of experiential programs (EPs) on enhancing consumer experience offerings at luxury resorts. EPs encompass a variety of activities, amenities, and services designed to immerse consumers in the local culture, scenery, and authenticity. The research focuses explicitly on EPs related to fitness, evening entertainment, children’s activities, and personalized experiences. By analyzing data from 30 resorts, significant trends and typologies within each category of EP emerged, highlighting the diverse ways in which resorts meet consumers’ desires for immersive and status-enhancing experiences. Valuable insights were gained through semi-structured interviews with two hoteliers, providing a deeper understanding of the strategic integration of EPs. Fitness EPs highlight activities, including hiking and yoga, whereas evening entertainment encompasses experiences like mixology, music, and astronomy education. For children, EPs prioritize cultural immersion through hands-on experiences, while personalized EPs—including romance packages and private dining—allow for consumer exclusivity. The research underscores how these EPs align with contemporary trends in conspicuous consumption, where luxury resorts leverage unique, high-quality, and culturally rich experiences to reinforce affluence and societal standing. The findings emphasize that EPs are a vital strategy for luxury resorts to differentiate themselves in a competitive market, enhancing consumer satisfaction, loyalty, and positive self-image. Full article

High Dynamic Range (HDR) image reconstruction has gained prominence in a wide range of fields; not only is it implemented in computer vision, but industries such as entertainment and medicine also benefit considerably from this technology due to its ability to capture and reproduce scenes with a greater variety of luminosities, extending conventional levels of perception. This article presents a review of the state of the art of HDR reconstruction methods based on deep learning, ranging from classical approaches that are still expressive and relevant to more recent proposals involving the advent of new architectures. The fundamental role of high-quality datasets and specific metrics in evaluating the performance of HDR algorithms is also discussed, as well as emphasizing the challenges inherent in capturing multiple exposures and dealing with artifacts. Finally, emerging trends and promising directions for overcoming current limitations and expanding the potential of HDR reconstruction in real-world scenarios are highlighted. Full article

This study investigates the evolving trends in social media usage in Pakistan across three key periods: pre-COVID-19, during COVID-19, and post-COVID-19. This research bases its analysis on data obtained from Stat Counter Global Stats to understand changes in user selection of platforms together with behavioral patterns and social consequences. To ensure validity and reliability, the data were cross-checked with publicly available statistics from individual social media platforms, ensuring consistency in reported usage trends. Facebook held the top spot on social media before the pandemic, yet YouTube together with Instagram and Twitter gained substantial growth from pandemic-era users seeking entertainment and information as well as social contact. Facebook resumed its leadership position following the pandemic period with Instagram and YouTube staying highly popular among users. This research shows Pakistan faces an ongoing digital disparity between metropolises and rural areas, thus requiring better Internet networks alongside digital education initiatives to overcome this gap. This research shows that social media platforms must deliver cultural-specific content together with features that address Pakistani user needs. This study recognizes mental health challenges from heavy social media usage, so it recommends platform-based tools establishing better online behavior practices. This paper proposes strategic guidance for policymakers and social media platforms to establish inclusive digital progress and achieve digital balance in Pakistan. Full article

In response to the global trend of population aging, the issue of providing elderly individuals suitable leisure and entertainment has become increasingly important. In this study, it aims to utilize artificial intelligence (AI) technology to offer the elderly with a healthy and enjoyable exercise and leisure experience. A human–machine interactive system is designed using computer vision, a subfield of AI, to promote positive physical adaptation for the elderly. The relevant literature on the needs of the elderly, technology, exercise, leisure, and AI techniques is reviewed. Case studies of interactive devices for exercise and leisure for the elderly, both domestically and internationally, are summarized to establish the prototype concept for system design. The proposed interactive exercise and leisure system is developed by integrating motion-sensing interfaces and real-time object detection using the YOLO algorithm. The system’s effectiveness is evaluated through questionnaire surveys and participant interviews, with the collected survey data analyzed statistically using IBM SPSS 26 and AMOS 23. Findings indicate that (1) AI technology provides new and enjoyable interactive experiences for the elderly’s exercise and leisure; (2) positive impacts are made on the elderly’s health and well-being; and (3) the system’s acceptance and attractiveness increase when elements related to personal experiences are incorporated into the system. Full article

The expansion of urban underground spaces has broadened the range of urban activities by accommodating functions such as transportation, retail, and entertainment. Underground shopping malls (USMs) have been widely developed as a sustainable strategy to expand urban space capacity, alleviate surface congestion, and optimize land-use efficiency. However, the development and utilization of USMs often neglect user-centered evaluations, risking mismatches between design outcomes and long-term sustainability goals such as energy efficiency, user retention, and spatial adaptability. Therefore, this study analyzes 12 typical USMs in Nanjing, China, based on environmental psychology principles, employing mixed-methods research that combines objective measurements of spatial elements with subjective user perception surveys to establish a regression model investigating correlations between USM spatial–physical environments and user comfort perception. The results show that users generally have a positive impression of the current underground environment, but there are significant differences in their subjective perceptions of the different attributes of the USMs. The USMs present a trend of humanization, human culture, and landscape in terms of spatial characteristics. These improvements are critical for fostering long-term sustainable use by minimizing vacancy rates and retrofitting needs. The findings reveal that the human-centric comfort level of the USMs is largely determined by multi-dimensional architecture-space features, as well as personal and social activity level features. Building on these insights, we propose actionable strategies to advance sustainable USM design, prioritizing adaptive reuse, energy-efficient layouts, and culturally resonant esthetics. This work clarifies the direction of USM design optimization and improvement from the perspective of users’ subjective perception and provides a theoretical foundation for aligning underground development with global sustainability frameworks like the UN SDGs. Full article

In the evolving world of influencer marketing, Artificial Intelligence (AI) influencers are creating significant impact and transforming the approach to brand promotions on social media platforms. In recent times, many popular brands have partnered with AI influencers to engage with their social media audiences. AI influencers have become popular as a novel method for brands to increase customer engagement and create purchase intention, but there is a scarcity of research on this emerging trend of marketing. The AI-based virtual influencers effect on consumer engagement and purchase intention remain largely unexplored. This study used a questionnaire-based survey method and 414 responses were collected. The result from the research shows that credibility, informative value and human-likeness are the major factors influencing consumer engagement purchase intention towards brands promoted through AI-based virtual influencers. The attractiveness and entertainment value of AI influencer’s social media posts affect consumer engagement but exhibit no effect on purchase intention. Theoretical and managerial recommendations related to AI influencers’ marketing are presented. Full article

Emerging as a pivotal trend on social media, food review vlogs not only narrate culinary experiences but also boost local cuisine and economic growth. This study delves into how such vlogs and vlogger traits affect viewer attitudes and restaurant visit intentions, guided by the stimulus–organism–response paradigm. Hypotheses were quantitatively assessed through an online survey with 347 participants from Amazon’s Mechanical Turk (MTurk), analyzed using SPSS 22 and AMOS 22 for structural equation modeling (SEM). The results indicated that informativeness, entertainment, and vividness influence viewers’ engagement with food review vlogs, while attractiveness and homophily are major predictors of parasocial relationships. Content engagement and parasocial relationships exerted positive influences on attitudes and visiting intentions toward the reviewed restaurants. The findings contribute to the empirical understanding of foodservice communication by identifying key characteristics of food review vlogs and vloggers that drive viewer engagement and behavioral intentions. Building on an established theoretical foundation, this study underscores the practical significance of the S–O–R model in digital marketing, offering actionable insights to empower content creators and marketers in driving audience engagement and shaping consumer behavior. Full article

Modern vehicles are equipped with various electronic control units (ECUs) for safety, entertainment, and autonomous driving. These ECUs operate independently according to their respective roles and generate considerable data. However, owing to capacity and security concerns, most of these data are not stored. In contrast, Tesla vehicles, equipped with multiple sensors and designed under the software-defined vehicle (SDV) concept, collect, store, and periodically transmit data to dedicated servers. The data stored inside and outside the vehicle by the manufacturer can be used for various purposes and can provide numerous insights to digital forensics researchers investigating incidents/accidents. In this study, various data stored inside and outside of Tesla vehicles are described sequentially from a digital forensics perspective. First, we identify the location and range of the obtainable storage media. Second, we explain how the data are acquired. Third, we describe how the acquired data are analyzed. Fourth, we verify the analyzed data by comparing them with one another. Finally, the cross-analysis of various data obtained from the actual accident vehicles and the data provided by the manufacturer revealed consistent trends across the datasets. Although the number of data points recorded during the same timeframe differed, the overall patterns remained consistent. This process enhanced the reliability of the vehicle data and improved the accuracy of the accident investigation. Full article

In recent years, China has witnessed a growing trend in the adoption of electric robotaxi services, with an increasing number of users beginning to experience this emerging mode of transportation. However, enhancing user willingness to ride remains a core challenge that the electric robotaxi industry urgently needs to address. Our study approached this issue from the perspective of interactive features, surveying 880 respondents and utilizing structural equation modeling to analyze user preferences. The research findings indicate that computer-based entertainment has a significant positive impact on traffic information completeness and social interaction, with a large effect (β > 0.5, p < 0.05), and it also exerts a small positive effect on behavioral intention (β > 0.1, p < 0.05). Traffic information completeness and social interaction have a medium positive effect on behavioral intention (β > 0.3, p < 0.05). In addition, we confirmed that inclusive design, gender, and age have significant moderating effects. Understanding the impact of inclusive design on user behavior can help drive industry changes, creating a more inclusive human–vehicle interaction environment for people with different abilities, such as those with autism. Our study reveals the key factors influencing users’ willingness to ride and offers insights and recommendations for the development and practical application of interactive features in electric robotaxis. Full article

In recent years, there has been a widespread integration of virtual reality (VR) technology across various sectors including healthcare, education, and entertainment, marking a significant rise in its societal importance. However, with the ongoing trend of population ageing, understanding the elderly’s acceptance of such new technologies has become a focal point in both academic and industrial discourse. Despite the attention it garners, there exists a gap in understanding the attitudes of older adults towards VR adoption, along with evident needs and barriers within this demographic. Hence, gaining an in-depth comprehension of the factors influencing the acceptance of VR technology among older adults becomes imperative to enhance its utility and efficacy within this group. This study employs renowned databases such as WoS and Scopus to scrutinize and analyze the utilization of VR among the elderly population. Utilizing VOSviewer software (version 1.6.20), statistical analysis is conducted on the pertinent literature to delve into research lacunae, obstacles, and recommendations in this domain. The findings unveil a notable surge in literature studies concerning VR usage among older adults, particularly evident since 2019. This study documents significant journals, authors, citations, countries, and research domains contributing to this area. Furthermore, it highlights pertinent issues and challenges surrounding the adoption of VR by older users, aiming to identify prevailing constraints, research voids, and future technological trajectories. Simultaneously, this study furnishes guidelines and suggestions tailored towards enhancing VR acceptance among the elderly, thereby fostering a more inclusive technological milieu. Ultimately, this research aspires to establish an encompassing technological ecosystem empowering older adults to harness VR technology for enriched engagement, learning, and social interactions. Full article

E-commerce has become uniquely relevant to small- and medium-sized enterprises (SMEs) as an essential catalyst for their growth and sustainability. SMEs see e-commerce portals as a strategic way to engage in digital business activities without having to implement costly proprietary e-commerce solutions. In addition, partnering with these portals frees them from complex tasks such as positioning, portal maintenance, and adapting the portal to new technologies and trends. This multifaceted advantage positions e-commerce portals as invaluable partners, streamlining operations and allowing SMEs to focus more on their core business competencies. However, e-commerce portals or e-marketplaces are not without their challenges. Today, they face increasing pressure to reduce their environmental impact and to empower local commercial businesses, as well as local businesses in the entertainment and culture industry. To address these challenges, there is a pressing need to propose new types of e-marketplaces that support the concept of the 15-minute city and in which virtual and augmented reality play a key role. These marketplaces would not only boost environmental sustainability but also strengthen the connection between local businesses and the community, creating a stronger and more collaborative network that benefits both businesses and consumers. Full article

Background: The COVID-19 pandemic brought significant changes to daily life in Poland, with restrictions affecting various sectors, including entertainment, education, and travel. The pandemic’s impact extended to intimate aspects of life. This study aimed to compare the sexual functioning of young adults in Poland before and during the pandemic, using the Changes in Sexual Functioning Questionnaire (CSFQ-14). Methods: The research involved an online survey with demographic questions, the CSFQ-14 for pre-pandemic sexual functioning, and modified CSFQ-14 questions for the pandemic period. Sexual dysfunction was determined using predefined cutoff scores. Results: Overall, the study found no significant difference in the sexual functioning of young Poles during the COVID-19 pandemic compared to before. However, there were gender-specific trends. Women reported enhanced pleasure, satisfaction, and orgasm during lockdown, while men faced challenges with erection and ejaculation. A higher proportion of women experienced overall sexual dysfunction compared to men, both before and during the pandemic. This research provides insights into the impact of the COVID-19 pandemic on the sexual lives of young Poles. While overall sexual functioning remained relatively stable, specific aspects varied by gender. Conclusions: The study emphasizes the need to consider demographic factors, such as age and gender, when assessing the effects of external stressors like a pandemic on sexual health. Further research is essential to fully grasp these complexities and their potential long-term consequences. Full article

Emotion recognition has become increasingly important in the field of Deep Learning (DL) and computer vision due to its broad applicability by using human–computer interaction (HCI) in areas such as psychology, healthcare, and entertainment. In this paper, we conduct a systematic review of facial and pose emotion recognition using DL and computer vision, analyzing and evaluating 77 papers from different sources under Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Our review covers several topics, including the scope and purpose of the studies, the methods employed, and the used datasets. The scope of this work is to conduct a systematic review of facial and pose emotion recognition using DL methods and computer vision. The studies were categorized based on a proposed taxonomy that describes the type of expressions used for emotion detection, the testing environment, the currently relevant DL methods, and the datasets used. The taxonomy of methods in our review includes Convolutional Neural Network (CNN), Faster Region-based Convolutional Neural Network (R-CNN), Vision Transformer (ViT), and “Other NNs”, which are the most commonly used models in the analyzed studies, indicating their trendiness in the field. Hybrid and augmented models are not explicitly categorized within this taxonomy, but they are still important to the field. This review offers an understanding of state-of-the-art computer vision algorithms and datasets for emotion recognition through facial expressions and body poses, allowing researchers to understand its fundamental components and trends. Full article