Search Results (2,191)

The changing habits of consuming entertainment via digital channels have been well researched in contemporary academic papers, as has the migration of different forms and formats into digital environments. Often these migrations are based on familiarity for facilitating the smooth transition into the new format, with additions specific to the digital channel (e.g., animations, sound effects, 3D perspectives, etc.) that are supposed to enhance user experience. In this paper, we present a comparative study of visual elements used in physical and digital versions of two tabletop games (Monopoly and UNO). Results from a sample of 100 players of both versions show higher overall satisfaction when engaging with the physical version of the games and significantly lower satisfaction with various visual elements in digital versions, such as overall visual perception, colors, and visual appearance of some key elements of the games. On closer inspection, the results show that the tendency to overload user interfaces with an abundance of interactive and visually enhanced features may reduce game enjoyment and overall satisfaction with the game, presumably due to factors such as information overload and cognitive distraction. In conclusion, it seems that the rule “less is more” could also be applied to the digital transition explained in this article. Full article

As our society increasingly relies on digital platforms for information, the spread of fake news has become a pressing concern. This study investigates the ability of Greek and Portuguese Instagram users to identify fake news, highlighting the influence of cultural differences. The responses of 220 Instagram users were collected through questionnaires in Greece and Portugal. The data analysis investigates characteristics of Instagram posts, social endorsement, and platform usage duration. The results reveal distinct user behaviors: Greeks exhibit a unique inclination towards social connections, displaying an increased trust in friends’ content and investing more time on Instagram, reflecting the importance of personal connections in their media consumption. They also give less importance to a certain post’s characteristics, such as content opposing personal beliefs, emotional language, and poor grammar, spelling, or formatting when identifying fake news, compared to the Portuguese, suggesting a weaker emphasis on content quality in their evaluations. These findings show that cultural differences affect how people behave on Instagram. Hence, content creators, platforms, and policymakers need specific plans to make online spaces more informative. Strategies should focus on enhancing awareness of key indicators of fake news, such as linguistic quality and post structure, while addressing the role of personal and social networks in the spread of misinformation. Full article

Today, cloud computing is a widely used technology that provides a wide range of services to numerous sectors around the world. This technology depends on the interaction and cooperation of virtual machines (VMs) to complete various computing tasks, propagating malware attacks quickly due to the complexity of cloud computing environments and users’ interfaces. As a result of the rising demand for cloud computing from multiple perspectives for complete analysis and decision-making across a range of life disciplines, multi-cloud environments (MCEs) are established. Therefore, in this work, we discuss impacted mathematical modeling for the MCEs’ network dynamics using two deterministic and stochastic approaches. In both approaches, appropriate assumptions are considered. Then, the proposed networks’ VMs are classified to have six different possible states covering media, healthcare, finance, and educational servers. After that, the two developed modeling approaches’ solution existence, uniqueness, equilibrium, and stability are carefully investigated. Using an optimal control strategy, both proposed models are tested for sustaining a certain level of security of the VMs’ states and reducing the propagation of malware within the networks. Finally, we verify the theoretical results by employing numerical simulations to track the malware’s propagation immunization. Results showed how the implemented control methods maintained the essential objectives of managing malware infections. Full article

Due to numerous distributed power sources connecting to the grid, which results in strong grid volatility and diminished power quality, the traditional energy storage configuration is limited in terms of flexibility and economy. Based on this, integrating electric vehicles (EVs) into the distribution network as energy storage devices has emerged as a promising development direction. This paper proposes a frequency-response optimization study considering the strong uncertainty model of EVs. First, from the perspective of temporal-spatial characteristics, energy storage resources, and users’ willingness to respond, the strong uncertainty model of EVs is constructed by fitting the trip chain and the access probability of their participation in energy storage. Second, the frequency optimization model is integrated and constructed according to the response capability of a single EV. Finally, examples and scenarios are analyzed to verify that the maximum and minimum frequency offsets are reduced by 69.41% and 66.69%, respectively, which significantly reduces frequency fluctuations and stabilizes the output of EV clusters. Full article

Pavement (or road) markings play an important role in road safety, influencing the dynamics of road users through their skid resistance properties. This study provides a comprehensive synthesis and analysis of international perspectives on the skid resistance of pavement markings and their requirements. It examines marking skid test results across various regions, including North America, Europe, and other parts of the world, and emphasizes the impact of different materials and test environments on skid resistance. The study also reviews current skid resistance standards and guidelines, from North American state-level standards to European and global specifications. Furthermore, it discusses the safety implications of these standards for diverse road users, especially motorcyclists, cyclists, and pedestrians. In conclusion, this paper highlights the importance of further innovation and consistency in skid resistance testing and standards to improve road safety. Full article

Peer-to-peer car-sharing systems are an evolving branch of urban mobility, aligning with global trends focused on sustainable development and reducing congestion in cities. A research gap has been identified concerning the specific vehicle attributes that would encourage the public to potentially use these services. Addressing this gap, and in the context of launching a new peer-to-peer car-sharing service in Katowice, Poland, this article investigates the technical features influencing the choice of vehicles in peer-to-peer car-sharing systems, particularly from the perspective of individuals who currently do not use such platforms. The study employs Social Network Analysis (SNA) to examine the interrelationships between vehicle attributes. The analysis reveals that key factors influencing users’ decisions include fuel/energy consumption, safety features, and technological advancement, with a particular emphasis on driver assistance systems, including autonomous driving capabilities. The network structure, characterized by a relatively low density (0.2536) and a short average path length (1.872), suggests that a few central vehicle features dominate user decisions, and improvements in these key areas can quickly propagate through the decision-making process, enhancing overall user satisfaction. To validate the findings, a Gradient Boosting Regression (GBR) analysis was conducted, confirming the significance of the key factors identified by the SNA, such as fuel efficiency, battery capacity, and safety systems, thus strengthening the reliability of the results. This study underscores the growing importance of sustainability and technological innovation in the automotive industry, particularly in the context of the sharing economy. It suggests that car-sharing platforms and vehicle manufacturers should prioritize these features to meet user expectations and preferences. These findings provide valuable insights for the strategic and operational management of peer-to-peer car-sharing services, emphasizing the importance of targeted vehicle selection and user-centered innovations to improve platform performance and scalability. Full article

In China, fruit tree diseases are a significant threat to the development of the fruit tree industry, and knowledge about fruit tree diseases is the most needed professional knowledge for fruit farmers and other practitioners in the fruit tree industry. Research papers are the primary sources of professional knowledge that represent the cutting-edge progress in fruit disease research. Traditional knowledge engineering methods for knowledge acquisition require extensive and cumbersome preparatory work, and they demand a high level of professional background and information technology skills from the handlers. This paper, from the perspective of fruit tree industry knowledge dissemination, aims at users such as fruit farmers, fruit tree experts, fruit tree knowledge communicators, and information gatherers. It proposes a fast, cost-effective, and low-technical-barrier method for extracting fruit tree disease knowledge from research paper abstracts—K-Extract, based on large language models (LLMs) and prompt engineering. Under zero-shot conditions, K-Extract utilizes conversational LLMs to automate the extraction of fruit tree disease knowledge. The K-Extract method has constructed a comprehensive classification system for fruit tree diseases and, through a series of optimized prompt questions, effectively overcomes the deficiencies of LLM models in providing factual accuracy. This paper tests multiple LLM models available in the Chinese market, and the results show that K-Extract can seamlessly integrate with any conversational LLM model, with the DeepSeek model and the Kimi model performing particularly well. The experimental results indicate that LLM models have a high accuracy rate in handling judgment tasks and simple knowledge Q&A tasks. The K-Extract method is simple, efficient, and accurate, and can serve as a convenient tool for knowledge extraction in the agricultural field. Full article

The remote sensing community benefits from new sensors and easier access to Earth Observation data to frequently released new land-cover maps. The propagation of such independent and heterogeneous products offers promising perspectives for various scientific domains and for the implementation and monitoring of land-use policies. Yet, it may also confuse the end-users when it comes to identifying the most appropriate product to address their requirements. Data fusion methods can help to combine competing and/or complementary maps in order to capitalize on their strengths while overcoming their limitations. We assessed the potential of the Dempster–Shafer Theory (DST) to enhance oil palm mapping in Sumatra (Indonesia) by combining four land-cover maps, hereafter named DESCALS, IIASA, XU, and MAPBIOMAS, according to the first author’s name or the research group that published it. The application of DST relied on four steps: (1) a discernment framework, (2) the assignment of mass functions, (3) the DST fusion rule, and (4) the DST decision rule. Our results showed that the DST decision map achieved significantly higher accuracy (Kappa = 0.78) than the most accurate input product (Kappa = 0.724). The best result was reached by considering the probabilities of pixels to belong to the OP class associated with DESCALS map. In addition, the belief (i.e., confidence) and conflict (i.e., uncertainty) maps produced by DST evidenced that industrial plantations were detected with higher confidence than smallholder plantations. Consequently, Kappa values computed locally were lower in areas dominated by smallholder plantations. Combining land-use products with DST contributes to producing state-of-the-art maps and continuous information for enhanced land-cover analysis. Full article

This research aims to optimize corridors in Hyderabad, Sindh, to promote modal choice, reduce congestion, and enhance livability. This study focused on developing and evaluating multimodal wide corridor routing methods, analyzing the modal choice behavior of travelers using a generalized cost model and a mixed constant and separate user balance model, and implementing and assessing innovative road space management strategies. The data were collected using GIS (Geographical Information System) to compare the performance and impacts of the proposed methods and techniques with existing ones, such as shortest path, minimum interference, maximum capacity, and lane addition, using various performance measures, such as travel time, modal share, congestion level, environmental impact, safety, and equity. This research aims to optimize corridors in Hyderabad, Sindh, to encourage various transportation options, such as the BRT system and Peoples Bus Service, to reduce congestion and enhance livability by developing and accessing different methods and strategies. This study analyzed available data through a geospatial perspective to optimize corridors in Hyderabad, Sindh, focusing on multimodal routing methods, modal choice behavior, and innovative road space management strategies to enhance urban livability rather than relying on simulation software or field-collected data. Full article

Human-Computer Interaction (HCI) research has illuminated how technology can influence users’ awareness of their environmental impact and the potential for mitigating these impacts. From hot water saving to food waste reduction, researchers have systematically and widely tried to find pathways to speed up achieving sustainable development goals through persuasive technology interventions. However, motivating users to adopt sustainable behaviors through interactive technologies presents significant psychological, cultural, and technical challenges in creating engaging and long-lasting experiences. Aligned with this perspective, there is a dearth of research and design solutions addressing the use of persuasive technology to promote sustainable recycling behavior. Guided by a participatory design approach, this investigation focuses on the design opportunities for leveraging persuasive and human-centered Internet of Things (IoT) applications to enhance user engagement in recycling activities. The assumption is that one pathway to achieve this goal is to adopt persuasive strategies that may be incorporated into the design of sustainable applications. The insights gained from this process can then be applied to various sustainable HCI scenarios and therefore contribute to HCI’s limited understanding in this area by providing a series of design-oriented research recommendations for informing the development of persuasive and socially engaged recycling platforms. In particular, we advocate for the inclusion of educational content, real-time interactive feedback, and intuitive interfaces to actively engage users in recycling activities. Moreover, recognizing the cultural context in which the technology is socially situated becomes imperative for the effective implementation of smart devices to foster sustainable recycling practices. To this end, we present a case study that seeks to involve children and adolescents in pro-recycling activities within the school environment. Full article

Based on spatiotemporal sensing techniques, the cross-regional traveling welcome short messaging service (TW-SMS) has been adopted in China and has become popular, typically being used when travelers pass through or arrive in cities. In this service, governmental institutions in combination with telecom operators send welcome messages with the local characteristics. As a typical location-based service for mobile users, the TW-SMS includes reminders or alerts related to COVID-19 prevention and control. In this paper, we investigate the perceptions and behavior of mobile users regarding this special TW-SMS through mixed-methods research. An online survey was conducted among mobile users who engaged in intercity travel. After analyzing samples of TW-SMS data collected during the COVID-19 pandemic, we found that the respondents exhibited a relatively positive overall attitudes and recognized the necessity and helpfulness of the TW-SMS with its trusted content. For content analysis, we found that more than 70% of the messages transmitted by the TW-SMS were released by official departments (e.g., the COVID-19 Prevention and Control Office). Reminders about traveling registration and nucleic acid testing were assigned the highest importance, as they offer convenience in communicating the most up-to-date prevention and control information to mobile users during intercity travel. Through this study, we provide insights into epidemic prevention and control experiences during public health emergencies in cities. Full article

The building and construction sector remains largely climate-unfriendly as a significant global greenhouse gas emitter. Public buildings can play a significant role in promoting sustainability practices. Unlike developed countries that have successfully promoted sustainable building practices, developing countries have experienced slow progress in implementing sustainable practices in public buildings. This research study investigated the challenges and opportunities for improving sustainability practices in public buildings from a multi-stakeholder perspective within the context of developing countries. Using Indonesian public buildings as a case study, a wide range of stakeholders directly involved in the public building sector such as policy-makers, building owners, building professionals, and building users were interviewed over two time periods of 2019 and 2023. The interview results show consistent findings on challenges and possible opportunities with respect to regulation, occupant behavior, and the primacy of technical intervention in the practice of sustainable buildings. Despite the importance of strong policy and the role of technology in sustainability practices in public buildings, this study advocates the need for greater intervention in occupant behavior so that sustainable practices in public buildings can be continuously promoted. Full article

Forest environments have been demonstrated to promote human health and well-being through rich sensory experiences. However, the mechanisms by which olfactory experience affects visitors’ mental health remain to be thoroughly researched, and discussions on emotional resilience, a key competency affecting an individual’s mental health, are particularly rare. To address the challenges of high subjectivity, difficulty in quantifying, and high context-dependency of olfactory experience and emotional resilience in such studies, large language models were introduced to study the National Forest Parks in China and analyse massive user-generated data. This provided new possibilities for constructing a more comprehensive theoretical paradigm of olfactory experience–emotional resilience. The findings indicate that olfactory experiences in National Forest Parks exert a substantial influence on tourists’ emotional resilience, with diverse olfactory experiences demonstrating a more pronounced impact on emotional resilience compared to a single type of olfactory experience. However, this impact exhibits an inverted U-shaped relationship. Natural environment olfactory experiences were found to be more conducive to attention restoration, while artificial environment olfactory experiences were more likely to induce nostalgic feelings. This study found that nostalgic feelings significantly mediated the relationship between artificial environment olfactory experience and emotional resilience, while attention restoration did not significantly mediate the relationship between natural environment olfactory experience and emotional resilience. This provides a novel perspective on the examination of the complex relationship between forest environments, olfactory experience, and emotional resilience. Semantic analyses revealed the complexity and network characteristics of olfactory experiences in National Forest Parks, and at the same time identified four main types of olfactory experiences and scenarios. This research offers valuable insights for forest recreation and leisure management, as well as public health policy development. Full article

Drug discovery is inherently a multi-criteria optimization problem. In the first instance, it involves a tremendously large chemical space, where each compound can be characterized by multiple molecular and biological properties. Modern computational approaches try to efficiently explore the chemical space in search of molecules with the desired combination of properties. For example, Pareto optimizers identify a so-called “Pareto front”, a set of non-dominated solutions. From a qualitative perspective, all solutions on the front are potentially equally desirable, each expressing a trade-off between the goals. However, often there is a need to weight the objectives differently, depending on their perceived importance. To address this, we recently implemented a new Multi-Criteria Decision Analysis (MCDA) method as part of the AI-powered Drug Design (AIDD^TM) technology initiative. This allows the user to weight various objective functions differently, which, in turn, efficiently directs the generative chemistry process toward the desired areas in chemical space. Full article

This research provides an integrated perspective on the application of ergonomics and human factors engineering (HFE) to enhance comfort and efficiency in military transport systems (MTS) and civilian transport systems (CTS), identified as imperative research needs. Comfort has become the definition of vehicle quality in CTS, while in MTS, comfort directly influences crew performance in operational environments, and protecting their health is essential. The study emphasizes the importance of adopting an integrative and scientifically grounded approach that eliminates systematic errors to meet user needs and ensure optimal vehicle performance in diverse operational settings. It further highlights how applying ergonomic principles optimizes human–machine interactions, improving user comfort and safety while providing a basis for future innovations in artificial intelligence and adaptive ergonomics. This study introduces a novel hybrid methodology combining bibliometric analysis and case studies to provide fresh insights into the application of ergonomics and human factors engineering, bridging gaps between civilian and military transport systems. This approach aims to promote efficiency, comfort, and performance in operational environments. The results confirm the research hypotheses, demonstrating that ergonomic principles and human factors engineering (HFE) can significantly enhance the comfort, safety, and performance of vehicle users in both civilian and military contexts. Full article