Search Results (6,242)

Prehabilitation programs for abdominal pre-operative patients are increasingly recognized for improving surgical outcomes, reducing post-operative complications, and enhancing recovery. Internet of Things (IoT)-enabled human movement monitoring systems offer promising support in mixed-mode settings that combine clinical supervision with home-based independence. These systems enhance accessibility, reduce pressure on healthcare infrastructure, and address geographical isolation. However, current implementations often lack personalized movement analysis, adaptive intervention mechanisms, and real-time clinical integration, frequently requiring manual oversight and limiting functional outcomes. This review-based paper proposes a conceptual framework informed by the existing literature, integrating Digital Twin (DT) technology, and machine learning/Artificial Intelligence (ML/AI) to enhance IoT-based mixed-mode prehabilitation programs. The framework employs inertial sensors embedded in wearable devices and smartphones to continuously collect movement data during prehabilitation exercises for pre-operative patients. These data are processed at the edge or in the cloud. Advanced ML/AI algorithms classify activity types and intensities with high precision, overcoming limitations of traditional Fast Fourier Transform (FFT)-based recognition methods, such as frequency overlap and amplitude distortion. The Digital Twin continuously monitors IoT behavior and provides timely interventions to fine-tune personalized patient monitoring. It simulates patient-specific movement profiles and supports dynamic, automated adjustments based on real-time analysis. This facilitates adaptive interventions and fosters bidirectional communication between patients and clinicians, enabling dynamic and remote supervision. By combining IoT, Digital Twin, and ML/AI technologies, the proposed framework offers a novel, scalable approach to personalized pre-operative care, addressing current limitations and enhancing outcomes. Full article

This study lays the foundation for a multidimensional framework aimed at facilitating the effective integration of Internet of Medical Things (IoMT) technologies into real-world health management systems. It critically examines the technological, organizational, and societal barriers that hinder this transition and identifies key enabling conditions, such as interoperability, user co-design, and ethical design principles, that promote sustainability, inclusiveness, and trust. By proposing a structured approach to integration, this paper aims to bridge the gap between innovation and long-term, reliable adoption across diverse healthcare contexts. Full article

Cloud monitoring systems combine physical sensors with cloud computing capabilities. Modern manufacturing techniques and smart factories under Industry 4.0 and Industry 5.0 call for the integration of monitoring systems as part of the broader digitization process. Digitization typically occurs by integrating external sensors onto existing legacy machines. Data obtained can be utilized in digital twins, simulations, machine learning models, and Industrial Internet Of Things (IIoT) applications. The adaptation of these new technologies usually stalls due to the reluctance of end users to make modifications to already existing equipment, the legacy equipment that is in use and does not provide the information needed, and the substantial costs of integrating new measuring systems that typically require additional IT infrastructure. Having identified the need for easily scalable affordable measurement systems, new disseminated systems that utilize cloud solutions and use 5G as an enabler for real-time communication are on the rise. This publication proposes a methodology, and tests and demonstrates a relevant manufacturing use case for integrating a non-invasive-to-IT-infrastructure, cloud-based and artificial intelligence-powered monitoring system focused on high performance applications. The proposed methodology has been evaluated in a real industrial environment. Full article

Gemstone samples, as objects of study in gemology, carry rich geological information and cultural value, playing an irreplaceable role in teaching, research, and public science communication. In the current age of big data, machine learning and artificial intelligence techniques based on gemstone databases have emerged as a cutting-edge area of gemology. However, traditional gemstone databases have three major limitations: an absence of standardized data schemas, incomplete core datasets (e.g., records of synthetic and treated gemstones and inclusion characteristics), and poor data interoperability. These deficiencies hinder the application of advanced technologies, such as machine learning (ML) and AI techniques. This paper reviews gemstone data and applications, as well as existing gem-related sample databases, and proposes a framework for a new gemstone database based on standardization (FAIR principles), integration (blockchain technology), and dynamism (real-time updates). This framework could transform the gemstone industry, shifting it from “experience-driven” to “data-driven” practices. Powered by big data technology, this novel database will revolutionize gemological research, jewelry authentication, market transactions, and educational outreach, fostering innovation in academic research and practical applications. Full article

Background/Objectives: The number of overweight and obese people has significantly increased in the world, and this phenomenon is referred to as globesity. Globally increasing obesity has become one of the major problems to be dealt with for countries, given obesity-related health problems, including nutrition-related noncommunicable diseases and some types of cancer, and the economic and social costs of obesity. Therefore, countries try to combat obesity through diverse strategies related to nutrition, physical activity, and education. In this regard, identifying the factors behind obesity is critical to making progress in the fight against obesity. Methods: This study explores the interplay amongst ICT (information and communication technologies) indicators, including Internet and mobile phone usage, unemployment, and adult obesity in the BRICS states from 1995 to 2022, using recently developed cointegration techniques and causality tests. Results: The outcomes of causality tests uncover an interaction between Internet and mobile phone usage, unemployment, and adult obesity. In addition, the cointegration coefficients reveal that Internet and mobile phone usage positively impact adult obesity, while unemployment has a negative effect on adult obesity. Conclusions: Our outcomes uncover that improper use of the Internet and mobile phones foster adult obesity, but proper utilization of the Internet and mobile phones can be effective instruments in combatting adult obesity through increasing the awareness of healthy lifestyles and online weight loss programs. Full article

Climate change is increasing the frequency and intensity of Marine Heatwave (MHW) events, threatening Western Tropical Pacific Small Island Developing States (SIDSs). MHWs critically threaten the fisheries sector which vitally supports food and nutrition security in local communities and local livelihoods. Currently, MHW risk to fisheries in Western Tropical Pacific SIDSs remains underexplored. Vanuatu is a Western Tropical Pacific SIDS which requires expanded MHW risk knowledge to improve the adaptive capacity of fisheries. A fundamental method for expanding MHW risk knowledge is tailored risk assessment. This study conducts the initial steps in a tailored MHW risk assessment methodology, displaying how a tailored indicator selection and weighting process can inform effective MHW risk assessment for fisheries in Western Tropical Pacific SIDSs. Hazard, vulnerability, and exposure indicators were selected through a combined process utilising a literature review and participatory research survey. Survey results were also used to develop a user-informed indicator weighting scheme. Selected indicators included sea surface temperature (SST), coral bleaching/mortality, and chlorophyll-a concentration (hazard); terrestrial-based food and income generation, fishing skills and technology, fishery fish diversity/fishery flexibility, and primary production of commercial fisheries (vulnerability); seagrass population/C content, coral habitat health/crown-of-thorns prevalence, crab stock health, and fish mortality/fish stock health (exposure). These indicators and their assigned weights are recommended for use in a future MHW risk assessment for Vanuatu fisheries. A tailored, fisheries-specific MHW risk assessment could advise local decision-makers on where/when MHW risk is high and aid the implementation of more effective fisheries risk management. Full article

Evaluation of an individual’s accessibility to urban services is crucial for urban planners and policymakers to assess various urban policies and scenarios. Most studies have emphasized accessibility in physical spaces, with limited attention to the role of Information and Communication Technology (ICT) in providing virtual access and its implications for quality of life (QOL) and sustainability. This study addresses this gap by examining the substitutability of physical activities with digital alternatives and their potential contribution to decarbonization. Using data from an online questionnaire survey in Japan, we analyze how individuals access services across both transportation and ICT networks. We propose an integrated evaluation framework that measures QOL by considering accessibility in both physical and virtual spaces. The analysis highlights differences in substitutability across activities such as shopping, working, schooling, and entertainment, while revealing that services like healthcare and physical tourism remain less substitutable. The results disclose that accessibility strongly influences individuals’ adoption of digital alternatives, which in turn offer significant benefits in terms of convenience and environmental impact. The proposed methodology provides valuable insights seeking to balance physical and virtual service accessibility, supporting sustainable urban development in line with UN Sustainable Development Goals 10 and 11. Full article

Cooperative navigation is a fundamental enabling technology for unlocking the full potential of Unmanned Underwater Vehicle (UUV) clusters in GNSS-denied environments. However, the severe constraints of the underwater acoustic channel, such as high latency, low bandwidth, and non-Gaussian noise, pose significant challenges to designing robust and efficient state estimation and information fusion algorithms. While numerous surveys have cataloged the available techniques, they have remained largely descriptive, lacking a rigorous, quantitative comparison of their performance trade-offs under realistic conditions. This paper provides a comprehensive and critical review that moves beyond qualitative descriptions to establish a novel quantitative comparison framework. Through a standardized benchmark scenario, we provide the first data-driven, comparative analysis of key frontier algorithms—from recursive filters like the Maximum Correntropy Kalman Filter (MCC-KF) to batch optimization methods like Factor Graph Optimization (FGO)—evaluating them across critical metrics including accuracy, computational complexity, communication load, and robustness. Our results empirically reveal the fundamental performance gaps and trade-offs, offering actionable insights for system design. Furthermore, this paper provides in-depth technical analyses of advanced topics, including distributed fusion architectures, intelligent strategies like Deep Reinforcement Learning (DRL), and the unique challenges of navigating in extreme environments such as the polar regions. Finally, leveraging the insights derived from our quantitative analysis, we propose a structured, data-driven research roadmap to systematically guide future investigations in this critical domain. Full article

An optical vortex is a typical structured light field characterized by a helical wavefront and a central phase singularity. With its expanding applications in modern information technology, the demand for generating vortex beams with diverse topological charges continues to grow. Existing methods for modulating the topological charges of vortex beams involve complex operations and high costs. This study proposes a novel approach to modulate the topological charges of optical vortices through edge diffraction of a high-order Hermit–Gaussian (HG) mode laser. First, a high-order HG mode laser is built using off-axis pumping configuration. By selectively obscuring specific lobes of the high-order HG beam, various optical vortices are generated using a cylindrical lens mode converter. The topological charge can be continuously tuned by controlling the number of obscured lobes. This method substantially improves the efficiency of topological charge modulation, while also enabling the generation of fractional vortex states. These advancements show potential in mode-division-multiplexed optical communications and encryption. Full article

Background/Objectives: Digital health technologies are increasingly integrated into perioperative care to standardize information delivery and improve patient empowerment. However, the overall effectiveness of preoperative education depends not only on digital tools but also on interpersonal factors, such as physician gender and clinical experience, which may shape patients’ perceptions and responses to digitally delivered content. Methods: Patients scheduled for elective surgery were included in the iPREDICT randomized trial prior to their preoperative anesthesia assessment. After preoperative anesthetic assessment, the anesthesiologist documented the communication quality and the risks explained. Patients completed a questionnaire to assess their knowledge of anesthesia-related risks and whether the consultation alleviated their fears. Results: A total of 275 included patients were consulted by 94 anesthesiologists, 65% of whom were female. Risk recall was mainly determined by patient-related factors, with online education significantly improving recall over time (β = 1.24, p = 0.034). Anesthesiologists with 1–4 years of clinical experience explained more risks than those with <1 year of professional experience (β = 2.30, p = 0.024). A reduction in post-consultation anxiety was noted when the anesthetist was female (β = 0.21, p = 0.022). Communication was overall rated as good, with higher ratings when anesthetists had more than 10 years of experience (β = 0.09, p = 0.049). Conclusions: Although we have shown with the iPREDICT study (registered in the German CTS; DRKS00032514; on 21 August 2023) that online education improves patients’ recall of anesthesia-related risks, the current sub-analysis emphasizes that interpersonal interactions remain essential for alleviating fears and improving the quality of communication. Together, these findings underscore the complementary roles of digital education and face-to-face consultations in optimizing preoperative preparation. Full article

Deaf-blindness, particularly in progressive conditions such as Usher syndrome, presents profound challenges to communication, independence, and access to information. Existing tactile communication technologies for individuals with Usher syndrome are often limited by the need for close physical proximity to trained interpreters, typically requiring hand-to-hand contact. In this study, we introduce a novel, cloud-based, AI-assisted gesture recognition and haptic communication system designed for long-term use by individuals with Usher syndrome, whose auditory and visual abilities deteriorate with age. Central to our approach is a wearable haptic interface that relocates tactile input and output from the hands to an arm-mounted sleeve, thereby preserving manual dexterity and enabling continuous, bidirectional tactile interaction. The system uses surface electromyography (sEMG) to capture user-specific muscle activations in the hand and forearm and employs lightweight, personalized convolutional neural networks (CNNs), hosted on a centralized server, to perform real-time gesture classification. A key innovation of the system is its ability to adapt over time to each user’s evolving physiological condition, including the progressive loss of vision and hearing. Experimental validation using a public dataset, along with real-time testing involving seven participants, demonstrates that personalized models consistently outperform cross-user models in terms of accuracy, adaptability, and usability. This platform offers a scalable, longitudinally adaptable solution for non-visual communication and holds significant promise for advancing assistive technologies for the deaf-blind community. Full article

Accommodation constitutes a key element in the competitiveness of a destination. However, there is limited information on how overnight tourists evaluate the destination according to the type of accommodation. To date, Information and Communication Technologies (ICTs) have led to an increased use of online media and the generation of large datasets available for analysis. This study analyses 47,568 feedback surveys administered by Spanish accommodation establishments to tourists, provided anonymously by a tourism software company. The main objective is to understand which destination attributes predict positive results on satisfaction and recommendation, depending on the type of accommodation (hotel and non-hotel). To this end, both a descriptive analysis and an analysis using neural networks are conducted. The results reveal significant differences in the evaluation of destination elements depending on whether the accommodation is a hotel or non-hotel, with the predictive variables varying across each typology. As a key conclusion, the study highlights that adopting this perspective makes it possible to understand destination evaluation from the standpoint of overnight tourists, thereby contributing to destination-related literature. From a practical perspective, recommendations are offered to both destination managers and accommodation providers. Full article

In the context of smart agriculture, the tea industry is undergoing a transformative shift toward intelligent development. As the birthplace of tea, China holds a significant position in the global tea industry, with Anxi County in Quanzhou City, Fujian Province—renowned as the origin of Tie Guan Yin—standing as the world’s largest oolong tea production area. Its intelligent transformation of the tea industry is typical and representative. However, current research on the digital literacy of farmers is not yet mature, and there is a lack of systematic research on this specific group of tea farmers, which to some extent restricts the transformation of the tea industry towards intelligent development. The level of digital literacy among tea farmers is crucial for the intelligent development and transformation of the tea industry. Improving the digital literacy of tea farmers is the key to promoting the intelligent development of the tea industry. Therefore, studying the digital literacy of tea farmers has significant practical significance. This article takes Anxi County as the research area and focuses on moderate-scale tea farmers as the research object. Based on the United Nations Global Framework for Digital Literacy and taking into account the actual situation of tea farmers, an evaluation index system and analysis framework for tea farmers’ digital literacy have been constructed from seven dimensions: equipment and software operation skills, digital information literacy, digital communication and collaboration literacy, digital content creation literacy, digital security literacy, problem-solving literacy, and professional digital literacy. Using literature review, questionnaire survey, interview, and quantitative analysis methods, a questionnaire containing the above-mentioned dimensions was designed. After collecting data, the rationality of the questionnaire structure was verified using SPSS software. The digital literacy level of 440 medium-sized tea farmers from 11 major tea-producing townships in Anxi County was measured, analyzed, and Two-Tailed correlation tests were conducted. The results indicate that there are currently six aspects of digital literacy among tea farmers that are at a moderate level, and professional digital literacy is the weakest among the seven digital literacy. The overall digital literacy level of tea farmers needs to be strengthened. Large-scale tea farmers have the conditions to apply smart agricultural equipment and technology, which can achieve intelligent and refined management of tea gardens and intelligent upgrading of the entire industry chain. Based on the research results of the seven digital literacy of tea farmers, this article proposes improvement measures corresponding to the seven digital literacy of tea farmers from the perspectives of “government, industry associations, and training institutions”, providing reference for Anxi County and other tea-producing areas in the world. Full article

(1) Background/Purpose: Our research focuses on stakeholders’ attitudes in the Slovak SME sector, which we assessed through a questionnaire. The ability to evolve and adapt continuously is critical for micro-enterprises in competitive markets. (2) Study Design/Methodology/Approach: The primary objective of our research is to gain a comprehensive understanding of the new work organization processes in SMEs operating in a rapidly changing economic environment. Our research employed a single-sample cross-sectional sampling method, wherein respondents completed a questionnaire within a defined time frame. The primary data collection was carried out using a questionnaire containing closed questions. The research assesses the opinions of the respondents regarding the problem under study over a given period of time. The survey was conducted online. (3) Findings: 31% of the companies surveyed considered that introducing new work organization processes would make the company more adaptable to the changing economic environment. Only one-third considered involving employees in the processes the most important means to achieve this. Higher employee satisfaction is reported as a positive by 24% of companies. However, only a quarter of them believe the best way to achieve this is to involve employees in processes. For micro-enterprises, limited resources and smaller staff prioritize effective communication, and gaps can cause significant difficulties. Regarding the sample examined, among the hypotheses based on the literature background, we were only able to accept hypothesis H3 with modifications, which states that the biggest challenge for micro-companies in the industrial sector in a competitive market is understanding new technologies when improving employee skills. (4) Originality/Value: The research shows that micro-enterprises are particularly sensitive to the challenges associated with new technologies, which can be important information for designing training programs and developing support strategies for enterprises. Full article

This paper presents a semi-quantum secret sharing (SQSS) protocol based on three-particle W states, designed for efficient and secure secret sharing in quantum-resource-constrained scenarios. In the protocol, a fully quantum-capable sender encodes binary secrets using W, while receivers with limited quantum capabilities reconstruct the secret through collaborative Z basis measurements and classical communication, ensuring no single participant can obtain the complete information independently. The protocol employs a four-state decoy photon technique ($\left\{\right|0⟩,|1⟩,|+⟩,|-⟩\}$) and position randomization, combined with photon number splitting (PNS) and wavelength filtering (WF) technologies, to resist intercept–resend, entanglement–measurement, and double controlled-NOT(CNOT) attacks. Theoretical analysis shows that the detection probability of intercept–resend attacks increases exponentially with the number of decoy photons (approaching 1). For entanglement–measurement attacks, any illegal operation by an attacker introduces detectable quantum state disturbances. Double CNOT attacks are rendered ineffective by the untraceability of particle positions and mixed-basis strategies. Leveraging the robust entanglement of W states, the protocol proves that the mutual information between secret bits and single-participant measurement results is strictly zero, ensuring lossless reconstruction only through authorized collaboration. Full article