Search Results (9,883)

While digital transformation (DT) promises significant advancements in the construction sector, many firms report a disconnect between technological investment and realized project performance. This study investigates the mechanisms through which DT drives project management optimization (PMO), hypothesizing that organizational agility (OA) and knowledge management capability (KMC) serve as critical mediating factors. We propose and test a conceptual model in which DT directly enhances PMO and also exerts indirect influence through the parallel pathways of OA and KMC. Data from a survey of 312 construction professionals were analyzed using structural equation modeling. The results confirm a significant direct effect of DT on PMO. Furthermore, both OA and KMC are identified as complementary and significant partial mediators. This finding underscores that the efficacy of digital technologies is contingent upon supportive organizational structures and systematic knowledge processes. The study provides a nuanced theoretical framework explaining how DT translates into improved project outcomes and offers strategic guidance for practitioners: to fully capitalize on digital investments, construction firms must concurrently cultivate adaptive capabilities and robust knowledge management systems. Full article

Background and Objectives: Falls are a leading cause of morbidity and mortality among older adults in hospitals and long-term care facilities (LTCFs). Digital healthcare approaches are increasingly being applied to fall detection and prevention; however, their effectiveness remains uncertain. This review evaluated the effectiveness, usability, and clinical applicability of detection- and prediction-based systems in institutional settings. Materials and Methods: We systematically searched major international and Korean databases—PubMed, Embase, Ovid-MEDLINE, CINAHL, the Cochrane Library, IEEE, KMbase, KISS, KoreaMed, and RISS—for studies published up to December 2024. The eligible studies included randomized controlled trials, quasi-experimental, and observational studies involving older adults in hospitals or LTCFs. Two reviewers independently screened the studies, extracted data, and assessed their quality using standardized tools. Results: Thirty-three studies comprising 20 fall detection systems and 13 fall prediction models were included. Detection systems using inertial, pressure, radar, or multimodal sensors have improved monitoring and achieved high usability (>80% acceptance); however, they did not consistently reduce fall incidence or the occurrence of injurious falls. For instance, one trial reported a nonsignificant reduction in injurious falls (aRR 0.56, 95% CI 0.17–1.79), whereas another trial observed a nonsignificant increase (aIRR 1.60, 95% CI 0.83–3.08). Frequent false alarms contribute to alarm fatigue. The prediction models showed moderate-to-strong discrimination. Gradient boosting and neural networks performed best for continuous gait features, while regression and boosting approaches were effective for categorical EHR data. Most models lacked external validation and were not linked to clinical care pathways. Conclusions: Digital approaches show potential for fall prevention in hospitals and LTCFs; however, current evidence remains inconsistent and limited. Detection systems improve surveillance but offer limited preventive effects, whereas prediction models demonstrate technical promise without establishing clinical benefits. Future research should refine the technology, validate models externally, and integrate them into patient-centered workflows. Full article

With the advancement of educational informatization, vast amounts of Chinese text are generated across online platforms and digital textbooks. Effectively classifying such text is essential for intelligent education systems. This study conducts a systematic comparative evaluation of three Transformer-based models—TinyBERT-4L, BERT-base-Chinese, and RoBERTa-wwm-ext—for Chinese educational text classification. Using a balanced four-category subset of the THUCNews corpus (Education, Technology, Finance, and Stock), the research investigates the trade-off between classification effectiveness and computational efficiency under a unified experimental framework. The experimental results show that RoBERTa-wwm-ext achieves the highest effectiveness (93.12% Accuracy, 93.08% weighted F1), validating the benefits of whole-word masking and extended pre-training. BERT-base-Chinese maintains a balanced performance (91.74% Accuracy, 91.66% F1) with moderate computational demand. These findings reveal a clear symmetry–asymmetry dynamic: structural symmetry arises from the shared Transformer encoder and identical fine-tuning setup, while asymmetry emerges from differences in model scale and pre-training strategy. This interplay leads to distinct accuracy–latency trade-offs, providing practical guidance for deploying pre-trained language models in resource-constrained intelligent education systems. Full article

This paper investigates the advantages and challenges associated with synchronous and asynchronous activities in intercultural virtual collaboration (IVC) projects, particularly in relation to student satisfaction and learning outcomes. This study draws parallels between two distinct IVC projects. The first facilitated real-time interaction among students, lecturers, and peers from partner universities in the Netherlands and Japan. In contrast, the second project involved separate live classes led by local instructors in the Netherlands and Spain and featured asynchronous interactions among peers. This latter arrangement required students to exercise a greater degree of autonomy in their collaborative efforts. In both IVC projects, students developed a business case study that explored the influence of cultural factors on international marketing strategies. They participated in discussions and reflective exercises concerning the issue of greenwashing within the selected company. Our research employs data derived from students’ final business case reports and satisfaction surveys. The surveys include both closed and open-ended questions to assess the effectiveness of the distinct IVC formats. Our research provides insights into the impact of the IVC formats on the student experience and learning. Findings indicate no substantial differences in the quality of work produced between the two formats; however, student satisfaction was notably higher in the synchronous model, highlighting that the way interactions are structured impacts the collaborative experience, even when final outputs are similar. This study offers important insights for educators navigating the challenges of virtual teaching and for policymakers looking to use digital technologies to foster a globally aware and responsible generation in an increasingly digital world. Full article

The paper focuses on exploring ways to achieve sustainability in the manufacturing process through targeted optimization and ergonomic improvements of the work environment. The introductory section emphasizes the importance of sustainability from the perspectives of worker well-being, occupational safety, and efficient resource utilization. The paper presents a digital approach to workstation design with an emphasis on sustainability, which includes the creation of a 3D model of the assembly station using SolidWorks (v.2017) and Jack software (v.8.3), where the work movements of a virtual mannequin with realistic parameters are simulated. The analytical section is dedicated to evaluating workstation ergonomics using the RULA (Rapid Upper Limb Assessment), SSP (Static Strength Prediction), OWAS (Ovako Working Posture Analysis), and Lower Back Analysis methods, with the aim of identifying operations that reduce the sustainability of the work process due to excessive physical strain. Badly designed operations have a negative impact on sustainability in the meaning of physical workload strain (social dimension), low effectivity and quality (economic dimension), and higher resource (material, energy, transport, etc.) usage (environmental dimension). All these dimensions can be measured and expressed by number, but this paper focuses on workload only. Based on the results, specific measures were proposed with a focus on sustainability—raising the working height of pallets, optimizing the positioning of tools, and adjusting work movements. Repeated analyses after the implementation of these changes confirmed not only a reduction in physical strain and increased safety but also the enhancement of the sustainability of the working environment and processes. The results of the article clearly demonstrate that digital simulation and ergonomic design, oriented toward sustainability, are of crucial importance for the long-term efficiency and sustainable development of manufacturing organizations. The novelty of the work is in contribution to empirical validation on the role of digital twins, virtual ergonomics, and human factors in Industry 5.0 contexts, where the synergy between technological efficiency and human-centric sustainability is increasingly emphasized. The proposed approach represents a practical model for further initiatives aimed at improving the sustainability of assembly workstations. Full article

Material handling (MH) plays a critical role in the performance, cost efficiency, and sustainability of high-rise construction projects. Despite its significance, MH practices in such projects remain challenged by complex vertical logistics, space constraints, fragmented supply chains, and increasing pressure to align with decarbonisation goals. This study applies a mixed-methods approach that integrates a systematic literature review, semi-structured expert interviews, and a SWOT–AHP (Strengths, Weaknesses, Opportunities, Threats—Analytic Hierarchy Process) model to identify and prioritise factors influencing MH optimisation in China’s high-rise construction sector. Eighteen factors were evaluated across four SWOT dimensions, and expert pairwise comparisons were aggregated using geometric means. The results revealed that Technological Adoption (S1) and Technological Advancements (O3) are the most critical enablers, while High Implementation Costs (W2) and Resource Scarcity (T3) are the most significant constraints. Interactions among these factors highlight the dual importance of internal digital capabilities and external technological trajectories in shaping MH strategies. Comparative analysis with practices in Europe, the United States, and the Middle East demonstrates that digitalisation, financial mechanisms, and policy incentives are globally consistent drivers of MH innovation. The findings advance theoretical understanding by integrating perspectives from the Resource-Based View, Technology-Organisation-Environment, and Institutional Theory, and they offer practical implications for policymakers and industry stakeholders seeking to align MH optimisation with China’s dual-carbon targets. This study contributes to the development of a comprehensive decision-support framework that enhances the sustainability, resilience, and efficiency of material logistics in high-rise construction projects. Full article

Digital transformation has driven the use of artificial intelligence (AI) in local government financial reporting to improve efficiency, transparency, and accountability. This study employs a systematic literature review (SLR) approach to analyze 20 relevant articles, identifying common characteristics of publications, research focus, methods, AI technologies used, key findings, research gaps, and future research directions. The analysis results show the dominance of machine learning and expert systems in detecting fraud, predicting financial performance, and improving reporting accuracy. However, limitations in infrastructure, regulations, and system integration across government agencies remain significant challenges to implementing AI in the public sector. This study proposes the need for the development of practical implementation models, collaboration between academics, government, and technology developers, as well as the formulation of policies that support ethical and responsible AI governance. These findings make a significant contribution to shaping the strategic direction of AI utilization to strengthen local government financial reporting systems sustainably. Full article

Building Information Modeling (BIM) has established itself as a strategic and indispensable tool for designing and implementing smart buildings within the context of smart cities. This study explores the potentialities and challenges of using BIM across the main stages of the smart building lifecycle: design, construction, and operation and maintenance. We conducted comprehensive, detailed, and interpretative literature research to extract the main concepts and knowledge, enabling us to identify the main potentialities and challenges and classify them by life-cycle phase for smart buildings. Potentialities and challenges were prioritized based on the number of projects that cited them. The inclusion criteria for identifying potentialities and challenges were based on their key attributes: significant impact, information modeling potential, integration capability with other tools and methods, and improved performance in processes and services across all life cycle phases and BIM dimensions. The findings reveal that the main potentials include optimizing information management, reducing operating costs, enhancing environmental sustainability, and enhancing decision-making processes. Furthermore, the study highlights BIM’s role in integrating technologies such as IoT, augmented reality, and energy simulations, contributing to the development of more sustainable and functional buildings. However, challenges to its full adoption persist, including financial constraints, interoperability issues between systems, a lack of specialized technical skills, and organizational resistance to change. The dependence on advanced technological infrastructure and robust connectivity poses an additional challenge, especially in developing countries, where such resources may be scarce or inconsistent. Finally, this study suggests that future research should explore the integration of BIM with emerging technologies, such as artificial intelligence and digital twins, further expanding its applicability in the smart urban context. Full article

Every element of our contemporary lives has changed as a result of the widespread use of computing infrastructure and information technology in daily life. Less focus has been placed on the hardware components that underpin the computing revolution, despite the fact that its effects on software applications have been the most obvious. The computer chip is the most basic component of computer hardware and powers all digital devices. Every gadget, including mainframes, laptops, cellphones, tablets, desktop PCs, and supercomputers, is powered by different computer chips. Although there are many different types of these chips, the biggest producers in this field are AMD (Advanced Micro Devices), Intel, and ARM (Advanced RISC Machines). These companies make processors for both consumer and business markets. Users have compared their products based on a number of factors, including pricing, cache and memory, approaches, etc. This paper provides a comprehensive comparative analysis of Intel, AMD, and ARM processors, focusing on their architectural characteristics and performance within the context of burgeoning artificial intelligence applications. The detailed architectural features, performance evaluation for AI workloads, a comparison of power efficiency and cost, and analysis for current market trends are presented. By thoroughly examining core architectural elements and key performance factors, this work provides valuable insights for users and developers to seek optimal processor choices to maximize AI tool utilization in the contemporary era. Full article

This paper addresses the mechanical characterization of dissimilar overlap joints made by autogenous laser welding between thin sheets of low-carbon steel (CS) and austenitic stainless steel (SS) with an optimized welding technology able to produce sound overlap joints. This involved applying the laser beam from the CS-side to reduce the SS overheating. The research is focused on the analysis of combined tensile-shear behavior of the weld and of the heat-affected zones. During testing, the applied tensile-shear load rotates the weld connecting the CS and SS plates. The rotation angle transmitted to the free ends of the plates, together with relevant strain fields, were measured by using a digital image correlation system, VIC-2D. Thus, it was found that the weld acts as a non-linear hinge which experiences a sudden loss of stiffness when strain concentrations develop from the weld ligament edges towards the loaded sides of the plates. The welded joint fails by yielding localization and necking in the CS plate, far from the weld. This mode of failure is a consequence of the weld and heat-affected zone strength mismatches of 1.09 and 1.33, respectively. These values are consistent with the hardness profile and the documented microstructural heterogeneities. Full article

This study investigates how smartphone app usage diversity (SAUD)—defined as the breadth of applications individuals actively engage with—relates to quality of life, and how these effects are conditioned by age and digital literacy. Drawing on Uses and Gratifications Theory and Cognitive Load Theory, we conceptualize SAUD as having both beneficial and detrimental potential, depending on users’ cognitive and demographic characteristics. Using cross-sectional, self-reported data from the annual nationwide surveys on smartphone overdependence in South Korea, we analyzed a final sample of 20,967 adults (48.4% male, 51.6% female; M_age = 46.0, SD = 13.7; age range 20–69). Results demonstrate that SAUD is positively associated with quality of life among younger and digitally literate users, but negatively associated among older adults and those with lower digital literacy, suggesting the presence of conditional effects. The hypothesized three-way interaction between SAUD, age, and digital literacy was not supported. These findings extend the literature by moving beyond simplistic time-based metrics of smartphone use, offering a more differentiated understanding of mobile technology’s impact on well-being. Practically, the study highlights the need for tailored digital literacy programs and policy interventions that recognize demographic and cognitive diversity in technology engagement. Future research should incorporate longitudinal designs and objective behavioral data to further validate these insights. 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

Digital Twin (DT) technology has emerged as a valuable tool for researchers and engineers, enabling them to optimize performance and enhance system efficiency. This paper presents a comprehensive Systematic Literature Review (SLR) following the PRISMA framework to explore current applications of DT technology in the power generation sector while highlighting key advancements. A new framework is developed to categorize DTs in terms of time-scale horizons and applications, focusing on power plant types (emissive vs. non-emissive), operational behaviors (including condition monitoring, predictive maintenance, fault detection, power generation prediction, and optimization), and specific components (e.g., power transformers). The time-scale is subdivided into a six-level structure to precisely indicate the speed and time range at which it is used. More importantly, each category in the application is further subcategorized into a three-level framework: component-level (i.e., fundamental physical properties and operational characteristics), system-level (i.e., interaction of subsystems and optimization), and service-level (i.e., value-adding service outputs). This classification can be utilized by various parties, such as stakeholders, engineers, scientists, and policymakers, to gain both a general and detailed understanding of potential research and operational gaps. Addressing these gaps could improve asset longevity and reduce energy consumption and emissions. Full article

The sustainable transformation of resource-based cities (RBCs) is a critical global challenge. The digital economy is emerging as a potential catalyst for this transition, but the precise mechanisms and spatial dynamics underlying its influence on urban resilience remain underexplored. This study addresses this gap by investigating how the digital economy impacts RBC’s resilience, with a focus on both internal mechanisms and cross-regional spatial effects. Fixed effects, mediation, exploratory spatial data analysis (ESDA) and spatial Durbin model (SDM) are used to examine the complex relationships observed in this context. The results reveal the following: (1) While the digital economy in Chinese RBCs demonstrated a stable upward trajectory, urban resilience, although it exhibited a general increase, remained fragile. (2) The digital economy significantly enhanced urban resilience (coefficient = 0.117, p < 0.05), in which context the most pronounced effects pertained to the social and economic resilience subsystems. (3) Green technological innovation (GTI) served as the core intermediary pathway (a × b = 0.017, p < 0.01). Industrial structure rationalization also served as a mediator. (4) The digital economy and urban resilience exhibited positive spatial autocorrelation (significant direct effects 0.032, p < 0.05), and the advancement of the digital economy in a focal city can enhance both the urban resilience of that city itself and that of neighboring cities indirectly. Full article

Wearable, rectifiable aerosol photometers (WRAPs), instruments with combined nephelometer and on-board filter-based sampling capabilities, generally show strong correlations with reference instruments across a range of ambient and household PM_2.5 concentrations. However, limited data exist on their performance when challenged by mixed aerosol exposures, such as those found in dusty occupational environments. Understanding how these instruments perform across a spectrum of environments is critical, as they are increasingly used in human health studies, including those in which concurrent PM_2.5 and coarse dust exposures occur simultaneously. The authors collected co-located, ~24 h. breathing zone gravimetric and nephelometer PM_2.5 measures using the MicroPEM v3.2A (RTI International) and the UPAS v2.1 PLUS (Access Sensor Technologies). Samples were collected from adult brick workers (n = 93) in Nepal during work and non-work activities. Median gravimetric/arithmetic mean (AM) PM_2.5 concentrations for the MicroPEM and UPAS were 207.06 (interquartile range [IQR]: 216.24) and 737.74 (IQR: 1399.98) µg/m³, respectively (p < 0.0001), with a concordance correlation coefficient (CCC) of 0.26. The median stabilized inverse probability-weighted nephelometer PM_2.5 concentrations, after gravimetric correction, for the MicroPEM and UPAS were 169.16 (IQR: 204.98) and 594.08 (IQR: 1001.00) µg/m³, respectively (p-value < 0.0001), with a CCC of 0.31. Digital microscope photos and electron micrographs of filters confirmed large particle breakthrough for both instruments. A possible explanation is that the miniaturized pre-separators were overwhelmed by high dust exposures. This study was unique in that it evaluated personal PM_2.5 monitors in a high dust occupational environment using both gravimetric and nephelometer-based measures. Our findings suggest that WRAPs may substantially overestimate personal PM_2.5 exposures in environments with concurrently high PM_2.5 and coarse dust levels, likely due to large particle breakthrough. This overestimation may obscure associations between exposures and health outcomes. For personal PM_2.5 monitoring in dusty environments, the authors recommend traditional pump and cyclone or impaction-based sampling methods in the interim while miniaturized pre-separators for WRAPs are designed and validated for use in high dust environments. Full article