Technology Research Articles

FACTORSINFLUENCINGEFFECTIVETELEHEALTHMANAGEMENT: PERSPECTIVES OF QUALITY COMPETENCY AND ORGANIZATIONAL CHANGE

This study investigates key factors influencing effective telehealth management in healthcare organizations in Saudi Arabia, particularly within primary health centers in Riyadh Saudi Arabia. Present study focuses on five primary areas: technology infrastructure, provider training and competency,patientengagement,regulatorycomplianceandqualityassurance,andorganizational culture and change management. A comprehensive survey questionnaire was conducted among healthcare staff, including directors, physicians, head nurses, and administrative personnel, to assess these factors' impact on telehealth effectiveness. SPSS was utilized for data analysis. Analysis of data revealed significant positive relationships between all suggested constructs which leads consequently to effective telehealth management. Specifically, technology infrastructure and organizational culture emerged as the strongest predictors. Further, findings emphasize the necessity of investing in robust technology systems, enhancingprovidertraining,,ensuringregulatorycompliance,promotingpatientengagement,and fostering a supportive organizational culture for the successful implementation of telehealth services. Study further provides practical implications for healthcare organizations and policymakers, offeringinsightsintooptimizingtelehealthservicestoimprovehealthcaredeliveryinSaudiArabia.

Coupling of Elements of Chemical–Technological System Operating under Vacuum (on the Example of an Amine Mixture Rectification Unit)

Coupling of Elements of Chemical–Technological System Operating under Vacuum (on the Example of an Amine Mixture Rectification Unit)

The mediating effects of perceived usefulness and perceived ease of use on nurses’ intentions to adopt advanced technology

This study explored the role of technology systems in influencing nurses’ intentions to adopt medical applications that enhance their performance and how technology contributes to improvements in hospital systems. The study examines the intention to use technology through the mediating effects of perceived usefulness and perceived ease of use, with technology sophistication. A random sampling method was employed to gather 687 responses from nurses. The statistical analysis was conducted using AMOS version 25.0 and SPSS. The findings indicate a significant association between technology sophistication (TS), perceived usefulness (PU), perceived ease of use (PEU), and intention to use (IU). Additionally, PU and PEU positively mediate the relationship between TS and IU. This research will benefit policymakers aiming to enhance nurses’ performance by adopting modern technology. Authorities should consider introducing advanced technology systems to meet the goals of hospital administration and support nurses effectively.

Assessment of Ecosystem Vulnerability in the Tropic of Cancer (Yunnan Section)

The stability and diversity of the natural landscape is critical to maintaining the ecological functions of a region. However, ecosystems in the Yunnan section of the Tropic of Cancer face increasing pressure from climate change, human activities, and natural disasters, which significantly influence their vulnerability. Ecosystem vulnerability is determined by structural and functional sensitivity, coupled with insufficient adaptability to external stressors. While previous research has emphasized the effects of climate change, the multidimensional impacts of land use and human activities have often been overlooked. This study aims to comprehensively assess the ecological vulnerability of the Yunnan section of the Tropic of Cancer, addressing this research gap by utilizing geographic information system (GIS) technology and the Vulnerability Scoping Diagram (VSD) model. The study constructs a multidimensional evaluation index system based on exposure, sensitivity, and adaptive capacity, with a specific focus on the effects of land use, human activities, and natural disasters. Key indicators include road and population density, soil erosion, and geological hazards, along with innovative considerations of economic adaptive capacity to address gaps in previous assessments. The findings highlight that ecological vulnerability is predominantly concentrated in areas with low vegetation cover and severe soil erosion. Human activities, particularly road and population density, are identified as significant drivers of ecological vulnerability. Sensitivity is heavily influenced by soil erosion and geological disasters, while economic adaptability emerges as a critical factor in mitigating ecological risks. By proposing targeted policy recommendations—such as enhancing ecological protection and restoration, optimizing land use planning, and increasing public environmental awareness—this study provides actionable strategies to reduce ecological vulnerability. The findings offer crucial scientific support for improving the ecological environment in the Tropic of Cancer region and contribute to achieving sustainable development goals.

Micro-physiological system of human lung: The current status and application to drug discovery.

Various attempts have been made to elucidate the mechanisms of human lung development, its physiological functions, and diseases, in the hope of new drug discovery. Recent technological advancements in experimental animals, cell culture, gene editing, and analytical methods have provided new insights and therapeutic strategies. However, the results obtained from animal experiments are often inconsistent with those obtained from human data because of reproducibility issues caused by structural and physiological differences between mice and humans. In addition, it is not possible to accurately reproduce the internal environment of the human lung structure using conventional two-dimensional (2D) or three-dimensional (3D) cell culture methods. As a result, the micro-physiological system (MPS) technology, such as "lung-on-a-chip" that can culture human cells in a state close to human body environment have been developed, and its applications to disease models, toxicological studies, and drug discovery are accelerated worldwide. Here, we focus on the mimetics of the lung, including "lung-on-a-chip" technology, and review their recent progress, achievements and challenges. Finally, we discuss the role of these chips in drug discovery for refractory lung diseases.

Construction of Key Technology System for Mine Ecological Restoration Under System Perspective

Mine ecological restoration has experienced a long-term development process in China, in which various technologies have been constantly developing and integrating. Based on the related theoretical research and field program, the technical system of mine ecological restoration was constructed, and the characteristics of key technologies were specifically grasped. In this research, the environment, including natural elements and the spatial environment, is the object of mine ecological restoration, which requires further long-term investigation and monitoring. Therefore, natural element restoration technology, space environment restoration technology, and environmental survey and restoration monitoring technology should be considered when establishing technical systems. The research showed that： ① In mine natural element restoration, where soil and water are important, traditional technologies like pollution abatement with physical, chemical, and biological methods have been extensively used. Meanwhile, artificial soil reconstruction and multi-technology joint remediation became the main study focus in soil restoration and artificial wetlands have been gradually constructed as a new method in water restoration, covering water system restoration and pollution control. ② The two tasks of space environment restoration were geological disaster prevention and vegetation re-greening. Major technologies of the former were applied to surface mine slope treatment and mining subsidence area control, the latter of which could be divided into three technical links： vegetation selection, construction, and maintenance. Although many technologies are valid, a few frontiers need to be further pursued. ③ The mine environmental investigation and restoration monitoring were based on 3S technologies, containing GIS, GPS, and RS, all of which are developing rapidly but still have a large space for integration and innovation.

Optimization design and application of library face recognition access control system based on improved PCA.

The application of face recognition technology in Library Access Control System (LACS) has an important impact on improving the security and management efficiency of the library. However, the traditional face recognition methods have some limitations in the face of complex environmental conditions such as illumination and posture change. To solve this problem, an improved method combining the Aggregating Spatial Embeddings for Face Recognition (ASEF) algorithm and Principal Component Analysis (PCA) is proposed. The PCA algorithm is optimized by introducing beta prior and full probability Bayesian model. In addition, the research also integrates K-means Clustering Algorithm (KA) to further improve the accuracy and efficiency of face recognition. The experiment showed that the improved PCA method had an average recognition rate of 92.6%, an average recognition speed of 0.40s, and higher accuracy compared to other related methods, reaching 96%. In practical applications, the system quickly and accurately completes the identification of personnel entry and exit, and improves the efficiency and security of library access management.

Advancements in large‐scale energy storage technologies for power systems

Advancements in large‐scale energy storage technologies for power systems

Surveillance Capitalism: Origins, History, Consequences

This article investigates the early history and recent development of what is now termed surveillance capitalism. It argues that an underappreciated aspect of the surveillance of people and intensive data collection is a regularization of behavior that attempts to erase uncertainty. This process has been ongoing for more than a century, but its expansion through increasingly sophisticated digital technology and the widespread adoption of data gathering as a business strategy has the potential to stifle and inhibit the innovative entrepreneurship that is crucial to the capitalist system. How this will play out remains unclear, but history argues that we should look for ways to mitigate the potentially negative consequences of complex technological systems such as these.

New horizons in smart plant sensors: key technologies, applications, and prospects.

As the source of data acquisition, sensors provide basic data support for crop planting decision management and play a foundational role in developing smart planting. Accurate, stable, and deployable on-site sensors make intelligent monitoring of various planting scenarios possible. Recent breakthroughs in plant advanced sensors and the rapid development of intelligent manufacturing and artificial intelligence (AI) have driven sensors towards miniaturization, intelligence, and multi-modality. This review outlines the key technologies in developing new advanced sensors, such as micro-nano technology, flexible electronics technology, and micro-electromechanical system technology. The latest technological frontiers and development trends in sensor principles, fabrication processes, and performance parameters in soil and different segmented crop scenarios are systematically expounded. Finally, future opportunities, challenges, and prospects are discussed. We anticipate that introducing advanced technologies like nanotechnology and AI will rapidly and radically revolutionize the accuracy and intelligence of agricultural sensors, leading to new levels of innovation.

Impedance Reshaping Strategy for Battery Energy Storage Systems Based on Partial Power Conversion

To avoid additional component losses while significantly improving the energy conversion efficiency of battery energy storage systems, the application of series-connected partial power converter (S-PPC) technology in battery energy storage systems is investigated in this study. In the S-PPC battery energy storage system configuration, coupling effects exist between the dc-link side and the battery-series side. The impedance modeling of a battery energy storage system is performed while taking these coupling effects into consideration. To address the instability observed during battery discharge conditions, an impedance reshaping control strategy that is suitable for the S-PPC battery energy storage system is proposed. The proposed method focuses on adjusting the input impedance of the load converter within a limited frequency band centered on the system’s oscillation frequency. This targeted approach significantly improves the stability of the system while ensuring ease of implementation and maintaining high reliability. Finally, the experimental results validate the theoretical analysis.

The Impact on International Law and Response Strategies of Artificial Intelligence Technology Development in the Context of Digital Economy: Taking WTO as a Research Perspective

The rapid development of digital technology has made international interactions more convenient and frequent, and nowadays, the rapid change and development of artificial intelligence has brought unprecedented challenges to the international law. The international community has put forward an urgent demand for the improvement and development of the international law system. On the one hand, the wide application of AI in international trade has had a great impact and influence on the global value management; on the other hand, the development of AI has put forward new challenges to the relevant rules of the WTO, which include, but are not limited to, whether the existing World Trade Organisation (WTO) treaties are applicable to AI in the context of the digital economy, such as the GATT, GATS; whether existing WTO rules are formulated with the application of AI, such as GATT, GATS; whether emerging technologies are taken into account in the formulation of existing WTO rules; and the challenge of AI to the existing legal system system. The World Trade Organisation (WTO), as the most important intergovernmental trade organisation in the world and the international community today, still plays an important role in regulating and deploying the development of AI technologies in the international trading system. Based on this, this paper takes the WTO as the research perspective to explore the impact of the digital economy and the development of artificial intelligence technology on international law, combining the existing rules system of the WTO and the characteristics of the development of artificial intelligence technology, research and argumentation to deal with the impact of the strategy, with a view to guaranteeing better development of artificial intelligence technology for the WTO, better service to mankind to offer advice.

Biosensor technology for adaptive intelligent education systems to enhance personalized English learning

The integration of biosensor technologies, like electroencephalography (EEG), has extended the limits of adaptive, intelligent education systems, offering real-time, personalized learning knowledge. This study explores the use of EEG to track and assess students’ cognitive states, allowing for the improvement of an active, adaptive English learning system that tailors content according to every student’s participation and improvement. Students’ cognitive states serve as the foundation for personalized education responses that motivate and enhance their participation. EEG data are gathered during English language testing to assess the correlation between learners’ cognitive states and their performance. Noise reduction is one of the preprocessing stages that ensures clear and pertinent data for analysis. Power spectral density (PSD) for feature extraction approaches is used to identify key cognitive patterns. Based on real-time EEG data, the personalized education feedback system constantly modified the course material, enhancing motivation and learning results. This research proposed a novel Dynamic Osprey Optimized Intelligent Gradient Boosting Machines (DOO-IGBM) to assess and improve the efficiency of an adaptive intelligent education system. The findings suggest that EEG-based adaptive systems make it possible to significantly progress English learning by offering personalized education paths based on brain activity to other conventional algorithms with 98.5% accuracy, 97.7% precision, 98% recall, and 98.6% F1-score. These outcomes provide precious insights and data to support the future development of adaptive, intelligent education systems for language learning.

Improved grey wolf optimizer for optimal reactive power dispatch with integration of wind and solar energy

The aim of this paper is to present a new improved grey wolf optimizer (IGWO) to solve the optimal reactive power dispatch (ORPD) problem with and without penetration of renewable energy resources (RERs). It is a nonlinear multivariable problem of optimization, with multiconstraints. The purpose is to minimize real power losses and improve the voltage profile of a given electric system by adjusting control variables, such as generator voltages, tap ratios of a transformer, switching VAr sources, without violating technical constraints that are presented as equalities and inequalities. Methodology. Metaheuristics are stochastic algorithms that can be applied to solve a wide variety of optimization problems without needing specific problem structure information. The penetration of RERs into electric power networks has been increased considerably to reduce the dependence of conventional energy resources, reducing the generation cost and greenhouse emissions. It is essential to include these sources in power flow studies. The wind and photovoltaic based systems are the most applied technologies in electrical systems compared to other technologies of RERs. Moreover, grey wolf optimizer (GWO) is a powerful metaheuristic algorithm that can be used to solve optimization problems. It is inspired from the social hierarchy and hunting behavior of grey wolves in the wild. The novelty. This paper presents an IGWO to solve the ORPD problem in presence of RERs. Methods. The IGWO based on enhancing the exploitation phase of the conventional GWO. The robustness of the method is tested on the IEEE 30 bus test system. For the control variables, a mixed representation (continuous/discrete), is proposed. The obtained results demonstrate the effectiveness of the introduced improvement and ability of the proposed algorithm for finding better solutions compared to other presented methods. References 40, tables 3, figures 9.

Zonal Safety and Particular Risk Analysis for Early Aircraft Design

Safety is paramount in aircraft design, and increasing aircraft complexity necessitates safety assessments early in design. For unconventional aircraft with novel propulsion or system technologies, it becomes even more critical to investigate safety as early as possible to avoid unfeasible configurations. In this context, the particular risk analysis (PRA) and the zonal safety analysis (ZSA) are essential to assess early, as they impact the aircraft configuration. These analyses require a three-dimensional (3D) aircraft model and substantial manual effort, limiting the ability to perform rapid iterations required to support design space exploration and multidisciplinary design optimization (MDO). To analyze many aircraft configurations and system architectures, the 3D parametric model and the PRA and ZSA require automation. This paper reviews methodologies for performing the ZSA and PRA from a systems point of view and proposes parametric zone definition, identification of risk zones, and a conceptual-level analysis of the component placement strategy. The effectiveness of the proposed approach is demonstrated with an aft equipment bay of a business aircraft for varying geometrical granularity and system electrification. Overall, the presented method is a step toward integrating system safety analysis into MDO environments, thus increasing conceptual design maturity and reducing development time.

Two distinct neural pathways for mechanical versus digital technology.

Technology pervades every aspect of our lives, making it crucial to investigate how the human mind deals with it. Here we examine the cognitive and neural foundations of technological cognition. In the first fMRI experiment, participants viewed videos depicting the use of mechanical tools (e.g., a screwdriver) and digital tools (e.g., a smartphone) compared to simple object movements. Results revealed a key dissociation: mechanical tools extensively activated the dorsal and ventro-dorsal visual streams, which are motor- and action-oriented brain systems. Conversely, digital tools largely engaged the ventral visual stream, associated with conceptual and social cognition. A second behavioral experiment showed a pronounced tendency to anthropomorphize digital tools. A third experiment involving a priming task confirmed that digital tools activate the social brain. The discovery of two different neurocognitive systems for mechanical versus digital technology offers new insights into human-technology interaction and its implications for the evolution of the human mind.

Design of an information system for the management, visibility, and scientific positioning in research centers: CRIS-AGROSAVIA System study case

This research focused on the use of technology to facilitate the management of resources, products, and knowledge services in research, development, and innovation (R+D+i) organizations. Specifically, it highlighted how Current Research Information Systems (CRIS) could be employed for this purpose. The study aimed to develop and implement a CRIS information system at the AGROSAVIA Research Center, with an emphasis on integrating the system with institutional repositories and external/internal systems to manage scientific and technological knowledge assets effectively.Methods:The process of creating the CRIS involved several stages: planning, requirements analysis, system design, development, and implementation. Key elements included the deployment of system interfaces for the target audience (stakeholders of the National System of Science, Technology, and Innovation) and the use of a recognized data model (CERIF standard) to enhance metadata generation, ensure standardization, and enable interoperability with external and internal systems.Results:The system was designed with two primary interfaces: a public version for the external scientific community and a corporate version for internal users of the research center. The CERIF-based data model facilitated repository structuring and the loading of an initial data baseline, supporting effective data management and decision-making processes.Conclusion:This study provides a valuable case for those looking to build information systems for knowledge management. The CRIS developed at AGROSAVIA acted as a tool for process evaluation, scientific communication, and dissemination, offering key insights into the technological architecture, data management model, and technological deployment required for such systems

Combining GIS and machine learning for enhanced tsunami risk management: A review of current approaches and unexplored future potential

This review article aims to discuss the current status and future potential of Geographic Information Systems (GIS) in map-based technology of tsunami risk management, especially in seismically active, well-known tsunami regions of the world. It presents GIS technologies for hazard mapping, risk assessment, and information generation for disaster-response operations. These are important tools for accurately mapping vulnerable areas by integrating real-time and historical data to develop accurate forecasts for possible tsunamis. Demographic and geographic data were also analyzed by GIS to determine the optimum route to develop evacuation strategies. A set of case studies demonstrates how GIS improves community resilience by supporting informed decision-making. In addition, suggestions are made for how future steeps as the integration of machine learning techniques as emerging tools for analyzing and classifying complex and vast datasets, which may enhance GIS applications in tsunami risk management to improve the accuracy and utility of these tools.

Integration of SSID and blockchain technology for advanced knowledge management system

Integration of SSID and blockchain technology for advanced knowledge management system

Digital grid-connected control technology for more electric aircraft power generation system based on model predictive control

Digital grid-connected control technology for more electric aircraft power generation system based on model predictive control