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Understanding Hazard Recognition Behaviors through Situational Awareness Assessment in Virtual Construction Environments
No full textEffective safety management at construction sites requires accurate hazard recognition. However, previous research studies have revealed a significant proportion of hazards remain unrecognized. Poor hazard recognition may be attributed to the deficiency at one or more levels of situational awareness (SA). Understanding how different hazard types, particularly those with high fatality rates, influence workers' SA is critical to improving safety outcomes. To address this research gap, three hazard types with different fatality hierarchies (F-I: fall, F-II: struck-by, and F-III: electrical hazards) were built in a complex and dynamic virtual reality (VR) construction environment. Participants' hazard recognition behaviors regarding hazard perception, comprehension, and projection (Level 1, 2, and 3 SA) were measured by a well-recognized situational awareness global assessment technique (SAGAT). The findings revealed that the achievement of SA varied among different hazard types and was impacted by fatality hierarchy. There was a consistent decline in success rates from Level 1 to Level 3 SA across all hazards, and the potential to achieve a high-level SA demonstrated a positive correlation with the hazard fatality hierarchy. Specific reasons for failure at each SA level attributed to shortcomings included a deficiency in prior knowledge, narrowed attention, and the increased demand for cognitive resources. The findings enhance the understanding of workers' SA in hazard recognition behaviors and provide a foundation for developing customized interventions. These interventions can be tailored to address SA deficiencies at different levels based on hazard types with distinct fatality hierarchies, ultimately improving safety performance at construction sites.
Thermoforming 2D films into 3D electronics for high-performance, customizable tactile sensing
No full textThe demand for tactile sensors in robotics, virtual reality, and health care highlights the need for high performance and customizability. Despite advances in vision-based technologies, tactile sensing remains crucial for precise interaction and subtle pressure detection. In this work, we present a design and fabrication method of customizable tactile sensors based on thermoformed three-dimensional electronics. This approach enables ultrawide modulus tunability (10 pascals to 1 megapascal) and superior mechanical properties, including negligible hysteresis and high creep resistance. These features allow the sensor to detect a broad spectrum of pressures, from acoustic waves to body weight, with high performance. The proposed sensors have high sensitivity (up to 5884 per kilopascal), high linearity (R2 = 0.999), low hysteresis (<0.5%), and fast response (0.1 milliseconds). We demonstrate applications in human-computer interaction and health care, showcasing their potential in various fields. This platform provides a scalable solution for fabricating versatile, high-performance tactile sensors.
A multi-model assessment of carbon neutrality pathways for Korea's power sector
No full textIn October 2021, Korea announced its mid-century carbon mitigation target of achieving carbon neutrality by 2050, reaffirming its commitment by enhancing its 2030 Nationally Determined Contribution (NDC). This study employs six energy-economic and integrated assessment models to explore net-zero emission pathways and strategies for Korea's power sector, while assessing the associated costs and challenges. The findings underscore the complexity and urgency of this transition, with the power sector playing a pivotal role in balancing the dual challenges of rapidly growing electricity demand and full decarbonization. A shift toward a renewable-dominated power sector emerges as a robust strategy, though it poses unprecedented technological and economic challenges. Large-scale low-carbon technologies, such as carbon capture and storage (CCS) and nuclear power, are identified as crucial solutions to reduce reliance on variable renewable energy sources and mitigate associated costs. Additionally, the study finds that current energy and climate policies are insufficient to meet the mid-century mitigation target, highlighting the urgent need for policy enhancements to bridge the gap and ensure the feasibility of Korea's carbon neutrality goal.
DEVICE PROVIDING GOLF TRAINING INTERFACE AND GOLF TRAINING METHOD USING THE SAME
No full text골프 트레이닝 인터페이스 장치가 개시된다. 본 발명에 따른, 골프 트레이닝 인터페이스 제공 장치는, 골프 스윙 시 사용자의 근전도 센서 신호를 포함하는 생체 역학적 데이터를 수집하는 사용자 데이터 수집부; 상기 사용자와 비교 대상이 되는 프로 골프 선수의 생체 역학적 데이터를 제공하는 프로 골퍼 데이터 제공부; 상기 사용자와 상기 프로 골프 선수의 생체 역학적 데이터를 비교 분석하는 데이터 비교 분석부; 및 상기 비교 분석 결과를 사용자에게 디스플레이하는 사용자 인터페이스;를 포함한다
A first-principles investigation of dual-ligand passivation for engineering surface defects in InAs colloidal quantum dots
No full textMultiFedRL: Efficient Training of Service Agents for Heterogeneous Internet of Things Environments
No full textThe Internet of Things (IoT) has gained more attention for enhancing users' daily lives in public spaces by providing services using shareable devices. However, uncertain factors and other services in the environment may affect the service severely, resulting in users' low satisfaction. Based on multiagent reinforcement learning and cluster-based federated learning, autonomous service agents may learn the complex influence of the factors from user feedback without sophisticated modeling and detection processes. However, conventional approaches are limited in dealing with multiple clustering dimensions of service agents and dynamic environmental contexts affecting the agents. In this work, we propose the multidimension and multiagent federated reinforcement learning (MultiFedRL) for efficient training of service agents in public IoT environments. First, we suggest a parallel structure of neural networks for multiple clustering dimensions to share parameters independently, solving the limitation of conventional cluster-based federated learning. Second, we suggest an environment-centric learnable communication protocol for the agents to summarize and interpret physical contexts consisting of static characteristics and dynamic states. To evaluate MultiFedRL, we developed a simulation framework for IoT services provided to mobile users in public spaces, imitating the user-service interaction based on crucial physics phenomena. Experimental results show that MultiFedRL increases user satisfaction by 82.9% and training efficiency by 24.5% compared to state-of-the-art cluster-based federated learning.
Predicting outcomes in patients with sepsis-associated encephalopathy using prefrontal functional connectivity analysis
No full textWe investigated the relationship between prefrontal functional connectivity of oxyhemoglobin and outcomes in sepsis-associated encephalopathy (SAE). Additionally, we developed a prognostic method for patients with SAE. A total of 40 consecutive patients with SAE were prospectively included. Cerebral oxyhemoglobin data were obtained using functional near-infrared spectroscopy. Functional connectivity such as density was evaluated as the strength of the temporal correlation between channels based on Pearson's correlation coefficient of oxyhemoglobin. We obtained clinical information and evaluated severity scores using Acute Physiology and Chronic Health Evaluation (APACHE) III. Outcomes were evaluated using the modified Rankin Scale (mRS) at discharge. Patients were categorized into two groups: good outcome (mRS 0-3), and poor outcome (mRS 4-6). Among the patients with SAE, 17 (42.5%) had good outcomes. Regarding connectivity analysis, density values were significantly higher in good outcome groups at all threshold values. The developed predictive method of good outcomes using the density value at a threshold of 0.6 and the APACHE III score showed very good predictive power (area under the curve 0.951 [95% confidence interval 0.893-1.00]). This method had better discrimination powers for predicting outcome than density had at 0.6 (0.716 [0.557-0.876]; P = 0.04) or the APACHE III score had alone (0.857 [0.735-0.979]; P = 0.09). A higher functional connectivity value of oxyhemoglobin in the prefrontal connectivity analysis was associated with good outcomes in SAE. Functional connectivity analysis of the prefrontal cortex and sepsis severity may help predict the prognosis in SAE patients.
Just Before Touch: Manipulating Perceived Haptic Sensations through Proactive Vibrotactile Cues in Virtual Reality
No full textSeasonal timing and interindividual differences in shiftwork adaptation
No full textMillions of shift workers in the U.S. face an increased risk of depression, cancer, and metabolic disease, yet individual responses to shift work vary widely. We find that a conserved biological system of morning and evening oscillators, which evolved for seasonal timing, may contribute to these interindividual differences. In this study, we analyze seasonality in medical interns working shifts, revealing that summer-winter variation correlates with increased circadian misalignment after shift work. Mathematical modeling suggests that seasonal timing influences the rate of adaptation to new schedules, predicting differential effects on morning and evening oscillators. Additionally, we examine genetic polymorphisms linked to seasonality in animals and find that human variants can impact how quickly circadian rhythms respond to schedule changes. Based on our findings, we hypothesize that the vast interindividual differences in shift work adaptation-critical for shift worker health-can in part be explained by biological mechanisms for seasonal timing.
