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Automated guided vehicles(AGV)are crucial for the horizontal transportation of automated container terminals.Accurate estimation of the travel time of each AGV will reduce the number of idle AGV resources and increase the efficiency of the entire terminal.This paper proposes a method for travel time estimation of AGV in automated container terminals.Firstly,the target route of AGV is divided and encoded into several segments.Secondly,other routes are encoded as environment information,which depart before or after the target route.And the conflict between these routes and target route is estimated as an auxiliary task.Finally,the travel time with all encodings is calculated.The proposed method introduces the influence of path conflicts on time estimation.Experiments based on historical data of automated terminals show that,compared with static time estimation methods commonly used in AGV scenarios,the proposed method can reduce the time estimation error by more than 18%,and can estimate the travel time more accurately.

Simple Summary: This study reports on a comparison between the Hugo RAS system and the da Vinci (DV) system in robot-assisted radical prostatectomy. The parameters consisted of intraoperative anastomosis and overall console time, functional outcomes, and oncological outcomes. We found that, although the anastomosis time of the urinary bladder and urethra was lengthened, the overall console time was not affected. In short-term functional and oncological outcomes, these two parameters were not compromised in the Hugo RAS group. Based on our results, the DV system could facilitate swift adaptation to the Hugo RAS system. Importantly, the functional and oncological outcomes would not be compromised in the process of adapting to the Hugo RAS system. Objective: In a previous study, we proved that an experienced urologist is more likely to adapt to the Hugo RAS system. Based on this, we further examine various parameters in this study. Parameters included in this study consisted of console time, functional outcomes, and oncological outcomes. Materials and Methods: A total of 60 patients who underwent robot-assisted radical prostatectomy (RARP) performed by a single surgeon using the da Vinci (DV) system (n = 30) or the Hugo RAS system (n = 30) between March 2023 and August 2023 were included in the analysis. The intraoperative operative time was categorized into vesicourethral anastomosis time and overall console time. Functional and oncological outcomes were documented at the 1st and 3rd postoperative months. Parametric and non-parametric methods were adopted after checking skewness and kurtosis, and an α value of 5% was used to determine the significance. Results: The vesicourethral anastomosis time was significantly lengthened (Hedge's g: 0.87; 95% confidence interval (CI): 0.34–1.39; J factor = 0.987). However, the overall console time was not affected. The functional (postoperative 3rd month: p = 0.130) and oncological outcomes (postoperative 3rd month: p = 0.103) were not significantly different. We also found that the adverse effect on surgical specimens and positive surgical margins was not affected (p = 0.552). Conclusion: During the process of adaptation, although intricate motions (such as the vesicourethral anastomosis time) would be lengthened, the overall console time would not change remarkably. In this process, the functional and oncological outcomes would not be compromised. This encourages urologists to adopt the Hugo RAS system in RARP if they have previous experiences of using the DV system, since their trifecta advantage would not be compromised. [ABSTRACT FROM AUTHOR]

AbstractCOVID-19 became a global epidemic after its breakout in December 2019. With the help of information technology, many countries developed contact tracing systems to reduce the spread of the epidemic. Although the WHO declared in May 2023 that COVID-19 is no longer a global public health emergency, the virus is still constantly changing and endangering individuals worldwide. In Taiwan, Social Distancing APP is a voluntary contact tracing app that has been downloaded and utilized approximately 9.5 million times. However, adoption remains low. To prevent the spread of the epidemic and encourage more people to use it, understanding the factors influencing continuance intentions to use social distancing apps is an important topic. The research model is composed of two parts: the modified expectation confirmation model (ECM) and personal norms. Our research model was assessed using data from a sample of 501 users of social distancing apps and was analyzed using the partial least squares structural equation model (PLS-SEM). The results of this study suggest that (1) personal norms are the most important factor influencing continuance intention, followed by satisfaction, perceived usefulness, and descriptive norms; (2) personal norms fully mediate the relationship between injunctive norms and continuance intention; (3) personal norms partially mediate the relationship between descriptive norms and continuance intention; (4) personal norms negatively moderate the relationship between satisfaction and continuance intention; and (5) personal norms positively moderate the relationship between disappointment and continuance intention. This study also discusses the implications of a modified ECM and personal norms for continuance intention to use contact tracing apps. [ABSTRACT FROM AUTHOR]