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The design goal for the tracking interval of high-speed railway trains in China is 3 min, but it is difficult to achieve, and it is widely believed that it is mainly limited by the tracking interval of train arrivals. If the train arrival tracking interval can be compressed, it will be beneficial for China's high-speed railway to achieve a 3-min train tracking interval. The goal of this article is to study how to compress the train arrival tracking interval.

By simulating the process of dense train groups arriving at the station and stopping, the headway between train arrivals at the station was calculated, and the pattern of train arrival headway was obtained, changing the traditional understanding that the train arrival headway is considered the main factor limiting the headway of trains.

When the running speed of trains is high, the headway between trains is short, the length of the station approach throat area is considerable and frequent train arrivals at the station, the arrival headway for the first group or several groups of trains will exceed the headway, but the subsequent sets of trains will have a headway equal to the arrival headway. This convergence characteristic is obtained by appropriately increasing the running time.

According to this pattern, there is no need to overly emphasize the impact of train arrival headway on the headway. This plays an important role in compressing train headway and improving high-speed railway capacity.

This paper aims to explore virtual simulations, merging artificial intelligence with real-world simulations, supporting Canadian armed forces (CAF) junior military leaders (JMLs) leadership development. Our research questions are: (1) How do virtual simulations support CAF junior military leadership development within a globalized and complex environment in the 21st century? (2) Could virtual simulations support a leadership culture change through efficacious “soft skills” training? In this paper, we explore the efficacy of virtual simulations for enhancing or developing leadership in JMLs in the CAF through a four-day pilot project with twenty JMLs (n = 20).

To assess the efficacy of virtual simulations for leadership development, we designed and studied a four-day leadership workshop for JMLs in the CAF using several virtual artificial intelligence leadership role-play simulations developed by McGraw Hill in their smart book textbook (Manning & Curtis, 2022) and several non-virtual in-class simulations for comparison. We selected four twenty to thirty-minute virtual role-play simulations that synergized with the in-person morning leadership workshop. We facilitated the three-hour leadership workshops and virtual/in-class simulations over four consecutive days. We emulated the ELESS model (De Freitas & Routledge, 2013) to assess soft and leadership skills.

The participants (JMLs) reported beneficial learning utility associated with the virtual simulations. Participants also expressed that further utility might be leveraged through virtual simulations incorporating greater complexity with multiple potential outcomes. They also suggested that leadership simulations designed around military situations would prove highly beneficial, something that was outside of the scope of this small pilot project.

Since this phase of our research is a pilot project, we secured a small amount of funding to test our hypothesis that simulations enhance leadership development for JMLs. These funding limitations resulted in several constraints in the research, such as the availability of virtual simulations articulating leadership from a military perspective. However, we believed the assigned organizational leadership simulations in the McGraw Hill Smart Book ecosystem would approximate generic leadership situations enough to test the hypothesis with the JMLs. As a pilot project, our sample size was relatively small (n = 20 JMLs) since participation was voluntary amidst a busy spring season for the JMLs. Since this is a pilot project, we suggest that twenty JMLs are an adequate sampling to test the hypothesis that simulations enhance JML leadership development. We will expand the sample size in the next phase of our research as we work with the CAF to expand the pool of participants to at least forty JML participants (n = 40). We also plan to secure further funding to collaborate with subject matter experts to design virtual simulations based on Canadian military leadership scenarios.

The CAF host robust simulations capabilities for combat training, but have not exploited the potential training and analytical capacity of virtual leadership simulations for leadership development within the CAF. We believe that virtual simulations provide an opportunity for the CAF to effect desired culture change through leadership development that leverages the substantial pedagogical benefits of simulations.

The CAF encountered several detrimental leadership scandals that eroded the reputational capital of the CAF. In the current geo-political climate of an expanding North American Treaty Organization (NATO) and threats from several international actors, the CAF seeks to expand its capabilities by adding and enhancing its human capital. However, the CAF currently experiences a significant gap in its human capital aspirations. There is a unanimous consensus that the endemic traditional culture of the CAF, as expressed in the recent explosive leadership scandals, is a deterrent to recruitment and thus weakens the CAF’s capability. The CAF targets leadership development with new leadership paradigms as pivotal to culture change. The CAF suggests that by enhancing leadership development in the CAF the new cadre of leadership will change the culture of the CAF and thereby enhance the reputational capital of the CAF. It is believed that this rejuvenated culture will lead to greater recruitment and retention, leading to a strengthened military. A strengthened military is important to provide effective support and protection for the Canadian people in these volatile and uncertain times. This expanded capacity will enable the CAF to address external military threats more effectively and also the increasing operations other than war (OOTW), such as the military support of long-term care facilities during COVID-19 or the military’s support in fighting record wildfires and the military’s support in climate change related disasters such as flooding.

The satisfaction measures indicated by the participants are typical evaluative measures of leadership development (Noe, 2023). These satisfaction ratings do not, however, indicate whether training has produced a change in behaviour (Brown, 2022). The implications of these outcomes for leadership education are that role-player simulations are useful leadership education and development tools because they provide a theatre of practice in which mistakes are not detrimental and serve as learning moments (Moore, 2012; Piro and O’Callaghan, 2021; Riotto, 2021). Further, the importance of role-player simulations that closely approximate the sector where leadership is experienced and practiced is perceived to enhance the experience. While the CAF invest in combat related simulations, but leadership development simulations are not as evident in the training and development array. This study seeks to assess their potential value as a leadership development tool within the wider context of character development as a leadership competency.

In the realm of construction education, the investigation of immersive learning and extended reality (XR) technologies has experienced a surge in recent times. Nevertheless, there remains a notable lack of comprehension surrounding the most efficient ways to integrate these technologies into tailored teaching approaches for vocational construction training. This research study aims to pinpoint the key factors that construction vocational education and training (VET) providers must consider when introducing XR technologies into their training schemes.

This study conducted an in-depth literature review to develop an initial framework to summarise training, technology and institutional factors influencing the educational-technology integration of XR technologies in VET. In addition, this study utilised a Delphi technique, including semi-structured group discussions and two rounds of online follow-up questionnaires, to capture VET experts’ judgements on the importance of decision-making criteria.

This study has identified the critical factors to be considered in the VET sector when adopting XR technologies. Findings revealed institutional factors were the most important criteria for participants, followed by training and technology factors.

The current decision-making process focuses on selecting XR technologies rather than evaluating their performance after implementation. Therefore, more research is needed to monitor the implementation of this technology in curricula from a senior management perspective. This will help to understand the cost and value factors related to the value proposition of XR technologies in courses.

To ensure the success and long-term viability of the technology-curriculum interface, it is important to consider factors such as the availability of technical and educational support, data security and cost-effectiveness. It is also crucial to focus on ease of use and content development that emphasises instruction to create engaging content for learners.

The potential impact of this study is underpinned by two facts: (1) it constitutes the first effort made in the field to comprehensively elicit VET expert judgements in relation to XR technologies, and (2) it offers decision-making criteria that are at play in seeking to take advantage of high-cost technologies that are rapidly evolving. While there is no simple checklist for XR implementation, this study takes a step further to identify significant factors influencing XR integration in vocational construction training.

This study explores the impact of new technologies, such as simulation and virtual reality, on the pedagogy and learning of engineering students. It aims to compare the effectiveness of these digital tools against traditional teaching methods in enhancing student learning experiences.

Utilizing a quantitative research approach, the study involved third-year engineering students from the “Production Management” course at the School of Engineering of Vitoria-Gasteiz. Data were collected through an ad hoc questionnaire and analyzed using SPSS software, focusing on student satisfaction, challenges in adopting new technologies and the evolving roles of students and teachers.

The research highlighted several key aspects. Firstly, it identified the need for adapting teaching methods to incorporate new technologies effectively. Secondly, the integration of simulation and virtual reality was found to facilitate a deeper understanding of real-world problems, as students could engage with these issues in a simulated, virtual environment. Finally, the study emphasized the importance of pedagogical approaches that leverage these technologies to increase student involvement and motivation. The results suggest a positive impact of digital tools on the learning process in engineering education.

The study’s scope was limited to one course within a single institution, suggesting the need for broader research across various disciplines and educational settings.

This research offers valuable insights into the integration of simulation and virtual reality in engineering education, underscoring their potential to enhance the learning experience and knowledge acquisition among students.

Three-dimensional (3D)printed skulls for neurosurgical training are increasingly being used due to the widespread access to 3D printing technology, their low cost and accuracy, as well as limitations and ethical concerns associated with using human cadavers. However, little is known about the risks of airborne particles or volatile organic compounds (VOCs) released while drilling into 3D-printed plastic models. The aim of this study is to assess the level of exposure to airborne contaminants while burr hole drilling.

3D-printed skull samples were produced using three different materials (polyethylene terephthalate glycol [PETG], white resin and Bone^STN) across three different 3D print processes (fused filament fabrication, stereolithography [SLA] and material jetting). A neurosurgeon performed extended burr hole drilling for 10 min on each sample. Spot measurements of particulate matter (PM2.5 and PM10) were recorded, and air samples were analysed for approximately 90 VOCs.

The particulate matter for PETG was found to be below the threshold value for respirable particles. However, the particulate matter for white resin and Bone^STN was found to be above the threshold value at PM10, which could be harmful for long periods of exposure without personal protective equipment (PPE). The VOC measurements for all materials were found to be below safety thresholds, and therefore not harmful.

To the best of the authors’ knowledge, this is the first study to evaluate the safety of 3D-printed materials for burr hole surgical drilling. It recommends PETG as a safe material requiring minimal respiratory control measures, whereas resin-based materials will require safety controls to deal with airborne particles.

We explore how sustainable management education (SME) can help prepare future leaders to manage crises effectively. Precisely, the intricacies of articulating moral and economic imperatives for businesses in a manner that engages students in sustainable behavior are a serious challenge for SME. We study how to integrate reminders of moral and economic imperatives in a socially responsible investment (SRI) stock-picking simulation created for SME.

Adopting an experimental design, we analyzed how the reminders affected the average environment social governance (ESG) integration in the portfolios of 127 graduate students in finance over a twelve-week period.

Our results show how essential it is to balance the two imperatives. The highest level of sustainable investment is attained when utilizing both reminders.

Our findings have practical implications for implementing and organizing SME in business schools to educate responsible leaders who are able to effectively manage crises. Learning responsible management is most effective when students are exposed to the inherent tension between moral and economic imperatives. Hence, our findings corroborate the win-win conception of SME.

No management decision study has experimentally measured the effects of SME practices on students' actual behavior. Our research fills this gap by complementing previous studies on the effectiveness of teaching practices, first by drawing on behavioral sciences and measuring changes in students' actual sustainability behavior and second by introducing moral and economic imperatives into an innovative teaching resource (TR) dedicated to SME.

As data centres grow in size and complexity, traditional air-cooling methods are becoming less effective and more expensive. Immersion cooling, where servers are submerged in a dielectric fluid, has emerged as a promising alternative. Ensuring reliable operations in data centre applications requires the development of an effective control framework for immersion cooling systems, which necessitates the prediction of server temperature. While deep learning-based temperature prediction models have shown effectiveness, further enhancement is needed to improve their prediction accuracy. This study aims to develop a temperature prediction model using Long Short-Term Memory (LSTM) Networks based on recursive encoder-decoder architecture.

This paper explores the use of deep learning algorithms to predict the temperature of a heater in a two-phase immersion-cooled system using NOVEC 7100. The performance of recursive-long short-term memory-encoder-decoder (R-LSTM-ED), recursive-convolutional neural network-LSTM (R-CNN-LSTM) and R-LSTM approaches are compared using mean absolute error, root mean square error, mean absolute percentage error and coefficient of determination (R²) as performance metrics. The impact of window size, sampling period and noise within training data on the performance of the model is investigated.

The R-LSTM-ED consistently outperforms the R-LSTM model by 6%, 15.8% and 12.5%, and R-CNN-LSTM model by 4%, 11% and 12.3% in all forecast ranges of 10, 30 and 60 s, respectively, averaged across all the workloads considered in the study. The optimum sampling period based on the study is found to be 2 s and the window size to be 60 s. The performance of the model deteriorates significantly as the noise level reaches 10%.

The proposed models are currently trained on data collected from an experimental setup simulating data centre loads. Future research should seek to extend the applicability of the models by incorporating time series data from immersion-cooled servers.

The proposed multivariate-recursive-prediction models are trained and tested by using real Data Centre workload traces applied to the immersion-cooled system developed in the laboratory.

This study demonstrates how becoming a high-reliability institution in health care is a priority, given the high-risk environment in which an error can result in harm. Literature conceptually supports the need for highly reliable health care facilities but does not show a comprehensive approach to operationalizing the concept into the daily workforce to support patients. The Veterans Health Administration closes the gap by documenting a case study that not only demonstrates specific actions and functions that create a high-reliability organization (HRO) for safety and improvement but also created a learning organization by spreading the knowledge to other facilities.

The authors instituted a methodology consisting of assessments, training and educational simulations to measure, establish and operationalize activities that identified and prevented harmful events. Visual communication boards were created to facilitate team huddles and discuss improvement ideas. Improvements were then measured and analyzed for purposeful outcomes and return on investment (ROI).

HRO can be operationalized successfully in health care systems. Measurable outcomes verified that psychological safety was achieved through the identification and participation of 3,184 process improvement projects over a five-year period, which yielded a US$2.8m ROI. Documented processes and activities were used for educational teachings, which were disseminated to other Veteran Affairs Medical Center’s through the Truman HRO Academy.

This case study is limited to one hospital in the Veterans Health Administration (VHA) network. As the VHA continues to deploy the methods outlined to other hospitals, the authors will perform incremental data collection and ongoing analysis for further validation of the HRO methods and operations. Hospitalists can adapt the methods in the case study for practical application in a health care setting outside of VHA. Although the model is rooted in health care, the methods may be adapted for use in other industries.

This case study overcomes the limitations within literature regarding operationalizing HRO by providing actual activities and demonstrations that can be implemented by other health care facilities.

The purpose of this study is to propose a precise and standardized strategy for numerically simulating vehicle aerodynamics.

Error sources in computational fluid dynamics were analyzed. Additionally, controllable experiential and discretization errors, which significantly influence the calculated results, are expounded upon. Considering the airflow mechanism around a vehicle, the computational efficiency and accuracy of each solution strategy were compared and analyzed through numerous computational cases. Finally, the most suitable numerical strategy, including the turbulence model, simplified vehicle model, calculation domain, boundary conditions, grids and discretization scheme, was identified. Two simplified vehicle models were introduced, and relevant wind tunnel tests were performed to validate the selected strategy.

Errors in vehicle computational aerodynamics mainly stem from the unreasonable simplification of the vehicle model, calculation domain, definite solution conditions, grid strategy and discretization schemes. Using the proposed standardized numerical strategy, the simulated steady and transient aerodynamic characteristics agreed well with the experimental results.

Building upon the modified Low-Reynolds Number k-e model and Scale Adaptive Simulation model, to the best of the authors’ knowledge, a precise and standardized numerical simulation strategy for vehicle aerodynamics is proposed for the first time, which can be integrated into vehicle research and design.

Generative AI and more specifically ChatGPT has brought a revolution in the lives  of people by providing them with required knowledge that it has learnt from an exponentially large knowledge base. In this viewpoint, we are initiating the debate and offer the first step towards Generative AI based knowledge management systems in organizations.

This study is a viewpoint and develops a conceptual foundation using existing literature on how ChatGPT can enhance the KM capability based on Nonaka’s SECI model. It further supports the concept by collecting data from a public sector univesity in Hong Kong to strenghten our argument of ChatGPT mediated knowledge management system.

We posit that all four processes, that is Socialization, Externalization, Combination and Internalization can significantly improve when integrated with ChatGPT. ChatGPT users are, in general, satisfied with the use of ChatGPT being capable of facilitating knowledge generation and flow in organizations.

The study provides a conceptual foundation to further the knowledge on how ChatGPT can be integrated within organizations to enhance the knowledge management capability of organizations. Further, it develops an understanding on how managers and executives can use ChatGPT for effective knowledge management through improving the four processes of Nonaka’s SECI model.

This is one of the earliest studies on the linkage of knowledge management with ChatGPT and lays a foundation for ChatGPT mediated knowledge management system in organizations.