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In this study, the authors propose a novel digital twinning approach specifically designed for controlling transient thermal systems. The purpose of this study is to harness the combined power of deep learning (DL) and physics-based methods (PBM) to create an active virtual replica of the physical system.

To achieve this goal, we introduce a deep neural network (DNN) as the digital twin and a Finite Element (FE) model as the physical system. This integrated approach is used to address the challenges of controlling an unsteady heat transfer problem with an integrated feedback loop.

The results of our study demonstrate the effectiveness of the proposed digital twinning approach in regulating the maximum temperature within the system under varying and unsteady heat flux conditions. The DNN, trained on stationary data, plays a crucial role in determining the heat transfer coefficients necessary to maintain temperatures below a defined threshold value, such as the material’s melting point. The system is successfully controlled in 1D, 2D and 3D case studies. However, careful evaluations should be conducted if such a training approach, based on steady-state data, is applied to completely different transient heat transfer problems.

The present work represents one of the first examples of a comprehensive digital twinning approach to transient thermal systems, driven by data. One of the noteworthy features of this approach is its robustness. Adopting a training based on dimensionless data, the approach can seamlessly accommodate changes in thermal capacity and thermal conductivity without the need for retraining.

This study aims to explore vocational teachers' perceptions regarding workplace learning that align with students' training models and collaborative teaching involving specialised professionals within the context of industry-university collaboration.

Using a qualitative approach, the study conducted nine semi-structured interviews from three subject areas to better understand how vocational teachers’ work-based learning enhances their pedagogical practice in guiding students’ professional training. Thematic analysis was adopted to identify patterns that emerged from concepts and theories related to coding categories.

The authors identified three key components: vocational teachers’ workplace learning in connection with students’ training models, collaborative teaching with specialised professionals and teachers’ regular interactions with enterprises. The findings demonstrate that vocational teachers’ engagement in workplace learning pertaining to specific subjects provides a valuable avenue for enhancing curriculum design with collaboration with industry experts. This is key for supporting vocational students’ transitions into the workplace and ensuring their knowledge and skills are tailored to the industry-standard practice.

The data are limited to the review of interviews from three vocational subject areas as the representative sector in the study. However, this research implies effective knowledge transfer between workplace settings and vocational institutions, and vocational teachers need to integrate work-based vocational knowledge and skills in a relevant and applicable way across diverse classroom settings.

Fostering collaborative partnerships with local industries and professionals can be a primary way to facilitate authentic learning experiences that are linked to a specific vocational field and bridge the gap between diverse classroom learning and real-world work scenarios.

This study combines contemporary workplace learning theories with the conceptual understanding of vocational teachers’ involvement with industry-specific practice. Connecting teachers’ knowledge to the industry extends the input and collaboration from professionals and field experts to the diverse vocational classrooms.

The purpose of this study is to investigate the impact of rapid internationalization by emerging-market multinational enterprises (EMNEs) on their innovation performance. It also seeks to identify any potential moderating factors that could influence this relationship.

By analyzing data from listed Chinese MNEs from 2012 to 2022, this study applies a negative binomial regression model to test the research hypotheses.

This study uncovers an inverted U-shaped relationship between the internationalization speed of EMNEs and their innovation performance. It also suggests that strong absorptive, learning and managerial capacities could play positive moderating roles in the effect of internationalization speed on EMNEs’ innovation performance.

This study highlights rapid global expansion, promoting new knowledge acquisition for EMNEs. However, due to time-compression dilemmas with limited EMNE firm-specific advantages, overly accelerated internationalization hinders learning effectiveness. Additionally, this study reveals the critical importance of three firm-specific capacities in EMNEs – absorptive, learning and managerial capacities – in efficiently assimilating newly acquired knowledge from foreign markets and enhancing their innovation performance through rapid internationalization.

Although change is a necessary part of organisational life, achieving a successful change is complex. Change readiness is a critical element in successful change implementation, yet studies assessing change readiness as an underlying mechanism in the link between organisational-level factors and successful change implementation are scarce, particularly in the African context. Accordingly, the present study examined the extent to which change readiness mediates the link between learning organisation and successful change implementation in the Ghanaian context.

The study utilized a standardized questionnaire to collect data from 364 participants, working in public and private universities in Ghana. The participants were selected via the convenience sampling strategy to complete the survey on the main variables at a single point in time. The study was purely quantitative, as path analysis – a form of structural equation modelling was employed to test the hypothesized relationships in the study.

The results show that both learning organisation and change readiness facilitated successful change implementation. Finally, it was observed that change readiness served as an important mediating mechanism in the link between learning organisation and successful change implementation.

Change readiness was found to explain the link between learning organisation and successful change implementation. Thus, it is important that managers and leaders of public and private sector educational institutions in Ghana invest resources into preparing and getting employees to accept, be committed to and ready for change.

The present study contributes to the scarce knowledge of the mediating role of change readiness in the link between learning organisation and successful change implementation in the African context.

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.

Compared with traditional methods relying on manual teaching or system modeling, data-driven learning methods, such as deep reinforcement learning and imitation learning, show more promising potential to cope with the challenges brought by increasingly complex tasks and environments, which have become the hot research topic in the field of robot skill learning. However, the contradiction between the difficulty of collecting robot–environment interaction data and the low data efficiency causes all these methods to face a serious data dilemma, which has become one of the key issues restricting their development. Therefore, this paper aims to comprehensively sort out and analyze the cause and solutions for the data dilemma in robot skill learning.

First, this review analyzes the causes of the data dilemma based on the classification and comparison of data-driven methods for robot skill learning; Then, the existing methods used to solve the data dilemma are introduced in detail. Finally, this review discusses the remaining open challenges and promising research topics for solving the data dilemma in the future.

This review shows that simulation–reality combination, state representation learning and knowledge sharing are crucial for overcoming the data dilemma of robot skill learning.

To the best of the authors’ knowledge, there are no surveys that systematically and comprehensively sort out and analyze the data dilemma in robot skill learning in the existing literature. It is hoped that this review can be helpful to better address the data dilemma in robot skill learning in the future.

This paper aims to solve the problem of the inability to apply learning methods for robot motion skills based on dynamic movement primitives (DMPs) in tasks with explicit environmental constraints, while ensuring the reliability of the robot system.

The authors propose a novel DMP that takes into account environmental constraints to enhance the generality of the robot motion skill learning method. First, based on the real-time state of the robot and environmental constraints, the task space is divided into different regions and different control strategies are used in each region. Second, to ensure the effectiveness of the generalized skills (trajectories), the control barrier function is extended to DMP to enforce constraint conditions. Finally, a skill modeling and learning algorithm flow is proposed that takes into account environmental constraints within DMPs.

By designing numerical simulation and prototype demonstration experiments to study skill learning and generalization under constrained environments. The experimental results demonstrate that the proposed method is capable of generating motion skills that satisfy environmental constraints. It ensures that robots remain in a safe position throughout the execution of generation skills, thereby avoiding any adverse impact on the surrounding environment.

This paper explores further applications of generalized motion skill learning methods on robots, enhancing the efficiency of robot operations in constrained environments, particularly in non-point-constrained environments. The improved methods are applicable to different types of robots.

Climate change is a problem that concerns all of us. Despite the information produced by organizations such as the Expert Team on Climate Change Detection and Indices and the United Nations, only a few cities have been planned taking into account the climate changes indices. This paper aims to study climatic variations, how climate conditions might change in the future and how these changes will affect the activities and living conditions in cities, specifically focusing on Mexico city.

In this approach, two distinct machine learning regression models, k-Nearest Neighbors and Support Vector Regression, were used to predict variations in climate change indices within select urban areas of Mexico city. The calculated indices are based on maximum, minimum and average temperature data collected from the National Water Commission in Mexico and the Scientific Research Center of Ensenada. The methodology involves pre-processing temperature data to create a training data set for regression algorithms. It then computes predictions for each temperature parameter and ultimately assesses the performance of these algorithms based on precision metrics scores.

This paper combines a geospatial perspective with computational tools and machine learning algorithms. Among the two regression algorithms used, it was observed that k-Nearest Neighbors produced superior results, achieving an R² score of 0.99, in contrast to Support Vector Regression, which yielded an R² score of 0.74.

The full potential of machine learning algorithms has not been fully harnessed for predicting climate indices. This paper also identifies the strengths and weaknesses of each algorithm and how the generated estimations can then be considered in the decision-making process.

This study aims to contribute to the enrichment of the literature by examining the impact of cross-cultural training on expatriates’ adjustment of Nigerian bankers on expatriate assignments in other African countries.

Data on cross-cultural adjustment from expatriate employees in five banks that collectively accounted for over 80 per cent of Nigerian banks with subsidiaries in other African were systematically selected for the investigation. This data was collected quantitatively via a survey instrument. Independent sample t-test, analysis of variance (ANOVA) and regression analysis were deployed in analyzing the data.

The study found that cross-cultural adjustment varied significantly across the different categories of gender, age, marital status, previous expatriate training, previous expatriate experience, and duration of expatriation. The study concludes that in order to attain higher levels of adjustment African banks and other organizations should provide a more comprehensive cross-cultural training program that mirrors the needs of employees following a detailed needs analysis. Also, the training must be sequential and not a one-off approach.

The literature though still nascent is largely focused on expatriate preparation and adjustment for expatriates moving from Western-to-western contexts and very little exists in the literature on how multinationals from Non-Western contexts like Africa prepare their staff for expatriation and its consequent impact on their adjustment. This study aims to enrich the literature by examining the impact of cross-cultural training on expatriates’ adjustment of Nigerian bankers on expatriate assignments in other African countries.

The dispute resolution process in the construction industry is known for delays in settlement, with some cases even escalating to complex arbitration and litigation. To avoid conflicts turning into disputes, the parties need to be proactive in identifying and resolving conflicts in their nascent stages. It is here that innovative lean construction practices can potentially act as a game-changer to avoid disputes, and this study aims to attempt to understand this phenomenon empirically.

A questionnaire-based empirical study, followed by semi-structured interviews, is conducted to understand the relevance of key tenets of lean principles in dispute avoidance.

Although stakeholders agree on the usefulness and practicality of lean principles in dispute avoidance, the extent of agreement is lesser when it comes to its implementation practicality. Moreover, there is a demographic influence observed on lean tenets such as “open communication”, “stakeholder collaboration” and “constraint identification”.

The results point towards an approach that combines contractual mandate, training and awareness creation to iron out the differences in the usefulness and practicality of lean approaches to avoid disputes.

Lean implementation is widely discussed in many construction contexts, such as sustainability, productivity improvement and planning. However, a discussion on lean philosophy’s role in dispute avoidance is muted. Therefore, this study assumes significance.