Search results

Grounding on the goal-setting theory and flow theory, this study explored the mechanism underlying the association between transfer design (TD); identical elements and training transfer (TT). Specifically, the authors explored a moderated mediation process of trainer performance and motivation to improve work through learning (MTIWL) that has received less consideration in the TT literature.

Data were collected using the retro-perspective survey method. The first survey was administered offline (t1: the day when leadership intervention was completed. Subsequently, trainees were requested to participate in an online survey (t2: 12–14 weeks later). In all, 355 executives participated.

The results of structural equation modeling (SEM) analyses suggested that trainees’ MTIWL mediational impact between leadership intervention triggers (transfer design and identical elements), and TT was supported. In addition, the indirect impact of these variables on TT was found to be significant when the trainer had high performance than when it was low. This confirmed the trainer’s performance as a potential moderator in the TT process.

This study is limited to the exploration of leadership intervention variables on TT. The findings have implications for leadership professionals and scholars who use leadership intervention and motivation metrics to predict TT.

This study offers a moderated mediation mechanism for enhancing TT through leadership intervention triggers. The proposed conceptual model included MTIWL as mediator and trainer performance during leadership intervention as moderator.

Research has established that 38%, 56% and 66% of training is not transferred to work immediately, six months and 12 months after training, respectively. This has led scholars to advocate the continuous examination of factors that enhance training transfer to have a comprehensive understanding of the factors that enhance it. As a result, this study aims to examine transfer opportunity as a pretraining factor and its influence on assimilated training content (in-training factor); the influence of assimilated training content on motivation to transfer (post-training factor) and training transfer; the influence of motivation to transfer on training transfer; and the mediating role of motivation to transfer in the relationship between assimilated training content and training transfer.

A structural equation model is developed to test the five hypotheses formulated in this study using survey data obtained from 195 respondents who attended various training programs across different organizations. Following the assessment of the measurement model, the determination of the significance of the hypothesized paths is assessed based on the bias-corrected and accelerated confidence intervals obtained from the bootstrapping of 10,000 subsamples.

The findings of this study are that: transfer opportunity positively influences assimilated training content; assimilated training content positively influences motivation to transfer and training transfer; motivation to transfer positively influences training transfer; and motivation to transfer plays a complementary mediation role between assimilated training content and training transfer.

The nature of the work environment regarding the opportunity to transfer training influences trainees’ assimilation of the training content when they undergo training. Hence, organizations need to ensure that employees are always afforded the opportunity to transfer training content assimilated from previously attended training programs to assimilate the content of subsequent training programs. Furthermore, for training to culminate in training transfer, organizations and, more specifically, learning and development practitioners ought to pay attention to trainees’ assimilation of the content of training programs.

To the best of the authors’ knowledge, this is the first study to empirically consider transfer opportunity as a direct antecedent of assimilated training content. More so, it is one of few studies to empirically examine the influence of assimilated training content on training transfer.

This study aims to investigate a new circuitous minichannel cold plate (MCP) design involving flow fragmentation. The overall thermal performance and the temperature uniformity analysis are performed and compared with the traditional serpentine design. The substrate thickness and its thermal conductivity are varied to analyse the effect of axial-back conduction due to the conjugate nature of heat transfer.

The traditional serpentine minichannel is modified into five new fragmented designs with two inlets and two outlets. A three-dimensional numerical model involving the effect of conjugate heat transfer with a single-phase laminar fluid flow subjected to constant heat flux is solved using a finite volume-based computational fluid dynamics solver.

The minimum and maximum temperature differences are observed for the two branch fragmented flow designs. The two-branch and middle channel fragmented design shows better temperature uniformity over other designs while the three-branch fragmented designs exhibited better hydrodynamic performance.

MCPs could be used as an indirect liquid cooling method for battery thermal management of pouch and prismatic cells. Coupling the modified cold plates with a battery module and investigating the effect of different battery parameters and environmental effects in a transient state are the prospects for further research.

The study involves several aspects of evaluation for a conclusive decision on optimum channel design by analysing the performance plot between the temperature uniformity index, average base temperature and overall thermal performance. The new fragmented channels are designed in a way to facilitate the fluid towards the outlet in the minimum possible path thereby reducing the pressure drop, also maximizing the heat transfer and temperature uniformity from the substrate due to two inlets and a reversed-flow pattern. Simplified minichannel designs are proposed in this study for practical deployment and ease of manufacturability.

Light emitting diode (LED) has been the best resource for commercial and industrial lighting applications. However, thermal management in high power LEDs is a major challenge in which the thermal resistance (R_th) and rise in junction temperature (T_J) are critical parameters. The purpose of this work is to evaluate the R_th and T_j of the LED attached with the modified heat transfer area of the heatsink to improve thermal management.

This paper deals with the design of metal substrate for heatsink applications where the surface area of the heatsink is modified. Numerical simulation on heat distribution proved the influence of the design aspects and surface area of heatsink.

T_J was low for outward step design when compared to flat heatsink design (ΔT ∼ 38°C) because of increase in surface area from 1,550 mm² (flat) to 3,076 mm² (outward step). On comparison with inward step geometry, the T_J value was low for outward step configuration (ΔT_J ∼ 6.6°C), which is because of efficient heat transfer mechanism with outward step design. The observed results showed that outward step design performs well for LED testing by reducing both R_th and T_J for different driving currents.

This work is authors’ own design and also has the originality for the targeted application. To the best of the authors’ knowledge, the proposed design has not been tried before in the electronic or LED applications.

Knowledge transfer which refers to the communication of knowledge from a source so that it is learned and applied by a recipient has long been a challenge for knowledge management. The purpose of this study is to understand influencing factors of transactive memory system (TMS) and knowledge transfer.

Drawing on the theories of communication visibility, social distance and flow, this study develops a research model. Then, data are collected from users of the social media mobile App. Partial least squares-structural equation modeling (PLS-SEM) is employed to analyze data.

TMS is a valid second-order construct in the social media mobile app context, which is more reflected by credibility. Meanwhile, communication visibility and social distance each have positive effects on TMS which further has a positive effect on knowledge transfer. Flow has a positive effect on knowledge transfer.

Developers of the mobile App should carefully consider the role of information and communication technology (ICT) in supporting TMS and knowledge transfer. They should consider recommendation algorithm so that the benefit of communication visibility can be retained. They should design the feature to classify users based on similarity so as to stimulate users' feeling of close social distance. They should keep on improving features based on users' holistic experience.

This study incorporates the perspectives of communication visibility, social distance and flow to understand TMS and knowledge transfer, presenting a new lens for research.

This study aims to examine the impact of knowledge and skills acquisition from youth leadership programs on the extent of training transfer. Additionally, it explores the role of self-esteem as a potential intervening mechanism in linking the acquired knowledge and skills to the transfer of training.

Using a non-probability purposive sampling, data were gathered from participants of youth leadership programs in Brunei. The study hypotheses were validated using multiple linear regression analysis and Hayes PROCESS macro.

The findings revealed that knowledge and skills acquisition positively affect the extent of training transfer among youth leadership program participants. Moreover, self-esteem is found to be a crucial mediator in the relationship between knowledge and skills acquired from youth leadership programs and the extent of training transfer.

The study suggests that to optimize the transfer of training in the youth leadership programs, relevant stakeholders – training providers, and practitioners – must prioritize not only the knowledge and skills acquisition but also the cultivation of participants’ self-esteem. To achieve this, a primary focus should be placed on the criticality of designing such programs to address these factors. Policymakers, particularly in Brunei, can enhance the leadership pipeline among the youth population and expedite progress toward achieving the national vision by aligning leadership development initiatives with the broader national development agenda.

Collectively, this study enhances understanding of training transfer in youth leadership development, an often-overlooked area in the literature.

The purpose of this research is to achieve multi-task autonomous driving by adjusting the network architecture of the model. Meanwhile, after achieving multi-task autonomous driving, the authors found that the trained neural network model performs poorly in untrained scenarios. Therefore, the authors proposed to improve the transfer efficiency of the model for new scenarios through transfer learning.

First, the authors achieved multi-task autonomous driving by training a model combining convolutional neural network and different structured long short-term memory (LSTM) layers. Second, the authors achieved fast transfer of neural network models in new scenarios by cross-model transfer learning. Finally, the authors combined data collection and data labeling to improve the efficiency of deep learning. Furthermore, the authors verified that the model has good robustness through light and shadow test.

This research achieved road tracking, real-time acceleration–deceleration, obstacle avoidance and left/right sign recognition. The model proposed by the authors (UniBiCLSTM) outperforms the existing models tested with model cars in terms of autonomous driving performance. Furthermore, the CMTL-UniBiCL-RL model trained by the authors through cross-model transfer learning improves the efficiency of model adaptation to new scenarios. Meanwhile, this research proposed an automatic data annotation method, which can save 1/4 of the time for deep learning.

This research provided novel solutions in the achievement of multi-task autonomous driving and neural network model scenario for transfer learning. The experiment was achieved on a single camera with an embedded chip and a scale model car, which is expected to simplify the hardware for autonomous driving.

The purpose of this study is to investigate the influence of enclosure shape on magnetohydrodynamic (MHD) nanofluidic flow, heat transfer and irreversibility in square, trapezoidal and triangular thermal systems under fluid volume constraints, with the aim of optimizing thermal behavior in diverse applications.

The study uses numerical simulations based on a finite element-based technique to analyze the effects of the Rayleigh number (Ra), Hartmann number (Ha), magnetic field orientation (γ) and nanoparticle concentration (ζ) on heat transfer characteristics and thermodynamic entropy production.

The key findings reveal that the geometrical design significantly influences fluid velocity, heat transfer and irreversibility. Trapezoidal thermal systems outperform square systems, while triangular systems achieve optimal enhancement. Nanoparticle concentration enhances heat transfer and flow strength at higher Rayleigh numbers. The magnetic field intensity has a significant impact on fluid flow and heat transport in natural convection, with higher Hartmann numbers resulting in reduced flow strength and heat transfer. The study also highlights the influence of various parameters on thermodynamic entropy production.

Further research can explore additional geometries, parameters and boundary conditions to expand the understanding of enclosure shape effects on MHD nanofluidic flow and heat transfer. Experimental validation can complement the numerical simulations presented in this study.

This study provides valuable insights into the impact of enclosure shape on heat transfer performance in MHD nanofluid flow systems. The findings contribute to the optimization of thermal behavior in applications such as electronics cooling and energy systems. The comparison of different enclosure shapes and the analysis of thermodynamic entropy production add novelty to the study.

The purpose of this study is to carry out a comprehensive analysis of magneto-hydrodynamics (MHD), nanofluidic flow dynamics and heat transfer as well as thermodynamic irreversibility, within a novel butterfly-shaped cavity. Gaining a thorough understanding of these phenomena will help to facilitate the design and optimization of thermal systems with complex geometries under magnetic fields in diverse applications.

To achieve the objective, the finite element method is used to solve the governing equations of the problem. The effects of various controlling parameters such as butterfly-shaped triangle vertex angle (T), Rayleigh number (Ra), Hartmann number (Ha) and magnetic field inclination angle (γ ) on the hydrothermal performance are analyzed meticulously. By investigating the effects of these parameters, the authors contribute to the existing knowledge by shedding light on their influence on heat and fluid transport within butterfly-shaped cavities.

The major findings of this study reveal that the geometrical shape significantly alters fluid motion, heat transfer and irreversibility production. Maximum heat transfer, as well as entropy generation, occurs when the Rayleigh number reaches its maximum, the Hartmann number is minimized and the angle of the magnetic field is set to 30° or 150°, while the butterfly wings angle or vertex angle is kept at a maximum of 120°. The intensity of the magnetic field significantly controls the heat flow dynamics, with higher magnetic field strength causing a reduction in the flow strength as well as heat transfer. This configuration optimizes the heat transfer characteristics in the system.

Further research can be expanded on this study by examining thermal performance under different curvature effects, orientations, boundary conditions and additional factors. This can be accomplished through numerical simulations or experimental investigations under various multiphysical scenarios.

The geometric configurations explored in this research have practical applications in various engineering fields, including heat exchangers, crystallization processes, microelectronic devices, energy storage systems, mixing processes, food processing, air-conditioning, filtration and more.

This study brings value by exploring a novel geometric configuration comprising the nanofluidic flow, and MHD effect, providing insights and potential innovations in the field of thermal fluid dynamics. The findings contribute a lot toward maximizing thermal performance in diverse fields of applications. The comparison of different hydrothermal behavior and thermodynamic entropy production under the varying geometric configuration adds novelty to this study.

The purpose of the study was to examine the factors that are important for strengthening university–industry collaboration (UIC). This study also investigates the outcome of UIC in the light of creativity, skill, knowledge, and research work.

A survey method has been used to collect data for the study. This study applied a purposive judgmental sampling technique where particular types of respondents like university faculty members and the top officials of the organizations were selected who are knowledgeable and can provide the desired information. The current study used the structural equation modeling method to analyze the data. In the first stage, this research assessed the demographic factors of the respondent. Then this study conducts confirmatory factors analysis and convergent and discriminant validity and reliability test. Finally, the hypotheses are tested by using nonparametric.

This study finds that knowledge transfer mechanism, governmental factors, organizational design factors, technology transfer and the collaborative network has a significant impact on strengthening UIC, which ultimately facilitates creativity, knowledge creation, skills development and supply of graduate according to the requirement of the industry, good research work.

The current study identified some important determinant that has a substantial influence on strengthening UIC. According to the study organizational design, government, technology, collaborative network and mechanism for knowledge transfer play very crucial roles in strengthening collaboration that ultimately increases the creativity, skills, knowledge and research capability of graduates.