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The impact of the loop current (LC) on the motor magnetic field in the analysis of the inter-turn short circuit (ITSC) fault is always ignored. This paper made a comparative study on the electromagnetic field of permanent magnet synchronous motors (PMSM). The purpose of this study is to explore the necessary of the LC existing in the fault analysis and the electromagnetic characteristics of the PMSM with the ITSC fault when taking into account the LC.

Based on the finite element method (FEM), the fault model was established, and the magnetic density of the fault condition was analyzed. The induced electromotive force (EMF) and the LC of the short circuit ring were studied. The three-phase induced EMF and the unbalance of the three-phase current under the fault condition were studied. Finally, a prototype test platform was built to obtain the data of the fault.

The influence of the fault on the magnetic density was obtained. The current phase lag when the ITSC fault occurs causes the magnetic enhancement of the armature reaction. The mechanism that LC hinders the flux change was revealed. The influence of the fault on the three-phase-induced EMF symmetry, the three-phase current balance and the loss was obtained.

The value of the LC in the short circuit ring and the influence of it on the motor electromagnetic field were obtained. On the basis of the electromagnetic field calculation model, the sensitivity of the LC to the magnetic density, induced EMF, current and loss were analyzed.

Taking a 2,000 r/min 10 kW permanent magnet motor as an example, the purpose of this paper is to study the influence of driving modes on the performance of permanent magnet motor at limit conditions, and researched the variation mechanism of motor performance influenced by different driving modes.

A two-dimensional electromagnetic field model of the permanent magnet motor was established, and a rectangular-wave driving circuit was built. By using the finite element method, the electromagnetic field, current, harmonic content and eddy current loss were calculated when the motor operated at rated load and limit load. On the basis of the motor loss calculation, the temperature field of the motor operating at rated condition and limit condition was researched, and the factors that influence motor limit overload capacity were analyzed. By analyzing the motor loss variation at different load conditions, the change mechanism of the motor temperature field was determined further. Combined with the related experiments, the correctness of the above analysis was verified.

Permanent magnet synchronous motor (PMSM) driven by sine wave is better compared with brushless direct current motor (BLDCM) driven by rectangular wave in reducing the magnetic field harmonics, motor losses and optimizing the temperature distribution in the motor. The method driven by sine wave could improve the motor output performance including the motor efficiency and the motor overload capacity. The winding temperature is the most important factor that limits the output capability of PMSM operating for a long time. However, because of the large rotor eddy current losses, the permanent magnet temperature is the most important factor that limits the output capability of BLDCM operating for a long time.

The influence of driving modes on the motor magnetic field, losses and temperature distribution, efficiency and overload capacity was determined, and the influence mechanism was also analyzed. Combined with the analysis of the electromagnetic and temperature fields, the advantages of different driving modes were presented. This study could provide an important basis for the design of permanent magnet motors with different driving modes, and it also provides reference for the application of permanent magnet motor.

This paper presents the influence of driving modes on permanent magnet motors. The limit output capacity of the motor with different driving modes was studied, and the key factors limiting the motor output capability were obtained.

Corporate site visits increase labor investment efficiency.

Our empirical model for the baseline analysis follows those of Jung et al. (2014) and Ghaly et al. (2020).

We show that corporate site visits are associated with significantly higher labor investment efficiency; more specifically, site visits reduce both over-hiring and under-hiring of employees. The effect of site visits on labor investment efficiency is more pronounced for firms with higher labor adjustment costs, greater financial constraints, weaker corporate governance and lower financial reporting quality. We also find that site visits mitigate labor cost stickiness.

First, while the literature has suggested how the presence of institutional investors and analysts may affect labor investment decisions, we focus on institutional investors and analysts’ activities and interactions with firm executives. We provide direct evidence that institutional investors and analysts may use corporate site visits to improve labor investment efficiency. Second, our study adds to a line of recent studies on how corporate site visits reduce information asymmetry and agency conflicts. We show that corporate site visits allow institutional investors and analysts to influence labor investment efficiency. We also provide new evidence that corporate site visits reduce labor cost stickiness.

Despite the proliferation of service chatbots in the tourism industry, the question on its continuance intentions among customers has largely remain unanswered. Building on an integrated framework using the task–technology fit theory (TTF) and the expectation–confirmation model (ECM), the present study aims to settle this debate by investigating the factors triggering customers to continue to use chatbots in a travel planning context.

The research followed a quantitative approach in which a survey of 322 chatbot users was undertaken. The model was empirically validated using the structural equation modelling approach using AMOS.

The results reveal that users’ expectations are confirmed when they believe that the technological characteristics of chatbots satisfy their task-related characteristics. Simply, the results reveal a significant and direct effect of TTF on customers’ confirmation and perceived usefulness towards chatbots. Moreover, perceived usefulness and confirmation were found to positively impact customers’ satisfaction towards chatbots, in which the former exerts a relatively stronger impact. Not surprisingly, customers’ satisfaction with the artificial intelligence(AI)-based chatbots emerged as a predominant predictor of their continuance use.

The findings have various practical ramifications for developers who must train chatbot algorithms on massive data to increase their accuracy and to answer more exhaustive inquiries, thereby generating a task–technology fit. It is recommended that service providers give consumers hassle-free service and precise answers to their inquiries to guarantee their satisfaction.

The present work attempted to empirically construct and evaluate the combination of the TTF model and the ECM, which is unique in the AI-based chatbots available in a tourism context. This research presents an alternate method for understanding the continuance intentions concerning AI-based service chatbots.

Even though the pandemic years resulted in a significant increase in massive open online courses (MOOCs), there are still countries where penetration is low. The rejection of MOOCs can inhibit individual and societal advancements. The purpose of this study is to explore what is behind the resistance to MOOCs in these regions. Using the theoretical framework of innovation resistance theory, it defines the factors that inhibit the adoption of MOOCs.

The research is based on two studies. In the first study, in-depth interviews were used to explore factors that may cause barriers to adoption. Following the results of the first phase, a survey was conducted to investigate resistance to MOOCs, including both users and nonusers of such platforms.

Structural equation modeling revealed the presence of functional and psychological barriers, with the most significant being usage and value-related barriers. The lack of information and the need for interaction were identified as the main factors contributing to these barriers.

The results help increase the acceptance and effective integration of MOOCs into different educational environments, especially in countries with high resistance.

This study aims to explore the key factors influencing the perceived quality of e-learning services in foreign language training at higher education institutions in Morocco.

A qualitative methodology was used, involving semi-structured interviews with various stakeholders, including students, instructors and administrators. The data collected were analyzed using NVivo software to identify themes and patterns related to the perceived quality of e-learning services.

The findings indicate a significant relationship between several factors – such as content relevance, user engagement and technical support – and the perceived quality of e-learning systems. Notably, the implementation of external e-learning platforms has not sufficiently addressed the diverse needs of students, particularly concerning individualized content delivery.

The study emphasizes the necessity for educational institutions to review their content and management strategies to better meet learners’ needs and improve overall satisfaction with e-learning services.

This lack of personalization has implications for student commitment and engagement. This research contributes to the existing literature by focusing on the Moroccan context and highlighting specific challenges and opportunities within e-learning for foreign language education.