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This paper aims to probe into the implementation of internship courses under the five-year cosmetology program in Taiwan from the perspective of Dewey's philosophies in hopes that the analysis can serve as reference for schools in planning their internship courses in the future.

This paper probes into the off-campus internship courses under Taiwan's five-year junior college education program by applying Dewey's empirical philosophy.

The study aims to understand the learning experience acquired by students from learning by doing internship courses as reference for future internship design. The current internship courses comprise the follows: summer, during the semester and for a full academic year. The experience of summer internship is career exploration, the experience for semester internship is career experience and the experience from academic-year internship is career choice. The internship strategies are designed according to the three different internship approaches, so that the internship courses can implement the educational effect of “learning from experience”.

To minimize the discrepancy between the cosmetology program under the five-year junior college education and the employment market, credit-based off-campus internship courses are arranged for students' final years at school.

Through on-site trainings, students accumulate work experience and explore into a related career field. The accumulation of experience and gaining of insights mirror the philosophy of learning by doing, which involves students' reflective thinking.

It is hoped that the analysis can serve as reference for internship courses planning in the future.

This paper aims that mobile health (mHealth) applications have emerged as a key tool to support public health. However, there are only a few studies examining the influences of health-related ascribes on continuance intention to use mHealth apps and how these influences are contingent on gender in the mHealth app using context.

This study takes the protection motivation theory as a theoretical framework to examine the ordered relationship between threat and coping appraisals and their impacts on continuance intention to use mHealth apps. In addition, this study further extends the literature on gender differences into the mHealth app's context to investigate the moderating role of gender. The suggested hypotheses are confirmed by a structural equation modeling approach and multigroup investigation employing survey data of 345 users of Spring Rain Doctor in China, a typical mHealth app.

The findings suggest that the impact of perceived disease threat on user's continuance intention is mediated entirely by coping appraisals. Furthermore, the three coping appraisals' impacts are contingent upon gender. Specifically, response efficacy is more crucial for male users in forecasting continuance intention, whereas self-efficacy and response cost have a more salient influence on continuance intention for female users.

This study examines the ordered influences of threat and coping appraisal, moderated by gender, on continuance intention on use mHealth apps. These findings could contribute to relevant theoretical and practical implications.

This paper aims to investigate the correlation between banking sector non-performing loans (NPLs) and the level of sustainable development.

Pearson correlation test statistic was used to assess the correlation between bank NPLs and sustainable development.

There is a significant positive correlation between banking sector NPLs and the level of sustainable development measured by the sustainable development index (SDI). The significant positive correlation is evident in European countries and in countries in the region of the Americas. There is a significant negative correlation between banking sector NPLs and achieving SDG3 and SDG7 in African countries and European countries. There is also a significant negative correlation between NPLs and achieving SDG10 in European countries. There is a significant positive correlation between banking sector NPLs and achieving SDG4 and SDG7 in the region of the Americas. There is also a significant positive correlation between NPLs and achieving SDG10 in African countries and in countries in the region of the Americas.

The present study is unique and different from other studies because it used a unique SDI to capture the level of sustainable development. The analysis is also unique because it covers several regions, which have not been covered in previous studies.

The scalability of similarity joins is threatened by the unexpected data characteristic of data skewness. This is a pervasive problem in scientific data. Due to skewness, the uneven distribution of attributes occurs, and it can cause a severe load imbalance problem. When database join operations are applied to these datasets, skewness occurs exponentially. All the algorithms developed to date for the implementation of database joins are highly skew sensitive. This paper presents a new approach for handling data-skewness in a character- based string similarity join using the MapReduce framework. In the literature, no such work exists to handle data skewness in character-based string similarity join, although work for set based string similarity joins exists. Proposed work has been divided into three stages, and every stage is further divided into mapper and reducer phases, which are dedicated to a specific task. The first stage is dedicated to finding the length of strings from a dataset. For valid candidate pair generation, MR-Pass Join framework has been suggested in the second stage. MRFA concepts are incorporated for string similarity join, which is named as “MRFA-SSJ” (MapReduce Frequency Adaptive – String Similarity Join) in the third stage which is further divided into four MapReduce phases. Hence, MRFA-SSJ has been proposed to handle skewness in the string similarity join. The experiments have been implemented on three different datasets namely: DBLP, Query log and a real dataset of IP addresses & Cookies by deploying Hadoop framework. The proposed algorithm has been compared with three known algorithms and it has been noticed that all these algorithms fail when data is highly skewed, whereas our proposed method handles highly skewed data without any problem. A set-up of the 15-node cluster has been used in this experiment, and we are following the Zipf distribution law for the analysis of skewness factor. Also, a comparison among existing and proposed techniques has been shown. Existing techniques survived till Zipf factor 0.5 whereas the proposed algorithm survives up to Zipf factor 1. Hence the proposed algorithm is skew insensitive and ensures scalability with a reasonable query processing time for string similarity database join. It also ensures the even distribution of attributes.

Tourism on wellness is a rapidly expanding segment of the travel industry; nevertheless, it is still in its infancy, and more study research is needed to develop a scientific foundation for health and wellness tourism. The study uses bibliometric indicators like as citations to determine the field structure on wellness tourism from 1998 to 2021, and the VOSviewer software to map the significant trends in wellness tourism (WT) area, to examine the present situation.

To reach this objective, the theme of “wellness tourism” was searched in the “Scopus” database, and bibliometrics data on the publications were obtained. In total, 414 papers were found during the initial search, which was then narrowed according to the criteria. Using this strategy, the author discovered 386 records, and after removing 4 duplicates and 1 irrelevant document, the refining produced 381 related documents. The most-cited papers, significant authors, co-citation of references, sources and authors were all investigated for the publications related to WT.

According to this report, research into wellness tourism has increased in recent years. The authors discovered two papers with over 238 “Scopus” citations and a total of 10 studies with 1414 citations. According to Scopus, the document Napier et al. receives 36.5% of citations each year. There were a total of 804 authors who published about WT between 1998 and 2021, with Smith, M, Voigt, c, and Puczkó, L being the most-cited reference authors in the subject. Han h. has the highest index of 56 of all the authors.

The “Scopus” database was used for bibliometric analysis, although the VOSviewer was used exclusively. This considered as a first study to utilize a bibliometric method to address this research gap, identifying the tools, journals, and, most crucially, conceptual subdomains like spa, yoga, therapy, spirituality and trekking that will be significant in future research.

Using a bibliometric analytic approach, this article looked at papers on wellness tourism published between 1998 and 2021. Thus, its goal is to learn more about wellness tourism and to enlighten wellness tourism scholars on the field's structure.

The ecological environment of the Loess Plateau, China, is extremely fragile under the context of global warming. Over the past two decades, the vegetation of the Loess Plateau has undergone great changes. This paper aims to clarify the response mechanisms of vegetation to climate change, to provide support for the restoration and environmental treatment of vegetation on the Loess Plateau.

The Savitsky–Golay (S-G) filtering algorithm was used to reconstruct time series of moderate resolution imaging spectroradiometer (MODIS) 13A2 data. Combined with trend analysis and partial correlation analysis, the influence of climate change on the phenology and enhanced vegetation index (EVI) during the growing season was described.

The S-G filtering algorithm is suitable for EVI reconstruction of the Loess Plateau. The date of start of growing season was found to gradually later along the Southeast–Northwest direction, whereas the date of the end of the growing season showed the opposite pattern and the length of the growing season gradually shortened. Vegetation EVI values decreased gradually from Southeast to Northwest. Vegetation changed significantly and showed clear differentiation according to different topographic factors. Vegetation correlated positively with precipitation from April to July and with temperature from August to November.

This study provides technical support for ecological environmental assessment, restoration of regional vegetation coverage and environmental governance of the Loess Plateau over the past two decades. It also provides theoretical support for the prediction model of vegetation phenology changes based on remote sensing data.

Collaboration is a common phenomenon in human society. The best way of collaborations can make the group achieve the best interests. Because of the low cost and high repeatability of simulation, it is a good method to explore the best way of collaborations by means of simulation. The traditional simulation is difficult to adapt to the crowd intelligence network simulation, so the crowd collaborations simulation is proposed.

In this paper, the atomic swarm intelligence unit and collective swarm intelligence unit are proposed to represent the behavior of individuals and groups in physical space and the interaction between them.

To explore the best collaboration mode of the group, a framework of crowd collaborations simulation is proposed, which decomposes the big goal into the small goals by constructing the cooperation chain and analyzes the cooperation results and feeds them back to the next simulation.

Two kinds of swarm intelligence units are used to represent the simulated individuals in the group, and the pattern is used to represent individual behavior. It is suitable for the simulation of collaboration problems in various types and situations.

The COVID-19 pandemic, which appeared in China in late 2019, has affected the world psychologically, socially and economically in 2020. Tourism is one of the areas where the effects of COVID-19 have been felt most clearly. The study aims to determine the effect of negative problem orientation (NPO) and perceived risk related to the COVID-19 pandemic on travel and destination visit intention.

This study employed a convenience and probabilistic sampling method for collecting data from 531 respondents using an online questionnaire. Partial least square structural equation modeling (PLS-SEM) was used for testing research model.

According to the findings, NPO and perceived risk related to the pandemic were found to have direct and indirect effects on the travel behavior of tourists. The results of this research provide theoretical and practical implications for hospitality and travel businesses on topics such as the psychological effects of the pandemic and the travel behaviors of tourists.

It is estimated that the pandemic will also affect tourist behavior due to its effects on human psychology. For this reason, a study conducted in the context of tourist behavior theories is expected to contribute to the literature, managers and future of the tourism.

This study intend to investigate a theoretical model looking at how particular tourist emotions, such as “joy,” “love,” and “positive surprise,” might predict their behavior by looking at how satisfied they are with their whole experience when visiting spas, and to examine the relationship of emotional experience, destination image, satisfaction and intention to revisit for spa tourism.

A sample of 345 individuals who traveled to Alleppey as domestic tourists participated in the research study. A non-probability (purposive) sampling method in this study. The structural model was analyzed using Structural Equation modeling (SEM), and the path coefficients were examined to test the hypotheses.

The results supported the hypotheses, indicating that specific emotions, image of the destination, and satisfaction significantly impacted tourists' intentions to revisit Alleppey as a spa tourism destination. This study demonstrated that “emotions of joy, love, and positive surprise” have a considerable influence on the image of the destination and satisfaction. The findings reveal a substantial correlation between satisfaction and behavioral intention (“Intention to revisit”). The research suggests that a higher degree of satisfaction would encourage visitors to revisit the location.

The research suggests that a higher degree of satisfaction would encourage visitors to revisit the location. This research offers vital information for developing, planning, and putting into practice tourism policies in the spa tourism sector. This article focuses on domestic travelers who travel to Alleppey, so the conclusions may not be relevant to research utilizing foreign tourists.

According to the literature study, and to the authors` knowledge, only limited number of studies that look at spa tourism from a wellness perspective. Additionally, Alleppey is used in the study as the study’s setting, providing insight into the visitor experiences of this expanding spa tourism business. This study gives understanding about how emotional experience predicts behavioral intentions.

Small highly saturated interior permanent magnet- synchronous machines (IPMSMs) show a very nonlinear behaviour. Such machines are mostly controlled with a closed-loop cascade control, which is based on a d-q two-axis dynamic model with constant concentrated parameters to calculate the control parameters. This paper aims to present the identification of a complete current- and rotor position-dependent d-q dynamic model, which is derived by using a finite element method (FEM) simulation. The machine’s constant parameters are determined for an operation on the maximum torque per ampere (MTPA) curve. The obtained MTPA control performance was evaluated on the complete FEM-based nonlinear d-q model.

A FEM model was used to determine the nonlinear properties of the complete d-q dynamic model of the IPMSM. Furthermore, a fitting procedure based on the nonlinear MTPA curve is proposed to determine adequate constant parameters for MTPA operation of the IPMSM.

The current-dependent d-q dynamic model of the machine models the relevant dynamic behaviour of the complete current- and rotor position-dependent FEM-based d-q dynamic model. The most adequate control response was achieved while using the constant parameters fitted to the nonlinear MTPA curve by using the proposed method.

The effect on the motor’s steady-state and dynamic behaviour of differently complex d-q dynamic models was evaluated. A workflow to obtain constant set of parameters for the decoupled operation in the MTPA region was developed and their effect on the control response was analysed.