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This study employs survey methods to statistically examine the internationalization of quality assurance (IQA) in Taiwanese higher education. The data collected were analyzed to assess the associations between administrators' opinions of the importance of IQA and their evaluations of its implementation, as well as the relationship between implementation and opinions on seven measures of international quality. The study also explores the mediating effect of implementation assessments on the relationship between opinions of the importance of IQA and opinions of international quality.

This study targeted higher education administrators from universities in Taiwan, including presidents, vice presidents, deans, section chiefs, directors, and heads of schools in various departments. Using systematic sampling methods, 80 universities were selected from a population of 159 higher education institutions in Taiwan, with 17-40 potential participants each in 2015. A total of 2,377 questionnaires were distributed to all the administrators of those institutions, and ultimately, 65 institutions and 337 valid questionnaires were analyzed.

The importance of IQA directly and positively influenced implementation of it on higher education institutions. The implementation directly and positively influenced the level of international quality of the institutions and the importance of IQA had an indirect positive influence on international quality through implementation. The aggregated institution-level results were similar to but much stronger than the individual-level results.

This study examined the IQA of higher education in Taiwan, which is increasingly important to institutions' competitiveness in the global higher education market. The data were analyzed using multilevel structural equation modeling at the individual-level and the aggregate-level. The analysis revealed direct and indirect associations between opinions about IQA and institutional quality. This study makes a significant contribution to the literature because it clarifies the role of administrators (individually and collectively) regarding their institutions' educational quality, and it provides useful information that institutions could apply to improve their international competitiveness.

Previous research has focused on the outcomes of telework, investigating the advantages and disadvantages of teleworking for employees. However, these investigations do not examine whether there are differences between teleworkers when evaluating the advantages and disadvantages of teleworking. The aim of this study is to identify of distinct classes of teleworkers based on the advantages and disadvantages that teleworking has for them.

This study used secondary survey data collected by the Spanish National Statistics Institute (INE). A sample of 842 people was used for this study. To identify the distinct classes of teleworkers, their perceived advantages and disadvantages of teleworking were analyzed using latent class analysis.

Three different classes of teleworkers were distinguished. Furthermore, sociodemographic covariates were incorporated into the latent class model, revealing that the composition of the classes varied in terms of education level, household income, and the amount of time spent on teleworking per week. This study also examined the influence of these emergent classes on employees’ experience of teleworking.

This study contributes to previous research investigating if telework is advantageous or disadvantageous for teleworkers, acknowledging that teleworkers are not identical and may respond differently to teleworking.

Drawing on COR theory and based on a person-centered approach, this study aims to explore profiles of both leadership behavior (transformational leadership, abusive supervision) and well-being indicators (cognitive irritation, emotional exhaustion). Additionally, we consider whether certain resource-draining (work intensification) and resource-creating factors (leader autonomy, psychological contract fulfillment) from the leaders' work context are related to profile membership.

The profiles are built using LPA on data from 153 leaders and their 1,077 followers. The relationship between profile membership and correlates from the leaders' work context is examined using multinomial logistic regression analyses.

LPA results in an interpretable four-profile solution with the profiles named (1) Good health – constructive leading, (2) Average health – inconsistent leading, (3) Impaired health – constructive leading and (4) Impaired health – destructive leading. The two groups with the highest sample share – Profiles 1 and 3 – both show highly constructive leadership behavior but differ significantly in their well-being indicators. The regression analyses show that work intensification and psychological contract fulfillment are significantly related to profile membership.

The person-centered approach provides a more nuanced view of the leadership behavior – leader well-being relationship, which can address inconsistencies in previous research. In terms of practical relevance, the person-centered approach allows for the identification of risk groups among leaders for whom organizations can provide additional resources and health-promoting interventions.

Background: This article presents a methodology to categorize scientific publications according to the targets of the 17 Sustainable Development Goals (SDGs) of the United Nations. For the above, a dataset with bibliographic and descriptive attributes of 2,379 articles from 2017 by co-authors affiliated to the Pontificia Universidad Católica de Chile, indexed in the Web of Science and Scopus databases, was used.

Methods: The methodology considered three relevant and consecutive milestones: establishment of the reading level that was applied for each publication record, which considers a proportional amount of information; assignment of one of the 18 categories identified for the analysis of the information, which include the 17 SDGs and the option “unclassified” and one of the 169 subcategories corresponding to the specific goals; and, finally, recording the status of the review process carried out, which allowed control of the progress and quality of the cross-review.

Results: The results show that 58.6% of the articles contribute to a primary target, of these 233 contribute to a secondary target; goals 3, 4, 9, and 11 are the most frequent in the process of assigning SDGs. There is an 81% increase in the use of alphanumeric targets when they are assigned as secondary targets. At the same time, cross-checking is shown to be beneficial when allowing the reclassification of 190 articles to some of the targets. Finally, it is established that levels 2 and 3 enabled better classification, given that the contents considered provide more information; however, it is significant that through level 1, 355 articles were categorized as “unclassified”.

Conclusions: It is concluded that the methodology allows for a conclusive, exhaustive, rigorous, extensive, and varied classification through the different milestones and actions carried out, providing strategic information for decision making and research management in the academy-society relationship.

In order to estimate the value of semi-automated subject indexing in operative library catalogues, the study aimed to investigate five different automated implementations of an open source software package on a large set of Swedish union catalogue metadata records, with Dewey Decimal Classification (DDC) as the target classification system. It also aimed to contribute to the body of research on aboutness and related challenges in automated subject indexing and evaluation.

On a sample of over 230,000 records with close to 12,000 distinct DDC classes, an open source tool Annif, developed by the National Library of Finland, was applied in the following implementations: lexical algorithm, support vector classifier, fastText, Omikuji Bonsai and an ensemble approach combing the former four. A qualitative study involving two senior catalogue librarians and three students of library and information studies was also conducted to investigate the value and inter-rater agreement of automatically assigned classes, on a sample of 60 records.

The best results were achieved using the ensemble approach that achieved 66.82% accuracy on the three-digit DDC classification task. The qualitative study confirmed earlier studies reporting low inter-rater agreement but also pointed to the potential value of automatically assigned classes as additional access points in information retrieval.

The paper presents an extensive study of automated classification in an operative library catalogue, accompanied by a qualitative study of automated classes. It demonstrates the value of applying semi-automated indexing in operative information retrieval systems.

This study aims to provide insight into the determinants of wellness tourism satisfaction, thereby taking a nonlinear approach regarding the relationships between attribute-level performance of wellness facility attributes, on the one hand, and wellness destination attributes, on the other hand, and global wellness tourist satisfaction. In addition, scores of impact range are calculated to reveal the potentially most determinant wellness facility and destination attributes.

This study uses data from a survey-based study conducted among 1,331 wellness tourists who have engaged in wellness tourism activities at one of 28 hotels with wellness offerings and 10 spas in Croatia. Impact-asymmetry analysis and impact-range analysis are used to quantify the potential of individual wellness attributes to generate satisfaction and dissatisfaction among wellness tourists and to perform a classification of wellness attributes according to the three-factor theory of customer satisfaction.

Operators of wellness tourism facilities, as well as managers of wellness destinations, must not make any compromises in quality levels because most wellness attributes have significantly higher potential to frustrate than please tourists. Basic factors such as cleanliness, punctuality or safety turned out to have the strongest influence on global satisfaction levels. Moreover, in line with previous research, wellness tourists have large expectations from destinations to have a preserved and beautiful nature, which is by far the most influential destination attribute. In addition to a safe environment and high-quality accommodation, wellness tourists further prefer rich cultural offerings.

To the best of the authors' knowledge, this is the first study to apply a nonlinear analysis approach to the quality–satisfaction relationship in a wellness tourism setting. Moreover, to the knowledge of the authors, this is the only study that used separate attribute models for wellness facilities, on the one hand, and wellness destinations, on the other hand, based on a nation-wide sample that covers multiple cases (i.e. multiple facilities and destinations).

本研究旨在深入了解养生旅游满意度的决定因素, 从而采用非线性方法来研究（i）养生设施属性和 （ii）养生目的地属性对国际养生游客满意度的关系。此外, 本文还计算了影响范围的分数, 以揭示潜在的最具决定性的养生设施和目的地属性。

本研究使用了基于对 1,331 名养生游客进行调查问卷的数据, 这些游客曾在克罗地亚 28 的酒店以及10个水疗中心进行了养生旅游活动。本文采用影响不对称分析（IAA）和影响范围分析（IRA）来量化个体养生属性在健康游客中产生满意度和不满意的潜力, 并根据顾客三因素满意度理论对健康属性进行分类。

养生旅游设施的运营商以及养生目的地的管理者不能在质量水平上做出任何妥协, 因为大多数养生属性很可能使游客感到沮丧, 而不是取悦游客。事实证明, 清洁、准时及安全等基本因素对全球满意度影响最大。此外, 根据之前的研究, 健康游客对目的地抱有很大的期望, 希望拥有保存完好且美丽的自然风光, 这是最具影响力的目的地属性。除了安全的环境和高品质的住宿外, 养生游客更看重丰富的文化产品。

这是第一项将非线性分析方法应用于养生旅游环境中的质量与满意度关系的研究。此外, 据作者所知, 这是唯一一项基于涵盖多个案例（即多个设施及目的地）的国家样本, 一方面对养生设施使用单独的属性模型, 另一方面对养生目的地使用单独的属性模型的研究。

Este estudio tiene como objetivo proporcionar información sobre los determinantes de la satisfacción del turismo de bienestar, adoptando así un enfoque no lineal con respecto a las relaciones entre el rendimiento a nivel de atributos de (i) atributos de instalaciones de bienestar, por un lado, y (ii) atributos de destino de bienestar, por otro lado, y la satisfacción del turista de bienestar global. Además, se calculan puntajes de rango de impacto para revelar las instalaciones de bienestar y los atributos de destino potencialmente más determinantes.

este estudio utiliza datos de un estudio basado en encuestas realizado entre 1,331 turistas de bienestar que participaron en actividades de turismo de bienestar en uno de los 28 hoteles con ofertas de bienestar y diez spas en Croacia. El análisis de asimetría de impacto (IAA) y el análisis de rango de impacto (IRA) se utilizan para cuantificar el potencial de los atributos de bienestar individuales para generar satisfacción e insatisfacción entre los turistas de bienestar y para realizar una clasificación de los atributos de bienestar de acuerdo con la teoría de los tres factores del cliente. satisfacción.

Los operadores de instalaciones de turismo de bienestar, así como los administradores de destinos de bienestar, no deben comprometer los niveles de calidad porque la mayoría de los atributos de bienestar tienen un potencial significativamente mayor para frustrar que para complacer a los turistas. Los factores básicos, como la limpieza, la puntualidad o la seguridad, resultaron ser los que más influyeron en los niveles de satisfacción global. En consecuencia, estos atributos no deben verse como fuentes potenciales de satisfacción y deleite del cliente, sino que deben otorgarse altos niveles de desempeño para evitar una fuerte insatisfacción. Además, en línea con investigaciones anteriores, los turistas de bienestar tienen grandes expectativas de que los destinos tengan una naturaleza preservada y hermosa, que es, con mucho, el atributo de destino más influyente. Además de un entorno seguro y un alojamiento de alta calidad, los turistas de bienestar prefieren una rica oferta cultural. Aplicando la teoría de los tres factores, una visión más matizada de la formación de la satisfacción del turista de bienestar mostró que estos atributos del destino tienen un potencial mucho mayor para crear una fuerte insatisfacción que satisfacción.

Este es el primer estudio que aplica un enfoque de análisis no lineal a la relación calidad-satisfacción en un entorno de turismo de bienestar. Además, según el conocimiento de los autores, este es el único estudio que utilizó modelos de atributos separados para instalaciones de bienestar, por un lado, y destinos de bienestar, por el otro, en base a una muestra nacional que cubre múltiples casos (es decir, múltiples instalaciones y destinos).

Surface roughness has a serious impact on the fatigue strength, wear resistance and life of mechanical products. Realizing the evolution of surface quality through theoretical modeling takes a lot of effort. To predict the surface roughness of milling processing, this paper aims to construct a neural network based on deep learning and data augmentation.

This study proposes a method consisting of three steps. Firstly, the machine tool multisource data acquisition platform is established, which combines sensor monitoring with machine tool communication to collect processing signals. Secondly, the feature parameters are extracted to reduce the interference and improve the model generalization ability. Thirdly, for different expectations, the parameters of the deep belief network (DBN) model are optimized by the tent-SSA algorithm to achieve more accurate roughness classification and regression prediction.

The adaptive synthetic sampling (ADASYN) algorithm can improve the classification prediction accuracy of DBN from 80.67% to 94.23%. After the DBN parameters were optimized by Tent-SSA, the roughness prediction accuracy was significantly improved. For the classification model, the prediction accuracy is improved by 5.77% based on ADASYN optimization. For regression models, different objective functions can be set according to production requirements, such as root-mean-square error (RMSE) or MaxAE, and the error is reduced by more than 40% compared to the original model.

A roughness prediction model based on multiple monitoring signals is proposed, which reduces the dependence on the acquisition of environmental variables and enhances the model's applicability. Furthermore, with the ADASYN algorithm, the Tent-SSA intelligent optimization algorithm is introduced to optimize the hyperparameters of the DBN model and improve the optimization performance.

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

Spam emails classification using data mining and machine learning approaches has enticed the researchers' attention duo to its obvious positive impact in protecting internet users. Several features can be used for creating data mining and machine learning based spam classification models. Yet, spammers know that the longer they will use the same set of features for tricking email users the more probably the anti-spam parties might develop tools for combating this kind of annoying email messages. Spammers, so, adapt by continuously reforming the group of features utilized for composing spam emails. For that reason, even though traditional classification methods possess sound classification results, they were ineffective for lifelong classification of spam emails duo to the fact that they might be prone to the so-called “Concept Drift”. In the current study, an enhanced model is proposed for ensuring lifelong spam classification model. For the evaluation purposes, the overall performance of the suggested model is contrasted against various other stream mining classification techniques. The results proved the success of the suggested model as a lifelong spam emails classification method.

This study investigates whether there are relationships between the characteristics of the boards of trustees of universities in the Arab region, higher education quality assurance and the output of scientific research.

The descriptive analytical approach was used in this study. The study was conducted on the universities of the Arab region that are included in the classification of the British Institution for the Arab Region: QS Arab Region University.

The findings show that there is an effect of the characteristics of the trustees combined in the universities of the Arab region on ensuring the quality of higher education, other than the output of scientific research. The findings also indicate when measuring the characteristics individually that the trustee system is not effective in the Arab region and it is only formal for nominal purposes.

Most universities in the Arab region do not disclose the data of boards of trustees, their roles, committees, rules of procedure and the nature of their work. A large number of universities also do not operate under the trustee system because the regulations and instructions do not allow this in the country.

This study seeks to improve practitioners knowledge, including boards of trustees, in ensuring the quality of higher education and the output of scientific research.

The research projected the governance model through the characteristics of the boards of directors of for-profit companies on the boards of trustees of universities in the Arab region. The study examines the nature of the characteristics of the boards of trustees that are compatible with its responsibilities, the most important of which is the supervision of the strategy to ensure the quality of higher education research.