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Under the new policy framework, the China Government will substantially increase education resources investment. As a result, financial under‐provision of schools will not be the main problem in the near future. However, school efficiency will emerge as the new factor in attracting the attention of the government and the public in China, which is also one of the important fields of Education Economics research.

The authors use Data Envelopment Analysis (DEA) to evaluate a sample of 58 primary schools in six districts in Beijing, hoping to find the solutions to school efficiency improvement as a result of under‐adequate investment.

In the years to come, the central government of China will continue to enhance transferring payment from the exchequer. The education input will be assured accordingly. However, if schools run under low efficiency, the education resources will not be well used and sustainability of elementary education will not be assured.

In light of the research purpose and the limited data, there has been no in‐depth discussion of the impact of, for example, families' social status, district development disparity, social cultural influence and history context. Obviously, considering more factors which may affect school efficiency will help to find the best solution for the public education sector of government.

Data integration is to combine data residing at different sources and to provide the users with a unified interface of these data. An important issue on data integration is the existence of conflicts among the different data sources. Data sources may conflict with each other at data level, which is defined as data inconsistency. The purpose of this paper is to aim at this problem and propose a solution for data inconsistency in data integration.

A relational data model extended with data source quality criteria is first defined. Then based on the proposed data model, a data inconsistency solution strategy is provided. To accomplish the strategy, fuzzy multi-attribute decision-making (MADM) approach based on data source quality criteria is applied to obtain the results. Finally, users feedbacks strategies are proposed to optimize the result of fuzzy MADM approach as the final data inconsistent solution.

To evaluate the proposed method, the data obtained from the sensors are extracted. Some experiments are designed and performed to explain the effectiveness of the proposed strategy. The results substantiate that the solution has a better performance than the other methods on correctness, time cost and stability indicators.

Since the inconsistent data collected from the sensors are pervasive, the proposed method can solve this problem and correct the wrong choice to some extent.

In this paper, for the first time the authors study the effect of users feedbacks on integration results aiming at the inconsistent data.

Numerous Chinese management studies have demonstrated significant differences between Chinese and Western management. This exploratory paper investigates the impact of Chinese culture and Western traditions on China's contemporary school leaders' views of leadership and management, particularly in the areas of relationship building, delegation, and promotion. Data were drawn from questionnaires completed by school leaders and individual interviews with principals from different parts of China. The findings indicate that the differences between Chinese and Western management practices in Chinese schools are not static and should not be over-stressed. To different extents, the respondent school leaders of China were affected by both Chinese and Western values and practices in school leadership and management. Specifically, they were more influenced by Chinese culture in the areas of school management and organization and by Western values and practices in the areas of relationship building, staff performance, and promotion. Their leadership and management preferences were also influenced by other factors, including gender, domestic politics, and development.

The purpose of this paper is to examine interruption patterns between residents and patients as well as the correlations between three categories of interruptions and patient satisfaction.

A total of 40 resident/patient consultations in a Canadian clinic were audiotaped, transcribed and analyzed for intrusive, cooperative and unsuccessful interruptions.

Residents made significantly more interruptions than patients, especially in the categories of intrusive interruptions. These findings provide support for situated identity theory. High correlations were found between residents and patients on all three categories of interruptions, providing unequivocal support for communication accommodation theory. Patient satisfaction was negatively correlated with residents' intrusive interruptions and positively correlated with residents' cooperative interruptions. Patient satisfaction was higher among patients those who inserted more cooperative interruptions; to increase patient satisfaction, it is necessary to raise patient participation in the medical consultation. In comparison with healthier patients, sicker patients were interrupted more frequently and were less satisfied with the way they were treated.

The negative correlations between residents' intrusive interruption and patient satisfaction, as well as the positive correlation between patient satisfaction and residents' cooperative interruption provides evidence that patients' perception of the medical consultation is shaped by the nature of interruptions.

Previous researches have considered that the impact of fashion change and fashion consumption is linear. Therefore, one reason was found as the ultimate source to explain why a fashion style/ trend was spread to the mass market. However, the existing market is complex and difficult to find out the holistic reason to explain fashion consumption. In this study, the chaotic perspective is taken into account to investigate the relationship between fashion change and fashion consumption. By using the grounded theory method, 33 in‐depth interviews were conducted. A chaotic fashion consumption model is developed from the findings to explain how different fashions are consumed and rejected while fashion changes. It is found that the interaction of being fashionable, perceived fashionability and system participation affects the ultimate decision on fashion consumption. It is also found that a pattern can be traced to forecast the degree of fashion consumption even when the fashion change phenomenon is chaotic. Thus, it is similar to the principle of chaos theory that short‐term prediction is possible in relation to the degree of fashion acceptance among consumers. Marketing implications are suggested with reference to the chaotic fashion consumption model.

Cobalt-based alloys exhibit a unique combination of wear resistance, strength and corrosion resistance. Localized corrosion of such alloys in seawater system can be several orders of magnitude faster than general corrosion, and direct experimental evidence of the local activation process is still lacking, which makes the accurate prediction for properties difficult, especially for long-term corrosion. The purpose of this study is revealing the relationship between multiple environments and corrosion properties to predict the corrosion of cobalt-based alloys.

A data-driven method for the prediction of the corrosion behavior of cast and hot isostatic-pressed CoCrMo/W alloys in seawater is proposed. The gradient boosting regression models calculate mean relative errors (MREs) of 0.160 and 0.435 by evaluating a hold-out set for breakdown potential (E_b) and maximum current density (i_max), respectively, considering various compositions, synthesis methods and corrosion environments.

The models can be used to estimate the “unseen” cobalt-based alloy after immersion in 3.5 Wt.% NaCl solution for one, two, four and eight months to obtain high precision with MREs of 7.8% and 9.8% for E_b and i_max, respectively.

Machine learning method provides novel and promising insights for the prediction of localized corrosion properties.

A number of previous studies have investigated international construction project risks and have proposed risk mitigation measures without examining their interdependence. The purpose of the current study is to identify the influence of various risk mitigation measures on macro-level risk factors in the international marketplace.

The authors initially identified 26 risk variables and nine risk mitigation measures through a literature review, which were then verified for their pertinence to international projects by three experts. Subsequently, 105 questionnaire survey responses were collected and analysed using factor analysis and structural equation modelling to test the interrelations between the risk variables and mitigation measures.

The findings suggest that joint ventures with local partners is emerged as the most critical risk mitigation measure that influences the international projects, which are exposed to political, project and firm-specific risk factors. Further, it is worth noting that among the recognised risk mitigation measures in international projects, offering more local employment is the least critical mitigation measure in the international projects.

The findings of this study are based on the macro-risk factors encountered by Indian construction firms in international projects, mostly from specific Asian and African regions. Thus, the opinions of construction firms from the developed countries might be different.

The main contribution of this study to existing knowledge is empirical evidence of the interrelationships between risk mitigation measures and risk factors that are portrayed as latent variables of different manifest risk variables. The generated model can assist construction firms in emphasising several risk mitigation methods, in order to reduce risk and enhance performance in international construction projects.

This study aims to clarify the key factors among physical‐mechanical properties of fabrics in relation to the dynamic pressure performance of compression garment.

The physical‐mechanical properties of 16 different fabrics were measured using a KESF standard evaluation system and INSTRON tensile tester, and the garment pressure was measured by dynamic pressure measuring system. Grey correlation analysis is used to determine the correlation degree of fabric physical‐mechanical properties and dynamic pressure magnitude.

The mechanical behaviors (e.g. tensile, shearing, and bending) and physical characteristics are different in elastic fabrics with varied content of elastic fiber, kinds of yarn, et al. Grey correlation analysis is a valid method to analyze the indices of a system, quantize them and put them in order. All the degrees of Grey correlation are more than 0.6. The degree of grey correlation between tensile force (F), shearing rigidity (G) and bending rigidity (B) are higher than others, hence it is conducted that these would significantly effect on garment pressure. The quantitative regression equations between pressure magnitude at extension of 50 percent and the individual key parameters (mean values in wale and course directions) of tested samples are illustrated.

The other parameters (e.g. fabric structure, yarn fineness, and pre‐tension, et al.) should be taken into account. Further, an integrative mathematic model would be established, which could predict the garment pressure directly from the physical‐mechanical properties of fabric.

The present study indicates that pressure magnitude of elastic fabric is an integrative action performed by physical‐mechanical properties. The developed illustrative equations and method offer a rational and practical tool for assessing pressure functional performance of elastic fabric in the stages of design and product development.

Examines the fifthteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.