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As manufacturing technology has developed, digital models from advanced measuring devices have been widely used in manufacturing sectors. To speed up the production cycle and reduce extra errors introduced in surface reconstruction processes, directly machining digital models in the polygonal stereolithographyformat has been considered as an effective approach in rapid digital manufacturing. In machining processes, Cutter Location (CL) data for numerical control (NC) machining is generated usually from an offset model. This model is created by offsetting each vertex of the original model along its vertex vector. However, this method has the drawback of overcut to the offset model. The purpose of this paper is to solve the overcut problem through an error compensation algorithm to the vertex offset model.

Based on the analysis of the vertex offset method and the offset model generated, the authors developed and implemented an error compensation method to correct the offset models and generated the accurate CL data for the subsequent machining process. This error compensation method is verified through three polygonal models and the tool paths generated were used for a real part machining.

Based on the analysis of the vertex offset method and the offset model generated, the authors developed an error compensation method to correct the offset models and generated the accurate CL data for the subsequent machining process. The developed error compensation algorithm can effectively solve the overcut drawback of the vertex offset method.

The error compensation method to the vertex offset model is used for generating the CL data with the using of a ball-end cutter.

On the study of CL data generation for a STL model, most of the current studies are focused on the determination of the offset vectors of the vertexes. The offset distance is usually fixed to the radius of the cutter used. Thus, the overcut problem to the offset model is inevitable and has not been much studied. The authors propose an effective approach to compensate the insufficient distance of the offset vertex and solve the overcut problem.

The directly tool paths generation from a STL model can reduce the error of surface reconstruction and speed up the machining progress.

The authors investigate the overcut problem occurred in vertex offset for CL data generation and present a new error compensation algorithm for generating the CL data that can effectively solve the overcut problem.

The purpose of this paper is to examine the impact of Chinese youth’s attention to and involvement with Chinese soccer and its professional league, the Chinese Super League (CSL), on their level of satisfaction.

A survey study was employed to test the hypotheses. Research participants (n=948) were students from five major universities that represented each of the five main geographic regions of China. Data were randomly assigned into two halves: one half for CFA (n=474) and the other half for structural equation modeling (SEM) (n=474). Mplus 7.0 was used to conduct both the CFA and SEM.

The findings of this study indicated an overall lack of attention to and involvement with Chinese soccer and CSL among Chinese youths. Discussions have been presented on the causes of the lack of youth passion for Chinese soccer and suggestions have been articulated to improve the effectiveness and efficiency of policy formulation, business operation and marketing strategy.

The present study built on the extant sport management literature, demonstrated the complexity of consumers’ cognition and conation in the professional soccer setting, and revealed counter-intuitive relationship between attitudinal traits and behavioral patterns, which in turn provided unique insights for Chinese professional soccer marketers, managers and administrators.

This research aims to collect human body variables via 2D images captured by digital cameras. Based on those human variables, the forecast and recommendation of the Digital Camouflage Uniforms (DCU) for Taiwan's military personnel are made.

A total of 375 subjects are recruited (male: 253; female: 122). In this study, OpenPose converts the photographed 2D images into four body variables, which are compared with those of a tape measure and 3D scanning simultaneously. Then, the recommendation model of the DCU is built by the decision tree. Meanwhile, the Euclidean distance of each size of the DCU in the manufacturing specification is calculated as the best three recommendations.

The recommended size established by the decision tree is only 0.62 and 0.63. However, for the recommendation result of the best three options, the DCU Fitting Score can be as high as 0.8 or more. The results of OpenPose and 3D scanning have the highest correlation coefficient even though the method of measuring body size is different. This result confirms that OpenPose has significant measurement validity. That is, inexpensive equipment can be used to obtain reasonable results.

In general, the method proposed in this study is suitable for applications in e-commerce and the apparel industry in a long-distance, non-contact and non-pre-labeled manner when the world is facing Covid-19. In particular, it can reduce the measurement troubles of ordinary users when purchasing clothing online.

Combining the collected human body variables by a 3D body scanner and the research results of medical computed tomography (CT) imaging, this research aims to develop a military bulletproof vest that is both protective and fit. In particular, the protective part must be able to cover the vital human internal organs completely. The results of this research help to make military bulletproof vests of different sizes for Taiwanese male and female soldiers. At the same time, the research results can provide a reference for the industry of making special-purpose clothing.

17 important human body variables of 988 participants (male: 716, 72.5%; female 272, 27.5%) are used for the analysis. The K-means algorithm firstly builds clusters of different body shapes for both sexes; the silhouette coefficient helps to determine the optimal number of clusters to be six. Thus, the standard size of the bulletproof vest for soldiers is determined. The specifications of the bulletproof vest's inner core and textile vest are calculated for each cluster user. Our research then makes twelve prototypes of the bulletproof vest. After that, 12 subjects are invited to try on the new version (the vest designed in this study) and the old version (the vest currently used) to contrast the differences between the two.

According to the index of the silhouette coefficient, the optimal number of clusters is determined to be six for both male and female clusters. Therefore, this study has designed six sizes of the bulletproof vest for male and female soldiers in Taiwan. After trying the new and old vests on, the subjects all indicate that the new vest fits better than the old one. In addition, the coverage of the bulletproof vest designed in this study is 94.38% for male users and 92.75% for female users.

The design of bulletproof vests must take note of the fit of the clothing itself and its protective function. Apart from the size design of general clothing only focusing on the human shape exteriorly, the bulletproof vest also needs to pay attention to the relative positions of vital organs inside the human body. Besides, for practical applications, it is quite effective to use the silhouette coefficient to determine the results of cluster analysis. Thus, the value of this research lies in the cross-field combination, enabling the integration of body measurement, data science and clothing design. Generally, bulletproof vests of newly designed sizes can meet the requirements of Taiwan's military. The research results can be used in the development of various military clothing for Taiwanese military personnel. At the same time, the results can be provided to the clothing industry as relevant parameters for designing unique functional clothing.

Remanufacturing of worn blades with various defects normally requires processes such as scanning, regenerating a geometrical reference model, additive manufacturing (AM) through laser cladding, adaptive machining and polishing and quality inspection. Unlike the manufacturing process of a new part, the most difficult problem for remanufacturing such a complex surface part is that the reference model adaptive to the worn part is no longer available or useful. The worn parts may suffer from geometrical deformation, distortion and other defects because of the effects of harsh operating conditions, thereby making their original computer aided design (CAD) models inadequate for the repair process. This paper aims to regenerate the geometric models for the worn parts, which is a key issue for implementing AM to build up the parts and adaptive machining to reform the parts. Unlike straight blades with similar cross sections, the tip geometry of the worn tip of a twist blade needs to be regenerated by a different method.

This paper proposes a surface extension algorithm for the reconstruction of a twist blade tip through the extremum parameterization of a B-spline basis function. Based on the cross sections of the scanned worn blade model, the given control points and knot vectors are firstly reconstructed into a B-spline curve D. After the extremum of each control point is calculated by extremum parameterization of a B-spline basis function, the unknown control points are calculated by substituting the extremum into the curve D. Once all control points are determined, the B-spline surface of the worn blade tip can be regenerated. Finally, the extension algorithm is implemented and validated with several examples.

The proposed algorithm was implemented and verified through the exampled blades. Through the extension algorithm, the tip geometry of the worn tip of a twist blade can be regenerated. This method solved a key problem for the repair of a twist blade tip. It provides an appropriate reference model for repairing worn blade tips through AM to build up the blade tip and adaptive machining/polishing processes to reform the blade geometry.

The extension errors for different repair models are compared and analyzed. The authors found that there are several factors affecting the accuracy of the regenerated model. When the cross-section interval and the extension length are set properly, the restoration accuracy for the blade tip can be improved, which is acceptable for the repairing.

The lack of a reference geometric model for worn blades is a significant problem when implementing blade repair through AM and adaptive machining processes. Because the geometric reference model is unavailable for the repair process, reconstruction of the geometry of a worn blade tip is the first crucial step. The authors proposed a surface extension algorithm for the reconstruction of a twist blade tip. Through the implementation of the proposed algorithm, the blade tip model can be regenerated.

Remanufacturing of worn blades with various defects is highly demeaned for the aerospace enterprises considering sustainable development. Unlike straight blades, repair of twist blades encountered a very difficult problem because the geometric reference model is unavailable for the repair processes. This paper proposed a different method to generate the reference model for the repair of a twist blade tip. With this model, repair of twist blades can be implemented through AM to build up the blade tip and adaptive machining to subtract the extra material.

The authors proposed a surface extension algorithm to reconstruct the geometric model for repair of twist blades.

Despite the high demand for certified public accountants, the supply of professionals produced by colleges and universities is insufficient. Contributing to the inadequate supply, which the profession refers to as a “pipeline challenge,” are students who major in accounting but do not sit for the CPA exam. We shed light on this issue by studying students’ perceptions about the content of the CPA exam and the value of earning a CPA credential based on a survey of graduate accounting students at two East Coast universities. Overall, we find that students who do not plan to take the CPA underestimate the value of the CPA credential. We find that students cite various reasons for avoiding the exam including the difficulty of the exam, difficulty in preparation time and cost. We contend that until students perceive the true value of the credential, initiatives to increase the pipeline may not fully succeed. We suggest several potential interventions to educate students about the importance of the exam and encourage them to reconsider taking it.

International students make valuable educational and economic contributions in higher education institutions (HEIs) all across the world. They contribute to the diversity and add different perspective in classrooms. Attracting international students is one of the objectives of HEIs. International students being present all over the world access information about the university online. Hence, all the relevant information must be available on the HEI website. Institutions are also present on social media platforms for interaction purposes. The owned media, including website, social media, discussion forums, etc. of institutions must be regularly monitored and analysed. Equally important is to analyse what students are discussing online about institutions, that is, what are their sentiments. This chapter is an attempt to develop a guide for HEI to draw the interest of international students for an institution through web analytics and social listening. Web analytics will help in understanding the behaviour of the visitor to the HEI website. Key performance indicators that will help in achieve the objective of attracting international students will be identified. On the other hand, analysing social listening on different platforms will help in understanding international students’ perspectives towards a specific institution.

This paper aims to investigate the relationships between several macro‐economic indicators and real estate investment in China.

This study proposes the “investment preference theory” to explain that bank deposits, stock investment and real estate investment are three important investment vehicles to Chinese households.

The authors find that interest rate, an important monetary aggregate indicator – M2 – and the size of new equity offering are negatively related to real estate investment, which may imply that Chinese investors would prefer to channel their funds to stock market and high‐interest‐rate‐bearing bank deposits to keep a good balance between risk and high return on investment while higher interest rate also increases the cost of borrowing for the property buyers.

This is one of the first studies which investigated the connections behind Chinese consumers' real estate investment and empirically tested the choices among bank deposit, stock and property investment. This study hopefully deepens the understanding towards the consumer investment behaviors in housing investment decisions.

Happiness is an important mental emotion and yet becoming a major health concern nowadays. For this reason, better recognizing the objective understanding of how humans respond to event-related observations in their daily lives is especially important.

This paper uses non-intrusive technology (hyperspectral imaging [HSI]) for happiness recognition. Experimental setup is conducted for data collection in real-life environments where observers are showing spontaneous expressions of emotions (calm, happy, unhappy: angry) during the experimental process. Based on facial imaging captured from HSI, this work collects our emotional database defined as SWU Happiness DB and studies whether the physiological signal (i.e. tissue oxygen saturation [StO2], obtained by an optical absorption model) can be used to recognize observer happiness automatically. It proposes a novel method to capture local dynamic patterns (LDP) in facial regions, introducing local variations in facial StO₂ to fully use physiological characteristics with regard to hyperspectral patterns. Further, it applies a linear discriminant analysis-based support vector machine to recognize happiness patterns.

The results show that the best classification accuracy is 97.89 per cent, objectively demonstrating a feasible application of LDP features on happiness recognition.

This paper proposes a novel feature (i.e. LDP) to represent the local variations in facial StO₂ for modeling the active happiness. It provides a possible extension to the promising practical application.

Administrative data on the universe of employees, firms, and unemployment insurance (UI) recipients in Canada over an 11-year period are used to examine the operation of UI using the firm as the unit of analysis. Persistent transfers through UI are present at both industry and firm levels, and an analysis using firm fixed effect indicates that an important fraction of variation in them can be attributed to firm effects. Calculations of overall efficiency loss are very sensitive to the degree to which firm-level information is used. A full appreciation of how UI interacts with the labour market requires recognition of the characteristics and human resource practices of firms.