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The purpose of this paper is to present a new stereolithograhy (SL) process which could substantially improve the efficiency of building process through controlling the beam spot size and optimizing the process parameters dynamically.

In this process, the focus length of UV laser scanning head is changed by the dynamic focus mirror according to the building program. The beam spot in the resin surface varies with the focus length, and the laser power is adjusted accordingly to the changing spot in building process.

The study finds that the efficiency of building process has a close relationship with the beam spot size. The experiments showed that the larger the laser spot diameter was, the less the depth and the larger the width of the cured lines would be. Then the building program would adjust the UV laser power to compensate for the decreased curing depth caused by the enlarged beam spot. At last, the spot compensation was optimized for the new method that could keep the same building accuracy with the traditional SL process.

The variable beam spot process could improve the building efficiency by 30 percent without increasing the cost of system, and keep the same accuracy compared with the conventional SL process.

The purpose of this paper is to critically assesses the major contributions to the academic literature on China’s increased focus on Africa, from 2001 to 2011. It discusses the key trends concerning China’s presence in Africa and draws conclusions on the significance of the studies by emphasizing and contrasting the prevailing positions.

Based on a qualitative approach using an integrative and comprehensive literature review, the authors performed a content analysis of high-impact, peer-reviewed papers.

The paper questions and repositions some of the existing controversies. The results from existing studies remain questionable, requiring further clarification and more theoretical backing. It, moreover, highlights the notion that behind the explicit neutrality views of China’s presence in Africa, implicit assumptions may exist. These are often the differences in narratives conveyed by Western and Southern stakeholders.

Most of the conclusions drawn from this paper need to be re-explored and supported by additional research. This could be done by widening the scope of the analysis. Studies need to provide more empirical support for their assertions through quantitative data and evidence-based qualitative analyses

all within a framework that considers more cultural, social and historical dimensions. The paper also suggests that an institutionally based view appears most relevant in better explaining China in Africa.

This paper reviews a decade of research on China in Africa and presents a snapshot of the current state of knowledge. It also raises concerns to be analyzed by future research and proposes new avenues for better understanding China’s presence in Africa.

This paper is intended to test the robustness of the fitness of nested GARCH models.

Both Monte‐Carlo simulation data and real‐world data are used in the paper. Likelihood‐family tests are used to test in‐sample fitness, while mean‐squared prediction error is employed for out‐sample prediction tests.

The paper finds that, generally, the parsimonious principle is found to work well for both criteria. However, it is found that conflict exists between the two criteria: in‐sample likelihood‐family tests pay more attention to conditional distributions or are more sensitive to fat tail effects; while the out‐sample criteria focus more on the accuracy of parameter estimation.

The paper shows that complexity does not necessarily mean good fitness; sometimes, the simpler model can fit better, especially for real‐world data.

This paper aim to build an information fusion model that can predict the bottom shape of welding groove for better welding quality control. Arc sensor is widely used in seam tracking due to its simplicity and good accessibility, but it heavily relies on the bottom shape of the groove. It is necessary to identify the welding groove bottom state. Therefore, arc sensor information and vision sensing information were fused by the rough set (RS) method to predict the groove state, which will lay the foundation for better welding quality control.

First, a multi-sensor information system was established, which included an arc sensing component and a vision sensing component. For the arc sensing system, the current waveform in each rotating period was obtained and divided into 12 parts to calculate variables representing the variation of arc length. For the vision sensing system, images were obtained by passive vision when the arc was near the groove sidewall. The positions of the sidewall and the arc were calculated to get the weld deviation which was unrelated with the bottom groove state. Second, experimental data were generated by workpiece with various bottom shapes. At last, the RS method was adopted to fuse the arc sensing and the vision information, and a rule-based model with good prediction ability was obtained.

By fusing arc sensing and vision sensing information, an RS-based model was built to predict the welding groove state.

The RS modeling method was used to fuse arc sensing information and vision sensing information to build a model that predicts groove bottom state. The arc sensing information represented the arc length variation, while the vision sensing information contains the seam deviation which was unrelated with the bottom groove state. The RS model gives satisfactory prediction results and can be applied to weld quality control.

The purpose of this paper is investigating the value of service guarantee (SG) program in Service e-Commerce (SeC) which is one resolution to promote service transactions. SeC is emerging as a booming form of e-commerce where various services are contracted, managed, sold and even delivered via the Internet. However, the uncertainty of service quality and the heterogeneity of buyer preferences have been major challenges to sustainable development of SeC.

This study uncovered the value of SG in SeC by empirically analyzing the data collected from zhubajie.com, a well-known service e-marketplace in China, to classify the service providers, to indentify the predictors for SG subscription and to study the effects of SG on service providers’ business performance and service quality.

The authors found that the distribution of service provisions is diversified in terms of low-success, mid-success and high-success providers, while proactive or high ability-ranking providers consistently tend to subscribe to SG program. The study revealed that SG has diverse effects on business performance for low-success and mid-success providers. For high-success providers, it seems to not be an effective choice for transaction promotion. Finally, the results showed that SG marginally improved service quality.

This research provides some practical implications for SeC markets to improve SG program. In addition, the results also help service providers to understand the value of SG in depth.

This article extended the research of SG from the traditional offline market to the online market, as with SeC, in which transactions are conducted without face to face contact.

This study aims to investigate dynamic relations among office property price indices of 10 major cities in China for the years 2005–2021.

Using monthly data, the authors adopt vector error correction modeling and the directed acyclic graph for the characterization of contemporaneous causality among the 10 indices.

The PC algorithm identifies the causal pattern, and the linear non-Gaussian acyclic model algorithm further determines the causal path from which we perform innovation accounting analysis. Sophisticated price dynamics are found in price adjustment processes following price shocks, which are generally dominated by the top tier of cities.

This suggests that policies on office property prices, in the long run, might need to be planned with particular attention paid to the top tier of cities.

The purpose of this paper is to focus on resource allocation and information disclosure policy for defending multiple targets against intentional attacks. The intentional attacks, like terrorism events, probably cause great losses and fatalities. Attackers and defenders usually make decisions based on incomplete information. Adaptive attacking and defending strategies are considered, to study how both sides make more effective decisions according to previous fights.

A stochastic game‐theoretic approach is proposed for modeling attacker‐defender conflicts. Attackers and defenders are supposed both to be strategic decision makers and partially aware of adversary's information. Adaptive strategies are compared with different inflexible strategies in a fortification‐patrol problem, where the fortification affects the security vulnerability of targets and the patrol indicates the defensive signal.

The result shows that the intentional risk would be elevated by adaptive attack strategies. An inflexible defending strategy probably fails when facing uncertainties of adversary. It is shown that the optimal response of defenders is to adjust defending strategies by learning from previous games and assessing behaviors of adversaries to minimize the expected loss.

This paper explores how adaptive strategies affect attacker‐defender conflicts. The key issue is defense allocation and information disclosure policy for mitigation of intentional threats. Attackers and defenders can adjust their strategies by learning from previous fights, and the strategic adjustment of both sides may be asynchronous.

In past decades, artificial neural network (ANN) models have revolutionised various stock market operations due to their superior ability to deal with nonlinear data and garnered considerable attention from researchers worldwide. The present study aims to synthesize the research field concerning ANN applications in the stock market to a) systematically map the research trends, key contributors, scientific collaborations, and knowledge structure, and b) uncover the challenges and future research areas in the field.

To provide a comprehensive appraisal of the extant literature, the study adopted the mixed approach of quantitative (bibliometric analysis) and qualitative (intensive review of influential articles) assessment to analyse 1,483 articles published in the Scopus and Web of Science indexed journals during 1992–2022. The bibliographic data was processed and analysed using VOSviewer and R software.

The results revealed the proliferation of articles since 2018, with China as the dominant country, Wang J as the most prolific author, “Expert Systems with Applications” as the leading journal, “computer science” as the dominant subject area, and “stock price forecasting” as the predominantly explored research theme in the field. Furthermore, “portfolio optimization”, “sentiment analysis”, “algorithmic trading”, and “crisis prediction” are found as recently emerged research areas.

To the best of the authors’ knowledge, the current study is a novel attempt that holistically assesses the existing literature on ANN applications throughout the entire domain of stock market. The main contribution of the current study lies in discussing the challenges along with the viable methodological solutions and providing application area-wise knowledge gaps for future studies.

This paper aims to analyse the class dimensions of racism in Taiwan against temporary migrant workers and migrants' efforts to build inter‐ethnic and labour‐community coalitions in struggle against racism.

An important source of data for this study were the unstructured interview. Between September 2000 and December 2005, more than 50 temporary migrants and their support groups in Taiwan were interviewed, specifically about migrants' experiences of racism and their resistance strategies. These interviews were conducted face‐to‐face, sometimes with the assistance of translators. Between 2001 and 2007, some 70 people were interviewed by telephone, between Australia and Taiwan.

In Taiwan, temporary migrants suffer the racism of exploitation in that capital and the state “racially” categorize them as suitable only for the lowest paid and least appealing jobs. Migrants also suffer neglect by and exclusion from the labour unions. However, migrants have succeeded, on occasions, in class mobilization by building powerful inter‐ethnic ties as well as coalitions with some labor unions, local organizations and human rights lobbies.

The research raises implications for understanding the economic, social and political conditions which influence the emergence of inter‐ethnic bonds and labour‐community coalitions in class struggle.

The research will contribute to a greater appreciation among Taiwan's labour activists of the real subordination of temporary migrant labour to capital and of the benefits of supporting migrants' mobilization efforts. These benefits can flow not only to migrants but also to the labour unions.

A significant body of academic literature has recently emerged on temporary and illegal migrants' efforts to engage the union movements of industrialized host countries. There is a dearth, however, of academic research on the capacity of temporary migrants to invigorate union activism in Asia, including Taiwan.

Traditional algorithms require at least two complete vector observations to estimate orientation parameters. However, sensor faults and disturbances may cause some components of vector observations unavailable. This paper aims to propose algorithms to realize orientation estimation using vector observations with one or two components lost.

The fundamental of the proposed method is using norm equation and dot product equation to estimate the lost components, then, using an improved TRIAD to calculate attitude matrix. Specific algorithms for one and two lost components cases are constructed respectively, and the nonuniqueness of orientation estimation is analyzed from a geometric point of view. At last, experiments are performed to test the proposed algorithms.

The loss of components results in the loss of orientation information. The introduction of the norm equation and dot product equation can partially compensate for the loss of information. Experiment results and analysis show that the proposed algorithms can provide effective orientation estimation, and in vast majority of applications, the proposed algorithms can provide a unique solution in one lost component case and double solutions in two lost components case.

The proposed method addresses the problem of orientation estimation when one or two components of vector observations are unavailable. The introduction of the norm equation and dot product equation makes the calculation cost low, while the analyses from a geometric point of view makes the study of nonuniqueness more intuitive.