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A three-dimensional (3D) printing error simulation approach is proposed to analyze the influence of tilted vertical beams on the 3D printing accuracy. The purpose of this study is to analyze the influence of such errors on printing accuracy and printing quality for delta-robot 3D printer.

First, the kinematic model of a delta-robot 3D printer with an ideal geometric structure is proposed by using vector analysis. Then, the normal kinematic model of a nonideal delta-robot 3D robot with tilted vertical beams is derived based on the above ideal kinematic model. Finally, a 3D printing error simulation approach is proposed to analyze the influence of tilted vertical beams on the 3D printing accuracy.

The results show that tilted vertical beams can indeed cause 3D printing errors and further influence the 3D printing quality of the final products and that the 3D printing errors of tilted vertical beams are related to the rotation angles of the tilted vertical beams. The larger the rotation angles of the tilted vertical beams are, the greater the geometric deformations of the printed structures.

Three vertical beams and six horizontal beams constitute the supporting parts of the frame of a delta-robot 3D printer. In this paper, the orientations of tilted vertical beams are shown to have a significant influence on 3D printing accuracy. However, the effect of tilted vertical beams on 3D printing accuracy is difficult to capture by instruments. To reveal the 3D printing error mechanisms under the condition of tilted vertical beams, the error generation mechanism and the quantitative influence of tilted vertical beams on 3D printing accuracy are studied by simulating the parallel motion mechanism of a delta-robot 3D printer with tilted vertical beams.

The purpose of this paper is to provide Australian evidence on both the extent and key determinants of discretionary disclosure in company annual reports of information about top executives' share rights, options and termination entitlement. Such information has value‐relevance to shareholders and the public, but prior evidence is lacking about the factors that influence top managements' decisions to voluntarily disclose or withhold personally sensitive details about their own remuneration.

The extent and nature of executive remuneration disclosure are obtained from the content analysis of annual reports of 191 Australian listed companies for the years 2003 and 2004, prior to a more detailed prescriptive regulatory environment occurring in this area when international financial reporting standards became effective in 2005. To explain the factors that could influence managements' decisions about the extent of discretionary disclosure details concerning their own remuneration, the perspectives of legitimacy theory and corporate governance structures are invoked. Relationships are hypothesized and tested between the extent of remuneration disclosure and the following variables: shareholder activism, media attention, company size, board composition and existence of a remuneration committee.

Regression results reveal significant relationships between these determinants and the extent of disclosures of rights, options and termination benefits of executives. These results suggested that, under a relatively unregulated environment, corporate management will react to community and shareholders' expectations by revealing personally sensitive information when their company is placed in a situation of higher shareholder and public scrutiny and when it is structured to meet expectations of good corporate governance.

This study advances knowledge of the influence that companies' legitimation circumstances and corporate governance structures can have on public disclosure decisions by management about the level of detail of their remuneration – information that is of high interest to shareholders and personally sensitive to management.

This study attempts to examine the issues relating to corporate financial reporting of Chinese listed companies under specified institutional settings as companies with different share‐categories are required to prepare annual reports under various General Accepted Accounting Principles (GAAP).

This study selects Chinese companies that issue negotiable shares to examine whether corporate disclosure patterns are different under various institutional settings. Negotiable shares can be traded on stock exchanges and are divided into A‐, B‐ and H‐shares. The extent of corporate disclosure is obtained from the content analysis of annual reports for 191 sampled Chinese listed companies with various share categories. The association are hypothesized and tested between the level of corporate disclosure and the following corporate determinants: company size, profitability, auditor, leverage, industry and ownership structure.

The extensive regulations and different standards influence on disclosures of companies with foreign investment participation and overseas listing status. By reconciliation of their annual reports according to the IFRSs or the GAAP of the listing country, these companies increased information disclosure voluntarily in order to enhance their reputation and credibility. Some corporate factors, such as company size, profitability and the size of auditor, have influenced the level of corporate disclosure in annual reports of domestic and foreign share‐based companies. Ownership structure has positive impact on the level of disclosure for companies with domestic investors.

This study advances knowledge of the influence that legislative circumstances and ownership structures can have on disclosure decisions made by management in their annual reports. This information is of high interest to domestic and foreign investors and regulators in understanding of financial reporting in Chinese listed companies.

The purpose of this paper is to investigate the potential impact of the approved Australian carbon emissions reduction plan on the cost of capital and the association between companies’ carbon emission intensity and the cost of capital.

A sample of Australian Stock Exchange 200 (ASX 200)-indexed companies from 2006 to 2010 is used. Hypotheses are tested based on Heckman’s two-stage approach. Three regression models are developed to examine the association between carbon emissions and the cost of capital.

Using a sample of ASX 200-indexed listed companies, the paper finds that the cost of capital, including the cost of debt and the cost of equity, will increase for emissions-liable companies. Results also show that the cost of debt is positively correlated with a company’s emission intensity. However, little evidence supports that the emission intensity affects the cost of equity.

As it is evident that the emissions reduction plan will adversely affect corporate entities’ cost of capital, this study suggests that companies, investors and lenders need to include carbon emission in risk analysis. An emissions-liable company should establish strategies to combat the impact of the Plan on rising cost that comes with the enforcement of the Plan. Government assistance is essential in the transitional period.

The purpose of this paper is to serve as a comprehensive review of short-term study abroad (STSA) outcomes to help guide future STSA and study abroad (SA) scholars and practitioners in the further development of the field.

This paper is the first comprehensive and systematic review of all outcomes of STSA programs within the SA body of research based on 156 papers.

The study provides the first comprehensive classification of all previously studied STSA outcomes (85) into six categories: cross-cultural outcomes, STSA pedagogy outcomes, personal and professional outcomes; language outcomes; teacher and faculty outcomes; and other outcomes. Distinct sub-categories are identified that provide insights on the current landscape of STSA and related research.

This study makes a significant contribution to the theory and practice of SA, and among the key contributions are a systematic understanding of the scale and scope of STSA outcomes; insights on the most efficient design of future STSA programs; and an expanded understanding of the role and importance of STSA programs in international education. Furthermore, a comprehensive STSA outcomes map develops an extensive research agenda.

While the COVID-19 pandemic currently limits the opportunities for STSA, given its previous popularity, the authors envisage a strong return in the coming years of this form of affordable and valuable global learning. STSA programs have become an important component of higher education and which require considerable resources from participants and educational institutions alike. Therefore, further research is needed to understand the impacts of STSA programs and to further improve program design. Such research will serve to better inform both academic understanding of the phenomenon and educational practice.

The study provides the first comprehensive classification of all studied STSA outcomes.

This paper aims to explore the effects of normative and hedonic motivations on continuous knowledge contribution, and how past contribution experience moderates the effects of the motivations on continuous knowledge contribution.

Based on goal-framing theory, the present study proposes a comprehensive theoretical model by integrating normative and hedonic motivations, past contribution experience and continuous knowledge contribution. The data for virtual community members' activities were collected using the Python Scrapy crawler. Logit regression was used to validate the integrative model.

The results show that both normative motivation (reflected by generalized reciprocity and social learning) and hedonic motivation (reflected by peer recognition and online attractiveness) are positively associated with continuous knowledge contribution. Moreover, these effects are found to be significantly influenced by members' past knowledge contribution experience. Specifically, the results suggest that past knowledge contribution experience undermines the influence of generalized reciprocity on continuous knowledge contribution but strengthens the effect of peer recognition and online attractiveness.

Although the emerging literature on continuous knowledge contribution mainly focuses on motivations as antecedents that promote continuous knowledge contribution, most of these studies assume that the relationship between motivating mechanisms and continuous knowledge contribution does not change over time. The study is one of the initial studies to examine whether and how the influence of multiple motivations evolves relative to levels of past contribution experience.

Scattered parts are laid randomly during the manufacturing process and have difficulty to recognize and manipulate. This study aims to complete the grasp of the scattered parts by a manipulator with a camera and learning method.

In this paper, a cascaded convolutional neural network (CNN) method for robotic grasping based on monocular vision and small data set of scattered parts is proposed. This method can be divided into three steps: object detection, monocular depth estimation and keypoint estimation. In the first stage, an object detection network is improved to effectively locate the candidate parts. Then, it contains a neural network structure and corresponding training method to learn and reason high-resolution input images to obtain depth estimation. The keypoint estimation in the third step is expressed as a cumulative form of multi-scale prediction from a network to use an red green blue depth (RGBD) map that is acquired from the object detection and depth map estimation. Finally, a grasping strategy is studied to achieve successful and continuous grasping. In the experiments, different workpieces are used to validate the proposed method. The best grasping success rate is more than 80%.

By using the CNN-based method to extract the key points of the scattered parts and calculating the possibility of grasp, the successful rate is increased.

This method and robotic systems can be used in picking and placing of most industrial automatic manufacturing or assembly processes.

Unlike standard parts, scattered parts are randomly laid and have difficulty recognizing and grasping for the robot. This study uses a cascaded CNN network to extract the keypoints of the scattered parts, which are also labeled with the possibility of successful grasping. Experiments are conducted to demonstrate the grasping of those scattered parts.

The purpose of this paper is to understand citizens' perceptions of smartphone-based city management apps and to identify facilitators and barriers that influence app adoption and use. An aim is to identify how current technology adoption theories might be expanded and enriched for studying citizen adoption of city apps in the US.

This paper presents a qualitative exploratory case study of citizen perceptions of city management apps in Tallahassee, a top-ranked digital city in the southeastern United States. The authors derive empirical data from focus group discussions with citizens using thematic analysis.

Overall, the findings suggest that city management apps are primarily perceived and used by citizens as handy and efficient tools for the provision of information and public services. The findings suggest that current technology adoption and use models applied to citizen adoption of m-government may benefit by being expanded for the US context.

This paper highlights what factors of m-government technology are effective, useful or inhibiting in citizens' lives from the perspective of a group of citizens in the southeastern US. Implications that might be learned for researchers and practitioners are discussed.

Helicopter fuselage vibration prediction is important to keep a safety and comfortable flight process. The helicopter vibration mechanism model is difficult to meet of demand for accurate vibration prediction. Thus, the purpose of this paper is to develop an intelligent algorithm for accurate helicopter fuselage vibration analysis.

In this research, a novel weighted variational mode decomposition (VMD)- extreme gradient boosting (xgboost) helicopter fuselage vibration prediction model is proposed. The vibration data is decomposed and reconstructed by the signal clustering results. The vibration response is predicted by xgboost algorithm based on the reconstructed data. The information transfer order between the controllable flight data and flight attitude are analyzed.

The mean absolute percentage error (MAPE), root mean square error (RMSE) and mean absolute error (MAE) of the proposed weighted VMD-xgboost model are decreased by 6.8%, 31.5% and 32.8% compared with xgboost model. The established weighted VMD-xgboost model has the highest prediction accuracy with the lowest mean MAPE, RMSE and MAE of 4.54%, 0.0162, and 0.0131, respectively. The attitude of horizontal tail and cycle pitch are the key factors to vibration.

A novel weighted VMD-xgboost intelligent prediction methods is proposed. The prediction effect of xgboost model is highly improved by using the signal-weighted reconstruction technique. In addition, the data set used is collected from actual helicopter flight process.

This paper studies the lateral stability regulation of intelligent electric vehicle (EV) based on model predictive control (MPC) algorithm.

Firstly, the bicycle model is adopted in the system modelling process. To improve the accuracy, the lateral stiffness of front and rear tire is estimated using the real-time yaw rate acceleration and lateral acceleration of the vehicle based on the vehicle dynamics. Then the constraint of input and output in the model predictive controller is designed. Soft constraints on the lateral speed of the vehicle are designed to guarantee the solved persistent feasibility and enforce the vehicle’s sideslip angle within a safety range.

The simulation results show that the proposed lateral stability controller based on the MPC algorithm can improve the handling and stability performance of the vehicle under complex working conditions.

The MPC schema and the objective function are established. The integrated active front steering/direct yaw moments control strategy is simultaneously adopted in the model. The vehicle’s sideslip angle is chosen as the constraint and is controlled in stable range. The online estimation of tire stiffness is performed. The vehicle’s lateral acceleration and the yaw rate acceleration are modelled into the two-degree-of-freedom equation to solve the tire cornering stiffness in real time. This can ensure the accuracy of model.