Search results

The purpose of this paper is to analyze the effect of the space thermal effect on satellite antenna.

In this paper, according to the geometric characteristics of parabolic reflector, the transient temperature field of an element along its thickness direction is built for shell structures using finite element discretization and the quadratic function interpolation, and heat conduction equations are derived based on the theory of the thermo-elastic dynamics. The modeling theory of rigid–flexible coupling system considering thermal effect is extended to the satellite antenna system. Then, the coupling dynamic equations are established including coupling stiffness matrix and thermal loaded undergoing a large overall motion. Finally, an adaptive controller is proposed and the adaptive update laws are designed under the parameter uncertainty.

The results of dynamic characteristic analysis show that the dynamic thermal loaded coupled with structure deformation induce the unstable vibration and coupled flutter. Further, the coupling effect degrades the antenna pointing accuracy seriously and leads to disturbances on satellite base. The results of the simulation show that the adaptive controller can ensure that antenna pointing closes to the expected trajectory progressively, and it demonstrates that the proposed control scheme is feasible and effective.

The paper considers only the effect of space thermal effect to satellite antenna. Further research could be done on the flexible multibody system by considering joint clearance in the future research.

The conclusions of this paper would be an academic significance and engineering value for the analysis and control of satellite antenna pointing.

In view of the significant changes in the capital structure of China’s real estate industry and enterprises in recent years, this chapter employs financial indicators and the linear regression function to analyze the relationship between corporate debt ratio and the performance of 111 A-share listed real estate enterprises in China. This study finds that the corporate debt ratio of China’s real estate enterprises in the past decade has a significant negative impact on enterprises’ performance. The study also finds that among China’s real estate companies, the corporate debt ratio has a more significant negative impact on the performance of non-state-owned enterprises than state-owned enterprises. In addition, a high debt ratio has a more significant negative impact on return on equity (ROE) than on return on assets (ROA). However, when Tobin’s Q serves as a proxy for firm performance, the negative impact of the corporate debt ratio becomes insignificant in the presence of the firm size factor. The research results of this chapter can provide some reference for subsequent policy-making and investment decisions in the Chinese real estate market.

This paper primarily aims to focus on a review of convolutional neural network (CNN)-based eye control systems. The performance of CNNs in big data has led to the development of eye control systems. Therefore, a review of eye control systems based on CNNs is helpful for future research.

In this paper, first, it covers the fundamentals of the eye control system as well as the fundamentals of CNNs. Second, the standard CNN model and the target detection model are summarized. The eye control system’s CNN gaze estimation approach and model are next described and summarized. Finally, the progress of the gaze estimation of the eye control system is discussed and anticipated.

The eye control system accomplishes the control effect using gaze estimation technology, which focuses on the features and information of the eyeball, eye movement and gaze, among other things. The traditional eye control system adopts pupil monitoring, pupil positioning, Hough algorithm and other methods. This study will focus on a CNN-based eye control system. First of all, the authors present the CNN model, which is effective in image identification, target detection and tracking. Furthermore, the CNN-based eye control system is separated into three categories: semantic information, monocular/binocular and full-face. Finally, three challenges linked to the development of an eye control system based on a CNN are discussed, along with possible solutions.

This research can provide theoretical and engineering basis for the eye control system platform. In addition, it also summarizes the ideas of predecessors to support the development of future research.

The United Nations through the Sustainable Development Goals (SDGs), for instance, the SDG 13 calls for climate action and SDG 11 calls for the development of smart and clean cities and communities. Empirical findings on this subject show the importance of clean fuels in fostering environmental sustainability. Literature shows a dearth on the studies examining on how “effective capital” affects the quality of the surroundings. “Effective capital” is fundamental because of its ability to cater for the complementarity of capital and energy.

This research uses the ecological footprint index to represent environmental damage, diverting from past studies that have extensively used carbon emission. The data of the European Union nations during the time 1990 to 2019 is utilized in data analysis. The contemporary method of data analysis, the Methods of Moments Quantile Regression, is employed; hence, reliable results are obtained in the presence of heterogeneity and cross-sectional dependence in the indicators and model.

The study findings show that effective capital is detrimental to environmental sustainability because of fossil fuel inclusion in this index. This calls for a transition by nations to clean fuels and technologies. Energy efficiency, research and development and renewable energy reduce ecological footprint. Research and development and renewable energy reduce ecological footprint in the upper quantiles, while energy efficiency reduces it in the lower and middle quantiles.

This study is presented to foster the growing body of knowledge on the influence of effective capital on the quality of the surroundings. The research presents essential policies on how environmental sustainability is achieved through energy transition and efficient use of energy.

The purpose of this paper is to undertake an analysis of the attempts of Gulf Cooperation Council (GCC) and Brazil, Russia, India and China (BRIC) countries to catch up in their national development to build an innovation-driven economy on which to base future growth and wealth. We conducted an analysis of GCC and BRIC countries to show the different strategies leaders have taken to try and achieve this aspiration. This paper analyses the various aspects of national innovation systems of BRIC and GCC countries, highlights similar and different approaches and attempts to quantify their success. For example, GCC countries spend extensively on research and development (R&D), but have so far achieved less than meaningful results. Brazil, China and India are catching up to the acknowledged world leaders in innovation, but Russia is lagging.

Our comparison was based mostly on secondary data from sources and institutions that use statistical data to build country rankings, such as the Global Competitiveness Index (GCI) produced by the World Economic Forum. BRIC and GCC countries were analyzed over 1996-2011 because most of the indicators data are only available from 1996. Data related to intellectual property rights have been collected since 1999 or 2000. The data available for the number of researchers proved problematic for both BRIC and GCC countries. For instance, some data for the GCC countries was missing. To not leave a gap, we extrapolated in line with the overall trend; using the least squares method to approximate a straight line for the missing data based on what had already been reported.

Counter-intuitively, we will argue that the push toward an innovation-based economy is actually not dependent on total expenditure on R&D, but rather relies on the efficient allocation of investments and the rigorous implementation of innovation strategy. And, we will demonstrate this by showing our ideas in relation to both BRIC and GCC countries. This analysis raises fascinating points of discussion for those looking to build an innovation economy in other countries and has practical implications for policy-makers and policy implementers in all countries.

First analysis of the correlation of gross expenditure on R&D (GERD) with gross domestic product (GDP) growth and Straits Times Index (STI) policy measures.

This study aims to expose the main knowledge management (KM) practices applied in BRIC (Brazil, Russia, India and China) industries using scientific literature published in the Scopus database from 2001 to 2010.

A search was performed in papers selected from the Scopus database, which houses the KM practices of industries in BRIC countries.

The results show that Brazil, Russia and India have an easier way of converting tacit knowledge into explicit knowledge compared to China, where informal relationships of trust and friendship play a special role within organizations, as well as where the political structure (communism) is an intervening factor. Brazil, Russia and India practice similar KM mechanisms such as the use of technology, process standardization and electronic data management. They also model the positive experiences of western companies. In China, interpersonal relationships shape the tacit and explicit features of organizations.

The methodological filter could potentially limit the volume of responses, as not every case study can demonstrate the usual practices of KM. Empirical studies are able to capture the nuances and even provide a holistic picture of these practices.

The results have practical implication, in particular. They are expected to help managers and workers to better comprehend KM practices in BRIC countries or even suggest new KM practices in the business.

The main discussion of this paper brings together a large range of KM practices applied in BRIC, addressing similarities and differences between KM deployments.

To improve production efficiency, industrial robots are expected to replace humans to complete the traditional manual operation on grasping, sorting and assembling workpieces. These implementations are closely related to the accuracy of workpiece location. However, workpiece location methods based on conventional machine vision are sensitive to the factors such as light intensity and surface roughness. To enhance the robustness of the workpiece location method and improve the location accuracy, a workpiece location algorithm based on improved Single Shot MultiBox Detector (SSD) is proposed.

The proposed algorithm integrates a weighted bi-directional feature pyramid network into SSD. A feature fusion architecture is structured by the combination of low-resolution, strong semantic features and high-resolution, weak semantic features. The architecture is built through a top-down pathway, bottom-up pathway, lateral connections and skip connections. To avoid treating all features equally, learnable weights are introduced into each feature layer to characterize its importance. More detailed information from the low-level layers is injected into the high-level layers, which could improve the accuracy of workpiece location.

It is found that the maximum location error at the center point calculated from the proposed algorithm is decreased by more than 22% compared with that of the SSD algorithm. Besides, the average location error evolves a decrease by at least 5%. In the trajectory prediction experiment of the workpiece center point, the results of the proposed algorithm demonstrate that the average location error is below 0.13 mm and the maximum error is no more than 0.23 mm.

In this work, a workpiece location algorithm based on improved SSD is developed to extract the center point of the workpiece. The results demonstrate that the proposed algorithm is beneficial for workpiece location. The proposed algorithm can be readily used in a variety of workpieces or adapted to other similar tasks.

Existing research focuses on the pension systems and reforms in China from a macro-level and financial perspective. The expectations of mid-life Chinese people regarding their retirement and pensions have been ignored to date, and this research set out to address this lacuna.

The application of qualitative research methods is relatively novel in Chinese social science. As a grounded theory (GT) study, the research reported here deployed semi-structured interviews to investigate middle-aged Chinese women's and men's perceptions of their pensions and retirement. In total, 36 interviews were conducted, following the constructivist GT method.

The data point to disparities between the choices and perceptions of individuals on the one hand and the official assumptions underlying the current pension regime on the other hand. Research participants had varying interpretations of the inequality in retirement incomes in China, the main division being between enterprise workers and public-sector employees.

Although there are in principle rigidly fixed retirement ages for men and women in contemporary China, the phenomena of early retirement and working post-retirement are increasing. There are trade-offs between work/retirement and family needs, which influence the choices of middle-aged citizens. Retirement pathways are increasingly individualised, reflecting broader patterns of individualisation and inequality in China.