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In practical workshop production process, there are many production emergencies, e.g. new manufacturing tasks, facilities failure and tasks change. On one hand, it results in poor timeliness and reliability of real-time production data collection, acquisition and transmission; on the other hand, it increases the difficulty of real-time data tracking and monitoring. This paper aims to develop a novel RFID-based tracking and monitoring approach of real-time data in production workshop (TM_rfid) to solve them.

At first, a three-layer model of real-time data based on RFID has been constructed, which contains RFID-based integrated acquisition center; “RFID & Cloud-service-rules”-based calculation and analysis center; and “RFID & Ontology-knowledge-base”-based monitoring and scheduling center. Then, a targeted analysis and evaluation method of TM_rfid with feasibility, quality and performance has been proposed. Finally, a prototype platform of a textile machinery manufacturing enterprise has been built to verify the effective of TM_rfid.

The effectiveness of TM_rfid is verified by applying two groups of actual experimental data from the case enterprise, the results show that TM_rfid can promote the efficiency, reliability and feasibility of tacking and monitoring of real-time data in production workshop.

RFID-based tracking and monitoring approach of real-time data in production workshop has been developed to solve the data information transmission and sharing problem. Three analysis and evaluation approaches have been introduced to solve the un-standardized evaluation problem of RFID application. A prototype platform of a textile machinery manufacturing enterprise has been constructed.

The purpose of this paper is to propose a binocular visual odometry algorithm based on the Random Sample Consensus (RANSAC) in visual navigation systems.

The authors propose a novel binocular visual odometry algorithm based on features from accelerated segment test (FAST) extractor and an improved matching method based on the RANSAC. Firstly, features are detected by utilizing the FAST extractor. Secondly, the detected features are roughly matched by utilizing the distance ration of the nearest neighbor and the second nearest neighbor. Finally, wrong matched feature pairs are removed by using the RANSAC method to reduce the interference of error matchings.

The performance of this new algorithm has been examined by an actual experiment data. The results shown that not only the robustness of feature detection and matching can be enhanced but also the positioning error can be significantly reduced by utilizing this novel binocular visual odometry algorithm. The feasibility and effectiveness of the proposed matching method and the improved binocular visual odometry algorithm were also verified in this paper.

This paper presents an improved binocular visual odometry algorithm which has been tested by real data. This algorithm can be used for outdoor vehicle navigation.

A binocular visual odometer algorithm based on FAST extractor and RANSAC methods is proposed to improve the positioning accuracy and robustness. Experiment results have verified the effectiveness of the present visual odometer algorithm.

To improve the efficiency of end-of-life product’s disassembly process, this paper aims to propose a disassembly sequence planning (DSP) method to reduce additional efforts of removing parts when considering the changes of disassembly directions and tools.

The methodology has three parts. First, a disassembly hybrid graph model (DHGM) was adopted to represent disassembly operations and their precedence relations. After representing the problem as DHGM, a new integer programming model was suggested for the objective of minimizing the total disassembly time. The objective takes into account several criteria such as disassembly tools change and the change of disassembly directions. Finally, a novel hybrid approach with a chaotic mapping-based hybrid algorithm of artificial fish swarm algorithm (AFSA) and genetic algorithm (GA) was developed to find an optimal or near-optimal disassembly sequence.

Numerical experiment with case study on end-of-life product disassembly planning has been carried out to demonstrate the effectiveness of the designed criteria and the results exhibited that the developed algorithm performs better than other relevant algorithms.

More complex case studies for DSP problems will be introduced. The performance of the CAAFG algorithm can be enhanced by improving the design of AFSA and GA by combining them with other search techniques.

DSP of an internal gear hydraulic pump is analyzed to investigate the accuracy and efficiency of the proposed method.

This paper proposes a novel CAAFG algorithm for solving DSP problems. The implemented tool generates a feasible optimal solution and the considered criteria can help the planer obtain satisfactory results.

Over the past two decades, China’s outward foreign direct investment (OFDI) has risen remarkably. Whether such an increase affects the Chinese export diversification (ED) is a significant issue that has surprisingly remained unaddressed. This study aims to explain this issue that how OFDI plays a vital role in symmetric and asymmetric effects on its ED.

The authors introduce a robust nonlinear autoregressive distributed lag (NARDL) model. Ironically, the purpose of this study is to analyze the symmetric and asymmetric effect of OFDI on ED.

The authors propose that growing OFDI would be more advantageous to China, rather than the policies of contraction. Therefore, the study provides valuable policy insights to consider the long-run asymmetric momentum given to ED by China’s OFDI.

The results of this study may seem to be an important newsletter for further policy discussion on how China can catch up on the benefits of ED through OFDI.

The purpose of this paper is to investigate the relations between the digital transformation of manufacturing enterprises and enterprise innovation to provide inspiration for promoting the digitization and upgrading of China's manufacturing industry and facilitate enterprises' innovative development.

Based on a panel data of 584 listed manufacturing companies in China from 2016 to 2020, and using a fixed effects approach, this paper empirically examines the impact of digital transformation on corporate innovation in manufacturing enterprises, as well as examining the influential mechanisms and heterogeneity.

The research shows that the digital transformation of manufacturing enterprises has effectively improved the innovation capacity of enterprises and verifies different situations through heterogeneity. At the same time, the research clarifies the mediating effect of the innovation investment mechanism, cost control mechanism, and profit guarantee mechanism on the relations between the digital transformation of manufacturing enterprises and the innovation capacity of enterprises.

Based on Chinese manufacturing enterprise samples, this paper empirically tests the influential mechanism of digital transformation on the innovation capability of manufacturing enterprises, therefore clarifying the main mediating effects. This paper could provide inspiration for manufacturing companies to make good use of digital transformation rules according to their own situation and improve their innovation capabilities, thereby enhancing competitiveness in the digital economy era.

China's Belt and Road Initiative (BRI) is the most ambitious investment strategy for infrastructural development belonging to the significant potential for stimulating regional economic growth in Asia, Europe and Africa. This study aims to investigate the impact of infrastructure on spurring inward foreign direct investment (FDI) within the purview of human capital, GDP per capita, foreign aid, trade, domestic investment, population and institutional quality in BRI countries.

In doing so, the authors analyze panel data from 2000 to 2019 within the framework of the system generalized method of movement (GMM) approach for 66 BRI countries from Europe, Asia, Africa and the Middle East.

The investigated results demonstrate that aggregate and disaggregate infrastructure indices, e.g. transport, telecommunications, financial and energy infrastructures, are the driving forces in attracting foreign direct investment (FDI) in the BRI countries. In addition, control variables (i.e. institutional quality, human capital, trade, domestic investment, foreign aid and GDP per capita) play an essential role in spurring FDI inflows.

The authors’ study uniquely investigates both the pre- (2000–2012) and post- (2013–2019) BRI scenarios using the aggregate and disaggregate infrastructural components from the perspectives of full and clustered sample regions, such as Asia, Europe, Africa and the Middle East. The study provides several policy implications.

This paper sets out to discuss white‐collar crime and fraud in China and to draw implications for Western businesses wishing to enter the Chinese market.

The paper provides examples of recent frauds committed in China and also provides a brief review of the literature. It traces the development of China's economy, describing China's modern‐day economy, and also looks at cultural issues and differences between Western and Chinese attitudes.

Western businesses planning to enter the Chinese market need to do their due diligence before committing resources. What works in Western society may not work in another culture, like China's. However, gaining an understanding of the culture and general way of life will go a long way towards laying the groundwork for success.

Additional focus should be placed on examining how cultural differences affect judgments and behaviors.

From a practical standpoint, the paper provides insights into possible areas of disagreement between employees from different cultures that can result from their divergent opinions about individuals' responsibility for fraudulent acts.

In the new development stage of comprehensively building a socialist modern state, it is imperative to adhere to the guidance of Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era, comprehensively summarize China's practical experiences in economic development, strengthen research on capital issues, construct theories of socialist political economy with Chinese characteristics regarding capital and provide scientific theoretical guidance for further promoting the positive role of various types of capital while preventing and overcoming their negative effects, which is a major theoretical issue and a glorious task for the theoretical and economic circles in China.

From the perspective of Marx's theory on capital and historical development, modern capital represents the organizational mode of socialized mass production and market economy. It serves as both the economic foundation of bourgeois society and a tool for socialist economic development.

The market economy represents an inevitable historical stage and form of socialist economic development, necessitating the adoption of capital as an organizational form within socialist economies.

The utilization of capital to advance a socialist economy is a remarkable achievement by the CPC and Chinese people, representing a significant innovation in both theory and practice. The role of capital is inherently dual under any social condition. In the context of a socialist system, capital can play a positive role effectively, and its behavior can be guided and regulated correctly to curb its negative or even destructive impact.

Intelligent and connected vehicle technology is in the ascendant. High-level autonomous driving places more stringent requirements on the accuracy and reliability of environmental perception. Existing research works on multitarget tracking based on multisensor fusion mostly focuses on the vehicle perspective, but limited by the principal defects of the vehicle sensor platform, it is difficult to comprehensively and accurately describe the surrounding environment information.

In this paper, a multitarget tracking method based on roadside multisensor fusion is proposed, including a multisensor fusion method based on measurement noise adaptive Kalman filtering, a global nearest neighbor data association method based on adaptive tracking gate, and a Track life cycle management method based on M/N logic rules.

Compared with fixed-size tracking gates, the adaptive tracking gates proposed in this paper can comprehensively improve the data association performance in the multitarget tracking process. Compared with single sensor measurement, the proposed method improves the position estimation accuracy by 13.5% and the velocity estimation accuracy by 22.2%. Compared with the control method, the proposed method improves the position estimation accuracy by 23.8% and the velocity estimation accuracy by 8.9%.

A multisensor fusion method with adaptive Kalman filtering of measurement noise is proposed to realize the adaptive adjustment of measurement noise. A global nearest neighbor data association method based on adaptive tracking gate is proposed to realize the adaptive adjustment of the tracking gate.