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To solve problems of low intelligence and poor robustness of traditional navigation systems, the purpose of this paper is to propose a brain-inspired localization method of the unmanned aerial vehicle (UAV).

First, the yaw angle of the UAV is obtained by modeling head direction cells with one-dimension continuous attractor neural network (1 D-CANN) and then inputs into 3D grid cells. After that, the motion information of the UAV is encoded as the firing of 3 D grid cells using 3 D-CANN. Finally, the current position of the UAV can be decoded from the neuron firing through the period-adic method.

Simulation results suggest that continuous yaw and position information can be generated from the conjunctive model of head direction cells and grid cells.

The proposed period-adic cell decoding method can provide a UAV with the 3 D position, which is more intelligent and robust than traditional navigation methods.

The purpose of this paper is to propose a seamless autonomous navigation method based on the motion constraint of the mobile robot, which is able to meet the practical need of maintaining the navigation accuracy during global positioning system (GPS) outages.

The seamless method uses the motion constraint of the mobile robot to establish the filter model of the system, in which the virtual observation about the speed is used to overcome the shortage of the navigation accuracy during GPS outages. The corresponding motion constraint model of the mobile robot is established. The proposed seamless navigation scheme includes two parts: the micro inertial navigation system (MINS)/GPS-integrated filter model and the motion constraint filter model. When the satellite signals are good, the system works on the MINS/GPS-integrated mode. If some obstacles block the GPS signals, the motion constraint measurement equation will be effective so as to improve the navigation accuracy of the mobile robot.

Three different vehicle tests of the mobile robot show that the seamless navigation method can overcome the shortage of the navigation accuracy during GPS outages, so as to improve the navigation performance in practical applications.

A seamless navigation system based on the motion constraint of the mobile robot is proposed to overcome the shortage of the navigation accuracy during GPS outages, thus improving the adaptability of the robot navigation.

The Embedded GPS/INS System (EGI) has been used more widely as central navigation equipment of aircraft. For certain cases needing high attitude accuracy, star sensor can be integrated with EGI to improve attitude performance. Since the filtering‐correction loop has already built in finished EGI product, centralized or federated Kalman filter is not applicable for integrating EGI with star sensor; it is a challenge to design multi‐sensor information fusion algorithm suitable for this situation. The purpose of this paper is to present a double‐layer fusion scheme and algorithms to meet the practical need of constructing integrated multi‐sensor navigation system by star sensor assisting finished EGI unit.

The alternate fusion algorithms for asynchronous measurements and the sequential fusion algorithms for synchronous measurements are presented. By combining alternate filtering and sequential filtering algorithms, a kind of double‐layer fusion algorithms for multi‐sensors is proposed and validated by semi‐physical test in this paper.

The double‐layer fusion algorithms represent a filtering strategy for multiple non‐identical parallel sensors to assist INS, while the independent estimation‐correction loop in EGI is still maintained. It has significant benefits in updating original navigation system by integrating new sensors.

The approach described in this paper can be used in designing similar multi‐sensor information fusion navigation system composed by EGI and various kinds of sensors, so as to improve the navigation performance.

Compared with conventional approach, in the situation that centralized and federated Kalman filter are not applicable, the double‐layer fusion scheme and algorithms give an external filtering strategy for measurements of finished EGI unit and star sensors.

Conservation of green space is crucial to the sustainable urban development of China. Nanjing is a central city in the Yangtze River Delta cluster in eastern China. Owing to urbanization, the green spaces in this city have been affected significantly in terms of their scale and structure. Assessing such changes can provide a basis for environmental protection measures and sustainable development. Using Landsat remote-sensing image data from 1998 and 2007, we constructed a distribution map of the patches of green spaces in Nanjing, and analyzed and assessed the changes in scale and spatial layout of the green spaces using various landscape metrics including CA, PLAND, PD, MPS, LPI, NP, PD, TE, ED, MPI, and LSI. Coinciding with a sharp increase in urban population, the area of green spaces in Nanjing decreased by 27.06% between 1998 and 2007. The patches of green space increased by 39%, and the average area per patch decreased by about 47.52%. Green space patches were found to be unevenly distributed among the districts of Nanjing. In urban areas, significant numbers of such patches were found primarily in various types of parks, while in suburban areas, they were concentrated mainly in the hilly forestlands. Green spaces exhibited tendencies towards fragmentation, miniaturization, and discretization.

This study aims to explore the spatial distribution characteristics and spactial reciprocity between industrial parks (IPs) and vocational education parks (VEPs): agglomeration density, functional matching, spatial organization efficiency, as well as space intensive utility. To achieve this objective, IPs and VEPs in urban centers of Jiangsu Province are selected as the objects of the study. First, spatial analysis of thermodynamic diagrams is employed in this study to qualitatively analyze the evolutionary characteristics of the spatial distribution of IPs and VEPs to explore the spatial aggregation characteristics of their clustering, integration, and comprehensive crossover. Second, a horizontal comparison of the data and indexes concerned reveals that areas with high agglomeration and functional matching exhibit a sound spatial reciprocity. Third, this study crystallizes the four structural prototpye paradigms formed during the reciprocity evolution between IPs and VEPs; it compares spatial organization efficiency, with the agglomeration–core structure ranking first, followed by the circle–core structure. Finally, SPSS is used to analyze the space intensive utility in order to verify the conclusions of qualitative analysis. The findings can comprehensively explain the regularities of the spatial distribution and reciprocity between IPs and VEPs. The findngs can also elucidate the design of regional industrial development and educational programs.

Influencer marketing mediated by social media is prevalent in social commerce. Micro-, meso- and macro-influencers all play an irreplaceable role in marketing. The purpose of this paper is to explore how companies with limited budgets choose influencers according to products' various levels of brand familiarity.

This study constructs an evolutionary game model of influencer marketing based on evolutionary game theory on complex networks. This model initiates various networks to demonstrate how influencers disseminate information and constructs update mechanisms to depict how individuals react to this information based on individuals' information utility and friends' strategies.

Simulation results suggest that companies should invest more in macro-influencers than in meso-influencers, however investing all in macro-influencers is not a good choice. The investment in meso-influencers will increase as brand familiarity decreases, whereas it will not exceed investment in macro-influencers. Furthermore, the accumulation of micro-influencers can accelerate the marketing process.

This study examines the combined effects of micro-influencers, meso-influencers and macro-influencers in marketing by simulating the marketing process initiated by influencers on social media.

Presently, 6 Degree of Freedom (6DOF) visual pose measurement methods enjoy popularity in the industrial sector. However, challenges persist in accurately measuring the visual pose of blank and rough metal casts. Therefore, this paper introduces a 6DOF pose measurement method utilizing stereo vision, and aims to the 6DOF pose measurement of blank and rough metal casts.

This paper studies the 6DOF pose measurement of metal casts from three aspects: sample enhancement of industrial objects, optimization of detector and attention mechanism. Virtual reality technology is used for sample enhancement of metal casts, which solves the problem of large-scale sample sampling in industrial application. The method also includes a novel deep learning detector that uses multiple key points on the object surface as regression objects to detect industrial objects with rotation characteristics. By introducing a mixed paths attention module, the detection accuracy of the detector and the convergence speed of the training are improved.

The experimental results show that the proposed method has a better detection effect for metal casts with smaller size scaling and rotation characteristics.

A method for 6DOF pose measurement of industrial objects is proposed, which realizes the pose measurement and grasping of metal blanks and rough machined casts by industrial robots.

The purpose of this paper is to explore financial quality problems, based on the dynamics of the ownership structure, in the privatization process to clarify the internal relation among the ownership’s attribution of the commercial mixed ownership company, the company’s performance and its financial relationships. This paper also examines the mixed ownership enterprise’s potential problems during the development process.

Adopting the single case study method, the authors selected the mixed ownership public company Hubei Sanxia New Building Materials Co., Ltd. (stock code: 600293) to explore, from a privatization perspective, the impact of mixed ownership on financial quality.

The study found that Sanxia experienced tight cash flow and heavy debt burdens due to the privatization and that its controlling shareholders used non-operating income to support Sanxia, thus characterizing the dual role of “the grabbing hand” and “the helping hand.” Sanxia’s privatization process highlighted the volatility of performance, the exception of monetary funds and the existence of accounting fraud rather than the prosperous development of the capital combination.

These findings provided case support that privatization negatively affects the financial quality of the company. Previous studies have indicated that there should be greater focus more on the issue that state-owned shares rebound during the process of privatization and that, with respect to commercial mixed ownership reform of state-owned enterprises, such reform must avoid the passive transfer of corporate control, ensure the fairness of the related transactions, prevent the loss of state-owned assets and preclude the controlling shareholders from seizing interests of listed companies.

With the analysis of the causes of corruption, this study aims to investigate specific anti-corruption measures that can be implemented to reform the political system and the social climate of China.

This study examines 97 severe corruption cases of high-ranking officials in China, which occurred between 2012 and 2015. As this insinuates that both institutional and social corruption are major problems in China, the analysis delves into multiple facts of corruption, including different types, four primary underlying causes, and suggestions regarding the implementation of three significant governmental shifts that focus on investigation, prevention tactics and legal regulations.

China’s corruption is not only individual-based but also it has developed into institutional corruption and social corruption. Besides human nature and instinct, the causes of corruption can be organised into four categories, namely, social customs, social transitions, institutional designs and institutional operations. For the removed high-ranking officials, the formation of interest chains was an important underlying cause behind their corruption.

This study makes a significant contribution to the literature because this study provides a well-rounded approach to a complex issue by highlighting the significance of democracy and the rule of law as ways to regulate human behaviour to combat future corruption.

In 2017, the Chinese Super League (CSL), the first professional football division in the People’s Republic of China (PRC), became the highest-spending league in the international players’ transfer market, with a total spending of €377m. Moreover, the government of the PRC is backing the CSL with an ambitious football plan. Therefore, the purpose of this paper is to examine the governance of the CSL by questioning the organisational viability of the league.

In addition to the relevant international literature, this study is based on 14 recent scholarly articles published in Mandarin from 2013 to 2018 to reflect the national academic debate. Moreover, website research on all CSL clubs has been conducted. The institutional analysis follows the integrative change model of Cunningham (2002) complemented by agency and bureaucracy theory.

The CSL still faces substantial governance problems caused by the divergence of goal setting, organisational inefficiencies and compliance issues. The organisational change is notably constrained by internal competitive value commitments and external power dependency.

The institutional findings on the CSL provide a starting point for empirical studies. The approach contributes to the theory of sport governance processes.

The material and insights are informative for decision makers to evaluate the competitiveness of the CSL.

This paper is the first international in-depth analysis of the governance of the CSL using the body of knowledge published in Mandarin.