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How to free the potential power of the capital market while simultaneously protecting the investors is critical in equity-based crowdfunding. To realize these goals, the purpose of this study was to investigate the value of information disclosure and leader-follower mechanism which have been widely adopted by crowdfunding platforms.

Based on the Elaboration Likelihood Model (ELM), a research framework was developed. Then, the authors conducted an in-depth exploratory empirical study of Dajiatou (www.dajiatou.com) which is a typical equity-based crowdfunding service provider in China. Independent-samples t-test and linear regression were used to uncover the value of project information disclosure and the lead investor in terms of fundraising performance improvement.

First, the quality of entrepreneurial team information, especially the ratio of full-time staff, staff number and enterprise business age, significantly improve fundraising performance. Second, entrepreneurs’ behaviors, including project updates and project video, play important roles in crowdfunding. Third, whether or not the project has a lead investor, leader’s credibility information and his/her advocacy behaviors – percentage of their investment, identity certification, investment experience and comments for projects – are important factors affecting fundraising performance.

The authors are one of the firsts to apply ELM to investigate the effects of diverse information on fundraising performance in equity-based crowdfunding. The value of lead investor which has been ignored in prior research was studied through second-hand data.

First, an equity-based crowdfunding platform should request the entrepreneur to disclose project quality-related information with more details. Second, crowdfunding platforms should set a high qualifications level for lead investor, and limit the lead investor’s committed percentage in a specific project.

This paper extended the research in crowdfunding by uncovering the value of information disclosure and lead investor based on ELM theory.

The purpose of this study is to address a significant gap in the understanding of entrepreneurship at the microfoundation level. It focuses on how individual entrepreneurs, specifically Hongbang entrepreneurs in China from 1896 to 1949, shape and transform their contexts. The aim is to provide a deeper understanding of the mechanisms that facilitate entrepreneurial success.

The study adopts a microhistorical approach, investigating the case of Hongbang entrepreneurs in China during 1896-1949. It involves an in-depth examination of historical records to explore the strategic interactions between these entrepreneurs and core stakeholders such as consumers, financial intermediaries, government regulators, and human resources. The research methodology emphasizes a process-oriented view, examining the evolution of personalized networks into extensive connections.

The research reveals that Hongbang entrepreneurs successfully reshaped their unfavorable embedded contexts by strategically collaborating with key stakeholders. They influenced consumer tastes, allied with financial intermediaries, negotiated with governments on regulation policies, and developed human resource stocks. The transformation was facilitated by the evolution of their networks from personalized to extensive connections. These findings highlight the localized strategies such as cronyism in resource acquisition within China’s private property development industry.

This study contributes to the field by offering insights into entrepreneurial contextualization and networking. It sheds light on the complex interplay between entrepreneurs and their contexts, providing a nuanced understanding of localized strategies in the Chinese context. The findings add value to the discourse on entrepreneurship by elucidating the strategic and processual acts through which entrepreneurs engage with stakeholders and reshape their environments.

This paper aims to resolve issues of the traditional artificial potential field method, such as falling into local minima, low success rate and lack of ability to sense the obstacle shapes in the planning process.

In this paper, an improved artificial potential field method is proposed, where the object can leave the local minima point, where the algorithm falls into, while it avoids the obstacle, following a shorter feasible path along the repulsive equipotential surface, which is locally optimized. The whole obstacle avoidance process is based on the improved artificial potential field method, applied during the mechanical arm path planning action, along the motion from the starting point to the target point.

Simulation results show that the algorithm in this paper can effectively perceive the obstacle shape in all the selected cases and can effectively shorten the distance of the planned path by 13%–41% with significantly higher planning efficiency compared with the improved artificial potential field method based on rapidly-exploring random tree. The experimental results show that the improved artificial potential field method can effectively plan a smooth collision-free path for the object, based on an algorithm with good environmental adaptability.

An improved artificial potential field method is proposed for optimized obstacle avoidance path planning of a mechanical arm in three-dimensional space. This new approach aims to resolve issues of the traditional artificial potential field method, such as falling into local minima, low success rate and lack of ability to sense the obstacle shapes in the planning process.

The purpose of this paper is to propose a novel jump control method based on Two Mass Spring Damp Inverted Pendulum (TMS-DIP) model, which makes the third generation of hydraulic driven wheel-legged robot prototype (WLR-3P) achieve stable jumping.

First, according to the configuration of the WLR, a TMS-DIP model is proposed to simplify the dynamic model of the robot. Then the jumping process is divided into four stages: thrust, ascent, descent and compression, and each stage is modeled and solved independently based on TMS-DIP model. Through WLR-3P kinematics, the trajectory of the upper and lower centroids of the TMS-DIP model can be mapped to the joint space of the robot. The corresponding control strategies are proposed for jumping height, landing buffer, jumping attitude and robotic balance, so as to realize the stable jump control of the WLR.

The TMS-DIP model proposed in this paper can simplify the WLR dynamic model and provide a simple and effective tool for the jumping trajectory planning of the robot. The proposed approach is suitable for hydraulic WLR jumping control. The performance of the proposed wheel-legged jump method was verified by experiments on WLR-3P.

This work provides an effective model (TMS-DIP) for the jump control of WLR-3P. The results showed that the number of landing shock (twice) and the pitch angle fluctuation range (0.44 rad) of center of mass of the jump control method based on TMS-DIP model are smaller than those based on spring-loaded inverted pendulum model. Therefore, the TMS-DIP model makes the jumping process of WLR more stable and gentler.

This paper aims to propose a method to solve the problem of localization and mapping of a two-wheeled inverted pendulum (TWIP) robot on the ground using the Stereo–inertial measurement unit (IMU) system. This method reparametrizes the pose according to the motion characteristics of TWIP and considers the impact of uneven ground on vision and IMU, which is more adaptable to the real environment.

When TWIP moves, it is constrained by the ground and swings back and forth to maintain balance. Therefore, the authors parameterize the robot pose as SE(2) pose plus pitch according to the motion characteristics of TWIP. However, the authors do not omit disturbances in other directions but perform error modeling, which is integrated into the visual constraints and IMU pre-integration constraints as an error term. Finally, the authors analyze the influence of the error term on the vision and IMU constraints during the optimization process. Compared to traditional algorithms, the algorithm is simpler and better adapt to the real environment.

The results of indoor and outdoor experiments show that, for the TWIP robot, the method has better positioning accuracy and robustness compared with the state-of-the-art.

The algorithm in this paper is proposed for the localization and mapping of a TWIP robot. Different from the traditional positioning method on SE(3), this paper parameterizes the robot pose as SE(2) pose plus pitch according to the motion of TWIP and the motion disturbances in other directions are integrated into visual constraints and IMU pre-integration constraints as error terms, which simplifies the optimization parameters, better adapts to the real environment and improves the accuracy of positioning.

One of the development trends of robots is to enable robots to have the ability of anthropomorphic manipulation. Grasping is the first step of manipulation. For mobile manipulator robots, grasping a target during the movement process is extremely challenging, which requires the robots to make rapid motion planning for arms under uncertain dynamic disturbances. However, there are many situations require robots to grasp a target quickly while they move, such as emergency rescue. The purpose of this paper is to propose a method for target dynamic grasping during the movement of a robot.

An off-line learning from demonstrations method is applied to learn a basic reach model for arm and a motion model for fingers. An on-line dynamic adjustment method of arm speed for active and passive grasping mode is designed.

The experimental results of the robot movement on flat, slope and speed bumps ground show that the proposed method can effectively solve the problem of fast planning under uncertain disturbances caused by robot movement. The method performs well in the task of target dynamic grasping during the robot movement.

The main contribution of this paper is to propose a method to solve the problem of rapid motion planning of the robot arm under uncertain disturbances while the robot is grasping a target in the process of robot movement. The proposed method significantly improves the grasping efficiency of the robot in emergency situations. Experimental results show that the proposed method can effectively solve the problem.

To propose a new investment-income valuation model by real options approach (ROA) for old community renewal (OCR) projects, which could help the government attract private capital's participation.

The new model is proposed by identifying the types of options private capital has in the OCR project, selecting the option model most suitable for private capital investment decisions, improving the valuation model through the triangular fuzzy numbers to take into account the uncertainty and flexibility, and demonstrating the feasibility of the calculation model through an actual OCR project case.

The new model can valuate OCR projects more accurately based on considering uncertainty and flexibility, compared with conventional methods that often underestimate the value of OCR projects.

The investment-income of OCR projects shall be re-valuated from the lens of real options, which could help reveal more real benefits beyond the capital growth of OCR projects, enable the government to attract private capital's investment in OCR, and alleviate government fiscal pressure.

The proposed OCR-oriented investment-income valuation model systematically analyzes the applicability of real option value (ROV) to OCR projects, innovatively integrates the ROV and the net present value (NPV) as expanded net present value (ENPV), and accurately evaluate real benefits in comparison with existing models. Furthermore, the newly proposed model holds the potential to be transferred to various social welfare projects as a tool to attract private capital's participation.

The purpose of this paper is to improve control performance and safety of a real two-wheeled inverted pendulum (TWIP) robot by dealing with model uncertainty and motion restriction simultaneously, which can be extended to other TWIP robotic systems.

The inequality of lumped model uncertainty boundary is derived from original TWIP dynamics. Several motion restriction conditions are derived considering zero dynamics, centripedal force, ground friction condition, posture stability, control torque limitation and so on. Sliding-mode control (SMC) and model predictive control (MPC) are separately adopted to design controllers for longitudinal and rotational motion, while taking model uncertainty into account. The reference value of the moving velocity and acceleration, delivered to the designed controller, should be restricted in a specified range, limited by motion restrictions, to keep safe.

The cancelation of model uncertainty commonly existing in real system can improve control performance. The motion commands play an important role in maintaining safety and reliability of TWIP, which can be ensured by the proposed motion restriction to avoid potential movement failure, such as slipping, lateral tipping over because of turning and large fluctuation of body.

An inequation of lumped model uncertainty boundary incorporating comprehensive errors and uncertainties of system is derived and elaborately calculated to determine the switching coefficients of SMC. The motion restrictions for TWIP robot moving in 3D are derived and used to impose constraints on reference trajectory to avoid possible instability or failure of movement.

In the context of fixed-wing aircraft wing assembly, there is a need for a rapid and precise measurement technique to determine the center distance between two double-hole components. This paper aims to propose an optical-based spatial point distance measurement technique using the spatial triangulation method. The purpose of this paper is to design a specialized measurement system, specifically a spherically mounted retroreflector nest (SMR nest), equipped with two laser displacement sensors and a rotary encoder as the core to achieve accurate distance measurements between the double holes.

To develop an efficient and accurate measurement system, the paper uses a combination of laser displacement sensors and a rotary encoder within the SMR nest. The system is designed, implemented and tested to meet the requirements of precise distance measurement. Software and hardware components have been developed and integrated for validation.

The optical-based distance measurement system achieves high precision at 0.04 mm and repeatability at 0.02 mm within a range of 412.084 mm to 1,590.591 mm. These results validate its suitability for efficient assembly processes, eliminating repetitive errors in aircraft wing assembly.

This paper proposes an optical-based spatial point distance measurement technique, as well as a unique design of a SMR nest and the introduction of two novel calibration techniques, all of which are validated by the developed software and hardware platform.

The purpose of this study is to study the quantitative evaluation method of contact wire cracks by analyzing the changing law of eddy current signal characteristics under different cracks of contact wire of high-speed railway so as to provide a new way of thinking and method for the detection of contact wire injuries of high-speed railway.

Based on the principle of eddy current detection and the specification parameters of high-speed railway contact wires in China, a finite element model for eddy current testing of contact wires was established to explore the variation patterns of crack signal characteristics in numerical simulation. A crack detection system based on eddy current detection was built, and eddy current detection voltage data was obtained for cracks of different depths and widths. By analyzing the variation law of eddy current signals, characteristic parameters were obtained and a quantitative evaluation model for crack width and depth was established based on the back propagation (BP) neural network.

Numerical simulation and experimental detection of eddy current signal change rule is basically consistent, based on the law of the selected characteristics of the parameters in the BP neural network crack quantitative evaluation model also has a certain degree of effectiveness and reliability. BP neural network training results show that the classification accuracy for different widths and depths of the classification is 100 and 85.71%, respectively, and can be effectively realized on the high-speed railway contact line cracks of the quantitative evaluation classification.

This study establishes a new type of high-speed railway contact wire crack detection and identification method, which provides a new technical means for high-speed railway contact wire injury detection. The study of eddy current characteristic law and quantitative evaluation model for different cracks in contact line has important academic value and practical significance, and it has certain guiding significance for the detection technology of contact line in high-speed railway.