Search results

The purpose of this paper is to apply virtual agonist–antagonist mechanisms (VAAMs) to robot joint control allowing for muscle-like functions and variably compliant joint motions. Biological muscles of animals have a surprising variety of functions, i.e. struts, springs and brakes.

Each joint is driven by a pair of VAAMs (i.e. passive components). The muscle-like functions as well as the variable joint compliance are simply achieved by tuning the damping coefficient of the VAAM.

With the VAAM, variably compliant joint motions can be produced without mechanically bulky and complex mechanisms or complex force/toque sensing at each joint. Moreover, through tuning the damping coefficient of the VAAM, the functions of the VAAM are comparable to biological muscles.

The model (i.e. VAAM) provides a way forward to emulate muscle-like functions that are comparable to those found in physiological experiments of biological muscles. Based on these muscle-like functions, the robotic joints can easily achieve variable compliance that does not require complex physical components or torque sensing systems, thereby capable of implementing the model on small-legged robots driven by, for example, standard servo motors. Thus, the VAAM minimizes hardware and reduces system complexity. From this point of view, the model opens up another way of simulating muscle behaviors on artificial machines.

The VAAM can be applied to produce variable compliant motions of a high degree-of-freedom robot. Only relying on force sensing at the end effector, this application is easily achieved by changing coefficients of the VAAM. Therefore, the VAAM can reduce economic cost on mechanical and sensing components of the robot, compared to traditional methods (e.g. artificial muscles).

The purpose of this paper is to overcome the shortcoming that discrete variable structure control (VSC) system trajectory oscillates in a neighborhood of the origin.

Among all the proposed reaching laws, W. Gao's theory is most perfect. It makes great progress in revealing the motion mechanism of discrete‐time VSC systems. However, it has an obvious defect, i.e. the system trajectory oscillates in a neighborhood of the origin rather than converges to the origin. So, a new reaching law named variable rate reaching law to which the stability at the origin can be expected is proposed. The special feature of this new reaching law is that it is directly proportional to the norm of the state vector and can result in a sector‐shaped switching region. On the basis of analyzing the characteristic of the variable rate and the conventional reaching laws, a new combined control algorithm that discards the shortcomings of the two reaching laws and carries on their merits is formed, so satisfactory control performance can be achieved.

A new combined reaching law control algorithm, which uses the exponential rate reaching law in the reaching mode and in the front phase of the sliding mode, and uses the variable rate reaching law in the back phase of the sliding mode and in the steady‐state mode, is formed.

The paper is a very useful reference for control system designers.

The new control strategy is applied to the controller design for a brushless DC servomotor and good control performance is obtained.

With frequent floods occurring, and the fast economic development in China, attention must be paid to flood prevention, water supply, and forecasting precision. In particular, mid‐ and long‐term runoff prediction is being paid more and more attention by researchers, and it is also the most difficult problem to solve. The purpose of this paper is to apply chaos phase space theory to forecast river run off.

Because the hydrologic system is a complicated huge system, there exist high non‐linear characteristics in the space‐time change of hydrologic factors. According to theory of chaotic phase space, the paper established four models of the single‐point, multi‐point, lineal, and three‐parameter D(m,τ,k) models, they have stronger non‐linear mapping function and much more information in the time series than traditional ways.

The results of calculation show that the models are highly effective and worthy of popularization and application. It is reasonable and superior to use these models in mid‐ and long‐term hydrologic prediction.

The method cannot reduce or eliminate the un‐prediction parts caused by the inner random factors, such as the noise information of the observed data.

The models are applied in the long‐term runoff prediction of Baishan reservoir.

The new approach of hydrology forecasting due to the theory of chaotic phase space. The paper is aimed at hydrology forecasting researches and engineers, especially those who dealt with the mid‐ and long‐term prediction.

The purpose of this paper is to analyze the effects of private investor's fair preference on the governmental compensation mechanism based on the uncertainty of income for the public-private-partnership (PPP) project.

Based on the governmental dilemma for the compensation of PPP project, a generalized compensation contract is designed by the combination of compensation before the event and compensation after the event. Then the private investor's claimed concession profit is taken as its fair reference point according to the idea of the BO model, and its fair utility function is established by improving the FS model. Thus the master-slave counter measure game is applied to conduct the behavior modeling for the governmental compensation contract design.

By analyzing the model given in this paper, some conclusions are obtained. First, the governmental optimal compensation contract is fair incentive for the private investor. Second, the private fair preference is not intuitively positive or negative related to the social efficiency of compensation. Only under some given conditions, the correlation will show the consistent effect. Third, the private fair behavior’s impact on the efficiency of compensation will become lower and lower as the social cost of compensation reduces. Fourth, the governmental effective compensation scheme should be carried out based on the different comparison scene of the private claimed portfolio profit and the expected revenue for the project.

This study analyzes the effects of private investor's fair preference on the validity of governmental generalized compensation contract of the PPP project for the first time; and the governmental generalized compensation contract designed in this study is a pioneering and exploratory attempt.

This study aims to examine the mechanism of how hotel executive brand identity influences physical facility quality, customer-based brand equity (CBBE) and employee-based brand equity (EBBE).

The study introduces a multilevel model and collects 925 executive and 1,978 employee responses from 62 upscale hotels in China.

Executive brand identity positively affects employee brand internalization, which leads to positive EBBE. Meanwhile, executive brand identity positively influences the physical facility quality, which leads to positive CBBE.

This study considers the tangible (physical facilities) and intangible (employees) elements of hotel services to comprehensively investigate the brand equity formation. By applying multilevel structural equation modeling, the study examines the bidirectional relationship between organizations and employees in the brand value transformation process.

This paper addresses the limitations of current graph neural network-based recommendation systems, which often neglect the integration of side information and the modeling of complex high-order interactions among nodes. The research motivation stems from the need to enhance recommendation performance by effectively utilizing all available data. We propose a novel method called MSHCN, which leverages hypergraph neural networks to integrate side information and model complex interactions, thereby improving user and item representations.

The MSHCN method employs a hypergraph structure to incorporate various types of side information, including social relationships among users and item attributes, which are essential for enriching user and item representations. The k-means clustering algorithm is utilized to create item-associated hypergraphs, while sentiment analysis on user reviews refines the modeling of user interests. Additionally, hypergraphs are constructed for user-user and item-item interactions based on interaction similarity. MSHCN also incorporates contrastive learning as an auxiliary task to enhance the representation learning process.

Extensive experiments demonstrate that MSHCN significantly outperforms existing recommendation models, particularly in its ability to capture and utilize side information and high-order interactions. This results in superior user and item representations and improved recommendation performance.

The novelty of MSHCN lies in its use of a hypergraph structure to integrate diverse side information and model intricate high-order interactions. The incorporation of contrastive learning as an auxiliary task sets it apart from other hypergraph-based models, providing a significant enhancement in recommendation accuracy.

The aim of the paper is to propose a global, automated and continuous curvature calibration strategy for bending sensors, which is used for the angle feedback control of soft fingers.

In this work, the proposed curvature calibration strategy for bending sensors is based on the constant curvature bending properties of soft fingers. The strategy is to install the bending sensor on the soft finger and use the laser distance sensor to assist calibration, then calculate the relationship between the curvature and the voltage of the bending sensor through geometric conversion. In addition, this work also develops a full set of standard calibration systems and collection procedures for the bending sensor curvature calibration and uses machine learning algorithms to fit the collected data.

First, compared with the traditional calibration methods, the proposed curvature calibration strategy can achieve constant curvature measurement with the advantages of better continuity. Second, using the sensor data obtained by the proposed calibration method as the feedback signal for the soft finger bending angle control, the control effect is better than that of the traditional method.

This work proposes and verifies a global, automated and continuous curvature calibration strategy for bending sensors and is used for the angle feedback control of soft fingers. In addition, this work also develops a full set of standard calibration systems and collection procedures, which can be applied to a variety of flexible bending sensors with a good adaptability.

This study aims to provide guidance for the reliability of electronic packaging. The reliability of solder joints at extremely temperature thermal shock is critical for electronic equipment operating in the field of deep space exploration. In this study, the Sn3.0Ag0.5Cu (SAC305)/Cu solder joints were prepared and thermally shocked with temperatures ranging from −110°C to 110°C, to investigate the effects of extreme temperature thermal shock on the microstructural evolution and property deterioration of the solder joints.

The interfacial intermetallic compound (IMC) stress gradient was calculated through thermal stress theory, mechanism of voids/cracks initiation was clarified, and prediction of the service life was analyzed with the energy-based model.

It is found that the Ag₃Sn, IMC and cracks/voids had evolved significantly with the increase in the cycle period. The microstructure of the IMC changed from short rod-like morphology to scallop shape, the voids in the Cu₃Sn IMC layer continued to increase and integrate, forming larger diameter voids, etc. In addition, the shear strength of SAC305/Cu solder joints decreased gradually with the increase in thermal shock cycles, the fracture mode changes from ductile fracture mode to ductile-brittle mixed fracture mode after 500 cycles. The characteristic lifetime of the SAC305/Cu solder joints under the action of extreme thermal shock is about 1427.86 cycles.

This work provides guidance for the reliability of the solder joints at extremely temperature thermal shock.

This chapter introduces the book’s purpose: to explore the niche technology space of Web3 and use it as a lens to reflect on the internet’s future. I’ll discuss the internet’s current state and key issues and then move into a definitional tour of Web3 and its underlying technology. The book’s core argument is presented: Web3 provides tangible social proof of what people want for the internet’s future. I’ll examine current challenges such as privacy concerns, unclear data ownership, and lack of transparency in online systems, which create power imbalances between technology controllers and users. The book argues for striving towards a more equitable and transparent digital future. This chapter serves as a starting point, offering insight into my decade-long research. It aims to familiarise readers with the case study approach and Web3 terminology used throughout the book. A chapter-by-chapter roadmap is provided to guide readers through the exploration of Web3 and its implications. Additionally, this chapter introduces my writing style and voice, preparing readers for the deeper analysis to come. While grounded in sociological knowledge, the chapter aims to make Web3 accessible and spark readers’ curiosity, encouraging them to pursue their own inquiries into this emerging field.

The purpose of this paper is to propose an improved method which can shorten the calculation time and improve the calculation efficiency under the premise of ensuring the calculation accuracy for calculating the response of dynamic systems with periodic time-varying characteristics.

An improved method is proposed based on Runge–Kutta method according to the composition characteristics of the state space matrix and the external load vector formed by the reduction of the dynamic equation of the periodic time-varying system. The recursive scheme of the holistic matrix of the system using the Runge–Kutta method is improved to be the sub-block matrix that is divided into the upper and lower parts to reduce the calculation steps and the occupied computer memory.

The calculation time consumption is reduced to a certain extent about 10–35% by changing the synthesis method of the time-varying matrix of the dynamics system, and the method proposed of paper consumes 43–75% less calculation time in total than the original Runge–Kutta method without affecting the calculation accuracy. When the ode45 command that implements the Runge–Kutta method in the MATLAB software used to solve the system dynamics equation include the time variable which cannot provide its specific analytic function form, so the time variable value corresponding to the solution time needs to be determined by the interpolation method, which causes the calculation efficiency of the ode45 command to be substantially reduced.

The proposed method can be applied to solve dynamic systems with periodic time-varying characteristics, and can consume less calculation time than the original Runge–Kutta method without affecting the calculation accuracy, especially the superiority of the improved method of this paper can be better demonstrated when the degree of freedom of the periodic time-varying dynamics system is greater.