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The purpose of this paper is to make compliant training control of exoskeleton for ankle joint with electromyograph (EMG)-torque interface.

A virtual compliant mapping which is modeled by mass-spring-damper system is incorporated into the whole system at the reference input. The EMG-torque interface contains both data acquisition and torque estimator/predictor, and extreme learning machine is utilized for joint torque estimation/prediction from multiple channels of EMG signals.

The reference ankle joint angle to follow is produced from the compliance mapping whose input is the measured/predicted torque on healthy subjects. The control system works well with the desired angle to track. In the actuation level, the input torque to drive the ankle exoskeleton is less than the actual torque of the subject(s). This may have positive influence on diminishing overshoot of input torque from motors and protect the actuators. The torque prediction and final tracking control performance demonstrate the efficiency of the presented architecture.

This work can be beneficial to compliant training of ankle exoskeleton system for pilots and enhance current training control module in rehabilitation.

Despite an intensified anti-corruption campaign, China's economic growth and social transition continue to breed loopholes and opportunities for big corruption, leading to a money-oriented mentality and the collapse of ethical standards, and exposing the communist regime to greater risk of losing moral credibility and political trust. In Hong Kong, the setting up of the Independent Commission Against Corruption (ICAC) in 1974 marked the advent of a new comprehensive strategy to eradicate corruption and to rebuild trust in government. The ICAC was not just an anti-corruption enforcement agency per se, but an institution spearheading and representing integrity and governance transformation. This chapter considers how mainland China can learn from Hong Kong's experience and use the fight against corruption as a major political strategy to win the hearts and minds of the population and reform governance in the absence of more fundamental constitutional reforms, in a situation similar to Hong Kong's colonial administration of the 1970s–1980s deploying administrative means to minimize a political crisis.

The purpose of this paper is to design a model-based bilateral teleoperation method to improve the feedback force and velocity/position tracking for robotic-assisted tasks (such as palpation, etc.) under constant and/or varying time delay with environment dynamic property. Time delay existing in bilateral teleoperation easily destabilizes the system. Proper control strategies are able to make the system stable, but at the cost of compromised performance. Model-based bilateral teleoperation is designed to achieve enhanced performance of this time-delayed system, but an accurate model is required.

Viscoelastic model has been used to describe the robot tool-soft tissue interaction behavior. Kevin-Boltzmann (K-B) model is selected to model the soft tissue behavior due to its good accuracy, transient and linearity properties among several viscoelastic models. In this work, the K-B model is designed at the master side to generate a virtual environment of remote robotic tool-soft tissue interaction. In order to obtain improved performance, a self perturbing recursive least square (SPRLS) algorithm is developed to on-line update the necessary parameters of the environment with varying dynamics.

With fast and optimal on-line estimation of primary parameters of the K-B model, the reflected force of the model-based bilateral teleoperation at the master side is improved as well as the position/velocity tracking performance. This model-based design in the bilateral teleoperation avoids the stability issue caused by time delay in the communication channel since the exchanged information become position/velocity and estimated parameters of the used model. Even facing with big and varying time delay, the system keeps stably and enhanced tracking performance. Besides, the fast convergence of the SPRLS algorithm helps to track the time-varying dynamic of the environment, which satisfies the surgical applications as the soft tissue properties usually are not static.

The originality of this work lies in that an enhanced perception of bilateral teleoperation structure under constant/varying time delay that benefits robotic assisted tele-palpation (time varying environment dynamic) tasks is developed. With SPRLS algorithm to on-line estimate the main parameters of environment, the feedback perception of system can be enhanced with stable velocity/position tracking. The superior velocity/position and force tracking performance of the developed method makes it possible for future robotic-assisted tasks with long-distance communication.

The reported Kullback–Leibler (K–L) distance-based generalized grey target decision method (GGTDM) for mixed attributes is an asymmetric decision-making basis (DMB) that does not have the symmetric characteristic of distance in common sense, which may affect the decision-making result. To overcome the deficiency of the asymmetric K–L distance, the symmetric K–L distance is investigated to act as the DMB of GGTDM for mixed attributes.

The decision-making steps of the proposed approach are as follows: First, all mixed attribute values are transformed into binary connection numbers, and the target centre indices of all attributes are determined. Second, all the binary connection numbers (including the target centre indices) are divided into deterministic and uncertain terms and converted into two-tuple (determinacy and uncertainty) numbers. Third, the comprehensive weighted symmetric K–L distance can be computed, as can the alternative index of normalized two-tuple (deterministic degree and uncertainty degree) number and that of the target centre. Finally, the decision-making is made by the comprehensive weighted symmetric K–L distance according to the rule that the smaller the value, the better the alternative.

The case study verifies the proposed approach with its sufficient theoretical basis for decision-making and reflects the preferences of decision-makers to address the uncertainty of an uncertain number.

This work compares the single-direction-based K–L distance to the symmetric one and uses the symmetric K–L distance as the DMB of GGTDM. At the same time, different coefficients are assigned to an uncertain number’s deterministic term and uncertain term in the calculation process, as this reflects the preference of the decision-maker.

The purpose of this paper is to propose a fractional order optimization method based on perturbation bound and gamma function of a DGM(r,1).

By analyzing and minimizing perturbation bound, the sub-optimal solution on fractional order interval is obtained through offline solving without iterative calculation. By this method, an optimized fractional order non-equidistant ROGM (OFONEROGM) is applied in fitting and prediction water quality parameters for a surface water pollution monitoring system.

This method can narrow fractional order interval in this work. In a surface water pollution monitoring system, the fitting and prediction performances of OFONEROGM are demonstrated comparing with integer order non-equidistant ROGM (IONEROGM).

A method of offline solving the sub-optimal solution on fractional order interval is proposed. It can narrow the optimized fractional order range of NEROGM without iterative calculation. A large number of calculations are eliminated. Besides that, optimized fractional order interval is only related to the number of original data, and convenient for practical application. In this work, an OFONEROGM is modeled for predicting water quality trend for preventing water pollution or stealing sewage discharge. It will provide guiding significance in water quality parameter fitting and predicting for water environment management.

The purpose of this paper is to establish a maturity evaluation model for the application of construction steel structure welding robotics suitable for the actual situation and specific characteristics of engineering projects in China and then to assess the maturity level of the technology in the application of domestic engineering projects more scientifically.

The research follows a qualitative and quantitative analysis method. In the first stage, the structure of the maturity model is constructed and the evaluation index system is designed by using the ideas of the capability maturity model and WSR methodology for reference. In the second stage, the design of the evaluation process and the selection of evaluation methods (analytic hierarchy process method, multi-level gray comprehensive evaluation method). In the third stage, the data are collected and organized (preparation of questionnaires, distribution of questionnaires, questionnaire collection). In the fourth stage, the established maturity evaluation model is used to analyze the data.

The evaluation model established by using multi-level gray theory can effectively transform various complex indicators into an intuitive maturity level or score status. The conclusion shows that the application maturity of building steel structure welding robot technology in this project is at the development level as a whole. The maturity levels of “WuLi – ShiLi – RenLi” are respectively: development level, development level, between starting level and development level. Comparison of maturity evaluation values of five important factors (from high to low): environmental factors, technical factors, management factors, benefit factors, personnel and group factors.

In this paper, based on the existing research related to construction steel structure welding robot technology, a quantitative and holistic evaluation of the application of construction steel structure welding robot technology in domestic engineering projects is conducted for the first time from a project perspective by designing a maturity evaluation index system and establishing a maturity evaluation model. This research will help the project team to evaluate the application level (maturity) of the welding robot in the actual project, identify the shortcomings and defects of the application of this technology, then improve the weak links pertinently, and finally realize the gradual improvement of the overall application level of welding robot technology for building steel structure.

The purpose of this paper is to examine information-seeking behavior (ISB) of strategic planners in enterprise across different work-task types and stages.

A case study was conducted in a pharmaceutical company in China, labeled as T Company. One of the authors worked in the department of strategic planning of this company as an intern. The data were collected via participant observation and unstructured in-depth interviews. Open coding was performed to analyze the data.

Four work-task stages were identified: project preparation, gathering, discovery and presentation, and strategy formulation. The results indicate that work-task types, work-task stages, and strategic planners’ work role or position affect their information needs, source selection, and seeking process. Task complexity, task familiarity, and task goal are of the most important task attributes that directly shape strategic planners’ ISB. Work role determines the extent to which strategic planners can access the information of the company. Internal information has priority, but external information is also important when internal information is not sufficient; both are equally important for strategic planning projects. Social media has been a very important channel to access, disseminate and share information. Workshops are an important approach to producing final project reports. Face-to-face discussion and information exchange play a critical role in the formulation of new strategies.

This is a case study with data collected from only one company in China. Some of the results may not be generalizable. However, it adds new knowledge to ISB research in enterprise, informs people how to provide better information services for strategic planners, and informs MBA education for students’ better information-seeking skills.

Though myriad studies on ISB, little research has been done to examine strategic planners’ ISB from a business context, especially taking into account the effect of work-task types and stages.

The purpose of this paper is to study the effect of vapor assembly sequence and assembly temperature on the corrosion protection of the complex silane films Al alloy. The performance and application range of silane films are enhanced.

The complex silane films were successfully prepared on the surface of aluminum alloy using via vapor phase assembly of 1,2,3-benzotriazole (BTA) and dodecyltrimethoxysilanes (DTMS). The protection of the assembly films against corrosion of Al alloy is investigated by the electrochemical measurements and the alkaline solution accelerated corrosion test. Thickness and hydrophobicity of the complex films are studied using ellipsometric spectroscopy and contact angle tests.

It shows that the anti-corrosion ability of the complex films is overall superior to that of the single-component assembled films. DTMS-BTA films have larger thickness and best anti-corrosion ability. The alkyl chains in DTMS have better compatibility with BTA molecules. The rigid BTA molecule can permeate into the long alkyl chain of DTMS as fillers and improve the barrier properties of the complex films.

In this paper, a green and efficient method of vapor phase assembly is proposed to rust prevention during manufacture of Al alloy workpiece.

During the COVID-19 pandemic, the public relied heavily on digital media to stay tuned for the latest update. Media preference could increase risk perceptions, although the influence of diverse media exposure remains unknown. Based on protection motivation theory, this study aims to investigate how digital media exposure diversity and information verification influence vaccination intention.

Analyzing survey data from 837 respondents in China, this study examined the effects of digital media exposure on information verification, including their influences on the threat appraisal, coping appraisal, vaccine misinformation beliefs, subjective norms and trust in vaccines.

Results indicate that diversity of digital media exposure increased threat appraisal (perceived severity) and coping appraisal (response efficacy and self-efficacy), while information verification increased only coping appraisal (response efficacy and self-efficacy). In addition, diversity of digital media exposure decreased vaccine misinformation beliefs. Furthermore, digital media exposure and information verification were linked to vaccination intention via the mediations of response efficacy, subjective norms and trust in vaccines.

This study is the first of its kind to investigate media exposure diversity in the context of vaccination and health crises. Our findings extended the PMT framework by exploring proactive information-related behaviors as antecedents of mediation processes. In addition, we examined misinformation beliefs, social norms and trust as societal influences. Theoretical and practical implications are also discussed.

The purpose of this paper is to study the effect of doping, annealing temperature and visible optical excitation on CuO-ZnO nanocomposites’ acetone sensing properties and introduce an attractive candidate for acetone detection at about room temperature.

ZnO nanoparticles doped with CuO were prepared by sol-gel method, and the structure and morphology were characterized via X-ray diffraction, scanning electron microscope, energy dispersive spectroscopy and Brunauer-Emmett-Teller. The photoelectric responses of CuO-ZnO nanocomposites to cetone under the irradiation of visible light were investigated at about 30°C. The photoelectric response mechanism was also discussed with the model of double Schottky.

The doping of CuO enhanced performance of ZnO nanoparticles in terms of the photoelectric responses and the gas response and selectivity to acetone of ZnO nanoparticles, in addition, decreasing the operating temperature to about 30ºC. The optimum performance was obtained by 4.17% CuO-ZnO nanocomposites. Even at the operating temperature, about 30ºC, the response to 1,000 ppm acetone was significantly increased to 579.24 under the visible light irradiation.

The sensor fabricated by 4.17% CuO-ZnO nanocomposites exhibited excellent acetone-sensing characteristics at about 30ºC. It is promising to be applied in low power and miniature acetone gas sensors.

In the present research, a new nanocomposite material of CuO-ZnO was prepared by Sol-gel method. The optimum gas sensing properties to acetone were obtained by 4.17% CuO-ZnO nanocomposites at about 30ºC operating temperature when it was irradiated by visible light with the wavelength more than 420 nm.