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This paper aims to conduct soft fault diagnosis of dual-redundancy sensors. An innovative fault diagnosis method, which combines a tracking differentiator and a sequential probability ratio test, is proposed.

First, two tracking differentiators are used to track and predict the two original signals, and determine their residuals. These residuals are used to calculate one quadratic residual. Then, a sequential probability ratio test is carried out on this quadratic residual to obtain log-likelihood ratio. A fault can be detected through comparing the log-likelihood ratio value with the threshold value. Finally, analyses of the difference in the residuals, which locates the fault, and of the difference in the original signals, which reveals the fault level and type, are completed successively.

Results from experimentation show that this method can realise soft fault diagnosis for dual-redundancy sensors.

The method proposed in the paper gives a new idea to study hybrid redundancy. The method provides a new application mode for tracking differentiators and sequential probability ratio test. The method can be used in robots, such as unmanned aerial vehicles and unmanned ground vehicles, to improve their fault tolerance. It can also be applied to the key parts of industrial production lines to decrease financial losses caused by sensor faults.

This study modified, revised and validated a travel safety attitude scale (TSAS) using data collected from Canadian residents with out-of-country travel experiences.

The authors proposed a higher component model (HCM) of TSAS, using a reflective-formative measurement model. In consultation with eight experts, a set of purified TSAS items was revised by checking wording and content. A questionnaire was administered to 531 participants using Amazon Mechanical Turk. The scale was validated with the partial least squares method of structural equation modelling (PLS-SEM), and the analysis was performed using SmartPLS 3.0.

The final results suggested a five-factor solution with 27 items, with a satisfactory level of reliability and validity at the first-order (reflective) and second-order (formative) constructs. The predictive validity result showed that TSAS is negatively related to tourist risk-taking intention.

TSAS advanced research on travel safety attitudes and demonstrated the feasibility of using PLS-SEM in examining the Type II model. Future studies can focus on replicating the study in other countries, adding more variables for predictive validity tests and examining the interrelationship with affective attitudes.

The authors suggested a more proactive approach to assess tourist safety attitudes based on travel safety information (TSI), health concern (HC), vulnerability to crime (VTC), personal safety (PES) and police safety (PS), listed in descending order of importance.

The study results provide directions for destination marketing organizations to allocate resources to maintain a positive travel safety attitude from potential and current tourists.

The purpose of this paper is to utilize a multi-method design for research on corruption in China. Corruption in any society is inimical to good governance. Singapore, despite her size, is argued to be a plausible model for China.

Taking a multi-method approach, the phenomena of corruption is investigated from: etymological analyses for corruption (European roots) and its Chinese equivalent, 贪污 (pinyin: tan wu) case studies taken from three periods: current, Qing Dynasty and to founding of China (zhong guo, Qin Dynasty) to ground our policy recommendation of China be modeling after Singapore on the basis of our analysis of statistical (2013 and longitudinal) data. In the process, the authors embark on inter-country comparisons (mainly Confucian China, Hong Kong, Taiwan, South Korea and Japan).

Here are the key insights: scholars are unaware the English word corruption is narrower in scope than the Chinese equivalent tan wu贪污. As far back as 3,000 years, the Chinese had attributed wu, 污 as filthy, polluting, dirty to psychological concept of greed tan, 贪. In English, corruption does not denote greed per se. Falsification of facts as a political ploy dates back to Qin dynasty. Destabilizing corrupt cases occurred in China today as in Qing Dynasty. Singapore rather Hong Kong is a better model for China in reforming society.

This paper illustrates a distinctively, in-depth approach to research on Chinese management. It shows why it is important to clarify key concepts: corruption in the West and tan wu贪污in the East. Historical cases are utilized to show the presence of a continuing Chinese mind set. The authors argued for China to embark on a city-by-city strategy (modeling after Singapore) toward becoming a corruption-free society. Now, as 3,000 years ago, the Chinese conceptualization of corruption embeds the psychology of greed.

China is at a crossroad of her economic development. There is a possible risk of China being destabilized through the corruption of the top rung of leadership. Chinese authorities must with urgency, rein in corruption. An approach is proposed in this paper.

In terms of style, approach and method of research, this paper is highly original. The integrative research here provides a rationale and basis for the Chinese leaders to implement a policy for a less corrupt society.

Micro aerial vehicle is nonlinear plant; it is difficult to obtain stable control for MAV attitude due to uncertainties. The purpose of this paper is to propose one robust stable control strategy for MAV to accommodate system uncertainties, variations, and external disturbances.

First, by employing interval type-II fuzzy neural network (ITIIFNN) to approximate the nonlinearity function and uncertainty functions in the attitude angle dynamic model of micro aircraft vehicle (MAV). Then, the Lyapunov stability theorem is used to testify the asymptotic stability of the closed-loop system, the parameters of the ITIIFNN and gain of sliding mode control can be tuned on-line by adaptive laws based on Lyapunov synthesis approach, and the Lyapunov stability theorem has been used to testify the asymptotic stability of the closed-loop system.

The validity of the proposed control method has been verified through real-time experiments. The experimental results show that the performance of interval type-II fuzzy neural network based gain adaptive sliding mode controller (GASMC-ITIIFNN) is significantly improved compared with conventional adaptive sliding mode controller (CASMC), type-I fuzzy neural network based sliding mode controller (GASMC-TIFNN).

This approach has been used in one MAV, the controller works well, and which could guarantee the MAV control system with good performances under uncertainties, variations, and external disturbances.

The main original contributions of this paper are: the proposed control scheme makes full use of the nominal model of the MAV attitude control model; the overall closed-loop control system is globally stable demonstrated by Lyapunov stable theory; the tracking error can be asymptotically attenuated to a desired small level around zero by appropriate chosen parameters and learning rates; and the MAV attitude control system based on GASMC-ITIIFNN controller can achieve favourable tracking performance than GASMC-TIFNN and CASMC.

This paper aims to investigate the influence of the regional business environment on local firm innovation, considering various dimensions such as administrative, financial and legal environments.

Multiple regression analysis is employed to analyze archival data for firms listed on Chinese stock markets.

We find that the optimizations of the administrative and financial environments positively affect firm innovation, whereas the legal environment does not exert a similar impact. Our analysis also reveals that the business environment’s optimization significantly influences innovation in firms that are small, non-state-owned and operating in high-tech industries. Furthermore, the business environment acts as a moderating variable in the relationship between firm innovation and firm value.

This study contributes to a more comprehensive understanding of institutional-level determinants of firm innovation, highlighting the nuances of the legal environment and the importance of context-specific analysis, especially in emerging markets like China.

Developing countries can significantly enhance firm innovation by improving the business environment, including the optimization of administrative and financial systems, reducing transaction costs and ensuring capital supply. Tailored legal frameworks and alternative institutional strategies may also be explored.

This study explicitly emphasizes the governmental role in promoting firm innovation, shedding light on policy formulation and strategic alignment with local administrative policies.

To the best of our knowledge, this paper is the first to explore the relationship between the business environment and firm innovation using World Bank indicators in an emerging market context, providing novel insights into the unique dynamics of legal, financial and administrative sub-environments.

The purpose of this paper is to characterise the TWIN-RRT* algorithm which solves a motion planning problem in which an agent has multiple possible targets where none of them is compulsory and retrieves feasible, “low cost”, asymptotically optimal and probabilistically complete paths. The TWIN-RRT* algorithm solves path planning problems for both holonomic and non-holonomic robots with or without kinematic constraints in a 2D environment.

It was designed to work equally well with higher degree of freedom agents in different applications. It provides a practical implementation of feasible and fast planning, namely where a closed loop is required. Initial and final configurations are allowed to be exactly the same.

The TWIN-RRT* algorithm computes an efficient path for a single agent towards multiple targets where none of them is mandatory. It inherits the low computational cost, probabilistic completeness and asymptotical optimality from RRT*.

It uses efficiency as cost function, which can be adjusted to the requirements of any given application. TWIN-RRT also shows compliance with kinematic constraints.

The practical application where this work has been used consists of an autonomous mobile robot that picks up golf balls in a driving range. The multiple targets are the golf balls and the optimum path is a requirement to reduce the time and energy to refill as quickly as possible the balls dispensing machine.

The new random sampling algorithm – TWIN-RRT* – is able to generate feasible efficient paths towards multiple targets retrieving closed-loop paths starting and finishing at the same configuration.

Expert systems are computer-based systems that mimic the logical processes of human experts or organizations to give advice in a specific domain of knowledge. Fuzzy expert systems use fuzzy logic to handle uncertainties generated by imprecise, incomplete and/or vague information. The purpose of this paper is to present a comprehensive review of the methods and applications in fuzzy expert systems.

The authors have carefully reviewed 281 journal publications and 149 conference proceedings published over the past 37 years since 1982. The authors grouped the journal publications and conference proceedings separately accordingly to the methods, application domains, tools and inference systems.

The authors have synthesized the findings and proposed useful suggestions for future research directions. The authors show that the most common use of fuzzy expert systems is in the medical field.

Fuzzy logic can be used to manage uncertainty in expert systems and solve problems that cannot be solved effectively with conventional methods. In this study, the authors present a comprehensive review of the methods and applications in fuzzy expert systems which could be useful for practicing managers developing expert systems under uncertainty.