Bin Li, Shoukun Wang, Jinge Si, Yongkang Xu, Liang Wang, Chencheng Deng, Junzheng Wang and Zhi Liu
Dynamically tracking the target by unmanned ground vehicles (UGVs) plays a critical role in mobile drone recovery. This study aims to solve this challenge under diverse random…
Abstract
Purpose
Dynamically tracking the target by unmanned ground vehicles (UGVs) plays a critical role in mobile drone recovery. This study aims to solve this challenge under diverse random disturbances, proposing a dynamic target tracking framework for UGVs based on target state estimation, trajectory prediction, and UGV control.
Design/methodology/approach
To mitigate the adverse effects of noise contamination in target detection, the authors use the extended Kalman filter (EKF) to improve the accuracy of locating unmanned aerial vehicles (UAVs). Furthermore, a robust motion prediction algorithm based on polynomial fitting is developed to reduce the impact of trajectory jitter caused by crosswinds, enhancing the stability of drone trajectory prediction. Regarding UGV control, a dynamic vehicle model featuring independent front and rear wheel steering is derived. Additionally, a linear time-varying model predictive control algorithm is proposed to minimize tracking errors for the UGV.
Findings
To validate the feasibility of the framework, the algorithms were deployed on the designed UGV. Experimental results demonstrate the effectiveness of the proposed dynamic tracking algorithm of UGV under random disturbances.
Originality/value
This paper proposes a tracking framework of UGV based on target state estimation, trajectory prediction and UGV predictive control, enabling the system to achieve dynamic tracking to the UAV under multiple disturbance conditions.
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Ji Kai, Ming Liu, Yue Wang and Ding Zhang
Nucleic acid testing is an effective method of accurate prevention and control and a key measure to block the spread of the epidemic. However, the fraud in nucleic acid testing…
Abstract
Purpose
Nucleic acid testing is an effective method of accurate prevention and control and a key measure to block the spread of the epidemic. However, the fraud in nucleic acid testing occurred frequently during epidemics. This paper aims to provide a viable scheme for the government to strengthen the supervision of nucleic acid testing and to provide a new condition for the punishment for the negative act of the government and the upper limit of the reward for nucleic acid testing institution of no data fraud.
Design/methodology/approach
This paper formulates an evolutionary game model between the government and nucleic acid testing institution under four different mechanisms of reward and punishment to solve the issue of nucleic acid testing supervision. The authors discuss the stability of equilibrium points under the four distinct strategies and conduct simulation experiments.
Findings
The authors find that the strategy of dynamic reward and static penalty outperforms the strategies of static reward and static penalty, dynamic reward and static penalty, static reward and dynamic penalty, dynamic reward and dynamic penalty. The results reveal the appropriate punishment for the negative act of the government can enhance the positivity of the government's supervision in the strategy of dynamic reward and static penalty, while the upper limit of the reward for nucleic acid testing institution of no data fraud cannot be too high. Otherwise, it will backfire. Another interesting and counterintuitive result is that in the strategy of dynamic reward and dynamic penalty, the upper limit of the penalty for data fraud of nucleic acid testing institution cannot be augmented recklessly. Otherwise, it will diminish the government's positivity for supervision.
Originality/value
Most of the existing evolutionary game researches related to the reward and punishment mechanism and data fraud merely highlight that increasing the intensity of reward and punishment can help improve the government's supervision initiative and can minimize data fraud of nucleic acid institution, but they fall short of the boundary conditions for the punishment and reward mechanism. Previous literature only study the supervision of nucleic acid testing qualitatively and lacks quantitative research. Moreover, they do not depict the problem scenario of testing data fraud of nucleic acid institution regulated by the government via the evolutionary game model. Thus, this study effectively bridges these gaps. This research is universal and can be extended to other industries.
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Thermal buckling of double-layered piezoelectric nanoplates has been analyzed by applying an external electric voltage on the nanoplates. The paper aims to discuss this issue.
Abstract
Purpose
Thermal buckling of double-layered piezoelectric nanoplates has been analyzed by applying an external electric voltage on the nanoplates. The paper aims to discuss this issue.
Design/methodology/approach
Double-layered nanoplates are connected to each other by considering linear van der Waals forces. Nanoplates are placed on a polymer matrix. A comprehensive thermal stress function is used for investigating thermal buckling. A linear electric function is used for taking external electric voltages into account. For considering the small-scale effect, the modified couple stress theory has been applied. An analytical solution has been used by taking various boundary conditions.
Findings
EEV has a considerable impacted on the results of various half-waves in all boundary conditions. By increasing EEV, the reduction of critical buckling temperature in higher half-waves is remarkably slower than lower half-waves. By considering long lengths, the effect of EEV on the critical temperature will be markedly decreased.
Originality/value
This paper uses electro-thermal stability analysis. Double-layered piezoelectric nanoplates are analyzed. A comprehensive thermal stress function is applied for taking into account critical temperature.
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Xueguang Yu, Xintian Liu, Xu Wang and Xiaolan Wang
This study aims to propose an improved affine interval truncation algorithm to restrain interval extension for interval function.
Abstract
Purpose
This study aims to propose an improved affine interval truncation algorithm to restrain interval extension for interval function.
Design/methodology/approach
To reduce the occurrence times of related variables in interval function, the processing method of interval operation sequence is proposed.
Findings
The interval variable is evenly divided into several subintervals based on correlation analysis of interval variables. The interval function value is modified by the interval truncation method to restrain larger estimation of interval operation results.
Originality/value
Through several uncertain displacement response engineering examples, the effectiveness and applicability of the proposed algorithm are verified by comparing with interval method and optimization algorithm.
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Hannes Velt and Rudolf R. Sinkovics
This chapter offers a comprehensive review the literature on authentic leadership (AL). The authors employ a bibliometric approach to identify, classify, visualise and synthesise…
Abstract
This chapter offers a comprehensive review the literature on authentic leadership (AL). The authors employ a bibliometric approach to identify, classify, visualise and synthesise relevant scholarly publications and the work of a core group of interdisciplinary scholars who are key contributors to the research on AL. They review 264 journal articles, adopting a clustering technique to assess the central themes of AL scholarship. They identify five distinct thematic clusters: authenticity in the context of leadership; structure of AL; social perspectives on AL; dynamism of AL; and value perceptions of AL. Velt and Sinkovics assert that these clusters will help scholars of AL to understand the dominant streams in the literature and provide a foundation for future research.
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Emir Malikov, Shunan Zhao and Jingfang Zhang
There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework…
Abstract
There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.