Institutional Accountability or Individual Agency in China’s Public Administration System

How to improve the performance and efficiency of a public administration system has been an eternal challenge and a regular item on the government agenda. In contrast to an institutional check-and-balance mechanism, cadre education and training plays a special role in the Chinese socialist system. Educational work to inculcate desirable contents in cadres’ thoughts has taken up a large part in the Party’s efforts to enhance cadres’ capability since the years of revolutionary struggle. It is a strategy adopted by the Party-state for the sake of making cadres loyal to the CCP in bothpolitical and administrative e aspects. The study reviews the conceptual and theoretical discussion on the term ‘responsibility.’ The practices that the CCP adopted to create cadre responsibility in China are analysed through the perspective of “structure-and-agency.” The paper argues that individual agency goes beyond institutionalaccountability within China’s Public Administration System.

Design of the Wearable Spatial Gravity Balance Mechanism

Gravity compensation mechanisms are widely used in manipulators and exoskeletons as passive components which generate counter-gravity force and save energy. While there have been making great progresses in the design of the planar gravity compensator and its spatial counterpart, a strict condition that the axes of the gravity compensators are aligned with the axes of the links being balanced (LBBs) exactly is usually assumed implicitly. In this paper, the design method of the wearable spatial gravity compensator compatible to the misalignment and drift of the rotation center of the LBB is carefully studied. First, the design of the planar gravity compensation unit (PGCU) is presented, and then it is adapted into the spatial gravity compensation unit (SGCU) by the motion features of the fixed-point rotation. Then, the type synthesis of the SGCU is conducted followed by the analyses of the acting patterns of synthesized SGCUs on the LBBs and gravity compensation performances when the misalignments and drifts of rotation centers of the LBBs occur. Finally, the SGCUs can be combined with timing belt mechanisms (TBMs) to construct gravity compensation mechanisms for spatial serial linkages. Simulations of the exoskeleton constructed by SGCUs are conducted to verify the performance of gravity balance and the effectiveness of the proposed design method.

A Novel Coaxial Balance Mechanism for Reciprocating Piston Engines

Vibration is an important issue faced by reciprocating piston engines, and is caused by reciprocating inertia forces of the piston set. To reduce the vibration without changing the main structure and size of the original engine, we proposed a novel coaxial balance mechanism design based on a compact unit body. By introducing a second-order balance mass, this mechanism can significantly increase the efficiency of vibration reduction. The proposed mechanism can effectively balance the first-order and second-order inertia forces with the potential of balancing high-order inertia forces. To accurately determine the second-order balance mass, a closed-form method was developed. Simulation results with a single-cylinder piston DK32 engine demonstrate the effectiveness and advantage of the proposed mechanism. At a crankshaft speed of 2350 r/min, compared with the first-order balance device, the average root mean square velocity of the test points on the engine’s cylinder was reduced by 97.31%, and the support reaction force was reduced by 96.54%.

Development and Optimization for a New Planar Spring Using Finite Element Method, Deep Feedforward Neural Networks, and Water Cycle Algorithm

The gravity balance mechanism plays a vital role in maintaining the equilibrium for robots and assistive devices. The purpose of this paper was to optimize the geometry of a planar spring, which is an essential element of the gravity balance mechanism. To implement the optimization process, a hybrid method is proposed by combining the finite element method, the deep feedforward neural network, and the water cycle algorithm. Firstly, datasets are collected using the finite element method with a full experiment design. Secondly, the output datasets are normalized to eliminate the effects of the difference of units. Thirdly, the deep feedforward neural network is then employed to build the approximate models for the strain energy, deformation, and stress of the planar spring. Finally, the water cycle algorithm is used to optimize the dimensions of the planar spring. The results found that the optimal geometries of the spring include the length of 45 mm, the thickness of 1.029 mm, the width of 9 mm, and the radius of 0.3 mm. Besides, the predicted results determined that the strain energy, the deformation, and the stress are 0.01123 mJ, 33.666 mm, and 79.050 MPa, respectively. The errors between the predicted result and the verifying results for the strain energy, the deformation, and the stress are about 1.87%, 1.69%, and 3.06%, respectively.

Towards a balancing safety against performance approach in human–robot co-manipulation for door-closing emergencies

Telemanipulation in power stations commonly require robots first to open doors and then gain access to a new workspace. However, the opened doors can easily close by disturbances, interrupt the operations, and potentially lead to collision damages. Although existing telemanipulation is a highly efficient master–slave work pattern due to human-in-the-loop control, it is not trivial for a user to specify the optimal measures to guarantee safety. This paper investigates the safety-critical motion planning and control problem to balance robotic safety against manipulation performance during work emergencies. Based on a dynamic workspace released by door-closing, the interactions between the workspace and robot are analyzed using a partially observable Markov decision process, thereby making the balance mechanism executed as belief tree planning. To act the planning, apart from telemanipulation actions, we clarify other three safety-guaranteed actions: on guard, defense and escape for self-protection by estimating collision risk levels to trigger them. Besides, our experiments show that the proposed method is capable of determining multiple solutions for balancing robotic safety and work efficiency during telemanipulation tasks.

Distributed Based Serial Regression Multiple Imputation for High Dimensional Multivariate Data in Multicore Environment of Cloud

Multiple imputations (MI) are predominantly applied in such processes that are involved in the transaction of huge chunks of missing data. Multivariate data that follow traditional statistical models undergoes great suffering for the inadequate availability of pertinent data. The field of distributed computing research faces the biggest hurdle in the form of insufficient high dimensional multivariate data. It mainly deals with the analysis of parallel input problems found in the cloud computing network in general and evaluation of high-performance computing in particular. In fact, it is a tough task to utilize parallel multiple input methods for accomplishing remarkable performance as well as allowing huge datasets achieves scale. In this regard, it is essential that a credible data system is developed and a decomposition strategy is used to partition workload in the entire process for minimum data dependence. Subsequently, a moderate synchronization and/or meager communication liability is followed for placing parallel impute methods for achieving scale as well as more processes. The present article proposes many novel applications for better efficiency. As the first step, this article suggests distributed-oriented serial regression multiple imputation for enhancing the efficiency of imputation task in high dimensional multivariate normal data. As the next step, the processes done in three diverse with parallel back ends viz. Multiple imputation that used the socket method to serve serial regression and the Fork Method to distribute work over workers, and also same work experiments in dynamic structure with a load balance mechanism. In the end, the set of distributed MI methods are used to experimentally analyze amplitude of imputation scores spanning across three probable scenarios in the range of 1:500. Further, the study makes an important observation that due to the efficiency of numerous imputation methods, the data is arranged proportionately in a missing range of 10% to 50%, low to high, while dealing with data between 1000 and 100,000 samples. The experiments are done in a cloud environment and demonstrate that it is possible to generate a decent speed by lessening the repetitive communication between processors.

Effect of an Internal Impact Balance Mechanism on the Perceptible Recoil of Machine Gun

In order to reasonably reduce the perceptible recoil of firearms, and design a recoil reduction device that can be commonly used in automatic rifles, semi-automatic rifles, and machine guns, a balancing mechanism for recoil reduction technology was proposed in this paper. With the perceptible recoil generated by the impact from automat to the balance mechanism as the objective function, the parametric analysis of the mass of the balance weight and the spring stiffness of the balance mechanism was conducted. The analysis showed that the influence of the mass of the balance weight on the reduction of the perceptible recoil of the balance mechanism is obviously greater than that of the spring stiffness of the balance mechanism within the allowable ranges of the two factors. The research results provide a reference for gun recoil reduction technology.