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The aim of this paper is to propose a grasping method based on intelligent perception for implementing a grasp task with human conduct.

First, the authors leverage Kinect to collect the environment information including both image and voice. The target object is located and segmented by gesture recognition and speech analysis and finally grasped through path teaching. To obtain the posture of the human gesture accurately, the authors use the Kalman filtering (KF) algorithm to calibrate the posture use the Gaussian mixture model (GMM) for human motion modeling, and then use Gaussian mixed regression (GMR) to predict human motion posture.

In the point-cloud information, many of which are useless, the authors combined human’s gesture to remove irrelevant objects in the environment as much as possible, which can help to reduce the computation while dividing and recognizing objects; at the same time to reduce the computation, the authors used the sampling algorithm based on the voxel grid.

The authors used the down-sampling algorithm, kd-tree algorithm and viewpoint feature histogram algorithm to remove the impact of unrelated objects and to get a better grasp of the state.

China has a bad reputation — justified or not — for corruption: in a recent Transparency International survey, it was listed by US and European businesspeople as one of the three most corrupt countries in Asia, though its ranking fell slightly in 1996. A national survey revealed that ordinary Chinese regard corruption as the most serious problem after inflation, though 52 per cent expressed doubt that the Government could do anything about it. In 1995, in Beijing alone, 1,085 cases of corruption were uncovered. In 1996, in the Working Report of the Supreme Peoples's Procuratorate, the Chief Procurator Zhang Siqing observed:

The purpose of this paper is to present a method to achieve small satellite formation keeping operations by using the differential lift and drag to control the drift caused by J2 perturbation in circular or near-circular low earth orbits (LEOs).

Each spacecraft is equipped with five large flat plates, which can be controlled to generate differential accelerations. The aerodynamic lift and drag acting on a flat plate is calculated by the kinetic theory. To maintain the formation within tracking error bounds in the presence of J2 perturbation, a nonlinear Lyapunov-based feedback control law is designed.

Simulation results demonstrate that the proposed method is efficient for the satellite formation keeping and better accuracy advantage in comparison with classical approaches via the fixed maximum differential aerodynamic acceleration.

Because the aerodynamic force will reduce drastically as the orbital altitude increases, the formation keeping control strategy for small satellites presented in this paper should be limited to the scenarios when satellites are in LEO.

The formation keeping control method in this paper can be applied to solve satellite formation keeping problem for small satellites in LEO.

This paper proposes a Lyapunov control strategy for satellite formation keeping considering both lift and drag forces, and simulation results show better performance with high accuracy under J2 perturbation.

This paper aims to extend understanding of how team creative potential translates into team creativity. Drawing on social exchange theories, the authors propose that reward interdependence produce cooperative intra-team interactions, which in turn enables aggregate levels of individual member creativity to translate into team creativity. Further, the authors propose that reward interdependence enhances this link indirectly by motivating collective norms around knowledge sharing.

Multi-source and multi-wave data was collected from 94 R&D teams in two large medical firms. At Time 1, team members assessed the degree of reward interdependence and knowledge sharing characterizing their team; team leaders rated each member’s individual creativity. Unit leaders reported on the team’s overall creativity at Time 2 (three months after Time 1).

The results indicate that the effect of aggregate member creativity (AMC) on team creativity is moderated by reward interdependence in such a way that when reward interdependence is high, AMC has stronger positive effects on team creativity. Furthermore, knowledge sharing, as motivated by reward interdependence, mediates this moderating effect.

By integrating the team design and team creativity literatures, this paper advances an interactive model in which team creative composition combines with reward interdependence and knowledge sharing to help team creativity.

The purpose of this study is to investigate the understanding and application of crime of sabotaging production and operation in internet era, and, at the same time, discuss the basic position for criminal law interpretation in cyberspace.

Doctrinal analysis and case study.

Along with the advent of the internet era, how to apply the traditional crime of sabotaging production and operation in virtual space has attracted people’s attention. The controversy caused by the conviction of malicious application of fake transactions is a typical example. The legal interest protected here includes not only the property value of the means of production itself, but also the expectation interest that can be obtained by normal production and operation activities. There is no reliable basis to believe that overlap of articles between special provision and general laws occurs in crime of sabotaging production and operation and crime of intentional damage of property. The production and operation activities carried out online can also be covered by crime of sabotaging production and operation, without doubt. Ejusdem Generis Rule should be fully respected, but crime of sabotaging production and operation has a dual structure of means behavior and purpose behavior, where the purpose behavior, sabotaging production and operation, is the key to the conviction. However, it is not necessarily premised on physical damage and violent characteristics. The understanding and application of traditional crimes should keep pace with the times in the internet era, and we should not stick to a completely rigid subjective interpretation.

This study demonstrates the possible application of crime of sabotaging production and operation in cyberspace, and clarifies many misunderstandings about this crime.

The purpose of this paper is to solve the problem that the standard particle swarm optimization (PSO) algorithm has a low success rate when applied to the optimization of multi-dimensional and multi-extreme value functions, the authors would introduce the extended memory factor to the PSO algorithm. Furthermore, the paper aims to improve the convergence rate and precision of basic artificial fish swarm algorithm (FSA), a novel FSA optimized by PSO algorithm with extended memory (PSOEM-FSA) is proposed.

In PSOEM-FSA, the extended memory for PSO is introduced to store each particle’ historical information comprising of recent places, personal best positions and global best positions, and a parameter called extended memory effective factor is employed to describe the importance of extended memory. Then, stability region of its deterministic version in a dynamic environment is analyzed by means of the classic discrete control theory. Furthermore, the extended memory factor is applied to five kinds of behavior pattern for FSA, including swarming, following, remembering, communicating and searching.

The paper proposes a new intelligent algorithm. On the one hand, this algorithm makes the fish swimming have the characteristics of the speed of inertia; on the other hand, it expands behavior patterns for the fish to choose in the search process and achieves higher accuracy and convergence rate than PSO-FSA, owning to extended memory beneficial to direction and purpose during search. Simulation results verify that these improvements can reduce the blindness of fish search process, improve optimization performance of the algorithm.

Because of the chosen research approach, the research results may lack persuasion. In the future study, the authors will conduct more experiments to understand the behavior of PSOEM-FSA. In addition, there are mainly two aspects that the performance of this algorithm could be further improved.

The proposed algorithm can be used to many practical engineering problems such as tracking problems.

The authors hope that the PSOEM-FSA can increase a branch of FSA algorithm, and enrich the content of the intelligent algorithms to some extent.

The novel optimized FSA algorithm proposed in this paper improves the convergence speed and searching precision of the ordinary FSA to some degree.

Quality failures in grid infrastructure construction would cause large-scale collapses in power supply and additional expenditures by reworks and repairs. Learning from quality failures (LFQF) extracts experience from previous quality events and converts them into preventive measures to reduce or eliminate future construction quality issues. This study aims to investigate the influence factors of LFQF in the construction of grid infrastructure.

The related factors of LFQF, including quality management (QM) practices, quality rectification, and individual learning, were identified by reviewing literature about organizational learning and extracting experience from previous failures. A questionnaire survey was distributed to the grid companies in North, Northeast, Northwest, East, Central, and Southwest China. 381 valid responses collected and analyzed using structural equation modeling (SEM) to test the influence of these factors on LFQF.

The SEM results support that QM practices positively affect individual learning and LFQF. Quality rectification indirectly impacts LFQF via individual learning, while the results did not support the direct link between quality rectification and LFQF.

The findings strengthen practical insights into extracting experience from poor-quality issues and continuous improvement. The contributory factors of LFQF found in this study benefit the practitioners by taking effective measures to enhance organizational learning capability and improve the long-term construction quality performance in the grid infrastructure industry.

Existing research about the application of LFQF still stays at the explorative and conceptual stage. This study investigates the related factors of LFQF, including QM practices, quality rectification, and individual learning, extending the model development of learning from failures (LFF) in construction QM.

With the increasing requirements for intelligence in the field of aviation manufacturing, manual assembly can hardly adapt to the trend of future production. The purpose of this study is to realize the semi-automatic assembly of the movable airfoil by proposing a human-robot collaborative assembly strategy based on adaptive admittance control.

A logical judgment system for operating intentions is introduced in terms of different situations of the movements; hence, a human cognition-based adaptive admittance control method is developed to curb the damage of inertia; then virtual limit walls are raised on the periphery of the control model to ensure safety; finally, simulated and experimental comparisons with other admittance control methods are conducted to validate the proposed method.

The proposed method can save at least 28.8% of the time in the stopping phase which effectively compensates for inertia during the assembly process and has high robustness concerning data disturbances.

Due to the human-robot collaboration to achieve compliant assembly of movable airfoils can preserve human subjectivity while overcoming the physical limits of humans, which is of great significance to the investigation of intelligent aircraft assembly, the proposed method that reflects the user's naturalness and intuitiveness can not only enhance the stability and the flexibility of the manipulation, but also contribute to applications of industrial robots in the field of human-robot collaboration.