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This study aims to explore the impact of high-performance work systems (HPWS) on open innovation and the moderating role of information technology (IT) capability on the relationship between HPWS and open innovation.

This study conducted a questionnaire survey in the industrial parks of the Yangzi River Delta in China and obtained 108 useful responses.

HPWS positively impacts open innovation. IT exploration capability strengthens the relationship between HPWS and open innovation, whereas IT exploitation capability and ambidexterity do not strengthen such relationship.

Firms should use HPWS to improve employees' motivation of external learning and searching for enhancing innovation openness. They should acknowledge the enabling role of IT exploration capability in facilitating employees' learning and searching toward open innovation and discreetly develop IT exploitation capability and ambidexterity during external knowledge searching, which may not achieve the desired facilitation purpose.

This study contributes to human resource management (HRM) by suggesting that a new antecedent, which is HPWS in our case, should be taken into account when considering the influence of HRM in the process of open innovation. This study has important implications for HPWS, IT capability and open innovation; open innovation can be improved by using HPWS and IT capability. This study also expands IT ambidexterity to HRM and innovation studies.

Precise vehicle localization is a basic and critical technique for various intelligent transportation system (ITS) applications. It also needs to adapt to the complex road environments in real-time. The global positioning system and the strap-down inertial navigation system are two common techniques in the field of vehicle localization. However, the localization accuracy, reliability and real-time performance of these two techniques can not satisfy the requirement of some critical ITS applications such as collision avoiding, vision enhancement and automatic parking. Aiming at the problems above, this paper aims to propose a precise vehicle ego-localization method based on image matching.

This study included three steps, Step 1, extraction of feature points. After getting the image, the local features in the pavement images were extracted using an improved speeded up robust features algorithm. Step 2, eliminate mismatch points. Using a random sample consensus algorithm to eliminate mismatched points of road image and make match point pairs more robust. Step 3, matching of feature points and trajectory generation.

Through the matching and validation of the extracted local feature points, the relative translation and rotation offsets between two consecutive pavement images were calculated, eventually, the trajectory of the vehicle was generated.

The experimental results show that the studied algorithm has an accuracy at decimeter-level and it fully meets the demand of the lane-level positioning in some critical ITS applications.

The purpose of this paper is to propose a robust control scheme for near space vehicle's (NSV's) reentry attitude tracking problem under aerodynamic parameter variations and external disturbances.

The robust control scheme is composed of dynamic surface control (DSC) and least squares support vector machines (LS‐SVM). DSC is used to design a nonlinear controller for HSV; then, to increase the robustness and improve the control performance of the controller. LS‐SVM is presented to estimate the lumped uncertainties, including aerodynamic parameter variations and external disturbances. The stability analysis shows that all closed‐loop signals are bounded, with output tracking error and estimate error of LS‐SVM weights exponentially converging to small compacts.

Simulation results demonstrate that the proposed method is effective, leading to promising performance.

First, a robust control scheme composed of DSC and adaptive LS‐SVM is proposed for NSV's reentry attitude tracking problem under aerodynamic parameter variations and external disturbances; second, the proposed method can achieve more favorable tracking performances than conventional dynamic surface control because of employing LS‐SVM to estimate aerodynamic parameter variations and external disturbances.

To ensure accurate position and force control of massage robot working on human body with unknown skin characteristics, this study aims to propose a novel intelligent impedance control system.

First, a skin dynamic model (SDM) is introduced to describe force-deformation on the human body as feed-forward for force control. Then a particle swarm optimization (PSO) method combined with graph-based knowledge transfer learning (GKT) is studied, which will effectively identify personalized skin parameters. Finally, a self-tuning impedance control strategy is designed to accommodate uncertainty of skin dynamics, system delay and signal noise exist in practical applications.

Compared with traditional least square method, genetic algorithm and other kinds of PSO methods, combination of PSO and GKT is validated using experimental data to improve the accuracy and convergence of identification results. The force control is effective, although there are contour errors, control delay and noise problems when the robot does massage on human body.

Integrating GKT into PSO identification algorithm, and designing an adaptive impedance control algorithm. As a result, the robot can understand textural and biological attributes of its surroundings and adapt its planning activities to carry out a stable and accurate force tracking control during dynamic contacts between a robot and a human.

This study is an inquiry into practical solutions in the field of emergent disaster rescue methods and prevention management, and it focuses on planning, real‐time rescue, and emergency management. This study is a conventional writing style. Thus, the purpose of this study is to offer methods for governor reducing disaster losses in terms of human life and livelihoods.

The government should establish permanent disaster recovery institutions, such as disaster recovery coordinators, resource distributors at the provincial or state level, and nodes in districts to manage supplies, rescue activities. During the preparation stage of disaster responses, government offices must prepare the rescue plans and policies for future disasters, as well as create the documents for establishing part‐time civilian and volunteer agreements.

Even though residents suffer tremendous losses in terms of human life, regional administrators are usually and poorly organized at the preparation stage.

Disaster rescue activities depend heavily on civilians and organizations. A disaster rescue manager plays a key role, because he or she has received training in and has become familiar with emergent rescue operations.

Disaster rescue management is a valuable topic because it is a globally significant challenge to safeguard people's lives. A complex disaster of earthquakes and tsunamis occurring can give rise to nuclear radiation damage, for example, that occurred in Japan on March 11, 2011, is an illustrative case.