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According to the requirements of servicing and deorbiting the failure satellites, especially the tumbling ones on geosynchronous orbit, this paper aims to design a docking mechanism to capture these tumbling satellites in orbit, to analyze the dynamics of the docking system and to develop a new collision force-limited control method in various docking speeds.

The mechanism includes a cone-rod mechanism which captures the apogee engine with a full consideration of despinning and damping characteristics and a locking and releasing mechanism which rigidly connects the international standard interface ring (Marman rings, such as 937B, 1194 and 1194A mechanical interface). The docking mechanism was designed under-actuated, aimed to greatly reduce the difficulty of control and ensure the continuity, synchronization and force uniformity under the process of repeatedly capturing, despinning, locking and releasing the tumbling satellite. The dynamic model of docking mechanism was established, and the impact force was analyzed in the docking process. Furthermore, a collision detection and compliance control method is proposed by using the active force-limited Cartesian impedance control and passive damping mechanism design.

A variety of conditions were set for the docking kinematics and dynamics simulation. The simulation and low-speed docking experiment results showed that the force translation in the docking phase was stable, the mechanism design scheme was reasonable and feasible and the proposed force-limited Cartesian impedance control could detect the collision and keep the external force within the desired value.

The paper presents a universal docking mechanism and force-limited Cartesian impedance control approach to capture the tumbling non-cooperative satellite. The docking mechanism was designed under-actuated to greatly reduce the difficulty of control and ensure the continuity, synchronization and force uniformity. The dynamic model of docking mechanism was established. The impact force was controlled within desired value by using a combination of active force-limited control approach and passive damping mechanism.

This paper primarily aims to focus on a review of convolutional neural network (CNN)-based eye control systems. The performance of CNNs in big data has led to the development of eye control systems. Therefore, a review of eye control systems based on CNNs is helpful for future research.

In this paper, first, it covers the fundamentals of the eye control system as well as the fundamentals of CNNs. Second, the standard CNN model and the target detection model are summarized. The eye control system’s CNN gaze estimation approach and model are next described and summarized. Finally, the progress of the gaze estimation of the eye control system is discussed and anticipated.

The eye control system accomplishes the control effect using gaze estimation technology, which focuses on the features and information of the eyeball, eye movement and gaze, among other things. The traditional eye control system adopts pupil monitoring, pupil positioning, Hough algorithm and other methods. This study will focus on a CNN-based eye control system. First of all, the authors present the CNN model, which is effective in image identification, target detection and tracking. Furthermore, the CNN-based eye control system is separated into three categories: semantic information, monocular/binocular and full-face. Finally, three challenges linked to the development of an eye control system based on a CNN are discussed, along with possible solutions.

This research can provide theoretical and engineering basis for the eye control system platform. In addition, it also summarizes the ideas of predecessors to support the development of future research.

The purpose of this paper is to apply a intelligent algorithm to conduct the force tracking control for electrohydraulic servo system (EHSS). Specifically, the adaptive neuro-fuzzy inference system (ANFIS) is selected to improve the control performance for EHSS.

Two types of input–output data were chosen to train the ANFIS models. The inputs are the desired and actual forces, and the output is the current. The first type is to set a sinusoidal signal for the current to produce the actual driving force, and the desired force is chosen as same as the actual force. The other type is to give a sinusoidal signal for the desired force. Under the action of the PI controller, the actual force tracks the desired force, and the current is the output of the PI controller.

The models built based on the two types of data are separately named as the ANFIS I controller and the ANFIS II controller. The results reveal that the ANFIS I controller possesses the best performance in terms of overshoot, rise time and mean absolute error and show adaptivity to different tracking conditions, including sinusoidal signal tracking and sudden change signal tracking.

This paper is the first time to apply the ANFIS to optimize the force tracking control for EHSS.

The purpose of this paper is to study the aerodynamic characteristics of Ahmed body in longitudinal and lateral platoons under crosswind by computational fluid dynamics simulation. It helps to improve the aerodynamic characteristics of vehicles by providing theoretical basis and engineering direction for the development and progress of intelligent transportation.

A two-car platoon model is used to compare with the experiment to prove the accuracy of the simulation method. The simplified Ahmed body model and the Reynolds Averaged N-S equation method are used to study the aerodynamic characteristics of vehicles at different distances under cross-winds.

When the longitudinal distance x/L = 0.25, the drag coefficients of the middle and trailing cars at β = 30° are improved by about 272% and 160% compared with β = 10°. The side force coefficients of the middle and trailing cars are increased by 50% and 62%. When the lateral distance y/W = 0.25, the side force coefficients of left and middle cars at β = 30° are reduced by 38% and 37.5% compared with β = 10°. However, the side force coefficient of the right car are increased by about 84.3%.

Most of the researches focus on the overtaking process, and there are few researches on the neat lateral platoon. The innovation of this paper is that in addition to studying the aerodynamic characteristics of longitudinal driving, the aerodynamic characteristics of neat lateral driving are also studied, and crosswind conditions are added. The authors hope to contribute to the development of intelligent transportation.

The purpose of this paper is to investigate the optimal average drag coefficient of the Ahmed body for mixed platoon driving under crosswind and no crosswind conditions using the response surface optimization method. This study has extraordinary implications for the planning of future intelligent transportation.

First, the single vehicle and vehicle platoon models are validated. Second, the configuration with the lowest average drag coefficient under the two conditions is obtained by response surface optimization. At the same time, the aerodynamic characteristics of the mixed platoon driving under different conditions are also analyzed.

The configuration with the lowest average drag coefficient under no crosswind conditions is 0.3 L for longitudinal spacing and 0.8 W for lateral spacing, with an average drag coefficient of 0.1931. The configuration with the lowest average drag coefficient under crosswind conditions is 10° for yaw angle, 0.25 L for longitudinal spacing, and 0.8 W for lateral spacing, with an average drag coefficient of 0.2251. Compared to the single vehicle, the average drag coefficients for the two conditions are reduced by 25.1% and 41.3%, respectively.

This paper investigates the lowest average drag coefficient for mixed platoon driving under no crosswind and crosswind conditions using a response surface optimization method. The computational fluid dynamics (CFD) results of single vehicle and vehicle platoon are compared and verified with the experimental results to ensure the reliability of this study. The research results provide theoretical reference and guidance for the planning of intelligent transportation.

Urban MICE competitiveness research consists of two clusters, one that is public-statistics-based and another that is questionnaire-based. Supply-side research on urban MICE competitiveness is rare. Based on the findings of Chen (2014) and other scholars, the purpose of this paper is to design counterpart statistical indicators to empirically analyze CMCA member cities.

After calculating the standardized Z value of the original statistical data for 17 CMCA member cities, the authors conducted confirmatory factor analysis for the first-level principal components, based on which hierarchical clustering was performed; then, regression analysis was conducted with the MICE profit factor as the dependent variable and the cost factor, tight support factor and facilitating factor as the independent variables to support publishing articles.

The confirmatory factor analysis showed that the urban MICE competitiveness indicators from the supply-side perspective include the profit factor, cost factor, tight support factor and facilitating factor.

On the basis of research findings from the demand perspective and the literature review, the authors constructed an urban MICE competitiveness indicator system from the perspective of the supply side and conducted principal component analysis. However, because of the inaccessibility of panel data, the current data were only sufficient to conduct the research. If panel data could be acquired, further research could be conducted to perfect the current indicator system for urban MICE competitiveness.

The findings suggest that tourism total income, tourism foreign exchange income, inbound tourist number, number of exhibitions, exhibition area, number of UFI member cities and number of ICCA member cities were the main reason for the gap between different cities’ competitiveness and the reform focus for improving urban MICE competitiveness. The cost factor had a significantly negative influence on urban MICE competitiveness, implying that the higher the average hotel room price and revenue per available room, the less competitive the MICE host city is.

The tight support factor exerts a significant positive influence on urban MICE competitiveness from the supply-side perspective, while the cost factor exerts a significant negative influence. The findings suggest that the tourism total income, tourism foreign exchange income, inbound tourist number, number of exhibitions, exhibition area, number of UFI member cities and number of ICCA member cities were the main reason for the gap between different cities’ competitiveness and the reform focus for improving urban MICE competitiveness. The cost factor had a significantly negative influence on urban MICE competitiveness, implying that the higher the average hotel room price and revenue per available room, the less competitive the MICE host city is.

The research bridge the empirical statistics and the questionnaire-based perception study on urban MICE tourism image, and advance to construct an empirical statistics based indicator system for urban MICE tourism image.

The purpose of this paper is to present a symmetrical method to extract smooth signal from linear mixtures in the frequency domain; with experimentations, the method is thereafter evaluated.

The Second‐order Frequency Identification (SOFI) algorithm has been presented to retrieve baseband signals which have inactive bands and different bandwidths in the frequency domain. However, the SOFI method will bring about accumulative error, therefore an improved method is proposed in this paper by using symmetric extraction mode. In contrast to the SOFI algorithm, the ISOFI method can extract simultaneously the signal with the highest degree of smoothness and the signal with the lowest degree of smoothness. This means that the signals are not extracted one by one; instead, they are extracted in parallel. Experimental results in both noise‐free and noisy scenarios verified that the proposed method has a significant improvement compared with the SOFI algorithm.

An improved SOFI (ISOFI) method is proposed to reduce the accumulated error encountered in the SOFI algorithm. In the proposed method, the symmetric mode is utilized to extract in parallel the signals with different smooth degrees. Experimental results demonstrated that the ISOFI has a higher accuracy and lower accumulated error compared to the original algorithm.

The paper demonstrates use of the symmetric extraction mode to overcome the disadvantage of accumulated errors existing in the SOFI algorithm.

Wireless sensor networks, due to their potentially wide application perspectives, may proliferate in future. Two major stumbling blocks are the dynamic variance of the network caused by both the capacity constraint of sensor nodes and uncertainties of wireless links, and secure routing in the special security sensitive environment. Therefore, adaptable and defendable routing mechanism is in urgent need for the deployment of sensor networks. This paper aims to propose a feedback‐based secure routing protocol (FBSR).

Feedback from the neighboring nodes serves as the dynamic information of the current network, with which sensor nodes make forwarding decisions in a secure and energy aware manner. Feedback message is included in the MAC layer acknowledgement frame to avoid network congestion, and it is authenticated with the proposed Keyed One Way Hash Chain (Keyed‐OWHC) to avoid feedback fabrication. FBSR's resilience to node compromise is enhanced by statistic efforts accomplished by the base station.

Both mathematical analysis and simulation results show that FBSR is not only reliable but also energy efficient.

The paper introduces a novel routing scheme for wireless sensor networks.

Currently on additive manufacturing, extensive research is directed toward mitigating the main challenges associated with multi-material in fused filament fabrication which has a weak bonding strength between dissimilar materials. Low interfacial bonding strength leads to defects, anisotropy and temperature gradient in materials which negatively impact the mechanical performance of the multi-material prints. The purpose of this study was to assess the performance of different interface geometry designs in terms of the mechanical properties of the specimens.

Tensile test specimens were printed using: mono-material without a boundary interface, mono-material with the interface geometries (Face-to-face; U-shape; T-shape; Dovetail; Encapsulation; Mechanical interlocking; and Overlap) and multi-material with the interface geometries. The materials chosen with high and low compatibility were Tough polylactic acid (PLA) and TPU.

The main results of this study indicate that the interface geometries with the mechanical constriction between materials provide better structural integrity to the specimens. Moreover, in the case of the mono-material parts, the most effective interface design was the mechanical interlocking for both Tough PLA and TPU. On the other hand, in the case of multi-material specimens, the encapsulation showed the highest ultimate tensile strength, whereas the overlap and T-shape presented more robust bonding.

This study examines the mechanical performance, particularly tensile strength, strain at break, Young’s modulus and yield strength of different interface designs which were not studied in the previous studies.