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The partition of unity of the standard meshless Galerkin method is used as basis in expressing the discontinuity of the contact surface displacement, particularly by adding discontinuous terms into the displacement mode, and constructing the discontinuous meshless displacement field function. In this study the contact surface equation is aimed to derive from the improved Coulomb friction contact model.

In this paper based on the basic idea of meshless method, an improved moving least squares approximation function (expansion method based on out of unit division) is applied to the analysis of two-dimensional contact problems.

On the basis of this equation after discrete processing, it is combined with the discrete form of the virtual work equation with added contact conditions, and eventually transformed into a standard linear complementary problem. Moreover, it is solved by using the Lemke algorithm, and a corresponding example is provided in this research.

The proposed method can effectively control the mutual embedding of the contact surface, and the stress distribution that is the same as the actual situation can be obtained on the contact surface.

Robotic wire and arc additive manufacturing (RWAAM) is becoming more and more popular for its capability of fabricating metallic parts with complicated structure. To unlock the potential of 6-DOF industrial robots and improve the power of additive manufacturing, this paper aims to present a method to fabricate curved overhanging thin-walled parts free from turn table and support structures.

Five groups of straight inclined thin-walled parts with different angles were fabricated with the torch aligned with the inclination angle using RWAAM, and the angle precision was verified by recording the growth of each layer in both horizontal and vertical directions; furthermore, the experimental phenomena was explained with the force model of the molten pool and the forming characteristics was investigated. Based on the results above, an algorithm for fabricating curved overhanging thin-walled part was presented and validated.

The force model and forming characteristics during the RWAAM process were investigated. Based on the result, the influence of the torch orientation on the weld pool flow was used to control the pool flow, then a practical algorithm for fabricating curved overhanging thin-walled part was proposed and validated.

Regarding the fabrication of curved overhanging thin-walled parts, given the influences of the torch angles on the deposited morphology, porosity formation rate and weld pool flow, the flexibility of 6-DOF industrial robot was fully used to realize instant adjustment of the torch angle. In this paper, the deposition point and torch orientation of each layer of a robotic fabrication path was determined by the contour equation of the curve surface. By adjusting the torch angle, the pool flow was controlled and better forming quality was acquired.

This paper aims to review the critical technology development of avian radar system at airports.

After the origin of avian radar technology is discussed, the target characteristics of flying birds are analyzed, including the target echo amplitude, flight speed, flight height, trajectory and micro-Doppler. Four typical airport avian radar systems of Merlin, Accipiter, Robin and CAST are introduced. The performance of different modules such as antenna, target detection and tracking, target recognition and classification, analysis of bird information together determines the detection ability of avian radar. The performances and key technologies of the ubiquitous avian radar are summarized and compared with other systems, and their applications, deployment modes, as well as their advantages and disadvantages are introduced and analyzed.

The ubiquitous avian radar achieves the long-time integration of target echoes, which greatly improves detection and classification ability of the targets of birds or drones, even under strong background clutter at airport. In addition, based on the big data of bird situation accumulated by avian radar, the rules of bird activity around the airport can be mined to guide the bird avoidance work.

This paper presented a novel avian radar system based on ubiquitous digital radar technology. The authors’ experience has confirmed that this system can be effective for airport bird strike prevention and management. In the future, the avian radar system will see continued improvement in both software and hardware, as the system is designed to be easily extensible.

This study aims to investigate if smartphone sensors can be used in an unmanned aerial vehicle (UAV) localization system. With the development of technology, smartphones have been tentatively used in micro-UAVs due to their lightweight, inexpensiveness and flexibility. In this study, a Samsung Galaxy S3 smartphone is selected as an on-board sensor platform for UAV localization in Global Positioning System (GPS)-denied environments and two main issues are investigated: Are the phone sensors appropriate for UAV localization? If yes, what are the boundary conditions of employing them?

Efficient accuracy estimation methodologies for the phone sensors are proposed without using any expensive instruments. Using these methods, one can estimate his phone sensors accuracy at any time without special instruments. Then, a visual-inertial odometry scheme is introduced to evaluate the phone sensors-based path estimation performance.

Boundary conditions of using smartphone in a UAV navigation system are found. Both indoor and outdoor localization experiments are carried out and experimental results validate the effectiveness of the boundary conditions and the corresponding implemented scheme.

With the phone as a payload, UAVs can be further realized in smaller scale at lower cost, which will be used widely in the field of industrial robots.

Five-level rectifiers have received widespread attention because of their excellent performance in high-voltage and high-power applications. Taking a five-level rectifier with only four-IGBT for this study, a sliding mode predictive control (SMPC) algorithm is proposed to solve the problem of poor dynamic performance and poor anti-disturbance ability under the traditional model predictive control with the PI outer loop.

First, mathematical models under the two-phase stationary coordinate system and two-phase synchronous rotating coordinate system are established. Then, the design of the outer-loop sliding mode controller is completed by establishing the sliding mode surface and design approach rate. The design of the inner-loop model predictive controller was completed by discretizing the mathematical model equations. The modulation part uses a space vector modulation technique to generate the PWM wave.

The sliding mode predictive control strategy is compared with the control strategy with a PI outer loop and a model predictive inner loop. The proposed control strategy has a faster dynamic response and stronger anti-interference ability.

For the five-level rectifier, the advantages of fast dynamic influence and parameter insensitivity of sliding mode control are used in the voltage outer loop to replace the traditional PI control, and which is integrated with the model predictive control used in the current inner loop to form a novel control strategy with a faster dynamic response and stronger immunity to disturbances. This novel strategy is called sliding mode predictive control (SMC).

It is shown in natural gas proportion mixing experiments that a mixed-source natural gas is the physical combination of end member gas. Both the carbon and hydrogen isotopes in the mixed-source natural gas can be expressed by the weighted average of corresponding components content and isotopes of end member gas. Under certain geological setting, the selection of end member gas is the key to mixed-source ratio calculation. Then, it's better to estimate the mixed-source ratio with δ¹³C₁ and component data according to the weighted average calculation formula. The analysis on natural gas geochemistry characteristics show that the natural gas extracted from Jingbian Gas Field in the Ordos Basin is mainly an upper Paleozoic coal-derived gas. In the analysis of geological conditions for reservoir forming and characteristics of natural gas, natural gas from Longtan 1 Well and Tao 6 Well were selected as the end member gases of lower Paleozoic oil-type gas and upper Paleozoic coal-type gas respectively to calculate the mixed-source ratio of natural gas in Jingbian Gas Field. The ratio of upper Paleozoic coal-derived gas mostly accounts for over 70% and its average ratio reaches 81%. Therefore, the exploration of natural gas of Ordos Basin should be focused on the upper palaeozoic coal source rock, and attention should be paid to the matching of coal source rock in the exploration of weathered crust gas deposit.

The construction of geographical indications agri-food (GIAF) brands play an important role in rural revitalization in China, this study aims to explore how to jointly promote brand building among multiple parties.

A tripartite game model of the producers, sales operating enterprises, and local governments is constructed to analyze the strategy choice of the parties in the complex system behavior evolution stability, and the simulation analysis of the influence factors of brand construction of GIAF and verify the game result.

(1) Increased government subsidies and supervision costs are beneficial to accelerating variety improvement and quality improvement of agri-food, but it is not conducive to the government, Therefore, it is necessary to ensure that the subsidy and supervision cost is kept within a reasonable range; (2) The dividend distributed to producers by sales operating enterprises play an important role in encouraging producers to improve the quality safety of agri-food, but it must be kept within a reasonable range to avoid discouraging the enthusiasm of sales operating enterprises; (3) Cost reduction, and revenue improvement are also effective ways to cooperate with all parties in brand co-construction.

This study does not consider consumers or logistics companies in the evolutionary game model.

This study proposes innovative policies and suggestions for improvement of the brand co-construction of all parties.

Based on the “Rural Revitalization” initiative, this study enriches research methods about brand value and provides a new perspective for brand value co-construction, and theoretical guidance, and empirical basis for formulating innovation policies and recommendations.

This paper explores the driving factors of parasocial relationship (PSR) in the virtual reality (VR) shopping environment, and how this relationship affects brand equity. The study also investigates the moderating role of the celebrity endorser dynamism (CED) in the relationship between PSR and its antecedents.

The primary data collection tool is a survey administered to Chinese consumers (n = 531) who have experienced the products of UNIQLO brand on Taobao Buy + platform, and who had a PSR with the endorser in their VR shopping process. Structural equation modeling is employed to examine the hypothesized relationships among all variables.

The findings show that VR shopping factors (i.e. physical attractiveness, social presence and technology novelty) perceived by consumers to affect PSR, and this relationship and brand equity are positively associated, while CED moderates the relationship between PSR and its antecedents.

This study sheds light on how PSR in the VR shopping environment can improve brand equity. It contributes to the theory of PSR and persuasion as well as marketing strategies. From a managerial perspective, guidelines are provided for firms to implement value communication activities using VR, and to increase their brand equity.

Online ratings (review valence) have been found to exert a strong influence on hotel room prices. This study aims to systematically synthesize research estimating the impact of online ratings on room rates using a meta-analytical method.

From major academic databases, a total of 163 estimates of the effects of online ratings on room rates were coded from 22 studies across different countries through a systematic review of relevant literature. All estimates were converted into elasticity-type effect sizes, and a hierarchical linear meta-regression was used to investigate factors explaining variations in the effect sizes.

The median elasticity of online ratings on hotel room rates was estimated to be 0.851. Meta-regression results highlighted four categories of factors moderating the size of this elasticity: data characteristics, research settings, variable measures and publication outlet. Among sub-ratings, results revealed value rating and room rating to exert the largest impact on room rates, whereas staff and cleanliness ratings demonstrated non-significant impacts.

This study provides practical implications on the relative importance of different types of online ratings for online reputation and revenue management.

This study represents the first research effort to understand factors moderating the effects of online ratings on hotel room rates based on a quantitative review of the literature. Moreover, this study provides beneficial insights into the specification of empirical hedonic pricing models and data-collection strategies, such as the selection of price variables and choices of model functional forms.

There is increasing desire and need in research of water region detection owing to the unexpected natural disaster that lead to financial, environment and human losses. Surveying of water region and research on its feature is very basic step for many planning, especially for countries like Japan, where tsunami has caused the changes on water region in March, 2011. Essentially, identifying water region from satellite images is one of the grand steps of water resources management for a country. Professional and academic institutions play a vital role in the management of water resources as they are instrumental in research. The objective of this paper is to identify the water region from satellite image. In this paper, the segmentation algorithm based on SOM (self-organizing map) neural network with compression pre-processing by wavelet transform and image smoothing using Gaussian low-pass frequency domain filters are presented.