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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.

The purpose of this paper is to take advantage of Internet of Things (IoT) for intelligent route programming of crowd emergency evacuation in metro station. It is a novel approach to ensure the crowd safety and reduce the casualties in the emergency context. An evacuation route programming model is constructed to select a suitable evacuation route and support the emergency decision maker of metro station.

The IoT technology is employed to collect and screen information, and to construct an expert decision model to support the metro station manager to make decision. As a feasible way to solve the multiple criteria decision-making problem, an improved multi-attributive border approximation area comparison (MABAC) approach is introduced.

The case study indicates that the model provides valuable suggestions for evacuation route programming and offers practical support for the design of an evacuation route guidance system. Moreover, IoT plays an important role in the process of intelligent route programming of crowd emergency evacuation in metro station. A library has similar structure and crowd characteristics of a metro station, thus the intelligent route programming approach can be applied to the library crowd evacuation.

The highlights of this paper are listed as followings: the accuracy and accessibility of the metro station’s real-time information are improved by integrating IoT technology with the intelligent route programming of crowd emergency evacuation. An improved MABAC approach is introduced to the expert support model. It promotes the applicability and reliability of decision making for emergency evacuation route selection in metro station. It is a novel way to combine the decision-making methods with practice.

This study aims to determine how and through what mechanisms the outward foreign direct investment (OFDI) promotion effect of the Belt and Road initiative (BRI-OFDI) affects domestic investment. It is motivated by the context that China is fostering a new development pattern, as well as by the impetus from the Belt and Road initiative for the new pattern.

Drawing on data of Chinese-listed companies, this study uses a difference-in-difference method to explore the effect of the BRI-OFDI on domestic investment and a mediation model to illustrate the mechanisms.

The BRI-OFDI has a significantly positive effect on domestic investment, meaning that the Belt and Road initiative's OFDI promotion effect crowds in domestic investment. The results are heterogeneous: the crowding-in effect mainly exists in non-state-owned and technology-intensive enterprises, while a crowding-out effect is seen in state-owned and labor-intensive enterprises. The easing of corporate financing constraints and the expansion of market demand are two important mechanisms.

This study uses the Belt and Road initiative as an exogenous shock to investigate the impact of the initiative-induced OFDI promotion effect on domestic investment. It addresses the potential endogeneity issue confronting the studies on the relationship between OFDI and domestic investment in the literature. The authors focus on the possible spillover effects of the Belt and Road initiative discussing the impact of the BRI-OFDI on domestic investment from the micro-firm perspective. It offers a new perspective to objectively assess the initiative's policy effect.

This study aims to study the connected vehicle (CV) impact on highway operational performance under a mixed CV and regular vehicle (RV) environment.

The authors implemented a mixed traffic flow model, along with a CV speed control model, in the simulation environment. According to the different traffic characteristics between CVs and RVs, this research first analyzed how the operation of CVs can affect highway capacity under both one-lane and multi-lane cases. A hypothesis was then made that there shall exist a critical CV penetration rate that can significantly show the benefit of CV to the overall traffic. To prove this concept, this study simulated the mixed traffic pattern under various conditions.

The results of this research revealed that performing optimal speed control to CVs will concurrently benefit RVs by improving highway capacity. Furthermore, a critical CV penetration rate should exist at a specified traffic demand level, which can significantly reduce the speed difference between RVs and CVs. The results offer effective insight to understand the potential impacts of different CV penetration rates on highway operation performance.

This approach assumes that there shall exist a critical CV penetration rate that can maximize the benefits of CV implementations. CV penetration rate (the proportion of CVs in mixed traffic) is the key factor affecting the impacts of CV on freeway operational performance. The evaluation criteria for freeway operational performance are using average travel time under different given traffic demand patterns.

With the acceleration of global energy structure transformation, hydrogen has been widely used for its non-pollution and high efficiency, and hydrogen detection is used to guarantee the hydrogen safety. The purpose of this paper is to study the research foundation, trend and hotspots of hydrogen detection field.

A total of 4,076 literature records from 2000 to 2021 were retrieved from the core collection of the Web of Science database selected as data sources. The literature information mining was realized by using CiteSpace software. Bibliometrics was used to analyze information, such as keywords, authors, journals, institutions, countries and cited references, and to track research hotspots.

Since the 21st century, the number of publications in the hydrogen detection field has been in a stable stepped uptrend. In terms of research foundation, the hotspots such as core-shell structures, nano-hybrid materials and optical fiber hydrogen sensors have been studied extensively. In combination with the discipline structure and research frontier, the selectivity, sensitivity, response speed and other performance parameters of hydrogen sensors need further improvement. The establishment of an interdisciplinary knowledge system centered on materials science and electronic science will become a long-term trend in the research of hydrogen detection.

This study presents an overview of research status, hotspots and laws in hydrogen detection field, through the quantitative analysis of much literature in the field and the use of data mining, so as to provide credible references for the research of hydrogen detection technology.

To solve the water resources deployment problem which is a multi‐objective nonlinear problem with the characteristic of space‐time variability, involving many factors, such as economy, society, ecology, environment and projects.

Coupling the characteristic of multi‐objective with chaotic optimization, a multi‐objective chaotic optimization algorithm (MCOA) is proposed for optimal water resources deployment. The algorithm magnifies the chaotic series generated by logistic mapping to the feasible region, and seeks the best results by iterative comparison which can avoid the difficulties that objective functions and the constraints should be continuous and differentiable. MCOA is a global optimization method and has high efficiency.

The proposed algorithm is applied to the optimal deployment of water resources in a certain river basin. The rationality of results is verified by the entropy change theory. The results indicate that the optimal water resources deployment can be realized using the proposed algorithm in a more rational way.

The numbers and the bounds of variables are the main limitations which the algorithm will be applied.

A very useful optimization algorithm for optimal water resources deployment.

The paper highlights the new optimization algorithm for optimal water resources deployment due to the MCOA.

A binary-tree subdivision method (BTSM) for numerical evaluation of weakly singular integrals with discontinuous kernel in the three-dimensional (3D) boundary element method (BEM) is presented in this paper.

In this method, the singular boundary element is split into two sub-elements and subdivided recursively until the termination criterion is met and the subdivision is stopped. Then, the source point is surrounded by one or more spherical cavities determined by the discontinuous kernel function. The sub-elements located in spherical cavities will be eliminated, and the regular triangular or rectangle elements are employed to fill the spherical cavities.

With the proposed method, the obtained sub-elements are automatically refined as they approach the source point, and they are “good” in shape and size for standard Gaussian quadrature. Thus, the proposed method can be used to evaluate singular integrals owing discontinuous kernel function accurately for cases of different element shapes and various source point locations.

Numerical examples show that the BTSM is suitable for planar and curved elements of arbitrary regular or irregular shape at various source point locations, and the results have much better accuracy and robustness than conventional subdivision method (CSM) when the kernel function is discontinuous.

In the context of fixed-wing aircraft wing assembly, there is a need for a rapid and precise measurement technique to determine the center distance between two double-hole components. This paper aims to propose an optical-based spatial point distance measurement technique using the spatial triangulation method. The purpose of this paper is to design a specialized measurement system, specifically a spherically mounted retroreflector nest (SMR nest), equipped with two laser displacement sensors and a rotary encoder as the core to achieve accurate distance measurements between the double holes.

To develop an efficient and accurate measurement system, the paper uses a combination of laser displacement sensors and a rotary encoder within the SMR nest. The system is designed, implemented and tested to meet the requirements of precise distance measurement. Software and hardware components have been developed and integrated for validation.

The optical-based distance measurement system achieves high precision at 0.04 mm and repeatability at 0.02 mm within a range of 412.084 mm to 1,590.591 mm. These results validate its suitability for efficient assembly processes, eliminating repetitive errors in aircraft wing assembly.

This paper proposes an optical-based spatial point distance measurement technique, as well as a unique design of a SMR nest and the introduction of two novel calibration techniques, all of which are validated by the developed software and hardware platform.

The purpose of this paper is to present an adaptive binary-tree element subdivision method (BTSM) for the evaluation of nearly singular integrals in three-dimensional boundary element method, which can facilitate automatic and high-quality patch generation.

In this method, the nearly singular element is split into two sub-elements. Each sub-element is then examined to determine if it is to be subdivided based on a specific subdivision criterion. The specific subdivision ensures that those sub-elements far from the source point are sparse. And then those sub-elements in close proximity to the source point are replaced by regular triangular elements.

With the proposed method, the sub-elements obtained are automatically refined as they approach the projection point, and they are “good” in shape and size for standard Gaussian quadrature. Thus, the proposed method can be used to evaluate nearly singular integrals accurately for cases of different element shapes and various locations of the source point.

Numerical examples for surface elements with various relative locations of the source point are presented. The results demonstrate that the proposed method has much better accuracy and robustness than some other methods.