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The purpose of this paper is to describe a strap‐down image stable strategy for multi‐load optoelectronic imaging platform hung below a tethered aerostat.

Four two dimension pods, each with a visible light camera, are fixed on the optoelectronic platform. A POS (Position and Orientation System) is used to acquire the attitude rate data of optoelectronic platform, while the data can be coupled to the pods' servo systems through corresponding coordinate rotation, then the motors of pods will adjust the line of sight to the opposite way to keep the stabilization of image exported by visible light camcorders. Simultaneously, two rate gyros are installed at the inner frame of each pod, which are used as a backup to avoid the failure of POS.

Using one attitude and position measurement system can realize the stabilization of multi optoelectronic pods, which is same as or even better than the ratio gyro stabilization.

As the tethered aerostat is a flexible body, it is affected a lot by the wind speed and wind direction at the low height (<1,000 m), which leads to the motors of pods always adjust the line of sight to the mechanical limiting of pods.

Strap‐down stabilization technology has been successfully used in the tethered aerostat monitoring platform to surveillance Shanghai World EXPO site. Long time experiments verify the feasible and effective of the multi‐load stabilization technology. The impact on the image by the adjustment of servos is less than 10 percent of the whole view of sight.

The paper introduces a strap‐down stabilization technology for multi‐load tethered aerostat platform, which is more suitable to be applied in the platform of relatively minor attitude change, like the airborne multi‐load platform and multi‐load UAV (unmanned aerial vehicle) platform.

The purpose of this paper is to summarize the advances in grey system theory research and various application achievements in science and engineering. At the same time, it commemorates the 40th anniversary of the birth of grey system theory and the 10th anniversary of Grey Systems–Theory and Application.

Firstly, the innovations of theoretical research in grey system theory were summarized and some of the widely recognized new results are briefly described. By searching and combing the research results of grey system theory in China national knowledge infrastructure (CNKI) database and Web of Science by Institute for Scientific Information (ISI), this paper shows the rapid development trend of grey system theory in the past 40 years, and the successful applications of grey system theory in the fields of social sciences, natural sciences and engineering technologies.

More than 227 thousands literature were found by input 10 phrases such as grey system, grey number and sequence operator etc. in CNKI database. After entering the new century, the number of grey system papers included in CNKI database is increasing rapidly. Since 2008, more than 10 thousands papers have been included per year and more than 15 thousands papers have been included per year since 2014. Grey system method and model are widely used in physics, chemistry, biology and other fields of natural science, as well as transportation, electric power, machinery and other fields of engineering technology, and a large number of valuable results have been achieved.

It can be seen that the grey system theory plays an important role in promoting China’s scientific and technological progress, innovation and development and high-level talent training from tens of thousands of literatures marked with important national science and technology projects and a large number of grey system literatures published by China’s double first-class universities and double first-class discipline construction universities.

Both innovations of theoretical research and practical application play important role in the growth of new theory. The innovations of theoretical research provide methods and tools for practical application, which is conducive to improve application efficiency and broaden application fields. A large number of practical applications needs have become the source of theoretical innovation and the solid background for the birth of theoretical innovation achievements.

With the development of deep learning-based analytical techniques, increased research has focused on fatigue data analysis methods based on deep learning, which are gaining in popularity. However, the application of deep neural networks in the material science domain is mainly inhibited by data availability. In this paper, to overcome the difficulty of multifactor fatigue life prediction with small data sets,

A multiple neural network ensemble (MNNE) is used, and an MNNE with a general and flexible explicit function is developed to accurately quantify the complicated relationships hidden in multivariable data sets. Moreover, a variational autoencoder-based data generator is trained with small sample sets to expand the size of the training data set. A comparative study involving the proposed method and traditional models is performed. In addition, a filtering rule based on the R2 score is proposed and applied in the training process of the MNNE, and this approach has a beneficial effect on the prediction accuracy and generalization ability.

A comparative study involving the proposed method and traditional models is performed. The comparative experiment confirms that the use of hybrid data can improve the accuracy and generalization ability of the deep neural network and that the MNNE outperforms support vector machines, multilayer perceptron and deep neural network models based on the goodness of fit and robustness in the small sample case.

The experimental results imply that the proposed algorithm is a sophisticated and promising multivariate method for predicting the contact fatigue life of a coating when data availability is limited.

A data generated model based on variational autoencoder was used to make up lack of data. An MNNE method was proposed to apply in the small data case of fatigue life prediction.

The purpose of this study was to fabricate silicone products that had different hardnesses and moduli, thus partially addressing the limitations of homogeneous materials whose deformation depends on altered structure or dimensions, and to provide new dimensions for the design of silicone soft structures.

A soft material three-dimensional printing platform with a dual-channel printing capability was designed and built. Using the material extrusion method, material screening was first performed using single-channel printing, followed by dual-channel-regulated printing experiments on products having different hardness and modulus values.

The proportion of additives has an effect on the accuracy of the printed product. Material screening revealed that Sylgard 527 and SE 1700 could be printed without additives. The hardness and mechanical properties of products are related to the percentage in their composition of hard and soft materials. The hardness of the products could be adjusted from 26A to 42A and the Young’s modulus from 0.875 to 2.378 Mpa.

Existing silicone products molded by casting or printing are mostly composed of a single material, whose uniform hardness and modulus cannot meet the demand for differentiated deformation in the structure. The existing multihardness silicone material printing method has the problems of long material mixing time and slow hardness switching and complicated multi-extrusion head switching. In this study, a simple, low-cost and responsive material extrusion-based hardness programmable preparation method for silicone materials is proposed.

The purpose of this study is to design and process the optimal V-shaped microstructure for 7075 aluminum alloy and reveal its wear resistance mechanism and performance.

The hydrodynamic pressure lubrication models of the nontextured, V-shaped, circular and square microtextures are established. The corresponding oil film pressure distributions are explored. The friction and wear experiments are conducted on a rotating device. The effects of the microstructure shapes and sizes on the wear mechanisms are investigated via the friction coefficients and surface morphologies.

In comparison, the V-shaped microtexture has the largest oil film carrying capacity and the lowest friction coefficient. The wear mechanism of the V-shaped microtexture is dominated by abrasive and adhesive wear. The V-shaped microtexture has excellent wear resistance under a side length of 300 µm, an interval of 300 µm and a depth of 20 µm.

This study is conductive to the design of wear-resistant surfaces for friction components.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

The purpose of this paper is to obtain risk indicators of water security of drought periods in which the indices of reliability, resiliency, and vulnerability are integrated.

It is not reasonable that weight coefficients of different risk indices are often determined subjectively in conventional procedures, so the entropy weight method is introduced and chosen to solve the problem. Entropy weight method can get the weight coefficients of different risk indices objectively and is valid from the case study.

The feasibility and validity of entropy weight methods to determine weight coefficients of different risk indices objectively are recognized.

Accessibility and availability of data are the main limitations.

The paper provides a more objective risk indicator of water security of drought periods for water resources managers.

This paper determines the weight coefficients of different risk indices for risk assessment of water security of drought periods based on hazard entropy. The paper is aimed at water resources managers and relative researchers, especially those who deal with risk assessment of water security of drought periods.

An electrochemical method based on the open circuit potential (OCP) fluctuations was put forward. It can be used to optimize the alloy compositions for improving the corrosion resistance of rust layer.

The potential trends and potential fluctuations of carbon steels in seawater were separated by Hodrick–Prescott filter. The Spearman correlation coefficient and max information coefficient were used to explore the correlation of alloy compositions and potential fluctuations.

After long-term immersion, potential fluctuation resistance (PFR) can be used to characterize the corrosion resistance of metals and its rust layers. In the 1,500 to 2,500 h exposure period, Fe, C and S compositions have strong negative correlations, whereas PFR and P composition have weak negative correlations. Mn, Cu and Ti alloy compositions help the rust layer of carbon steels have higher PFRs. These elements that exhibit higher PFRs in this period have been confirmed to have the effect on improving the corrosion resistance of rust layer.

A new computing method for alloy composition optimization of carbon steels based on the OCP fluctuations was put forward. This method combines electrochemical monitoring with the long-term actual seawater environmental tests of various carbon steels.