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In view of the drawback of traditional deterministic prediction that it cannot provide uncertainty information, this study proposed a prediction model that integrates point estimation and interval estimation, and innovatively applied it to the field of food safety risk pre-warning. In the point estimation, wavelet packet decomposition (WPD) was used to decompose the weekly risk level sequence and the autoregressive integrated moving average (ARIMA) model was used for prediction. In the interval estimation, the generalized autoregressive conditional heteroskedastic (GARCH) model was used to predict the residual. The WPD-ARIMA-GARCH model established in this study was applied to the safety risk prediction of soy sauce and pot-roast meat products from a certain region. The results showed that the safety risk of soy sauce and pot-roast meat products from this region was relatively high at the end of March and July in 2019, which was consistent with the actual situation. Meanwhile, in the risk prediction of soy sauce and pot-roast meat products from 10 different regions, the mean square error, mean absolute error, and mean absolute percentage error of the model were 1.626, 0.806, and 20.824, respectively, and the prediction interval normalized average and coverage width-based criterion values at the 90% confidence interval were both 0.024, which could cover all true values. Therefore, the model has high prediction accuracy and low error, is useful for risk control for the quality and safety of soy sauce and pot-roast meat products, and provide technical support for daily food safety supervision.

A coal gangue detection method in coal preparation plant based on YOLOv5s-FSW model is proposed to address the problems of insufficient feature extraction, large parameter quantity, low detection precision, and poor real-time performance in existing coal gangue detection models. This model is improved on the basis of YOLOv5s. Firstly, the C3 module in the Backbone section is replaced with a FasterNet Block structure, which improves detection speed by reducing the number of model parameters and computation. Secondly, in the Neck section, a parameter free SimAM attention mechanism is introduced to enhance the model's attention to important targets in complex environments, further improving the model's feature extraction capability. Finally, in the Prediction layer, the CIoU bounding box loss function is replaced with Wise-IoU, and the model focuses on ordinary quality anchor boxes to improve convergence speed and bounding box detection precision. The results of the ablation experiment indicate that compared with the YOLOv5s model, The mean average precision (mAP) of the YOLOv5s-FSW model has been improved by 1.9%, the model weight has been reduced by 0.6 MiB, the number of parameters has been reduced by 4.7%, and the detection speed has been improved by 19.3%. The comparative experimental results show that the YOLOv5s-FSW model has a mAP of 95.8%, which is 1.1%, 1.5%, and 1.2% higher compared to the YOLOv5s-CBC, YOLOv5s-ASA, and YOLOv5s-SDE models, respectively, and compared to YOLOv5m, YOLOv6s improved by 0.3%, 0.6% respectively. The detection speed of the YOLOv5s-FSW reaches 36.4 frames per second, which is 28.2% and 20.5% higher than the YOLOv5s-CBC and YOLOv5s-ASA models, respectively. Compared to YOLOv5m, YOLOv6s and YOLOv7, the detection speed of the YOLOv5s-FSW has increased by 16.3%, 15.2%, and 45.0%, respectively. The visualization experiment results of the thermal map show that the YOLOv5s-FSW model is more sensitive to the target feature areas of coal gangue and has higher attention. The detection experiment results show that in complex scenes with dim environments, blurred images, and mutual occlusion of targets, the YOLOv5s-FSW model has a higher confidence score for coal gangue target detection than the YOLOv5s model, and effectively avoids the occurrence of false positives and missed detection.

Using radiation-variation insensitivity feature transform (RIFT) to calculate feature descriptors and perform feature matching on the maximum index map (MIM) is time-consuming. To solve this problem, an algorithm named binary descriptor for RIFT (BRIFT) is proposed. First, the phase consistency of the image is calculated and the MIM is obtained. Then, the feature descriptor is calculated and binarized through fast algorithm on MIM. Finally, the descriptor of each feature point is matched based on Hamming distance. Taking the remote sensing images with various geometric distortions and non-linear radiation distortions as the test data, the BRIFT algorithm is compared with other feature matching algorithms including SIFT, BRISK, BRIEF, RIFT. The comparison result shows that the proposed BRIFT algorithm can save about 80% to 90% of time consumption of feature descriptor evaluation and about 50% of feature matching time consumption with a slight loss of matching accuracy, and achieve fast and robust matching of remote sensing images from different sources.

For all-weather, all-day and multi-task warfare requirements, multi-mode composite guidance technology has gradually become a research hotspot in the field of precision guidance in recent years. Compared with common single-mode guidance technology, multi-mode composite guidance technology has played their own advantages and maken up for their disadvantages. In addition, multi-mode composite guidance technology has improved the adaptability of missiles to small and weak targets, stealth targets and complex backgrounds, and has become an important development direction in the field of precision guidance. Based on a brief introduction of the basic concepts of single-mode and multi-mode composite guidance technology, this paper describes the characteristics and principles of multi-mode composite guidance, lists several well-known multi-mode composite guidance weapons abroad, analyzes the development status and trend of multi-mode composite guidance technology, and summarizes the problems faced by multi-mode composite guidance technology.

Radar ground target recognition technology is an important technical base for intellectualization and informatization of radar seeker of air-to-ground missile. Recently, ground target recognition technology has been paid much attention by researchers. However, with the increasingly fierce offensive and defensive confrontation in modern war, the application of radar ground target recognition technology is facing many problems, which has become a bottleneck factor restricting the development of weapons for a long time. To ensure that relevant radar practitioners better understand the development and future trend of this field, this paper introduces the conception of radar target recognition technology, and summarizes the technical difficulties of radar ground target recognition for equipment application. Afterwards, the research status at home and abroad are reviewed. Finally, the development trend of this technology is prospected.

For the problem of excessive stresses in the runner after hydraulic turbine reformation,two solutions are put forward in this paper,which are the extension of the outlet edge of the blade near the crown and applying reinforcing triangular piece. In order to identify the loads acting on the runner,the water flow of whole passage has been investigated by using CFD method. The water pressure was loaded on the finite element model of runner,and rigidity ＆ strength analysis was conducted.The maximum equivalent stress and the maximum deformation of runner in two solutions were obtained. The results show that: the maximum stress of the original runner appears in rated condition,because the pressure difference between the pressure side and suction side at the center of blade and outlet of near the crown is very big,thus the distribution of load is uneven. Under the rated condition,the maximum stress of blade decreases by 14. 5% in the same degree in both the two solutions. The maximum total deformation of blade in solution A is greater than which in solution B. The maximum stress is located in the the intersection of triangular piece and blade outlet,which is a little far from the blade root,so the force condition of blade root is improved effectively. At the same time,the flow field analysis results show that energy characteristics and the cavitation performance in the two solutions under various operating conditions is less affected.

In order to reduce the current dependence on fossil and nuclear-fueled power plants to cope with the growing demand of electrical energy, the ocean energy technologies must be improved to develop more energy. There are several types of ocean energy that can be feasible to exploit: wave energy, marine-current energy, tidal barrages, ocean thermal energy and so on. But the most promising in the short term may be wave and marine-current energy. Marine-current energy can be exploited by a marine current turbine. So how to improve the efficiency of mariner current turbine is the key research subject in ocean energy development. The key to efficiency improvement is the performance improvement of hydrofoil, which is used to establish the turbine blade. In order to improve the hydrofoil's performance, a multi-point optimization method is presented in this paper. In this method, the Bezier curve was used to parameterize the hydrofoil. The Latin Hypercube experiment design method was used to select the sample points in the design space which were used for training the Radial Basis Function neural network. The hydrodynamic performance for each sample was calculated by the computational fluid dynamic method, and then the Radial Basis Function neural network would be trained by these sample points. After the neural network had been trained, the multi-point optimization method of hydrofoil was solved by combining the NSGA-II method and the Radial Basis Function neural network. The method mentioned above was applied to the optimal design of NACA63-815 hydrofoil, and the optimization problems of the hydrofoil in three typical conditions in which the attack angle is 0, 6° and 12° were mainly studied in this paper. After optimization, two optimized hydrofoils were selected in the Pareto solution to compare with initial, which were named Optimal A and Optimal B. According to the CFD simulation, the optimized hydrofoil's performance was gotten and compared with the initial hydrofoil. By comparison, it was found that the drag coefficient of the optimized hydrofoil in the three conditions are less than or equal to the initial. Moreover, the lift-drag ratios of the Optimal A hydrofoil in which the attack angles is 0, 6° and 12° have been improve by 4.6%, 4.4% and 22.8% respectively. And the lift-drag ratios of the Optimal B hydrofoils have also been improved by 6.6%, 3.8% and 16.6% respectively. In addition, according to the comparison of the optimized and initial hydrofoil's pressure coefficient at the 12° attack angle, it can be found that the optimized hydrofoil can effectively suppress the stall phenomenon. Finally, two conclusions can be drawn from the optimal results. Firstly, use the Radial Basis Function neural network to replace the CFD simulation can effectively decrease the time that the optimization cycle spent. Secondly, the hydrofoil optimization problem is a multi-solution problem. The optimized hydrofoil does not have the only one geometry. The optimized hydrofoil can have different geometry just like Optimal A and Optimal B. Moreover, both Optimal A and Optimal B hydrofoil have better performance than the initial one. The optimal result also confirms the feasibility and the theory validity of this optimization method. [ABSTRACT FROM AUTHOR]

The design of a hydro turbine's runner involves many disciplines, such as fluid, structure, strength and so on. As the hydro turbine's capacity increases, the owner of a power plant has strengthened the demand for the turbine's stability. But the traditional sequence design method has difficulty meet ing the demand of the design requirements. So it is necessary to establish a new optimization design method called the multidisciplinary design optimization method, which can consider the interaction of each discipline. At present, the optimal design method of a hydro turbine's runner still can not combine each discipline perfectly in design process. It is necessary to carry out the research about multidisciplinary design optimization (MDO) design method of hydro turbine's runner. Based on the research findings of other fields about multidisciplinary optimization, this paper draws the MDO design method into hydro turbine's runner design, and carries out a preliminary study on the turbine runner's MDO design method. On the basis of design characteristics of a hydro turbine, an optimization design system has been established according to the multidisciplinary method in this paper. This optimization design system could improve the runner blade's hydraulic performance and structural strength simultaneously. In addition, a parameterized module based on the Bezier curve, auto mesh module, computational fluid dynamic module, and finite element analysis module were integrated in the system. The system automatically completes geometry modeling, mesh generation, and multidisciplinary performance analysis. This system uses the geometric shape parameters of a runner blade as optimization variables, and the hydraulic efficiency and maximum stress of runner blade were used as objective functions. The NSGA-II algorithm was used to carry out the optimization. In order to reduce the time of optimization and increase this method's practicability, the calculation method of weak coupling was used for multidisciplinary analysis during optimization. After the multidisciplinary optimization system had been built, a bulb model turbine's runner was optimized using this system. After optimization, the Pareto solution was selected as the optimum solution. The optimum solution was then compared with the initial blade. The comparison results showed that after optimization, the efficiency of blade in optimum operating conditions had been improved 0.3%, and the maximum static stress on blade had been decreased 16.3%. The stress gradient on blade became more uniform, which showed that the optimum blade has better stress performance. In order to comprehensively compare the optimum blade with the initial, performance of initial and optimum blade in other conditions was also calculated and compared. The comparison showed that the optimum blade not only performs better in optimum conditions, but also performs better in other conditions. The comparison results verify that the idea of multidisciplinary optimization design of a hydro turbine runner is feasible, and the optimization system is effective. [ABSTRACT FROM AUTHOR]

Objectives: To isolate aortic arch pathologies and keep the branches superior in arch patent, it always need physicians to do in-vivo fenestration or in-situ fenestration when performing the thoracic endovascular aortic repair (TEVAR). However, both of those fenestration techniques need structure modification of the stent-graft, which may affect their long-term stability. We designed an adjustable pre-fenestration aortic stent-graft to treat pathologies in this area and obtained a patent branch arteries. This study used this new designed stent-graft to perform fenestrated-TEVAR (f-TEVAR) in canine aorta. This study aims to identify its feasibility and safety through animal experiments, which might provide preliminary data for potential human implantation., Methods: A total of 8 Labrador Retrievers were underwent f-TEVAR by using the new devices. Digital subtraction angiography was performed before and after f-TEVAR to evaluate the success of the procedures. All the canines were divided into a 4-week group (feeding for 4 weeks after operation) and a 12-week group (feeding for 12 weeks after operation). Computed tomography angiography (CTA) were performed before euthanasia., Results: The success rate of operation was 100%. During the operation, there was no accident of major bleeding or failure to be released by fenestration. Adjustable fenestration worked well. No stent-graft migration was found in CTA at 4 weeks and 12 weeks after the operation. All branch arteries kept by the adjustable fenestration were patent., Conclusions: The result of feasibility and safety of the new designed adjustable pre-fenestration aortic stent-graft in f-TEVAR of canine is acceptable. This study provides a reference for further optimization of this stent and human f-TEVAR implantation involving aortic arch lesions.