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Research on Braking Process of High-speed Train with Aerodynamic Brake
Yonghua Zhu,Weilie Shang,Xia Zhang,Hongjie Yan,Pin Wu 보안공학연구지원센터 2014 International Journal of Control and Automation Vol.7 No.12
The speed is higher, the kinetic energy is greater. In order to ensure the safety of a new generation train running in a high speed, it is necessary to research on its braking performance. In this paper, the braking force, running resistance, braking time, braking distance and the deceleration generated by the train with two kinds of braking wings were analyzed while the high-speed train was doing deceleration movement. And the results were compared and analyzed between the train with and without braking wing, and between the two kinds of braking wings. The results showed that the high speed train with braking wings made much contribution to the acceleration in the braking process, especially the train is in high speed.
A Linear Iteration Image Restoration Method Based on Homology Continuity
Yonghua Zhu,Shunyi Mao,Pin Wu,Honghao Gao,Zhiguo Wu 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.11
A novel image restoration method based on homology continuity is proposed in this paper. We view images as a collection of gray scale points, taking advantage of the homology continuity principle to combine each point and its fuzzy point derived by drop mass function to constitute the path direction and obtain distinct restore points. The gather of all the restore points is the sharply focused image of the original image. At last, we found every picture by iteration method is clearer than the last by experiment with the method proposed in the paper. The result verifies its feasibility.
Application of the Multi-Source Data Fusion Algorithm in the Hail Identification
Yonghua Zhu,Yongqing Wang,Zhiqun Hu,Fansen Xu,Renqiang Liu 한국기상학회 2022 Asia-Pacific Journal of Atmospheric Sciences Vol.58 No.3
In this study, the canonical correlation analysis algorithm (CCA) is used to fuse the two-dimensional wind field retrieved from the single-Doppler weather radar, the three-dimensional wind field retrieved from the dual-Doppler weather radars, the observations from the ground automatic weather stations and the meteorological reanalysis data in three hail episodes (“0625” episode in Beijing, “0330” and “0801” episodes in Guangdong). During the hail episode in Beijing on June 25, 2020, an evident and long-lasting three-body scatter spike was observed, which played an important role in the hail identification and warning. In the three-dimensional wind field retrieved from the dual-Doppler weather radars, there is horizontal convergence of northeasterly and northwesterly winds and that of northwesterly and southeasterly winds in the low-level strong echo area, and there are obvious updrafts in the vertical wind field structure. Such a circulation configuration is favorable for the development and maintenance of hail storm. The multi-source data fusion of the wind fields can effectively improve the identification of the low-level convergence. The data fusion for the other two hail episodes (“0330” and “0801” episodes in Guangdong) yields the same conclusion. It is revealed that the dual-radar fusion performs better than the single-radar fusion in the identification of the meso-γ scale vortices. It can visually illustrate the characteristics of the cyclonic convergent flow fields which is more consistent with the near-surface observation. It can be concluded that the multi-source data fusion technique is practicable in the three severe convection processes.
Yonghua Cui,Yuxin Shu,Yuanyuan Zhu,Yonghui Shi,Guowei Le 한국식품영양과학회 2012 Journal of medicinal food Vol.15 No.8
High-fat diets (HFDs) have been found to influence central nervous system development and to cause cognitive impairments in human epidemiologic studies, as well as in animal investigations. These adverse effects on learning and memory induced by an HFD have been associated with an impaired hippocampus, including hippocampal oxidative damage. Previously, we had found that a-lipoic acid (a-LA) could ameliorate the oxidative stress in non-neural organs (liver, jejunum,and spleen) induced by a 10-week HFD (21.2% fat) food regimen in mice. In this study, we investigated whether a 10-week HFD (21.2% fat) induced oxidative stress in the hippocampus or impaired spatial learning in mice and whether LA ameliorated these effects. The HFD was found to induce oxidative stress (a decrease in catalase activity, glutathione peroxidase activity, and total antioxidative capacity and an increase in malondialdehyde levels) in the mouse hippocampus. In addition,we found that the HFD impaired spatial recognition memory of mice in the Y-maze paradigm. Furthermore, the hippocampal oxidative stress and impaired spatial recognition memory of the mice were reduced in HFD diets supplemented with 0.1% LA. These findings suggest that LA, as a strong antioxidant, may help prevent HFD-induced learning impairments by ameliorating associated oxidative stress in the hippocampus.
Honghao Gao,Yucong Duan,Yonghua Zhu 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.6
With the increasing of Web services on Internet, services composition requests considering not only the static information compatibility, such as interface grammar and semantic, but also the structural behavior compatibility, i.e., control flow and communication protocol. However, due to the uncertainty of Internet, application failures occurred in service-based software will cause kinds of economic losses. This stochastic phenomenon has been impacted on the structural behavior which makes services composition should take the probabilistic compatibility into account. The probabilistic compatibility needs to compute the degree of compatibility for the effective performance evaluation, which has been an important issue during services collaboration. In this paper, the probabilistic interface automaton is proposed to formalize service behaviors. Then, the synchronized product model is used to the qualitative checking for verifying whether they can interact with each other or not. Third, the probabilistic compatibilities of composite service and component service are discussed for the quantitative computing. Our method provides a reference to generate the correctness and reliable services composition.
Research on Probabilistic Optimization to Dynamic Composition for Service Replacement
Honghao Gao,Minjie Bian,Yucong Duan,Yonghua Zhu 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.10
A growing number of enterprises have been moving their works to encapsulate system functions, business logics and processing modules into Web service because of its flexibility and low-cost. However, service-oriented software calls for constantly adjusting its architecture in order to respond to varying user requirements and instable runtime environments. One of the most challenging issues is how to effectively implement a reconfiguration to ensure the business-critical application is trustworthy. In this paper, it proposes a method to dynamic composition for service replacement, which focuses on the probabilistic optimization to service planning of candidate compositions when the service failure is occurred. First, the input and output data specification is defined to describe interface behaviors, and then the probabilistic solution graph is introduced to formalize replacement strategies. Second, corresponding algorithms are discussed for optimization selection purpose, which includes reliability calculation process and model modification process. The former computes the probability value of each service planning generated from probabilistic solution graph. The latter modifies probabilistic solution graph model to recommend Top-k solutions, pruning the service planning which does not satisfy the specified probability value. Third, the architecture of prototype is presented to demonstrate the feasibility of the proposed method. Our method provides a reference to guarantee the reliability of service process in E-commerce.
Research on Feature Extraction based on Deep Learning
Wu Pin,Yan Hongjie,Shang Weilie,Zhu Yonghua,Gao Honghao 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.11
With the development of deep learning, it has achieved impressive results in feature extraction field. This paper drives research in feature extraction based on deep learning. First, this paper gives a brief introduction on the world's research status on deep learning and principle of Restricted Boltzmann machine (RBM). Then this paper conducts reducing experiment based on RBM for handwritten digits. According to the analysis based on the results of the experiments, this paper tries to get a proper dimension which handwritten digits reduced to achieve better performance. Finally, this paper finds that it reach the goal when handwritten digits is reduced to half dimensional raw digits. This is an important foundation of deep learning layering and offers help to researchers in feature extraction based on deep learning.