61 research outputs found
A fault diagnosis model based on singular value manifold features, optimized SVMs and multi-sensor information fusion
To achieve better fault diagnosis of rotating machinery, this paper presents a novel intelligent fault diagnosis model based on singular value manifold features (SVMF), optimized support vector machines (SVMs) and multi-sensor information fusion. Firstly, a new fault feature named SVMF is developed to better represent faults. SVMF is acquired by extracting manifold topology features of the singular spectrum. Compared with frequently-used fault features, the feature scale of SVMF is constant for variable rotating speed, and the extraction process of SVMF also has the effect of self-weighting. So SVMF has a better representation of faults. Then, to select optimal parameters for model training of SVMs, an improved fruit fly algorithm is proposed by introducing a guidance search mechanism and enhanced local search operation, and as a result both the convergence speed and accuracy are improved. Finally, the Dempster–Shafer evidence theory is introduced to fuse decision-level information from SVM models of multiple sensors. Information fusion eliminates the conflict of conclusions on fault diagnosis from multiple sensors, which leads to high robustness and accuracy of the fault diagnosis model. As a summary, the proposed method combines the advantages of SVMF in fault representation, SVMs in fault identification and the Dempster–Shafer evidence theory in information fusion, and as a result the proposed method will perform better at fault diagnosis. The proposed intelligent fault diagnosis model is subsequently applied to fault diagnosis of the gearbox. Experimental results show that the proposed diagnostic framework is versatile at detecting faults accurately
Genome-wide association and genomic prediction for resistance to southern corn rust in DH and testcross populations
Southern corn rust (SCR), caused by Puccinia polysora Underw, is a destructive disease that can severely reduce grain yield in maize (Zea mays L.). Owing to P. polysora being multi-racial, it is very important to explore more resistance genes and develop more efficient selection approaches in maize breeding programs. Here, four Doubled Haploid (DH) populations with 384 accessions originated from selected parents and their 903 testcross hybrids were used to perform genome-wide association (GWAS). Three GWAS processes included the additive model in the DH panel, additive and dominant models in the hybrid panel. As a result, five loci were detected on chromosomes 1, 7, 8, 8, and 10, with P-values ranging from 4.83×10-7 to 2.46×10-41. In all association analyses, a highly significant locus on chromosome 10 was detected, which was tight chained with the known SCR resistance gene RPPC and RPPK. Genomic prediction (GP), has been proven to be effective in plant breeding. In our study, several models were performed to explore predictive ability in hybrid populations for SCR resistance, including extended GBLUP with different genetic matrices, maker based prediction models, and mixed models with QTL as fixed factors. For GBLUP models, the prediction accuracies ranged from 0.56-0.60. Compared with traditional prediction only with additive effect, prediction ability was significantly improved by adding additive-by-additive effect (P-value< 0.05). For maker based models, the accuracy of BayesA and BayesB was 0.65, 8% higher than other models (i.e., RRBLUP, BRR, BL, BayesC). Finally, by adding QTL into the mixed linear prediction model, the accuracy can be further improved to 0.67, especially for the G_A model, the prediction performance can be increased by 11.67%. The prediction accuracy of the BayesB model can be further improved significantly by adding QTL information (P-value< 0.05). This study will provide important valuable information for understanding the genetic architecture and the application of GP for SCR in maize breeding
Ploidy effect and genetic architecture exploration of stalk traits using DH and its corresponding haploid populations in maize
Examining The Timing Effect Of Information Diffusion On Social Media Platforms: A Temporal Network Approach
An Efficient V2I Authentication Scheme for VANETs
The advent of intelligent transportation system has a crucial impact on the traffic safety and efficiency. To cope with security issues such as spoofing attack and forgery attack, many authentication schemes for vehicular ad hoc networks (VANETs) have been developed, which are based on the hypothesis that secret keys are kept perfectly secure. However, key exposure is inevitable on account of the openness of VANET environment. To address this problem, key insulation is introduced in our proposed scheme. With a helper device, vehicles could periodically update their own secret keys. In this way, the forward and backward secrecy has been achieved. In addition, the elliptic curve operations have been integrated to improve the performance. The random oracle model is adopted to prove the security of the proposed scheme, and the experiment has been conducted to demonstrate the comparison between our scheme and the existing similar schemes
Research and Design of Dynamic Migration Access Control Technology Based on Heterogeneous Network
With the continuous development of wireless networks, the amount of privacy services in heterogeneous mobile networks is increasing, such as information storage, user access, and so on. Access control security issues for heterogeneous mobile radio network, this paper proposes a dynamic migration access control technology based on heterogeneous network. Through the system architecture of the mutual trust system, we can understand the real-time mobile node failure or abnormal state. To make the service can be terminated for the node. And adopt the 802.1X authentication way to improve the security of the system. Finally, it by combining the actual running test data, the trust update algorithm of the system is optimized to reduce the actual security threats in the environment. Experiments show that the system’s anti-attack, the success rate of access, bit error rate is in line with the expected results. This system can effectively reduce the system authentication information is illegally obtained after the network security protection mechanism failure and reduce the risk of user data leakage
Research and Design of Dynamic Migration Access Control Technology Based on Heterogeneous Network
With the continuous development of wireless networks, the amount of privacy services in heterogeneous mobile networks is increasing, such as information storage, user access, and so on. Access control security issues for heterogeneous mobile radio network, this paper proposes a dynamic migration access control technology based on heterogeneous network. Through the system architecture of the mutual trust system, we can understand the real-time mobile node failure or abnormal state. To make the service can be terminated for the node. And adopt the 802.1X authentication way to improve the security of the system. Finally, it by combining the actual running test data, the trust update algorithm of the system is optimized to reduce the actual security threats in the environment. Experiments show that the system’s anti-attack, the success rate of access, bit error rate is in line with the expected results. This system can effectively reduce the system authentication information is illegally obtained after the network security protection mechanism failure and reduce the risk of user data leakage
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