A fault detection method based on incremental locally linear embedding(LLE)is presented to improve fault detecting accuracy for satellites with telemetry data.Since conventional LLE algorithm cannot handle incremental...A fault detection method based on incremental locally linear embedding(LLE)is presented to improve fault detecting accuracy for satellites with telemetry data.Since conventional LLE algorithm cannot handle incremental learning,an incremental LLE method is proposed to acquire low-dimensional feature embedded in high-dimensional space.Then,telemetry data of Satellite TX-I are analyzed.Therefore,fault detection are performed by analyzing feature information extracted from the telemetry data with the statistical indexes T2 and squared prediction error(SPE)and SPE.Simulation results verify the fault detection scheme.展开更多
Let W be a standard Brownian motion,and define Y(t) =∫t 0 ds W(s) as Cauchy' s principal value related to the local time of W.We study some limitresults on lag increments of Y(t) and obtain various results all...Let W be a standard Brownian motion,and define Y(t) =∫t 0 ds W(s) as Cauchy' s principal value related to the local time of W.We study some limitresults on lag increments of Y(t) and obtain various results all of which are related to earlier work by Hanson and Russo in 1 983展开更多
In rotational incremental sheet forming( RISF) process,the friction heating of rotational tool could lead to local temperature rise of the sheet and cause the improvement of sheet's formability.Lightweight metal,s...In rotational incremental sheet forming( RISF) process,the friction heating of rotational tool could lead to local temperature rise of the sheet and cause the improvement of sheet's formability.Lightweight metal,such as magnesium alloy,could be deformed by RISF without additional heating. The objective of this study is to investigate the effects of forming parameters,namely,tool rotational speed,feed-rate,step size and wall angle,on the local temperature rise. Using response surface methodology and central composite design( CCD) experimental design,the significance,sequence of parameters and regression models would be analyzed with AZ31 B as the experimental material,and 3D response surface plots would be shown. Combined with actual processing conditions,the measures to improve the local temperature rise by modifying each parameter would be discussed in the end. The results showed that hierarchy of the parameters with respect to the significance of their effects on the local temperature at the side wall was: feed-rate,step size,and rotational speed,while at the bottom it was: feed-rate,step size,wall angle, and rotational speed, and no significant interaction appeared. It was found that the most significant parameter was not rotational speed,but feed-rate,followed by step size,for both test positions. In addition, the local temperature would increase by elevating step size,wall angle,rotating rate,and bringing down of feed-rate.展开更多
In this paper, we propose a new online system that can quickly detect malicious spam emails and adapt to the changes in the email contents and the Uniform Resource Locator (URL) links leading to malicious websites by ...In this paper, we propose a new online system that can quickly detect malicious spam emails and adapt to the changes in the email contents and the Uniform Resource Locator (URL) links leading to malicious websites by updating the system daily. We introduce an autonomous function for a server to generate training examples, in which double-bounce emails are automatically collected and their class labels are given by a crawler-type software to analyze the website maliciousness called SPIKE. In general, since spammers use botnets to spread numerous malicious emails within a short time, such distributed spam emails often have the same or similar contents. Therefore, it is not necessary for all spam emails to be learned. To adapt to new malicious campaigns quickly, only new types of spam emails should be selected for learning and this can be realized by introducing an active learning scheme into a classifier model. For this purpose, we adopt Resource Allocating Network with Locality Sensitive Hashing (RAN-LSH) as a classifier model with a data selection function. In RAN-LSH, the same or similar spam emails that have already been learned are quickly searched for a hash table in Locally Sensitive Hashing (LSH), in which the matched similar emails located in “well-learned” are discarded without being used as training data. To analyze email contents, we adopt the Bag of Words (BoW) approach and generate feature vectors whose attributes are transformed based on the normalized term frequency-inverse document frequency (TF-IDF). We use a data set of double-bounce spam emails collected at National Institute of Information and Communications Technology (NICT) in Japan from March 1st, 2013 until May 10th, 2013 to evaluate the performance of the proposed system. The results confirm that the proposed spam email detection system has capability of detecting with high detection rate.展开更多
基金supported by the Fundamental Research Funds for the Central Universities(No.2016083)
文摘A fault detection method based on incremental locally linear embedding(LLE)is presented to improve fault detecting accuracy for satellites with telemetry data.Since conventional LLE algorithm cannot handle incremental learning,an incremental LLE method is proposed to acquire low-dimensional feature embedded in high-dimensional space.Then,telemetry data of Satellite TX-I are analyzed.Therefore,fault detection are performed by analyzing feature information extracted from the telemetry data with the statistical indexes T2 and squared prediction error(SPE)and SPE.Simulation results verify the fault detection scheme.
文摘Let W be a standard Brownian motion,and define Y(t) =∫t 0 ds W(s) as Cauchy' s principal value related to the local time of W.We study some limitresults on lag increments of Y(t) and obtain various results all of which are related to earlier work by Hanson and Russo in 1 983
基金National Natural Science Foundation of China(No.51205217)the Project of Shandong Province Higher Educational Science and Technology Program,China(No.J10LD13)+1 种基金the Taishan Scholar Project of Shandong Province,China(No.ts 201511038)the Key Research Project of Shandong Province,China(No.2016ZDJS02A15)
文摘In rotational incremental sheet forming( RISF) process,the friction heating of rotational tool could lead to local temperature rise of the sheet and cause the improvement of sheet's formability.Lightweight metal,such as magnesium alloy,could be deformed by RISF without additional heating. The objective of this study is to investigate the effects of forming parameters,namely,tool rotational speed,feed-rate,step size and wall angle,on the local temperature rise. Using response surface methodology and central composite design( CCD) experimental design,the significance,sequence of parameters and regression models would be analyzed with AZ31 B as the experimental material,and 3D response surface plots would be shown. Combined with actual processing conditions,the measures to improve the local temperature rise by modifying each parameter would be discussed in the end. The results showed that hierarchy of the parameters with respect to the significance of their effects on the local temperature at the side wall was: feed-rate,step size,and rotational speed,while at the bottom it was: feed-rate,step size,wall angle, and rotational speed, and no significant interaction appeared. It was found that the most significant parameter was not rotational speed,but feed-rate,followed by step size,for both test positions. In addition, the local temperature would increase by elevating step size,wall angle,rotating rate,and bringing down of feed-rate.
文摘In this paper, we propose a new online system that can quickly detect malicious spam emails and adapt to the changes in the email contents and the Uniform Resource Locator (URL) links leading to malicious websites by updating the system daily. We introduce an autonomous function for a server to generate training examples, in which double-bounce emails are automatically collected and their class labels are given by a crawler-type software to analyze the website maliciousness called SPIKE. In general, since spammers use botnets to spread numerous malicious emails within a short time, such distributed spam emails often have the same or similar contents. Therefore, it is not necessary for all spam emails to be learned. To adapt to new malicious campaigns quickly, only new types of spam emails should be selected for learning and this can be realized by introducing an active learning scheme into a classifier model. For this purpose, we adopt Resource Allocating Network with Locality Sensitive Hashing (RAN-LSH) as a classifier model with a data selection function. In RAN-LSH, the same or similar spam emails that have already been learned are quickly searched for a hash table in Locally Sensitive Hashing (LSH), in which the matched similar emails located in “well-learned” are discarded without being used as training data. To analyze email contents, we adopt the Bag of Words (BoW) approach and generate feature vectors whose attributes are transformed based on the normalized term frequency-inverse document frequency (TF-IDF). We use a data set of double-bounce spam emails collected at National Institute of Information and Communications Technology (NICT) in Japan from March 1st, 2013 until May 10th, 2013 to evaluate the performance of the proposed system. The results confirm that the proposed spam email detection system has capability of detecting with high detection rate.
