In cone-beam computed tomography （CBCT）, there are often cases where the size of the specimen is larger than the field of view （FOV） （referred to as over FOV-sized （OFS））. To acquire the complete projection da...In cone-beam computed tomography （CBCT）, there are often cases where the size of the specimen is larger than the field of view （FOV） （referred to as over FOV-sized （OFS））. To acquire the complete projection data for OFS objects, some scan modes have been developed for long objects and short but over-wide objects. However, these modes still cannot meet the requirements for both longitudinally long and transversely wide objects. In this paper, we propose a multiple helical scan mode and a corresponding reconstruction algorithm for both longitudinally long and transversely wide objects. The simulation results show that our model can deal with the problem and that the results are acceptable, while the OFS object is twice as long compared with the FOV in the same latitude.展开更多
Pattern matching is a fundamental approach to detect malicious behaviors and information over Internet, which has been gradually used in high-speed network traffic analysis. However, there is a performance bottleneck ...Pattern matching is a fundamental approach to detect malicious behaviors and information over Internet, which has been gradually used in high-speed network traffic analysis. However, there is a performance bottleneck for multi-pattern matching on online compressed network traffic(CNT), this is because malicious and intrusion codes are often embedded into compressed network traffic. In this paper, we propose an online fast and multi-pattern matching algorithm on compressed network traffic(FMMCN). FMMCN employs two types of jumping, i.e. jumping during sliding window and a string jump scanning strategy to skip unnecessary compressed bytes. Moreover, FMMCN has the ability to efficiently process multiple large volume of networks such as HTTP traffic, vehicles traffic, and other Internet-based services. The experimental results show that FMMCN can ignore more than 89.5% of bytes, and its maximum speed reaches 176.470MB/s in a midrange switches device, which is faster than the current fastest algorithm ACCH by almost 73.15 MB/s.展开更多
The cereals and their products,which have been easily infected by fungi and contaminated with mycotoxins,are serious threat to both human and animals alike.And yet,detection of these unknown fungal infection and mycot...The cereals and their products,which have been easily infected by fungi and contaminated with mycotoxins,are serious threat to both human and animals alike.And yet,detection of these unknown fungal infection and mycotoxins contaminates remains a great challenge.In this work,a holistic approach based on multiple characteristic structure fragments scans and high-resolution mass spectrometry(HRMS)was proposed for discovering unknown structural analogues of mycotoxins.The structural similarity of the same class of compounds provides a direction for the discovery and identification of unknown structural analogues of mycotoxins.The following steps were carried out:the fragmentation pathways of four types of mycotoxins were elucidated through comprehensive fragment analysis.By the combination of fragmentation pathways,the multiple characteristic structure fragments were screened out,with the common fragments were obtained by Veen diagram.Finally multiple characteristic structure fragments scans were carried out to find the unknown structural analogues of mycotoxins.The approach,first proposed by us,was proved to be effective in discovering and identifying 5 structural analogues of mycotoxins in real samples.It was proved to be a simple,fast and accurate method for early detection of fungal infection and mycotoxin contaminants,even for trace amounts of chemicals in complex matrix,and is of great significance to prevent hazardous substances infection from the food supply chains worldwide.展开更多
This paper proposes an effective method for reducing test data volume undermultiple scan chain designs. The proposed method is based on reduction of distinct scan vectorsusing selective don't-care identification. ...This paper proposes an effective method for reducing test data volume undermultiple scan chain designs. The proposed method is based on reduction of distinct scan vectorsusing selective don't-care identification. Selective don't-care identification is repeatedlyexecuted under condition that each bit of frequent scan vectors is fixed to binary values (0 or 1).Besides, a code extension technique is adopted for improving compression efficiency with keepingdecompressor circuits simple in the manner that the code length for infrequent scan vectors isdesigned as double of that for frequent ones. The effectiveness of the proposed method is shownthrough experiments for ISCAS'89 and ITC'99 benchmark circuits.展开更多
基金Project supported by the National Basic Research Program of China (Grant No. 2011CB707701)the National High Technology Research and Development Program of China (Grant No. 2009AA012200)the National Nature Science Foundation of China(Grant No. 30970722)
文摘In cone-beam computed tomography （CBCT）, there are often cases where the size of the specimen is larger than the field of view （FOV） （referred to as over FOV-sized （OFS））. To acquire the complete projection data for OFS objects, some scan modes have been developed for long objects and short but over-wide objects. However, these modes still cannot meet the requirements for both longitudinally long and transversely wide objects. In this paper, we propose a multiple helical scan mode and a corresponding reconstruction algorithm for both longitudinally long and transversely wide objects. The simulation results show that our model can deal with the problem and that the results are acceptable, while the OFS object is twice as long compared with the FOV in the same latitude.
基金supported by China MOST project (No.2012BAH46B04)
文摘Pattern matching is a fundamental approach to detect malicious behaviors and information over Internet, which has been gradually used in high-speed network traffic analysis. However, there is a performance bottleneck for multi-pattern matching on online compressed network traffic(CNT), this is because malicious and intrusion codes are often embedded into compressed network traffic. In this paper, we propose an online fast and multi-pattern matching algorithm on compressed network traffic(FMMCN). FMMCN employs two types of jumping, i.e. jumping during sliding window and a string jump scanning strategy to skip unnecessary compressed bytes. Moreover, FMMCN has the ability to efficiently process multiple large volume of networks such as HTTP traffic, vehicles traffic, and other Internet-based services. The experimental results show that FMMCN can ignore more than 89.5% of bytes, and its maximum speed reaches 176.470MB/s in a midrange switches device, which is faster than the current fastest algorithm ACCH by almost 73.15 MB/s.
基金financially supported by National Key Research and Development Program of China(2018YFC1602702)National“Ten thousand Plan”Scientific and Technological Innovation Leading Talent Project(Feng ZHANG).
文摘The cereals and their products,which have been easily infected by fungi and contaminated with mycotoxins,are serious threat to both human and animals alike.And yet,detection of these unknown fungal infection and mycotoxins contaminates remains a great challenge.In this work,a holistic approach based on multiple characteristic structure fragments scans and high-resolution mass spectrometry(HRMS)was proposed for discovering unknown structural analogues of mycotoxins.The structural similarity of the same class of compounds provides a direction for the discovery and identification of unknown structural analogues of mycotoxins.The following steps were carried out:the fragmentation pathways of four types of mycotoxins were elucidated through comprehensive fragment analysis.By the combination of fragmentation pathways,the multiple characteristic structure fragments were screened out,with the common fragments were obtained by Veen diagram.Finally multiple characteristic structure fragments scans were carried out to find the unknown structural analogues of mycotoxins.The approach,first proposed by us,was proved to be effective in discovering and identifying 5 structural analogues of mycotoxins in real samples.It was proved to be a simple,fast and accurate method for early detection of fungal infection and mycotoxin contaminants,even for trace amounts of chemicals in complex matrix,and is of great significance to prevent hazardous substances infection from the food supply chains worldwide.
文摘This paper proposes an effective method for reducing test data volume undermultiple scan chain designs. The proposed method is based on reduction of distinct scan vectorsusing selective don't-care identification. Selective don't-care identification is repeatedlyexecuted under condition that each bit of frequent scan vectors is fixed to binary values (0 or 1).Besides, a code extension technique is adopted for improving compression efficiency with keepingdecompressor circuits simple in the manner that the code length for infrequent scan vectors isdesigned as double of that for frequent ones. The effectiveness of the proposed method is shownthrough experiments for ISCAS'89 and ITC'99 benchmark circuits.
