The maximum of k numerical functions defined on , , by , ??is used here in Statistical classification. Previously, it has been used in Statistical Discrimination [1] and in Clustering [2]. We present first some theore...The maximum of k numerical functions defined on , , by , ??is used here in Statistical classification. Previously, it has been used in Statistical Discrimination [1] and in Clustering [2]. We present first some theoretical results on this function, and then its application in classification using a computer program we have developed. This approach leads to clear decisions, even in cases where the extension to several classes of Fisher’s linear discriminant function fails to be effective.展开更多
In Wireless Sensor Networks(WSN),attacks mostly aim in limiting or eliminating the capability of the network to do its normal function.Detecting this misbehaviour is a demanding issue.And so far the prevailing researc...In Wireless Sensor Networks(WSN),attacks mostly aim in limiting or eliminating the capability of the network to do its normal function.Detecting this misbehaviour is a demanding issue.And so far the prevailing research methods show poor performance.AQN3 centred efficient Intrusion Detection Systems(IDS)is proposed in WSN to ameliorate the performance.The proposed system encompasses Data Gathering(DG)in WSN as well as Intrusion Detection(ID)phases.In DG,the Sensor Nodes(SN)is formed as clusters in the WSN and the Distance-based Fruit Fly Fuzzy c-means(DFFF)algorithm chooses the Cluster Head(CH).Then,the data is amassed by the discovered path.Next,it is tested with the trained IDS.The IDS encompasses‘3’steps:pre-processing,matrix reduction,and classification.In pre-processing,the data is organized in a clear format.Then,attributes are presented on the matrix format and the ELDA(entropybased linear discriminant analysis)lessens the matrix values.Next,the output as of the matrix reduction is inputted to the QN3 classifier,which classifies the denial-of-services(DoS),Remotes to Local(R2L),Users to Root(U2R),and probes into attacked or Normal data.In an experimental estimation,the proposed algorithm’s performance is contrasted with the prevailing algorithms.The proposed work attains an enhanced outcome than the prevailing methods.展开更多
A new set of descriptors,namely score vectors of the zero dimension,one dimension,two dimensions and three dimensions(SZOTT),was derived from principle component analysis of a matrix of 1369 structural variables inclu...A new set of descriptors,namely score vectors of the zero dimension,one dimension,two dimensions and three dimensions(SZOTT),was derived from principle component analysis of a matrix of 1369 structural variables including 0D,1D,2D and 3D information for the 20 coded amino acids. SZOTT scales were then used in cleavage site prediction of human immunodeficiency virus type 1 protease. Linear discriminant analysis(LDA) and support vector machines(SVM) were applied to developing models to predict the cleavage sites. The results obtained by linear discriminant analysis(LDA) and support vector machines(SVM) are as follows. The Matthews correlation coefficients(MCC) by the resubstitution test,leave-one-out cross validation(LOOCV) and external validation are 0.879 and 0.911,0.849 and 0.901,0.822 and 0.846,respectively. The receiver operating characteristic(ROC) analysis showed that the SVM model possesses better simulative and predictive ability in comparison with the LDA model. Satisfactory results show that SZOTT descriptors can be further used to predict cleavage sites of human immunodeficiency virus type 1 protease.展开更多
文摘The maximum of k numerical functions defined on , , by , ??is used here in Statistical classification. Previously, it has been used in Statistical Discrimination [1] and in Clustering [2]. We present first some theoretical results on this function, and then its application in classification using a computer program we have developed. This approach leads to clear decisions, even in cases where the extension to several classes of Fisher’s linear discriminant function fails to be effective.
文摘In Wireless Sensor Networks(WSN),attacks mostly aim in limiting or eliminating the capability of the network to do its normal function.Detecting this misbehaviour is a demanding issue.And so far the prevailing research methods show poor performance.AQN3 centred efficient Intrusion Detection Systems(IDS)is proposed in WSN to ameliorate the performance.The proposed system encompasses Data Gathering(DG)in WSN as well as Intrusion Detection(ID)phases.In DG,the Sensor Nodes(SN)is formed as clusters in the WSN and the Distance-based Fruit Fly Fuzzy c-means(DFFF)algorithm chooses the Cluster Head(CH).Then,the data is amassed by the discovered path.Next,it is tested with the trained IDS.The IDS encompasses‘3’steps:pre-processing,matrix reduction,and classification.In pre-processing,the data is organized in a clear format.Then,attributes are presented on the matrix format and the ELDA(entropybased linear discriminant analysis)lessens the matrix values.Next,the output as of the matrix reduction is inputted to the QN3 classifier,which classifies the denial-of-services(DoS),Remotes to Local(R2L),Users to Root(U2R),and probes into attacked or Normal data.In an experimental estimation,the proposed algorithm’s performance is contrasted with the prevailing algorithms.The proposed work attains an enhanced outcome than the prevailing methods.
基金Supported by the Research on National High-tech R&D Program (the 863 program) (Grant No. 2006AA02Z312)Innovative Group Program for Graduates of Chong- qing University, Science and Innovation Fund (Grant No. 200711C1A0010260)
文摘A new set of descriptors,namely score vectors of the zero dimension,one dimension,two dimensions and three dimensions(SZOTT),was derived from principle component analysis of a matrix of 1369 structural variables including 0D,1D,2D and 3D information for the 20 coded amino acids. SZOTT scales were then used in cleavage site prediction of human immunodeficiency virus type 1 protease. Linear discriminant analysis(LDA) and support vector machines(SVM) were applied to developing models to predict the cleavage sites. The results obtained by linear discriminant analysis(LDA) and support vector machines(SVM) are as follows. The Matthews correlation coefficients(MCC) by the resubstitution test,leave-one-out cross validation(LOOCV) and external validation are 0.879 and 0.911,0.849 and 0.901,0.822 and 0.846,respectively. The receiver operating characteristic(ROC) analysis showed that the SVM model possesses better simulative and predictive ability in comparison with the LDA model. Satisfactory results show that SZOTT descriptors can be further used to predict cleavage sites of human immunodeficiency virus type 1 protease.
