Robust regulation with 2 performance

We consider the problem of minimizing the ₂ norm of a feedback system subject to the constraint that the controller robustly regulate against constants and sinusoids. We show that, for any ε > 0, there exists a controller that both achieves robust regulation and renders the closed-loop ₂ norm within ε of the optimal norm (the norm achievable without the robust regulation constraint). We also provide conditions that are both necessary and sufficient for there to exist a robustly regulating controller that achieves the optimal ₂ norm. All proofs are constructive.     

Time series determination of transfer functions in random fatigue

Time series determination of the transfer function which relates the input random excitation and the output response in random fatigue experiment is established. This process involves determination of univariate time series of input and output, transfer function and noise models, and the transfer functionnoise model.     

Determination of surface area/monolayer capacity or limiting micropore volume of carbons from binary and ternary mixtures

It is shown that one can predict the adsorption of binary and ternary mixtures in any percentage ratio from the adsorption of individual component gases by means of John's isotherm equation. The surface area of mesoporous materials or the limiting micropore volume of microporous materials from binary and ternary mixture adsorption isotherms is given. The relation given by Lewis et al. may be used to prove the validity of the above method and determine the contribution of each component of the mixture.     

A Feature Reduced Intrusion Detection System with Optimized SVM Using Big Bang Big Crunch Optimization

The swift proliferation in traffic across computer networks has led to certain types of attacks and intrusions, raising a serious global concern of information security. Attack detection is possible by monitoring and observing occurrences in intrusion detection systems, however these systems tend to suffer from problem of curse of dimensionality, high false alarm rate, high time complexity and low detections. In order to overcome these limitations, we propose a feature reduced intrusion detection system employing optimized SVM as a classifier. Feature Reduction has been performed by fusing ranked features from information gain and chi square in a way that it has helped in retaining only important features and discarding the rest. The study further proposes an optimized version of SVM classifier using Big Bang Big Crunch (BBBC) optimization that simulates the big bang and big crunch theory of evolution of universe. BBBC has helped in finding an optimal set of SVM parameters quickly that are further used for classification. We also experimented with a number of fitness functions for gauging the performance of IDS and propose a new fitness function based on the weighted F1 score of various traffic classes. KDD-99 dataset has been used for experimentation and analysis. The paper further experiments the effects of under-sampling and oversampling of various traffic classes on the proposed IDS performance and recommends that maintaining a desired ratio for a mix of under-sampling and over-sampling of desired classes produces the best results.

     

An efficient hybrid security mechanism based on chaos and improved BPCS

Commonly used security mechanisms such as cryptography and steganography suffer from weaknesses when used in a standalone manner. Extra efforts in the form of additional permutations/diffusions etc. result in higher ciphering/deciphering time complexity. Thus, there is a requirement for a security mechanism(s) which can provide adequate security without putting a considerable burden on ciphering/deciphering time complexity. This paper is an effort in this direction. The paper proposes a hybrid mechanism that employs chaotic based encryption scheme to encrypt data and an improved Bit-Plane Complexity Segmentation Steganography algorithm to embed the data. The proposed mechanism uses two new complexity measures to differentiate between noisy regions and simple ones appropriately. The scheme was implemented in MATLAB, and the simulation results show that the proposed mechanism has high embedding capacity, high security with a moderate decrease in PSNR value and is computationally fast.