Impact of linear dimensionality reduction methods on the performance of anomaly detection algorithms in hyperspectral images

Anomaly Detection (AD) has recently become an important application of hyperspectral images analysis. The goal of these algorithms is to find the objects in the image scene which are anomalous in comparison to their surrounding background. One way to improve the performance and runtime of these algorithms is to use Dimensionality Reduction (DR) techniques. This paper evaluates the effect of three popular linear dimensionality reduction methods on the performance of three benchmark anomaly detection algorithms. The Principal Component Analysis (PCA), Fast Fourier Transform (FFT) and Discrete Wavelet Transform (DWT) as DR methods, act as pre-processing step for AD algorithms. The assessed AD algorithms are Reed-Xiaoli (RX), Kernel-based versions of the RX (Kernel-RX) and Dual Window-Based Eigen Separation Transform (DWEST). The AD methods have been applied to two hyperspectral datasets acquired by both the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Hyperspectral Mapper (HyMap) sensors. The evaluation of experiments has been done using Receiver Operation Characteristic (ROC) curve, visual investigation and runtime of the algorithms. Experimental results show that the DR methods can significantly improve the detection performance of the RX method. The detection performance of neither the Kernel-RX method nor the DWEST method changes when using the proposed methods. Moreover, these DR methods increase the runtime of the RX and DWEST significantly and make them suitable to be implemented in real time applications

A novel selection of optimal statistical features in the DWPT domain for discrimination of ictal and seizure-free electroencephalography signals

Properly determining the discriminative features which characterize the inherent behaviors of electroencephalography (EEG) signals remains a great challenge for epileptic seizure detection. In this present study, a novel feature selection scheme based on the discrete wavelet packet decomposition and cuckoo search algorithm (CSA) was proposed. The normal as well as epileptic EEG recordings were frst decomposed into various frequency bands by means of wavelet packet decomposition, and subsequently, statistical features at all developed nodes in the wavelet packet decomposition tree were derived. Instead of using the complete set of the extracted features to construct a wavelet neural networks-based classifer, an optimal feature subset that maximizes the predictive competence of the classifer was selected by using the CSA. Experimental results on the publicly available benchmarks demonstrated that the proposed feature subset selection scheme achieved promising recognition accuracies of 98.43–100%, and the results were statistically signifcant using z-test with p value <0.0001

Selective hydrogenation catalysed by transition metal complexes

This work is an investigation of the mechanism by which norbornadiene, methyl oleate and methyl linoleate are hydrogenated in acetone at 30[sup]oC, 1 atmosphere or 3 atmospheres pressure, using rhodium complexes of the type [Rh(diene)L[sub]n][sup]+A[sup]-(where diene = norbornadiene , L = tertiary phosphine, phosphite, A = CIO[sup]-[sub]4 or PF[sup]-[sub]6). The results were interpreted assuming three active catalyst species, (Rh(diene)L[sub]2)[sup]+, (RhH[sub]2L[sub]2)[sup]+ and RhHL[sub]2. Also investigated were the effects of adding acid (HClO[sub]4) or base (Net[sub]3) and how this altered the equilibrium (RhH[sub]2L[sub]2)[sup]+ H[sup]+ + RhHL[sub]2. At atmospheric pressure, the rate of hydrogenation of norbornadiene and norbornene varies with ligand in the order PPh[sub]3 < PPh[sub]2Me < PPhMe[sub]2, suggesting that oxidative addition of hydrogen is an important first stage of the catalysis. The addition of acid, slowed the rate of hydrogenation for catalysts containing more electron donating ligands (relative to triphenyl phosphine), indicating that the monohydride was a more active specie than the dihydride. With triphenylphosphine or less electron donating ligands in the catalyst, the rate remains constant or increase slightly, indicating that an "unsaturate route" emanating from a diene complex is probably important. The catalyst containing cyclohexylphosphine ligands which are strongly electrondonating but sterically crowded is ineffective in hydrogenation, suggesting that steric crowding may cause an alternative route to operate. Higher pressure (3 atm.) causes faster hydrogenation and provided other mechanistic insights. For methyl oleate at atmospheric pressure, the rate of hydrogenation varies with ligand in the order PPh[sub]3 > PPh[sub]2Me > PPhMe[sub]2, but this order is reversed at 3 atm. pressure. The rate of isomerisation of methyl oleate varies with ligand in the order PPh[sub]3 < PPh[sub]2Me < PPhMe[sub]2, at both pressures. The rate of isomerisation of methyl oIeate and methyl linoleate is lowest, when there is no or a slight excess of acid present but is highest in presence of a base (especially for the catalyst containing diphenylmethylphosphine ligand). Mechanistic interpretations were made