Cancelable Iris recognition system based on comb filter

This paper presents a novel scheme for cancelable iris recognition based on comb filtering. This scheme begins with a coarse-to-fine iris localization stage. After that, Gabor filtering is applied for feature extraction. The two-dimensional phase pattern of features generated with the LogGabor filter is distorted through comb filtering. The objective of this distortion process is to generate a cancelable feature pattern that represents the iris. The ability to reinitiate a new cancelable pattern is guaranteed through the variation of the comb filter order. The proposed scheme is compared with a cancelable random projection scheme for iris recognition. Experimental results are conducted on CASIA-IrisV3-Interval database for both random projection and comb filtering schemes. Moreover, evaluation metrics are estimated for different comb filter orders of 6, 8, 10, and 12 in addition to the case of original iris features. Hamming distance and Receiver Operating Characteristic (ROC) curve are estimated for both random projection and comb filtering schemes to check robustness and stability. The experimental results show a significant gain in both privacy and performance. Also, the comb filtering scheme achieves a superior performance for all orders compared to the random projection scheme. The proposed comb filtering scheme achieves the highest accuracy of 99.75% for order 6 and a promising Equal Error Rate (EER) of 0.36% for order 10.

     

Noise-Parameter Uncertainties: A Monte Carlo Simulation

This paper reports the formulation and results of a Monte Carlo study of uncertainties in noise-parameter measurements. The simulator permits the computation of the dependence of the uncertainty in the noise parameters on uncertainties in the underlying quantities. Results are obtained for the effect due to uncertainties in the reflection coefficients of the input terminations, the noise temperature of the hot noise source, connector variability, the ambient temperature, and the measurement of the output noise. Representative results are presented for both uncorrelated and correlated uncertainties in the underlying quantities. The simulation program is also used to evaluate two possible enhancements of noise-parameter measurements: the use of a cold noise source as one of the input terminations and the inclusion of a measurement of the “reverse configuration,” in which the noise from the amplifier input is measured directly.     

Directional scanning of complex electromagnetic environments

A directional scanning technique is formulated for determining characteristics of an electromagnetic (EM) environment with a relatively small number of measurements, and results of a simulated application are presented. The method relies on measurements with a directional probe to obtain information about the coefficients in a planewave expansion of the field within a large volume. The simulation indicates that although the spatial variation of the field can not be accurately determined, the spatial average of the field intensity can.     

Formal Power Series

We present a formalization of the topological ring of formal power series in Isabelle/HOL. We also formalize formal derivatives, division, radicals, composition and reverses. As an application, we show how formal elementary and hyper-geometric series yield elegant proofs for some combinatorial identities. We easily derive a basic theory of polynomials. Then, using a generic formalization of the fraction field of an integral domain, we obtain formal Laurent series and rational functions for free.     

Precision measurement method for cryogenic amplifier noise temperatures below 5 K

We report precision measurements of the effective input noise temperature of a cryogenic (liquid-helium temperature) monolithic-microwave integrated-circuit amplifier at the amplifier reference planes within the cryostat. A method is given for characterizing and removing the effect of the transmission lines between the amplifier reference planes and the input and output connectors of the cryostat. In conjunction with careful noise measurements, this method enables us to measure amplifier noise temperatures below 5 K with an uncertainty of 0.3 K. The particular amplifier that was measured exhibits a noise temperature below 5.5 K from 1 to 11 GHz, attaining a minimum value of 2.3 K/spl plusmn/0.3 K at 7 GHz. This corresponds to a noise figure of 0.034 dB/spl plusmn/0.004 dB. The measured amplifier gain is between 33.4 dB/spl plusmn/0.3 dB and 35.8 dB/spl plusmn/0.3 dB over the 1-12-GHz range.     

Incremental data-driven learning of a novelty detection model for one-class classification with application to high-dimensional noisy data

Most conventional learning algorithms require both positive and negative training data for achieving accurate classification results. However, the problem of learning classifiers from only positive data arises in many applications where negative data are too costly, difficult to obtain, or not available at all. This paper describes a new machine learning approach, called ILoNDF (Incremental data-driven Learning of Novelty Detector Filter). The approach is inspired by novelty detection theory and its learning method, which typically requires only examples from one class to learn a model. One advantage of ILoNDF is the ability of its generative learning to capture the intrinsic characteristics of the training data by continuously integrating the information relating to the relative frequencies of the features of training data and their co-occurrence dependencies. This makes ILoNDF rather stable and less sensitive to noisy features which may be present in the representation of the positive data. In addition, ILoNDF does not require extensive computational resources since it operates on-line without repeated training, and no parameters need to be tuned. In this study we mainly focus on the robustness of ILoNDF in dealing with high-dimensional noisy data and we investigate the variation of its performance depending on the amount of data available for training. To make our study comparable to previous studies, we investigate four common methods: PCA residuals, Hotelling’s T ² test, an auto-associative neural network, and a one-class version of the SVM classifier (lately a favored method for one-class classification). Experiments are conducted on two real-world text corpora: Reuters and WebKB. Results show that ILoNDF tends to be more robust, is less affected by initial settings, and consistently outperforms the other methods.     

Protease Substrate-Independent Universal Assay for Monitoring Digestion of Native Unmodified Proteins

Proteases are a group of enzymes with a catalytic function to hydrolyze peptide bonds of proteins. Proteases regulate the activity, signaling mechanism, fate, and localization of many proteins, and their dysregulation is associated with various pathological conditions. Proteases have been identified as biomarkers and potential therapeutic targets for multiple diseases, such as acquired immunodeficiency syndrome, cardiovascular diseases, osteoporosis, type 2 diabetes, and cancer, where they are essential to disease progression. Thus, protease inhibitors and inhibitor-like molecules are interesting drug candidates. To study proteases and their substrates and inhibitors, simple, rapid, and sensitive protease activity assays are needed. Existing fluorescence-based assays enable protease monitoring in a high-throughput compatible microtiter plate format, but the methods often rely on either molecular labeling or synthetic protease targets that only mimic the hydrolysis site of the true target proteins. Here, we present a homogenous, label-free, and time-resolved luminescence utilizing the protein-probe method to assay proteases with native and denatured substrates at nanomolar sensitivity. The developed protein-probe method is not restricted to any single protein or protein target class, enabling digestion and substrate fragmentation studies with the natural unmodified substrate proteins. The versatility of the assay for studying protease targets was shown by monitoring the digestion of a substrate panel with different proteases. These results indicate that the protein-probe method not only monitors the protease activity and inhibition, but also studies the substrate specificity of individual proteases.     

International comparison of thermal noise-temperature measurementsat 2, 4, and 12 GHz

We discuss an international comparison of thermal noise-power measurements (GTRF-92-2), which has recently been completed under the auspices of the Consultative Committee for Electricity and Magnetism (CCEM). The noise temperatures of two solid-state sources with GPC-7 connectors were measured at 2, 4, and 12 GHz at the national laboratories in France, Germany, the United Kingdom, and the United States. Good agreement was found among the results from the different laboratories, with all results agreeing within the expanded uncertainties, which ranged from approximately 0.5% to 2.9%. The comparison was performed in accordance with the guidelines recently adopted by the Bureau International des Poids et Mesures (BIPM)