Bias in the nonlinear filter generator output sequence

Nonlinear filter generators are common components used in the keystream generators for stream ciphers and more recently for authentication mechanisms. They consist of a Linear Feedback Shift Register (LFSR) and a nonlinear Boolean function to mask the linearity of the LFSR output. Properties of the output of a nonlinear filter are not well studied. Anderson noted that the m-tuple output of a nonlinear filter with consecutive taps to the filter function is unevenly distributed. Current designs use taps which are not consecutive. We examine m-tuple outputs from nonlinear filter generators constructed using various LFSRs and Boolean functions for both consecutive and uneven (full positive difference sets where possible) tap positions. The investigation reveals that in both cases, the m-tuple output is not uniform. However, consecutive tap positions result in a more biased distribution than uneven tap positions, with some m-tuples not occurring at all. These biased distributions indicate a potential flaw that could be exploited for cryptanalysis

Clone Detection in Repositories of Business Process Models

Business process model repositories capture precious knowledge about an organization or a business domain. In many cases, these repositories contain hundreds or even thousands of models and they represent several man-years of effort. Over time, process model repositories tend to accumulate duplicate fragments, as new process models are created by copying and merging fragments from other models. This calls for methods to detect duplicate fragments in process models that can be refactored as separate subprocesses in order to increase readability and maintainability. This paper presents an indexing structure to support the fast detection of clones in large process model repositories. Experiments show that the algorithm scales to repositories with hundreds of models. The experimental results also show that a significant number of non-trivial clones can be found in process model repositories taken from industrial practice.

Development of a novel rolling-circle amplification technique to detect Banana streak virus which also discriminates between integrated and episomal virus sequences

Bananas are hosts to a large number of banana streak virus (BSV) species. However, diagnostic methods for BSV are inadequate because of the considerable genetic and serological diversity amongst BSV isolates and the presence of integrated BSV sequences in some banana cultivars which leads to false positives. In this study, a sequence non-specific, rolling-circle amplification (RCA) technique was developed and shown to overcome these limitations for the detection and subsequent characterisation of BSV isolates infecting banana. This technique was shown to discriminate between integrated and episomal BSV DNA, specifically detecting the latter in several banana cultivars known to contain episomal and/or integrated sequences of Banana streak Mysore virus (BSMyV), Banana streak OL virus (BSOLV) and Banana streak GF virus (BSGFV). Using RCA, the presence of BSMyV and BSOLV was confirmed in Australia, while BSOLV, BSGFV, Banana streak Uganda I virus (BSUgIV), Banana streak Uganda L virus (BSUgLV) and Banana streak Uganda M virus (BSUgMV) were detected in Uganda. This is the first confirmed report of episomally-derived BSUglV, BSUgLV and BSUgMV in Uganda. As well as its ability to detect BSV, RCA was shown to detect two other pararetroviruses, Sugarcane bacilliform virus in sugarcane and Cauliflower mosaic virus in turnip.

Detection of anomalies from user profiles generated from system logs

We describe research into the identification of anomalous events and event patterns as manifested in computer system logs. Prototype software has been developed with a capability that identifies anomalous events based on usage patterns or user profiles, and alerts administrators when such events are identified. To reduce the number of false positive alerts we have investigated the use of different user profile training techniques and introduce the use of abstractions to group together applications which are related. Our results suggest that the number of false alerts that are generated is significantly reduced when a growing time window is used for user profile training and when abstraction into groups of applications is used.

Sensitivity of Dot-ELISA on Nitrocellulose Membranes in Comparison with ELISA on Polystyrene Plates for the Detection of Four Plant Viruses

ABSTR.4CT Senitivity of dot-immunobindinding ELf SA on nitrocellulose membrane (DotELISA)was compared with double-antibody sandwich ELISA (DAS-ELlSA) on polystyrene plates for the detection of bean yellow mosaic virus (BYMV), broad bean stain virus (WMV-2). Dot-ELISA was 2 and 1O times more sensitive than DAS-ELISA for the detection of BBSV and WMV-2, respectively, whereas DAS-ELISA was more sensitive than Dot-ELiSA for {he detection of BYMV. Both techniques were equally sensitive for the detection of BYDV. Using one day instead uf the two-day procedure, the four viruses were still detectable and the ralative sensitivity of both techniques remained the same.

Detection of dsRNA from Cleistothecia and Conidia of the Grape Powdery Mildew Pathogen, Uncinula Necator

Double-stranded RNA species ranging in molecular weight from 0.95 to 6.3 × 106 were detected in grapevines in New York. We recently showed that two of the species (Mr = 5.3 and 4.4 × 106) are associated with rupestris stem pitting disease. In this report, we show that the other eight detectable dsRNA species are associated with the powdery mildew fungus, Uncinula necator. These dsRNAs associated with the powdery mildew fungus were previously detected in leaves and epidermal stem tissue of grapevines infected with powdery mildew. The same dsRNA species were also detected from extracts of isolated cleistothecia and conidia of U. necator devoid of plant tissue. Isometric and rigid rodlike particles were observed in single cleistothecia preparations when examined under transmission electron microscopy.

Detection of dsRNA in Grapevines Showing Symptoms of Rupestris Stem Pitting Disease and the Variabilities Encountered

Rupestris stem pitting (rSP), a graft-transmissible grapevine disease, can be identified only by its reaction (pitted wood) on inoculated Vitis rupestris ‘St. George.’ DsRNA was extracted from grapevines from California and Canada that indexed positive for rSP on St. George. Two distinct dsRNA species (B and C) (Mr = 5.3 × 106 and 4.4 × 106, respectively) were detected from the stem tissue of rSP-positive samples. Although similar dsRNA species (B and C) were detected in extracts of grapevines from New York, the association of dsRNA B and C with rSP in New York samples was not consistent. Also, eight different dsRNAs, known to be associated with the powdery mildew fungus, Uncinula necator, were detected in leaves of New York samples. In New York, the dsRNAs were not observed in leaves or stem samples collected from June through late August during the 1988 and 1989 growing seasons, suggesting that dsRNA detection in the grape tissue is variable throughout the season. We suggest that dsRNA species B and C are associated with rSP disease. The inconsistent results with New York samples are discussed.

Sequence Changes in Six Variants of Rice Tungro Bacilliform Virus and Their Phylogenetic Relationships

The DNA of three biological variants, G1, Ic and G2, which originated from the same greenhouse isolate of rice tungro bacilliform virus (RTBV) at the International Rice Research Institute (IRRI), was cloned and sequenced. Comparison of the sequences revealed small differences in genome sizes. The variants were between 95 and 99% identical at the nucleotide and amino acid levels. Alignment of the three genome sequences with those of three published RTBV sequences (Phi-1, Phi-2 and Phi-3) revealed numerous nucleotide substitutions and some insertions and deletions. The published RTBV sequences originated from the same greenhouse isolate at IRRI 20, 11 and 9 years ago. All open reading frames (ORFs) and known functional domains were conserved across the six variants. The cysteine-rich region of ORF3 showed the greatest variation. When the six DNA sequences from IRRI were compared with that of an isolate from Malaysia (Serdang), similar changes were observed in the cysteine-rich region in addition to other nucleotide substitutions and deletions across the genome. The aligned nucleotide sequences of the IRRI variants and Serdang were used to analyse phylogenetic relationships by the bootstrapped parsimony, distance and maximum-likelihood methods. The isolates clustered in three groups: Serdang alone; Ic and G1; and Phi-1, Phi-2, Phi-3 and G2. The distribution of phylogenetically informative residues in the IRRI sequences shared with the Serdang sequence and the differing tree topologies for segments of the genome suggested that recombination, as well as substitutions and insertions or deletions, has played a role in the evolution of RTBV variants. The significance and implications of these evolutionary forces are discussed in comparison with badnaviruses and caulimoviruses.

Complete Nucleotide Sequence of Rice Tungro Spherical Virus Genome of a Highly Virulent Strain Vt6

The complete nucleotide sequence of rice tungro spherical virus (RTSV) strain Vt6, originally from Mindanao, the Philippines, with higher virulence to resistant rice cultivars, was determined and compared with the published sequence for the Philippine-type strain A (RTSV-A-Shen). It was reported that RTSV-A was not able to infect a rice resistant cultivar TKM 6 (10). RTSV-Vt6 and RTSV-A-Shen share 90% and 95% homology at nucleotide and amino-acid levels, respectively. The N-terminal leader sequence of RTSV-Vt6 contained a 39-amino acids-region (positions 65 to 103) which was totally different from that of RTSV-A-Shen; the difference resulted from frame shifting by nucleotide insertions and deletions. To confirm the amino-acid sequence differences of the leader polypeptide, the same region was cloned and sequenced using a newly obtained variant of RTSV-type 6, which had been collected in the field of IRRI, and seven field isolates from Mindanao, the Philippines. Since all the sequences of the target region are identical to that of the Vt6 leader polypeptide, the sequence difference in the leader region seems not to correlate with the virulence of Vt6.

Model-order selection in Zernike polynomial expansion of corneal surfaces using the efficient detection criterion

Corneal-height data are typically measured with videokeratoscopes and modeled using a set of orthogonal Zernike polynomials. We address the estimation of the number of Zernike polynomials, which is formalized as a model-order selection problem in linear regression. Classical information-theoretic criteria tend to overestimate the corneal surface due to the weakness of their penalty functions, while bootstrap-based techniques tend to underestimate the surface or require extensive processing. In this paper, we propose to use the efficient detection criterion (EDC), which has the same general form of information-theoretic-based criteria, as an alternative to estimating the optimal number of Zernike polynomials. We first show, via simulations, that the EDC outperforms a large number of information-theoretic criteria and resampling-based techniques. We then illustrate that using the EDC for real corneas results in models that are in closer agreement with clinical expectations and provides means for distinguishing normal corneal surfaces from astigmatic and keratoconic surfaces.

The delta-phase spectrum with application to voice activity detection and speaker recognition

For several reasons, the Fourier phase domain is less favored than the magnitude domain in signal processing and modeling of speech. To correctly analyze the phase, several factors must be considered and compensated, including the effect of the step size, windowing function and other processing parameters. Building on a review of these factors, this paper investigates a spectral representation based on the Instantaneous Frequency Deviation, but in which the step size between processing frames is used in calculating phase changes, rather than the traditional single sample interval. Reflecting these longer intervals, the term delta-phase spectrum is used to distinguish this from instantaneous derivatives. Experiments show that mel-frequency cepstral coefficients features derived from the delta-phase spectrum (termed Mel-Frequency delta-phase features) can produce broadly similar performance to equivalent magnitude domain features for both voice activity detection and speaker recognition tasks. Further, it is shown that the fusion of the magnitude and phase representations yields performance benefits over either in isolation.

Noise robust voice activity detection using normal probability testing and time-domain histogram analysis

This paper presents a method of voice activity detection (VAD) suitable for high noise scenarios, based on the fusion of two complementary systems. The first system uses a proposed non-Gaussianity score (NGS) feature based on normal probability testing. The second system employs a histogram distance score (HDS) feature that detects changes in the signal through conducting a template-based similarity measure between adjacent frames. The decision outputs by the two systems are then merged using an open-by-reconstruction fusion stage. Accuracy of the proposed method was compared to several baseline VAD methods on a database created using real recordings of a variety of high-noise environments.

Person-independent facial expression detection using constrained local models

In automatic facial expression detection, very accurate registration is desired which can be achieved via a deformable model approach where a dense mesh of 60-70 points on the face is used, such as an active appearance model (AAM). However, for applications where manually labeling frames is prohibitive, AAMs do not work well as they do not generalize well to unseen subjects. As such, a more coarse approach is taken for person-independent facial expression detection, where just a couple of key features (such as face and eyes) are tracked using a Viola-Jones type approach. The tracked image is normally post-processed to encode for shift and illumination invariance using a linear bank of filters. Recently, it was shown that this preprocessing step is of no benefit when close to ideal registration has been obtained. In this paper, we present a system based on the Constrained Local Model (CLM) which is a generic or person-independent face alignment algorithm which gains high accuracy. We show these results against the LBP feature extraction on the CK+ and GEMEP datasets.

Noise robust voice activity detection using features extracted from the time-domain autocorrelation function

This paper presents a method of voice activity detection (VAD) for high noise scenarios, using a noise robust voiced speech detection feature. The developed method is based on the fusion of two systems. The first system utilises the maximum peak of the normalised time-domain autocorrelation function (MaxPeak). The second zone system uses a novel combination of cross-correlation and zero-crossing rate of the normalised autocorrelation to approximate a measure of signal pitch and periodicity (CrossCorr) that is hypothesised to be noise robust. The score outputs by the two systems are then merged using weighted sum fusion to create the proposed autocorrelation zero-crossing rate (AZR) VAD. Accuracy of AZR was compared to state of the art and standardised VAD methods and was shown to outperform the best performing system with an average relative improvement of 24.8% in half-total error rate (HTER) on the QUT-NOISE-TIMIT database created using real recordings from high-noise environments.