Development of a Biometric Personal Authentication System Based on Fingerprint and Speech

Biometrics deals with the physiological and behavioral characteristics of an individual to establish identity. Fingerprint based authentication is the most advanced biometric authentication technology. The minutiae based fingerprint identification method offer reasonable identification rate. The feature minutiae map consists of about 70-100 minutia points and matching accuracy is dropping down while the size of database is growing up. Hence it is inevitable to make the size of the fingerprint feature code to be as smaller as possible so that identification may be much easier. In this research, a novel global singularity based fingerprint representation is proposed. Fingerprint baseline, which is the line between distal and intermediate phalangeal joint line in the fingerprint, is taken as the reference line. A polygon is formed with the singularities and the fingerprint baseline. The feature vectors are the polygonal angle, sides, area, type and the ridge counts in between the singularities. 100% recognition rate is achieved in this method. The method is compared with the conventional minutiae based recognition method in terms of computation time, receiver operator characteristics (ROC) and the feature vector length. Speech is a behavioural biometric modality and can be used for identification of a speaker. In this work, MFCC of text dependant speeches are computed and clustered using k-means algorithm. A backpropagation based Artificial Neural Network is trained to identify the clustered speech code. The performance of the neural network classifier is compared with the VQ based Euclidean minimum classifier. Biometric systems that use a single modality are usually affected by problems like noisy sensor data, non-universality and/or lack of distinctiveness of the biometric trait, unacceptable error rates, and spoof attacks. Multifinger feature level fusion based fingerprint recognition is developed and the performances are measured in terms of the ROC curve. Score level fusion of fingerprint and speech based recognition system is done and 100% accuracy is achieved for a considerable range of matching threshold

An objective climatology of the dynamical forcing of polar lows in the Nordic seas

A new objective climatology of polar lows in the Nordic (Norwegian and Barents) seas has been derived from a database of diagnostics of objectively identified cyclones spanning the period January 2000 to April 2004. There are two distinct parts to this study: the development of the objective climatology and a characterization of the dynamical forcing of the polar lows identified. Polar lows are an intense subset of polar mesocyclones. Polar mesocyclones are distinguished from other cyclones in the database as those that occur in cold air outbreaks over the open ocean. The difference between the wet-bulb potential temperature at 700 hPa and the sea surface temperature (SST) is found to be an effective discriminator between the atmospheric conditions associated with polar lows and other cyclones in the Nordic seas. A verification study shows that the objective identification method is reliable in the Nordic seas region. After demonstrating success at identifying polar lows using the above method, the dynamical forcing of the polar lows in the Nordic seas is characterized. Diagnostics of the ratio of mid-level vertical motion attributable to quasi-geostrophic forcing from upper and lower levels (U/L ratio) are used to determine the prevalence of a recently proposed category of extratropical cyclogenesis, type C, for which latent heat release is crucial to development. Thirty-one percent of the objectively identified polar low events (36 from 115) exceeded the U/L ratio of 4.0, previously identified as a threshold for type C cyclones. There is a contrast between polar lows to the north and south of the Nordic seas. In the southern Norwegian Sea, the population of polar low events is dominated by type C cyclones. These possess strong convection and weak low-level baroclinicity. Over the Barents and northern Norwegian seas, the well-known cyclogenesis types A and B dominate. These possess stronger low-level baroclinicity and weaker convection.

Modified radial basis function neural network using output transformation

A modified radial basis function (RBF) neural network and its identification algorithm based on observational data with heterogeneous noise are introduced. The transformed system output of Box-Cox is represented by the RBF neural network. To identify the model from observational data, the singular value decomposition of the full regression matrix consisting of basis functions formed by system input data is initially carried out and a new fast identification method is then developed using Gauss-Newton algorithm to derive the required Box-Cox transformation, based on a maximum likelihood estimator (MLE) for a model base spanned by the largest eigenvectors. Finally, the Box-Cox transformation-based RBF neural network, with good generalisation and sparsity, is identified based on the derived optimal Box-Cox transformation and an orthogonal forward regression algorithm using a pseudo-PRESS statistic to select a sparse RBF model with good generalisation. The proposed algorithm and its efficacy are demonstrated with numerical examples.

Combined CloudSat-CALIPSO-MODIS retrievals of the properties of ice clouds

In this paper, data from spaceborne radar, lidar and infrared radiometers on the “A-Train” of satellites are combined in a variational algorithm to retrieve ice cloud properties. The method allows a seamless retrieval between regions where both radar and lidar are sensitive to the regions where one detects the cloud. We first implement a cloud phase identification method, including identification of supercooled water layers using the lidar signal and temperature to discriminate ice from liquid. We also include rigorous calculation of errors assigned in the variational scheme. We estimate the impact of the microphysical assumptions on the algorithm when radiances are not assimilated by evaluating the impact of the change in the area-diameter and the density-diameter relationships in the retrieval of cloud properties. We show that changes to these assumptions affect the radar-only and lidar-only retrieval more than the radar-lidar retrieval, although the lidar-only extinction retrieval is only weakly affected. We also show that making use of the molecular lidar signal beyond the cloud as a constraint on optical depth, when ice clouds are sufficiently thin to allow the lidar signal to penetrate them entirely, improves the retrieved extinction. When infrared radiances are available, they provide an extra constraint and allow the extinction-to-backscatter ratio to vary linearly with height instead of being constant, which improves the vertical distribution of retrieved cloud properties.

Deposition of charged inhaled aerosols with transient airflow in sequential lung airway model

Transport and deposition of charged inhaled aerosols in double planar bifurcation representing generation three to five of human respiratory system has been studied under a light activity breathing condition. Both steady and oscillatory laminar inhalation airflow is considered. Particle trajectories are calculated using a Lagrangian reference frame, which is dominated by the fluid force driven by airflow, gravity force and electrostatic forces (both of space and image charge forces). The particle-mesh method is selected to calculate the space charge force. This numerical study investigates the deposition efficiency in the three-dimensional model under various particle sizes, charge values, and inlet particle distribution. Numerical results indicate that particles carrying an adequate level of charge can improve deposition efficiency in the airway model.

Rapid protein domain assignment from amino acid sequence using predicted secondary structure

The elucidation of the domain content of a given protein sequence in the absence of determined structure or significant sequence homology to known domains is an important problem in structural biology. Here we address how successfully the delineation of continuous domains can be accomplished in the absence of sequence homology using simple baseline methods, an existing prediction algorithm (Domain Guess by Size), and a newly developed method (DomSSEA). The study was undertaken with a view to measuring the usefulness of these prediction methods in terms of their application to fully automatic domain assignment. Thus, the sensitivity of each domain assignment method was measured by calculating the number of correctly assigned top scoring predictions. We have implemented a new continuous domain identification method using the alignment of predicted secondary structures of target sequences against observed secondary structures of chains with known domain boundaries as assigned by Class Architecture Topology Homology (CATH). Taking top predictions only, the success rate of the method in correctly assigning domain number to the representative chain set is 73.3%. The top prediction for domain number and location of domain boundaries was correct for 24% of the multidomain set (±20 residues). These results have been put into context in relation to the results obtained from the other prediction methods assessed

Detection of gyrA mutations in quinolone-resistant Salmonella enterica by denaturing high-performance liquid chromatography

Denaturing high-performance liquid chromatography (DHPLC) was evaluated as a rapid screening and identification method for DNA sequence variation detection in the quinolone resistance-determining region of gyrA from Salmonella serovars. A total of 203 isolates of Salmonella were screened using this method. DHPLC analysis of 14 isolates representing each type of novel or multiple mutations and the wild type were compared with LightCycler-based PCR-gyrA hybridization mutation assay (GAMA) and single-strand conformational polymorphism (SSCP) analyses. The 14 isolates gave seven different SSCP patterns, and LightCycler detected four different mutations. DHPLC detected 11 DNA sequence variants at eight different codons, including those detected by LightCycler or SSCP. One of these mutations was silent. Five isolates contained multiple mutations, and four of these could be distinguished from the composite sequence variants by their DHPLC profile. Seven novel mutations were identified at five different loci not previously described in quinolone-resistant salmonella. DHPLC analysis proved advantageous for the detection of novel and multiple mutations. DHPLC also provides a rapid, high-throughput alternative to LightCycler and SSCP for screening frequently occurring mutations.

The Diffusion Kernel Filter

A particle filter method is presented for the discrete-time filtering problem with nonlinear ItA ` stochastic ordinary differential equations (SODE) with additive noise supposed to be analytically integrable as a function of the underlying vector-Wiener process and time. The Diffusion Kernel Filter is arrived at by a parametrization of small noise-driven state fluctuations within branches of prediction and a local use of this parametrization in the Bootstrap Filter. The method applies for small noise and short prediction steps. With explicit numerical integrators, the operations count in the Diffusion Kernel Filter is shown to be smaller than in the Bootstrap Filter whenever the initial state for the prediction step has sufficiently few moments. The established parametrization is a dual-formula for the analysis of sensitivity to gaussian-initial perturbations and the analysis of sensitivity to noise-perturbations, in deterministic models, showing in particular how the stability of a deterministic dynamics is modeled by noise on short times and how the diffusion matrix of an SODE should be modeled (i.e. defined) for a gaussian-initial deterministic problem to be cast into an SODE problem. From it, a novel definition of prediction may be proposed that coincides with the deterministic path within the branch of prediction whose information entropy at the end of the prediction step is closest to the average information entropy over all branches. Tests are made with the Lorenz-63 equations, showing good results both for the filter and the definition of prediction.

Modelagem linear e identificação do modelo dinâmico de um robô móvel com acionamento diferencial

This work presents a modelling and identification method for a wheeled mobile robot, including the actuator dynamics. Instead of the classic modelling approach, where the robot position coordinates (x,y) are utilized as state variables (resulting in a non linear model), the proposed discrete model is based on the travelled distance increment Delta_l. Thus, the resulting model is linear and time invariant and it can be identified through classical methods such as Recursive Least Mean Squares. This approach has a problem: Delta_l can not be directly measured. In this paper, this problem is solved using an estimate of Delta_l based on a second order polynomial approximation. Experimental data were colected and the proposed method was used to identify the model of a real robot

Experimental Active Vibration Control in Truss Structures Considering Uncertainties in System Parameters

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The CMS experiment at the CERN LHC

The Compact Muon Solenoid (CMS) detector is described. The detector operates at the Large Hadron Collider (LHC) at CERN. It was conceived to study proton-proton (and lead-lead) collisions at a centre-of-mass energy of 14 TeV (5.5 TeV nucleon-nucleon) and at luminosities up to 10(34)cm(-2)s(-1) (10(27)cm(-2)s(-1)). At the core of the CMS detector sits a high-magnetic-field and large-bore superconducting solenoid surrounding an all-silicon pixel and strip tracker, a lead-tungstate scintillating-crystals electromagnetic calorimeter, and a brass-scintillator sampling hadron calorimeter. The iron yoke of the flux-return is instrumented with four stations of muon detectors covering most of the 4 pi solid angle. Forward sampling calorimeters extend the pseudo-rapidity coverage to high values (vertical bar eta vertical bar <= 5) assuring very good hermeticity. The overall dimensions of the CMS detector are a length of 21.6 m, a diameter of 14.6 m and a total weight of 12500 t.

SPH simulations of clumps formation by dissipative collisions of molecular clouds - II. Magnetic case

We performed computer simulations of interstellar cloud-cloud collisions using the three-dimensional smoothed particle magnetohydrodynamics method. In order to study the role of the magnetic field on the process of collision-triggered fragmentation, we focused our attention on head-on supersonic collisions between two identical spherical molecular-clouds. Two extreme configurations of the magnetic field were adopted: parallel and perpendicular to the initial clouds motion. The initial magnetic field strength was approximately 12.0 muG. In the parallel case, much more of the collision debris were retained in the shocking region than in the non-magnetic case where gas escaped freely throughout the symmetry plane. Differently from the non-magnetic case, eddy-like vortices were formed. The regions of highest vorticity and the the regions of highest density are offset. We found clumps formation only in the parallel case, however, they were larger, hotter and less dense than in the analogous non-magnetic case. In the perpendicular case, the compressed field works as a magnetic wall, preventing a stronger compression of the colliding clouds. This last effect inhibits direct contact of the two clouds. In both cases, we found that the field lines show a chaotic aspect in large scales. Also, the field magnitude is considerably amplified in the shock layer. However, the field distribution is almost coherent in the higher density regions.

Richards growth model and viability indicators for populations subject to interventions

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genetic structure of populations of Rhizoctonia solani AG-3 on potato in eastern North Carolina

A polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method was developed to identify and differentiate genotypes of Rhizoctonia solani anastomosis group 3 subgroup PT (AG-3 PT), a fungal pathogen of potato. Polymorphic co-dominant single-locus PCR-RFLP markers were identified after sequencing of clones from a genomic library and digestion with restriction enzymes. Multilocus genotypes were determined by a combination of PCR product and digestion with a specific restriction enzyme for each of seven loci. A sample of 104 isolates from one commercial field in each of five counties in eastern North Carolina was analyzed, and evidence for high levels of gene flow between populations was revealed. When data were clone-corrected and samples pooled into one single North Carolina population, random associations of alleles were found for all loci or pairs of loci, indicating random mating. However, when all genotypes were analyzed, the observed genotypic diversity deviated from panmixia and alleles within and between loci were not randomly associated. These findings support a model of population structure for R. solani AG-3 PT on potato that includes both recombination and clonality.

Eficiência polinizadora de apis mellifera l. e polinizaç ão entomófila em pimentão variedade cascadura ikeda

The aim of this research was to identify the insects visiting flowers of sweet pepper and evaluate the effects of entomophilous pollination as a whole and, more especifically, of honeybees as pollinators of this crop. This study was carried out in the municipality of Taubaté, State of São Paulo, Brazil (21°01'S; 45°29'W; altitude: 570 m) from April to September, 2002. Insects were collected in thirty-six plants during 10 minutes/hour between 6:00 and 17:00h during days of maximum blooming. Twelve plots were subjected to the following treatments: (1) open-pollinated plots, freely visited by insects; (2) caged plots; (3) caged plots containing a hive of honeybees. Twelve species of insects visited the flowers. Exomalopsis spp. (Hymenoptera, Apidae) were the commonest ones (53,9% of visits). Fruits yielded in treatments (1) and (3) were heavier, presented higher diameter, thicker pericarp and more seeds per fruit than fruits in treatment (2). Results showed that fruits from insect pollinated plots presented better quality. Honeybeesas as pollinators were efficient as the other insects. sweet pepper, Capsicum annuum L., Solanaceae, pollination, Apis mellifera, honeybee.