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

On the design of education conditional cash transfer programs and non education outcomes: the case of teenage pregnancy

We investigate the effect of education Conditional Cash Transfer programs (CCTs) on teenage pregnancy. Our main concern is with how the size and sign of the effect may depend on the design of the program. Using a simple model we show that an education CCT that conditions renewal on school performance reduces teenage pregnancy; the program can increase teenage pregnancy if it does not condition on school performance. Then, using an original data base, we estimate the causal impact on teenage pregnancy of two education CCTs implemented in Bogot´a (Subsidio Educativo, SE, and Familias en Acci´on, FA); both programs differ particularly on whether school success is a condition for renewal or not. We show that SE has negative average effect on teenage pregnancy while FA has a null average effect. We also find that SE has either null or no effect for adolescents in all age and grade groups while FA has positive, null or negative effects for adolescents in different age and grade groups. Since SE conditions renewal on school success and FA does not, we can argue that the empirical results are consistent with the predictions of our model and that conditioning renewal of the subsidy on school success crucially determines the effect of the subsidy on teenage pregnancy

The representation of conditional expectations of non-Gaussian noise

For Wiener spaces conditional expectations and $L^{2}$-martingales w.r.t. the natural filtration have a natural representation in terms of chaos expansion. In this note an extension to larger classes of processes is discussed. In particular, it is pointed out that orthogonality of the chaos expansion is not required.

Preliminary results on the non-thermal effects of 200-350 GHz radiation on the growth rate of S. cerevisiae cells in microcolonies

We report preliminary results from studies of biological effects induced by non-thermal levels of non-ionizing electromagnetic radiation. Exponentially growing Saccharomyces cerevisiae yeast cells grown on dry media were exposed to electromagnetic fields in the 200–350 GHz frequency range at low power density to observe possible non-thermal effects on the microcolony growth. Exposure to the electromagnetic field was conducted over 2.5 h. The data from exposure and control experiments were grouped into either large-, medium- or small-sized microcolonies to assist in the accurate assessment of growth. The three groups showed significant differences in growth between exposed and control microcolonies. A statistically significant enhanced growth rate was observed at 341 GHz. Growth rate was assessed every 30 min via time-lapse photography. Possible interaction mechanisms are discussed, taking into account Frohlich's hypothesis.

Using non-personal computers for eLearning: Sri Lankan experience

Communal Internet access facilities or telecentres are considered a good way to provide connectivity to people who do not possess home connectivity. Attempts are underway to utilize telecentres as eLearning centres providing access to learning materials to students who would otherwise not be able to take up eLearning. This paper reports on the findings of qualitative interviews conducted with 18 undergraduate students from two Sri Lankan universities on their eLearning experiences using communal Internet access centres. The findings suggest that despite the efforts by telecentres to provide a good service to eLearners, there are various problems faced by students including: costs, logistics, scarcity of resources, connectivity speeds, excessive procedures, and lack of support. The experiences of these Sri Lankan students suggest that there is much that needs to be understood about user perspectives in using telecentres, which could help formulate better policies and strategies to support eLearners who depend on communal access facilities.

Bicorrelations and cross-bicorrelations as non-linearity tests and tools for exchange rate forecasting

This paper proposes and implements a new methodology for forecasting time series, based on bicorrelations and cross-bicorrelations. It is shown that the forecasting technique arises as a natural extension of, and as a complement to, existing univariate and multivariate non-linearity tests. The formulations are essentially modified autoregressive or vector autoregressive models respectively, which can be estimated using ordinary least squares. The techniques are applied to a set of high-frequency exchange rate returns, and their out-of-sample forecasting performance is compared to that of other time series models

Forecasting exchange rate volatility using conditional variance models selected by information criteria

This paper uses appropriately modified information criteria to select models from the GARCH family, which are subsequently used for predicting US dollar exchange rate return volatility. The out of sample forecast accuracy of models chosen in this manner compares favourably on mean absolute error grounds, although less favourably on mean squared error grounds, with those generated by the commonly used GARCH(1, 1) model. An examination of the orders of models selected by the criteria reveals that (1, 1) models are typically selected less than 20% of the time.

Targeting medication non-adherence behavior in selected autoimmune diseases: a systematic approach to digital health program development

Background 29 autoimmune diseases, including Rheumatoid Arthritis, gout, Crohn’s Disease, and Systematic Lupus Erythematosus affect 7.6-9.4% of the population. While effective therapy is available, many patients do not follow treatment or use medications as directed. Digital health and Web 2.0 interventions have demonstrated much promise in increasing medication and treatment adherence, but to date many Internet tools have proven disappointing. In fact, most digital interventions continue to suffer from high attrition in patient populations, are burdensome for healthcare professionals, and have relatively short life spans. Objective Digital health tools have traditionally centered on the transformation of existing interventions (such as diaries, trackers, stage-based or cognitive behavioral therapy programs, coupons, or symptom checklists) to electronic format. Advanced digital interventions have also incorporated attributes of Web 2.0 such as social networking, text messaging, and the use of video. Despite these efforts, there has not been little measurable impact in non-adherence for illnesses that require medical interventions, and research must look to other strategies or development methodologies. As a first step in investigating the feasibility of developing such a tool, the objective of the current study is to systematically rate factors of non-adherence that have been reported in past research studies. Methods Grounded Theory, recognized as a rigorous method that facilitates the emergence of new themes through systematic analysis, data collection and coding, was used to analyze quantitative, qualitative and mixed method studies addressing the following autoimmune diseases: Rheumatoid Arthritis, gout, Crohn’s Disease, Systematic Lupus Erythematosus, and inflammatory bowel disease. Studies were only included if they contained primary data addressing the relationship with non-adherence. Results Out of the 27 studies, four non-modifiable and 11 modifiable risk factors were discovered. Over one third of articles identified the following risk factors as common contributors to medication non-adherence (percent of studies reporting): patients not understanding treatment (44%), side effects (41%), age (37%), dose regimen (33%), and perceived medication ineffectiveness (33%). An unanticipated finding that emerged was the need for risk stratification tools (81%) with patient-centric approaches (67%). Conclusions This study systematically identifies and categorizes medication non-adherence risk factors in select autoimmune diseases. Findings indicate that patients understanding of their disease and the role of medication are paramount. An unexpected finding was that the majority of research articles called for the creation of tailored, patient-centric interventions that dispel personal misconceptions about disease, pharmacotherapy, and how the body responds to treatment. To our knowledge, these interventions do not yet exist in digital format. Rather than adopting a systems level approach, digital health programs should focus on cohorts with heterogeneous needs, and develop tailored interventions based on individual non-adherence patterns.

Nonparametric specification tests for conditional duration models

This paper deals with the testing of autoregressive conditional duration (ACD) models by gauging the distance between the parametric density and hazard rate functions implied by the duration process and their non-parametric estimates. We derive the asymptotic justification using the functional delta method for fixed and gamma kernels, and then investigate the finite-sample properties through Monte Carlo simulations. Although our tests display some size distortion, bootstrapping suffices to correct the size without compromising their excellent power. We show the practical usefulness of such testing procedures for the estimation of intraday volatility patterns.

Association between distressing non-work-related events and occupational injuries

The following is a report on a case-control study whose objective was to investigate the association between distressing non-work-related events and occupational injures. Ninety three injured workers (cases) were matched with 372 non-injured controls in a large metallurgical factory in southeastern Brazil. Exposure to distressing non-work-related events was measured through a questionnaire focusing on situations pertaining to personal problems unrelated to work activities. The data were analyzed by adjusting a conditional logistic regression model, where occurrence of the work injury was the dependent dichotomous variable and answers from the questionnaire were independent continuous variables. The analysis showed an association between some distressing non-work-related events and occupational injuries. These findings imply expanding the horizon of preventive measures used in targeting. work injuries which have traditionally been focused on the control of strictly workplace risks.

Aging reduces complexity of heart rate variability assessed by conditional entropy and symbolic analysis

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

Application of non-isothermal cure kinetics on the interaction of poly(ethylene terephthalate) - Alkyd resin paints

Samples of paint (P), reused PET (PET-R) and paint/PET-R mixtures (PPET-R) were evaluated using DSC to verify their physical-chemical properties and thermal behavior. Films from paints and PPET-R are visually similar. It was possible to establish that the maximum amount of PET-R that can be added to paint without significantly altering its filming properties is 2%. The cure process (80-203°C) was identified through DSC curves. The kinetic parameters, activation energy (E a) and Arrhenius parameters (A) for the samples containing 0.5 to 1% of PET-R, were calculated using the Flynn-Wall-Ozawa isoconversional method. It was observed that for greater amounts of PET-R added, there is a decrease in the E a values for the cure process. A Kinetic compensation effect (KCE), represented by the equation InA=-2.70+0.31E a was observed for all the samples. The most suitable kinetic model to describe this cure process is the autocatalytic Šesták-Berggreen, model applied to heterogeneous systems. © 2007 Springer Science+Business Media, LLC.

Aging reduces complexity of heart rate variability assessed by conditional entropy and symbolic analysis

Increasing age is associated with a reduction in overall heart rate variability as well as changes in complexity of physiologic dynamics. The aim of this study was to verify if the alterations in autonomic modulation of heart rate caused by the aging process could be detected by Shannon entropy (SE), conditional entropy (CE) and symbolic analysis (SA). Complexity analysis was carried out in 44 healthy subjects divided into two groups: old (n = 23, 63 +/- A 3 years) and young group (n = 21, 23 +/- A 2). It was analyzed SE, CE [complexity index (CI) and normalized CI (NCI)] and SA (0V, 1V, 2LV and 2ULV patterns) during short heart period series (200 cardiac beats) derived from ECG recordings during 15 min of rest in a supine position. The sequences characterized by three heart periods with no significant variations (0V), and that with two significant unlike variations (2ULV) reflect changes in sympathetic and vagal modulation, respectively. The unpaired t test (or Mann-Whitney rank sum test when appropriate) was used in the statistical analysis. In the aging process, the distributions of patterns (SE) remain similar to young subjects. However, the regularity is significantly different; the patterns are more repetitive in the old group (a decrease of CI and NCI). The amounts of pattern types are different: 0V is increased and 2LV and 2ULV are reduced in the old group. These differences indicate marked change of autonomic regulation. The CE and SA are feasible techniques to detect alteration in autonomic control of heart rate in the old group.