Improved Biometric Authentication System Using Multimodal Cue Integration

Biometrics is an efficient technology with great possibilities in the area of security system development for official and commercial applications. The biometrics has recently become a significant part of any efficient person authentication solution. The advantage of using biometric traits is that they cannot be stolen, shared or even forgotten. The thesis addresses one of the emerging topics in Authentication System, viz., the implementation of Improved Biometric Authentication System using Multimodal Cue Integration, as the operator assisted identification turns out to be tedious, laborious and time consuming. In order to derive the best performance for the authentication system, an appropriate feature selection criteria has been evolved. It has been seen that the selection of too many features lead to the deterioration in the authentication performance and efficiency. In the work reported in this thesis, various judiciously chosen components of the biometric traits and their feature vectors are used for realizing the newly proposed Biometric Authentication System using Multimodal Cue Integration. The feature vectors so generated from the noisy biometric traits is compared with the feature vectors available in the knowledge base and the most matching pattern is identified for the purpose of user authentication. In an attempt to improve the success rate of the Feature Vector based authentication system, the proposed system has been augmented with the user dependent weighted fusion technique.

Prion protein NMR structure and species barrier for prion diseases

The structural basis of species specificity of transmissible spongiform encephalopathies, such as bovine spongiform encephalopathy or “mad cow disease” and Creutzfeldt–Jakob disease in humans, has been investigated using the refined NMR structure of the C-terminal domain of the mouse prion protein with residues 121–231. A database search for mammalian prion proteins yielded 23 different sequences for the fragment 124–226, which display a high degree of sequence identity and show relevant amino acid substitutions in only 18 of the 103 positions. Except for a unique isolated negative surface charge in the bovine protein, the amino acid differences are clustered in three distinct regions of the three-dimensional structure of the cellular form of the prion protein. Two of these regions represent potential species-dependent surface recognition sites for protein–protein interactions, which have independently been implicated from in vitro and in vivo studies of prion protein transformation. The third region consists of a cluster of interior hydrophobic side chains that may affect prion protein transformation at later stages, after initial conformational changes in the cellular protein.

Voice-processing technologies--their application in telecommunications.

As the telecommunications industry evolves over the next decade to provide the products and services that people will desire, several key technologies will become commonplace. Two of these, automatic speech recognition and text-to-speech synthesis, will provide users with more freedom on when, where, and how they access information. While these technologies are currently in their infancy, their capabilities are rapidly increasing and their deployment in today's telephone network is expanding. The economic impact of just one application, the automation of operator services, is well over $100 million per year. Yet there still are many technical challenges that must be resolved before these technologies can be deployed ubiquitously in products and services throughout the worldwide telephone network. These challenges include: (i) High level of accuracy. The technology must be perceived by the user as highly accurate, robust, and reliable. (ii) Easy to use. Speech is only one of several possible input/output modalities for conveying information between a human and a machine, much like a computer terminal or Touch-Tone pad on a telephone. It is not the final product. Therefore, speech technologies must be hidden from the user. That is, the burden of using the technology must be on the technology itself. (iii) Quick prototyping and development of new products and services. The technology must support the creation of new products and services based on speech in an efficient and timely fashion. In this paper I present a vision of the voice-processing industry with a focus on the areas with the broadest base of user penetration: speech recognition, text-to-speech synthesis, natural language processing, and speaker recognition technologies. The current and future applications of these technologies in the telecommunications industry will be examined in terms of their strengths, limitations, and the degree to which user needs have been or have yet to be met. Although noteworthy gains have been made in areas with potentially small user bases and in the more mature speech-coding technologies, these subjects are outside the scope of this paper.

Agriculture and sustainable development: The role of small scale agriculture in obtaining food security

The international community has expressed a renewed interest in small scale agriculture and the role it plays in long-term food security in the face of climate change and population growth. This interest has led to a new development paradigm in which small scale producers are being brought into the global market. Undoubtedly, small scale agriculture should be pursued as a sustainable form of development which can contribute to poverty alleviation, environmental stewardship, and the preservation of genetic diversity. These unique contributions are inherently threatened by a system captured in the idea of the neoliberal food regime. The ability of small scale agriculture to uphold the goals of food security are dependent on recognition and preservation of these contributions.

Gene delivery of the elastase inhibitor elafin protects macrophages from neutrophil elastase-mediated impairment of apoptotic cell recognition

The resolution of inflammation is dependent on recognition and phagocytic removal of apoptotic cells by macrophages. Receptors for apoptotic cells are sensitive to degradation by human neutrophil elastase (HNE). We show in the present study that HNE cleaves macrophage cell surface CD14 and in so doing, reduces phagocytic recognition of apoptotic lymphocytic cells (Mutu 1). Using an improved method of adenovirus-mediated transfection of macrophages with the HNE inbibitor elafin, we demonstrate that elafin overexpression prevents CD14 cleavage and restores apoptotic cell recognition by macrophages. This approach of genetic modification of macrophages could be used to restore apoptotic cell recognition in inflammatory conditions. (C) 2004 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Differential requirement for CD4 help in the development of an antigen-specific CD8+ T cell response depending on the route of immunization.

Previous studies in our laboratory have shown that DBA/2 mice injected i.p. with syngeneic P815 tumor cells transfected with the HLA-CW3 gene (P815-CW3) showed a dramatic expansion of activated CD8+CD62L- T cells expressing exclusively the Vbeta10 segment. We have used this model to study the regulatory mechanisms involved in the development of the CW3-specific CD8+ response, with respect to different routes of immunization. Whereas both intradermal (i.d.) and i.p. immunization of DBA/2 mice with P815-CW3 cells led to a strong expansion of CD8+CD62L-Vbeta10+ cells, only the i.d. route allowed this expansion after immunization with P815 cells transfected with a minigene coding for the antigenic epitope CW3 170-179 (P815 miniCW3). Furthermore, depletion of CD4+ T cells in vivo completely abolished the specific response of CD8+CD62L-Vbeta10+ cells and prevented the rejection of P815-CW3 tumor cells injected i.p., whereas it did not affect CD8S+CD62L-Vbeta10+ cell expansion after i.d. immunization with either P815-CW3 or P815 miniCW3. Finally, the CW3-specific CD8+ memory response was identical whether or not CD4+ T cells were depleted during the primary response. Collectively, these results suggest that the CD8+ T cell response to P815-CW3 tumor cells injected i.p. is strictly dependent upon recognition of a helper epitope by CD4+ T cells, whereas no such requirement is observed for i.d. injection.

ÄÄNEEN PERUSTUVA KÄYTTÄJÄN TODENTAMINEN PUHELINVERKON LISÄARVOPALVELUISSA

Tässä diplomityössä perehdytään puhujantunnistukseen ja sen käyttökelpoisuuteen käyttäjän henkilöllisyyden todentamisessa osana puhelinverkon lisäarvopalveluja. Puhelimitse ohjattavat palvelut ovat yleensä perustuneet puhelimen näppäimillä lähetettäviin äänitaajuusvalintoihin. Käyttäjän henkilöllisyydestä on voitu varmistua esimerkiksi käyttäjätunnuksen ja salaisen tunnusluvun perusteella. Tulevaisuudessa palvelut voivat perustua puheentunnistukseen, jolloin myös käyttäjän todentaminen äänen perusteella vaikuttaa järkevältä. Työssä esitellään aluksi erilaisia biometrisiä tunnistamismenetelmiä. Työssä perehdytään tarkemmin äänen perusteella tapahtuvaan puhujan todentamiseen. Työn käytännön osuudessa toteutettiin puhelinverkon palveluihin soveltuva puhujantodennussovelluksen prototyyppi. Työn tarkoituksena oli selvittää teknologian käyttömahdollisuuksia sekä kerätä kokemusta puhujantodennuspalvelun toteuttamisesta tulevaisuutta silmällä pitäen. Prototyypin toteutuksessa ohjelmointikielenä käytettiin Javaa.

Wavelet-based cepstrum calculation

In this paper we present a new wavelet-based algorithm for low-cost computation of the cepstrum. It can be used for real time precise pitch determination in automatic speech and speaker recognition systems. Many wavelet families are examined to determine the one that works best. The results confirm the efficacy and accuracy of the proposed technique for pitch extraction. (C) 2008 Elsevier B.V. All rights reserved.

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

On the determination of epsilon during discriminative GMM training

Discriminative training of Gaussian Mixture Models (GMMs) for speech or speaker recognition purposes is usually based on the gradient descent method, in which the iteration step-size, ε, uses to be defined experimentally. In this letter, we derive an equation to adaptively determine ε, by showing that the second-order Newton-Raphson iterative method to find roots of equations is equivalent to the gradient descent algorithm. © 2010 IEEE.

Influências do tamanho da ninhada e da atividade física sobre a plasticidade glial na formação hipocampal em modelo murino

Estudos anteriores demonstraram efeitos importantes do estresse perinatal no desempenho cognitivo na vida adulta e durante o envelhecimento. Entretanto permanece por ser estudado em detalhe como o exercício físico em diferentes fases da vida contribui para reduzir esses déficits. Isso é particularmente verdadeiro quando se trata de documentar as alterações da matriz extracelular e das células da glia, largamente ignoradas nesses estudos. Assim o objetivo geral do presente trabalho é o de investigar as possíveis influências do tamanho da ninhada e da atividade física sobre a memória de reconhecimento de objetos na vida adulta e possíveis alterações associadas à plasticidade glial e da matriz extracelular da formação hipocampal em modelo murino. Para alcançar esses objetivos alteramos o tamanho da ninhada de ratos Wistar de modo a acentuar o grau de competição entre os filhotes por tetas funcionais e diminuir a quantidade de cuidado materno por indivíduo. Durante o período de aleitamento quantificamos o cuidado materno em ninhadas de diferentes tamanhos. Em várias janelas temporais submetemos grupos selecionados de sujeitos ao exercício em esteira durante 5 semanas adotando o mesmo protocolo de treinamento. Após o exercício alguns grupos de animais adultos e senis foram submetidos ao teste de memória de reconhecimento de objetos que é dependente do hipocampo, sendo sacrificados e processados para imunohistoquímica seletiva para micróglia. Outros grupos de animais adultos não submetidos aos testes comportamentais foram igualmente sacrificados sendo um dos hemisférios empregado para registro de parâmetros difusionais no hipocampo enquanto que o outro foi empregado para imunohistoquímicas seletivas para astrócitos, células NG2 e reelina. Encontramos que o aumento do tamanho da ninhada está relacionado à redução do cuidado materno, ao declínio cognitivo, à proliferação e alteração da morfologia microglial, astrocitária e de células NG2 positivas, assim como às alterações nos padrões de difusão encontradas no tecido hipocampal. Além disso que tais alterações podem ser revertidas pelo menos de forma parcial pela atividade física e que esse efeito é tanto maior quanto mais jovem é o sujeito. O envelhecimento agrava as alterações morfológicas microgliais induzidas pelo aumento do tamanho da ninhada e reduz o desempenho nos testes de memória de reconhecimento de objeto. Os mecanismos moleculares associados a esses efeitos permanecem por ser investigados.

GMM-based classifiers for the automatic detection of obstructive sleep apnea

The aim of automatic pathological voice detection systems is to serve as tools, to medical specialists, for a more objective, less invasive and improved diagnosis of diseases. In this respect, the gold standard for those system include the usage of a optimized representation of the spectral envelope, either based on cepstral coefficients from the mel-scaled Fourier spectral envelope (Mel-Frequency Cepstral Coefficients) or from an all-pole estimation (Linear Prediction Coding Cepstral Coefficients) forcharacterization, and Gaussian Mixture Models for posterior classification. However, the study of recently proposed GMM-based classifiers as well as Nuisance mitigation techniques, such as those employed in speaker recognition, has not been widely considered inpathology detection labours. The present work aims at testing whether or not the employment of such speaker recognition tools might contribute to improve system performance in pathology detection systems, specifically in the automatic detection of Obstructive Sleep Apnea. The testing procedure employs an Obstructive Sleep Apnea database, in conjunction with GMM-based classifiers looking for a better performance. The results show that an improved performance might be obtained by using such approach.

Relevance of the glottal pulse and the vocal tract in gender detection

Gender detection is a very important objective to improve efficiency in tasks as speech or speaker recognition, among others. Traditionally gender detection has been focused on fundamental frequency (f0) and cepstral features derived from voiced segments of speech. The methodology presented here consists in obtaining uncorrelated glottal and vocal tract components which are parameterized as mel-frequency coefficients. K-fold and cross-validation using QDA and GMM classifiers showed that better detection rates are reached when glottal source and vocal tract parameters are used in a gender-balanced database of running speech from 340 speakers.

Desarrollo de una herramienta de análisis de la señal de voz

El habla es la principal herramienta de comunicación de la que dispone el ser humano que, no sólo le permite expresar su pensamiento y sus sentimientos sino que le distingue como individuo. El análisis de la señal de voz es fundamental para múltiples aplicaciones como pueden ser: síntesis y reconocimiento de habla, codificación, detección de patologías, identificación y reconocimiento de locutor… En el mercado se pueden encontrar herramientas comerciales o de libre distribución para realizar esta tarea. El objetivo de este Proyecto Fin de Grado es reunir varios algoritmos de análisis de la señal de voz en una única herramienta que se manejará a través de un entorno gráfico. Los algoritmos están siendo utilizados en el Grupo de investigación en Aplicaciones MultiMedia y Acústica de la Universidad Politécnica de Madrid para llevar a cabo su tarea investigadora y para ofertar talleres formativos a los alumnos de grado de la Escuela Técnica Superior de Ingeniería y Sistemas de Telecomunicación. Actualmente se ha encontrado alguna dificultad para poder aplicar los algoritmos ya que se han ido desarrollando a lo largo de varios años, por distintas personas y en distintos entornos de programación. Se han adaptado los programas existentes para generar una única herramienta en MATLAB que permite: . Detección de voz . Detección sordo/sonoro . Extracción y revisión manual de frecuencia fundamental de los sonidos sonoros . Extracción y revisión manual de formantes de los sonidos sonoros En todos los casos el usuario puede ajustar los parámetros de análisis y se ha mantenido y, en algunos casos, ampliado la funcionalidad de los algoritmos existentes. Los resultados del análisis se pueden manejar directamente en la aplicación o guardarse en un fichero. Por último se ha escrito el manual de usuario de la aplicación y se ha generado una aplicación independiente que puede instalarse y ejecutarse aunque no se disponga del software o de la versión adecuada de MATLAB. ABSTRACT. The speech is the main communication tool which has the human that as well as allowing to express his thoughts and feelings distinguishes him as an individual. The analysis of speech signal is essential for multiple applications such as: synthesis and recognition of speech, coding, detection of pathologies, identification and speaker recognition… In the market you can find commercial or open source tools to perform this task. The aim of this Final Degree Project is collect several algorithms of speech signal analysis in a single tool which will be managed through a graphical environment. These algorithms are being used in the research group Aplicaciones MultiMedia y Acústica at the Universidad Politécnica de Madrid to carry out its research work and to offer training workshops for students at the Escuela Técnica Superior de Ingeniería y Sistemas de Telecomunicación. Currently some difficulty has been found to be able to apply the algorithms as they have been developing over several years, by different people and in different programming environments. Existing programs have been adapted to generate a single tool in MATLAB that allows: . Voice Detection . Voice/Unvoice Detection . Extraction and manual review of fundamental frequency of voiced sounds . Extraction and manual review formant voiced sounds In all cases the user can adjust the scan settings, we have maintained and in some cases expanded the functionality of existing algorithms. The analysis results can be managed directly in the application or saved to a file. Finally we have written the application user’s manual and it has generated a standalone application that can be installed and run although the user does not have MATLAB software or the appropriate version.

Neural correlates of context-dependent memory : the role of the insula in episodic encoding and recognition memory ; an fMRI experiment

Magdeburg, Univ., Med. Fak., Diss., 2014