With the booming development of WWW, many search engines have been developed to help users to find useful information from a great quantity of data. However, users may have different needs in different situations. Opposite to the Information Retrieval where users retrieve data actively, Information Filtering (IF) sends information from servers to passive users through broadcast mediums, rather than being searched by them. Therefore, each user has his (or her) profile stored in the database, where a profile records a set of interest items that can present his (or her) interests or habits. To efficiently store many user profiles in servers and filter irrelevant users, many signature-based index techniques are applied in IF systems. By using signatures, IF does not need to compare each item of profiles to filter out irrelevant ones. However, because signatures are incomplete information of profiles, it is very hard to answer the complex queries by using only the signatures. Therefore, a critical issue of the signature-based IF service is how to index the signatures of user profiles for an efficient filtering process. There are often two types of queries in the signature-based IF systems, the inexact filtering and the similarity search queries. In the inexact filtering, a query is an incoming document and it needs to find the profiles whose interest items are all included in the query. On the other hand, in the similarity search, a query is a user profile and it needs to find the users whose interest items are similar to the query user. In this thesis, we propose an ID-tree index strategy, which indexes signatures of user profiles by partitioning them into subgroups using a binary tree structure according to all of the different items among them. Basically, our ID-tree index strategy is a kind of the signature tree. In an ID-tree, each path from the root to a leaf node is the signature of the profile pointed by the leaf node. Because each profile is pointed only by one leaf node of the ID-tree, there will be no collision in the structure. In other words, there will be no two profiles assigned to the same signature. Moreover, only the different items among subgroups of profiles will be checked at one time to filter out irrelevant profiles for queries. Therefore, our strategy can answer the inexact filtering and the similarity search queries with less number of accessed profiles as compared to the previous strategies. Moreover, to build the index of signatures, it needs less time to batch a great deal of database profiles. From our simulation results, we show that our strategy can access less number of profiles to answer the queries than Chen's signature tree strategy for the inexact filtering and Aggarwal et al.'s SG-table strategy for the similarity search.

Due to convenience and efficiency, electronic voting (e-voting) techniques gradually replace traditional paper-based voting activities in some developed countries. A secure anonymous e-voting system has to satisfy many properties, such as completeness, tally correctness, and uncoercibility, where the uncoercibility property is the most difficult one to be achieved. Since each voter can obtain a voting receipt in an electronic voting system, coercion and bribe (vote-buying and vote-selling are included) become more and more serious in electronic voting environments than traditional paper-based voting environments. Unfortunately, most of the solutions, like receipt-freeness or untappable channels, proposed in the literature, are impractical owing to lack of efficiency or too complicated to be implemented. It will make uncoercible e-voting systems unacceptable by the people. In order to cope with the drawbacks of the previous schemes, this thesis will present a generic idea, which is independent of the underlying cryptographic components, on electronic voting to achieve the uncoercibility property and other requirements. The proposed method is an efficient and quite practical solution to match the current environments of electronic voting.

Project aim – preparation of electronic signature certification authority (CA) project and certificate managing software (information system) prototype. The work reviews the problems of electronic signature infrastructure development in Lithuania. The analytical survey of electronic signature CA was carried out. The standards determining the structure of electronic signature Certificate, CA activities, requirements for Trustworthy Systems Managing Certificates were examined. The organizational structure of CA was prepared and working model was worked out. The workflow model was worked out to depict the hierarchy of certification processes. The use case model were created for certificate issuing, data processing and providing data of revoked certificates. Detail descriptions of information streams between the system and computerized tasks are provided. Structural diagrams on the information streams were created. According to information flows the entity relations diagram was created, the logical structure of data bases (DB) for certificates was developed. The DB Esign of valid certificates and DB Esign_archives of revoked certificates were created. Specification of program modules was made up. Three types of manuals were prepared for system users – a manual for the client, a manual for the user and a manual for the programmer. The certificate managing system prototype was tested. The results of the experiment are presented. For practical realization of the project the... [to full text]

While all the modern world is moving to the electronic space and the services are assuming a digital form, one also gives thought to the means to approach to this more and more often, and one of many of the means is digital signature. Electronic signature would even overtake its inky prototype not only in science or IT business, but also in the heads of the consumers, if there were not any traditional, organizational barriers, any fear of innovations and uncertainty amongst many other factors that are useful to explore. The most popular implementation of digital signature - PKI (Public key infrastructure) – can fill a lot more than one function; the variety of all of the PKI application areas is very wide. Also known as assymetric cryptography, PKI can provide an opportunity not only to sign a document, but also a reverse process is possible, that is to communicate safely in the Internet or other net using public key for encoding and private key for decoding. The paper strives to point out the essence and the main principles of PKI, to disclose its possibilities and means for the organizations and the users, to analyse the empirical information in an organization, to measure the current PKI situation in Lithuania also touching Europe, to reveal the mindset and behaviour peculiarities of a potential user of the digital signature. / Visam šiuolaikiniam pasauliui persikeliant į elektronines erdves, paslaugoms įgaunant skaitmeninę formą, vis dažniau susimąstoma ir apie visas priemones tam pasiekti, iš kurių viena – e.parašas. E.parašas kai kuriais atžvilgiais netgi lenktų rašalinį savo prototipą ne tik moksle ir IT versle, bet ir vartotojų galvose, jei ne tradiciniai, organizaciniai barjerai, naujovių ir nežinomybės baimė, bei daugelis kitų veiksnių, kuriuos naudinga ištirti. Labiausiai paplitusi e.parašo realizacija PKI (Public key infrastructure) – viešojo rakto infrastruktūra – gali atlikti žymiai daugiau nei vieną funkciją, visos PKI taikymo sričių įvairovės darbe nepavyktų atskleisti dėl vietos ir laiko stokos. Dar vadinama asimetriniu šifravimu, PKI gali ne tik suteikti galimybę pasirašyti dokumentą, bet įmanomas ir atvirkštinis procesas, t.y., užšifravimui naudojant viešąjį, o iššifravimui – privatųjį raktą, saugiai komunikuoti internete ar kitame tinkle. Darbas siekia parodyti PKI esmę ir pagrindinius principus, atskleisti galimybes ir priemones organizacijoms ir vartotojams, išanaliztuoi empirinę informaciją organizacijoje, įvertinti dabartinę PKI situaciją Lietuvoje, paliečiant Europą, atskleisti galimo skaitmeninio parašo vartotojo elgsenos ypatumus.

The online trading is growing widely day by day, which makes safety the biggest concern while carrying out trading by electronic means. As many other operations can be done with digital environment and internet, operation that provides identity validation should also be added to the digital environment. When data are transferred, the user should make sure that there are no changes in the original data while transferring them from sender to receiver. And it has also become necessary to authenticate the users often to ensure security and to avoid fraud. There are lot of different ways of online identification, in which digital signature is considered to be one of the powerful way of authentication. So, the online user use digital signature to authenticate the sender and to maintain the integrity of the document sent. In this paper, a study is carried out to identify the usage of digital signature and the perspective of people towards it in developed and developing countries and a survey is taken to support the theory.

The field of metagenomics has shown great promise in the ability to recover microbial DNA from communities whose members resist traditional cultivation techniques, although in most instances the recovered material comprises short anonymous genomic fragments rather than complete genome sequences. In order to effectively assess the microbial diversity and ecology represented in such samples, accurate methods for DNA classification capable of assigning metagenomic fragments into their most likely taxonomic unit are required. Existing DNA classification methods have shown high levels of accuracy in attempting to classify sequences derived from low-complexity communities, however genome distinguishability generally deteriorates for complex communities or those containing closely related organisms. The goal of this thesis was to identify factors both intrinsic or external to the genome that may lead to the improvement of existing DNA classification methods and to probe the fundamental limitations of composition-based genome distinguishability. To assess the suite of factors affecting the distinguishability of genomes, support vector machine classifiers were trained to discriminate between pairs of microbial genomes using the relative frequencies of oligonucleotide patterns calculated from orthologous genes or short genomic fragments, and the resulting classification accuracy scores used as the measure of genomic distinguishability. Models were generated in order to relate distinguishability to several measures of genomic and taxonomic similarity, and interesting outlier genome pairs were identified by large residuals to the fitted models. Examination of the outlier pairs identified numerous factors that influence genome distinguishability, including genome reduction, extreme G+C composition, lateral gene transfer, and habitat-induced genome convergence. Fragments containing multiple protein-coding and non-coding sequences showed an increased tendency for misclassification, except in cases where the genomes were very closely related. Analysis of the biological function annotations associated with each fragment demonstrated that certain functional role categories showed increased or decreased tendency for misclassification. The use of pre-processing steps including DNA recoding, unsupervised clustering, 'symmetrization' of oligonucleotide frequencies, and correction for G+C content did not improve distinguishability. Existing composition-based DNA classifiers will benefit from the results reported in this thesis. Sequence-segmentation approaches will improve genome distinguishability by decreasing fragment heterogeneity, while factors such as habitat, lifestyle, extreme G+C composition, genome reduction, and biological role annotations may be used to express confidence in the classification of individual fragments. Although genome distinguishability tends to be proportional to genomic and taxonomic relatedness, these trends can be violated for closely related genome pairs that have undergone rapid compositional divergence, or unrelated genome pairs that have converged in composition due to similar habitats or unusual selective pressures. Additionally, there are fundamental limits to the resolution of composition-based classifiers when applied to genomic fragments typical of current metagenomic studies.

Temperate maize is one of few model species that relies mainly on endogenous indicators of the plant’s developmental stage to cue the onset of reproductive development. The INDETERMINATE1 (ID1) transcription factor is a key regulator of the floral transition and id1 mutants are very late-flowering. ID1 is expressed and remains localized in developing leaves, while florigenic signals originate in mature, photosynthetically active leaves. Since very little is known about the molecular components of the floral transition in maize, and in autonomously flowering species at large, this work utilized id1 mutants to analyze the transcriptional and physiological alterations associated with the floral transition in maize. Analyses of functional categories of transcriptional change between developing leaves of id1 non-flowering mutants and normal flowering maize suggest a role for ID1 in energy metabolism and epigenetic regulation of leaf development. In addition, a novel family of -glucosidase genes were found to be expressed exclusively in immature leaves of normal flowering maize in a pattern similar to the ID1 gene suggesting that these genes may act in concert downstream of ID1. Further, profiling of transcript and metabolite alterations in mature leaves, which are likely the source of floral cues, suggest that coordination of resource storage in the form of transitory starch is an important signal for floral promotion in maize. Finally, analysis of the floral transition in Balsas teosinte, the progenitor of modern maize and an obligate short-day plant, suggests that ID1 may define a regulatory module unique to the autonomous floral regulation pathway in maize and related grass species.

Human gait identification has become an active area of research due to increased security requirements. Human gait identification is a potential new tool for identifying individuals beyond traditional methods. The emergence of motion capture techniques provided a chance of high accuracy in identification because completely recorded gait information can be recorded compared with security cameras. The aim of this research was to build a practical method of gait identification and investigate the individual characteristics of gait. For this purpose, a gait identification approach was proposed, identification results were compared by different methods, and several studies about the individual characteristics of gait were performed. This research included the following: (1) a novel, effective set of gait features were proposed; (2) gait signatures were extracted by three different methods: statistical method, principal component analysis, and Fourier expansion method; (3) gait identification results were compared by these different methods; (4) two indicators were proposed to evaluate gait features for identification; (5) novel and clear definitions of gait phases and gait cycle were proposed; (6) gait features were investigated by gait phases; (7) principal component analysis and the fixing root method were used to elucidate which features were used to represent gait and why; (8) gait similarity was investigated; (9) gait attractiveness was investigated. This research proposed an efficient framework for identifying individuals from gait via a novel feature set based on 3D motion capture data. A novel evaluating method of gait signatures for identification was proposed. Three different gait signature extraction methods were applied and compared. The average identification rate was over 93%, with the best result close to 100%. This research also proposed a novel dividing method of gait phases, and the different appearances of gait features in eight gait phases were investigated. This research identified the similarities and asymmetric appearances between left body movement and right body movement in gait based on the proposed gait phase dividing method. This research also initiated an analysing method for gait features extraction by the fixing root method. A prediction model of gait attractiveness was built with reasonable accuracy by principal component analysis and linear regression of natural logarithm of parameters. A systematic relationship was observed between the motions of individual markers and the attractiveness ratings. The lower legs and feet were extracted as features of attractiveness by the fixing root method. As an extension of gait research, human seated motion was also investigated.

Sub-Riemannian geometry is the natural setting for studying dynamical systems, as noise often has a lower dimension than the dynamics it enters. This makes sub-Riemannian geometry an important field of study. In this thesis, we analysis some of the aspects of sub-Riemannian diffusion processes on manifolds. We first focus on studying the small-time asymptotics of sub-Riemannian diffusion bridges. After giving an overview of recent work by Bailleul, Mesnager and Norris on small-time fluctuations for the bridge of a sub-Riemannian diffusion, we show, by providing a specific example, that, unlike in the Riemannian case, small-time fluctuations for sub-Riemannian diffusion bridges can exhibit exotic behaviours, that is, qualitatively different behaviours compared to Brownian bridges. We further extend the analysis by Bailleul, Mesnager and Norris of small-time fluctuations for sub-Riemannian diffusion bridges, which assumes the initial and final positions to lie outside the sub-Riemannian cut locus, to the diagonal and describe the asymptotics of sub-Riemannian diffusion loops. We show that, in a suitable chart and after a suitable rescaling, the small-time diffusion loop measures have a non-degenerate limit, which we identify explicitly in terms of a certain local limit operator. Our analysis also allows us to determine the loop asymptotics under the scaling used to obtain a small-time Gaussian limit for the sub-Riemannian diffusion bridge measures by Bailleul, Mesnager and Norris. In general, these asymptotics are now degenerate and need no longer be Gaussian. We close by reporting on work in progress which aims to understand the behaviour of Brownian motion conditioned to have vanishing $N$th truncated signature in the limit as $N$ tends to infinity. So far, it has led to an analytic proof of the stand-alone result that a Brownian bridge in $\mathbb{R}^d$ from $0$ to $0$ in time $1$ is more likely to stay inside a box centred at the origin than any other Brownian bridge in time $1$.

A deduplicação consiste na tarefa de identificar quais objetos (registros, documentos, textos, etc.) são potencialmente os mesmos em uma base de dados (ou em um conjunto de bases de dados). A identificação de dados duplicados depende da intervenção do usuário, principalmente para a criação de um conjunto contendo pares duplicados e não duplicados. Tais informações são usadas para ajudar na identificação de outros possíveis pares duplicados presentes na base de dados. Em geral, quando a deduplicação é estendida para grandes conjuntos de dados, a eficiência e a qualidade das duplicatas dependem diretamente do “ajuste” de um usuário especialista. Nesse cenário, a configuração das principais etapas da deduplicação (etapas de blocagem e classificação) demandam que o usuário seja responsável pela tarefa pouco intuitiva de definir valores de limiares e, em alguns casos, fornecer pares manualmente rotulados. Desse modo, o processo de calibração exige que o usuário detenha um conhecimento prévio sobre as características específicas da base de dados e os detalhes do funcionamento do método de deduplicação. O objetivo principal desta tese é tratar do problema da configuração da deduplicação de grandes bases de dados, de modo a reduzir o esforço do usuário. O usuário deve ser somente requisitado para rotular um conjunto reduzido de pares automaticamente selecionados. Para isso, é proposta uma metodologia, chamada FS-Dedup, que incorpora algoritmos do estado da arte da deduplicação para permitir o processamento de grandes volumes de dados e adiciona um conjunto de estratégias com intuito de possibilitar a definição dos parâmetros do deduplicador, removendo os detalhes de configuração da responsabilidade do usuário. A metodologia pode ser vista como uma camada capaz de identificar as informações requisitadas pelo deduplicador (principalmente valores de limiares) a partir de um conjunto de pares rotulados pelo usuário. A tese propõe também uma abordagem que trata do problema da seleção dos pares informativos para a criação de um conjunto de treinamento reduzido. O desafio maior é selecionar um conjunto reduzido de pares suficientemente informativo para possibilitar a configuração da deduplicação com uma alta eficácia. Para isso, são incorporadas estratégias para reduzir o volume de pares candidatos a um algoritmo de aprendizagem ativa. Tal abordagem é integrada à metodologia FS-Dedup para possibilitar a remoção da intervenção especialista nas principais etapas da deduplicação. Por fim, um conjunto exaustivo de experimentos é executado com objetivo de validar as ideias propostas. Especificamente, são demonstrados os promissores resultados alcançados nos experimentos em bases de dados reais e sintéticas, com intuito de reduzir o número de pares manualmente rotulados, sem causar perdas na qualidade da deduplicação. / Deduplication is the task of identifying which objects (e.g., records, texts, documents, etc.) are potentially the same in a given dataset (or datasets). It usually requires user intervention in several stages of the process, mainly to ensure that pairs representing matchings and non-matchings can be determined. This information can be used to help detect other potential duplicate records. When deduplication is applied to very large datasets, the matching quality depends on expert users. The expert users are requested to define threshold values and produce a training set. This intervention requires user knowledge of the noise level of the data and a particular approach to deduplication so that it can be applied to configure the most important stages of the process (e.g. blocking and classification). The main aim of this thesis is to provide solutions to help in tuning the deduplication process in large datasets with a reduced effort from the user, who is only required to label an automatically selected subset of pairs. To achieve this, we propose a methodology, called FS-Dedup, which incorporates state-of-the-art algorithms in its deduplication core to address high performance issues. Following this, a set of strategies is proposed to assist in setting its parameters, and removing most of the detailed configuration concerns from the user. The methodology proposed can be regarded as a layer that is able to identify the specific information requested in the deduplication approach (mainly, threshold values) through pairs that are manually labeled by the user. Moreover, this thesis proposed an approach which would enable to select an informative set of pairs to produce a reduced training set. The main challenge here is how to select a “representative” set of pairs to configure the deduplication with high matching quality. In this context, the proposed approach incorporates an active learning method with strategies that allow the deduplication to be carried out on large datasets. This approach is integrated with the FS-Dedup methodology to avoid the need for a definition of threshold values in the most important deduplication stages. Finally, exhaustive experiments using both synthetic and real datasets have been conducted to validate the ideas outlined in this thesis. In particular, we demonstrate the ability of our approach to reduce the user effort without degrading the matching quality.