The copy-and-paste paradigm is a fundamental operation in graphical user interfaces. However, existing copy-and-paste techniques have limitations, in particular in terms of efficiency and robustness against interruptions. This thesis is focusing on improving the user interface used to copy-and-paste objects across different contexts, such as a series folders. To improve this fundamental operation, a new copy-and-paste technique, called Bag-and-Dump, is proposed, implemented and evaluated. Bag-and-Dump aims to substantially reduce mouse movement by allowing the user to gather up (‘bag’) source data across different folders before ‘dumping’ the whole load at the destination. Additionally, Bag-and-Dump provides constant visual feedback in the form of a bag-like semantic cursor to increase robustness against interruptions. Bag-and-Dump was eval- uated against two standard copy-and-paste techniques (Keyboard Shortcuts and Drag-and-Drop) under a different number of contexts (folders) and with and without inter- ruptions. Results from the experiment not only showed that Bag-and-Dump indeed significantly reduces mouse movement, it also confirmed that Bag-and-Dump was 9% faster than Keyboard Shortcuts, one of the most popular copy-paste techniques among “expert users”.

In this work we investigated the in vivo and in vitro ecological conditions that can favour the fumonisin production, both free and hidden forms, in the maize-Fusarium verticillioides pathosystem. Samples of different maize hybrids have been collected from dough to the harvest maturity to follow the trend of fungal incidence and both fumonisin forms contamination, but also the changes in chemical composition. Differences in the level of contamination have been found among hybrids during the growing season. Furthermore, the production of fumonisins has been found correlated to the total lipids content, another parameter that changed during the growing season. This finding underlined the existence of a relationship between toxin contamination and fatty acids composition of the hybrids. Recently the existence of a cross talk between plant and pathogen has been demonstrated, based on some oxidized signal molecules (oxylipins) produced from fatty acid precursors. This result was also confirmed by the molecular analysis on the in vitro pathosystem that showed differences in the activation of the genes involved in plant and fungal oxylipins production during the incubation time. Also post-harvest contamination of maize was investigated in this study, with particular attention to the effects of the drying treatment, a common post-harvest practice aimed at decreasing the water availability, and to the storage capacity of a new low cost storage system, silo bag. The drying treatment was showed to affect fumonisins content, in particular an increased fumonisins contamination was detected after heat treatments. This increment seemed to be produced by chemical changes of matrix components, caused by high temperature, that produced the release of hidden fumonisin in free form. Silo bags were shown to be an effective system to store cereals because no significant change occurred in fungi or toxins contamination during a 9-month storage. Therefore, being more flexible and less expensive than traditional store houses, they should be very useful for farmers.

This thesis presents a framework for automatic recognition of human actions in uncontrolled, realistic video data such as movies, internet and surveillance videos. In this thesis, the human action recognition problem is solved from the perspective of local spatio-temporal feature and bag-of-features representation. The bag-of-features model only contains statistics of unordered low-level primitives, and any information concerning temporal ordering and spatial structure is lost. To address this issue, we proposed a novel multiscale local part model on the purpose of maintaining both structure information and ordering of local events for action recognition. The method includes both a coarse primitive level root feature covering event-content statistics and higher resolution overlapping part features incorporating local structure and temporal relationships. To extract the local spatio-temporal features, we investigated a random sampling strategy for efficient action recognition. We also introduced the idea of using very high sampling density for efficient and accurate classification. We further explored the potential of the method with the joint optimization of two constraints: the classification accuracy and its efficiency. On the performance side, we proposed a new local descriptor, called GBH, based on spatial and temporal gradients. It significantly improved the performance of the pure spatial gradient-based HOG descriptor on action recognition while preserving high computational efficiency. We have also shown that the performance of the state-of-the-art MBH descriptor can be improved with a discontinuity-preserving optical flow algorithm. In addition, a new method based on histogram intersection kernel was introduced to combine multiple channels of different descriptors. This method has the advantages of improving recognition accuracy with multiple descriptors and speeding up the classification process. On the efficiency side, we applied PCA to reduce the feature dimension which resulted in fast bag-of-features matching. We also evaluated the FLANN method on real-time action recognition. We conducted extensive experiments on real-world videos from challenging public action datasets. We showed that our methods achieved the state-of-the-art with real-time computational potential, thus highlighting the effectiveness and efficiency of the proposed methods.

Orientador: Rogério Peres Soratto / Resumo: O clima é fator imprescindível para a agricultura. Frente às mudanças climáticas situações extremas relacionando água e temperatura do ar e do solo são determinantes para a produção agrícola. A produção de alimentos, como o feijão, estará ameaçada caso não se desenvolva novas cultivares com maior tolerância ou resistência à seca e alta temperatura adaptados ao bioma brasileiro. Bancos de dados fenotípicos e genotípicos gerados na área de recursos genéticos auxiliam na escolha de genitores com características desejáveis, que possuam variabilidade alélica e produzam populações segregantes promissoras. No acervo de germoplasma de feijão comum do Banco Ativo de Germoplasma da Embrapa Arroz e Feijão existem 745 acessos de feijão do grupo comercial mulatinho. Este grupo é importante, tanto pelo cultivo como, pela possibilidade de seleção de características interessantes às extremidades climáticas. Isso se deve ao ambiente de cultivo que ocorre onde predominam solos de baixa fertilidade e clima seco e quente, como o norte de Minas Gerais e região Nordeste do país. Foi realizado screening inicial, em que foram selecionados 240 acessos mais pertinentes às características buscadas para cultivares com este tipo de grão. Estes acessos foram submetidos a testes mais minuciosos com relação a cada característica buscada. Dos 240 acessos testados e analisados, foram selecionados os 100 acessos que asseguraram a conservação de alelos distintos presentes no grupo. Essa conclusão é geral e fund... (Resumo completo, clicar acesso eletrônico abaixo) / Doutor

O presente trabalho tem por objetivo avaliar a técnica de desaguamento de resíduos sólidos gerados em estações de tratamento de água utilizando tubos geotêxteis - Bags, que representam uma alternativa tecnológica para a redução do teor de umidade dos resíduos. O trabalho foi dividido em duas etapas: ensaios com Bags suspensos e com Bags dispostos sobre o solo. Nos estudos são abordadas as características mais relevantes do processo de desaguamento face às solicitações mecânicas e hidráulicas a que qualquer sistema está submetido, bem como são apresentados resultados e discussões sobre as características físico-químicas dos resíduos gerados, geocondicionados nos Bags geotêxteis e da água drenada. A técnica de desaguamento por Bags mostrou-se uma alternativa viável para a redução do teor de umidade, apresentando um melhor desempenho em relação às técnicas convencionais. Pode-se também utilizá-la em paralelo com outras técnicas já existentes para a otimização do processo de desaguamento. Ressalta-se que a correta operação da tecnologia garante a eficiência da drenagem, sendo, então, necessária a adição de polímeros como agentes coagulantes, de forma a promover a separação da fase líquida da fase sólida. Observou-se que os resíduos geocondicionados ao reduzirem o teor de umidade passam a concentrar alguns componentes químicos tais como: sílica, nitrogênio e alumínio. As dificuldades relacionadas à disposição de resíduos sólidos em estações de tratamento de água justificam esse estudo. A despeito dos resultados satisfatórios desse estudo, é importante salientar a necessidade de mais projetos que avaliem os resultados obtidos nos ensaios e o comportamento dos Bags com o passar do tempo, já que a técnica mostrou-se viável ambiental, econômica e tecnicamente. / The present study aims at evaluating the disposal process of slurry from a water treatment plant. In replacement to the conventional technique of disposing slurry in pools, a geotextile tube has been used to dehydrate and retain the slurry inside the Bag. This is achieved because the geotextile is permeable, yet soil-tight, and any excess water pressure is expelled from the tube. The work has been divided in two sets of tests: suspended Bags to define a treatment methodology and a prototype geoBag laid on the ground over a drained layer to simulate the treatment process. The mechanical, hydraulic and chemical responses associated with this process considering both solid waste and drained water contents have been evaluated and discussed. As a whole, the use of geoBags has proved to be a viable option to reduce the water content in slurry, as well as an attractive alternative to replace or to be combined with other techniques currently in use in Brazil. A critical aspect controlling the efficiency of the operation is the addition of polymers for flocculation before introducing slurry into the Bag so that liquid and solid phases are dissociated. Upon monitoring the process, it has been observed that solids retained inside the Bag exhibit concentrated levels of chemical components such as silica, nitrogen and aluminum. This study has been considered relevant in face of the environmental needs and public policy control of the disposal of solid wastes. In spite of being a promising alternative technique to slurry treatment, further investigation is needed to evaluate the trials results of this research and bag behavior as time goes by. So far, the technique has proved to be environmentally, economically and technically feasible.

O presente trabalho tem por objetivo avaliar a técnica de desaguamento de resíduos sólidos gerados em estações de tratamento de água utilizando tubos geotêxteis - Bags, que representam uma alternativa tecnológica para a redução do teor de umidade dos resíduos. O trabalho foi dividido em duas etapas: ensaios com Bags suspensos e com Bags dispostos sobre o solo. Nos estudos são abordadas as características mais relevantes do processo de desaguamento face às solicitações mecânicas e hidráulicas a que qualquer sistema está submetido, bem como são apresentados resultados e discussões sobre as características físico-químicas dos resíduos gerados, geocondicionados nos Bags geotêxteis e da água drenada. A técnica de desaguamento por Bags mostrou-se uma alternativa viável para a redução do teor de umidade, apresentando um melhor desempenho em relação às técnicas convencionais. Pode-se também utilizá-la em paralelo com outras técnicas já existentes para a otimização do processo de desaguamento. Ressalta-se que a correta operação da tecnologia garante a eficiência da drenagem, sendo, então, necessária a adição de polímeros como agentes coagulantes, de forma a promover a separação da fase líquida da fase sólida. Observou-se que os resíduos geocondicionados ao reduzirem o teor de umidade passam a concentrar alguns componentes químicos tais como: sílica, nitrogênio e alumínio. As dificuldades relacionadas à disposição de resíduos sólidos em estações de tratamento de água justificam esse estudo. A despeito dos resultados satisfatórios desse estudo, é importante salientar a necessidade de mais projetos que avaliem os resultados obtidos nos ensaios e o comportamento dos Bags com o passar do tempo, já que a técnica mostrou-se viável ambiental, econômica e tecnicamente. / The present study aims at evaluating the disposal process of slurry from a water treatment plant. In replacement to the conventional technique of disposing slurry in pools, a geotextile tube has been used to dehydrate and retain the slurry inside the Bag. This is achieved because the geotextile is permeable, yet soil-tight, and any excess water pressure is expelled from the tube. The work has been divided in two sets of tests: suspended Bags to define a treatment methodology and a prototype geoBag laid on the ground over a drained layer to simulate the treatment process. The mechanical, hydraulic and chemical responses associated with this process considering both solid waste and drained water contents have been evaluated and discussed. As a whole, the use of geoBags has proved to be a viable option to reduce the water content in slurry, as well as an attractive alternative to replace or to be combined with other techniques currently in use in Brazil. A critical aspect controlling the efficiency of the operation is the addition of polymers for flocculation before introducing slurry into the Bag so that liquid and solid phases are dissociated. Upon monitoring the process, it has been observed that solids retained inside the Bag exhibit concentrated levels of chemical components such as silica, nitrogen and aluminum. This study has been considered relevant in face of the environmental needs and public policy control of the disposal of solid wastes. In spite of being a promising alternative technique to slurry treatment, further investigation is needed to evaluate the trials results of this research and bag behavior as time goes by. So far, the technique has proved to be environmentally, economically and technically feasible.

Submitted by ANA CLÁUDIA DE LIMA SILVA (analima.agro@gmail.com) on 2018-01-30T14:24:27Z No. of bitstreams: 1 Microsoft Word - tese 54 - inicio-Combinação .pdf: 1436840 bytes, checksum: dc6ffd99c8230d99f4026c94bfb54e06 (MD5) / Rejected by Maria Lucia Martins Frederico null (mlucia@fca.unesp.br), reason: Prezada Inserir em seu arquivo a folha de aprovação . Se por ventura alterar a numeração deverá solicitar nova ficha catalográfica. on 2018-01-30T17:21:28Z (GMT) / Submitted by ANA CLÁUDIA DE LIMA SILVA (analima.agro@gmail.com) on 2018-03-16T06:59:47Z No. of bitstreams: 1 Tese Versão Final.pdf: 4005531 bytes, checksum: 3f8d92005723ab54f36f313d780308e0 (MD5) / Approved for entry into archive by Maria Lucia Martins Frederico null (mlucia@fca.unesp.br) on 2018-03-16T11:19:03Z (GMT) No. of bitstreams: 1 silva_acl_dr_botfca.pdf: 4005531 bytes, checksum: 3f8d92005723ab54f36f313d780308e0 (MD5) / Made available in DSpace on 2018-03-16T11:19:03Z (GMT). No. of bitstreams: 1 silva_acl_dr_botfca.pdf: 4005531 bytes, checksum: 3f8d92005723ab54f36f313d780308e0 (MD5) Previous issue date: 2017-05-31 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / O clima é fator imprescindível para a agricultura. Frente às mudanças climáticas situações extremas relacionando água e temperatura do ar e do solo são determinantes para a produção agrícola. A produção de alimentos, como o feijão, estará ameaçada caso não se desenvolva novas cultivares com maior tolerância ou resistência à seca e alta temperatura adaptados ao bioma brasileiro. Bancos de dados fenotípicos e genotípicos gerados na área de recursos genéticos auxiliam na escolha de genitores com características desejáveis, que possuam variabilidade alélica e produzam populações segregantes promissoras. No acervo de germoplasma de feijão comum do Banco Ativo de Germoplasma da Embrapa Arroz e Feijão existem 745 acessos de feijão do grupo comercial mulatinho. Este grupo é importante, tanto pelo cultivo como, pela possibilidade de seleção de características interessantes às extremidades climáticas. Isso se deve ao ambiente de cultivo que ocorre onde predominam solos de baixa fertilidade e clima seco e quente, como o norte de Minas Gerais e região Nordeste do país. Foi realizado screening inicial, em que foram selecionados 240 acessos mais pertinentes às características buscadas para cultivares com este tipo de grão. Estes acessos foram submetidos a testes mais minuciosos com relação a cada característica buscada. Dos 240 acessos testados e analisados, foram selecionados os 100 acessos que asseguraram a conservação de alelos distintos presentes no grupo. Essa conclusão é geral e fundamentada em um modelo teórico que adota, a partir das variáveis estudadas, suposições sobre alguns parâmetros utilizados no cálculo das similaridades de acessos. Esses 100 acessos foram selecionados e compuseram experimentos em Porangatu-Goiás para caracterização morfoagronômica e em Santo Antônio de Goiás para caracterização nos ambientes considerados normais. A partir do resultado dos experimentos com os 100 acessos foi possível definir os 30 acessos que compuseram a coleção temática para altas temperaturas. Foi observado que as médias alcançadas produtividade de grãos por acesso foi respectivamente, foi de 2068,88 e 1227,19 kg ha-1, para os ambientes de Santo Antônio de Goiás-GO e Porangatu-GO quando avaliado os 96 acessos, sendo que esse valor se altera para quando se faz a seleção para a formação temática, e o valor vai de para 2400,83 e 1271,48, respectivamente. Com os 30 acessos também realizou-se a caracterização fenotípica radicular da coleção temática. A análise dos dados permitiu identificar genótipos superiores em relação aos caracteres avaliados, mas não houve correlações significativas e de elevada magnitude entre os caracteres avaliados. Os dados foram avaliados conjuntamente com a produtividade dos acessos da coleção temática avaliados para alta temperatura em Porangatu – GO e foi verificado divergências em relação à produção e sistema radicular. / The climate is factor indispensable for agriculture. Due to climate change extreme situations water and air temperature related which are very important for the agricultural production. The production of food, including the beans, will be threatened if there isn’t development of new varieties of beans, with more tolerance or resistance to drought and high temperature adapted to the Brazilian biome. Bank of phenotypic data, generated in the area of genetic resources help in the selection of parents with desirable characteristics, which have allelic variability and produce promising segregating populations. In the collection of comum bean germplasm of active bank of germaplasm of Embrapa Rice and Beans there are 745 accessions of bean of the mulatinho commercial group. This group it’s important, both by cultivation and by the possibility of selecting interesting characteristics ate climatic extremes. This is due to the cultivation environment that occurs where soils of low fertility and dry and hot climate predominate, such as the north of Minas Gerais and the Northeast region of the country. An initial screening was performed, in which 240 accessions were selected that were more pertinent to the characteristics sought for cultivars with this type of grain. These accesses were subjected to more detailed test in relation to each characteristic. Of the 240 accessions tested and analyzed, we selected the 100 accesses that ensured the conservation of distinct alleles present in the group. This conclusion in general and based on a theoretical model that adopts, based on the studied variables, assumption about some parameters used in the calculation of the similarities of accesses. These 100 accessions were selected and composed experiment in Porangatu – Goias for morphoagronomic characterization in environments considered normal. From the results of experiments with the 100 accessions it was possible to define the 30 accesses that composed the thematic collection for high temperatures. It was observed that the averages reached grain yield per access were, respectively, 2068.88 and 1227.19 Kg ha-1, for the environments of Santo Antonio of Goias and Porangatu both in Goias, that this value changes when the selection is made for the thematic formation, and the value goes from 2400.83 and 1271.4, respectively. With the 30 accesses, the phenotypic root characterization of the thematic collection. The analysis of the data allowed to identify superior genotypes in relation to the evaluated characters, but there were no significant correlation and of high magnitude among the evaluated characters. The data were evaluated together with the productivity of the accesses of the thematic collection evaluated for high temperature in Porangatu in Goias and differences were verified in relation to the production and root system. / 2014/01695-5

abstract: Temporal data are increasingly prevalent and important in analytics. Time series (TS) data are chronological sequences of observations and an important class of temporal data. Fields such as medicine, finance, learning science and multimedia naturally generate TS data. Each series provide a high-dimensional data vector that challenges the learning of the relevant patterns This dissertation proposes TS representations and methods for supervised TS analysis. The approaches combine new representations that handle translations and dilations of patterns with bag-of-features strategies and tree-based ensemble learning. This provides flexibility in handling time-warped patterns in a computationally efficient way. The ensemble learners provide a classification framework that can handle high-dimensional feature spaces, multiple classes and interaction between features. The proposed representations are useful for classification and interpretation of the TS data of varying complexity. The first contribution handles the problem of time warping with a feature-based approach. An interval selection and local feature extraction strategy is proposed to learn a bag-of-features representation. This is distinctly different from common similarity-based time warping. This allows for additional features (such as pattern location) to be easily integrated into the models. The learners have the capability to account for the temporal information through the recursive partitioning method. The second contribution focuses on the comprehensibility of the models. A new representation is integrated with local feature importance measures from tree-based ensembles, to diagnose and interpret time intervals that are important to the model. Multivariate time series (MTS) are especially challenging because the input consists of a collection of TS and both features within TS and interactions between TS can be important to models. Another contribution uses a different representation to produce computationally efficient strategies that learn a symbolic representation for MTS. Relationships between the multiple TS, nominal and missing values are handled with tree-based learners. Applications such as speech recognition, medical diagnosis and gesture recognition are used to illustrate the methods. Experimental results show that the TS representations and methods provide better results than competitive methods on a comprehensive collection of benchmark datasets. Moreover, the proposed approaches naturally provide solutions to similarity analysis, predictive pattern discovery and feature selection. / Dissertation/Thesis / Ph.D. Industrial Engineering 2012

La représentation d’image sous une forme hiérarchique a été largement utilisée dans un contexte de classification. Une telle représentation est capable de modéliser le contenu d’une image à travers une structure arborescente. Dans cette thèse, nous étudions les méthodes à noyaux qui permettent de prendre en entrée des données sous une forme structurée et de tenir compte des informations topologiques présentes dans chaque structure en concevant des noyaux structurés. Nous présentons un noyau structuré dédié aux structures telles que des arbres non ordonnés et des chemins (séquences de noeuds) équipés de caractéristiques numériques. Le noyau proposé, appelé Bag of Subpaths Kernel (BoSK), est formé en sommant les noyaux calculés sur les sous-chemins (un sac de tous les chemins et des noeuds simples) entre deux sacs. Le calcul direct de BoSK amène à une complexité quadratique par rapport à la taille de la structure (nombre de noeuds) et la quantité de données (taille de l’ensemble d’apprentissage). Nous proposons également une version rapide de notre algorithme, appelé Scalable BoSK (SBoSK), qui s’appuie sur la technique des Random Fourier Features pour projeter les données structurées dans un espace euclidien, où le produit scalaire du vecteur transformé est une approximation de BoSK. Cet algorithme bénéficie d’une complexité non plus linéaire mais quadratique par rapport aux tailles de la structure et de l’ensemble d’apprentissage, rendant ainsi le noyau adapté aux situations d’apprentissage à grande échelle. Grâce à (S)BoSK, nous sommes en mesure d’effectuer un apprentissage à partir d’informations présentes à plusieurs échelles dans les représentations hiérarchiques d’image. (S)BoSK fonctionne sur des chemins, permettant ainsi de tenir compte du contexte d’un pixel (feuille de la représentation hiérarchique) par l’intermédiaire de ses régions ancêtres à plusieurs échelles. Un tel modèle est utilisé dans la classification des images au niveau pixel. (S)BoSK fonctionne également sur les arbres, ce qui le rend capable de modéliser la composition d’un objet (racine de la représentation hiérarchique) et les relations topologiques entre ses sous-parties. Cette stratégie permet la classification des tuiles ou parties d’image. En poussant plus loin l’utilisation de (S)BoSK, nous introduisons une nouvelle approche de classification multi-source qui effectue la classification directement à partir d’une représentation hiérarchique construite à partir de deux images de la même scène prises à différentes résolutions, éventuellement selon différentes modalités. Les évaluations sur plusieurs jeux de données de télédétection disponibles dans la communauté illustrent la supériorité de (S)BoSK par rapport à l’état de l’art en termes de précision de classification, et les expériences menées sur une tâche de classification urbaine montrent la pertinence de l’approche de classification multi-source proposée. / Hierarchical image representations have been widely used in the image classification context. Such representations are capable of modeling the content of an image through a tree structure. In this thesis, we investigate kernel-based strategies that make possible taking input data in a structured form and capturing the topological patterns inside each structure through designing structured kernels. We develop a structured kernel dedicated to unordered tree and path (sequence of nodes) structures equipped with numerical features, called Bag of Subpaths Kernel (BoSK). It is formed by summing up kernels computed on subpaths (a bag of all paths and single nodes) between two bags. The direct computation of BoSK yields a quadratic complexity w.r.t. both structure size (number of nodes) and amount of data (training size). We also propose a scalable version of BoSK (SBoSK for short), using Random Fourier Features technique to map the structured data in a randomized finite-dimensional Euclidean space, where inner product of the transformed feature vector approximates BoSK. It brings down the complexity from quadratic to linear w.r.t. structure size and amount of data, making the kernel compliant with the large-scale machine-learning context. Thanks to (S)BoSK, we are able to learn from cross-scale patterns in hierarchical image representations. (S)BoSK operates on paths, thus allowing modeling the context of a pixel (leaf of the hierarchical representation) through its ancestor regions at multiple scales. Such a model is used within pixel-based image classification. (S)BoSK also works on trees, making the kernel able to capture the composition of an object (top of the hierarchical representation) and the topological relationships among its subparts. This strategy allows tile/sub-image classification. Further relying on (S)BoSK, we introduce a novel multi-source classification approach that performs classification directly from a hierarchical image representation built from two images of the same scene taken at different resolutions, possibly with different modalities. Evaluations on several publicly available remote sensing datasets illustrate the superiority of (S)BoSK compared to state-of-the-art methods in terms of classification accuracy, and experiments on an urban classification task show the effectiveness of proposed multi-source classification approach.

The purpose of this thesis is to develop a toolkit to visualize bag calculations for teaching. We take full advantage of interaction techniques in Computer Science to achieve it, which could lead to a modern and impressive way for teaching.   In this thesis, the developed toolkit is going to show the bag calculations and corresponding animations interactively and aesthetically which make new learners easier to acquire the concept of multiset.