Visualização de padrões temporais cíclicos em estudos de fenologia

Orientadores: Ricardo da Silva Torres, Leonor Patrícia Cerdeira MorellatoTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Em diversas aplicações, grandes volumes de dados multidimensionais têm sido gerados continuamente ao longo do tempo. Uma abordagem adequada para lidar com estas coleções consiste no uso de métodos de visualização de informação, a partir dos quais padrões de interesse podem ser identificados, possibilitando o entendimento de fenômenos temporais complexos. De fato, em diversos domínios, o desenvolvimento de ferramentas adequadas para apoiar análises complexas, por exemplo, aquelas baseadas na identificação de padrões de mudanças ou correlações existentes entre múltiplas variáveis ao longo do tempo é de suma importância. Em estudos de fenologia, por exemplo, especialistas observam as mudanças que ocorrem ao longo da vida de plantas e animais e investigam qual é a relação entre essas mudanças com variáveis ambientais. Neste cenário, especialistas em fenologia cada vez mais precisam de ferramentas para, adequadamente, visualizar séries temporais longas, com muitas variáveis e de diferentes tipos (por exemplo, texto e imagem), assim como identificar padrões temporais cíclicos. Embora diversas abordagens tenham sido propostas para visualizar dados que variam ao longo do tempo, muitas não são apropriadas ou aplicáveis para dados de fenologia, porque não são capazes de: (i) lidar com séries temporais longas, com muitas variáveis de diferentes tipos de dados e de uma ou mais dimensões; e (ii) permitir a identificação de padrões temporais cíclicos e drivers ambientais associados. Este trabalho aborda essas questões a partir da proposta de duas novas abordagens para apoiar a análise e visualização de dados temporais multidimensionais. Nossa primeira proposta combina estruturas visuais radiais com ritmos visuais. As estruturas radiais são usadas para fornecer informação contextual sobre fenômenos cíclicos, enquanto que o ritmo visual é usado para sumarizar séries temporais longas em representações compactas. Nós desenvolvemos, avaliamos e validamos nossa proposta com especialistas em fenologia em tarefas relacionadas à visualização de dados de observação direta da fenologia de plantas em nível tanto de indivíduos quanto de espécies. Nós também validamos a proposta usando dados temporais relacionados a imagens obtidas de sistemas de monitoramento de vegetação próxima à superfície. Nossa segunda abordagem é uma nova representação baseada em imagem, chamada Change Frequency Heatmap (CFH), usada para codificar mudanças temporais de dados numéricos multivariados. O método calcula histogramas de padrões de mudanças observados em sucessivos instantes de tempo. Nós validamos o uso do CFH a partir da criação de uma ferramenta de caracterização de mudanças no ciclo de vida de plantas de múltiplos indivíduos e espécies ao longo do tempo. Nós demonstramos o potencial do CFH para ajudar na identificação visual de padrões de mudanças temporais complexas, especialmente na identificação de variações entre indivíduos em estudos relacionados à fenologia de plantasAbstract: In several applications, large volumes of multidimensional data have been generated continuously over time. One suitable approach for handling those collections in a meaningful way consists in the use of information visualization methods, based on which patterns of interest can be identified, triggering the understanding of complex temporal phenomena. In fact, in several domains, the development of appropriate tools for supporting complex analysis based, for example, on the identification of change patterns in temporal data or existing correlations, over time, among multiple variables, is of paramount importance. In phenology studies, for instance, phenologists observe changes in the development of plants and animals throughout their lives and investigate what is the relationship between these changes with environmental changes. Therefore, phenologists increasingly need tools for visualizing appropriately long-term series with many variables of different data types, as well as for identifying cyclical temporal patterns. Although several approaches have been proposed to visualize data varying over time, most of them are not appropriate or applicable to phenology data, because they are not able: (i) to handle long-term series with many variables of different data types and one or more dimensions and (ii) to support the identification of cyclical temporal patterns and associated environmental drivers. This work addresses these shortcomings by presenting two new approaches to support the analysis and visualization of multidimensional temporal data. Our first proposal to visualize phenological data combines radial visual structures along with visual rhythms. Radial visual structures are used to provide contextual insights regarding cyclical phenomena, while the visual rhythm encoding is used to summarize long-term time series into compact representations. We developed, evaluated, and validated our proposal with phenology experts using plant phenology direct observational data both at individuals and species levels. Also we validated the proposal using image-related temporal data obtained from near-surface vegetation monitoring systems. Our second approach is a novel image-based representation, named Change Frequency Heatmap (CFH), used to encode temporal changes of multivariate numerical data. The method computes histograms of change patterns observed at successive timestamps. We validated the use of CFHs through the creation of a temporal change characterization tool to support complex plant phenology analysis, concerning the characterization of plant life cycle changes of multiple individuals and species over time. We demonstrated the potential of CFH to support visual identification of complex temporal change patterns, especially to decipher interindividual variations in plant phenologyDoutoradoCiência da ComputaçãoDoutora em Ciência da Computação162312/2015-62013/501550-0CNPQCAPESFAPES

Reconhecimento de ações em vídeos baseado na fusão de representações de ritmos visuais

Orientadores: Hélio Pedrini, David Menotti GomesTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Avanços nas tecnologias de captura e armazenamento de vídeos têm promovido uma grande demanda pelo reconhecimento automático de ações. O uso de câmeras para propó- sitos de segurança e vigilância tem aplicações em vários cenários, tais coomo aeroportos, parques, bancos, estações, estradas, hospitais, supermercados, indústrias, estádios, escolas. Uma dificuldade inerente ao problema é a complexidade da cena sob condições habituais de gravação, podendo conter fundo complexo e com movimento, múltiplas pes- soas na cena, interações com outros atores ou objetos e movimentos de câmera. Bases de dados mais recentes são construídas principalmente com gravações compartilhadas no YouTube e com trechos de filmes, situações em que não se restringem esses obstáculos. Outra dificuldade é o impacto da dimensão temporal, pois ela infla o tamanho dos da- dos, aumentando o custo computacional e o espaço de armazenamento. Neste trabalho, apresentamos uma metodologia de descrição de volumes utilizando a representação de Ritmos Visuais (VR). Esta técnica remodela o volume original do vídeo em uma imagem, em que se computam descritores bidimensionais. Investigamos diferentes estratégias para construção do ritmo visual, combinando configurações em diversos domínios de imagem e direções de varredura dos quadros. A partir disso, propomos dois métodos de extração de características originais, denominados Naïve Visual Rhythm (Naïve VR) e Visual Rhythm Trajectory Descriptor (VRTD). A primeira abordagem é a aplicação direta da técnica no volume de vídeo original, formando um descritor holístico que considera os eventos da ação como padrões e formatos na imagem de ritmo visual. A segunda variação foca na análise de pequenas vizinhanças obtidas a partir do processo das trajetórias densas, que permite que o algoritmo capture detalhes despercebidos pela descrição global. Testamos a nossa proposta em oito bases de dados públicas, sendo uma de gestos (SKIG), duas em primeira pessoa (DogCentric e JPL), e cinco em terceira pessoa (Weizmann, KTH, MuHAVi, UCF11 e HMDB51). Os resultados mostram que a técnica empregada é capaz de extrair elementos de movimento juntamente com informações de formato e de aparência, obtendo taxas de acurácia competitivas comparadas com o estado da arteAbstract: Advances in video acquisition and storage technologies have promoted a great demand for automatic recognition of actions. The use of cameras for security and surveillance purposes has applications in several scenarios, such as airports, parks, banks, stations, roads, hospitals, supermarkets, industries, stadiums, schools. An inherent difficulty of the problem is the complexity of the scene under usual recording conditions, which may contain complex background and motion, multiple people on the scene, interactions with other actors or objects, and camera motion. Most recent databases are built primarily with shared recordings on YouTube and with snippets of movies, situations where these obstacles are not restricted. Another difficulty is the impact of the temporal dimension since it expands the size of the data, increasing computational cost and storage space. In this work, we present a methodology of volume description using the Visual Rhythm (VR) representation. This technique reshapes the original volume of the video into an image, where two-dimensional descriptors are computed. We investigated different strategies for constructing the representation by combining configurations in several image domains and traversing directions of the video frames. From this, we propose two feature extraction methods, Naïve Visual Rhythm (Naïve VR) and Visual Rhythm Trajectory Descriptor (VRTD). The first approach is the straightforward application of the technique in the original video volume, forming a holistic descriptor that considers action events as patterns and formats in the visual rhythm image. The second variation focuses on the analysis of small neighborhoods obtained from the process of dense trajectories, which allows the algorithm to capture details unnoticed by the global description. We tested our methods in eight public databases, one of hand gestures (SKIG), two in first person (DogCentric and JPL), and five in third person (Weizmann, KTH, MuHAVi, UCF11 and HMDB51). The results show that the developed techniques are able to extract motion elements along with format and appearance information, achieving competitive accuracy rates compared to state-of-the-art action recognition approachesDoutoradoCiência da ComputaçãoDoutor em Ciência da Computação2015/03156-7FAPES

Sport Modalities, Performance and Health

Sport modalities are highly practiced in order to improve many aspects of human beings, including performance and health. The increasing interest in the quantitative and qualitative aspects of sport training is ascribable to the fact that several training systems and new methodologies are appearing in all sport modalities. These methodologies can have different effects on the organism depending on the degree of training.On the other hand, some of the main objectives in sport research are to describe match activity and to detect effective performance indicators. A better knowledge of players' performance adaptations and game dynamics during competition is extremely useful for optimizing the training process. The need to develop training methodologies according to actions occurring during the game is essential for each sport

Understanding people through the aggregation of their digital footprints

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 160-172).Every day, millions of people encounter strangers online. We read their medical advice, buy their products, and ask them out on dates. Yet our views of them are very limited; we see individual communication acts rather than the person(s) as a whole. This thesis contends that socially-focused machine learning and visualization of archived digital footprints can improve the capacity of social media to help form impressions of online strangers. Four original designs are presented that each examine the social fabric of a different existing online world. The designs address unique perspectives on the problem of and opportunities offered by online impression formation. The first work, Is Britney Spears Span?, examines a way of prototyping strangers on first contact by modeling their past behaviors across a social network. Landscape of Words identifies cultural and topical trends in large online publics. Personas is a data portrait that characterizes individuals by collating heterogenous textual artifacts. The final design, Defuse, navigates and visualizes virtual crowds using metrics grounded in sociology. A reflection on these experimental endeavors is also presented, including a formalization of the problem and considerations for future research. A meta-critique by a panel of domain experts completes the discussion.by Aaron Robert Zinman.Ph.D

Using Auditory Modalities to Develop Rhythmic Competency in Children\u27s Fundamental Movement Skills

Physical education classrooms often have low levels of moderate to vigorous physical activity levels. This is a problem since many young elementary students are not building a foundation of fundamental movement skills necessary to be lifelong participants in physical activities. This study investigated how elementary physical education teachers used auditory modalities in their classrooms. The research question explored the emergence of rhythmic competency in fundamental movement skills to increase overall moderate to vigorous activity levels. This concurrent, mixed-methods, multiple case study used a constructivist paradigm using the schema and dynamic system theories as the underlying motor system theoretical framework. Two research sites were selected: a suburban Maryland public school system and a private liberal arts college located in the same county. The participants included 21 elementary physical education teachers and 6 physical education or exercise science majors from nationally recognized programs. Data were collected from a focus group, interviews, classroom observations, and a 10-item response Likert style survey designed for elementary physical education teachers to recognize current trends in the field of auditory modalities and rhythmic competency. The data were analyzed to identify auditory modality instructional methods for the emergence of rhythmic competencies. The results consisted of a list of best practices for use such as musical rhythms, verbal cues, and sound cues by physical education teachers and specialists. This research promotes positive social change by providing information for successfully planning interventions in the discipline of motor skill and rhythmic development that can lead to overall increased more-vigorous physical activity

Columbus State University Honors College: Senior Theses, Fall 2021/Spring 2022

This is a collection of senior theses written by honors students at Columbus State University during the Fall 2021 and Spring 2022 semesters.https://csuepress.columbusstate.edu/honors_theses/1003/thumbnail.jp

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Open articulations

Open Articulations invites an exchange between human and environmental worlds through cycles of improvisation, reflection, and rebirth. It is a study of how exchanges emerge, what forms they can take, how they are mediated, and how we can sustain them with each other and with our surroundings. Through our coordinated immersion in landscapes and our spontaneous creation in them through frameworks encouraging play, we channel the spirit of a jazz drummer riffing with his midnight quartet, exchanging rhythms, images, sounds, movements, and textual fragments. A gentle breath, a flickering sensation, a gesture: expressions of a specific time rooted in a specific place. The thesis is a window into how we experience and perceive landscapes in our own way through places that are often geographically separated, and how we find a sense of belonging in place through our improvisation and mindful presence in these spaces. Through a call and response with each other and with our own environments, we become motivated to explore new directions in our spaces, to take creative risks, and to nurture a more forgiving atmosphere, embracing our own and others’ mistakes. In making participatory archives of our experiences, we open a collective space for multiple voices to be heard and explore a shared history of a territory, thus offering new ways of understanding a place and each other. Together, our voices find new resonance points, commonalities, contrasts, and tunings, and our expressions take on new meaning as a result. This in turn shapes our next engagement with the world

Contextualizing Entrepreneurship Theory

As the breadth and empirical diversity of entrepreneurship research have increased rapidly during the last decade, the quest to find a "one-size-fits-all" general theory of entrepreneurship has given way to a growing appreciation for the importance of contexts. This promises to improve both the practical relevance and the theoretical rigor of research in this field. Entrepreneurship means different things to different people at different times and in different places and both its causes and its consequences likewise vary. For example, for some people entrepreneurship can be a glorious path to emancipation, while for others it can represent the yoke tethering them to the burdens of overwork and drudgery. For some communities it can drive renaissance and vibrancy while for others it allows only bare survival. In this book, we assess and attempt to push forward contemporary conceptualizations of contexts that matter for entrepreneurship, pointing in particular to opportunities generating new insights by attending to contexts in novel or underexplored ways. This book shows that the ongoing contextualization of entrepreneurship research should not simply generate a proliferation of unique theories – one for every context – but can instead result in better theory construction, testing and understanding of boundary conditions, thereby leading us to richer and more profound understanding of entrepreneurship across its many forms. Contextualizing Entrepreneurship Theory will critically review the current debate and existing literature on contexts and entrepreneurship and use this to synthesize new theoretical and methodological frameworks that point to important directions for future research

Contextualizing Entrepreneurship Theory

As the breadth and empirical diversity of entrepreneurship research have increased rapidly during the last decade, the quest to find a "one-size-fits-all" general theory of entrepreneurship has given way to a growing appreciation for the importance of contexts. This promises to improve both the practical relevance and the theoretical rigor of research in this field. Entrepreneurship means different things to different people at different times and in different places and both its causes and its consequences likewise vary. For example, for some people entrepreneurship can be a glorious path to emancipation, while for others it can represent the yoke tethering them to the burdens of overwork and drudgery. For some communities it can drive renaissance and vibrancy while for others it allows only bare survival. In this book, we assess and attempt to push forward contemporary conceptualizations of contexts that matter for entrepreneurship, pointing in particular to opportunities generating new insights by attending to contexts in novel or underexplored ways. This book shows that the ongoing contextualization of entrepreneurship research should not simply generate a proliferation of unique theories – one for every context – but can instead result in better theory construction, testing and understanding of boundary conditions, thereby leading us to richer and more profound understanding of entrepreneurship across its many forms. Contextualizing Entrepreneurship Theory will critically review the current debate and existing literature on contexts and entrepreneurship and use this to synthesize new theoretical and methodological frameworks that point to important directions for future research