A rank aggregation framework for video multimodal geocoding

This paper proposes a rank aggregation framework for video multimodal geocoding. Textual and visual descriptions associated with videos are used to define ranked lists. These ranked lists are later combined, and the resulting ranked list is used to define appropriate locations for videos. An architecture that implements the proposed framework is designed. In this architecture, there are specific modules for each modality (e.g, textual and visual) that can be developed and evolved independently. Another component is a data fusion module responsible for combining seamlessly the ranked lists defined for each modality. We have validated the proposed framework in the context of the MediaEval 2012 Placing Task, whose objective is to automatically assign geographical coordinates to videos. Obtained results show how our multimodal approach improves the geocoding results when compared to methods that rely on a single modality (either textual or visual descriptors). We also show that the proposed multimodal approach yields comparable results to the best submissions to the Placing Task in 2012 using no extra information besides the available development/training data. Another contribution of this work is related to the proposal of a new effectiveness evaluation measure. The proposed measure is based on distance scores that summarize how effective a designed/tested approach is, considering its overall result for a test dataset. © 2013 Springer Science+Business Media New York.

Fusão de dados multisensor para a identificação e o mapeamento de ambientes flúvio-estuarinos da Amazônia

A fusão de imagens multisensor tem sido um procedimento amplamente utilizado em função da natureza complementar dos vários conjuntos de dados. Este artigo compara o desempenho de quatro métodos diferentes para fusão de imagens Landsat-7 ETM+ e RADARSAT-1 W1. A comparação foi baseada nas características espectrais das imagens, utilizando-se de análise estatística e visual dos produtos gerados. Quatro métodos foram usados para a fusão das imagens Landsat-7 ETM+ e RADARSAT-1 W1: i) fusão do SAR (radar de abertura sintética) com a tríade selecionada pelo OIF (Optimum Index Factor); ii) realce por decorrelação da tríade selecionada pelo OIF, seguida da fusão com SAR; iii) ACP (Análise por Componentes Principais) para as seis bandas ETM+ do espectro refletido (1, 2, 3, 4, 5 e 7) e posterior fusão das três primeiras componentes principais (1CP; 2CP; 3CP) com o SAR; iv) SPC-SAR (Principal Componente Seletivo - SAR). O produto SPC-SAR mostrou melhor desempenho na identificação das feições costeiras e permitiu o realce mais efetivo dos diferentes ambientes.

Geoestatística multivariada na delimitação de zonas de manejo na cultura de cana-de-açúcar

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Leitor contemporâneo: os livros mais vendidos no Brasil de 1966 a 2004

Este trabalho procura examinar o que o leitor brasileiro contemporâneo lê, com o propósito de explicar as razões que levam esse leitor a realizar suas escolhas. Nesse sentido, portanto, o objetivo central do trabalho será examinar o perfil desse leitor brasileiro. O levantamento dos dados para estabelecer o corpus da pesquisa foi realizado por meio do registro das listas de livros mais vendidos, publicadas em dois jornais brasileiros. O primeiro jornal fonte da pesquisa foi o Leia, periódico mensal que circulou no território nacional durante o período de abril de 1978 a setembro de 1991. O segundo, foi o Jornal do Brasil, diário carioca que publicou listas dos livros mais vendidos no Brasil a partir de 1966 até o mês de dezembro de 2004, data de encerramento da pesquisa, em caderno destinado à leitura. Como o segundo jornal interrompeu a publicação das listas dos mais vendidos durante o período de fevereiro de 1976 a abril de 1984, propusemos uma fusão dos dados dos dois jornais de forma a cobrir um período que compreende os anos de 1966 até 2004. A base teórica a partir da qual se estabeleceu o exame do perfil do leitor brasileiro foi a semiótica da escola de Paris. Para o tratamento da questão da leitura elegeu-se o exame das manifestações da enunciação no discurso, as projeções do enunciador e do enunciatário e o tratamento das paixões. Foram observados em cada um dos textos do corpus como essas categorias enunciativas projetam-se em cada um dos textos mais lidos pelos leitores brasileiros e, posteriormente, como, nas listas dos livros mais vendidos, esse leitor manifesta-se como enunciador. Para tanto propôs-se a contraposição entre o ethos do enunciador-leitor das listas e o pathos do enunciatário dos discursos de leitura. Uma vez que o corpus da pesquisa revelou um crescimento na opção pelos textos de auto-ajuda, foi examinada a questão específica... (Resumo completo, clicar acesso eletrônico abaixo)

Efficient subsequence alignment of time series

Zeitreihen sind allgegenwärtig. Die Erfassung und Verarbeitung kontinuierlich gemessener Daten ist in allen Bereichen der Naturwissenschaften, Medizin und Finanzwelt vertreten. Das enorme Anwachsen aufgezeichneter Datenmengen, sei es durch automatisierte Monitoring-Systeme oder integrierte Sensoren, bedarf außerordentlich schneller Algorithmen in Theorie und Praxis. Infolgedessen beschäftigt sich diese Arbeit mit der effizienten Berechnung von Teilsequenzalignments. Komplexe Algorithmen wie z.B. Anomaliedetektion, Motivfabfrage oder die unüberwachte Extraktion von prototypischen Bausteinen in Zeitreihen machen exzessiven Gebrauch von diesen Alignments. Darin begründet sich der Bedarf nach schnellen Implementierungen. Diese Arbeit untergliedert sich in drei Ansätze, die sich dieser Herausforderung widmen. Das umfasst vier Alignierungsalgorithmen und ihre Parallelisierung auf CUDA-fähiger Hardware, einen Algorithmus zur Segmentierung von Datenströmen und eine einheitliche Behandlung von Liegruppen-wertigen Zeitreihen.rnrnDer erste Beitrag ist eine vollständige CUDA-Portierung der UCR-Suite, die weltführende Implementierung von Teilsequenzalignierung. Das umfasst ein neues Berechnungsschema zur Ermittlung lokaler Alignierungsgüten unter Verwendung z-normierten euklidischen Abstands, welches auf jeder parallelen Hardware mit Unterstützung für schnelle Fouriertransformation einsetzbar ist. Des Weiteren geben wir eine SIMT-verträgliche Umsetzung der Lower-Bound-Kaskade der UCR-Suite zur effizienten Berechnung lokaler Alignierungsgüten unter Dynamic Time Warping an. Beide CUDA-Implementierungen ermöglichen eine um ein bis zwei Größenordnungen schnellere Berechnung als etablierte Methoden.rnrnAls zweites untersuchen wir zwei Linearzeit-Approximierungen für das elastische Alignment von Teilsequenzen. Auf der einen Seite behandeln wir ein SIMT-verträgliches Relaxierungschema für Greedy DTW und seine effiziente CUDA-Parallelisierung. Auf der anderen Seite führen wir ein neues lokales Abstandsmaß ein, den Gliding Elastic Match (GEM), welches mit der gleichen asymptotischen Zeitkomplexität wie Greedy DTW berechnet werden kann, jedoch eine vollständige Relaxierung der Penalty-Matrix bietet. Weitere Verbesserungen umfassen Invarianz gegen Trends auf der Messachse und uniforme Skalierung auf der Zeitachse. Des Weiteren wird eine Erweiterung von GEM zur Multi-Shape-Segmentierung diskutiert und auf Bewegungsdaten evaluiert. Beide CUDA-Parallelisierung verzeichnen Laufzeitverbesserungen um bis zu zwei Größenordnungen.rnrnDie Behandlung von Zeitreihen beschränkt sich in der Literatur in der Regel auf reellwertige Messdaten. Der dritte Beitrag umfasst eine einheitliche Methode zur Behandlung von Liegruppen-wertigen Zeitreihen. Darauf aufbauend werden Distanzmaße auf der Rotationsgruppe SO(3) und auf der euklidischen Gruppe SE(3) behandelt. Des Weiteren werden speichereffiziente Darstellungen und gruppenkompatible Erweiterungen elastischer Maße diskutiert.

Design and implementation of a 3D computer game controller using inertial MEMS sensors

Though 3D computer graphics has seen tremendous advancement in the past two decades, most available mechanisms for computer interaction in 3D are high cost and targeted for industry and virtual reality applications. Recent advances in Micro-Electro-Mechanical-System (MEMS) devices have brought forth a variety of new low-cost, low-power, miniature sensors with high accuracy, which are well suited for hand-held devices. In this work a novel design for a 3D computer game controller using inertial sensors is proposed, and a prototype device based on this design is implemented. The design incorporates MEMS accelerometers and gyroscopes from Analog Devices to measure the three components of the acceleration and angular velocity. From these sensor readings, the position and orientation of the hand-held compartment can be calculated using numerical methods. The implemented prototype is utilizes a USB 2.0 compliant interface for power and communication with the host system. A Microchip dsPIC microcontroller is used in the design. This microcontroller integrates the analog to digital converters, the program memory flash, as well as the core processor, on a single integrated circuit. A PC running Microsoft Windows operating system is used as the host machine. Prototype firmware for the microcontroller is developed and tested to establish the communication between the design and the host, and perform the data acquisition and initial filtering of the sensor data. A PC front-end application with a graphical interface is developed to communicate with the device, and allow real-time visualization of the acquired data.

A user supported object tracking framework for interactive video production

We present a user supported tracking framework that combines automatic tracking with extended user input to create error free tracking results that are suitable for interactive video production. The goal of our approach is to keep the necessary user input as small as possible. In our framework, the user can select between different tracking algorithms - existing ones and new ones that are described in this paper. Furthermore, the user can automatically fuse the results of different tracking algorithms with our robust fusion approach. The tracked object can be marked in more than one frame, which can significantly improve the tracking result. After tracking, the user can validate the results in an easy way, thanks to the support of a powerful interpolation technique. The tracking results are iteratively improved until the complete track has been found. After the iterative editing process the tracking result of each object is stored in an interactive video file that can be loaded by our player for interactive videos.

Raw as Archival Still Image Format: A Consideration

Source materials like fine art, over-sized, fragile maps, and delicate artifacts have traditionally been digitally converted through the use of controlled lighting and high resolution scanners and camera backs. In addition the capture of items such as general and special collections bound monographs has recently grown both through consortial efforts like the Internet Archive's Open Content Alliance and locally at the individual institution level. These projects, in turn, have introduced increasingly higher resolution consumer-grade digital single lens reflex cameras or "DSLRs" as a significant part of the general cultural heritage digital conversion workflow. Central to the authors' discussion is the fact that both camera backs and DSLRs commonly share the ability to capture native raw file formats. Because these formats include such advantages as access to an image's raw mosaic sensor data within their architecture, many institutions choose raw for initial capture due to its high bit-level and unprocessed nature. However to date these same raw formats, so important to many at the point of capture, have yet to be considered "archival" within most published still imaging standards, if they are considered at all. Throughout many workflows raw files are deleted and thrown away after more traditionally "archival" uncompressed TIFF or JPEG 2000 files have been derived downstream from their raw source formats [1][2]. As a result, the authors examine the nature of raw anew and consider the basic questions, Should raw files be retained? What might their role be? Might they in fact form a new archival format space? Included in the discussion is a survey of assorted raw file types and their attributes. Also addressed are various sustainability issues as they pertain to archival formats with a special emphasis on both raw's positive and negative characteristics as they apply to archival practices. Current common archival workflows versus possible raw-based ones are investigated as well. These comparisons are noted in the context of each approach's differing levels of usable captured image data, various preservation virtues, and the divergent ideas of strictly fixed renditions versus the potential for improved renditions over time. Special attention is given to the DNG raw format through a detailed inspection of a number of its various structural components and the roles that they play in the format's latest specification. Finally an evaluation is drawn of both proprietary raw formats in general and DNG in particular as possible alternative archival formats for still imaging.

Recognition of activities of daily living in healthy subjects using two ad-hoc classifiers

Activities of daily living (ADL) are important for quality of life. They are indicators of cognitive health status and their assessment is a measure of independence in everyday living. ADL are difficult to reliably assess using questionnaires due to self-reporting biases. Various sensor-based (wearable, in-home, intrusive) systems have been proposed to successfully recognize and quantify ADL without relying on self-reporting. New classifiers required to classify sensor data are on the rise. We propose two ad-hoc classifiers that are based only on non-intrusive sensor data. METHODS: A wireless sensor system with ten sensor boxes was installed in the home of ten healthy subjects to collect ambient data over a duration of 20 consecutive days. A handheld protocol device and a paper logbook were also provided to the subjects. Eight ADL were selected for recognition. We developed two ad-hoc ADL classifiers, namely the rule based forward chaining inference engine (RBI) classifier and the circadian activity rhythm (CAR) classifier. The RBI classifier finds facts in data and matches them against the rules. The CAR classifier works within a framework to automatically rate routine activities to detect regular repeating patterns of behavior. For comparison, two state-of-the-art [Naïves Bayes (NB), Random Forest (RF)] classifiers have also been used. All classifiers were validated with the collected data sets for classification and recognition of the eight specific ADL. RESULTS: Out of a total of 1,373 ADL, the RBI classifier correctly determined 1,264, while missing 109 and the CAR determined 1,305 while missing 68 ADL. The RBI and CAR classifier recognized activities with an average sensitivity of 91.27 and 94.36%, respectively, outperforming both RF and NB. CONCLUSIONS: The performance of the classifiers varied significantly and shows that the classifier plays an important role in ADL recognition. Both RBI and CAR classifier performed better than existing state-of-the-art (NB, RF) on all ADL. Of the two ad-hoc classifiers, the CAR classifier was more accurate and is likely to be better suited than the RBI for distinguishing and recognizing complex ADL.

Proglacial river dataset from the Akuliarusiarsuup Kuua River northern tributary, Southwest Greenland, 2008 - 2013, version 2.0

The dataset contains measurements of river stage and discharge for one sites along the Akuliarusiarsuup Kuua River's northern tributary, with 30 minute temporal resolution between June 2008 and August 2013 This river is a tributary to the Watson River discharging into Kangerlussuaq Fjord by the town of Kangerlussuaq, Southwest Greenland. Additional data of water temperature, air pressure are also provided. Compared to version 1.0 of the dataset, this dataset used a total of 36 in situ discharge observations collected between 2008 and 2012 to construct the rating curve. Furthermore, data of Station AK-004-001 between 2010-09-06T11:30 to 2010-09-07T13:30 have been removed from version 2.0 because these values were likely caused by backflow when a jokulhlaup from a large glacier dammed lake caused increased water levels in the downstreams lake. Thus, data measured at AK-004-001 between 2010-09-06T11:30 to 2010-09-07T13:30 are not representative for the AK-004 catchment.

Registry of all samples from the Tara Oceans Expedition (2009-2013)

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. Data sets in this collection provide methodological and environmental context to all samples collected during the Tara Oceans Expedition (2009-2013).

Desing and Validation of a Light Inference System to Support Embedded Context Reasoning

Embedded context management in resource-constrained devices (e.g. mobile phones, autonomous sensors or smart objects) imposes special requirements in terms of lightness for data modelling and reasoning. In this paper, we explore the state-of-the-art on data representation and reasoning tools for embedded mobile reasoning and propose a light inference system (LIS) aiming at simplifying embedded inference processes offering a set of functionalities to avoid redundancy in context management operations. The system is part of a service-oriented mobile software framework, conceived to facilitate the creation of context-aware applications—it decouples sensor data acquisition and context processing from the application logic. LIS, composed of several modules, encapsulates existing lightweight tools for ontology data management and rule-based reasoning, and it is ready to run on Java-enabled handheld devices. Data management and reasoning processes are designed to handle a general ontology that enables communication among framework components. Both the applications running on top of the framework and the framework components themselves can configure the rule and query sets in order to retrieve the information they need from LIS. In order to test LIS features in a real application scenario, an ‘Activity Monitor’ has been designed and implemented: a personal health-persuasive application that provides feedback on the user’s lifestyle, combining data from physical and virtual sensors. In this case of use, LIS is used to timely evaluate the user’s activity level, to decide on the convenience of triggering notifications and to determine the best interface or channel to deliver these context-aware alerts.d

Design and Validation of a Light Inference System to Support Embedded Context Reasoning

Embedded context management in resource-constrained devices (e.g. mobile phones, autonomous sensors or smart objects) imposes special requirements in terms of lightness for data modelling and reasoning. In this paper, we explore the state-of-the-art on data representation and reasoning tools for embedded mobile reasoning and propose a light inference system (LIS) aiming at simplifying embedded inference processes offering a set of functionalities to avoid redundancy in context management operations. The system is part of a service-oriented mobile software framework, conceived to facilitate the creation of context-aware applications?it decouples sensor data acquisition and context processing from the application logic. LIS, composed of several modules, encapsulates existing lightweight tools for ontology data management and rule-based reasoning, and it is ready to run on Java-enabled handheld devices. Data management and reasoning processes are designed to handle a general ontology that enables communication among framework components. Both the applications running on top of the framework and the framework components themselves can configure the rule and query sets in order to retrieve the information they need from LIS. In order to test LIS features in a real application scenario, an ?Activity Monitor? has been designed and implemented: a personal health-persuasive application that provides feedback on the user?s lifestyle, combining data from physical and virtual sensors. In this case of use, LIS is used to timely evaluate the user?s activity level, to decide on the convenience of triggering notifications and to determine the best interface or channel to deliver these context-aware alerts.

Unsupervised method to classify PM10 pollutant concentrations

In this paper a method based mainly on Data Fusion and Artificial Neural Networks to classify one of the most important pollutants such as Particulate Matter less than 10 micrometer in diameter (PM10) concentrations is proposed. The main objective is to classify in two pollution levels (Non-Contingency and Contingency) the pollutant concentration. Pollutant concentrations and meteorological variables have been considered in order to build a Representative Vector (RV) of pollution. RV is used to train an Artificial Neural Network in order to classify pollutant events determined by meteorological variables. In the experiments, real time series gathered from the Automatic Environmental Monitoring Network (AEMN) in Salamanca Guanajuato Mexico have been used. The method can help to establish a better air quality monitoring methodology that is essential for assessing the effectiveness of imposed pollution controls, strategies, and facilitate the pollutants reduction.

Integración de Fuentes con Información de Contexto y Sistemas Interactivos

Durante el transcurso de esta Tesis Doctoral se ha realizado un estudio de la problemática asociada al desarrollo de sistemas de interacción hombre-máquina sensibles al contexto. Este problema se enmarca dentro de dos áreas de investigación: los sistemas interactivos y las fuentes de información contextual. Tradicionalmente la integración entre ambos campos se desarrollaba a través de soluciones verticales específicas, que abstraen a los sistemas interactivos de conocer los procedimientos de bajo nivel de acceso a la información contextual, pero limitan su interoperabilidad con otras aplicaciones y fuentes de información. Para solventar esta limitación se hace imprescindible potenciar soluciones interoperables que permitan acceder a la información del mundo real a través de procedimientos homogéneos. Esta problemática coincide perfectamente con los escenarios de \Computación Ubicua" e \Internet de las Cosas", donde se apunta a un futuro en el que los objetos que nos rodean serán capaces de obtener información del entorno y comunicarla a otros objetos y personas. Los sistemas interactivos, al ser capaces de obtener información de su entorno a través de la interacción con el usuario, pueden tomar un papel especial en este escenario tanto como consumidores como productores de información. En esta Tesis se ha abordado la integración de ambos campos teniendo en cuenta este escenario tecnológico. Para ello, en primer lugar se ha realizado un an álisis de las iniciativas más importantes para la definición y diseño de sistemas interactivos, y de las principales infraestructuras de suministro de información. Mediante este estudio se ha propuesto utilizar el lenguaje SCXML del W3C para el diseño de los sistemas interactivos y el procesamiento de los datos proporcionados por fuentes de contexto. Así, se ha reflejado cómo las capacidades del lenguaje SCXML para combinar información de diferentes modalidades pueden también utilizarse para procesar e integrar información contextual de diferentes fuentes heterogéneas, y por consiguiente diseñar sistemas de interacción sensibles al contexto. Del mismo modo se presenta a la iniciativa Sensor Web, y a su extensión semántica Semantic Sensor Web, como una iniciativa idónea para permitir un acceso y suministro homogéneo de la información a los sistemas interactivos sensibles al contexto. Posteriormente se han analizado los retos que plantea la integración de ambos tipos de iniciativas. Como resultado se ha conseguido establecer una serie de funcionalidades que son necesarias implementar para llevar a cabo esta integración. Utilizando tecnologías que aportan una gran flexibilidad al proceso de implementación y que se apoyan en recomendaciones y estándares actuales, se implementaron una serie de desarrollos experimentales que integraban las funcionalidades identificadas anteriormente. Finalmente, con el fin de validar nuestra propuesta, se realizaron un conjunto de experimentos sobre un entorno de experimentación que simula el escenario de la conducción. En este escenario un sistema interactivo se comunica con una extensión semántica de una plataforma basada en los estándares de la Sensor Web para poder obtener información y publicar las observaciones que el usuario realizaba al sistema. Los resultados obtenidos han demostrado la viabilidad de utilizar el lenguaje SCXML para el diseño de sistemas interactivos sensibles al contexto que requieren acceder a plataformas avanzadas de información para consumir y publicar información a la vez que interaccionan con el usuario. Del mismo modo, se ha demostrado cómo la utilización de tecnologías semánticas en los procesos de consulta y publicación de información puede facilitar la reutilización de la información publicada en infraestructuras Sensor Web por cualquier tipo de aplicación, y de este modo contribuir al futuro escenario de Internet de las Cosas. ABSTRACT In this Thesis, we have addressed the difficulties related to the development of context-aware human-machine interaction systems. This issue is part of two research fields: interactive systems and contextual information sources. Traditionally both fields have been integrated through domain-specific vertical solutions that allow interactive systems to access contextual information without having to deal with low-level procedures, but restricting their interoperability with other applications and heterogeneous data sources. Thus, it is essential to boost the research on interoperable solutions that provide access to real world information through homogeneous procedures. This issue perfectly matches with the scenarios of \Ubiquitous Computing" and \Internet of Things", which point toward a future in which many objects around us will be able to acquire meaningful information about the environment and communicate it to other objects and to people. Since interactive systems are able to get information from their environment through interaction with the user, they can play an important role in this scenario as they can both consume real-world data and produce enriched information. This Thesis deals with the integration of both fields considering this technological scenario. In order to do this, we first carried out an analysis of the most important initiatives for the definition and design of interactive systems, and the main infrastructures for providing information. Through this study the use of the W3C SCXML language is proposed for both the design of interactive systems and the processing of data provided by different context sources. Thus, this work has shown how the SCXML capabilities for combining information from different modalities can also be used to process and integrate contextual information from different heterogeneous sensor sources, and therefore to develope context-aware interaction systems. Similarly, we present the Sensor Web initiative, and its semantic extension Semantic Sensor Web, as an appropriate initiative to allow uniform access and delivery of information to the context-aware interactive systems. Subsequently we have analyzed the challenges of integrating both types of initiatives: SCXML and (Semantic) Sensor Web. As a result, we state a number of functionalities that are necessary to implement in order to perform this integration. By using technologies that provide exibility to the implementation process and are based on current recommendations and standards, we implemented a series of experimental developments that integrate the identified functionalities. Finally, in order to validate our approach, we conducted different experiments with a testing environment simulating a driving scenario. In this framework an interactive system can access a semantic extension of a Telco plataform, based on the standards of the Sensor Web, to acquire contextual information and publish observations that the user performed to the system. The results showed the feasibility of using the SCXML language for designing context-aware interactive systems that require access to advanced sensor platforms for consuming and publishing information while interacting with the user. In the same way, it was shown how the use of semantic technologies in the processes of querying and publication sensor data can assist in reusing and sharing the information published by any application in Sensor Web infrastructures, and thus contribute to realize the future scenario of \Internet of Things".