820 resultados para Android Google Play Services Activity Recognition


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In children, levels of play, physical activity, and fitness are key indicators of health and disease and closely tied to optimal growth and development. Cardiopulmonary exercise testing (CPET) provides clinicians with biomarkers of disease and effectiveness of therapy, and researchers with novel insights into fundamental biological mechanisms reflecting an integrated physiological response that is hidden when the child is at rest. Yet the growth of clinical trials utilizing CPET in pediatrics remains stunted despite the current emphasis on preventative medicine and the growing recognition that therapies used in children should be clinically tested in children. There exists a translational gap between basic discovery and clinical application in this essential component of child health. To address this gap, the NIH provided funding through the Clinical and Translational Science Award (CTSA) program to convene a panel of experts. This report summarizes our major findings and outlines next steps necessary to enhance child health exercise medicine translational research. We present specific plans to bolster data interoperability, improve child health CPET reference values, stimulate formal training in exercise medicine for child health care professionals, and outline innovative approaches through which exercise medicine can become more accessible and advance therapeutics across the child health spectrum.

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El propósito de la presente tesis es identificar y diseñar un modelo de negocio que permita aprovechar las oportunidades del mercado de descarga de aplicaciones y juegos en dispositivos móviles entre universitarios de clase media-alta de Quito en sistemas iOS y Android. Entre los propósitos específicos se encuentran el esquematizar la evolución de los dispositivos móviles y el mercado de aplicaciones y juegos. Analizar el mercado de los dispositivos móviles y las descargas de juegos y aplicaciones en el mundo actual. También analizar el mercado de juegos y aplicaciones móviles entre los universitarios de clase media – alta de Quito (factores de crecimiento, aplicaciones y juegos más descargados, dispositivos más populares, uso de Appstore y Google Play). Asimismo detectar las aplicaciones que los jóvenes necesitan y quisieran tener en su smartphone pero no encuentran. Finalmente diseñar y proponer un modelo de negocio que permita aprovechar la información recopilada y las oportunidades de negocio en este mercado. La hipótesis utilizada fue que ciertas aplicaciones móviles y juegos para dispositivos móviles son los más utilizados y descargados entre los estudiantes universitarios de clase media-alta de Quito por lo que las herramientas identificadas en el estudio son sustentables para formar parte de un modelo de negocio. Se realizó un estudio descriptivo para identificar los principales factores del auge de este mercado. Para la investigación se utilizó el método empírico a través de una encuesta a 100 estudiantes universitarios. Se encontró que los universitarios no pagan por aplicaciones y prefieren aplicaciones gratuitas. La gran mayoría utiliza el sistema operativo Android, WhatsApp y Facebook, además de usar Dropbox para tener archivos en la nube. Angry Birds es el juego más popular por lo cual se validó la hipótesis. Esto permitió diseñar el modelo de una aplicación gratuita que permite que los universitarios puedan recibir periódicamente en su celular recomendaciones sobre las mejores aplicaciones (de las miles disponibles cada mes) personalizadas individualmente, además de permitirles borrar y tener control sobre las aplicaciones que más espacio consumen y no utilizan periódicamente.

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Os utilizadores de transportes públicos enfrentam dificuldades no seu dia-a-dia quando usam o autocarro para deslocar-se. Essas dificuldades passam por atrasos pessoais, por enganos na consulta dos horários das carreiras, entre outros, resultando na perda do autocarro. Este trabalho consistiu no desenvolvimento de uma aplicação móvel para a plataforma Android, tendo como principal objectivo fornecer ao utilizador uma ferramenta leve, rápida e útil para utilizar quando se encontra em movimento. O público-alvo desta aplicação são os utilizadores de transportes públicos da empresa Horários do Funchal, que necessitam de realizar deslocações frequentes, e não têm acesso constante à internet, dentro e fora de casa. Realizou-se uma pesquisa, através de um inquérito divulgado nas redes sociais, aos utilizadores de transportes públicos e, posteriormente, utilizou-se essa pesquisa no processo de brainstorming para construir as ideias para as funcionalidades da aplicação. Também se pesquisaram por outras aplicações com objectivos semelhantes e compararam-se essas com a aplicação desta dissertação. Posteriormente, implementou-se o primeiro protótipo e realizaram-se mais testes com novos utilizadores, que usaram a aplicação no seu dia-a-dia. Após se terem corregido os erros encontrados pelos utilizadores na aplicação, lançou-se uma versão beta online no mercado da Google Play. Os resultados obtidos com esta aplicação comprovam não só que existe a necessidade de uma aplicação destas no mercado, mas também permitiram ainda recolher dados sobre melhoramentos que podem ser feitos na mesma. Ao desenvolver esta aplicação pôde-se compreender as necessidades e as limitações que são impostas pelo cliente, como também colocar em prática os conhecimentos adquiridos ao longo do curso.

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Pós-graduação em Televisão Digital: Informação e Conhecimento - FAAC

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This occasional paper examines the experiences of three leading global centres of the ICT industry – India, Silicon Valley, and Estonia – to reflect on how the lessons of these models can be applied to the context of countries in the Caribbean region.Several sectors of the technology industry are considered in relation to the suitability for their establishment in the Caribbean. Animation is an area that is showing encouraging signs of development in several countries, and which offers some promise to provide a significant source of employment in the region. However, the global market for animation production is likely to become increasingly competitive, as improved technology has reduced barriers to entry into the industry not only in the Caribbean, but around the world. The region’s animation industry will need to move swiftly up the value chain if it is to avoid the downsides of being caught in an increasingly commoditized market. Mobile applications development has also been widely a heralded industry for the Caribbean. However, the market for consumer-oriented smartphone applications has matured very quickly, and is now a very difficult sector in which to compete. Caribbean mobile developers would be better served to focus on creating applications to suit the needs of regional industries and governments, rather than attempting to gain notice in over-saturated consumer marketplaces such as the iTunes App Store and Google Play. Another sector considered for the Caribbean is “big data” analysis. This area holds significant potential for growth in coming years, but the Caribbean, which is generally considered to be a datapoor region, currently lacks a sufficient base of local customers to form a competitive foundation for such an industry. While a Caribbean big data industry could plausibly be oriented toward outsourcing, that orientation would limit positive externalities from the sector, and benefits from its establishment would largely accrue only to a relatively small number of direct participants in the industry. Instead, development in the big data sector should be twinned with the development of products to build a regional customer base for the industry. The region has pressing needs in areas such as disaster risk reduction, water resource management, and support for agricultural production. Development of big data solutions – and other technology products – to address areas such as these could help to establish niche industries that both support the needs of local populations, and provide viable opportunities for the export of higher-value products and services to regions of the world with similar needs.

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Pós-graduação em Engenharia Mecânica - FEG

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Lo scopo della tesi e quello di giungere alla realizzazione di un prototipo, che si basi su tecnologie specifiche quali GPS, Android e Bluetooth, per l'infrastruttura di un sistema che può essere visto come l'unione di tre macro parti distinte, centrale di controllo, dispositivo mobile e pulsossimetro. Concentrandosi in particolare sugli ultimi due componenti citati e realizzando un sistema di comunicazione che si basa su un Web Service ispirato al modello REST, si giungerà, attraverso un attento processo logico dettato dai canoni dell'ingegneria del software, al prototipo finale. Il prototipo che sarà realizzato rappresenterà oltre che un primo sistema funzionante e operativo, un punto di partenza per estensioni future, con lo scopo di perfezionare le funzionalità già esistenti o di fornirne di aggiuntive.

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The ActiGraph accelerometer is commonly used to measure physical activity in children. Count cut-off points are needed when using accelerometer data to determine the time a person spent in moderate or vigorous physical activity. For the GT3X accelerometer no cut-off points for young children have been published yet. The aim of the current study was thus to develop and validate count cut-off points for young children. Thirty-two children aged 5 to 9 years performed four locomotor and four play activities. Activity classification into the light-, moderate- or vigorous-intensity category was based on energy expenditure measurements with indirect calorimetry. Vertical axis as well as vector magnitude cut-off points were determined through receiver operating characteristic curve analyses with the data of two thirds of the study group and validated with the data of the remaining third. The vertical axis cut-off points were 133 counts per 5 sec for moderate to vigorous physical activity (MVPA), 193 counts for vigorous activity (VPA) corresponding to a metabolic threshold of 5 MET and 233 for VPA corresponding to 6 MET. The vector magnitude cut-off points were 246 counts per 5 sec for MVPA, 316 counts for VPA - 5 MET and 381 counts for VPA - 6 MET. When validated, the current cut-off points generally showed high recognition rates for each category, high sensitivity and specificity values and moderate agreement in terms of the Kappa statistic. These results were similar for vertical axis and vector magnitude cut-off points. The current cut-off points adequately reflect MVPA and VPA in young children. Cut-off points based on vector magnitude counts did not appear to reflect the intensity categories better than cut-off points based on vertical axis counts alone.

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Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.

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Este Proyecto Fin de Carrera (PFC) tiene como objetivo el análisis, diseño e implementación de un videojuego móvil multijugador, con un enfoque educativo, para la sensibilización sobre el Índice de Desarrollo Humano (IDH). El sistema resultante se ha desarrollado para la Plataforma Android, utilizando el Framework AndEngine, que utiliza aceleración hardware de la GPU para garantizar un buen rendimiento en terminales de gama baja, de modo que pueda utilizarse en un amplio número de terminales móviles disponibles en el mercado. La aplicación se presenta como un juego de cartas con los diferentes países y sus datos humanitarios, los jugadores deben conocer el peso de los índices de desarrollo (esperanza de vida, renta, educación) de los países en comparación con los países de los otros jugadores. El sistema de juego premia a los jugadores con mayores conocimientos sobre los datos humanos de los diferentes países del mundo, de ese modo los mejores jugadores serán los que tengan más conocimientos de estos datos. El juego permite jugar partidas en solitario utilizando jugadores manejados por la CPU, o multijugador mediante WIFI o 3G. La actualización de la información y de los datos de las partidas se realiza a través de la comunicación con un servidor web ya implementado de forma complementaria a la realización de este proyecto. El sistema ha sido integrado y validado satisfactoriamente con diferentes terminales móviles y usuarios de diferente perfil de edad y uso. El videojuego se puede descargar de la página web creada en un proyecto complementario a éste (pendiente de publicación web), y ya se encuentra también disponible en Google Play. https://play.google.com/store/apps/details?id=xnetcom.pro.cartas&hl=es_419 ABSTRACT. This Project End of Career (PFC) takes as an aim the analysis, design and implementation of a multiplayer mobile videogame, with an educational approach, for the awareness on the Human Development Index (HDI). The resultant system has been developed for the Platform Android, using the AndEngine Framework, which uses hardware acceleration of the GPU to ensure a good performance on low-end terminals, so that it can be used in a wide range of mobile handsets available in the market. The application is presented as a card game with the different countries and his humanitarian information, the players must know the weight of the indexes of development (life expectancy, revenue, education) of the countries in comparison with the countries of other players. The game system rewards players with more knowledge on human information of different countries, thus the best players will be those with more knowledge of these information. The game allows to play items in solitarily using players handled by the CPU, or multiplayer by means of WIFI or 3G. The update of the information and data of the online games is done through communication with a web server implemented as a complement to the realization of this project. The system has been built and successfully validated with different mobile terminals and users of different age and usage profile. The game can be downloaded from the website created in a complementary project to this (web publication pending), and is now also available on Google Play https://play.google.com/store/apps/details?id=xnetcom.pro.cartas&hl=es_419

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En el marco del proyecto europeo FI-WARE, en el CoNWet Lab (laboratorio de la ETSI Informáticos de la UPM) se ha implementado la plataforma Web Wstore que es una implementación de referencia del Store Generic Enabler perteneciente a dicho proyecto. El objetivo de FI-WARE es crear la plataforma núcleo del Internet del Futuro (IoF) con la intención de incrementar la competitividad global europea en el mundo de las TI. El proyecto introduce una infraestructura innovadora para la creación y distribución de servicios digitales en internet. WStore ofrece a los proveedores de servicios la plataforma donde publicar sus ofertas y desde la cual los clientes podrán acceder ellas. Estos proveedores ofrecen servicios Web, aplicaciones, widgets y data sets del mismo modo que Google ofrece aplicaciones en la tienda online Google Play o Apple en el App Store. WStore está implementada actualmente como una plataforma Web, por lo que una organización que desee ofrecer el servicio de la store necesita instalar el software en un servidor propio y disponer de un dominio para ofrecer sus productos. El objetivo de este trabajo es migrar WStore a un entorno de computación en la nube de manera que con una única instancia se ofrezca el servicio a las organizaciones que deseen disponer de su propia plataforma, de la cual tendrán total control como si se encontrase en su propia infraestructura. Para esto se implementa una versión de WStore que será desplegada en una infraestructura cloud y ofrecida como Software as a Service. La implementación incluye una serie de módulos de código que se podrán añadir opcionalmente en el proceso de instalación si se desea que la instancia instalada sea Multitenant. Además, en este trabajo se estudian y prueban las herramientas que ofrece MongoDB para desplegar la plataforma Wstore Multitenant en una infraestructura cloud. Estas herramientas son replica sets y sharding que permiten desplegar una base de datos escalable y de alta disponibilidad. ---ABSTRACT---In the context of the European project FI-WARE, the CoNWeT Lab (IT Lab from ETSIINF UPM university) has been implemented the web platform WStore. WStore is a reference implementation of the Generic Enabler Store from FI-WARE project. The FI-WARE goal is to create the core platform of the Future Internet (IoF) with the intention of enhancing Europe's global competitiveness in IT technologies. FI-WARE introduces an innovative infrastructure for the creation and distribution of digital services over the Internet. WStore offers to service providers a platform to publicate offerings and where customers can access them. The providers offer web services, applications, widgets and data sets in the same way that Google offers online applications on Google Play or Apple on App Store plataforms. WStore is currently implemented as a web platform, so if an organization wants to offer the store service, it need to install the software on it’s own serves and have a domain to offer their products. The objective of this paper is to migrate WStore to a cloud computing environment where a single instance of the WStore is offered as a web service to organizations who want their own store. Customers (tenants) of the WStore web service will have total control over the software and WStore administration. The implementation includes several code modules that can be optionally added in the installation process to build a Multitenant instance. In addition, this paper review the tools that MongoDB provide for scalability and high availability (replica sets and sharding) with the purpose of deploying multi-tenant WStore on a cloud infrastructure.

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O contexto tecnológico em que vivemos é uma realidade. E a tendência é para ser assim também no futuro. Cada vez mais. É o caso das representações de locais e entidades em mapas digitais na web. Na visão de Crocker (2014), esta tendência é ainda mais acentuada, no âmbito das aplicações móveis, como mostram as mais diversas location-based applications. No setor do desporto e da respetiva gestão nem sempre foi fácil desenvolver aplicações, recorrendo a este tipo de representações espaciais. A tecnologia não era fácil e o know-how não era adequadamente qualificado. Mas, as empresas fornecedoras de tecnologia geoespacial simplificaram o desenvolvimento de aplicações web nesta área, através da utilização de application programming interfaces (API). Como refere Svennerberg (2010), estas API’s servem de interface entre um serviço proporcionado por uma empresa, caso da Google Maps (2013) e uma aplicação web ou móvel que utiliza esses serviços. Foi com este objetivo que desenvolvemos uma aplicação web, utilizando as metodologias próprias neste domínio, como a framework de Zachman (2009), tal como foi originalmente adaptada por Whitten e Bentley (2005), onde um dos módulos é precisamente a representação de espaços desportivos, recorrendo à utilização dos serviços da Google Maps. Para além disso, toda a aplicação é suportada numa abordagem Model-View-Control (MVC). Para conseguir representar as instalações desportivas num mapa, criámos uma base de dados MySQL, com dados de longitude e latitude, de cada instalação desportiva. Através de JavaScript criou-se o mapa propriamente dito, indicando o tipo (mapa de estradas, satélite ou street view) e as respetivas opções (nível de zoom, alinhamento, controlo de interface e posicionamente, entre muitas outras opções). O passo seguinte consistiu em passar os dados para o frontend da aplicação web. Para isso, recorreu-se à integração do PHP com as livrarias externas de código JavaSrcipt, criadas especificamente para o efeito (caso da MarkerManager). A implementação destas funcionalidades permite georeferenciar todos os tipos e géneros de espaços desportivos de um concelho, região ou País. Obteve-se ainda know-how, background e massa crítica, para o desenvolvimento de novas funcionalidades. A sua utilização em dispositivos móveis é outra das possibilidades atualmente já em desenvolvimento.

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This paper presents the novel theory for performing multi-agent activity recognition without requiring large training corpora. The reduced need for data means that robust probabilistic recognition can be performed within domains where annotated datasets are traditionally unavailable. Complex human activities are composed from sequences of underlying primitive activities. We do not assume that the exact temporal ordering of primitives is necessary, so can represent complex activity using an unordered bag. Our three-tier architecture comprises low-level video tracking, event analysis and high-level inference. High-level inference is performed using a new, cascading extension of the Rao–Blackwellised Particle Filter. Simulated annealing is used to identify pairs of agents involved in multi-agent activity. We validate our framework using the benchmarked PETS 2006 video surveillance dataset and our own sequences, and achieve a mean recognition F-Score of 0.82. Our approach achieves a mean improvement of 17% over a Hidden Markov Model baseline.

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This paper presents a semi-parametric Algorithm for parsing football video structures. The approach works on a two interleaved based process that closely collaborate towards a common goal. The core part of the proposed method focus perform a fast automatic football video annotation by looking at the enhance entropy variance within a series of shot frames. The entropy is extracted on the Hue parameter from the HSV color system, not as a global feature but in spatial domain to identify regions within a shot that will characterize a certain activity within the shot period. The second part of the algorithm works towards the identification of dominant color regions that could represent players and playfield for further activity recognition. Experimental Results shows that the proposed football video segmentation algorithm performs with high accuracy.

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This paper proposes a semi-supervised intelligent visual surveillance system to exploit the information from multi-camera networks for the monitoring of people and vehicles. Modules are proposed to perform critical surveillance tasks including: the management and calibration of cameras within a multi-camera network; tracking of objects across multiple views; recognition of people utilising biometrics and in particular soft-biometrics; the monitoring of crowds; and activity recognition. Recent advances in these computer vision modules and capability gaps in surveillance technology are also highlighted.