872 resultados para 3G, Chinese regional cities, mobile phones


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Whether the use of mobile phones is a risk factor for brain tumors in adolescents is currently being studied. Case--control studies investigating this possible relationship are prone to recall error and selection bias. We assessed the potential impact of random and systematic recall error and selection bias on odds ratios (ORs) by performing simulations based on real data from an ongoing case--control study of mobile phones and brain tumor risk in children and adolescents (CEFALO study). Simulations were conducted for two mobile phone exposure categories: regular and heavy use. Our choice of levels of recall error was guided by a validation study that compared objective network operator data with the self-reported amount of mobile phone use in CEFALO. In our validation study, cases overestimated their number of calls by 9% on average and controls by 34%. Cases also overestimated their duration of calls by 52% on average and controls by 163%. The participation rates in CEFALO were 83% for cases and 71% for controls. In a variety of scenarios, the combined impact of recall error and selection bias on the estimated ORs was complex. These simulations are useful for the interpretation of previous case-control studies on brain tumor and mobile phone use in adults as well as for the interpretation of future studies on adolescents.

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In recent years there has been a personal and organizational trend toward mobility and the use of mobile technologies such as laptops, mobile phones and tablets. With this proliferation of devices, the desire to combine as many functions as possible into one device has also arisen. This concept is commonly called convergence. Generally, device convergence has been segmented between devices for work and devices for home use. Recently, however, the concept of Bring Your Own Device (BYOD) has emerged as organizations attempt to bridge the work/home divide in hopes of increasing employee productivity and reducing corporate technology costs. This paper examines BYOD projects at IBM, Cisco, Citrix, and Intel and then integrates this analysis with current literature to develop and present a BYOD Implementation Success model.

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Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.

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In this study, we apply the inter-regional input–output model to explain the relationship between China’s inter-regional spillover of CO2 emissions and domestic supply chains for 2002 and 2007. Based on this model, we propose alternative indicators such as the trade in CO2 emissions, CO2 emissions in trade, regional trade balances, and comparative advantage of CO2 emissions. The empirical results not only reveal the nature and significance of inter-regional environmental spillover within China’s domestic regions but also demonstrate how CO2 emissions are created and distributed across regions via domestic production networks. The main finding shows that a region’s CO2 emissions depend on not only its intra-regional production technique, energy use efficiency but also its position and participation degree in domestic and global supply chains.

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Mobile phones are becoming increasingly popular and are already the first access technology to information and communication. However, people with disabilities have to face a lot of barriers when using this kind of technology. This paper presents an Accessible Contact Manager and a Real Time Text application, designed to be used by all users with disabilities. Both applications are focused to improve accessibility of mobile phones.

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The apparition of new mobile phones operating systems often leads to a flood of mobile applications rushing into the market without taking into account needs of the most vulnerable users groups: the people with disabilities. The need of accessible applications for mobile is very important especially when it comes to access basic mobile functions such as making calls through a contact manager. This paper presents the technical validation process and results of an Accessible Contact Manager for mobile phones as a part of the evaluation of accessible applications for mobile phones for people with disabilities.

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Due to the intensive use of mobile phones for diferent purposes, these devices usually contain condential information which must not be accessed by another person apart from the owner of the device. Furthermore, the new generation phones commonly incorporate an accelerometer which may be used to capture the acceleration signals produced as a result of owner s gait. Nowadays, gait identication in basis of acceleration signals is being considered as a new biometric technique which allows blocking the device when another person is carrying it. Although distance based approaches as Euclidean distance or dynamic time warping have been applied to solve this identication problem, they show di±culties when dealing with gaits at diferent speeds. For this reason, in this paper, a method to extract an average template from instances of the gait at diferent velocities is presented. This method has been tested with the gait signals of 34 subjects while walking at diferent motion speeds (slow, normal and fast) and it has shown to improve the performance of Euclidean distance and classical dynamic time warping.

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Durante la actividad diaria, la sociedad actual interactúa constantemente por medio de dispositivos electrónicos y servicios de telecomunicaciones, tales como el teléfono, correo electrónico, transacciones bancarias o redes sociales de Internet. Sin saberlo, masivamente dejamos rastros de nuestra actividad en las bases de datos de empresas proveedoras de servicios. Estas nuevas fuentes de datos tienen las dimensiones necesarias para que se puedan observar patrones de comportamiento humano a grandes escalas. Como resultado, ha surgido una reciente explosión sin precedentes de estudios de sistemas sociales, dirigidos por el análisis de datos y procesos computacionales. En esta tesis desarrollamos métodos computacionales y matemáticos para analizar sistemas sociales por medio del estudio combinado de datos derivados de la actividad humana y la teoría de redes complejas. Nuestro objetivo es caracterizar y entender los sistemas emergentes de interacciones sociales en los nuevos espacios tecnológicos, tales como la red social Twitter y la telefonía móvil. Analizamos los sistemas por medio de la construcción de redes complejas y series temporales, estudiando su estructura, funcionamiento y evolución en el tiempo. También, investigamos la naturaleza de los patrones observados por medio de los mecanismos que rigen las interacciones entre individuos, así como medimos el impacto de eventos críticos en el comportamiento del sistema. Para ello, hemos propuesto modelos que explican las estructuras globales y la dinámica emergente con que fluye la información en el sistema. Para los estudios de la red social Twitter, hemos basado nuestros análisis en conversaciones puntuales, tales como protestas políticas, grandes acontecimientos o procesos electorales. A partir de los mensajes de las conversaciones, identificamos a los usuarios que participan y construimos redes de interacciones entre los mismos. Específicamente, construimos una red para representar quién recibe los mensajes de quién y otra red para representar quién propaga los mensajes de quién. En general, hemos encontrado que estas estructuras tienen propiedades complejas, tales como crecimiento explosivo y distribuciones de grado libres de escala. En base a la topología de estas redes, hemos indentificado tres tipos de usuarios que determinan el flujo de información según su actividad e influencia. Para medir la influencia de los usuarios en las conversaciones, hemos introducido una nueva medida llamada eficiencia de usuario. La eficiencia se define como el número de retransmisiones obtenidas por mensaje enviado, y mide los efectos que tienen los esfuerzos individuales sobre la reacción colectiva. Hemos observado que la distribución de esta propiedad es ubicua en varias conversaciones de Twitter, sin importar sus dimensiones ni contextos. Con lo cual, sugerimos que existe universalidad en la relación entre esfuerzos individuales y reacciones colectivas en Twitter. Para explicar los factores que determinan la emergencia de la distribución de eficiencia, hemos desarrollado un modelo computacional que simula la propagación de mensajes en la red social de Twitter, basado en el mecanismo de cascadas independientes. Este modelo nos permite medir el efecto que tienen sobre la distribución de eficiencia, tanto la topología de la red social subyacente, como la forma en que los usuarios envían mensajes. Los resultados indican que la emergencia de un grupo selecto de usuarios altamente eficientes depende de la heterogeneidad de la red subyacente y no del comportamiento individual. Por otro lado, hemos desarrollado técnicas para inferir el grado de polarización política en redes sociales. Proponemos una metodología para estimar opiniones en redes sociales y medir el grado de polarización en las opiniones obtenidas. Hemos diseñado un modelo donde estudiamos el efecto que tiene la opinión de un pequeño grupo de usuarios influyentes, llamado élite, sobre las opiniones de la mayoría de usuarios. El modelo da como resultado una distribución de opiniones sobre la cual medimos el grado de polarización. Aplicamos nuestra metodología para medir la polarización en redes de difusión de mensajes, durante una conversación en Twitter de una sociedad políticamente polarizada. Los resultados obtenidos presentan una alta correspondencia con los datos offline. Con este estudio, hemos demostrado que la metodología propuesta es capaz de determinar diferentes grados de polarización dependiendo de la estructura de la red. Finalmente, hemos estudiado el comportamiento humano a partir de datos de telefonía móvil. Por una parte, hemos caracterizado el impacto que tienen desastres naturales, como innundaciones, sobre el comportamiento colectivo. Encontramos que los patrones de comunicación se alteran de forma abrupta en las áreas afectadas por la catástofre. Con lo cual, demostramos que se podría medir el impacto en la región casi en tiempo real y sin necesidad de desplegar esfuerzos en el terreno. Por otra parte, hemos estudiado los patrones de actividad y movilidad humana para caracterizar las interacciones entre regiones de un país en desarrollo. Encontramos que las redes de llamadas y trayectorias humanas tienen estructuras de comunidades asociadas a regiones y centros urbanos. En resumen, hemos mostrado que es posible entender procesos sociales complejos por medio del análisis de datos de actividad humana y la teoría de redes complejas. A lo largo de la tesis, hemos comprobado que fenómenos sociales como la influencia, polarización política o reacción a eventos críticos quedan reflejados en los patrones estructurales y dinámicos que presentan la redes construidas a partir de datos de conversaciones en redes sociales de Internet o telefonía móvil. ABSTRACT During daily routines, we are constantly interacting with electronic devices and telecommunication services. Unconsciously, we are massively leaving traces of our activity in the service providers’ databases. These new data sources have the dimensions required to enable the observation of human behavioral patterns at large scales. As a result, there has been an unprecedented explosion of data-driven social research. In this thesis, we develop computational and mathematical methods to analyze social systems by means of the combined study of human activity data and the theory of complex networks. Our goal is to characterize and understand the emergent systems from human interactions on the new technological spaces, such as the online social network Twitter and mobile phones. We analyze systems by means of the construction of complex networks and temporal series, studying their structure, functioning and temporal evolution. We also investigate on the nature of the observed patterns, by means of the mechanisms that rule the interactions among individuals, as well as on the impact of critical events on the system’s behavior. For this purpose, we have proposed models that explain the global structures and the emergent dynamics of information flow in the system. In the studies of the online social network Twitter, we have based our analysis on specific conversations, such as political protests, important announcements and electoral processes. From the messages related to the conversations, we identify the participant users and build networks of interactions with them. We specifically build one network to represent whoreceives- whose-messages and another to represent who-propagates-whose-messages. In general, we have found that these structures have complex properties, such as explosive growth and scale-free degree distributions. Based on the topological properties of these networks, we have identified three types of user behavior that determine the information flow dynamics due to their influence. In order to measure the users’ influence on the conversations, we have introduced a new measure called user efficiency. It is defined as the number of retransmissions obtained by message posted, and it measures the effects of the individual activity on the collective reacixtions. We have observed that the probability distribution of this property is ubiquitous across several Twitter conversation, regardlessly of their dimension or social context. Therefore, we suggest that there is a universal behavior in the relationship between individual efforts and collective reactions on Twitter. In order to explain the different factors that determine the user efficiency distribution, we have developed a computational model to simulate the diffusion of messages on Twitter, based on the mechanism of independent cascades. This model, allows us to measure the impact on the emergent efficiency distribution of the underlying network topology, as well as the way that users post messages. The results indicate that the emergence of an exclusive group of highly efficient users depends upon the heterogeneity of the underlying network instead of the individual behavior. Moreover, we have also developed techniques to infer the degree of polarization in social networks. We propose a methodology to estimate opinions in social networks and to measure the degree of polarization in the obtained opinions. We have designed a model to study the effects of the opinions of a small group of influential users, called elite, on the opinions of the majority of users. The model results in an opinions distribution to which we measure the degree of polarization. We apply our methodology to measure the polarization on graphs from the messages diffusion process, during a conversation on Twitter from a polarized society. The results are in very good agreement with offline and contextual data. With this study, we have shown that our methodology is capable of detecting several degrees of polarization depending on the structure of the networks. Finally, we have also inferred the human behavior from mobile phones’ data. On the one hand, we have characterized the impact of natural disasters, like flooding, on the collective behavior. We found that the communication patterns are abruptly altered in the areas affected by the catastrophe. Therefore, we demonstrate that we could measure the impact of the disaster on the region, almost in real-time and without needing to deploy further efforts. On the other hand, we have studied human activity and mobility patterns in order to characterize regional interactions on a developing country. We found that the calls and trajectories networks present community structure associated to regional and urban areas. In summary, we have shown that it is possible to understand complex social processes by means of analyzing human activity data and the theory of complex networks. Along the thesis, we have demonstrated that social phenomena, like influence, polarization and reaction to critical events, are reflected in the structural and dynamical patterns of the networks constructed from data regarding conversations on online social networks and mobile phones.

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A Internet está inserida no cotidiano do indivíduo, e torna-se cada vez mais acessível por meio de diferentes tipos de dispositivos. Com isto, diversos estudos foram realizados com o intuito de avaliar os reflexos do seu uso excessivo na vida pessoal, acadêmica e profissional. Esta dissertação buscou identificar se a perda de concentração e o isolamento social são alguns dos reflexos individuais que o uso pessoal e excessivo de aplicativos de comunicação instantânea podem resultar no ambiente de trabalho. Entre as variáveis selecionadas para avaliar os aspectos do uso excessivo de comunicadores instantâneos tem-se a distração digital, o controle reduzido de impulso, o conforto social e a solidão. Através de uma abordagem de investigação quantitativa, utilizaram-se escalas aplicadas a uma amostra de 283 pessoas. Os dados foram analisados por meio de técnicas estatísticas multivariadas como a Análise Fatorial Exploratória e para auferir a relação entre as variáveis, a Regressão Linear Múltipla. Os resultados deste estudo confirmam que o uso excessivo de comunicadores instantâneos está positivamente relacionado com a perda de concentração, e a variável distração digital exerce uma influência maior do que o controle reduzido de impulso. De acordo com os resultados, não se podem afirmar que a solidão e o conforto social exercem relações com aumento do isolamento social, devido à ausência do relacionamento entre os construtos.

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The first automatic mobile phone service was launched in Australia in 1981, with the first cellular mobile service following in 1987. In 2003 there were over 14.5 million mobile phone subscribers, and the technology had become central to everyday life and culture. Despite the significance of mobile phones, little has been written about their Australian histories. This paper offers some notes on the history of mobile telecommunications in Australia. As well as reviewing the development of the mobile phone in Australia, it looks at the cultural representation of this technology.

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Online multimedia data needs to be encrypted for access control. To be capable of working on mobile devices such as pocket PC and mobile phones, lightweight video encryption algorithms should be proposed. The two major problems in these algorithms are that they are either not fast enough or unable to work on highly compressed data stream. In this paper, we proposed a new lightweight encryption algorithm based on Huffman error diffusion. It is a selective algorithm working on compressed data. By carefully choosing the most significant parts (MSP), high performance is achieved with proper security. Experimental results has proved the algorithm to be fast. secure: and compression-compatible.

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Mobile phones are increasingly being used collaboratively by social networks of users in spite of the fact that they are primarily designed to support single users and one-to-one communication. It is not well understood how services such as group SMS, SMS-based discussion lists and mobile instant messaging (IM) will be used by mobile groups in natural settings. Studying specific instances of common styles of in situ, group interaction may provide a way to see behavior patterns and typical interaction problems. We conducted a study of a mobile, group communication probe used during a rendezvousing activity in an urban environment. Usability problems relating to group usage, phone interface design and context were identified. Several major issues included: multitasking during message composition and reading; speed of text entry; excessive demand on visual attention; and ambiguity of intended recipients. We suggest that existing mobile device designs are overly-focused on individual users to the detriment of usability for mobile groups of users. We provide recommendations for the design of future mobile, group interfaces, used in similar situations to those explored here

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Even before business has really come to grips with the intricacies of incorporating emarketing and e-commerce into their organisational strategies, they are now being encouraged to make significant investments in developing capabilities for mobile phone marketing. Fuelled once again by huge profit predictions reminiscent of the mid-1990s when speaking of e-commerce (Anckar and D’Incau 2002) marketers are tapping into this mobility. So, instead of having to drive consumers to web sites through the ‘sit and search’ context, marketers are now exploring ways to develop strategies to deliver relevant and timely information in a ‘roam and receive’ context directly to their potential customers anywhere, anytime, any place (Mort and Drennan 2002).

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Internet of Things (IoT) can be defined as a “network of networks” composed by billions of uniquely identified physical Smart Objects (SO), organized in an Internet-like structure. Smart Objects can be items equipped with sensors, consumer devices (e.g., smartphones, tablets, or wearable devices), and enterprise assets that are connected both to the Internet and to each others. The birth of the IoT, with its communications paradigms, can be considered as an enabling factor for the creation of the so-called Smart Cities. A Smart City uses Information and Communication Technologies (ICT) to enhance quality, performance and interactivity of urban services, ranging from traffic management and pollution monitoring to government services and energy management. This thesis is focused on multi-hop data dissemination within IoT and Smart Cities scenarios. The proposed multi-hop techniques, mostly based on probabilistic forwarding, have been used for different purposes: from the improvement of the performance of unicast protocols for Wireless Sensor Networks (WSNs) to the efficient data dissemination within Vehicular Ad-hoc NETworks (VANETs).

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O objetivo principal dessa pesquisa é analisar os processos de comunicação mercadológica que utilizam os celulares como plataforma de divulgação. É intenção da pesquisa conhecer as práticas de mobile marketing realizadas no Brasil e a forma como os conteúdos desenvolvidos para celulares são utilizados na divulgação empresarial. As características dos jovens consumidores conectados, com destaque para a desenvoltura com que transitam nas novas mídias, e as formas como as empresas se comunicam com esses consumidores também fazem parte dos temas abordados neste estudo. Entrevistas em profundidade com profissionais da área foram utilizadas como metodologia para essa pesquisa qualitativa, de cunho exploratório, e os levantamentos bibliográfico e documental serviram como base para a análise das entrevistas. A pesquisa observou que no universo da comunicação móvel é fundamental desenvolver campanhas que proporcionem experiência com as marcas e ofereçam conteúdos relevantes aos consumidores. Contudo, alguns entraves tecnológicos não permitem que, até o presente momento, essas ações sejam expandidas para todos os consumidores brasileiros que possuem um celular.