732 resultados para Mobile Phones, Experiential Consumption, Emotions Theory, ESM
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In recent years, mobile learning has emerged as an educational approach to decrease the limitation of learning location and adapt the teaching-learning process to all type of students. However, the large number and variety of Web-enabled devices poses challenges for Web content creators who want to automatic get the delivery context and adapt the content to mobile devices. In this paper we study several approaches to adapt the learning content to mobile phones. We present an architecture for deliver uniform m-Learning content to students in a higher School. The system development is organized in two phases: firstly enabling the educational content to mobile devices and then adapting it to all the heterogeneous mobile platforms. With this approach, Web authors will not need to create specialized pages for each kind of device, since the content is automatically transformed to adapt to any mobile device capabilities from WAP to XHTML MP-compliant devices.
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In recent years, mobile learning has emerged as an educational approach to decrease the limitation of learning location and adapt the teaching-learning process to all type of students. However, the large number and variety of Web-enabled devices poses challenges for Web content creators who want to automatic get the delivery context and adapt the content to mobile devices. This paper studies several approaches to adapt the learning content to mobile phones. It presents an architecture for deliver uniform m-Learning content to students in a higher School. The system development is organized in two phases: firstly enabling the educational content to mobile devices and then adapting it to all the heterogeneous mobile platforms. With this approach, Web authors will not need to create specialized pages for each kind of device, since the content is automatically transformed to adapt to any mobile device capabilities from WAP to XHTML MP-compliant devices.
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Nykypäivän maailma tukeutuu verkkoihin. Tietokoneverkot ja langattomat puhelimet ovat jo varsin tavallisia suurelle joukolle ihmisiä. Uusi verkkotyyppi on ilmestynyt edelleen helpottamaan ihmisten verkottunutta elämää. Ad hoc –verkot mahdollistavat joustavan verkonmuodostuksen langattomien päätelaitteiden välille ilman olemassa olevaa infrastruktuuria. Diplomityö esittelee uuden simulaatiotyökalun langattomien ad hoc –verkkojen simulointiin protokollatasolla. Se esittelee myös kyseisten verkkojen taustalla olevat periaatteet ja teoriat. Lähemmin tutkitaan OSI-mallin linkkikerroksen kaistanjakoprotokollia ad hoc –verkoissa sekä vastaavan toteutusta simulaattorissa. Lisäksi esitellään joukko simulaatioajoja esimerkiksi simulaattorin toiminnasta ja mahdollisista käyttökohteista.
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Ce mémoire examine l'adoption des téléphones mobiles et l'utilisation des messages texte (SMS) par les adolescents chinois, selon la théorie des usages et gratifications et de la recherche sur la communication par ordinateur. Certains champs particuliers de l'utilisation des messages textes par les adolescents chinois, comme le contrôle parental, la circulation des chaînes de messages, la popularité des messages de salutations et l'utilisation répandue des émoticônes ont été étudiés. La fonction sociale des SMS, plus particulièrement des pratiques sociales et des relations émotionnelles des adolescents chinois, a également été explorée. Cette étude est basée sur un sondage réalisé sur le terrain auprès de 100 adolescents chinois. Elle révèle que chez les adolescents chinois, les deux principales raisons pour l'adoption du téléphone mobile sont l'influence parentale et le besoin de communication sociale. Quant à l'utilisation des messages texte, elle répond à sept usages et gratifications : la flexibilité, le coût modique, l’intimité, éviter l'embarras, le divertissement, l'engouement et l'évasion. Il a également été observé que les messages texte jouent un rôle positif dans la construction et l'entretien des relations sociales des adolescents chinois.
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Pocket Data Mining (PDM) is our new term describing collaborative mining of streaming data in mobile and distributed computing environments. With sheer amounts of data streams are now available for subscription on our smart mobile phones, the potential of using this data for decision making using data stream mining techniques has now been achievable owing to the increasing power of these handheld devices. Wireless communication among these devices using Bluetooth and WiFi technologies has opened the door wide for collaborative mining among the mobile devices within the same range that are running data mining techniques targeting the same application. This paper proposes a new architecture that we have prototyped for realizing the significant applications in this area. We have proposed using mobile software agents in this application for several reasons. Most importantly the autonomic intelligent behaviour of the agent technology has been the driving force for using it in this application. Other efficiency reasons are discussed in details in this paper. Experimental results showing the feasibility of the proposed architecture are presented and discussed.
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As telecomunicações no mundo têm avançado a passos largos na oferta de novas tecnologias e padrões que viabilizam e flexibilizam a transmissão / recepção de informações entre pessoas e a Internet. Em especial, no que tange à ubiqüidade, o uso de dispositivos de comunicações móveis sem fio, como telefones celulares e PDAs (Personnal Digital Assistant), tem permitido às empresas alcançarem seus clientes a qualquer hora e em qualquer lugar. Muitos padrões de comunicação wireless têm surgido, inicialmente na indústria de telefonia móvel celular e, em seguida, na indústria de computadores e PDAs, habilitando a comunicação wireless de dados em banda larga e o comércio eletrônico móvel (m-commerce). Em especial, o padrão Wi-Fi tem sido difundido mundialmente através da expansão de redes públicas sem fio (PWLANs). Assim, os fabricantes de equipamentos de telecomunicações, as empresas operadoras de serviços de telefonia fixa e móvel e até provedores de acesso à Internet têm manifestado grande interesse nessa área por perceberem novas oportunidades de aumento de receita através da tecnologia Wi-Fi. Todos estes aspectos da recente história do Wi-Fi têm gerado questionamentos quanto a seu futuro sucesso e real geração de vantagem competitiva sustentável, não obstante o volume de negócios relativos a esta tecnologia estar em franco crescimento. Este trabalho propõe-se a analisar o mercado de serviços PWLAN Wi-Fi brasileiro, identificando os principais atores e os modelos de negócio praticados por eles, comparando esses modelos aos modelos identificados por Shubar e Lechner. O estudo propõe-se, também, a avaliar tais empresas e seus respectivos modelos de negócio segundo o framework VRIO desenvolvido por Barney com base na visão estratégica baseada em recursos (RBV- Resource Based View).
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Ao entender os processos organizacionais e humanos que transformam a informação em percepção, conhecimento e ação, uma organização é capaz de perceber como investir mais adequadamente na captação, manutenção e desenvolvimento de suas fontes de informação. Esse cenário pode ser ainda mais crítico num setor de mão de obra intensiva como o varejo, onde o elo primário da relação com seus consumidores é a força de vendas. O objetivo principal deste trabalho é identificar como e por quê os profissionais de vendas que atuam no varejo usam a informação em sua rotina profissional, atentando para as limitações que cercam esses profissionais no desempenho de suas atividades. Para tanto, foi desenvolvido um estudo de caso em organização varejista brasileira de grande porte, com foco no lançamento do novo conceito de loja voltado para a comercialização de produtos de tecnologia móvel, quais sejam celulares, smartphones, tablets e acessórios, tendo a teoria do uso da informação de Choo (2003) servido de alicerce principal para o estudo. O uso da informação pelos profissionais de vendas foi analisado em três arenas estratégicas: sensemaking, construção de conhecimento e tomada de decisão. Nossas descobertas nos levam a acreditar que o profissional de vendas usa a informação nas referidas arenas, no entanto, tal uso parece apresentar gradações, com maior ou menor intensidade, de acordo com a arena em questão.
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In this paper, a trajectory tracking control problem for a nonholonomic mobile robot by the integration of a kinematic neural controller (KNC) and a torque neural controller (TNC) is proposed, where both the kinematic and dynamic models contains disturbances. The KNC is a variable structure controller (VSC) based on the sliding mode control theory (SMC), and applied to compensate the kinematic disturbances. The TNC is a inertia-based controller constituted of a dynamic neural controller (DNC) and a robust neural compensator (RNC), and applied to compensate the mobile robot dynamics, and bounded unknown disturbances. Stability analysis with basis on Lyapunov method and simulations results are provided to show the effectiveness of the proposed approach. © 2012 Springer-Verlag.
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Pós-graduação em Artes - IA
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Pós-graduação em Televisão Digital: Informação e Conhecimento - FAAC
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A growing body of literature addresses possible health effects of mobile phone use in children and adolescents by relying on the study participants' retrospective reconstruction of mobile phone use. In this study, we used data from the international case-control study CEFALO to compare self-reported with objectively operator-recorded mobile phone use. The aim of the study was to assess predictors of level of mobile phone use as well as factors that are associated with overestimating own mobile phone use. For cumulative number and duration of calls as well as for time since first subscription we calculated the ratio of self-reported to operator-recorded mobile phone use. We used multiple linear regression models to assess possible predictors of the average number and duration of calls per day and logistic regression models to assess possible predictors of overestimation. The cumulative number and duration of calls as well as the time since first subscription of mobile phones were overestimated on average by the study participants. Likelihood to overestimate number and duration of calls was not significantly different for controls compared to cases (OR=1.1, 95%-CI: 0.5 to 2.5 and OR=1.9, 95%-CI: 0.85 to 4.3, respectively). However, likelihood to overestimate was associated with other health related factors such as age and sex. As a consequence, such factors act as confounders in studies relying solely on self-reported mobile phone use and have to be considered in the analysis.
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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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During the last decade wireless mobile communications have progressively become part of the people’s daily lives, leading users to expect to be “alwaysbest-connected” to the Internet, regardless of their location or time of day. This is indeed motivated by the fact that wireless access networks are increasingly ubiquitous, through different types of service providers, together with an outburst of thoroughly portable devices, namely laptops, tablets, mobile phones, among others. The “anytime and anywhere” connectivity criterion raises new challenges regarding the devices’ battery lifetime management, as energy becomes the most noteworthy restriction of the end-users’ satisfaction. This wireless access context has also stimulated the development of novel multimedia applications with high network demands, although lacking in energy-aware design. Therefore, the relationship between energy consumption and the quality of the multimedia applications perceived by end-users should be carefully investigated. This dissertation addresses energy-efficient multimedia communications in the IEEE 802.11 standard, which is the most widely used wireless access technology. It advances the literature by proposing a unique empirical assessment methodology and new power-saving algorithms, always bearing in mind the end-users’ feedback and evaluating quality perception. The new EViTEQ framework proposed in this thesis, for measuring video transmission quality and energy consumption simultaneously, in an integrated way, reveals the importance of having an empirical and high-accuracy methodology to assess the trade-off between quality and energy consumption, raised by the new end-users’ requirements. Extensive evaluations conducted with the EViTEQ framework revealed its flexibility and capability to accurately report both video transmission quality and energy consumption, as well as to be employed in rigorous investigations of network interface energy consumption patterns, regardless of the wireless access technology. Following the need to enhance the trade-off between energy consumption and application quality, this thesis proposes the Optimized Power save Algorithm for continuous Media Applications (OPAMA). By using the end-users’ feedback to establish a proper trade-off between energy consumption and application performance, OPAMA aims at enhancing the energy efficiency of end-users’ devices accessing the network through IEEE 802.11. OPAMA performance has been thoroughly analyzed within different scenarios and application types, including a simulation study and a real deployment in an Android testbed. When compared with the most popular standard power-saving mechanisms defined in the IEEE 802.11 standard, the obtained results revealed OPAMA’s capability to enhance energy efficiency, while keeping end-users’ Quality of Experience within the defined bounds. Furthermore, OPAMA was optimized to enable superior energy savings in multiple station environments, resulting in a new proposal called Enhanced Power Saving Mechanism for Multiple station Environments (OPAMA-EPS4ME). The results of this thesis highlight the relevance of having a highly accurate methodology to assess energy consumption and application quality when aiming to optimize the trade-off between energy and quality. Additionally, the obtained results based both on simulation and testbed evaluations, show clear benefits from employing userdriven power-saving techniques, such as OPAMA, instead of IEEE 802.11 standard power-saving approaches.
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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.