931 resultados para User interfaces (Computer systems)


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Electronic apppliances are increasingly a part of our everyday lives. In particular, mobile devices, with their reduced dimensions with power rivaling desktop computers, have substantially augmented our communication abilities offering instant availability, anywhere, to everyone. These devices have become essential for human communication but also include a more comprehensive tool set to support productivity and leisure applications. However, the many applications commonly available are not adapted to people with special needs. Rather, most popular devices are targeted at teenagers or young adults with excellent eyesight and coordination. What is worse, most of the commonly used assistive control interfaces are not available in a mobile environment where user's position, accommodation and capacities can vary even widely. To try and address people with special needs new approaches and techniques are sorely needed. This paper presents a control interface to allow tetraplegic users to interact with electronic devices. Our method uses myographic information (Electromyography or EMG) collected from residually controlled body areas. User evaluations validate electromyography as a daily wearable interface. In particular our results show that EMG can be used even in mobility contexts.

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Temporal data are a core element of a reservation. In this paper we formulate 10 requirements and 14 sub-requirements for handling temporal data in online hotel reservation systems (OHRS) from a usability viewpoint. We test the fulfillment of these requirements for city and resort hotels in Austria and Switzerland. Some of the requirements are widely met; however, many requirements are fulfilled only by a surprisingly small number of hotels. In particular, numerous systems offer options for selecting data which lead to error messages in the next step. A few screenshots illustrate flaws of the systems. We also draw conclusions on the state of applying software engineering principles in the development of Web pages.

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The intention of an authentication and authorization infrastructure (AAI) is to simplify and unify access to different web resources. With a single login, a user can access web applications at multiple organizations. The Shibboleth authentication and authorization infrastructure is a standards-based, open source software package for web single sign-on (SSO) across or within organizational boundaries. It allows service providers to make fine-grained authorization decisions for individual access of protected online resources. The Shibboleth system is a widely used AAI, but only supports protection of browser-based web resources. We have implemented a Shibboleth AAI extension to protect web services using Simple Object Access Protocol (SOAP). Besides user authentication for browser-based web resources, this extension also provides user and machine authentication for web service-based resources. Although implemented for a Shibboleth AAI, the architecture can be easily adapted to other AAIs.

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For smart cities applications, a key requirement is to disseminate data collected from both scalar and multimedia wireless sensor networks to thousands of end-users. Furthermore, the information must be delivered to non-specialist users in a simple, intuitive and transparent manner. In this context, we present Sensor4Cities, a user-friendly tool that enables data dissemination to large audiences, by using using social networks, or/and web pages. The user can request and receive monitored information by using social networks, e.g., Twitter and Facebook, due to their popularity, user-friendly interfaces and easy dissemination. Additionally, the user can collect or share information from smart cities services, by using web pages, which also include a mobile version for smartphones. Finally, the tool could be configured to periodically monitor the environmental conditions, specific behaviors or abnormal events, and notify users in an asynchronous manner. Sensor4Cities improves the data delivery for individuals or groups of users of smart cities applications and encourages the development of new user-friendly services.

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Since the emergence of the Internet and Social Media, privacy concerns and need for regulation in this area have been a frequent subject on the agenda of numerous stakeholders and policy-makers worldwide. Contributing to this debate, this paper builds on the responses of 553 Internet users to uncover users’ current privacy concerns and their attitudes towards legal assurances in this context. Our findings suggest that users have a complex attitude towards these issues. While they express strong concerns about privacy when asked directly, they often have difficulties formulating the exact nature of these concerns. In the Facebook context, Facebook itself is often mentioned as the primary source of threat, closely followed by marketing organizations. Users feel ill-protected by existing legal framework, especially when using Social Networking Sites. Reasons include common beliefs that the law is unable to address complexities of the Internet; local character of laws; possibilities to disregard the law, particularly since enforcement is difficult. Overall, positive changes in legal framework are desirable, with many respondents willing to pay more in taxes to ensure progress in this area.

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Limited in motivation and cognitive ability to process the increasing amount of information on their Newsfeed, users apply heuristic processing to form their attitudes. Rather than extensively analysing the content, they increasingly rely on heuristic cues – such as the amount of comments and likes as well as the level of relationship with the “poster” – to process the incoming information. In the paper we explore what impact these heuristic cues have on the affective and cognitive attitude of users towards the posts on their Newsfeed. We conduct a survey on based on a Facebook application that allows users to evaluate Newsfeed posts in real time. Applying two distinct panel-regression methods we report robust results that indicate that there is a certain relationship primacy effect when users are processing information: only if the level of relationship with the “poster” is low, the impact of comments and likes on the attitude is considered, whereby likes trigger positive, whereas comments – negative evaluations.

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Abstract. During the last decade mobile communications increasingly became part of people's daily routine. Such usage raises new challenges regarding devices' battery lifetime management when using most popular wireless access technologies, such as IEEE 802.11. This paper investigates the energy/delay trade-off of using an end-user driven power saving approach, when compared with the standard IEEE 802.11 power saving algorithms. The assessment was conducted in a real testbed using an Android mobile phone and high-precision energy measurement hardware. The results show clear energy benefits of employing user-driven power saving techniques, when compared with other standard approaches.

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Our research project develops an intranet search engine with concept- browsing functionality, where the user is able to navigate the conceptual level in an interactive, automatically generated knowledge map. This knowledge map visualizes tacit, implicit knowledge, extracted from the intranet, as a network of semantic concepts. Inductive and deductive methods are combined; a text ana- lytics engine extracts knowledge structures from data inductively, and the en- terprise ontology provides a backbone structure to the process deductively. In addition to performing conventional keyword search, the user can browse the semantic network of concepts and associations to find documents and data rec- ords. Also, the user can expand and edit the knowledge network directly. As a vision, we propose a knowledge-management system that provides concept- browsing, based on a knowledge warehouse layer on top of a heterogeneous knowledge base with various systems interfaces. Such a concept browser will empower knowledge workers to interact with knowledge structures.

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Long Term Evolution (LTE) represents the fourth generation (4G) technology which is capable of providing high data rates as well as support of high speed mobility. The EU FP7 Mobile Cloud Networking (MCN) project integrates the use of cloud computing concepts in LTE mobile networks in order to increase LTE's performance. In this way a shared distributed virtualized LTE mobile network is built that can optimize the utilization of virtualized computing, storage and network resources and minimize communication delays. Two important features that can be used in such a virtualized system to improve its performance are the user mobility and bandwidth prediction. This paper introduces the architecture and challenges that are associated with user mobility and bandwidth prediction approaches in virtualized LTE systems.

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Software developers often ask questions about software systems and software ecosystems that entail exploration and navigation, such as who uses this component?, and where is this feature implemented?. Software visualisation can be a great aid to understanding and exploring the answers to such questions, but visualisations require expertise to implement effectively, and they do not always scale well to large systems. We propose to automatically generate software visualisations based on software models derived from open source software corpora and from an analysis of the properties of typical developers queries and commonly used visualisations. The key challenges we see are (1) understanding how to match queries to suitable visualisations, and (2) scaling visualisations effectively to very large software systems and corpora. In the paper we motivate the idea of automatic software visualisation, we enumerate the challenges and our proposals to address them, and we describe some very initial results in our attempts to develop scalable visualisations of open source software corpora.

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Recently telecommunication industry benefits from infrastructure sharing, one of the most fundamental enablers of cloud computing, leading to emergence of the Mobile Virtual Network Operator (MVNO) concept. The most momentous intents by this approach are the support of on-demand provisioning and elasticity of virtualized mobile network components, based on data traffic load. To realize it, during operation and management procedures, the virtualized services need be triggered in order to scale-up/down or scale-out/in an instance. In this paper we propose an architecture called MOBaaS (Mobility and Bandwidth Availability Prediction as a Service), comprising two algorithms in order to predict user(s) mobility and network link bandwidth availability, that can be implemented in cloud based mobile network structure and can be used as a support service by any other virtualized mobile network services. MOBaaS can provide prediction information in order to generate required triggers for on-demand deploying, provisioning, disposing of virtualized network components. This information can be used for self-adaptation procedures and optimal network function configuration during run-time operation, as well. Through the preliminary experiments with the prototype implementation on the OpenStack platform, we evaluated and confirmed the feasibility and the effectiveness of the prediction algorithms and the proposed architecture.

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Various avours of a new research field on (socio-)physical or personal analytics have emerged, with the goal of deriving semantically-rich insights from people's low-level physical sensing combined with their (online) social interactions. In this paper, we argue for more comprehensive data sources, including environmental (e.g. weather, infrastructure) and application-specific data, to better capture the interactions between users and their context, in addition to those among users. To illustrate our proposed concept of synergistic user <-> context analytics, we first provide some example use cases. Then, we present our ongoing work towards a synergistic analytics platform: a testbed, based on mobile crowdsensing and the Internet of Things (IoT), a data model for representing the different sources of data and their connections, and a prediction engine for analyzing the data and producing insights.

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Introduction Language is the most important mean of communication and plays a central role in our everyday life. Brain damage (e.g. stroke) can lead to acquired disorders of lan- guage affecting the four linguistic modalities (i.e. reading, writing, speech production and comprehension) in different combinations and levels of severity. Every year, more than 5000 people (Aphasie Suisse) are affected by aphasia in Switzerland alone. Since aphasia is highly individual, the level of difficulty and the content of tasks have to be adapted continuously by the speech therapists. Computer-based assignments allow patients to train independently at home and thus increasing the frequency of ther- apy. Recent developments in tablet computers have opened new opportunities to use these devices for rehabilitation purposes. Especially older people, who have no prior experience with computers, can benefit from the new technologies. Methods The aim of this project was to develop an application that enables patients to train language related tasks autonomously and, on the other hand, allows speech therapists to assign exercises to the patients and to track their results online. Seven categories with various types of assignments were implemented. The application has two parts which are separated by a user management system into a patient interface and a therapist interface. Both interfaces were evaluated using the SUS (Subject Usability Scale). The patient interface was tested by 15 healthy controls and 5 patients. For the patients, we also collected tracking data for further analysis. The therapist interface was evaluated by 5 speech therapists. Results The SUS score are xpatients = 98 and xhealthy = 92.7 (median = 95, SD = 7, 95% CI [88.8, 96.6]) in case of the patient interface and xtherapists = 68 in case of the therapist interface. Conclusion Both, the patients and the healthy subjects, attested high SUS scores to the patient interface. These scores are considered as "best imaginable". The therapist interface got a lower SUS score compared to the patient interface, but is still considered as "good" and "usable". The user tracking system and the interviews revealed that there is room for improvements and inspired new ideas for future versions.

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In this work, electrophoretic preconcentration of protein and peptide samples in microchannels was studied theoretically using the 1D dynamic simulator GENTRANS, and experimentally combined with MS. In all configurations studied, the sample was uniformly distributed throughout the channel before power application, and driving electrodes were used as microchannel ends. In the first part, previously obtained experimental results from carrier-free systems are compared to simulation results, and the effects of atmospheric carbon dioxide and impurities in the sample solution are examined. Simulation provided insight into the dynamics of the transport of all components under the applied electric field and revealed the formation of a pure water zone in the channel center. In the second part, the use of an IEF procedure with simple well defined amphoteric carrier components, i.e. amino acids, for concentration and fractionation of peptides was investigated. By performing simulations a qualitative description of the analyte behavior in this system was obtained. Neurotensin and [Glu1]-Fibrinopeptide B were separated by IEF in microchannels featuring a liquid lid for simple sample handling and placement of the driving electrodes. Component distributions in the channel were detected using MALDI- and nano-ESI-MS and data were in agreement with those obtained by simulation. Dynamic simulations are demonstrated to represent an effective tool to investigate the electrophoretic behavior of all components in the microchannel.