916 resultados para Context-Aware and Adaptable Architectures


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Context-aware applications rely on implicit forms of input, such as sensor-derived data, in order to reduce the need for explicit input from users. They are especially relevant for mobile and pervasive computing environments, in which user attention is at a premium. To support the development of context-aware applications, techniques for modelling context information are required. These must address a unique combination of requirements, including the ability to model information supplied by both sensors and people, to represent imperfect information, and to capture context histories. As the field of context-aware computing is relatively new, mature solutions for context modelling do not exist, and researchers rely on information modelling solutions developed for other purposes. In our research, we have been using a variant of Object-Role Modeling (ORM) to model context. In this paper, we reflect on our experiences and outline some research challenges in this area.

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Pervasive computing applications must be sufficiently autonomous to adapt their behaviour to changes in computing resources and user requirements. This capability is known as context-awareness. In some cases, context-aware applications must be implemented as autonomic systems which are capable of dynamically discovering and replacing context sources (sensors) at run-time. Unlike other types of application autonomy, this kind of dynamic reconfiguration has not been sufficiently investigated yet by the research community. However, application-level context models are becoming common, in order to ease programming of context-aware applications and support evolution by decoupling applications from context sources. We can leverage these context models to develop general (i.e., application-independent) solutions for dynamic, run-time discovery of context sources (i.e., context management). This paper presents a model and architecture for a reconfigurable context management system that supports interoperability by building on emerging standards for sensor description and classification.

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This research examines the role of the information management process within a process-oriented enterprise, Xerox Ltd. The research approach is based on a post-positive paradigm and has resulted in thirty-five idiographic statements. The three major outcomes are: 1. The process-oriented holistic enterprise is an organisation that requires a long-term management commitment to its development. It depends on the careful management of people, tasks, information and technology. A complex integration of business processes is required and this can be managed through the use of consistent documentation techniques, clarity in the definition of process responsibilities and management attention to the global metrics and the centralisation of the management of the process model are critical to its success. 2. The role of the information management process within the context of a process-oriented enterprise is to provide flexible and cost-effective applications, technological, and process support to the business. This is best achieved through a centralisation of the management of information management and of the process model. A business-led approach combined with the consolidation of applications, information, process, and data architectures is central to providing effective business and process-focused support. 3. In a process oriented holistic enterprise, process and information management are inextricably linked. The model of process management depends heavily on information management, whilst the model of information management is totally focused around supporting and creating the process model. The two models are mutually creating - one cannot exist without the other. There is a duality concept of process and information management.

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Novel computing systems are increasingly being composed of large numbers of heterogeneous components, each with potentially different goals or local perspectives, and connected in networks which change over time. Management of such systems quickly becomes infeasible for humans. As such, future computing systems should be able to achieve advanced levels of autonomous behaviour. In this context, the system's ability to be self-aware and be able to self-express becomes important. This paper surveys definitions and current understanding of self-awareness and self-expression in biology and cognitive science. Subsequently, previous efforts to apply these concepts to computing systems are described. This has enabled the development of novel working definitions for self-awareness and self-expression within the context of computing systems.

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METPEX is a 3 year, FP7 project which aims to develop a PanEuropean tool to measure the quality of the passenger's experience of multimodal transport. Initial work has led to the development of a comprehensive set of variables relating to different passenger groups, forms of transport and journey stages. This paper addresses the main challenges in transforming the variables into usable, accessible computer based tools allowing for the real time collection of information, across multiple journey stages in different EU countries. Non-computer based measurement instruments will be used to gather information from those who may not have or be familiar with mobile technology. Smartphone-based measurement instruments will also be used, hosted in two applications. The mobile applications need to be easy to use, configurable and adaptable according to the context of use. They should also be inherently interesting and rewarding for the participant, whilst allowing for the collection of high quality, valid and reliable data from all journey types and stages (from planning, through to entry into and egress from different transport modes, travel on public and personal vehicles and support of active forms of transport (e.g. cycling and walking). During all phases of the data collection and processing, the privacy of the participant is highly regarded and is ensured. © 2014 Springer International Publishing.

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Mediation techniques provide interoperability and support integrated query processing among heterogeneous databases. While such techniques help data sharing among different sources, they increase the risk for data security, such as violating access control rules. Successful protection of information by an effective access control mechanism is a basic requirement for interoperation among heterogeneous data sources. ^ This dissertation first identified the challenges in the mediation system in order to achieve both interoperability and security in the interconnected and collaborative computing environment, which includes: (1) context-awareness, (2) semantic heterogeneity, and (3) multiple security policy specification. Currently few existing approaches address all three security challenges in mediation system. This dissertation provides a modeling and architectural solution to the problem of mediation security that addresses the aforementioned security challenges. A context-aware flexible authorization framework was developed in the dissertation to deal with security challenges faced by mediation system. The authorization framework consists of two major tasks, specifying security policies and enforcing security policies. Firstly, the security policy specification provides a generic and extensible method to model the security policies with respect to the challenges posed by the mediation system. The security policies in this study are specified by 5-tuples followed by a series of authorization constraints, which are identified based on the relationship of the different security components in the mediation system. Two essential features of mediation systems, i. e., relationship among authorization components and interoperability among heterogeneous data sources, are the focus of this investigation. Secondly, this dissertation supports effective access control on mediation systems while providing uniform access for heterogeneous data sources. The dynamic security constraints are handled in the authorization phase instead of the authentication phase, thus the maintenance cost of security specification can be reduced compared with related solutions. ^

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The current research sought to clarify the diverging relationships between counterfactual thinking and hindsight bias observed in the literature thus far. In a non-legal context, Roese and Olson (1996) found a positive relationship between counterfactuals and hindsight bias, such that counterfactual mutations that undid the outcome also increased participants’ ratings of the outcome’s a priori likelihood. Further, they determined that this relationship is mediated by causal attributions about the counterfactually mutated antecedent event. Conversely, in the context of a civil lawsuit, Robbennolt and Sobus (1997) found that the relationship between counterfactual thinking and hindsight bias is negative. The current research sought to resolve the conflicting findings in the literature within a legal context. ^ In Experiment One, the manipulation of the normality of the defendant’s target behavior, designed to manipulate participants’ counterfactual thoughts about said behavior, did moderate the hindsight effect of outcome knowledge on mock jurors’ judgments of the foreseeability of that outcome as well as their negligence verdicts. Although I predicted that counterfactual thinking would increase, or exacerbate, the hindsight bias, as found by Roese and Olson (1996), my results provided some support for Robbenolt and Sobus’s (1997) finding that counterfactual thinking decreases the hindsight bias. Behavior normality did not moderate the hindsight effect of outcome knowledge in Experiment Two, nor did causal proximity in Experiment Three. ^ Additionally, my hypothesis that self-referencing may be an effective hindsight debiasing technique received little support across the three experiments. Although both the self-referencing instructions and self-report measure consistently decreased mock jurors’ likelihood of finding the defendant negligent, and self-referencing instructions decreased their foreseeability ratings in studies two and three, the self-referencing manipulation did not interact with outcome knowledge to moderate a hindsight bias effect on either foreseeability or negligence judgments. The consistent pattern of results across the three experiments, however, suggests that self-referencing may be an effective technique in reducing the likelihood of negligence verdicts.^

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The current research sought to clarify the diverging relationships between counterfactual thinking and hindsight bias observed in the literature thus far. In a non-legal context, Roese and Olson (1996) found a positive relationship between counterfactuals and hindsight bias, such that counterfactual mutations that undid the outcome also increased participants’ ratings of the outcome’s a priori likelihood. Further, they determined that this relationship is mediated by causal attributions about the counterfactually mutated antecedent event. Conversely, in the context of a civil lawsuit, Robbennolt and Sobus (1997) found that the relationship between counterfactual thinking and hindsight bias is negative. The current research sought to resolve the conflicting findings in the literature within a legal context. In Experiment One, the manipulation of the normality of the defendant’s target behavior, designed to manipulate participants’ counterfactual thoughts about said behavior, did moderate the hindsight effect of outcome knowledge on mock jurors’ judgments of the foreseeability of that outcome as well as their negligence verdicts. Although I predicted that counterfactual thinking would increase, or exacerbate, the hindsight bias, as found by Roese and Olson (1996), my results provided some support for Robbenolt and Sobus’s (1997) finding that counterfactual thinking decreases the hindsight bias. Behavior normality did not moderate the hindsight effect of outcome knowledge in Experiment Two, nor did causal proximity in Experiment Three. Additionally, my hypothesis that self-referencing may be an effective hindsight debiasing technique received little support across the three experiments. Although both the self-referencing instructions and self-report measure consistently decreased mock jurors’ likelihood of finding the defendant negligent, and self-referencing instructions decreased their foreseeability ratings in studies two and three, the self-referencing manipulation did not interact with outcome knowledge to moderate a hindsight bias effect on either foreseeability or negligence judgments. The consistent pattern of results across the three experiments, however, suggests that self-referencing may be an effective technique in reducing the likelihood of negligence verdicts.

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In Marxist frameworks “distributive justice” depends on extracting value through a centralized state. Many new social movements—peer to peer economy, maker activism, community agriculture, queer ecology, etc.—take the opposite approach, keeping value in its unalienated form and allowing it to freely circulate from the bottom up. Unlike Marxism, there is no general theory for bottom-up, unalienated value circulation. This paper examines the concept of “generative justice” through an historical contrast between Marx’s writings and the indigenous cultures that he drew upon. Marx erroneously concluded that while indigenous cultures had unalienated forms of production, only centralized value extraction could allow the productivity needed for a high quality of life. To the contrary, indigenous cultures now provide a robust model for the “gift economy” that underpins open source technological production, agroecology, and restorative approaches to civil rights. Expanding Marx’s concept of unalienated labor value to include unalienated ecological (nonhuman) value, as well as the domain of freedom in speech, sexual orientation, spirituality and other forms of “expressive” value, we arrive at an historically informed perspective for generative justice. 

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Internet users consume online targeted advertising based on information collected about them and voluntarily share personal information in social networks. Sensor information and data from smart-phones is collected and used by applications, sometimes in unclear ways. As it happens today with smartphones, in the near future sensors will be shipped in all types of connected devices, enabling ubiquitous information gathering from the physical environment, enabling the vision of Ambient Intelligence. The value of gathered data, if not obvious, can be harnessed through data mining techniques and put to use by enabling personalized and tailored services as well as business intelligence practices, fueling the digital economy. However, the ever-expanding information gathering and use undermines the privacy conceptions of the past. Natural social practices of managing privacy in daily relations are overridden by socially-awkward communication tools, service providers struggle with security issues resulting in harmful data leaks, governments use mass surveillance techniques, the incentives of the digital economy threaten consumer privacy, and the advancement of consumergrade data-gathering technology enables new inter-personal abuses. A wide range of fields attempts to address technology-related privacy problems, however they vary immensely in terms of assumptions, scope and approach. Privacy of future use cases is typically handled vertically, instead of building upon previous work that can be re-contextualized, while current privacy problems are typically addressed per type in a more focused way. Because significant effort was required to make sense of the relations and structure of privacy-related work, this thesis attempts to transmit a structured view of it. It is multi-disciplinary - from cryptography to economics, including distributed systems and information theory - and addresses privacy issues of different natures. As existing work is framed and discussed, the contributions to the state-of-theart done in the scope of this thesis are presented. The contributions add to five distinct areas: 1) identity in distributed systems; 2) future context-aware services; 3) event-based context management; 4) low-latency information flow control; 5) high-dimensional dataset anonymity. Finally, having laid out such landscape of the privacy-preserving work, the current and future privacy challenges are discussed, considering not only technical but also socio-economic perspectives.

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Stand-alone and networked surgical virtual reality based simulators have been proposed as means to train surgical skills with or without a supervisor nearby the student or trainee -- However, surgical skills teaching in medicine schools and hospitals is changing, requiring the development of new tools to focus on: (i) importance of mentors role, (ii) teamwork skills and (iii) remote training support -- For these reasons, a surgical simulator should not only allow the training involving a student and an instructor that are located remotely, but also the collaborative training of users adopting different medical roles during the training sesión -- Collaborative Networked Virtual Surgical Simulators (CNVSS) allow collaborative training of surgical procedures where remotely located users with different surgical roles can take part in the training session -- To provide successful training involving good collaborative performance, CNVSS should handle heterogeneity factors such as users’ machine capabilities and network conditions, among others -- Several systems for collaborative training of surgical procedures have been developed as research projects -- To the best of our knowledge none has focused on handling heterogeneity in CNVSS -- Handling heterogeneity in this type of collaborative sessions is important because not all remotely located users have homogeneous internet connections, nor the same interaction devices and displays, nor the same computational resources, among other factors -- Additionally, if heterogeneity is not handled properly, it will have an adverse impact on the performance of each user during the collaborative sesión -- In this document, the development of a context-aware architecture for collaborative networked virtual surgical simulators, in order to handle the heterogeneity involved in the collaboration session, is proposed -- To achieve this, the following main contributions are accomplished in this thesis: (i) Which and how infrastructure heterogeneity factors affect the collaboration of two users performing a virtual surgical procedure were determined and analyzed through a set of experiments involving users collaborating, (ii) a context-aware software architecture for a CNVSS was proposed and implemented -- The architecture handles heterogeneity factors affecting collaboration, applying various adaptation mechanisms and finally, (iii) A mechanism for handling heterogeneity factors involved in a CNVSS is described, implemented and validated in a set of testing scenarios

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Repeatability of behavioural and physiological traits is increasingly a focus for animal researchers, for which fish have become important models. Almost all of this work has been done in the context of evolutionary ecology, with few explicit attempts to apply repeatability and context dependency of trait variation toward understanding conservation-related issues. Here, we review work examining the degree to which repeatability of traits (such as boldness, swimming performance, metabolic rate and stress responsiveness) is context dependent. We review methods for quantifying repeatability (distinguishing between within-context and across-context repeatability) and confounding factors that may be especially problematic when attempting to measure repeatability in wild fish. Environmental factors such temperature, food availability, oxygen availability, hypercapnia, flow regime and pollutants all appear to alter trait repeatability in fishes. This suggests that anthropogenic environmental change could alter evolutionary trajectories by changing which individuals achieve the greatest fitness in a given set of conditions. Gaining a greater understanding of these effects will be crucial for our ability to forecast the effects of gradual environmental change, such as climate change and ocean acidification, the study of which is currently limited by our ability to examine trait changes over relatively short time scales. Also discussed are situations in which recent advances in technologies associated with electronic tags (biotelemetry and biologging) and respirometry will help to facilitate increased quantification of repeatability for physiological and integrative traits, which so far lag behind measures of repeatability of behavioural traits.

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As the interest in the Web of Things increases, specially for the general population, the barriers to entry for the use of these technologies should decrease. Current applications can be developed to adapt their behaviour to predefined conditions and users preferences, facilitating their use. In the future,Web of Things software should be able to automatically adjust its behaviour to non-predefined preferences or context of its users. In this vision paper we define the Situational-Context as the combination of the virtual profiles of the entities (things or people) that concur at a particular place and time. The computation of the Situational-Context allow us to predict the expected system behaviour and the required interaction between devices to meet the entities’ goals, achieving a better adjustment of the system to variable contexts.