73 resultados para California, USA


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The programming and retasking of sensor nodes could benefit greatly from the use of a virtual machine (VM) since byte code is compact, can be loaded on demand, and interpreted on a heterogeneous set of devices. The challenge is to ensure good programming tools and a small footprint for the virtual machine to meet the memory constraints of typical WSN platforms. To this end we propose Darjeeling, a virtual machine modelled after the Java VM and capable of executing a substantial subset of the Java language, but designed specifically to run on 8- and 16-bit microcontrollers with 2 - 10 KB of RAM. The Darjeeling VM uses a 16- rather than a 32-bit architecture, which is more efficient on the targeted platforms. Darjeeling features a novel memory organisation with strict separation of reference from non-reference types which eliminates the need for run-time type inspection in the underlying compacting garbage collector. Darjeeling uses a linked stack model that provides light-weight threads, and supports synchronisation. The VM has been implemented on three different platforms and was evaluated with micro benchmarks and a real-world application. The latter includes a pure Java implementation of the collection tree routing protocol conveniently programmed as a set of cooperating threads, and a reimplementation of an existing environmental monitoring application. The results show that Darjeeling is a viable solution for deploying large-scale heterogeneous sensor networks. Copyright 2009 ACM.

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A number of learning problems can be cast as an Online Convex Game: on each round, a learner makes a prediction x from a convex set, the environment plays a loss function f, and the learner’s long-term goal is to minimize regret. Algorithms have been proposed by Zinkevich, when f is assumed to be convex, and Hazan et al., when f is assumed to be strongly convex, that have provably low regret. We consider these two settings and analyze such games from a minimax perspective, proving minimax strategies and lower bounds in each case. These results prove that the existing algorithms are essentially optimal.

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We demonstrate a modification of the algorithm of Dani et al for the online linear optimization problem in the bandit setting, which allows us to achieve an O( \sqrt{T ln T} ) regret bound in high probability against an adaptive adversary, as opposed to the in expectation result against an oblivious adversary of Dani et al. We obtain the same dependence on the dimension as that exhibited by Dani et al. The results of this paper rest firmly on those of Dani et al and the remarkable technique of Auer et al for obtaining high-probability bounds via optimistic estimates. This paper answers an open question: it eliminates the gap between the high-probability bounds obtained in the full-information vs bandit settings.

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Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive definite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space -- classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semi-definite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -- using the labelled part of the data one can learn an embedding also for the unlabelled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method to learn the 2-norm soft margin parameter in support vector machines, solving another important open problem. Finally, the novel approach presented in the paper is supported by positive empirical results.

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Identity-Based (IB) cryptography is a rapidly emerging approach to public-key cryptography that does not require principals to pre-compute key pairs and obtain certificates for their public keys— instead, public keys can be arbitrary identifiers such as email addresses, while private keys are derived at any time by a trusted private key generator upon request by the designated principals. Despite the flurry of recent results on IB encryption and signature, some questions regarding the security and efficiency of practicing IB encryption (IBE) and signature (IBS) as a joint IB signature/encryption (IBSE) scheme with a common set of parameters and keys, remain unanswered. We first propose a stringent security model for IBSE schemes. We require the usual strong security properties of: (for confidentiality) indistinguishability against adaptive chosen-ciphertext attacks, and (for nonrepudiation) existential unforgeability against chosen-message insider attacks. In addition, to ensure as strong as possible ciphertext armoring, we also ask (for anonymity) that authorship not be transmitted in the clear, and (for unlinkability) that it remain unverifiable by anyone except (for authentication) by the legitimate recipient alone. We then present an efficient IBSE construction, based on bilinear pairings, that satisfies all these security requirements, and yet is as compact as pairing-based IBE and IBS in isolation. Our scheme is secure, compact, fast and practical, offers detachable signatures, and supports multirecipient encryption with signature sharing for maximum scalability.

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The classic white formal shirt is a widely and readily familiar object with considerable historical cultural significance to diverse social groups, and is therefore deserving of iconic status. For more than two hundred years, this singular item of apparel has been able to define and represent status, wealth, gender shifts and fashion norms. This garment, which has historically been relinquished to undergarment status, deserves an escalation of standing. The classic white formal shirt, for both men and women, can be used as a mirror to map considerable social change and the diversity of influence can be traced through many examples, including: Beau Brummell’s dandy status with his legendry white shirting; the Gibson Girl with her decorated white shirt style blouse defining ideals of female beauty; IBM business employees in the 1920s marketing trustworthiness through the uniformity of white shirts; the fictional advertising creation of the Arrow Collar Man, with his rigid white shirt, promoting American masculine ideals; and the iconic 1980s Hugo Boss style crisp white dress shirt symbolising power. The origins of the influence of the white shirt can be best traced in the Victorian era where it was an important symbol of wealth and class distinction and a powerful emblem of sobriety and uniformity for men. The pure white colour fulfilled masculine ideals of resolute austerity and the shirt, through its constancy, epitomised conformity and dependability. For women, the white cloth of the ‘shirt-waist’ from this period was also linked to ideals of cleanliness and purity and was seen as an iconic symbol of the new independent working class woman. This paper will propose that the classic white formal shirt, for both men and women, has been a powerful marker of social shifts in Western society and this underrated item of apparel, with limited scholarly writing, is worthy of iconic status. The discussion will trace the historical development of both the men’s and women’s white shirt, each with their own unique history, and in doing so highlight the considerable historical cultural significance associated with the white formal shirt. Discussed first will be the men’s white formal shirt.

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The communal nature of knowledge production predicts the importance of creating learning organisations where knowledge arises out of processes that are personal, social, situated and active. It follows that workplaces must provide both formal and informal learning opportunities for interaction with ideas and among individuals. This grounded theory for developing contemporary learning organisations harvests insights from the knowledge management, systems sciences, and educational learning literatures. The resultant hybrid theoretical framework informs practical application, as reported in a case study that harnesses the accelerated information exchange possibilities enabled through web 2.0 social networking and peer production technologies. Through complementary organisational processes, 'meaning making' is negotiated in formal face-to-face meetings supplemented by informal 'boundary spanning' dialogue. The organisational capacity building potential of this participatory and inclusive approach is illustrated through the example of the Dr. Martin Luther King, Jr. Library in San Jose, California, USA. As an outcome of the strategic planning process at this joint city-university library, communication, decision-making, and planning structures, processes, and systems were re-invented. An enterprise- level redesign is presented, which fosters contextualising information interactions for knowledge sharing and community building. Knowledge management within this context envisions organisations as communities where knowledge, identity, and learning are situated. This framework acknowledges the social context of learning - i.e., that knowledge is acquired and understood through action, interaction, and sharing with others. It follows that social networks provide peer-to-peer enculturation through intentional exchange of tacit information made explicit. This, in turn, enables a dynamic process experienced as a continuous spiral that perpetually elevates collective understanding and enables knowledge creation.

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Effective management of chronic diseases is a global health priority. A healthcare information system offers opportunities to address challenges of chronic disease management. However, the requirements of health information systems are often not well understood. The accuracy of requirements has a direct impact on the successful design and implementation of a health information system. Our research describes methods used to understand the requirements of health information systems for advanced prostate cancer management. The research conducted a survey to identify heterogeneous sources of clinical records. Our research showed that the General Practitioner was the common source of patient's clinical records (41%) followed by the Urologist (14%) and other clinicians (14%). Our research describes a method to identify diverse data sources and proposes a novel patient journey browser prototype that integrates disparate data sources.

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In this paper, a framework for isolating unprecedented faults for an EGR valve system is presented. Using normal behavior data generated by a high fidelity engine simulation, the recently introduced Growing Structure Multiple Model System (GSMMS) is used to construct models of normal behavior for an EGR valve system and its various subsystems. Using the GSMMS models as a foundation, anomalous behavior of the entire system is then detected as statistically significant departures of the most recent modeling residuals from the modeling residuals during normal behavior. By reconnecting anomaly detectors to the constituent subsystems, the anomaly can be isolated without the need for prior training using faulty data. Furthermore, faults that were previously encountered (and modeled) are recognized using the same approach as the anomaly detectors.

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Contracting essentially involves an agreement between two parties in relation to a particular matter. When defined in this way, contracting has been occurring as a social practice since humans first bartered and conducted trade, and should be understood as both an economic as well as a social transaction. This entry explains key aspects of the sociology While contracting is commonly understood to be a market based transaction, Polyani famously argued that for most of recorded history commercial transactions were in fact secondary to social relationships. In other words, whenever economic transactions occurred, they were always in the context of reciprocal social relationships. Historically the primary mode of exchange may well have been based on social exchange and reciprocity, however with the rise of extensive industrialization in the 18th Century, the primary mode of exchange has led to more of a market based mode of exchange in developed countries, with the focus more about the economic transaction. As an agreement between two entities, contracting is an essential element to economic systems as it is the basis of most transactions, whether the agreement is verbal or written, explicit or implied. Contracting is thus a pervasive activity in our society, particularly between organizations, although individuals also engage in contracting. Typically, when discussing contracting, authors have either focused on the nature of the agreement itself, or on the governance arrangements in place to carry out the agreement.

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Nonprofit organizations have existed, in one form or another, for thousands of years. In many countries of the world nonprofits employ significant numbers of people, and contribute a significant percentage of GDP. Consequently, nonprofits are an important element of modern economies. Additionally, nonprofits make a significant contribution to society, due to the roles they play in caring for the poor or sick, fostering civil society, providing education and promoting religion...

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Outsourcing, or contracting-out as it is also known, is a prevalent business practice across all sectors of the economy. This entry will give a number of explanations about why organizations outsource, as well as a number of difficulties which may be encountered when outsourcing...