55 resultados para Knowledge representation (Information theory)


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We review the recent progress of information theory in optical communications, and describe the current experimental results and associated advances in various individual technologies which increase the information capacity. We confirm the widely held belief that the reported capacities are approaching the fundamental limits imposed by signal-to-noise ratio and the distributed non-linearity of conventional optical fibres, resulting in the reduction in the growth rate of communication capacity. We also discuss the techniques which are promising to increase and/or approach the information capacity limit.

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Technology-Enhanced Learning in Higher Education is an anthology produced by the international association, Learning in Higher Education (LiHE). LiHE, whose scope includes the activities of colleges, universities and other institutions of higher education, has been one of the leading organisations supporting a shift in the education process from a transmission-based philosophy to a student-centred, learning-based approach. Traditionally education has been envisaged as a process in which the teacher disseminates knowledge and information to the student, and directs them to perform – instructing, cajoling, encouraging them as appropriate – despite different students’ abilities. Yet higher education is currently experiencing rapid transformation, with the introduction of a broad range of technologies which have the potential to enhance student learning. This anthology draws upon the experiences of those practitioners who have been pioneering new applications of technology in higher education, highlighting not only the technologies themselves but also the impact which they have had on student learning. The anthology illustrates how new technologies – which are increasingly well-known and accepted by today’s ‘digital natives’ undertaking higher education – can be adopted and incorporated. One key conclusion is that learning remains a social process even in technology-enhanced learning contexts. So the technology-based proxies we construct need to retain and reflect the agency of the teacher. Technology-Enhanced Learning in Higher Education showcases some of the latest pedagogical technologies and their most creative, state-of-the-art applications to learning in higher education from around the world. Each of the chapters explores technology-enhanced learning in higher education in terms of either policy or practice. They contain detailed descriptions of approaches taken in very different curriculum areas, and demonstrate clearly that technology may and can enhance learning only if it is designed with the learning process of students at its core. So the use of technology in education is more linked to pedagogy than it is to bits and bytes.

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We present the analytical description of a specific nonlinear fibre channel with non-compensated dispersion. Information theory analysis shows that capacity of such nonlinear fibre channel does not decay with growing signal-to-noise ratio. © 2012 IEEE.

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A closed-form expression for a lower bound on the per soliton capacity of the nonlinear optical fibre channel in the presence of (optical) amplifier spontaneous emission (ASE) noise is derived. This bound is based on a non-Gaussian conditional probability density function for the soliton amplitude jitter induced by the ASE noise and is proven to grow logarithmically as the signal-to-noise ratio increases.

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Erasure control coding has been exploited in communication networks with an aim to improve the end-to-end performance of data delivery across the network. To address the concerns over the strengths and constraints of erasure coding schemes in this application, we examine the performance limits of two erasure control coding strategies, forward erasure recovery and adaptive erasure recovery. Our investigation shows that the throughput of a network using an (n, k) forward erasure control code is capped by r =k/n when the packet loss rate p ≤ (te/n) and by k(l-p)/(n-te) when p > (t e/n), where te is the erasure control capability of the code. It also shows that the lower bound of the residual loss rate of such a network is (np-te)/(n-te) for (te/n) < p ≤ 1. Especially, if the code used is maximum distance separable, the Shannon capacity of the erasure channel, i.e. 1-p, can be achieved and the residual loss rate is lower bounded by (p+r-1)/r, for (1-r) < p ≤ 1. To address the requirements in real-time applications, we also investigate the service completion time of different schemes. It is revealed that the latency of the forward erasure recovery scheme is fractionally higher than that of the scheme without erasure control coding or retransmission mechanisms (using UDP), but much lower than that of the adaptive erasure scheme when the packet loss rate is high. Results on comparisons between the two erasure control schemes exhibit their advantages as well as disadvantages in the role of delivering end-to-end services. To show the impact of the bounds derived on the end-to-end performance of a TCP/IP network, a case study is provided to demonstrate how erasure control coding could be used to maximize the performance of practical systems. © 2010 IEEE.

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Clusters of temporal optical solitons—stable self-localized light pulses preserving their form during propagation—exhibit properties characteristic of that encountered in crystals. Here, we introduce the concept of temporal solitonic information crystals formed by the lattices of optical pulses with variable phases. The proposed general idea offers new approaches to optical coherent transmission technology and can be generalized to dispersion-managed and dissipative solitons as well as scaled to a variety of physical platforms from fiber optics to silicon chips. We discuss the key properties of such dynamic temporal crystals that mathematically correspond to non-Hermitian lattices and examine the types of collective mode instabilities determining the lifetime of the soliton train. This transfer of techniques and concepts from solid state physics to information theory promises a new outlook on information storage and transmission.

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It has been suggested that, in order to maintain its relevance, critical research must develop a strong emphasis on empirical work rather than the conceptual emphasis that has typically characterized critical scholarship in management. A critical project of this nature is applicable in the information systems (IS) arena, which has a growing tradition of qualitative inquiry. Despite its relativist ontology, actor–network theory places a strong emphasis on empirical inquiry and this paper argues that actor–network theory, with its careful tracing and recording of heterogeneous networks, is well suited to the generation of detailed and contextual empirical knowledge about IS. The intention in this paper is to explore the relevance of IS research informed by actor–network theory in the pursuit of a broader critical research project as de? ned in earlier work.

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This paper will outline a research methodology informed by theorists who have contributed to actor network theory (ANT). Research informed from such a perspective recognizes the constitutive role of accounting systems in the achievement of broader social goals. Latour, Knoor Cetina and others argue that the bringing in of non-human actants, through the growth of technology and science, has added immeasurably to the complexity of modern society. The paper ‘sees’ accounting and accounting systems as being constituted by technological ‘black boxes’ and seeks to discuss two questions. One concerns the processes which surround the establishment of ‘facts’, i.e. how ‘black boxes’ are created or accepted (even if temporarily) within society. The second concerns the role of existing ‘black boxes’ within society and organizations. Accounting systems not only promote a particular view of the activities of an organization or a subunit, but in their very implementation and operation ‘mobilize’ other organizational members in a particular direction. The implications of such an interpretation are explored in this paper. Firstly through a discussion of some of the theoretic constructs that have been proposed to frame ANT research. Secondly an attempt is made to relate some of these ideas to aspects of the empirics in a qualitative case study. The case site is in the health sector and involves the implementation of a casemix accounting system. Evidence from the case research is used to exemplify aspects of the theoretical constructs.

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Web document cluster analysis plays an important role in information retrieval by organizing large amounts of documents into a small number of meaningful clusters. Traditional web document clustering is based on the Vector Space Model (VSM), which takes into account only two-level (document and term) knowledge granularity but ignores the bridging paragraph granularity. However, this two-level granularity may lead to unsatisfactory clustering results with “false correlation”. In order to deal with the problem, a Hierarchical Representation Model with Multi-granularity (HRMM), which consists of five-layer representation of data and a twophase clustering process is proposed based on granular computing and article structure theory. To deal with the zero-valued similarity problemresulted from the sparse term-paragraphmatrix, an ontology based strategy and a tolerance-rough-set based strategy are introduced into HRMM. By using granular computing, structural knowledge hidden in documents can be more efficiently and effectively captured in HRMM and thus web document clusters with higher quality can be generated. Extensive experiments show that HRMM, HRMM with tolerancerough-set strategy, and HRMM with ontology all outperform VSM and a representative non VSM-based algorithm, WFP, significantly in terms of the F-Score.

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The paper proposes an ISE (Information goal, Search strategy, Evaluation threshold) user classification model based on Information Foraging Theory for understanding user interaction with content-based image retrieval (CBIR). The proposed model is verified by a multiple linear regression analysis based on 50 users' interaction features collected from a task-based user study of interactive CBIR systems. To our best knowledge, this is the first principled user classification model in CBIR verified by a formal and systematic qualitative analysis of extensive user interaction data. Copyright 2010 ACM.