898 resultados para COLLABORATIVE AND PARALLEL FUZZY CLUSTERING


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The planctomycetes are a phylum of bacteria that have a unique cell compartmentalisation and yeast-like budding cell division and peptidoglycan-less proteinaceous cell walls. We wished to further our understanding of these unique organisms at the molecular level by searching for conserved amino acid sequence motifs and domains in the proteins encoded by Rhodopirellula baltica. Using BLAST and single-linkage clustering, we have discovered several new protein domains and sequence motifs in this planctomycete. R. baltica has multiple members of the newly discovered GEFGR protein family and the ASPIC C-terminal domain family, whilst most other organisms for which whole genome sequence is available have no more than one. Many of the domains and motifs appear to be restricted to the planctomycetes. It is possible that these protein domains and motifs may have been lost or replaced in other phyla, or they may have undergone multiple duplication events in the planctomycete lineage. One of the novel motifs probably represents a novel N-terminal export signal peptide. With their unique cell biology, it may be that the planctomycete cell compartmentalisation plan in particular needs special membrane transport mechanisms. The discovery of these new domains and motifs, many of which are associated with secretion and cell-surface functions, will help to stimulate experimental work and thus enhance further understanding of this fascinating group of organisms. (C) 2004 Federation of European Microbiological Societies. Published by Elsevier B.V. All rights reserved.

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This paper presents a finite-difference time-domain (FDTD) simulator for electromagnetic analysis and design applications in MRI. It is intended to be a complete FDTD model of an MRI system including all RF and low-frequency field generating units and electrical models of the patient. The pro-ram has been constructed in an object-oriented framework. The design procedure is detailed and the numerical solver has been verified against analytical solutions for simple cases and also applied to various field calculation problems. In particular, the simulator is demonstrated for inverse RF coil design, optimized source profile generation, and parallel imaging in high-frequency situations. The examples show new developments enabled by the simulator and demonstrate that the proposed FDTD framework can be used to analyze large-scale computational electromagnetic problems in modern MRI engineering. (C) 2004 Elsevier Inc. All rights reserved.

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Around the world, consumers and retailers of fresh produce are becoming more and more discerning about factors such as food safety and traceability, health, convenience and the sustainability of production systems, and in doing so they are changing the way in which fresh produce supply chains are configured and managed. When consumers demand fresh, safe, convenient, value-for-money produce, retailers in an increasingly competitive environment are attracted to those business models most capable of meeting these demands profitably. Traditional models are proving less and less able to deliver competitive advantage in such an environment. As a result, opportunistic, adversarial, price-based approaches to doing business between chain members are being replaced by approaches that are more strategic, collaborative and value-based. The shaping force behind this change is the need for producers, wholesalers, category managers, retailers and consumers to have more certainty about the performance of the supply chains upon which they rely. Certainty is generated through the supply chain's ability to create, deliver and share value. How to build supply chains that create, deliver and share value is arguably the single biggest challenge to the competitiveness of fresh produce firms, and therefore to the industries to which they belong.

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Similar pathological processes may be involved in the deposition of extracellular proteins in the brains of patients with Creutzfeldt-Jakob disease (CJD) and Alzheimer's disease (AD). Hence, this study compared the spatial patterns of prion protein (PrP) deposits in the cerebral cortex and hippocampus in cases of sporadic CJD with those of β-amyloid (Aβ) deposits in sporadic AD. PrP and Aβ deposits were aggregated into clusters and, in 90% of brain areas in CJD and 57% in AD, the clusters were regularly distributed parallel to the tissue boundary. In a significant proportion of cortical analyses, the mean diameter of the clusters of PrP and Aβ deposits were similar to those of the cells of origin of the cortico-cortical pathways. Aβ deposits in AD were distributed more frequently in larger-sized clusters than PrP deposits in CJD. In addition, in the hippocampus and dentate gyrus, clustering of Aβ deposits was observed in AD but PrP deposits were rare in these regions in CJD. The size, location and distribution of the extracellular protein deposits within the cortex of both disorders was consistent with the degeneration of the cortico-cortical pathways. Furthermore, spread of the pathology along these pathways may be a pathogenic feature common to CJD and AD. © 2001 Elsevier Science Ireland Ltd.

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Contrast masking from parallel grating surrounds (doughnuts) and superimposed orthogonal masks have different characteristics. However, it is not known whether the saturation of the underlying suppression that has been found for parallel doughnut masks depends on (i) relative mask and target orientation, (ii) stimulus eccentricity or (iii) surround suppression. We measured contrast-masking functions for target patches of grating in the fovea and in the periphery for cross-oriented superimposed and doughnut masks and parallel doughnut masks. When suppression was evident, the factor that determined whether it accelerated or saturated was whether the mask stimulus was crossed or parallel. There are at least two interpretations of the asymptotic behaviour of the parallel surround mask. (1) Suppression arises from pathways that saturate with (mask) contrast. (2) The target is processed by a mechanism that is subject to surround suppression at low target contrasts, but a less sensitive mechanism that is immune from surround suppression ‘breaks through’ at higher target contrasts. If the mask can be made less potent, then masking functions should shift downwards, and sideways for the two accounts, respectively. We manipulated the potency of the mask by varying the size of the hole in a parallel doughnut mask. The results provided strong evidence for the first account but not the second. On the view that response compression becomes more severe progressing up the visual pathway, our results suggest that superimposed cross-orientation suppression precedes orientation tuned surround suppression. These results also reveal a previously unrecognized similarity between surround suppression and crowding (Pelli, Palomares, & Majaj, 2004).

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Serial and parallel interconnection of photonic devices is integral to the construction of any all-optical data processing system. This thesis presents results from a series of experiments centering on the use of the nonlinear-optical loop mirror (NOLM) switch in architectures for the manipulation and generation of ultrashort pulses. Detailed analysis of soliton switching in a single NOLM and cascade of two NOLM's is performed, centering on primary limitations to device operation, effect of cascading on amplitude response, and impact of switching on the characteristics of incident pulses. By using relatively long input pulses, device failure due to stimulated Raman generation is postponed to demonstrate multiple-peaked switching for the first time. It is found that while cascading leads to a sharpening of the overall switching characteristic, pulse spectral and temporal integrity is not significantly degraded, and emerging pulses retain their essential soliton character. In addition, by including an asymmetrically placed in-fibre Bragg reflector as a wavelength selective loss element in the basic NOLM configuration, both soliton self-switching and dual-wavelength control-pulse switching are spectrally quantised. Results are presented from a novel dual-wavelength laser configuration generating pulse trains with an ultra-low rms inter-pulse-stream timing jitter level of 630fs enabling application in ultrafast switching environments at data rates as high as 130GBits/s. In addition, the fibre NOLM is included in architectures for all-optical memory, demonstrating storage and logical inversion of a 0.5kByte random data sequence; and ultrafast phase-locking of a gain-switched distributed feedback laser at 1.062GHz, the fourteenth harmonic of the system baseband frequency. The stringent requirements for environmental robustness of these architectures highlight the primary weaknesses of the NOLM in its fibre form and recommendations to overcome its inherent drawbacks are presented.

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The 21-day experimental gingivitis model, an established noninvasive model of inflammation in response to increasing bacterial accumulation in humans, is designed to enable the study of both the induction and resolution of inflammation. Here, we have analyzed gingival crevicular fluid, an oral fluid comprising a serum transudate and tissue exudates, by LC-MS/MS using Fourier transform ion cyclotron resonance mass spectrometry and iTRAQ isobaric mass tags, to establish meta-proteomic profiles of inflammation-induced changes in proteins in healthy young volunteers. Across the course of experimentally induced gingivitis, we identified 16 bacterial and 186 human proteins. Although abundances of the bacterial proteins identified did not vary temporally, Fusobacterium outer membrane proteins were detected. Fusobacterium species have previously been associated with periodontal health or disease. The human proteins identified spanned a wide range of compartments (both extracellular and intracellular) and functions, including serum proteins, proteins displaying antibacterial properties, and proteins with functions associated with cellular transcription, DNA binding, the cytoskeleton, cell adhesion, and cilia. PolySNAP3 clustering software was used in a multilayered analytical approach. Clusters of proteins that associated with changes to the clinical parameters included neuronal and synapse associated proteins.

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In Fourier domain optical coherence tomography (FD-OCT), a large amount of interference data needs to be resampled from the wavelength domain to the wavenumber domain prior to Fourier transformation. We present an approach to optimize this data processing, using a graphics processing unit (GPU) and parallel processing algorithms. We demonstrate an increased processing and rendering rate over that previously reported by using GPU paged memory to render data in the GPU rather than copying back to the CPU. This avoids unnecessary and slow data transfer, enabling a processing and display rate of well over 524,000 A-scan/s for a single frame. To the best of our knowledge this is the fastest processing demonstrated to date and the first time that FD-OCT processing and rendering has been demonstrated entirely on a GPU.

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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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We present a video-based system which interactively captures the geometry of a 3D object in the form of a point cloud, then recognizes and registers known objects in this point cloud in a matter of seconds (fig. 1). In order to achieve interactive speed, we exploit both efficient inference algorithms and parallel computation, often on a GPU. The system can be broken down into two distinct phases: geometry capture, and object inference. We now discuss these in further detail. © 2011 IEEE.

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Job satisfaction is a significant predictor of organisational innovation – especially where employees (including shop-floor workers) experience variety in their jobs and work in a single-status environment. The relationship between job satisfaction and performance has long intrigued work psychologists. The idea that "happy workers are productive workers" underpins many theories of performance, leadership, reward and job design. But contrary to popular belief, the relationship between job satisfaction and performance at individual level has been shown to be relatively weak. Research investigating the link between job satisfaction and creativity (the antecedent to innovation) shows that job dissatisfaction promotes creative outcomes. The logic is that those who are dissatisfied (and have decided to stay with the organisation) are determined to change things and have little to lose in doing so (see JM George & J Zhou, 2002). We were therefore surprised to find in the course of our own research into managerial practices and employee attitudes in manufacturing organisations that job satisfaction was a highly significant predictor of product and technological innovation. These results held even though the research was conducted longitudinally, over two years, while controlling for prior innovation. In other words, job satisfaction was a stronger predictor of innovation than any pre-existing orientation organisations had towards working innovatively. Using prior innovation as a control variable, as well as a longitudinal research design, strengthened our case against the argument that people are satisfied because they belong to a highly innovative organisation. We found that the relationship between job satisfaction and innovation was stronger still where organisations showed that they were committed to promoting job variety, especially at shop-floor level. We developed precise instruments to measure innovation, taking into account the magnitude of the innovation both in terms of the number of people involved in its implementation, and how new and different it was. Using this instrument, we are able to give each organisation in our sample a "score" from one to seven for innovation in areas ranging from administration to production technology. We found that much innovation is incremental, involving relatively minor improvements, rather than major change. To achieve sustained innovation, organisations have to draw on the skills and knowledge of employees at all levels. We also measured job satisfaction at organisational level, constructing a mean "job satisfaction" score for all organisations in our sample, and drawing only on those companies whose employees tended to respond in a similar manner to the questions they were asked. We argue that where most of the workforce experience job satisfaction, employees are more likely to collaborate, to share ideas and aim for high standards because people are keen to sustain their positive feelings. Job variety and single-status arrangements further strengthen the relationship between satisfaction and performance. This makes sense; where employees experience variety, they are exposed to new and different ideas and, provided they feel positive about their jobs, are likely to be willing to try to apply these ideas to improve their jobs. Similarly, staff working in single-status environments where hierarchical barriers are reduced are likely to feel trusted and valued by management and there is evidence (see G Jones & J George, 1998) that people work collaboratively and constructively with those they trust. Our study suggests that there is a strong business case for promoting employee job satisfaction. Managers and HR practitioners need to ensure their strategies and practices support and sustain job satisfaction among their workforces to encourage constructive, collaborative and creative working. It is more important than ever for organisations to respond rapidly to demands of the external environment. This study shows the positive association between organisational-level job satisfaction and innovation. So if a happy workforce is the key to unlocking innovation and organisations want to thrive in the global economy, it is vital that managers and HR practitioners pay close attention to employee perceptions of the work environment. In a world where the most innovative survive it could make all the difference.

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The intensity of global competition and ever-increasing economic uncertainties has led organizations to search for more efficient and effective ways to manage their business operations. Data envelopment analysis (DEA) has been widely used as a conceptually simple yet powerful tool for evaluating organizational productivity and performance. Fuzzy DEA (FDEA) is a promising extension of the conventional DEA proposed for dealing with imprecise and ambiguous data in performance measurement problems. This book is the first volume in the literature to present the state-of-the-art developments and applications of FDEA. It is designed for students, educators, researchers, consultants and practicing managers in business, industry, and government with a basic understanding of the DEA and fuzzy logic concepts.

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Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. Crisp input and output data are fundamentally indispensable in conventional DEA. However, the observed values of the input and output data in real-world problems are sometimes imprecise or vague. Many researchers have proposed various fuzzy methods for dealing with the imprecise and ambiguous data in DEA. This chapter provides a taxonomy and review of the fuzzy DEA (FDEA) methods. We present a classification scheme with six categories, namely, the tolerance approach, the α-level based approach, the fuzzy ranking approach, the possibility approach, the fuzzy arithmetic, and the fuzzy random/type-2 fuzzy set. We discuss each classification scheme and group the FDEA papers published in the literature over the past 30 years. © 2014 Springer-Verlag Berlin Heidelberg.

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In data mining, efforts have focused on finding methods for efficient and effective cluster analysis in large databases. Active themes of research focus on the scalability of clustering methods, the effectiveness of methods for clustering complex shapes and types of data, high-dimensional clustering techniques, and methods for clustering mixed numerical and categorical data in large databases. One of the most accuracy approach based on dynamic modeling of cluster similarity is called Chameleon. In this paper we present a modified hierarchical clustering algorithm that used the main idea of Chameleon and the effectiveness of suggested approach will be demonstrated by the experimental results.