855 resultados para complex knowledge structures


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This dissertation investigates the very important and current problem of modelling human expertise. This is an apparent issue in any computer system emulating human decision making. It is prominent in Clinical Decision Support Systems (CDSS) due to the complexity of the induction process and the vast number of parameters in most cases. Other issues such as human error and missing or incomplete data present further challenges. In this thesis, the Galatean Risk Screening Tool (GRiST) is used as an example of modelling clinical expertise and parameter elicitation. The tool is a mental health clinical record management system with a top layer of decision support capabilities. It is currently being deployed by several NHS mental health trusts across the UK. The aim of the research is to investigate the problem of parameter elicitation by inducing them from real clinical data rather than from the human experts who provided the decision model. The induced parameters provide an insight into both the data relationships and how experts make decisions themselves. The outcomes help further understand human decision making and, in particular, help GRiST provide more accurate emulations of risk judgements. Although the algorithms and methods presented in this dissertation are applied to GRiST, they can be adopted for other human knowledge engineering domains.

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Martin Huelse: Generating complex connectivity structures for large-scale neural models. In: V. Kurkova, R. Neruda, and J. Koutnik (Eds.): ICANN 2008, Part II, LNCS 5164, pp. 849?858, 2008. Sponsorship: EPSRC

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Modern medical imaging techniques enable the acquisition of in vivo high resolution images of the vascular system. Most common methods for the detection of vessels in these images, such as multiscale Hessian-based operators and matched filters, rely on the assumption that at each voxel there is a single cylinder. Such an assumption is clearly violated at the multitude of branching points that are easily observed in all, but the Most focused vascular image studies. In this paper, we propose a novel method for detecting vessels in medical images that relaxes this single cylinder assumption. We directly exploit local neighborhood intensities and extract characteristics of the local intensity profile (in a spherical polar coordinate system) which we term as the polar neighborhood intensity profile. We present a new method to capture the common properties shared by polar neighborhood intensity profiles for all the types of vascular points belonging to the vascular system. The new method enables us to detect vessels even near complex extreme points, including branching points. Our method demonstrates improved performance over standard methods on both 2D synthetic images and 3D animal and clinical vascular images, particularly close to vessel branching regions. (C) 2008 Elsevier B.V. All rights reserved.

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We propose several new metrics to describe the complex ownership structure of business groups, and provide simple formulas and algorithms to compute these metrics. We use these measures to describe in detail the ownership structure of Korean chaebols in the period of 2003 to 2004. In addition, we validate the usefulness of our new metrics by showing empirically that they are important for understanding the valuation and performance of group firms. In particular, we show evidence that firms that are central to the control structure of the chaebol (central firms), firms in cross-shareholdings, and firms that are placed at the bottom of the group (i.e., with lower ultimate ownership) have lower profitability than other group firms. The valuation results suggest that central firms and firms in cross-shareholding loops have lower valuations than other public Chaebol firms. The lower valuation of these firms is not explained by variation in measures of ownership concentration and separation between ownership and control.

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In Chapter 1 I will present a brief introduction on the state of art of nanotechnologies, nanofabrication techniques and unconventional lithography as a technique to fabricate the novel electronic device as resistive switch so-called memristor is shown. In Chapter 2 a detailed description of the main fabrication and characterization techniques employed in this work is reported. Chapter 3 parallel local oxidation lithography (pLOx) describes as a main technique to obtain accurate patterning process. All the effective parameters has been studied and the optimized condition observed to highly reproducible with excellent patterned nanostructures. The effect of negative bias, calls local reduction (LR) studied. Moreover, the use of AC bias shows faster patterning process respect to DC bias. In Chapter 4 (metal/ e-SiO2/ Si nanojunction) it is shown how the electrochemical oxide nanostructures by using pLOx can be used in the fabrication of novel devices call memristor. We demonstrate a new concept, based on conventional materials, where the lifetime problem is resolved by introducing a “regeneration” step, which restores the nano-memristor to its pristine condition by applying an appropriate voltage cycle. In Chapter 5 (Graphene/ e-SiO2/ Si), Graphene as a building block material is used as an electrode to selectively oxidize the silicon substrate by pLOx set up for the fabrication of novel resistive switch device. In Chapter 6 (surface architecture) I will show another application of pLOx in biotechnology is shown. So the surface functionalization combine with nano-patterning by pLOx used to design a new surface to accurately bind biomolecules with the possibility of studying those properties and more application in nano-bio device fabrication. So, in order to obtain biochips, electronic and optical/photonics devices Nano patterning of DNA used as scaffolds to fabricate small functional nano-components.

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Among hyperbranched polymers, polyglycerol is one of the most promising and commonly used macromolecules due to its biocompatibility and versatility. However, the synthesis of high molecular weight polyglycerols still involves many intricacies and has only been understood to a limited extent. Furthermore, only few complex structures like star or block copolymers incorporating polyglycerol have been realized so far. Particularly biocompatible block copolymers are considered promising candidates for biomedical applications.rnThe scope of this thesis was the enhancement of the synthetic process leading to polyglycerol derivatives which implies improved molecular weight control for a broad molecular weight range as well as the assembly of more complex structures like amphiphilic block copolymers. Further insight into the relation between reaction solvent, degree of deprotonation during the ring-opening multibranching polymerization of glycidol and the characteristics of the obtained polymers were achieved within the scope of this work. Based on these results, a novel concept for the preparation of hyperbranched polyglycerols with molecular weights up to 20,000 g/mol was developed, applying a two step synthesis pathway. Starting from a partially deprotonated TMP core, low molecular weight hb-PGs were prepared using the known synthetic protocol that has been established since the late 1990ies. In a subsequent reaction sequence, these well defined polymers were used as hyperbranched macroinitiator cores in order to obtain high molecular weight hb-PGs with remarkably low polydispersity (Mw/Mn < 1.8). Molecular weight control was shown to be excellent and undesired low molecular weight side products were absent. Furthermore, the technique of continuous spin fractionation has been discovered as an efficient method for polyglycerol work-up to remove quantitatively residual monomer- and oligomer traces from hb-PG compositions to result in samples with significantly reduced polydispersities. Based on these results the synthesis of amphiphilic block copolymers containing hydrophilic hyperbranched polyglycerol blocks and linear, apolar poly(propylene oxide) blocks has been significantly improved and augmented to hb-PG-b-l-PPO-b-hb-PG ABA block copolymers. The influence of different polyglycerol-based amphiphiles on the fibril formation was studied by Thioflavin T Fluorescence showing remarkable increasing lag times which is promising in order to enhance the stability of this protein. In addition the first synthesis of poly(glyceryl glycerols) (PGG), introducing a new solketyl glycidyl ether monomer (IGG) was shown. It was furthermore demonstrated that core-functional carbosilane wedges allow application in block copolymer synthesis. Bisglycidolized amine functional polymers were successfully employed as macroinitiators for glycidol polymerization. This resulted in the first example of amphiphilic hyperbranched-hyperbranched polymer structures. Finally, it has been shown that the previously reported synthetic pathway to carboxylated hyperbranched polyglycerol polyelectrolytes can also be applied for the amphiphilic linear-hyperbranched block copolymers. These novel biocompatible and highly amphiphilic polyelectrolytes offer great potential for further investigations. rnrn

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"NSF/RA-780529."

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Background: Research into mental-health risks has tended to focus on epidemiological approaches and to consider pieces of evidence in isolation. Less is known about the particular factors and their patterns of occurrence that influence clinicians’ risk judgements in practice. Aims: To identify the cues used by clinicians to make risk judgements and to explore how these combine within clinicians’ psychological representations of suicide, self-harm, self-neglect, and harm to others. Method: Content analysis was applied to semi-structured interviews conducted with 46 practitioners from various mental-health disciplines, using mind maps to represent the hierarchical relationships of data and concepts. Results: Strong consensus between experts meant their knowledge could be integrated into a single hierarchical structure for each risk. This revealed contrasting emphases between data and concepts underpinning risks, including: reflection and forethought for suicide; motivation for self-harm; situation and context for harm to others; and current presentation for self-neglect. Conclusions: Analysis of experts’ risk-assessment knowledge identified influential cues and their relationships to risks. It can inform development of valid risk-screening decision support systems that combine actuarial evidence with clinical expertise.

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The last major study of sales performance variance explained by salespeople attributes was by Churchill et al. (1985). They examined the effect of role, skills, motivation, personal factors, aptitude, and organizational/environmental factors on sales performance—factors that have dominated the sales performance area. About the same time, Weitz, Sujan, and Sujan (1986) introduced the concepts of salespeople's knowledge structures. Considerable work on the relationship of the elements of knowledge structures and performance can be found in the literature. In this research note, we determine the degree to which sales performance can be explained by knowledge structure variables, a heretofore unexplored area. If knowledge structure variables explain more variance than traditional variables, then this paper would be a call to further research in this area. In examining this research question in a retail context, we find that knowledge structure variables explain 50.2 percent of the variance in sales performance. We also find that variance explained by knowledge structures is significantly different based on gender. The impact of knowledge structures on performance was higher for men than for women. The models using education demonstrated smaller differences.

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This thesis addressed the problem of risk analysis in mental healthcare, with respect to the GRiST project at Aston University. That project provides a risk-screening tool based on the knowledge of 46 experts, captured as mind maps that describe relationships between risks and patterns of behavioural cues. Mind mapping, though, fails to impose control over content, and is not considered to formally represent knowledge. In contrast, this thesis treated GRiSTs mind maps as a rich knowledge base in need of refinement; that process drew on existing techniques for designing databases and knowledge bases. Identifying well-defined mind map concepts, though, was hindered by spelling mistakes, and by ambiguity and lack of coverage in the tools used for researching words. A novel use of the Edit Distance overcame those problems, by assessing similarities between mind map texts, and between spelling mistakes and suggested corrections. That algorithm further identified stems, the shortest text string found in related word-forms. As opposed to existing approaches’ reliance on built-in linguistic knowledge, this thesis devised a novel, more flexible text-based technique. An additional tool, Correspondence Analysis, found patterns in word usage that allowed machines to determine likely intended meanings for ambiguous words. Correspondence Analysis further produced clusters of related concepts, which in turn drove the automatic generation of novel mind maps. Such maps underpinned adjuncts to the mind mapping software used by GRiST; one such new facility generated novel mind maps, to reflect the collected expert knowledge on any specified concept. Mind maps from GRiST are stored as XML, which suggested storing them in an XML database. In fact, the entire approach here is ”XML-centric”, in that all stages rely on XML as far as possible. A XML-based query language allows user to retrieve information from the mind map knowledge base. The approach, it was concluded, will prove valuable to mind mapping in general, and to detecting patterns in any type of digital information.

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Strain-free epitaxial quantum dots (QDs) are fabricated by a combination of Al local droplet etching (LDE) of nanoholes in AlGaAs surfaces and subsequent hole filling with GaAs. The whole process is performed in a conventional molecular beam epitaxy (MBE) chamber. Autocorrelation measurements establish single-photon emission from LDE QDs with a very small correlation function g (2)(0)≃ 0.01 of the exciton emission. Here, we focus on the influence of the initial hole depth on the QD optical properties with the goal to create deep holes suited for filling with more complex nanostructures like quantum dot molecules (QDM). The depth of droplet etched nanoholes is controlled by the droplet material coverage and the process temperature, where a higher coverage or temperature yields deeper holes. The requirements of high quantum dot uniformity and narrow luminescence linewidth, which are often found in applications, set limits to the process temperature. At high temperatures, the hole depths become inhomogeneous and the linewidth rapidly increases beyond 640 °C. With the present process technique, we identify an upper limit of 40-nm hole depth if the linewidth has to remain below 100 μeV. Furthermore, we study the exciton fine-structure splitting which is increased from 4.6 μeV in 15-nm-deep to 7.9 μeV in 35-nm-deep holes. As an example for the functionalization of deep nanoholes, self-aligned vertically stacked GaAs QD pairs are fabricated by filling of holes with 35 nm depth. Exciton peaks from stacked dots show linewidths below 100 μeV which is close to that from single QDs.