909 resultados para knowledge based development


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The study of the morphodynamics of tidal channel networks is important because of their role in tidal propagation and the evolution of salt-marshes and tidal flats. Channel dimensions range from tens of metres wide and metres deep near the low water mark to only 20-30cm wide and 20cm deep for the smallest channels on the marshes. The conventional method of measuring the networks is cumbersome, involving manual digitising of aerial photographs. This paper describes a semi-automatic knowledge-based network extraction method that is being implemented to work using airborne scanning laser altimetry (and later aerial photography). The channels exhibit a width variation of several orders of magnitude, making an approach based on multi-scale line detection difficult. The processing therefore uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels using a distance-with-destination transform. Breaks in the networks are repaired by extending channel ends in the direction of their ends to join with nearby channels, using domain knowledge that flow paths should proceed downhill and that any network fragment should be joined to a nearby fragment so as to connect eventually to the open sea.

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In a knowledge-based economy and dynamic work environment retaining competitiveness is increasingly dependent on creativity, skills, individual abilities and appropriate motivation. For instance, the UK government explicitly stated in the recent "Review of Employee Engagement and Investment" report that new ways are required through which British companies could boost employee engagement at work, improving staff commitment and, thereby, increase workplace productivity. Although creativity and innovation have been studied extensively, little is known about employees' intrinsic willingness to contribute novel ideas and solutions (defined here as creative participation). For instance, the same individual can thrive in one organisation but be completely isolated in another and the question is to what extent this depends on individual characteristics and organisational settings. The main aim of this research is, therefore, to provide a conceptual framework for identification of individual characteristics that influence employees' willingness to contribute new ideas. In order to achieve this aim the investigation will be based on a developed psychological experiment, and will include personal-profiling inventory and a questionnaire. Understanding how these parameters influence willingness of an individual to put forward created ideas would offer an opportunity for companies to improve motivation practices and team efficiency, and can consequently lead to better overall performance.

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Motivation: Hydrogen bonds are one of the most important inter-atomic interactions in biology. Previous experimental, theoretical and bioinformatics analyses have shown that the hydrogen bonding potential of amino acids is generally satisfied and that buried unsatisfied hydrogen-bond-capable residues are destabilizing. When studying mutant proteins, or introducing mutations to residues involved in hydrogen bonding, one needs to know whether a hydrogen bond can be maintained. Our aim, therefore, was to develop a rapid method to evaluate whether a sidechain can form a hydrogen-bond. Results: A novel knowledge-based approach was developed in which the conformations accessible to the residues involved are taken into account. Residues involved in hydrogen bonds in a set of high resolution crystal structures were analyzed and this analysis is then applied to a given protein. The program was applied to assess mutations in the tumour-suppressor protein, p53. This raised the number of distinct mutations identified as disrupting sidechain-sidechain hydrogen bonding from 181 in our previous analysis to 202 in this analysis.

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“Fast & frugal” heuristics represent an appealing way of implementing bounded rationality and decision-making under pressure. The recognition heuristic is the simplest and most fundamental of these heuristics. Simulation and experimental studies have shown that this ignorance-driven heuristic inference can prove superior to knowledge based inference (Borges, Goldstein, Ortman & Gigerenzer, 1999; Goldstein & Gigerenzer, 2002) and have shown how the heuristic could develop from ACT-R’s forgetting function (Schooler & Hertwig, 2005). Mathematical analyses also demonstrate that, under certain conditions, a “less-is-more effect” will always occur (Goldstein & Gigerenzer, 2002). The further analyses presented in this paper show, however, that these conditions may constitute a special case and that the less-is-more effect in decision-making is subject to the moderating influence of the number of options to be considered and the framing of the question.

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Password Authentication Protocol (PAP) is widely used in the Wireless Fidelity Point-to-Point Protocol to authenticate an identity and password for a peer. This paper uses a new knowledge-based framework to verify the PAP protocol and a fixed version. Flaws are found in both the original and the fixed versions. A new enhanced protocol is provided and the security of it is proved The whole process is implemented in a mechanical reasoning platform, Isabelle. It only takes a few seconds to find flaws in the original and the fixed protocol and to verify that the enhanced version of the PAP protocol is secure.

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A hybridised and Knowledge-based Evolutionary Algorithm (KEA) is applied to the multi-criterion minimum spanning tree problems. Hybridisation is used across its three phases. In the first phase a deterministic single objective optimization algorithm finds the extreme points of the Pareto front. In the second phase a K-best approach finds the first neighbours of the extreme points, which serve as an elitist parent population to an evolutionary algorithm in the third phase. A knowledge-based mutation operator is applied in each generation to reproduce individuals that are at least as good as the unique parent. The advantages of KEA over previous algorithms include its speed (making it applicable to large real-world problems), its scalability to more than two criteria, and its ability to find both the supported and unsupported optimal solutions.

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It is indisputable that climate is an important factor in many livestock diseases. Nevertheless, our knowledge of the impact of climate change on livestock infectious diseases is much less certain.Therefore, the aim of the article is to conduct a systematic review of the literature on the topic utilizing available retrospective data and information. Across a corpus of 175 formal publications,limited empirical evidence was offered to underpin many of the main arguments. The literature reviewed was highly polarized and often inconsistent regarding what the future may hold. Historical explorations were rare. However, identifying past drivers to livestock disease may not fully capture the extent that new and unknown drivers will influence future change. As such, our current predictive capacity is low. We offer a number of recommendations to strengthen this capacity in the coming years. We conclude that our current approach to research on the topic is limiting and unlikely to yield sufficient, actionable evidence to inform future praxis. Therefore, we argue for the creation of a reflexive, knowledge-based system, underpinned by a collective intelligence framework to support the drawing of inferences across the literature.

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This study adopts the RBV of the firm in order to identify critical advantage-generating resources and capabilities with strong positive export strategy and performance implications. The proposed export performance model is tested using a structural equation modeling approach on a sample of 356 British exporters. We examine the individual as well as the concurrent (simultaneous) direct and indirect effects of five resource bundles on export performance. We find that four resources/capabilities: managerial, knowledge, planning, and technology, have a significant positive direct effect on export performance, while relational and physical resources exhibited no unique positive effect. We also find that the firm’s export strategy mediates the resource-performance nexus in the case of managerial and knowledge-based resources. The theoretical and methodological grounding of this study contributes to the advancement of export related research by providing better specification of the nature of the effects – direct or indirect – of particular resource factors on export performance.

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The Prism family of algorithms induces modular classification rules in contrast to the Top Down Induction of Decision Trees (TDIDT) approach which induces classification rules in the intermediate form of a tree structure. Both approaches achieve a comparable classification accuracy. However in some cases Prism outperforms TDIDT. For both approaches pre-pruning facilities have been developed in order to prevent the induced classifiers from overfitting on noisy datasets, by cutting rule terms or whole rules or by truncating decision trees according to certain metrics. There have been many pre-pruning mechanisms developed for the TDIDT approach, but for the Prism family the only existing pre-pruning facility is J-pruning. J-pruning not only works on Prism algorithms but also on TDIDT. Although it has been shown that J-pruning produces good results, this work points out that J-pruning does not use its full potential. The original J-pruning facility is examined and the use of a new pre-pruning facility, called Jmax-pruning, is proposed and evaluated empirically. A possible pre-pruning facility for TDIDT based on Jmax-pruning is also discussed.

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In order to gain knowledge from large databases, scalable data mining technologies are needed. Data are captured on a large scale and thus databases are increasing at a fast pace. This leads to the utilisation of parallel computing technologies in order to cope with large amounts of data. In the area of classification rule induction, parallelisation of classification rules has focused on the divide and conquer approach, also known as the Top Down Induction of Decision Trees (TDIDT). An alternative approach to classification rule induction is separate and conquer which has only recently been in the focus of parallelisation. This work introduces and evaluates empirically a framework for the parallel induction of classification rules, generated by members of the Prism family of algorithms. All members of the Prism family of algorithms follow the separate and conquer approach.

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Calls for understanding the interface between L2 linguistic knowledge and development (Gregg 1996; Carroll 2001; Towell 2003) provide a context for analysing the role of memory (Paradis 2004), specifically working memory (Baddeley 1986, 2003) in L2 development. Miyake and Friedman (1998) have claimed that Working Memory (WM) may be the key to L2 acquisition, especially in explaining individual variation in L2 acquisition. Recent findings found a robust connection between greater working memory (WM) capacity and rapid, successful acquisition of L2 vocabulary, reading and oral fluency (Service 1992; Harrington and Sawyer 1992; Fortkamp 1999). This study adds to the growing body of research by investigating correlations between WM and variation in grammatical development, focusing on asymmetries in processing L2 English wh-constructions in an immersion setting.

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It is indisputable that climate is an important factor in many livestock diseases. Nevertheless, our knowledge of the impact of climate change on livestock infectious diseases is much less certain. Therefore, the aim of the article is to conduct a systematic review of the literature on the topic utilizing available retrospective data and information. Across a corpus of 175 formal publications, limited empirical evidence was offered to underpin many of the main arguments. The literature reviewed was highly polarized and often inconsistent regarding what the future may hold. Historical explorations were rare. However, identifying past drivers to livestock disease may not fully capture the extent that new and unknown drivers will influence future change. As such, our current predictive capacity is low. We offer a number of recommendations to strengthen this capacity in the coming years. We conclude that our current approach to research on the topic is limiting and unlikely to yield sufficient, actionable evidence to inform future praxis. Therefore, we argue for the creation of a reflexive, knowledge-based system, underpinned by a collective intelligence framework to support the drawing of inferences across the literature.

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A virtual system that emulates an ARM-based processor machine has been created to replace a traditional hardware-based system for teaching assembly language. The proposed virtual system integrates, in a single environment, all the development tools necessary to deliver introductory or advanced courses on modern assembly language programming. The virtual system runs a Linux operating system in either a graphical or console mode on a Windows or Linux host machine. No software licenses or extra hardware are required to use the virtual system, thus students are free to carry their own ARM emulator with them on a USB memory stick. Institutions adopting this, or a similar virtual system, can also benefit by reducing capital investment in hardware-based development kits and enable distance learning courses.

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We investigated the processes of how adult readers evaluate and revise their situation model during reading by monitoring their eye movements as they read narrative texts and subsequent critical sentences. In each narrative text, a short introduction primed a knowledge-based inference, followed by a target concept that was either expected (e.g., “oven”) or unexpected (e.g., “grill”) in relation to the inferred concept. Eye movements showed that readers detected a mismatch between the new unexpected information and their prior interpretation, confirming their ability to evaluate inferential information. Just below the narrative text, a critical sentence included a target word that was either congruent (e.g., “roasted”) or incongruent (e.g., “barbecued”) with the expected but not the unexpected concept. Readers spent less time reading the congruent than the incongruent target word, reflecting the facilitation of prior information. In addition, when the unexpected (but not expected) concept had been presented, participants with lower verbal (but not visuospatial) working memory span exhibited longer reading times and made more regressions (from the critical sentence to previous information) on encountering congruent information, indicating difficulty in inhibiting their initial incorrect interpretation and revising their situation model