882 resultados para knowledge-based system


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L'article és una reflexió sobre els requisits de formació dels professionals que demana la societat del coneixement. Un dels objectius més importants que ha de tenir la universitat en la societat del coneixement és la formació de professionals competents que tinguin prou eines intel·lectuals per a enfrontar-se a la incertesa de la informació, a la consciència que aquesta té una data de caducitat a curt termini i a l'ansietat que això provoca. Però, a més, també han de ser capaços de definir i crear les eines de treball amb què donaran sentit i eficàcia a aquest coneixement mudable i mutant. Per això, l'espai europeu d'ensenyament superior prioritza la competència transversal del treball col·laboratiu amb l'objectiu de promoure un aprenentatge autònom, compromès i adaptat a les noves necessitats de l'empresa del segle xxi. En aquest context, es presenta l'entorn teòric que fonamenta el treball desenvolupat a la plataforma informàtica ACME, que uneix el treball col·laboratiu i l'aprenentatge semipresencial o blended learning. Així mateix, es descriuen amb detall alguns exemples de wikis, paradigma del treball col·laboratiu, fets en assignatures impartides per la Universitat de Girona en l'espai virtual ACME

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Esta dissertação tem como objectivo principal procurar contribuir para a discussão em torno das valências das ferramentas da Qualidade aplicadas ao campo museal. O seu enfoque particular desenvolve-se ao nível dos serviços educativos, procurando avaliar os seus processos e resultados. Partindo da premissa de que os museus que aplicam os princípios da Qualidade nas suas práticas museais estão mais aptos a inspirarem e apoiarem as necessidades de aprendizagem dos seus utilizadores, esta dissertação defenderá as instituições museológicas enquanto organizações de conhecimento, sendo a aprendizagem o âmago da sua acção. A sua questão orientadora centra-se em torno da pertinência da aplicação da ferramenta de auto-avaliação Inspiring Learning for All em museus portugueses.

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The impact of selected observing systems on forecast skill is explored using the European Centre for Medium-Range Weather Forecasts (ECMWF) 40-yr reanalysis (ERA-40) system. Analyses have been produced for a surface-based observing system typical of the period prior to 1945/1950, a terrestrial-based observing system typical of the period 1950-1979 and a satellite-based observing system consisting of surface pressure and satellite observations. Global prediction experiments have been undertaken using these analyses as initial states, and which are available every 6 h, for the boreal winters of 1990/1991 and 2000/2001 and the summer of 2000, using a more recent version of the ECMWF model. The results show that for 500-hPa geopotential height, as a representative field, the terrestrial system in the Northern Hemisphere extratropics is only slightly inferior to the control system, which makes use of all observations for the analysis, and is also more accurate than the satellite system. There are indications that the skill of the terrestrial system worsens slightly and the satellite system improves somewhat between 1990/1991 and 2000/2001. The forecast skill in the Southern Hemisphere is dominated by the satellite information and this dominance is larger in the latter period. The overall skill is only slightly worse than that of the Northern Hemisphere. In the tropics (20 degrees S-20 degrees N), using the wind at 850 and 250 hPa as representative fields, the information content in the terrestrial and satellite systems is almost equal and complementary. The surface-based system has very limited skill restricted to the lower troposphere of the Northern Hemisphere. Predictability calculations show a potential for a further increase in predictive skill of 1-2 d in the extratropics of both hemispheres, but a potential for a major improvement of many days in the tropics. As well as the Eulerian perspective of predictability, the storm tracks have been calculated from all experiments and validated for the extratropics to provide a Lagrangian perspective.

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Tidal channel networks play an important role in the intertidal zone, exerting substantial control over the hydrodynamics and sediment transport of the region and hence over the evolution of the salt marshes and tidal flats. The study of the morphodynamics of tidal channels is currently an active area of research, and a number of theories have been proposed which require for their validation measurement of channels over extensive areas. Remotely sensed data provide a suitable means for such channel mapping. The paper describes a technique that may be adapted to extract tidal channels from either aerial photographs or LiDAR data separately, or from both types of data used together in a fusion approach. Application of the technique to channel extraction from LiDAR data has been described previously. However, aerial photographs of intertidal zones are much more commonly available than LiDAR data, and most LiDAR flights now involve acquisition of multispectral images to complement the LiDAR data. In view of this, the paper investigates the use of multispectral data for semiautomatic identification of tidal channels, firstly from only aerial photographs or linescanner data, and secondly from fused linescanner and LiDAR data sets. A multi-level, knowledge-based approach is employed. The algorithm based on aerial photography can achieve a useful channel extraction, though may fail to detect some of the smaller channels, partly because the spectral response of parts of the non-channel areas may be similar to that of the channels. The algorithm for channel extraction from fused LiDAR and spectral data gives an increased accuracy, though only slightly higher than that obtained using LiDAR data alone. The results illustrate the difficulty of developing a fully automated method, and justify the semi-automatic approach adopted.

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Inferences consistent with “recognition-based” decision-making may be drawn for various reasons other than recognition alone. We demonstrate that, for 2-alternative forced-choice decision tasks, less-is-more effects (reduced performance with additional learning) are not restricted to recognition-based inference but can also be seen in circumstances where inference is knowledge-based but item knowledge is limited. One reason why such effects may not be observed more widely is the dependence of the effect on specific values for the validity of recognition and knowledge cues. We show that both recognition and knowledge validity may vary as a function of the number of items recognized. The implications of these findings for the special nature of recognition information, and for the investigation of recognition-based inference, are discussed

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The study of the morphology of tidal networks and their relation to salt marsh vegetation is currently an active area of research, and a number of theories have been developed which require validation using extensive observations. Conventional methods of measuring networks and associated vegetation can be cumbersome and subjective. Recent advances in remote sensing techniques mean that these can now often reduce measurement effort whilst at the same time increasing measurement scale. The status of remote sensing of tidal networks and their relation to vegetation is reviewed. The measurement of network planforms and their associated variables is possible to sufficient resolution using digital aerial photography and airborne scanning laser altimetry (LiDAR), with LiDAR also being able to measure channel depths. A multi-level knowledge-based technique is described to extract networks from LiDAR in a semi-automated fashion. This allows objective and detailed geomorphological information on networks to be obtained over large areas of the inter-tidal zone. It is illustrated using LIDAR data of the River Ems, Germany, the Venice lagoon, and Carnforth Marsh, Morecambe Bay, UK. Examples of geomorphological variables of networks extracted from LiDAR data are given. Associated marsh vegetation can be classified into its component species using airborne hyperspectral and satellite multispectral data. Other potential applications of remote sensing for network studies include determining spatial relationships between networks and vegetation, measuring marsh platform vegetation roughness, in-channel velocities and sediment processes, studying salt pans, and for marsh restoration schemes.

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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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Two ongoing projects at ESSC that involve the development of new techniques for extracting information from airborne LiDAR data and combining this information with environmental models will be discussed. The first project in conjunction with Bristol University is aiming to improve 2-D river flood flow models by using remote sensing to provide distributed data for model calibration and validation. Airborne LiDAR can provide such models with a dense and accurate floodplain topography together with vegetation heights for parameterisation of model friction. The vegetation height data can be used to specify a friction factor at each node of a model’s finite element mesh. A LiDAR range image segmenter has been developed which converts a LiDAR image into separate raster maps of surface topography and vegetation height for use in the model. Satellite and airborne SAR data have been used to measure flood extent remotely in order to validate the modelled flood extent. Methods have also been developed for improving the models by decomposing the model’s finite element mesh to reflect floodplain features such as hedges and trees having different frictional properties to their surroundings. Originally developed for rural floodplains, the segmenter is currently being extended to provide DEMs and friction parameter maps for urban floods, by fusing the LiDAR data with digital map data. The second project is concerned with the extraction of tidal channel networks from LiDAR. These networks are important features of the inter-tidal zone, and play a key role in tidal propagation and in the evolution of salt-marshes and tidal flats. The study of their morphology is currently an active area of research, and a number of theories related to networks have been developed which require validation using dense and extensive observations of network forms and cross-sections. The conventional method of measuring networks is cumbersome and subjective, involving manual digitisation of aerial photographs in conjunction with field measurement of channel depths and widths for selected parts of the network. A semi-automatic technique has been developed to extract networks from LiDAR data of the inter-tidal zone. A multi-level knowledge-based approach has been implemented, whereby low level algorithms first extract channel fragments based mainly on image properties then a high level processing stage improves the network using domain knowledge. The approach adopted at low level uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels. The higher level processing includes a channel repair mechanism.

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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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Educational reforms in many countries currently call for the development of knowledge-based societies. In particular, emphasis is placed on the promotion of creativity, especially in the areas of science education and of design and technology education. In this paper, perceptions of the nature of creativity and of the conditions for its realization are discussed. The notion of modelling as a creative act is outlined and the scope for using modelling as a bridge between science education and design and technology education explored. A model for the creative act of modelling is proposed and its major aspects elaborated upon. Finally, strategies for forging links between the two subjects are outlined.

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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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The Java language first came to public attention in 1995. Within a year, it was being speculated that Java may be a good language for parallel and distributed computing. Its core features, including being objected oriented and platform independence, as well as having built-in network support and threads, has encouraged this view. Today, Java is being used in almost every type of computer-based system, ranging from sensor networks to high performance computing platforms, and from enterprise applications through to complex research-based.simulations. In this paper the key features that make Java a good language for parallel and distributed computing are first discussed. Two Java-based middleware systems, namely MPJ Express, an MPI-like Java messaging system, and Tycho, a wide-area asynchronous messaging framework with an integrated virtual registry are then discussed. The paper concludes by highlighting the advantages of using Java as middleware to support distributed applications.

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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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This paper discusses the design, implementation and synthesis of an FFT module that has been specifically optimized for use in the OFDM based Multiband UWB system, although the work is generally applicable to many other OFDM based receiver systems. Previous work has detailed the requirements for the receiver FFT module within the Multiband UWB ODFM based system and this paper draws on those requirements coupled with modern digital architecture principles and low power design criteria to converge on our optimized solution. The FFT design obtained in this paper is also applicable for implementation of the transmitter IFFT module therefore only needing one FFT module for half-duplex operation. The results from this paper enable the baseband designers of the 200Mbit/sec variant of Multiband UWB systems (and indeed other OFDM based receivers) using System-on-Chip (SoC), FPGA and ASIC technology to create cost effective and low power solutions biased toward the competitive consumer electronics market.