72 resultados para skill and knowledge


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Successful innovation diffusion process may well take the form of knowledge transfer process. Therefore, the primary objectives of this paper include: first, to evaluate the interrelations between transfer of knowledge and diffusion of innovation; and second to develop a model to establish a connection between the two. This has been achieved using a four-step approach. The first step of the approach is to assess and discuss the theories relating to knowledge transfer (KT) and innovation diffusion (ID). The second step focuses on developing basic models for KT and ID, based on the key theories surrounding these areas. A considerable amount of literature has been written on the association between knowledge management and innovation, the respective fields of KT and ID. The next step, therefore, explores the relationship between innovation and knowledge management in order to identify the connections between the latter, i.e. KT and ID. Finally, step four proposes and develops an integrated model for KT and ID. As the developed model suggests the sub-processes of knowledge transfer can be connected to the innovation diffusion process in several instances as discussed and illustrated in the paper.

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It is becoming increasingly important to be able to verify the spatial accuracy of precipitation forecasts, especially with the advent of high-resolution numerical weather prediction (NWP) models. In this article, the fractions skill score (FSS) approach has been used to perform a scale-selective evaluation of precipitation forecasts during 2003 from the Met Office mesoscale model (12 km grid length). The investigation shows how skill varies with spatial scale, the scales over which the data assimilation (DA) adds most skill, and how the loss of that skill is dependent on both the spatial scale and the rainfall coverage being examined. Although these results come from a specific model, they demonstrate how this verification approach can provide a quantitative assessment of the spatial behaviour of new finer-resolution models and DA techniques.

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Explanations of the marked individual differences in elementary school mathematical achievement and mathematical learning disability (MLD or dyscalculia) have involved domain-general factors (working memory, reasoning, processing speed and oral language) and numerical factors that include single-digit processing efficiency and multi-digit skills such as number system knowledge and estimation. This study of third graders (N = 258) finds both domain-general and numerical factors contribute independently to explaining variation in three significant arithmetic skills: basic calculation fluency, written multi-digit computation, and arithmetic word problems. Estimation accuracy and number system knowledge show the strongest associations with every skill and their contributions are both independent of each other and other factors. Different domain-general factors independently account for variation in each skill. Numeral comparison, a single digit processing skill, uniquely accounts for variation in basic calculation. Subsamples of children with MLD (at or below 10th percentile, n = 29) are compared with low achievement (LA, 11th to 25th percentiles, n = 42) and typical achievement (above 25th percentile, n = 187). Examination of these and subsets with persistent difficulties supports a multiple deficits view of number difficulties: most children with number difficulties exhibit deficits in both domain-general and numerical factors. The only factor deficit common to all persistent MLD children is in multi-digit skills. These findings indicate that many factors matter but multi-digit skills matter most in third grade mathematical achievement.

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The role of state and trait anxiety on observer ratings of social skill and negatively biased self-perception of social skill was examined. Participants were aged between 7 and 13 years (mean=9.65; sd=1.77; N=102), 47 had a current anxiety diagnosis and 55 were non-anxious controls. Participants were randomly allocated to a high or low anxiety condition and asked to complete social tasks. Task instructions were adjusted across conditions to manipulate participants’ state anxiety. Observers rated anxious participants as having poorer social skills than non-anxious controls but there was no evidence that anxious participants exhibited a negative self-perception bias, relative to controls. However, as participants’ ratings of state anxiety increased, their perception of their performance became more negatively biased. The results suggest that anxious children may exhibit real impairments in social skill and that high levels of state anxiety can lead to biased judgements of social skills in anxious and non-anxious children.

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Compared to skilled adult readers, children typically make more fixations that are longer in duration, shorter saccades, and more regressions, thus reading more slowly (Blythe & Joseph, 2011). Recent attempts to understand the reasons for these differences have discovered some similarities (e.g., children and adults target their saccades similarly; Joseph, Liversedge, Blythe, White, & Rayner, 2009) and some differences (e.g., children’s fixation durations are more affected by lexical variables; Blythe, Liversedge, Joseph, White, & Rayner, 2009) that have yet to be explained. In this article, the E-Z Reader model of eye-movement control in reading (Reichle, 2011; Reichle, Pollatsek, Fisher, & Rayner, 1998) is used to simulate various eye-movement phenomena in adults versus children in order to evaluate hypotheses about the concurrent development of reading skill and eye-movement behavior. These simulations suggest that the primary difference between children and adults is their rate of lexical processing, and that different rates of (post-lexical) language processing may also contribute to some phenomena (e.g., children’s slower detection of semantic anomalies; Joseph et al., 2008). The theoretical implications of this hypothesis are discussed, including possible alternative accounts of these developmental changes, how reading skill and eye movements change across the entire lifespan (e.g., college-aged vs. elderly readers), and individual differences in reading ability.

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A new method for assessing forecast skill and predictability that involves the identification and tracking of extratropical cyclones has been developed and implemented to obtain detailed information about the prediction of cyclones that cannot be obtained from more conventional analysis methodologies. The cyclones were identified and tracked along the forecast trajectories, and statistics were generated to determine the rate at which the position and intensity of the forecasted storms diverge from the analyzed tracks as a function of forecast lead time. The results show a higher level of skill in predicting the position of extratropical cyclones than the intensity. They also show that there is potential to improve the skill in predicting the position by 1 - 1.5 days and the intensity by 2 - 3 days, via improvements to the forecast model. Further analysis shows that forecasted storms move at a slower speed than analyzed storms on average and that there is a larger error in the predicted amplitudes of intense storms than the weaker storms. The results also show that some storms can be predicted up to 3 days before they are identified as an 850-hPa vorticity center in the analyses. In general, the results show a higher level of skill in the Northern Hemisphere (NH) than the Southern Hemisphere (SH); however, the rapid growth of NH winter storms is not very well predicted. The impact that observations of different types have on the prediction of the extratropical cyclones has also been explored, using forecasts integrated from analyses that were constructed from reduced observing systems. A terrestrial, satellite, and surface-based system were investigated and the results showed that the predictive skill of the terrestrial system was superior to the satellite system in the NH. Further analysis showed that the satellite system was not very good at predicting the growth of the storms. In the SH the terrestrial system has significantly less skill than the satellite system, highlighting the dominance of satellite observations in this hemisphere. The surface system has very poor predictive skill in both hemispheres.

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This paper uses a Foucauldian governmentality framework to analyse and interrogate the discourses and strategies adopted by the state and sections of the business community in their attempts to shape and influence emerging agendas of governance in post-devolution Scotland. Much of the work on governmentality has examined the ways in which governments have developed particular techniques, rationales and mechanisms to enable the functioning of governance programmes. This paper expands upon such analyses by also looking at the ways in which particular interests may use similar procedures, discourses and practices to promote their own agendas and develop new forms of resistance, contestation and challenge to emerging policy frameworks. Using the example of business interest mobilization in post-devolution Scotland, it is argued that governments may seek to mobilize defined forms of expertise and knowledge, linking them to wider political debates. This, however, creates new opportunities for interests to shape and contest the discourses and practices of government. The governmentalization of politics can, therefore, be seen as more of a dialectical process of definition and contestation than is often apparent in existing Foucault-inspired writing.

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Evaluating agents in decision-making applications requires assessing their skill and predicting their behaviour. Both are well developed in Poker-like situations, but less so in more complex game and model domains. This paper addresses both tasks by using Bayesian inference in a benchmark space of reference agents. The concepts are explained and demonstrated using the game of chess but the model applies generically to any domain with quantifiable options and fallible choice. Demonstration applications address questions frequently asked by the chess community regarding the stability of the rating scale, the comparison of players of different eras and/or leagues, and controversial incidents possibly involving fraud. The last include alleged under-performance, fabrication of tournament results, and clandestine use of computer advice during competition. Beyond the model world of games, the aim is to improve fallible human performance in complex, high-value tasks.

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The existence of endgame databases challenges us to extract higher-grade information and knowledge from their basic data content. Chess players, for example, would like simple and usable endgame theories if such holy grail exists: endgame experts would like to provide such insights and be inspired by computers to do so. Here, we investigate the use of artificial neural networks (NNs) to mine these databases and we report on a first use of NNs on KPK. The results encourage us to suggest further work on chess applications of neural networks and other data-mining techniques.

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In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.

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Construction materials and equipment are essential building blocks of every construction project and may account for 50-60 per cent of the total cost of construction. The rate of their utilization, on the other hand, is the element that most directly relates to a project progress. A growing concern in the industry that inadequate efficiency hinders its success could thus be accommodated by turning construction into a logistic process. Although mostly limited, recent attempts and studies show that Radio Frequency IDentification (RFID) applications have significant potentials in construction. However, the aim of this research is to show that the technology itself should not only be used for automation and tracking to overcome the supply chain complexity but also as a tool to generate, record and exchange process-related knowledge among the supply chain stakeholders. This would enable all involved parties to identify and understand consequences of any forthcoming difficulties and react accordingly before they cause major disruptions in the construction process. In order to achieve this aim the study focuses on a number of methods. First of all it develops a generic understanding of how RFID technology has been used in logistic processes in industrial supply chain management. Secondly, it investigates recent applications of RFID as an information and communication technology support facility in construction logistics for the management of construction supply chain. Based on these the study develops an improved concept of a construction logistics architecture that explicitly relies on integrating RFID with the Global Positioning System (GPS). The developed conceptual model architecture shows that categorisation provided through RFID and traceability as a result of RFID/GPS integration could be used as a tool to identify, record and share potential problems and thus vastly improve knowledge management processes within the entire supply chain. The findings thus clearly show a need for future research in this area.

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With 25% of the UK population predicted to be obese by 2010, the costs to individuals and society are set to rise. Due to the extra economic and social pressures obesity causes, there is an increasing need to understand what motivates and prevents consumers from eating a healthy diet so as to be able to tailor policy interventions to specific groups in society. In so doing, it is important to explore potential variations in attitudes, motivation and behaviour as a function of age and gender. Both demographic factors are easily distinguished within society and a future intervention study which targets either, or both, of these would likely be both feasible and cost-effective for policy makers. As part of a preliminary study, six focus groups (total n = 43) were conducted at the University of Reading in November 2006, with groups segmented on the basis of age and gender. In order to gather more sensitive information, participants were also asked to fill out a short anonymous questionnaire before each focus group began, relating to healthy eating, alcohol consumption and body dissatisfaction. Making use of thematic content analysis, results suggested that most participants were aware of the type of foods that contribute to a healthy diet and the importance of achieving a healthy balance within a diet. However, they believed that healthy eating messages were often conflicting, and were uncertain about where to find information on the topic. Participants believed that the family has an important role in educating children about eating habits. Despite these similarities, there were a number of key differences among the groups in terms of their reasons for making food choices. Older participants (60+ years old) were more likely to make food choices based on health considerations. Participants between the ages of 18–30 were less concerned with this link, and instead focused on issues of food preparation and knowledge, prices and time. Younger female participants said they had more energy when they ate healthier diets; however, very often their food choices related to concern with their appearance. Older female participants also expressed this concern within the questionnaire, rather than in the group discussions. Overall, these results suggest that consumer motivations for healthy eating are diverse and that this must be considered by government, retailers and food producers.

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The very long chain (VLC) n-3 polyunsaturated fatty acids (PUFA), particularly eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), are widely recognised to have beneficial effects on human health. However, recommended intakes of VLC n-3 PUFA (450 mg/day) are not being met by the diet in the majority of the population mainly because of low consumption of oil-rich fish. Current mean intake of VLC n-3 PUFA by adults is estimated to be about 282 mg/day with EPA and DHA contributing about 244 mg/day. Furthermore, the fact that only about 27% of adults eat any oil-rich fish (excluding canned tuna) and knowledge of the poor conversion of α-linolenic acid to EPA and DHA in vivo, particularly in men, leads to the need to review current dietary sources of these fatty acids. Animal-derived foods are likely to have an important function in increasing intake and studies have shown that feeding fish oils to animals can increase the EPA and DHA content of the resulting food products. This paper highlights the importance of examining current and projected consumption trends of meat and other animal products when exploring the potential impact of enriched foods by means of altering animal diets. When related to current food consumption data, potential dietary intakes of EPA+DHA from foods derived from animals fed enriched diets are calculated to be about 231 mg/day. If widely consumed, such foods could have a significant impact on progression of conditions such as cardiovascular disease. Consideration is also given to the sources of VLC n-3 PUFA in animal diets, with the sustainability of fish oil being questioned and the need to investigate the use of alternative dietary sources such as those of algal origin.

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In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.

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This paper investigates and evaluates the process of knowledge transfer in construction projects. Due to the highly competitive nature of business environments, knowledge transfer between organisations has become increasingly popular in recent years. However, although organisations can realise remarkable benefits by transferring knowledge from one unit to another, successful knowledge transfer can be difficult to achieve. The discussions presented in the paper are mainly based on findings of two case studies. The two cases were selected from Private Finance Initiative (PFI) projects in the UK. According to the case study findings, different stages of a knowledge transfer process can be overlapped, omitted, repeated as well as intermitted and then restarted. One of the significant findings of the case studies was the role of the "knowledge mediator". In selected case studies, there were external consultants and expert staff in the form of knowledge mediators. The importance of their roles was frequently highlighted by the interview participants. They were not only facilitating the close liaison between the knowledge source and the receiver, but also their role was strongly associated with practices of translation and interpretation. This combined role of mediator/translator, therefore, appears to be particularly significant for inter-organisational knowledge transfer in PFI projects.