919 resultados para VLE data sets
Resumo:
Evidence-based policy is a means of ensuring that policy is informed by more than ideology or expedience. However, what constitutes robust evidence is highly contested. In this paper, we argue policy must draw on quantitative and qualitative data. We do this in relation to a long entrenched problem in Australian early childhood education and care (ECEC) workforce policy. A critical shortage of qualified staff threatens the attainment of broader child and family policy objectives linked to the provision of ECEC and has not been successfully addressed by initiatives to date. We establish some of the limitations of existing quantitative data sets and consider the potential of qualitative studies to inform ECEC workforce policy. The adoption of both quantitative and qualitative methods is needed to illuminate the complex nature of the work undertaken by early childhood educators, as well as the environmental factors that sustain job satisfaction in a demanding and poorly understood working environment.
Resumo:
Support Vector Machines(SVMs) are hyperplane classifiers defined in a kernel induced feature space. The data size dependent training time complexity of SVMs usually prohibits its use in applications involving more than a few thousands of data points. In this paper we propose a novel kernel based incremental data clustering approach and its use for scaling Non-linear Support Vector Machines to handle large data sets. The clustering method introduced can find cluster abstractions of the training data in a kernel induced feature space. These cluster abstractions are then used for selective sampling based training of Support Vector Machines to reduce the training time without compromising the generalization performance. Experiments done with real world datasets show that this approach gives good generalization performance at reasonable computational expense.
Resumo:
In order to predict the current state and future development of Earth s climate, detailed information on atmospheric aerosols and aerosol-cloud-interactions is required. Furthermore, these interactions need to be expressed in such a way that they can be represented in large-scale climate models. The largest uncertainties in the estimate of radiative forcing on the present day climate are related to the direct and indirect effects of aerosol. In this work aerosol properties were studied at Pallas and Utö in Finland, and at Mount Waliguan in Western China. Approximately two years of data from each site were analyzed. In addition to this, data from two intensive measurement campaigns at Pallas were used. The measurements at Mount Waliguan were the first long term aerosol particle number concentration and size distribution measurements conducted in this region. They revealed that the number concentration of aerosol particles at Mount Waliguan were much higher than those measured at similar altitudes in other parts of the world. The particles were concentrated in the Aitken size range indicating that they were produced within a couple of days prior to reaching the site, rather than being transported over thousands of kilometers. Aerosol partitioning between cloud droplets and cloud interstitial particles was studied at Pallas during the two measurement campaigns, First Pallas Cloud Experiment (First PaCE) and Second Pallas Cloud Experiment (Second PaCE). The method of using two differential mobility particle sizers (DMPS) to calculate the number concentration of activated particles was found to agree well with direct measurements of cloud droplet. Several parameters important in cloud droplet activation were found to depend strongly on the air mass history. The effects of these parameters partially cancelled out each other. Aerosol number-to-volume concentration ratio was studied at all three sites using data sets with long time-series. The ratio was found to vary more than in earlier studies, but less than either aerosol particle number concentration or volume concentration alone. Both air mass dependency and seasonal pattern were found at Pallas and Utö, but only seasonal pattern at Mount Waliguan. The number-to-volume concentration ratio was found to follow the seasonal temperature pattern well at all three sites. A new parameterization for partitioning between cloud droplets and cloud interstitial particles was developed. The parameterization uses aerosol particle number-to-volume concentration ratio and aerosol particle volume concentration as the only information on the aerosol number and size distribution. The new parameterization is computationally more efficient than the more detailed parameterizations currently in use, but the accuracy of the new parameterization was slightly lower. The new parameterization was also compared to directly observed cloud droplet number concentration data, and a good agreement was found.
Resumo:
Radiation therapy (RT) plays currently significant role in curative treatments of several cancers. External beam RT is carried out mostly by using megavoltage beams of linear accelerators. Tumor eradication and normal tissue complications correlate to dose absorbed in tissues. Normally this dependence is steep and it is crucial that actual dose within patient accurately correspond to the planned dose. All factors in a RT procedure contain uncertainties requiring strict quality assurance. From hospital physicist´s point of a view, technical quality control (QC), dose calculations and methods for verification of correct treatment location are the most important subjects. Most important factor in technical QC is the verification that radiation production of an accelerator, called output, is within narrow acceptable limits. The output measurements are carried out according to a locally chosen dosimetric QC program defining measurement time interval and action levels. Dose calculation algorithms need to be configured for the accelerators by using measured beam data. The uncertainty of such data sets limits for best achievable calculation accuracy. All these dosimetric measurements require good experience, are workful, take up resources needed for treatments and are prone to several random and systematic sources of errors. Appropriate verification of treatment location is more important in intensity modulated radiation therapy (IMRT) than in conventional RT. This is due to steep dose gradients produced within or close to healthy tissues locating only a few millimetres from the targeted volume. The thesis was concentrated in investigation of the quality of dosimetric measurements, the efficacy of dosimetric QC programs, the verification of measured beam data and the effect of positional errors on the dose received by the major salivary glands in head and neck IMRT. A method was developed for the estimation of the effect of the use of different dosimetric QC programs on the overall uncertainty of dose. Data were provided to facilitate the choice of a sufficient QC program. The method takes into account local output stability and reproducibility of the dosimetric QC measurements. A method based on the model fitting of the results of the QC measurements was proposed for the estimation of both of these factors. The reduction of random measurement errors and optimization of QC procedure were also investigated. A method and suggestions were presented for these purposes. The accuracy of beam data was evaluated in Finnish RT centres. Sufficient accuracy level was estimated for the beam data. A method based on the use of reference beam data was developed for the QC of beam data. Dosimetric and geometric accuracy requirements were evaluated for head and neck IMRT when function of the major salivary glands is intended to be spared. These criteria are based on the dose response obtained for the glands. Random measurement errors could be reduced enabling lowering of action levels and prolongation of measurement time interval from 1 month to even 6 months simultaneously maintaining dose accuracy. The combined effect of the proposed methods, suggestions and criteria was found to facilitate the avoidance of maximal dose errors of up to even about 8 %. In addition, their use may make the strictest recommended overall dose accuracy level of 3 % (1SD) achievable.
Resumo:
This research explored the feasibility of using multidimensional scaling (MDS) analysis in novel combination with other techniques to study comprehension of epistemic adverbs expressing doubt and certainty (e.g., evidently, obviously, probably) as they relate to health communication in clinical settings. In Study 1, Australian English speakers performed a dissimilarity-rating task with sentence pairs containing the target stimuli, presented as "doctors' opinions". Ratings were analyzed using a combination of cultural consensus analysis (factor analysis across participants), weighted-data classical-MDS, and cluster analysis. Analyses revealed strong within-community consistency for a 3-dimensional semantic space solution that took into account individual differences, strong statistical acceptability of the MDS results in terms of stress and explained variance, and semantic configurations that were interpretable in terms of linguistic analyses of the target adverbs. The results confirmed the feasibility of using MDS in this context. Study 2 replicated the results with Canadian English speakers on the same task. Semantic analyses and stress decomposition analysis were performed on the Australian and Canadian data sets, revealing similarities and differences between the two groups. Overall, the results support using MDS to study comprehension of words critical for health communication, including in future studies, for example, second language speaking patients and/or practitioners. More broadly, the results indicate that the techniques described should be promising for comprehension studies in many communicative domains, in both clinical settings and beyond, and including those targeting other aspects of language and focusing on comparisons across different speech communities.
Resumo:
Computational modelling of mechanisms underlying processes in the real world can be of great value in understanding complex biological behaviours. Uptake in general biology and ecology has been rapid. However, it often requires specific data sets that are overly costly in time and resources to collect. The aim of the current study was to test whether a generic behavioural ecology model constructed using published data could give realistic outputs for individual species. An individual-based model was developed using the Pattern-Oriented Modelling (POM) strategy and protocol, based on behavioural rules associated with insect movement choices. Frugivorous Tephritidae (fruit flies) were chosen because of economic significance in global agriculture and the multiple published data sets available for a range of species. The Queensland fruit fly (Qfly), Bactrocera tryoni, was identified as a suitable individual species for testing. Plant canopies with modified architecture were used to run predictive simulations. A field study was then conducted to validate our model predictions on how plant architecture affects fruit flies’ behaviours. Characteristics of plant architecture such as different shapes, e.g., closed-canopy and vase-shaped, affected fly movement patterns and time spent on host fruit. The number of visits to host fruit also differed between the edge and centre in closed-canopy plants. Compared to plant architecture, host fruit has less contribution to effects on flies’ movement patterns. The results from this model, combined with our field study and published empirical data suggest that placing fly traps in the upper canopy at the edge should work best. Such a modelling approach allows rapid testing of ideas about organismal interactions with environmental substrates in silico rather than in vivo, to generate new perspectives. Using published data provides a saving in time and resources. Adjustments for specific questions can be achieved by refinement of parameters based on targeted experiments.
Resumo:
ABSTRACT Sense of coherence (SOC) is a core concept within Antonovsky s salutogenic theory and is argued to be a psychological determinant of health. The present social-epidemiological study explores the associations between a wide range of generalized resistance resources of SOC among Finnish- and Swedish-speaking women and men with a view to gaining deeper insight into its developmental circumstances and determinants. Secondly, a five-year follow-up study was conducted in order to assess the stability of SOC in difficult life events. Finally the role and effect of SOC in the intentions to retire early was investigated in a prospective study. The above studies were based on two data sets: the Finnish 'Survey on Living Conditions' (ELO-94) conducted in 1994 by means of personal face-to-face interviews (N=6506), and a prospective postal survey of the 15-year Health and Social Support (HeSSup) study for which the baseline data was collected in 1998 (N=25 898) and the follow-up in 2003. The present study reveals that the level of SOC in adulthood is strongly dependent on close and successful social relationships during both childhood and adulthood, and that there is a strong association with qualitative work features. Not having a partner as well as being unable to use one s skills at work proved to threaten men s SOC in particular, whereas a lack of social support did the same for women. Otherwise, the association with generalized resistance resources turned out to be quite similar in both genders. Swedish-speaking Finns appear to have a slightly stronger SOC due to the better psycho-emotional circumstances in the childhood home and work circumstances in adulthood, in other words higher levels of generalized resistance resources compared to Finnish speakers. These language group differences did not concern any social-life factors included in the present study. The results of the five-year follow-up study suggest that SOC is not stable, and that the level clearly decreases after a negative life event. Even a strong SOC decreased during the follow-up period and, furthermore, was no more stable than a mediocre or weak SOC. There seems to be a clear and independent association with the intentions to retire early among both men and women following full adjustment. Swedish speakers appear to be less inclined to retire early than Finnish speakers. In the light of the present study, it seems that SOC is determined not only by socio-economic factors but also by close and successful social relationships during both childhood and adulthood. This applied to both genders and language groups. Interventions aimed at promoting the health of the disadvantaged should therefore focus on families with children, and extend later also to other than socio-economic spheres of life. SOC theory could also be applied in efforts to inhibit early retirement: management practices aimed at providing employees with a work environment and tasks that are comprehensible, manageable and meaningful could potentially decrease the intentions to retire early.
Resumo:
A popular dynamic imaging technique, k-t BLAST (ktB) is studied here for BAR imaging. ktB utilizes correlations in k-space and time, to reconstruct the image time series with only a fraction of the data. The algorithm works by unwrapping the aliased Fourier conjugate space of k-t (y-f-space). The unwrapping process utilizes the estimate of the true y-f-space, by acquiring densely sampled low k-space data. The drawbacks of this method include separate training scan, blurred training estimates and aliased phase maps. The proposed changes are incorporation of phase information from the training map and using generalized-series-extrapolated training map. The proposed technique is compared with ktB on real fMRI data. The proposed changes allow for ktB to operate at an acceleration factor of 6. Performance is evaluated by comparing activation maps obtained using reconstructed images. An improvement of up to 10 dB is observed in thePSNR of activation maps. Besides, a 10% reduction in RMSE is obtained over the entire time series of fMRI images. Peak improvement of the proposed method over ktB is 35%, averaged over five data sets. (C)2010 Elsevier Inc. All rights reserved.
Resumo:
A plethora of indices have been proposed and used to construct dominance hierarchies in a variety of vertebrate and invertebrate societies, although the rationale for choosing a particular index for a particular species is seldom explained. In this study, we analysed and compared three such indices, viz Clutton-Brock et al.'s index (CBI), originally developed for red deer, Cervus elaphus, David's score (DS) originally proposed by the statistician H. A. David and the frequency-based index of dominance (FDI) developed and routinely used by our group for the primitively eusocial wasps Ropalidia marginata and Ropalidia cyathiformis. Dominance ranks attributed by all three indices were strongly and positively correlated for both natural data sets from the wasp colonies and for artificial data sets generated for the purpose. However, the indices differed in their ability to yield unique (untied) ranks in the natural data sets. This appears to be caused by the presence of noninteracting individuals and reversals in the direction of dominance in some of the pairs in the natural data sets. This was confirmed by creating additional artificial data sets with noninteracting individuals and with reversals. Based on the criterion of yielding the largest proportion of unique ranks, we found that FDI is best suited for societies such as the wasps belonging to Ropalidia, DS is best suited for societies with reversals and CBI remains a suitable index for societies such as red deer in which multiple interactions are uncommon. (C) 2009 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.
Resumo:
This study investigates how the religious community as a socialization context affects the development of young people's religious identity and values, using Finnish Seventh-day Adventism as a context for the case study. The research problem is investigated through the following questions: (1) What aspects support the intergenerational transmission of values and tradition in religious home education? (2) What is the role of social capital and the social networks of the religious community in the religious socialization process? (3) How does the religious composition of the peer group at school (e.g., a denominational school in comparison to a mainstream school) affect these young people s social relations and choices and their religious identity (as challenged versus as reinforced by values at school)? And (4) How do the young people studied negotiate their religious values and religious membership in the diverse social contexts of the society at large? The mixed method study includes both quantitative and qualitative data sets (3 surveys: n=106 young adults, n=100 teenagers, n=55 parents; 2 sets of interviews: n=10 young adults and n=10 teenagers; and fieldwork data from youth summer camps). The results indicate that, in religious home education, the relationship between parents and children, the parental example of a personally meaningful way of life, and encouraging critical thinking in order for young people to make personalized value choices were important factors in socialization. Overall, positive experiences of the religion and the religious community were crucial in providing direction for later choices of values and affiliations. Education that was experienced as either too severe or too permissive was not regarded as a positive influence for accepting similar values and lifestyle choices to those of the parents. Furthermore, the religious community had an important influence on these young people s religious socialization in terms of the commitment to denominational values and lifestyle and in providing them with religious identity and rooting them in the social network of the denomination. The network of the religious community generated important social resources, or social capital, for both the youth and their families, involving both tangible and intangible benefits, and bridging and bonding effects. However, the study also illustrates the sometimes difficult negotiations the youth face in navigating between differentiation and belonging when there is a tension between the values of a minority group and the larger society, and one wants to and does belong to both. It also demonstrates the variety within both the majority and the minority communities in society, as well as the many different ways one can find a personally meaningful way of being an Adventist. In the light of the previous literature about socialization-in-context in an increasingly pluralistic society, the findings were examined at four levels: individual, family, community and societal. These were seen as both a nested structure and as constructing a funnel in which each broader level directs the influences that reach the narrower ones. The societal setting directs the position and operation of religious communities, families and individuals, and the influences that reach the developing children and young people are in many ways directed by societal, communal and family characteristics. These levels are by nature constantly changing, as well as being constructed of different parts, like the pieces of a jigsaw puzzle, each of which alters in significance: for some negotiations on values and memberships the parental influence may be greater, whereas for others the peer group influences are. Although agency does remain somewhat connected to others, the growing youth are gradually able to take more responsibility for their own choices and their agency plays a crucial role in the process of choosing values and group memberships. Keywords: youth, community, Adventism, socialization, values, identity negotiations
Resumo:
The increased availability of high frequency data sets have led to important new insights in understanding of financial markets. The use of high frequency data is interesting and persuasive, since it can reveal new information that cannot be seen in lower data aggregation. This dissertation explores some of the many important issues connected with the use, analysis and application of high frequency data. These include the effects of intraday seasonal, the behaviour of time varying volatility, the information content of various market data, and the issue of inter market linkages utilizing high frequency 5 minute observations from major European and the U.S stock indices, namely DAX30 of Germany, CAC40 of France, SMI of Switzerland, FTSE100 of the UK and SP500 of the U.S. The first essay in the dissertation shows that there are remarkable similarities in the intraday behaviour of conditional volatility across European equity markets. Moreover, the U.S macroeconomic news announcements have significant cross border effect on both, European equity returns and volatilities. The second essay reports substantial intraday return and volatility linkages across European stock indices of the UK and Germany. This relationship appears virtually unchanged by the presence or absence of the U.S stock market. However, the return correlation among the U.K and German markets rises significantly following the U.S stock market opening, which could largely be described as a contemporaneous effect. The third essay sheds light on market microstructure issues in which traders and market makers learn from watching market data, and it is this learning process that leads to price adjustments. This study concludes that trading volume plays an important role in explaining international return and volatility transmissions. The examination concerning asymmetry reveals that the impact of the positive volume changes is larger on foreign stock market volatility than the negative changes. The fourth and the final essay documents number of regularities in the pattern of intraday return volatility, trading volume and bid-ask spreads. This study also reports a contemporaneous and positive relationship between the intraday return volatility, bid ask spread and unexpected trading volume. These results verify the role of trading volume and bid ask quotes as proxies for information arrival in producing contemporaneous and subsequent intraday return volatility. Moreover, asymmetric effect of trading volume on conditional volatility is also confirmed. Overall, this dissertation explores the role of information in explaining the intraday return and volatility dynamics in international stock markets. The process through which the information is incorporated in stock prices is central to all information-based models. The intraday data facilitates the investigation that how information gets incorporated into security prices as a result of the trading behavior of informed and uninformed traders. Thus high frequency data appears critical in enhancing our understanding of intraday behavior of various stock markets’ variables as it has important implications for market participants, regulators and academic researchers.
Resumo:
This paper aims at evaluating the methods of multiclass support vector machines (SVMs) for effective use in distance relay coordination. Also, it describes a strategy of supportive systems to aid the conventional protection philosophy in combating situations where protection systems have maloperated and/or information is missing and provide selective and secure coordinations. SVMs have considerable potential as zone classifiers of distance relay coordination. This typically requires a multiclass SVM classifier to effectively analyze/build the underlying concept between reach of different zones and the apparent impedance trajectory during fault. Several methods have been proposed for multiclass classification where typically several binary SVM classifiers are combined together. Some authors have extended binary SVM classification to one-step single optimization operation considering all classes at once. In this paper, one-step multiclass classification, one-against-all, and one-against-one multiclass methods are compared for their performance with respect to accuracy, number of iterations, number of support vectors, training, and testing time. The performance analysis of these three methods is presented on three data sets belonging to training and testing patterns of three supportive systems for a region and part of a network, which is an equivalent 526-bus system of the practical Indian Western grid.
Resumo:
In the thesis we consider inference for cointegration in vector autoregressive (VAR) models. The thesis consists of an introduction and four papers. The first paper proposes a new test for cointegration in VAR models that is directly based on the eigenvalues of the least squares (LS) estimate of the autoregressive matrix. In the second paper we compare a small sample correction for the likelihood ratio (LR) test of cointegrating rank and the bootstrap. The simulation experiments show that the bootstrap works very well in practice and dominates the correction factor. The tests are applied to international stock prices data, and the .nite sample performance of the tests are investigated by simulating the data. The third paper studies the demand for money in Sweden 1970—2000 using the I(2) model. In the fourth paper we re-examine the evidence of cointegration between international stock prices. The paper shows that some of the previous empirical results can be explained by the small-sample bias and size distortion of Johansen’s LR tests for cointegration. In all papers we work with two data sets. The first data set is a Swedish money demand data set with observations on the money stock, the consumer price index, gross domestic product (GDP), the short-term interest rate and the long-term interest rate. The data are quarterly and the sample period is 1970(1)—2000(1). The second data set consists of month-end stock market index observations for Finland, France, Germany, Sweden, the United Kingdom and the United States from 1980(1) to 1997(2). Both data sets are typical of the sample sizes encountered in economic data, and the applications illustrate the usefulness of the models and tests discussed in the thesis.
Resumo:
Whilst previous research on Human Resource Management (HRM) in subsidiaries of multinational companies (MNCs) has focused extensively on the HRM practices that exist in foreign subsidiaries and the extent to which they resemble MNC home country and/or local host country practices, considerably less attention has been directed at the question of how these practices come to exist. Accordingly, this thesis aims to shed light on the processes that shape HRM practices and capabilities in MNC subsidiaries. The main contribution of the thesis is the focus on how; how HRM practices are integrated in MNC subsidiaries, and how subsidiary HRM capabilities are developed through involvement in social networks. Furthermore, this thesis includes a time aspect which, despite not being purely longitudinal, provides an indication of the ongoing changes in HRM in MNC subsidiaries in China. Data for this study were collected in 2005-2006 through structured face to face interviews with 153 general managers and HR managers in 87 subsidiaries of European MNCs located in China. Five of the six thesis papers build on this questionnaire data and one paper builds on qualitative data collected at the same time. Two papers build on dual data sets, meaning that they in addition to the abovementioned data include quantitative questionnaire data from 1996 and 1999 respectively. The thesis focuses on the following four sub-questions i) To what extent do subsidiary HRM practices resemble parent MNC and host country practices? How has this changed over time and why? ii) How are HRM practices integrated into MNC subsidiaries and why are certain integration mechanisms used? iii) How does involvement in internal and external social networks influence subsidiary HRM capabilities? iv) What factors influence the strategic role of the subsidiary HR department? Regarding the first sub-question the findings indicate that the HRM practices of MNC subsidiaries in China are converging with both local company practices and parent MNC practices. This is interesting in the sense that it suggests that the isomorphic pressures the subsidiary faces from the MNC and from its local host environment are not always in conflict with each other. Concerning the question of how HRM practices are integrated into MNC subsidiaries and why certain integration mechanisms are used, the thesis provides a fine-grained examination of four mechanisms that MNCs use to integrate HRM practices in subsidiaries. The findings suggest that MNCs use a variety of different integration mechanisms as complements rather than as substitutes for each other. Furthermore, it is apparent that different contextual factors in the subsidiary and the subsidiary-headquarters relationship influence why certain mechanisms are or are not used. The most interesting contribution of the thesis in regard to the third question is that it highlights the importance of network involvement for learning about HRM practices in the Chinese context. Networks with other MNCs in China clearly emerged as particularly important contributors to enhanced HRM capabilities. Finally, concerning the fourth sub-question the findings indicate that the role of the HR department in MNC subsidiaries in China had become more strategic between 1999 and 2006.
Resumo:
Core Vector Machine(CVM) is suitable for efficient large-scale pattern classification. In this paper, a method for improving the performance of CVM with Gaussian kernel function irrespective of the orderings of patterns belonging to different classes within the data set is proposed. This method employs a selective sampling based training of CVM using a novel kernel based scalable hierarchical clustering algorithm. Empirical studies made on synthetic and real world data sets show that the proposed strategy performs well on large data sets.