420 resultados para Goodness
Resumo:
Aerial surveys of kangaroos (Macropus spp.) in Queensland are used to make economically important judgements on the levels of viable commercial harvest. Previous analysis methods for aerial kangaroo surveys have used both mark-recapture methodologies and conventional distance-sampling analyses. Conventional distance sampling has the disadvantage that detection is assumed to be perfect on the transect line, while mark-recapture methods are notoriously sensitive to problems with unmodelled heterogeneity in capture probabilities. We introduce three methodologies for combining together mark-recapture and distance-sampling data, aimed at exploiting the strengths of both methodologies and overcoming the weaknesses. Of these methods, two are based on the assumption of full independence between observers in the mark-recapture component, and this appears to introduce more bias in density estimation than it resolves through allowing uncertain trackline detection. Both of these methods give lower density estimates than conventional distance sampling, indicating a clear failure of the independence assumption. The third method, termed point independence, appears to perform very well, giving credible density estimates and good properties in terms of goodness-of-fit and percentage coefficient of variation. Estimated densities of eastern grey kangaroos range from 21 to 36 individuals km-2, with estimated coefficients of variation between 11% and 14% and estimated trackline detection probabilities primarily between 0.7 and 0.9.
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Objectives. The sentence span task is a complex working memory span task used for estimating total working memory capacity for both processing (sentence comprehension) and storage (remembering a set of words). Several traditional models of working memory suggest that performance on these tasks relies on phonological short-term storage. However, long-term memory effects as well as the effects of expertise and strategies have challenged this view. This study uses a working memory task that aids the creation of retrieval structures in the form of stories, which have been shown to form integrated structures in longterm memory. The research question is whether sentence and story contexts boost memory performance in a complex working memory task. The hypothesis is that storage of the words in the task takes place in long-term memory. Evidence of this would be better recall for words as parts of sentences than for separate words, and, particularly, a beneficial effect for words as part of an organized story. Methods. Twenty stories consisting of five sentences each were constructed, and the stimuli in all experimental conditions were based on these sentences and sentence-final words, reordered and recombined for the other conditions. Participants read aloud sets of five sentences that either formed a story or not. In one condition they had to report all the last words at the end of the set, in another, they memorised an additional separate word with each sentence. The sentences were presented on the screen one word at a time (500 ms). After the presentation of each sentence, the participant verified a statement about the sentence. After five sentences, the participant repeated back the words in correct positions. Experiment 1 (n=16) used immediate recall, experiment 2 (n=21) both immediate recall and recall after a distraction interval (the operation span task). In experiment 2 a distracting mental arithmetic task was presented instead of recall in half of the trials, and an individual word was added before each sentence in the two experimental conditions when the participants were to memorize the sentence final words. Subjects also performed a listening span task (in exp.1) or an operation span task (exp.2) to allow comparison of the estimated span and performance in the story task. Results were analysed using correlations, repeated measures ANOVA and a chi-square goodness of fit test on the distribution of errors. Results and discussion. Both the relatedness of the sentences (the story condition) and the inclusion of the words into sentences helped memory. An interaction showed that the story condition had a greater effect on last words than separate words. The beneficial effect of the story was shown in all serial positions. The effects remained in delayed recall. When the sentences formed stories, performance in verification of the statements about sentence context was better. This, as well as the differing distributions of errors in different experimental conditions, suggest different levels of representation are in use in the different conditions. In the story condition, the nature of these representations could be in the form of an organized memory structure, a situation model. The other working memory tasks had only few week correlations to the story task. This could indicate that different processes are in use in the tasks. The results do not support short-term phonological storage, but instead are compatible with the words being encoded to LTM during the task.
Design and testing of stand-specific bucking instructions for use on modern cut-to-length harvesters
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This study addresses three important issues in tree bucking optimization in the context of cut-to-length harvesting. (1) Would the fit between the log demand and log output distributions be better if the price and/or demand matrices controlling the bucking decisions on modern cut-to-length harvesters were adjusted to the unique conditions of each individual stand? (2) In what ways can we generate stand and product specific price and demand matrices? (3) What alternatives do we have to measure the fit between the log demand and log output distributions, and what would be an ideal goodness-of-fit measure? Three iterative search systems were developed for seeking stand-specific price and demand matrix sets: (1) A fuzzy logic control system for calibrating the price matrix of one log product for one stand at a time (the stand-level one-product approach); (2) a genetic algorithm system for adjusting the price matrices of one log product in parallel for several stands (the forest-level one-product approach); and (3) a genetic algorithm system for dividing the overall demand matrix of each of the several log products into stand-specific sub-demands simultaneously for several stands and products (the forest-level multi-product approach). The stem material used for testing the performance of the stand-specific price and demand matrices against that of the reference matrices was comprised of 9 155 Norway spruce (Picea abies (L.) Karst.) sawlog stems gathered by harvesters from 15 mature spruce-dominated stands in southern Finland. The reference price and demand matrices were either direct copies or slightly modified versions of those used by two Finnish sawmilling companies. Two types of stand-specific bucking matrices were compiled for each log product. One was from the harvester-collected stem profiles and the other was from the pre-harvest inventory data. Four goodness-of-fit measures were analyzed for their appropriateness in determining the similarity between the log demand and log output distributions: (1) the apportionment degree (index), (2) the chi-square statistic, (3) Laspeyres quantity index, and (4) the price-weighted apportionment degree. The study confirmed that any improvement in the fit between the log demand and log output distributions can only be realized at the expense of log volumes produced. Stand-level pre-control of price matrices was found to be advantageous, provided the control is done with perfect stem data. Forest-level pre-control of price matrices resulted in no improvement in the cumulative apportionment degree. Cutting stands under the control of stand-specific demand matrices yielded a better total fit between the demand and output matrices at the forest level than was obtained by cutting each stand with non-stand-specific reference matrices. The theoretical and experimental analyses suggest that none of the three alternative goodness-of-fit measures clearly outperforms the traditional apportionment degree measure. Keywords: harvesting, tree bucking optimization, simulation, fuzzy control, genetic algorithms, goodness-of-fit
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The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.
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Sampling design is critical to the quality of quantitative research, yet it does not always receive appropriate attention in nursing research. The current article details how balancing probability techniques with practical considerations produced a representative sample of Australian nursing homes (NHs). Budgetary, logistical, and statistical constraints were managed by excluding some NHs (e.g., those too difficult to access) from the sampling frame; a stratified, random sampling methodology yielded a final sample of 53 NHs from a population of 2,774. In testing the adequacy of representation of the study population, chi-square tests for goodness of fit generated nonsignificant results for distribution by distance from major city and type of organization. A significant result for state/territory was expected and was easily corrected for by the application of weights. The current article provides recommendations for conducting high-quality, probability-based samples and stresses the importance of testing the representativeness of achieved samples.
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This doctoral dissertation introduces an algorithm for constructing the most probable Bayesian network from data for small domains. The algorithm is used to show that a popular goodness criterion for the Bayesian networks has a severe sensitivity problem. The dissertation then proposes an information theoretic criterion that avoids the problem.
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The material I analyze for my master's thesis is a teaching manual used by the Mormons (the Church of Jesus Christ of Latter-day Saints), called "Duties and Blessings of the Priesthood". This work includes numerous lesson plans, each one with a separate topic. The manual is intended especially for teaches, but can also be used for individual study. The main target of my research is to find out how men and their bodies are constructed in the manual. Prescriptive texts together with narrative stories and illustrations create a multifaceted picture of Mormon notions of masculinity and corporeality. I approach my research material from a constructivist perspective. I build my interpretative reading upon Critical Discourse Analysis. I am especially interested in how the manual interprets and understands connections between gender, embodiment and religion. I understand gender in Judith Butler's terms, as a performance of styled and repeated gestures. Some of the discussions I raise in my work draw upon the disciplines of Critical Men's Studies and Sociology of Religion. In Mormonism, gender is thought to be an elementary part of human ontology. It is an eternal trait inherited from God the Father (and God the Mother). The place of men in Mormon cosmology is determined by their double role as patriarchs, fathers and priests. The main objective of mortal life is to gain salvation together with one's family. The personal goal of a Mormon man is to one day become a god. Patriarchs are responsible for the spiritual and material well-being of their family. The head of a household should be gentle and loving, but still an unconditional authority. In the manual, a Mormon man is depicted as a successor of mythical and exemplary men of sacred history. The perfect and sinless body of Jesus Christ serves as an ideal for the male body. Mormon masculinity is also defined by priesthood - the holy power of God - which is given to practically all male Mormons. Through the priesthood, a Mormon man serves as the governor of God on Earth. The Mormon priest has the authority to bind the immanent and the transcendent worlds together with gestures, poses and motions performed with his body. In Mormonism, the body also symbolizes a temple or a space where the sacred meets the profane. Because the priesthood borne by a man is holy, he has to treat his body accordingly. The body is valuable in itself, without it one cannot be saved. Men are forbidden of polluting their bodies by using stimulants or by having sexual relations out of wedlock. A priesthood holder must uphold healthy habits, dress neatly, and conduct himself in a temperate manner. He must also be outgoing and attentive. The manual suggests that a man's goodness or wickedness can be perceived from his external appearance. The Church of Jesus Christ of Latter-day Saints is a hierarchical and man-led organisation. The ideals of gender and corporeality are set by a homogenous priesthood leadership that consists mainly of white heterosexual American men. The larger Mormon community can control individual men by sanctioning. Growing as a Mormon man happens under the guidance of one's reference group.
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While many measures of viewpoint goodness have been proposed in computer graphics, none have been evaluated for ribbon representations of protein secondary structure. To fill this gap, we conducted a user study on Amazon’s Mechanical Turk platform, collecting human viewpoint preferences from 65 participants for 4 representative su- perfamilies of protein domains. In particular, we evaluated viewpoint entropy, which was previously shown to be a good predictor for human viewpoint preference of other, mostly non-abstract objects. In a second study, we asked 7 molecular biology experts to find the best viewpoint of the same protein domains and compared their choices with viewpoint entropy. Our results show that viewpoint entropy overall is a significant predictor of human viewpoint preference for ribbon representations of protein secondary structure. However, the accuracy is highly dependent on the complexity of the structure: while most participants agree on good viewpoints for small, non-globular structures with few secondary structure elements, viewpoint preference varies considerably for complex structures. Finally, experts tend to choose viewpoints of both low and high viewpoint entropy to emphasize different aspects of the respective structure.
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This thesis studies binary time series models and their applications in empirical macroeconomics and finance. In addition to previously suggested models, new dynamic extensions are proposed to the static probit model commonly used in the previous literature. In particular, we are interested in probit models with an autoregressive model structure. In Chapter 2, the main objective is to compare the predictive performance of the static and dynamic probit models in forecasting the U.S. and German business cycle recession periods. Financial variables, such as interest rates and stock market returns, are used as predictive variables. The empirical results suggest that the recession periods are predictable and dynamic probit models, especially models with the autoregressive structure, outperform the static model. Chapter 3 proposes a Lagrange Multiplier (LM) test for the usefulness of the autoregressive structure of the probit model. The finite sample properties of the LM test are considered with simulation experiments. Results indicate that the two alternative LM test statistics have reasonable size and power in large samples. In small samples, a parametric bootstrap method is suggested to obtain approximately correct size. In Chapter 4, the predictive power of dynamic probit models in predicting the direction of stock market returns are examined. The novel idea is to use recession forecast (see Chapter 2) as a predictor of the stock return sign. The evidence suggests that the signs of the U.S. excess stock returns over the risk-free return are predictable both in and out of sample. The new "error correction" probit model yields the best forecasts and it also outperforms other predictive models, such as ARMAX models, in terms of statistical and economic goodness-of-fit measures. Chapter 5 generalizes the analysis of univariate models considered in Chapters 2 4 to the case of a bivariate model. A new bivariate autoregressive probit model is applied to predict the current state of the U.S. business cycle and growth rate cycle periods. Evidence of predictability of both cycle indicators is obtained and the bivariate model is found to outperform the univariate models in terms of predictive power.
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In this paper we present a novel algorithm for learning oblique decision trees. Most of the current decision tree algorithms rely on impurity measures to assess goodness of hyperplanes at each node. These impurity measures do not properly capture the geometric structures in the data. Motivated by this, our algorithm uses a strategy, based on some recent variants of SVM, to assess the hyperplanes in such a way that the geometric structure in the data is taken into account. We show through empirical studies that our method is effective.
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The aim of the study is to examine Luther s theology of music from the standpoint of pleasure. The theological assessment of musical pleasure is related to two further questions: the role of emotions in Christianity and the apprehension of beauty. The medieval discussion of these themes is portrayed in the background chapter. Significant traits were: the suspicion felt towards sensuous gratification in music, music as a mathematical discipline, the medieval theory of emotions informed by Stoic apatheia and Platonic-Aristotelian metriopatheia, the notion of beauty as an attribute of God, medieval aesthetics as the aesthetic of proportion and the aesthetic of light and the emergence of the Aristotelian view of science that is based on experience rather than speculation. The treatment of Luther s theology of music is initiated with the notion of gift. Luther says that music is the excellent (or even the best) gift of God. This has sometimes been understood as a mere music-lover s enthusiasm. Luther is, however, not likely to use the word gift loosely. His theology can be depicted as a theology of gift. The Triune God is categorically giving. The notion of gift also includes reciprocity. When we receive the gifts of God, it evokes praise in us. Praising God is predominantly a musical phenomenon. The particular benefit of music in Luther s thought is that it can move human emotions. This emphasis is connected to the overall affectivity of Luther s theology. In contrast to the medieval discussion, Luther ascribes to saints not just emotions but particularly warm and tender affections. The power of music is related to the auditory and vocal character of the Word. Faith comes through hearing the Word that is at once musical and affective perception. Faith is not a mere opinion but the affective trust of the heart. Music can touch the human heart and persuade with its sweetness, like the good news of the Gospel. Music allows us to perceive Luther s theology as a theology of joy and pleasure. Joy is for Luther a gift of the Holy Spirit that fills the heart and bursts out in voice and gestures. Pleasure appears to be a central aspect to Luther s theology. The problem of the Bondage of the Will is precisely the human inability to feel pleasure in God s will. To be pleased in the visible and tangible creation is not something a Christian should avoid. On the contrary, if one is not pleased with the world that God has created, it is a sign of unbelief and ingratitude. The pleasure of music is aesthetic perception. This in turn necessitates the investigation of Luther s aesthetics. Aesthetic evaluation is not just a part of Luther s thought. Eventually his theology as a whole could be portrayed in aesthetic terms. Luther s extremely positive appreciation of music illutrates his theology as an affective acknowledgement of the goodness of the Creation and faith as an aesthetic contentment.
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Lahopuun määrästä ja sijoittumisesta ollaan kiinnostuneita paitsi elinympäristöjen monimuotoisuuden, myös ilmakehän hiilen varastoinnin kannalta. Tutkimuksen tavoitteena oli kehittää aluepohjainen laserkeilausdataa hyödyntävä malli lahopuukohteiden paikantamiseksi ja lahopuun määrän estimoimiseksi. Samalla tutkittiin mallin selityskyvyn muuttumista mallinnettavan ruudun kokoa suurennettaessa. Tutkimusalue sijaitsi Itä-Suomessa Sonkajärvellä ja koostui pääasiassa nuorista hoidetuista talousmetsistä. Tutkimuksessa käytettiin harvapulssista laserkeilausdataa sekä kaistoittain mitattua maastodataa kuolleesta puuaineksesta. Aineisto jaettiin siten, että neljäsosa datasta oli käytössä mallinnusta varten ja loput varattiin valmiiden mallien testaamiseen. Lahopuun mallintamisessa käytettiin sekä parametrista että ei-parametrista mallinnusmenetelmää. Logistisen regression avulla erikokoisille (0,04, 0,20, 0,32, 0,52 ja 1,00 ha) ruuduille ennustettiin todennäköisyys lahopuun esiintymiselle. Muodostettujen mallien selittävät muuttujat valittiin 80 laserpiirteen ja näiden muunnoksien joukosta. Mallien selittävät muuttujat valittiin kolmessa vaiheessa. Aluksi muuttujia tarkasteltiin visuaalisesti kuvaamalla ne lahopuumäärän suhteen. Ensimmäisessä vaiheessa sopivimmiksi arvioitujen muuttujien selityskykyä testattiin mallinnuksen toisessa vaiheessa yhden muuttujan mallien avulla. Lopullisessa usean muuttujan mallissa selittävien muuttujien kriteerinä oli tilastollinen merkitsevyys 5 % riskitasolla. 0,20 hehtaarin ruutukoolle luotu malli parametrisoitiin muun kokoisille ruuduille. Logistisella regressiolla toteutetun parametrisen mallintamisen lisäksi, 0,04 ja 1,0 hehtaarin ruutukokojen aineistot luokiteltiin ei-parametrisen CART-mallinnuksen (Classification and Regression Trees) avulla. CARTmenetelmällä etsittiin aineistosta vaikeasti havaittavia epälineaarisia riippuvuuksia laserpiirteiden ja lahopuumäärän välillä. CART-luokittelu tehtiin sekä lahopuustoisuuden että lahopuutilavuuden suhteen. CART-luokituksella päästiin logistista regressiota parempiin tuloksiin ruutujen luokituksessa lahopuustoisuuden suhteen. Logistisella mallilla tehty luokitus parani ruutukoon suurentuessa 0,04 ha:sta(kappa 0,19) 0,32 ha:iin asti (kappa 0,38). 0,52 ha:n ruutukoolla luokituksen kappa-arvo kääntyi laskuun (kappa 0,32) ja laski edelleen hehtaarin ruutukokoon saakka (kappa 0,26). CART-luokitus parani ruutukoon kasvaessa. Luokitustulokset olivat logistista mallinnusta parempia sekä 0,04 ha:n (kappa 0,24) että 1,0 ha:n (kappa 0,52) ruutukoolla. CART-malleilla määritettyjen ruutukohtaisten lahopuutilavuuksien suhteellinen RMSE pieneni ruutukoon kasvaessa. 0,04 hehtaarin ruutukoolla koko aineiston lahopuumäärän suhteellinen RMSE oli 197,1 %, kun hehtaarin ruutukoolla vastaava luku oli 120,3 %. Tämän tutkimuksen tulosten perusteella voidaan todeta, että maastossa mitatun lahopuumäärän ja tutkimuksessa käytettyjen laserpiirteiden yhteys on pienellä ruutukoolla hyvin heikko, mutta vahvistuu hieman ruutukoon kasvaessa. Kun mallinnuksessa käytetty ruutukoko kasvaa, pienialaisten lahopuukeskittymien havaitseminen kuitenkin vaikeutuu. Tutkimuksessa kohteen lahopuustoisuus pystyttiin kartoittamaan kohtuullisesti suurella ruutukoolla, mutta pienialaisten kohteiden kartoittaminen ei onnistunut käytetyillä menetelmillä. Pienialaisten kohteiden paikantaminen laserkeilauksen avulla edellyttää jatkotutkimusta erityisesti tiheäpulssisen laserdatan käytöstä lahopuuinventoinneissa.
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An attempt is made in this paper to arrive at a methodology for generating building technologies appropriate to rural housing. An evaluation of traditional modern' technologies currently in use reveals the need for alternatives. The lacunae in the presently available technologies also lead to a definition of rural housing needs. It is emphasised that contending technologies must establish a 'goodness of fit' between the house form and the pattern of needs. A systems viewpoint which looks at the dynamic process of building construction and the static structure of the building is then suggested as a means to match the technologies to the needs. The process viewpoint emphasises the role of building materials production and transportation in achieving desired building performances. A couple of examples of technological alternatives like the compacted soil block and the polythene-stabilised soil roof covering are then discussed. The static structural system viewpoint is then studied to arrive at methodologies of cost reduction. An illustrative analysis is carried out using the dynamic programming technique, to arrive at combinations of alternatives for the building components which lead to cost reduction. Some of the technological options are then evaluated against the need patterns. Finally, a guideline for developments in building technology is suggested
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In this paper, we shed light on the cross-layer interactions between the PHY, link and routing layers in networks with MIMO links operating in the diversity mode. Many previous studies assume an overly simplistic PHY layer model that does not sufficiently capture these interactions. We show that the use of simplistic models can in fact lead to misleading conclusions with regards to the higher layer performance with MIMO diversity. Towards understanding the impact of various PHY layer features on MIMO diversity, we begin with a simple but widely-used model and progressively incorporate these features to create new models. We examine the goodness of these models by comparing the simulated performance results with each, with measurements on an indoor 802.11 n testbed. Our work reveals several interesting cross-layer dependencies that affect the gains due to MIMO diversity. In particular, we observe that relative to SISO links: (a) PHY layer gains due to MIMO diversity do not always carry over to the higher layers, (b) the use of other PHY layer features such as FEC codes significantly influence the gains due to MIMO diversity, and (c) the choice of the routing metric can impact the gains possible with MIMO.
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In this paper, we present a new algorithm for learning oblique decision trees. Most of the current decision tree algorithms rely on impurity measures to assess the goodness of hyperplanes at each node while learning a decision tree in top-down fashion. These impurity measures do not properly capture the geometric structures in the data. Motivated by this, our algorithm uses a strategy for assessing the hyperplanes in such a way that the geometric structure in the data is taken into account. At each node of the decision tree, we find the clustering hyperplanes for both the classes and use their angle bisectors as the split rule at that node. We show through empirical studies that this idea leads to small decision trees and better performance. We also present some analysis to show that the angle bisectors of clustering hyperplanes that we use as the split rules at each node are solutions of an interesting optimization problem and hence argue that this is a principled method of learning a decision tree.