912 resultados para Bias-Variance Trade-off
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In this paper we present a novel mechanism for the protection of dynamic itineraries for mobile agent applications. Itineraries that are decided as the agent goes are essential in complex applications based on mobile agents, but no approach has been presented until now to protect them. We have conceived a cryptographic scheme for shielding dynamic itineraries from tampering, impersonation and disclosure. By using trust strategically, our scheme provides a balanced trade-off between flexibility and security. Our protection scheme has been thought always bearing in mind a feasible implementation, and thus facilitates the development of applications that make use of it. An example application based on a real healthcare scenario is also presented to show its operation.
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Aims: In perennial species, the allocation of resources to reproduction results in a reduction of allocation to vegetative growth and, therefore, impacts future reproductive success. As a consequence, variation in this trade-off is among the most important driving forces in the life-history evolution of perennial plants and can lead to locally adapted genotypes. In addition to genetic variation, phenotypic plasticity might also contribute to local adaptation of plants to local conditions by mediating changes in reproductive allocation. Knowledge on the importance of genetic and environmental effects on the trade-off between reproduction and vegetative growth is therefore essential to understand how plants may respond to environmental changes. Methods: We conducted a transplant experiment along an altitudinal gradient from 425 m to 1921 m in the front range of the Western Alps of Switzerland to assess the influence of both altitudinal origin of populations and altitude of growing site on growth, reproductive investment and local adaptation in Poa alpina. Important findings: In our study, the investment in reproduction increased with plant size. Plant growth and the relative importance of reproductive investment decreased in populations originating from higher altitudes compared to populations originating from lower altitudes. The changes in reproductive investment were mainly explained by differences in plant size. In contrast to genetic effects, phenotypic plasticity of all traits measured was low and not related to altitude. As a result, the population from the lowest altitude of origin performed best at all sites. Our results indicate that in P. alpina genetic differences in growth and reproductive investment are related to local conditions affecting growth, i.e. interspecific competition and soil moisture content.
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This paper studies fiscal federalism when regions differ in voters' ability to monitor publicofficials. We develop a model of political agency in which rent-seeking politicians providepublic goods to win support from heterogeneously informed voters. In equilibrium, voterinformation increases government accountability but displays decreasing returns. Therefore,political centralization reduces aggregate rent extraction when voter information varies acrossregions. It increases welfare as long as the central government is required to provide publicgoods uniformly across regions. The need for uniformity implies an endogenous trade off between reducing rents through centralization and matching idiosyncratic preferences throughdecentralization. We find that a federal structure with overlapping levels of government canbe optimal only if regional differences in accountability are sufficiently large. The modelpredicts that less informed regions should reap greater benefits when the central governmentsets a uniform policy. Consistent with our theory, we present empirical evidence that lessinformed states enjoyed faster declines in pollution after the 1970 Clean Air Act centralizedenvironmental policy at the federal level.
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The increasing interest aroused by more advanced forecasting techniques, together with the requirement for more accurate forecasts of tourismdemand at the destination level due to the constant growth of world tourism, has lead us to evaluate the forecasting performance of neural modelling relative to that of time seriesmethods at a regional level. Seasonality and volatility are important features of tourism data, which makes it a particularly favourable context in which to compare the forecasting performance of linear models to that of nonlinear alternative approaches. Pre-processed official statistical data of overnight stays and tourist arrivals fromall the different countries of origin to Catalonia from 2001 to 2009 is used in the study. When comparing the forecasting accuracy of the different techniques for different time horizons, autoregressive integrated moving average models outperform self-exciting threshold autoregressions and artificial neural network models, especially for shorter horizons. These results suggest that the there is a trade-off between the degree of pre-processing and the accuracy of the forecasts obtained with neural networks, which are more suitable in the presence of nonlinearity in the data. In spite of the significant differences between countries, which can be explained by different patterns of consumer behaviour,we also find that forecasts of tourist arrivals aremore accurate than forecasts of overnight stays.
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Diplomityön ensimmäisessä vaiheessa tutkittiin hydraulisen kuristimen ominaisuuksia ja esiteltiin numeerisesti tehokas kuristinmalli käyttäenpolynomifunktiota virtauksen laminaarisen ja transitioalueen kuvaukseen. Puoliempiirisen mallin paremmuus tulee esille siinä, että kuristimen geometriatietoja ei tarvita laskettaessa virtausta paine-eron perusteella. Reaaliaikasimuloinnissa esiintyy kompromisseja tarkkuuden ja laskentanopeuden välillä. Tätä asiaa tutkittiin kahden virtausalueen kuristinmallilla. Transition paine-eron ja integrointiaika-askelen valinnan vaikutus tarkkuuteen ja laskentanopeuteen tutkittiin. Toisessa vaiheessa tutkittiin mahdollisimman hyvän liiketuntuman tuottamista liikealustalla ohjaussignaalia kehittämällä. Liikealustan liikeradan rajallisuudesta johtuen ohjauksessa on perinteisesti käytetty washout-suodatusta, joka erottelee simuloitavan järjestelmän kiihtyvyyssignaalista vain nopeatkiihtyvyydet. Tässä työssä tutkittiin hitaiden kiihtyvyyksien ottamista mukaan liikealustan ohjaukseen liikealustan liikeradan puitteissa. Tämä toteutettiin kuvaamalla hitaat kiihtyvyydet kallistamalla liikealustaa, jolloin käyttäjään kohdistuva voima saatiin kuvattua gravitaatiota hyväksi käyttäen.
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Tutkielman tavoitteena on selvittää lineaarisen regressioanalyysin avulla paneelidataa käyttäen suomalaisten pörssiyritysten pääomarakenteisiin vaikuttavat tekijät vuosina 1999-2004. Näiden tekijöiden avulla päätellään, mitä pääomarakenneteoriaa/-teorioita nämä yritykset noudattavat. Pääomarakenneteoriat voidaan jakaa kahteen luokkaan sen mukaan, pyritäänkö niissä optimaaliseen pääomarakenteeseen vai ei. Tradeoff- ja siihen liittyvässä agenttiteoriassa pyritään optimaaliseen pääomarakenteeseen. Tradeoff-teoriassa pääomarakenne valitaan punnitsemalla vieraan pääoman hyötyjä ja haittoja. Agenttiteoria on muuten samanlainen kuin tradeoff-teoria, mutta siinä otetaan lisäksi huomioon velan agenttikustannukset. Pecking order - ja ajoitusteoriassa ei pyritä optimaaliseen pääoma-rakenteeseen. Pecking order -teoriassa rahoitus valitaan hierarkian mukaan (tulorahoitus, vieras pääoma, välirahoitus, oma pääoma). Ajoitusteoriassa valitaan se rahoitusmuoto, jota on kannattavinta hankkia vallitsevassa markkinatilanteessa. Empiiristen tulosten mukaan velkaantumisaste riippuu positiivisesti riskistä, vakuudesta ja aineettomasta omaisuudesta. Velkaantumisaste riippuu negatiivisesti likviditeetistä, osaketuotoista ja kannattavuudesta. Osingoilla ei ole vaikutusta velkaantumisasteeseen. Toimialoista teollisuustuotteiden ja -palveluiden sekä perusteollisuuden aloilla on korkeammat velkaantumisasteet kuin muilla toimialoilla. Tulokset tukevat pääosin pecking order -teoriaa ja jonkin verran ajoitusteoriaa. Muut teoriat saavat vain vähäistä tukea.
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Many colour ornaments are composite traits consisting of at least four components, which themselves may be more complex, determined by independent evolutionary pathways, and potentially being under different environmental control. To date, little evidence exists that several different components of colour elaboration are condition dependent and no direct evidence exists that different ornamental components are affected by different sources of variation. For example, in carotenoid-based plumage colouration, one of the best-known condition-dependent ornaments, colour elaboration stems from both condition-dependent pigment concentration and structural components. Some environmental flexibility of these components has been suggested, but specifically which and how they are affected remains unknown. Here, we tested whether multiple colour components may be condition dependent, by using a comprehensive 3 × 2 experimental design, in which we carotenoid supplemented and immune challenged great tit nestlings (Parus major) and quantified effects on different components of colouration. Plumage colouration was affected by an interaction between carotenoid availability and immune challenge. Path analyses showed that carotenoid supplementation increased plumage saturation via feather carotenoid concentration and via mechanisms unrelated to carotenoid deposition, while immune challenge affected feather length, but not carotenoid concentration. Thus, independent condition-dependent pathways, affected by different sources of variation, determine colour elaboration. This provides opportunities for the evolution of multiple signals within components of ornamental traits. This finding indicates that the selective forces shaping the evolution of different components of a composite trait and the trait's signal content may be more complex than believed so far, and that holistic approaches are required for drawing comprehensive evolutionary conclusions.
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The three essays constituting this thesis focus on financing and cash management policy. The first essay aims to shed light on why firms issue debt so conservatively. In particular, it examines the effects of shareholder and creditor protection on capital structure choices. It starts by building a contingent claims model where financing policy results from a trade-off between tax benefits, contracting costs and agency costs. In this setup, controlling shareholders can divert part of the firms' cash ows as private benefits at the expense of minority share- holders. In addition, shareholders as a class can behave strategically at the time of default leading to deviations from the absolute priority rule. The analysis demonstrates that investor protection is a first order determinant of firms' financing choices and that conflicts of interests between firm claimholders may help explain the level and cross-sectional variation of observed leverage ratios. The second essay focuses on the practical relevance of agency conflicts. De- spite the theoretical development of the literature on agency conflicts and firm policy choices, the magnitude of manager-shareholder conflicts is still an open question. This essay proposes a methodology for quantifying these agency conflicts. To do so, it examines the impact of managerial entrenchment on corporate financing decisions. It builds a dynamic contingent claims model in which managers do not act in the best interest of shareholders, but rather pursue private benefits at the expense of shareholders. Managers have discretion over financing and dividend policies. However, shareholders can remove the manager at a cost. The analysis demonstrates that entrenched managers restructure less frequently and issue less debt than optimal for shareholders. I take the model to the data and use observed financing choices to provide firm-specific estimates of the degree of managerial entrenchment. Using structural econometrics, I find costs of control challenges of 2-7% on average (.8-5% at median). The estimates of the agency costs vary with variables that one expects to determine managerial incentives. In addition, these costs are sufficient to resolve the low- and zero-leverage puzzles and explain the time series of observed leverage ratios. Finally, the analysis shows that governance mechanisms significantly affect the value of control and firms' financing decisions. The third essay is concerned with the documented time trend in corporate cash holdings by Bates, Kahle and Stulz (BKS,2003). BKS find that firms' cash holdings double from 10% to 20% over the 1980 to 2005 period. This essay provides an explanation of this phenomenon by examining the effects of product market competition on firms' cash holdings in the presence of financial constraints. It develops a real options model in which cash holdings may be used to cover unexpected operating losses and avoid inefficient closure. The model generates new predictions relating cash holdings to firm and industry characteristics such as the intensity of competition, cash flow volatility, or financing constraints. The empirical examination of the model shows strong support of model's predictions. In addition, it shows that the time trend in cash holdings documented by BKS can be at least partly attributed to a competition effect.
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El presente trabajo aborda el estudio de los factores determinantes del endeudamiento empresarial para contrastar empíricamente la hipótesis del Pecking Order. El endeudamiento empresarial se mide junto a su madurez y para los diferentes tamaños empresariales dada la importancia de diferenciar sus posibles efectos contrapuestos o compensados. Los modelos utilizados para el contraste de hipótesis se han estimado con una muestra de 1.320 empresas manufactureras españolas proporcionada por la Encuesta sobre Estrategias Empresariales (ESEE), para el período 1993-2001. El análisis empírico aplica un modelo multivariante de regresión logística que permite concluir que la teoría del Pecking Order es la de mejor cumplimiento, además de constatarse que las empresas de menor tamaño tienen mayores dificultades de acceso a la financiación con deuda a largo plazo.
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Occupational exposure modeling is widely used in the context of the E.U. regulation on the registration, evaluation, authorization, and restriction of chemicals (REACH). First tier tools, such as European Centre for Ecotoxicology and TOxicology of Chemicals (ECETOC) targeted risk assessment (TRA) or Stoffenmanager, are used to screen a wide range of substances. Those of concern are investigated further using second tier tools, e.g., Advanced REACH Tool (ART). Local sensitivity analysis (SA) methods are used here to determine dominant factors for three models commonly used within the REACH framework: ECETOC TRA v3, Stoffenmanager 4.5, and ART 1.5. Based on the results of the SA, the robustness of the models is assessed. For ECETOC, the process category (PROC) is the most important factor. A failure to identify the correct PROC has severe consequences for the exposure estimate. Stoffenmanager is the most balanced model and decision making uncertainties in one modifying factor are less severe in Stoffenmanager. ART requires a careful evaluation of the decisions in the source compartment since it constitutes ∼75% of the total exposure range, which corresponds to an exposure estimate of 20-22 orders of magnitude. Our results indicate that there is a trade off between accuracy and precision of the models. Previous studies suggested that ART may lead to more accurate results in well-documented exposure situations. However, the choice of the adequate model should ultimately be determined by the quality of the available exposure data: if the practitioner is uncertain concerning two or more decisions in the entry parameters, Stoffenmanager may be more robust than ART.
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Diplomityön tavoitteena oli erään prosessiteollisuuden yrityksen toimitusketjun kehittäminen pääasiakkaan toimitusten osalta. Ongelmana olivat epäoptimaalinen tuotannon lajinvaihto ja toimitusketjun jakelutoimintojen tehottomuus asiakkaan tilausmäärien huonon ennustettavuuden vuoksi. Työssä keskityttiin tuotannon lajinvaihto- ja jakelutoimintoihin sekä niiden kustannusten määrittämiseen toimintolaskennan avulla. Päätavoitteena oli mallintaa Excel-pohjainen työkalu, joka soveltuu tuotannon lajinvaihdon, kuljetusten ja jakeluvarastoinnin karkeasuunnitteluun tarpeiden ja kapasiteetin yhteensovittamiseksi sekä em. kustannusten määrittämiseksi. Työkalua voidaan käyttää myös analysointityökaluna simuloimalla kustannuksia eri toimintavaihtoehdoilla ja tarkastelemalla kustannusten suhdetta toisiinsa. Työkalun avulla laskettiin tuotantotiheyden, kuljetuseräkoon ja tuotantoerien lukumäärän kustannusvaikutukset. Edellytyksenä työkalun käytölle suunnittelussa ja analysoinnissa ovat viikkokohtaiset kysyntäennusteet, joiden saamiseksi ehdotetaan yhteistyön kehittämistä asiakkaan kanssa. Työkalua voidaan jatkossa käyttää myös apuna erään tietojärjestelmän syöttötietojen määrittelyssä.
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Many species are able to learn to associate behaviours with rewards as this gives fitness advantages in changing environments. Social interactions between population members may, however, require more cognitive abilities than simple trial-and-error learning, in particular the capacity to make accurate hypotheses about the material payoff consequences of alternative action combinations. It is unclear in this context whether natural selection necessarily favours individuals to use information about payoffs associated with nontried actions (hypothetical payoffs), as opposed to simple reinforcement of realized payoff. Here, we develop an evolutionary model in which individuals are genetically determined to use either trial-and-error learning or learning based on hypothetical reinforcements, and ask what is the evolutionarily stable learning rule under pairwise symmetric two-action stochastic repeated games played over the individual's lifetime. We analyse through stochastic approximation theory and simulations the learning dynamics on the behavioural timescale, and derive conditions where trial-and-error learning outcompetes hypothetical reinforcement learning on the evolutionary timescale. This occurs in particular under repeated cooperative interactions with the same partner. By contrast, we find that hypothetical reinforcement learners tend to be favoured under random interactions, but stable polymorphisms can also obtain where trial-and-error learners are maintained at a low frequency. We conclude that specific game structures can select for trial-and-error learning even in the absence of costs of cognition, which illustrates that cost-free increased cognition can be counterselected under social interactions.
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Genetic color polymorphism is widespread in nature. There is an increasing interest in understanding the adaptive value of heritable color variation and trade-off resolution by differently colored individuals. Melanin-based pigmentation is often associated with variation in many different life history traits. These associations have recently been suggested to be the outcome of pleiotropic effects of the melanocortin system. Although pharmacological research supports that MC1R, a gene with a major role in vertebrate pigmentation, has important immunomodulatory effects, evidence regarding pleiotropy at MC1R in natural populations is still under debate. We experimentally assessed whether MC1R-based pigmentation covaries with both inflammatory and humoral immune responses in the color polymorphic Eleonora's falcon. By means of a cross-fostering experiment, we disentangled potential genetic effects from environmental effects on the covariation between coloration and immunity. Variation in both immune responses was primarily due to genetic factors via the nestlings' MC1R-related color genotype/phenotype, although environmental effects via the color morph of the foster father also had an influence. Overall, dark nestlings had lower immune responses than pale ones. The effect of the color morph of the foster father was also high, but in the opposite direction, and nestlings raised by dark eumelanic foster fathers had higher immune responses than those raised by pale foster fathers. Although we cannot completely discard alternative explanations, our results suggest that MC1R might influence immunity in this species. Morph-specific variation in immunity as well as pathogen pressure may therefore contribute to the long-term maintenance of genetic color polymorphism in natural populations.
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Maximum entropy modeling (Maxent) is a widely used algorithm for predicting species distributions across space and time. Properly assessing the uncertainty in such predictions is non-trivial and requires validation with independent datasets. Notably, model complexity (number of model parameters) remains a major concern in relation to overfitting and, hence, transferability of Maxent models. An emerging approach is to validate the cross-temporal transferability of model predictions using paleoecological data. In this study, we assess the effect of model complexity on the performance of Maxent projections across time using two European plant species (Alnus giutinosa (L.) Gaertn. and Corylus avellana L) with an extensive late Quaternary fossil record in Spain as a study case. We fit 110 models with different levels of complexity under present time and tested model performance using AUC (area under the receiver operating characteristic curve) and AlCc (corrected Akaike Information Criterion) through the standard procedure of randomly partitioning current occurrence data. We then compared these results to an independent validation by projecting the models to mid-Holocene (6000 years before present) climatic conditions in Spain to assess their ability to predict fossil pollen presence-absence and abundance. We find that calibrating Maxent models with default settings result in the generation of overly complex models. While model performance increased with model complexity when predicting current distributions, it was higher with intermediate complexity when predicting mid-Holocene distributions. Hence, models of intermediate complexity resulted in the best trade-off to predict species distributions across time. Reliable temporal model transferability is especially relevant for forecasting species distributions under future climate change. Consequently, species-specific model tuning should be used to find the best modeling settings to control for complexity, notably with paleoecological data to independently validate model projections. For cross-temporal projections of species distributions for which paleoecological data is not available, models of intermediate complexity should be selected.
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Diagnosis of community acquired legionella pneumonia (CALP) is currently performed by means of laboratory techniques which may delay diagnosis several hours. To determine whether ANN can categorize CALP and non-legionella community-acquired pneumonia (NLCAP) and be standard for use by clinicians, we prospectively studied 203 patients with community-acquired pneumonia (CAP) diagnosed by laboratory tests. Twenty one clinical and analytical variables were recorded to train a neural net with two classes (LCAP or NLCAP class). In this paper we deal with the problem of diagnosis, feature selection, and ranking of the features as a function of their classification importance, and the design of a classifier the criteria of maximizing the ROC (Receiving operating characteristics) area, which gives a good trade-off between true positives and false negatives. In order to guarantee the validity of the statistics; the train-validation-test databases were rotated by the jackknife technique, and a multistarting procedure was done in order to make the system insensitive to local maxima.