947 resultados para Link quality estimation
Resumo:
Construction of multiple sequence alignments is a fundamental task in Bioinformatics. Multiple sequence alignments are used as a prerequisite in many Bioinformatics methods, and subsequently the quality of such methods can be critically dependent on the quality of the alignment. However, automatic construction of a multiple sequence alignment for a set of remotely related sequences does not always provide biologically relevant alignments.Therefore, there is a need for an objective approach for evaluating the quality of automatically aligned sequences. The profile hidden Markov model is a powerful approach in comparative genomics. In the profile hidden Markov model, the symbol probabilities are estimated at each conserved alignment position. This can increase the dimension of parameter space and cause an overfitting problem. These two research problems are both related to conservation. We have developed statistical measures for quantifying the conservation of multiple sequence alignments. Two types of methods are considered, those identifying conserved residues in an alignment position, and those calculating positional conservation scores. The positional conservation score was exploited in a statistical prediction model for assessing the quality of multiple sequence alignments. The residue conservation score was used as part of the emission probability estimation method proposed for profile hidden Markov models. The results of the predicted alignment quality score highly correlated with the correct alignment quality scores, indicating that our method is reliable for assessing the quality of any multiple sequence alignment. The comparison of the emission probability estimation method with the maximum likelihood method showed that the number of estimated parameters in the model was dramatically decreased, while the same level of accuracy was maintained. To conclude, we have shown that conservation can be successfully used in the statistical model for alignment quality assessment and in the estimation of emission probabilities in the profile hidden Markov models.
Resumo:
During the last part of the 1990s the chance of surviving breast cancer increased. Changes in survival functions reflect a mixture of effects. Both, the introduction of adjuvant treatments and early screening with mammography played a role in the decline in mortality. Evaluating the contribution of these interventions using mathematical models requires survival functions before and after their introduction. Furthermore, required survival functions may be different by age groups and are related to disease stage at diagnosis. Sometimes detailed information is not available, as was the case for the region of Catalonia (Spain). Then one may derive the functions using information from other geographical areas. This work presents the methodology used to estimate age- and stage-specific Catalan breast cancer survival functions from scarce Catalan survival data by adapting the age- and stage-specific US functions. Methods: Cubic splines were used to smooth data and obtain continuous hazard rate functions. After, we fitted a Poisson model to derive hazard ratios. The model included time as a covariate. Then the hazard ratios were applied to US survival functions detailed by age and stage to obtain Catalan estimations. Results: We started estimating the hazard ratios for Catalonia versus the USA before and after the introduction of screening. The hazard ratios were then multiplied by the age- and stage-specific breast cancer hazard rates from the USA to obtain the Catalan hazard rates. We also compared breast cancer survival in Catalonia and the USA in two time periods, before cancer control interventions (USA 1975–79, Catalonia 1980–89) and after (USA and Catalonia 1990–2001). Survival in Catalonia in the 1980–89 period was worse than in the USA during 1975–79, but the differences disappeared in 1990–2001. Conclusion: Our results suggest that access to better treatments and quality of care contributed to large improvements in survival in Catalonia. On the other hand, we obtained detailed breast cancer survival functions that will be used for modeling the effect of screening and adjuvant treatments in Catalonia
Resumo:
Interest in analytical methods for quality control of herbal drugs has grown sharply due to the scarcity of monographs in official manuals. Thus, the aim of the present study was to evaluate analytical procedures for quantitative determination of flavonoids from leaves of Bauhinia forficata Link (pata-de-vaca). Two procedures for quantification of total flavonoids (with and without acid hydrolysis) by spectrophotometry were tested. The proposed methods proved to be specific, sensitive, precise, accurate and robust, being suitable for routine laboratory use.
Resumo:
The application of automated correlation optimized warping (ACOW) to the correction of retention time shift in the chromatographic fingerprints of Radix Puerariae thomsonii (RPT) was investigated. Twenty-seven samples were extracted from 9 batches of RPT products. The fingerprints of the 27 samples were established by the HPLC method. Because there is a retention time shift in the established fingerprints, the quality of these samples cannot be correctly evaluated by using similarity estimation and principal component analysis (PCA). Thus, the ACOW method was used to align these fingerprints. In the ACOW procedure, the warping parameters, which have a significant influence on the alignment result, were optimized by an automated algorithm. After correcting the retention time shift, the quality of these RPT samples was correctly evaluated by similarity estimation and PCA. It is demonstrated that ACOW is a practical method for aligning the chromatographic fingerprints of RPT. The combination of ACOW, similarity estimation, and PCA is shown to be a promising method for evaluating the quality of Traditional Chinese Medicine.
Resumo:
As primary objective, this thesis examines Finnair Technical Procurement’s service quality with its underlying process. As an internal unit, Technical Procurement serves as a link between external suppliers and internal customers. It is argued that external service quality requires a certain quality level within an organization. At the same time, aircraft maintenance business is subject to economic restraints. Therefore, a methodology was developed with a modified House of Quality that assists management in analyzing and evaluating Technical Procurement’s service level and connected process steps. It could be shown that qualitative and quantitative objectives do not exclude each other per se.
Resumo:
Increased emissions of greenhouse gases into the atmosphere are causing an anthropogenic climate change. The resulting global warming challenges the ability of organisms to adapt to the new temperature conditions. However, warming is not the only major threat. In marine environments, dissolution of carbon dioxide from the atmosphere causes a decrease in surface water pH, the so called ocean acidification. The temperature and acidification effects can interact, and create even larger problems for the marine flora and fauna than either of the effects would cause alone. I have used Baltic calanoid copepods (crustacean zooplankton) as my research object and studied their growth and stress responses using climate predictions projected for the next century. I have studied both direct temperature and pH effects on copepods, and indirect effects via their food: the changing phytoplankton spring bloom composition and toxic cyanobacterium. The main aims of my thesis were: 1) to find out how warming and acidification combined with a toxic cyanobacterium affect copepod reproductive success (egg production, egg viability, egg hatching success, offspring development) and oxidative balance (antioxidant capacity, oxidative damage), and 2) to reveal the possible food quality effects of spring phytoplankton bloom composition dominated by diatoms or dinoflagellates on reproducing copepods (egg production, egg hatching, RNA:DNA ratio). The two copepod genera used, Acartia sp. and Eurytemora affinis are the dominating mesozooplankton taxa (0.2 – 2 mm) in my study area the Gulf of Finland. The 20°C temperature seems to be within the tolerance limits of Acartia spp., because copepods can adapt to the temperature phenotypically by adjusting their body size. Copepods are also able to tolerate a pH decrease of 0.4 from present values, but the combination of warm water and decreased pH causes problems for them. In my studies, the copepod oxidative balance was negatively influenced by the interaction of these two environmental factors, and egg and nauplii production were lower at 20°C and lower pH, than at 20°C and ambient pH. However, presence of toxic cyanobacterium Nodularia spumigena improved the copepod oxidative balance and helped to resist the environmental stress, in question. In addition, adaptive maternal effects seem to be an important adaptation mechanism in a changing environment, but it depends on the condition of the female copepod and her diet how much she can invest in her offspring. I did not find systematic food quality difference between diatoms and dinoflagellates. There are both good and bad diatom and dinoflagellate species. Instead, the dominating species in the phytoplankton bloom composition has a central role in determining the food quality, although copepods aim at obtaining as a balanced diet as possible by foraging on several species. If the dominating species is of poor quality it can cause stress when ingested, or lead to non-optimal foraging if rejected. My thesis demonstrates that climate change induced water temperature and pH changes can cause problems to Baltic Sea copepod communities. However, their resilience depends substantially on their diet, and therefore the response of phytoplankton to the environmental changes. As copepods are an important link in pelagic food webs, their future success can have far reaching consequences, for example on fish stocks.
Resumo:
Since its discovery, chaos has been a very interesting and challenging topic of research. Many great minds spent their entire lives trying to give some rules to it. Nowadays, thanks to the research of last century and the advent of computers, it is possible to predict chaotic phenomena of nature for a certain limited amount of time. The aim of this study is to present a recently discovered method for the parameter estimation of the chaotic dynamical system models via the correlation integral likelihood, and give some hints for a more optimized use of it, together with a possible application to the industry. The main part of our study concerned two chaotic attractors whose general behaviour is diff erent, in order to capture eventual di fferences in the results. In the various simulations that we performed, the initial conditions have been changed in a quite exhaustive way. The results obtained show that, under certain conditions, this method works very well in all the case. In particular, it came out that the most important aspect is to be very careful while creating the training set and the empirical likelihood, since a lack of information in this part of the procedure leads to low quality results.
Resumo:
Our objective is to develop a diffusion Monte Carlo (DMC) algorithm to estimate the exact expectation values, ($o|^|^o), of multiplicative operators, such as polarizabilities and high-order hyperpolarizabilities, for isolated atoms and molecules. The existing forward-walking pure diffusion Monte Carlo (FW-PDMC) algorithm which attempts this has a serious bias. On the other hand, the DMC algorithm with minimal stochastic reconfiguration provides unbiased estimates of the energies, but the expectation values ($o|^|^) are contaminated by ^, an user specified, approximate wave function, when A does not commute with the Hamiltonian. We modified the latter algorithm to obtain the exact expectation values for these operators, while at the same time eliminating the bias. To compare the efficiency of FW-PDMC and the modified DMC algorithms we calculated simple properties of the H atom, such as various functions of coordinates and polarizabilities. Using three non-exact wave functions, one of moderate quality and the others very crude, in each case the results are within statistical error of the exact values.
Resumo:
Within the context of international adoption, previous research has focused on parentchild attachment relationships and various aspects of the adoption process. However, less is known about other aspects of parent-child relationships (e.g., cohesion, conflict) within internationally adoptive families. Additionally, there is a need for research that explores both parent and child perceptions of the process of adoption - including pre- and post-adoptive factors - and its connection to the quality of parent-child relationships. This research utilized a qualitatively-oriented methodology to conduct separate, in-depth interviews with 10 adoptive Canadian mothers and their adopted Chinese children (aged 9 to 11 years). Results highlight parent and child reports of mainly strong, positive relationships. Several pre-adoption experiences are examined, including institutionalization, age at the time of adoption, and parental stress/expectations. A key finding concerns the link that adoptive parents perceive between the quality of their child's pre-adoptive care (i.e., mainly early institutionalized care) and the quality of their relationship. Interestingly, this link is perceived in two different ways - either as a challenge for the parent-child relationship or as a means to strengthen it. Post-adoption experiences are also explored, including cultural socialization, creating a transracial family, discussing adoption, parental stress, and sibling involvement. A key finding involves parent and child reports that cultural socialization efforts (i.e., familiarizing children with Chinese culture) are linked to more positive parent-child relationships. The implications of these findings are discussed in relation to theory and practice within the context of international adoption.
Resumo:
Une estimation des quantités de carbone organique dissous dans les millions de lacs boréaux est nécessaire pour améliorer notre connaissance du cycle global du carbone. Les teneurs en carbone organique dissous sont corrélées avec les quantités de matière organique dissoute colorée qui est visible depuis l’espace. Cependant, les capteurs actuels offrent une radiométrie et une résolution spatiale qui sont limitées par rapport à la taille et l’opacité des lacs boréaux. Landsat 8, lancé en février 2013, offrira une radiométrie et une résolution spatiale améliorées, et produira une couverture à grande échelle des régions boréales. Les limnologistes ont accumulé des années de campagnes de terrain dans les régions boréales pour lesquelles une image Landsat 8 sera disponible. Pourtant, la possibilité de combiner des données de terrain existantes avec une image satellite récente n'a pas encore été évaluée. En outre, les différentes stratégies envisageables pour sélectionner et combiner des mesures répétées au cours du temps, sur le terrain et depuis le satellite, n'ont pas été évaluées. Cette étude présente les possibilités et les limites d’utiliser des données de terrain existantes avec des images satellites récentes pour développer des modèles de prédiction du carbone organique dissous. Les méthodes se basent sur des données de terrain recueillies au Québec dans 53 lacs boréaux et 10 images satellites acquises par le capteur prototype de Landsat 8. Les délais entre les campagnes de terrain et les images satellites varient de 1 mois à 6 ans. Le modèle de prédiction obtenu se compare favorablement avec un modèle basé sur des campagnes de terrain synchronisées avec les images satellite. L’ajout de mesures répétées sur le terrain, sur le satellite, et les corrections atmosphériques des images, n’améliorent pas la qualité du modèle de prédiction. Deux images d’application montrent des distributions différentes de teneurs en carbone organique dissous et de volumes, mais les quantités de carbone organique dissous par surface de paysage restent de même ordre pour les deux sites. Des travaux additionnels pour intégrer les sédiments dans l’estimation sont nécessaires pour améliorer le bilan du carbone des régions boréales.
Resumo:
Le modèle GARCH à changement de régimes est le fondement de cette thèse. Ce modèle offre de riches dynamiques pour modéliser les données financières en combinant une structure GARCH avec des paramètres qui varient dans le temps. Cette flexibilité donne malheureusement lieu à un problème de path dependence, qui a empêché l'estimation du modèle par le maximum de vraisemblance depuis son introduction, il y a déjà près de 20 ans. La première moitié de cette thèse procure une solution à ce problème en développant deux méthodologies permettant de calculer l'estimateur du maximum de vraisemblance du modèle GARCH à changement de régimes. La première technique d'estimation proposée est basée sur l'algorithme Monte Carlo EM et sur l'échantillonnage préférentiel, tandis que la deuxième consiste en la généralisation des approximations du modèle introduites dans les deux dernières décennies, connues sous le nom de collapsing procedures. Cette généralisation permet d'établir un lien méthodologique entre ces approximations et le filtre particulaire. La découverte de cette relation est importante, car elle permet de justifier la validité de l'approche dite par collapsing pour estimer le modèle GARCH à changement de régimes. La deuxième moitié de cette thèse tire sa motivation de la crise financière de la fin des années 2000 pendant laquelle une mauvaise évaluation des risques au sein de plusieurs compagnies financières a entraîné de nombreux échecs institutionnels. À l'aide d'un large éventail de 78 modèles économétriques, dont plusieurs généralisations du modèle GARCH à changement de régimes, il est démontré que le risque de modèle joue un rôle très important dans l'évaluation et la gestion du risque d'investissement à long terme dans le cadre des fonds distincts. Bien que la littérature financière a dévoué beaucoup de recherche pour faire progresser les modèles économétriques dans le but d'améliorer la tarification et la couverture des produits financiers, les approches permettant de mesurer l'efficacité d'une stratégie de couverture dynamique ont peu évolué. Cette thèse offre une contribution méthodologique dans ce domaine en proposant un cadre statistique, basé sur la régression, permettant de mieux mesurer cette efficacité.
Resumo:
Urbanization refers to the process in which an increasing proportion of a population lives in cities and suburbs. Urbanization fuels the alteration of the Land use/Land cover pattern of the region including increase in built-up area, leading to imperviousness of the ground surface. With increasing urbanization and population pressures; the impervious areas in the cities are increasing fast. An impervious surface refers to an anthropogenic ally modified surface that prevents water from infiltrating into the soil. Surface imperviousness mapping is important for the studies related to water cycling, water quality, soil erosion, flood water drainage, non-point source pollution, urban heat island effect and urban hydrology. The present study estimates the Total Impervious Area (TIA) of the city of Kochi using high resolution satellite image (LISS IV, 5m. resolution). Additionally the study maps the Effective Impervious Area (EIA) by coupling the capabilities of GIS and Remote Sensing. Land use/Land cover map of the study area was prepared from the LISS IV image acquired for the year 2012. The classes were merged to prepare a map showing pervious and impervious area. Supervised Maximum Likelihood Classification (Supervised MLC),which is a simple but accurate method for image classification, is used in calculating TIA and an overall classification accuracy of 86.33% was obtained. Water bodies are 100% pervious, whereas urban built up area are 100% impervious. Further based on percentage of imperviousness, the Total Impervious Area is categorized into various classes
Resumo:
Software systems are progressively being deployed in many facets of human life. The implication of the failure of such systems, has an assorted impact on its customers. The fundamental aspect that supports a software system, is focus on quality. Reliability describes the ability of the system to function under specified environment for a specified period of time and is used to objectively measure the quality. Evaluation of reliability of a computing system involves computation of hardware and software reliability. Most of the earlier works were given focus on software reliability with no consideration for hardware parts or vice versa. However, a complete estimation of reliability of a computing system requires these two elements to be considered together, and thus demands a combined approach. The present work focuses on this and presents a model for evaluating the reliability of a computing system. The method involves identifying the failure data for hardware components, software components and building a model based on it, to predict the reliability. To develop such a model, focus is given to the systems based on Open Source Software, since there is an increasing trend towards its use and only a few studies were reported on the modeling and measurement of the reliability of such products. The present work includes a thorough study on the role of Free and Open Source Software, evaluation of reliability growth models, and is trying to present an integrated model for the prediction of reliability of a computational system. The developed model has been compared with existing models and its usefulness of is being discussed.
Resumo:
A real-time analysis of renewable energy sources, such as arable crops, is of great importance with regard to an optimised process management, since aspects of ecology and biodiversity are considered in crop production in order to provide a sustainable energy supply by biomass. This study was undertaken to explore the potential of spectroscopic measurement procedures for the prediction of potassium (K), chloride (Cl), and phosphate (P), of dry matter (DM) yield, metabolisable energy (ME), ash and crude fibre contents (ash, CF), crude lipid (EE), nitrate free extracts (NfE) as well as of crude protein (CP) and nitrogen (N), respectively in pretreated samples and undisturbed crops. Three experiments were conducted, one in a laboratory using near infrared reflectance spectroscopy (NIRS) and two field spectroscopic experiments. Laboratory NIRS measurements were conducted to evaluate to what extent a prediction of quality parameters is possible examining press cakes characterised by a wide heterogeneity of their parent material. 210 samples were analysed subsequent to a mechanical dehydration using a screw press. Press cakes serve as solid fuel for thermal conversion. Field spectroscopic measurements were carried out with regard to further technical development using different field grown crops. A one year lasting experiment over a binary mixture of grass and red clover examined the impact of different degrees of sky cover on prediction accuracies of distinct plant parameters. Furthermore, an artificial light source was used in order to evaluate to what extent such a light source is able to minimise cloud effects on prediction accuracies. A three years lasting experiment with maize was conducted in order to evaluate the potential of off-nadir measurements inside a canopy to predict different quality parameters in total biomass and DM yield using one sensor for a potential on-the-go application. This approach implements a measurement of the plants in 50 cm segments, since a sensor adjusted sideways is not able to record the entire plant height. Calibration results obtained by nadir top-of-canopy reflectance measurements were compared to calibration results obtained by off-nadir measurements. Results of all experiments approve the applicability of spectroscopic measurements for the prediction of distinct biophysical and biochemical parameters in the laboratory and under field conditions, respectively. The estimation of parameters could be conducted to a great extent with high accuracy. An enhanced basis of calibration for the laboratory study and the first field experiment (grass/clover-mixture) yields in improved robustness of calibration models and allows for an extended application of spectroscopic measurement techniques, even under varying conditions. Furthermore, off-nadir measurements inside a canopy yield in higher prediction accuracies, particularly for crops characterised by distinct height increment as observed for maize.
Resumo:
Brazil has been increasing its importance in agricultural markets. The reasons are well known to be the relative abundance of land, the increasing technology used in crops, and the development of the agribusiness sector which allow for a fast response to price stimuli. The elasticity of acreage response to increases in expected return is estimated for Soybeans in a dynamic (long term) error correction model. Regarding yield patterns, a large variation in the yearly rates of growth in yield is observed, climate being probably the main source of this variation which result in ‘good’ and ‘bad’ years. In South America, special attention should be given to the El Niño and La Niña phenomena, both said to have important effects on rainfalls patterns and consequently in yield. The influence on El Niño and La Niña in historical data is examined and some ways of estimating the impact of climate on yield of Soybean and Corn markets are proposed. Possible implications of climate change may apply.