909 resultados para classification and regression trees


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Verrucous carcinoma of the vulva is a rare lesion (1). Affecting essentially postmenopausal women, this lesion is a distinct and particular entity in vulval carcinoma classification and its scalability is uncertain and unpredictable. Here, we present a case concerning a 48-year-old patient, without follow-up after a condyloma acuminate of the vulva (large left lip). The origin of this case will be discussed in this article. The treatment decided was only surgical. A review of literature shows the rarity of this lesion of the female genital tract.

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Approximately 7.2% of the Atlantic rainforest remains in Brazil, with only 16% of this forest remaining in the State of Rio de Janeiro, all of it distributed in fragments. This forest fragmentation can produce biotic and abiotic differences between edges and the fragment interior. In this study, we compared the structure and richness of tree communities in three habitats - an anthropogenic edge (AE), a natural edge (NE) and the fragment interior (FI) - of a fragment of Atlantic forest in the State of Rio de Janeiro, Brazil (22°50'S and 42°28'W). One thousand and seventy-six trees with a diameter at breast height > 4.8 cm, belonging to 132 morphospecies and 39 families, were sampled in a total study area of 0.75 ha. NE had the greatest basal area and the trees in this habitat had the greatest diameter:height allometric coefficient, whereas AE had a lower richness and greater variation in the height of the first tree branch. Tree density, diameter, height and the proportion of standing dead trees did not differ among the habitats. There was marked heterogeneity among replicates within each habitat. These results indicate that the forest interior and the fragment edges (natural or anthropogenic) do not differ markedly considering the studied parameters. Other factors, such as the age from the edge, type of matrix and proximity of gaps, may play a more important role in plant community structure than the proximity from edges.

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Finland’s rural landscape has gone through remarkable changes from the 1950’s, due to agricultural developments. Changed farming practices have influenced especially traditional landscape management, and modifications in the arable land structure and grasslands transitions are notable. The review of the previous studies reveal the importance of the rural landscape composition and structure to species and landscape diversity, whereas including the relevance in presence of the open ditches, size of the field and meadow patches, topology of the natural and agricultural landscape. This land-change study includes applying remote sensed data from two time series and empirical geospatial analysis in Geographic Information Systems (GIS). The aims of this retrospective research is to detect agricultural landscape use and land cover change (LULCC) dynamics and discuss the consequences of agricultural intensification to landscape structure covering from the aspects of landscape ecology. Measurements of LULC are derived directly from pre-processed aerial images by a variety of analytical procedures, including statistical methods and image interpretation. The methodological challenges are confronted in the process of landscape classification and combining change detection approaches with landscape indices. Particular importance is paid on detecting agricultural landscape features at a small scale, demanding comprehensive understanding of such agroecosystems. Topological properties of the classified arable land and valley are determined in order to provide insight and emphasize the aspect the field edges in the agricultural landscape as important habitat. Change detection dynamics are presented with change matrix and additional calculations of gain, loss, swap, net change, change rate and tendencies are made. Transition’s possibility is computed following Markov’s probability model and presented with matrix, as well. Thesis’s spatial aspect is revealed with illustrative maps providing knowledge of location of the classified landscape categories and location of the dynamics of the changes occurred. It was assured that in Rekijoki valley’s landscape, remarkable changes in landscape has occurred. Landscape diversity has been strongly influenced by modern agricultural landscape change, as NP of open ditches has decreased and the MPS of the arable plot has decreased. Overall change in the diversity of the landscape is determined with the decrease of SHDI. Valley landscape considered as traditional land use area has experienced major transitional changes, as meadows class has lost almost one third of the area due to afforestation. Also, remarkable transitions have occurred from forest to meadow and arable land to built area. Boundaries measurement between modern and traditional landscape has indicated noticeable proportional increase in arable land-forest edge type and decrease in arable land-meadow edge type. Probability calculations predict higher future changes for traditional landscape, but also for arable land turning into built area.

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This thesis studies the development of service offering model that creates added-value for customers in the field of logistics services. The study focusses on offering classification and structures of model. The purpose of model is to provide value-added solutions for customers and enable superior service experience. The aim of thesis is to define what customers expect from logistics solution provider and what value customers appreciate so greatly that they could invest in value-added services. Value propositions, costs structures of offerings and appropriate pricing methods are studied. First, literature review of creating solution business model and customer value is conducted. Customer value is found out with customer interviews and qualitative empiric data is used. To exploit expertise knowledge of logistics, innovation workshop tool is utilized. Customers and experts are involved in the design process of model. As a result of thesis, three-level value-added service offering model is created based on empiric and theoretical data. Offerings with value propositions are proposed and the level of model reflects the deepness of customer-provider relationship and the amount of added value. Performance efficiency improvements and cost savings create the most added value for customers. Value-based pricing methods, such as performance-based models are suggested to apply. Results indicate the interest of benefitting networks and partnership in field of logistics services. Networks development is proposed to be investigated further.

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The aim of this study is to investigate the floristic composition of an Atlantic rain forest fragment located in Cananéia, São Paulo, Brazil, and to contribute to the knowledge on Atlantic forest through the comparative analysis of this and other floristic surveys both on the southern and southeastern Brazil, in different soil and relief types. We surveyed 215 species in 132 genera and 51 families. Classification and ordination analysis were applied to a binary matrix in order to analyze the similarity among 24 surveys, including the present one, of Atlantic forest from the south and southeast coast of Brazil. Higher floristic similarity was observed among this area and the ones where there was marine influence and more rugged relief. The surveys in areas with greater marine influence (sandy soil) were separated from those in other conditions, possibly indicating a species replacement gradient from the steep slopes towards the lowland and were probably related to different edaphic conditions. A latitudinal gradient was found among the surveys apparently confirming a continuous species replacement along the Atlantic forest, related to a restricted distribution of the species. This suggests that it is essential to preserve areas from the whole Atlantic coast. Atlantic forest distribution is quite complex and its composition cannot be adequately represented by small localized areas.

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Genetic distances among cacao cultivars were calculated through multivariate analysis, using the D2 statistic, to examine racial group classification and to assess heterotic hybrids. A 5 x 5 complete diallel was evaluated. Over a five-year period (1986-1990), five cultivars of the S1 generation, pertaining to the Lower Amazon Forastero and Trinitario racial groups and 20 crosses between the corresponding S0 parents were analyzed, based upon five yield components - number of healthy and collected fruits per plant (NHFP and NCFP), wet seed weight per plant and per fruit (WSWP and WSWF), and percentage of diseased fruits per plant (PDFP). The diversity analysis suggested a close relationship between the Trinitario and Lower Amazon Forastero groups. A correlation coefficient (r) was calculated to determine the association between genetic diversity and heterosis. Genetic distance of parents by D2 was found to be linearly related to average performance of hybrids for WSWP and WSWF (r = 0.68, P < 0.05 and r = 0.76, P < 0.05, respectively). The heterotic performance for the same components was also correlated with D2, both with r = 0.66 (P < 0.05). A relationship between genetic divergence and combining ability effects was suggested because the most divergent cultivar exhibited a high general combining ability, generating the best performing hybrids. Results indicated that genetic diversity estimates can be useful in selecting parents for crosses and in assessing relationships among cacao racial groups.

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Customer satisfaction should be the main focus for all of the parts of the business. Usually supply chain behind the business is in a key role when this focus is pursued especially in repair service business. When focusing on the materials that are needed to make repairs to equipment under service contracts, the time aspect of quality is critical. Do late deliveries from supplier have an effect on the service performance of repairs when distribution center of a centralized purchasing unit is acting as a buffer between suppliers and repair service business? And if so, how should the improvement efforts be prioritized? These are the two main questions that this thesis focuses on. Correlation and linear regression was tested between service levels of supplier and distribution center. Percentage of on-time deliveries were compared to outbound delivery service level. It was found that there is statistically significant correlation between inbound and outbound operations success. The other main question of the thesis, improvement prioritization, was answered by creating material availability based supplier classification and additional to that, by developing the decision process for the analysis of most critical suppliers. This was built on a basis of previous supplier and material classification methods.

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Ellagitannins are secondary metabolites that are produced by plants. Among other features, they are assumed to function as plants’ defensive compounds against plant-eating herbivores. This thesis focuses on a theory, which suggests that the biological activity of ellagitannins is based on their tendency to oxidize at the highly alkaline gut conditions of insect herbivores (oxidative activity). To study the biological activities of ellagitannins, a wide variety of structurally different ellagitannins were purified from different plant species by using liquid chromatographic techniques. The structures were characterized with the aid of spectrometric methods. Based on the acquired data, it was also possible to create a scheme, which enables the classification and even identification of ellagitannins from plant extracts without the need to isolate each compound for individual characterization. The biological activities of ellagitannins were determined with methods that are based on the abilities of the compounds to scavenge radicals, chelate iron ions, and on their rate of oxidation at high pH. The results showed that ellagitannins possess oxidative activities both at high and neutral pH, and that their activities depend on structure. The occurrence, distribution and content of ellagitannins in Finnish plant species were also studied. The specific ellagitannin profiles of the studied plant species were found to correlate well with their taxonomic classification.

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Neoadjuvant chemotherapy has practical and theoretical advantages over adjuvant chemotherapy strategy in breast cancer (BC) management. Moreover, metronomic delivery has a more favorable toxicity profile. The present study examined the feasibility of neoadjuvant metronomic chemotherapy in two cohorts [HER2+ (TraQme) and HER2− (TAME)] of locally advanced BC. Twenty patients were prospectively enrolled (TraQme, n=9; TAME, n=11). Both cohorts received weekly paclitaxel at 100 mg/m2 during 8 weeks followed by weekly doxorubicin at 24 mg/m2 for 9 weeks in combination with oral cyclophosphamide at 100 mg/day (fixed dose). The HER2+ cohort received weekly trastuzumab. The study was interrupted because of safety issues. Thirty-six percent of patients in the TAME cohort and all patients from the TraQme cohort had stage III BC. Of note, 33% from the TraQme cohort and 66% from the TAME cohort displayed hormone receptor positivity in tumor tissue. The pathological complete response rates were 55% and 18% among patients enrolled in the TraQme and TAME cohorts, respectively. Patients in the TraQme cohort had more advanced BC stages at diagnosis, higher-grade pathological classification, and more tumors lacking hormone receptor expression, compared to the TAME cohort. The toxicity profile was also different. Two patients in the TraQme cohort developed pneumonitis, and in the TAME cohort we observed more hematological toxicity and hand-foot syndrome. The neoadjuvant metronomic chemotherapy regimen evaluated in this trial was highly effective in achieving a tumor response, especially in the HER2+ cohort. Pneumonitis was a serious, unexpected adverse event observed in this group. Further larger and randomized trials are warranted to evaluate the association between metronomic chemotherapy and trastuzumab treatment.

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The sorption behavior of dry products is generally affected by the drying method. The sorption isotherms are useful to determine and compare thermodynamic properties of passion fruit pulp powder processed by different drying methods. The objective of this study is to analyze the effects of different drying methods on the sorption properties of passion fruit pulp powder. Passion fruit pulp powder was dehydrated using different dryers: vacuum, spray dryer, vibro-fluidized, and freeze dryer. The moisture equilibrium data of Passion Fruit Pulp (PFP) powders with 55% of maltodextrin (MD) were determined at 20, 30, 40 and 50 ºC. The behavior of the curves was type III, according to Brunauer's classification, and the GAB model was fitted to the experimental equilibrium data. The equilibrium moisture contents of the samples were little affected by temperature variation. The spray dryer provides a dry product with higher adsorption capacity than that of the other methods. The vibro-fluidized bed drying showed higher adsorption capacity than that of vacuum and freeze drying. The vacuum and freeze drying presented the same adsorption capacity. The isosteric heats of sorption were found to decrease with increasing moisture content. Considering the effect of drying methods, the highest isosteric heat of sorption was observed for powders produced by spray drying, whereas powders obtained by vacuum and freeze drying showed the lowest isosteric heats of sorption.

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TAVOITTEET: Tämän tutkielman tarkoitus on tarkastella eri toimialojen likviditeettitasoja vuosien 2007 ja 2013 välillä. Se tarkastelee myös kassanhallinnan ja likviditeetin kirjallisuutta, erilaisia likviditeettiä kuvaavia tunnuslukuja sekä asioita, joilla on vaikutusta likviditeettiin. Tämän lisäksi se tutkii informaatio ja kommunikaatio sektoria tarkemmin. DATA: Data on kerätty Orbis tietokannasta. Toimialakohtaiset keskiarvot on laskettu joko kappaleen 2 esittämillä kaavoilla tai noudettu suoraan tietokannasta. Hajonta kuvaajat on tehty Excelillä ja korrelaatio matriisi ja regressioanalyysit SAS EG:llä. TULOKSET: Tämä tutkimus esittää toimialakohtaiset keskiarvot liquidity ratiosta, solvency ratiosta sekä gearingista, kuten monista muista likviditeettiä kuvaavista tai siihen vaikuttavista tunnusluvuista. Tutkimus osoittaa, että keskimäärin likviditeetti ja maksuvalmius ovat säilyneet melko samana, mutta toimialakohtaiset muutokset ovat voimakkaita. IC sektorilla likviditeettiin vaikuttaa katetuotto, työntekijöiden määrä, liikevaihto, taseen määrä sekä maksuaika.

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Breeding soybean for high seed quality is an important approach for developing cultivars for tropical regions, and the lignin content in the seed coat is one of the screening parameters for this trait. Considering that many breeding lines are evaluated in each growing season using the presently recommended method for lignin determination, a long period is required for the evaluation of the whole breeding program. This time limitation may influence lignin content assessment, if lignin is degraded during storage. This research reported was designed to determine whether lignin was degraded in the seed coat of soybean seed cultivars stored for one year in a controlled environment (10°C temperature and 50% air relative humidity). Seeds of 12 selected soybean cultivars that had a range in seed coat lignin content were evaluated. Seeds were hand harvested just after physiological maturity and evaluated for seed coat lignin content at harvest and after one year of storage in a cold room (10°C and 50% RH). The lignin content in seed coats differed significantly among cultivars in both analyses, but for both results the sequence of cultivar classification and the lignin content values of each cultivar did not change. A regression analysis of lignin content at harvest and after one year of storage indicated a direct relationship between both lignin determinations suggesting no differences between the lignin content of each cultivar due to prolonged storage (r² = 0.98***). This indicates that the lignin determination in the soybean seed coat can be performed over a long time period without any bias due to change in its content.

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Remote sensing techniques involving hyperspectral imagery have applications in a number of sciences that study some aspects of the surface of the planet. The analysis of hyperspectral images is complex because of the large amount of information involved and the noise within that data. Investigating images with regard to identify minerals, rocks, vegetation and other materials is an application of hyperspectral remote sensing in the earth sciences. This thesis evaluates the performance of two classification and clustering techniques on hyperspectral images for mineral identification. Support Vector Machines (SVM) and Self-Organizing Maps (SOM) are applied as classification and clustering techniques, respectively. Principal Component Analysis (PCA) is used to prepare the data to be analyzed. The purpose of using PCA is to reduce the amount of data that needs to be processed by identifying the most important components within the data. A well-studied dataset from Cuprite, Nevada and a dataset of more complex data from Baffin Island were used to assess the performance of these techniques. The main goal of this research study is to evaluate the advantage of training a classifier based on a small amount of data compared to an unsupervised method. Determining the effect of feature extraction on the accuracy of the clustering and classification method is another goal of this research. This thesis concludes that using PCA increases the learning accuracy, and especially so in classification. SVM classifies Cuprite data with a high precision and the SOM challenges SVM on datasets with high level of noise (like Baffin Island).

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En écologie, dans le cadre par exemple d’études des services fournis par les écosystèmes, les modélisations descriptive, explicative et prédictive ont toutes trois leur place distincte. Certaines situations bien précises requièrent soit l’un soit l’autre de ces types de modélisation ; le bon choix s’impose afin de pouvoir faire du modèle un usage conforme aux objectifs de l’étude. Dans le cadre de ce travail, nous explorons dans un premier temps le pouvoir explicatif de l’arbre de régression multivariable (ARM). Cette méthode de modélisation est basée sur un algorithme récursif de bipartition et une méthode de rééchantillonage permettant l’élagage du modèle final, qui est un arbre, afin d’obtenir le modèle produisant les meilleures prédictions. Cette analyse asymétrique à deux tableaux permet l’obtention de groupes homogènes d’objets du tableau réponse, les divisions entre les groupes correspondant à des points de coupure des variables du tableau explicatif marquant les changements les plus abrupts de la réponse. Nous démontrons qu’afin de calculer le pouvoir explicatif de l’ARM, on doit définir un coefficient de détermination ajusté dans lequel les degrés de liberté du modèle sont estimés à l’aide d’un algorithme. Cette estimation du coefficient de détermination de la population est pratiquement non biaisée. Puisque l’ARM sous-tend des prémisses de discontinuité alors que l’analyse canonique de redondance (ACR) modélise des gradients linéaires continus, la comparaison de leur pouvoir explicatif respectif permet entre autres de distinguer quel type de patron la réponse suit en fonction des variables explicatives. La comparaison du pouvoir explicatif entre l’ACR et l’ARM a été motivée par l’utilisation extensive de l’ACR afin d’étudier la diversité bêta. Toujours dans une optique explicative, nous définissons une nouvelle procédure appelée l’arbre de régression multivariable en cascade (ARMC) qui permet de construire un modèle tout en imposant un ordre hiérarchique aux hypothèses à l’étude. Cette nouvelle procédure permet d’entreprendre l’étude de l’effet hiérarchisé de deux jeux de variables explicatives, principal et subordonné, puis de calculer leur pouvoir explicatif. L’interprétation du modèle final se fait comme dans une MANOVA hiérarchique. On peut trouver dans les résultats de cette analyse des informations supplémentaires quant aux liens qui existent entre la réponse et les variables explicatives, par exemple des interactions entres les deux jeux explicatifs qui n’étaient pas mises en évidence par l’analyse ARM usuelle. D’autre part, on étudie le pouvoir prédictif des modèles linéaires généralisés en modélisant la biomasse de différentes espèces d’arbre tropicaux en fonction de certaines de leurs mesures allométriques. Plus particulièrement, nous examinons la capacité des structures d’erreur gaussienne et gamma à fournir les prédictions les plus précises. Nous montrons que pour une espèce en particulier, le pouvoir prédictif d’un modèle faisant usage de la structure d’erreur gamma est supérieur. Cette étude s’insère dans un cadre pratique et se veut un exemple pour les gestionnaires voulant estimer précisément la capture du carbone par des plantations d’arbres tropicaux. Nos conclusions pourraient faire partie intégrante d’un programme de réduction des émissions de carbone par les changements d’utilisation des terres.

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La scoliose idiopathique de l’adolescent (SIA) est une déformation tri-dimensionelle du rachis. Son traitement comprend l’observation, l’utilisation de corsets pour limiter sa progression ou la chirurgie pour corriger la déformation squelettique et cesser sa progression. Le traitement chirurgical reste controversé au niveau des indications, mais aussi de la chirurgie à entreprendre. Malgré la présence de classifications pour guider le traitement de la SIA, une variabilité dans la stratégie opératoire intra et inter-observateur a été décrite dans la littérature. Cette variabilité s’accentue d’autant plus avec l’évolution des techniques chirurgicales et de l’instrumentation disponible. L’avancement de la technologie et son intégration dans le milieu médical a mené à l’utilisation d’algorithmes d’intelligence artificielle informatiques pour aider la classification et l’évaluation tridimensionnelle de la scoliose. Certains algorithmes ont démontré être efficace pour diminuer la variabilité dans la classification de la scoliose et pour guider le traitement. L’objectif général de cette thèse est de développer une application utilisant des outils d’intelligence artificielle pour intégrer les données d’un nouveau patient et les évidences disponibles dans la littérature pour guider le traitement chirurgical de la SIA. Pour cela une revue de la littérature sur les applications existantes dans l’évaluation de la SIA fut entreprise pour rassembler les éléments qui permettraient la mise en place d’une application efficace et acceptée dans le milieu clinique. Cette revue de la littérature nous a permis de réaliser que l’existence de “black box” dans les applications développées est une limitation pour l’intégration clinique ou la justification basée sur les évidence est essentielle. Dans une première étude nous avons développé un arbre décisionnel de classification de la scoliose idiopathique basé sur la classification de Lenke qui est la plus communément utilisée de nos jours mais a été critiquée pour sa complexité et la variabilité inter et intra-observateur. Cet arbre décisionnel a démontré qu’il permet d’augmenter la précision de classification proportionnellement au temps passé à classifier et ce indépendamment du niveau de connaissance sur la SIA. Dans une deuxième étude, un algorithme de stratégies chirurgicales basé sur des règles extraites de la littérature a été développé pour guider les chirurgiens dans la sélection de l’approche et les niveaux de fusion pour la SIA. Lorsque cet algorithme est appliqué à une large base de donnée de 1556 cas de SIA, il est capable de proposer une stratégie opératoire similaire à celle d’un chirurgien expert dans prêt de 70% des cas. Cette étude a confirmé la possibilité d’extraire des stratégies opératoires valides à l’aide d’un arbre décisionnel utilisant des règles extraites de la littérature. Dans une troisième étude, la classification de 1776 patients avec la SIA à l’aide d’une carte de Kohonen, un type de réseaux de neurone a permis de démontrer qu’il existe des scoliose typiques (scoliose à courbes uniques ou double thoracique) pour lesquelles la variabilité dans le traitement chirurgical varie peu des recommandations par la classification de Lenke tandis que les scolioses a courbes multiples ou tangentielles à deux groupes de courbes typiques étaient celles avec le plus de variation dans la stratégie opératoire. Finalement, une plateforme logicielle a été développée intégrant chacune des études ci-dessus. Cette interface logicielle permet l’entrée de données radiologiques pour un patient scoliotique, classifie la SIA à l’aide de l’arbre décisionnel de classification et suggère une approche chirurgicale basée sur l’arbre décisionnel de stratégies opératoires. Une analyse de la correction post-opératoire obtenue démontre une tendance, bien que non-statistiquement significative, à une meilleure balance chez les patients opérés suivant la stratégie recommandée par la plateforme logicielle que ceux aillant un traitement différent. Les études exposées dans cette thèse soulignent que l’utilisation d’algorithmes d’intelligence artificielle dans la classification et l’élaboration de stratégies opératoires de la SIA peuvent être intégrées dans une plateforme logicielle et pourraient assister les chirurgiens dans leur planification préopératoire.