873 resultados para Support Vector Machines and Naive Bayes Classifier
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Possible new ways in the pharmacological treatment of bipolar disorder and comorbid alcoholism. Azorin JM, Bowden CL, Garay RP, Perugi G, Vieta E, Young AH. Source Department of Psychiatry, CHU Sainte Marguerite, Marseilles, France. Abstract About half of all bipolar patients have an alcohol abuse problem at some point of their lifetime. However, only one randomized, controlled trial of pharmacotherapy (valproate) in this patient population was published as of 2006. Therefore, we reviewed clinical trials in this indication of the last four years (using mood stabilizers, atypical antipsychotics, and other drugs). Priority was given to randomized trials, comparing drugs with placebo or active comparator. Published studies were found through systematic database search (PubMed, Scirus, EMBASE, Cochrane Library, Science Direct). In these last four years, the only randomized, clinically relevant study in bipolar patients with comorbid alcoholism is that of Brown and colleagues (2008) showing that quetiapine therapy decreased depressive symptoms in the early weeks of use, without modifying alcohol use. Several other open-label trials have been generally positive and support the efficacy and tolerability of agents from different classes in this patient population. Valproate efficacy to reduce excessive alcohol consumption in bipolar patients was confirmed and new controlled studies revealed its therapeutic benefit to prevent relapse in newly abstinent alcoholics and to improve alcohol hallucinosis. Topiramate deserves to be investigated in bipolar patients with comorbid alcoholism since this compound effectively improves physical health and quality of life of alcohol-dependent individuals. In conclusion, randomized, controlled research is still needed to provide guidelines for possible use of valproate and other agents in patients with a dual diagnosis of bipolar disorder and substance abuse or dependence.
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Background: Documenting the distribution of radiotherapy departments and the availability of radiotherapy equipment in the European countries is an important part of HERO the ESTRO Health Economics in Radiation Oncology project. HERO has the overall aim to develop a knowledge base of the provision of radiotherapy in Europe and build a model for health economic evaluation of radiation treatments at the European level. The aim of the current report is to describe the distribution of radiotherapy equipment in European countries. Methods: An 84-item questionnaire was sent out to European countries, principally through their national societies. The current report includes a detailed analysis of radiotherapy departments and equipment (questionnaire items 2629), analyzed in relation to the annual number of treatment courses and the socio-economic status of the countries. The analysis is based on validated responses from 28 of the 40 European countries defined by the European Cancer Observatory (ECO). Results: A large variation between countries was found for most parameters studied. There were 2192 linear accelerators, 96 dedicated stereotactic machines, and 77 cobalt machines reported in the 27 countries where this information was available. A total of 12 countries had at least one cobalt machine in use. There was a median of 0.5 simulator per MV unit (range 0.31.5) and 1.4 (range 0.44.4) simulators per department. Of the 874 simulators, a total of 654 (75%) were capable of 3D imaging (CT-scanner or CBCToption). The number of MV machines (cobalt, linear accelerators, and dedicated stereotactic machines) per million inhabitants ranged from 1.4 to 9.5 (median 5.3) and the average number of MV machines per department from 0.9 to 8.2 (median 2.6). The average number of treatment courses per year per MV machine varied from 262 to 1061 (median 419). While 69% of MV units were capable of IMRT only 49% were equipped for image guidance (IGRT). There was a clear relation between socio-economic status, as measured by GNI per capita, and availability of radiotherapy equipment in the countries. In many low income countries in Southern and Central-Eastern Europe there was very limited access to radiotherapy and especially to equipment for IMRT or IGRT. Conclusions: The European average number of MV machines per million inhabitants and per department is now better in line with QUARTS recommendations from 2005, but the survey also showed a significant heterogeneity in the access to modern radiotherapy equipment in Europe. High income countries especially in Northern-Western Europe are well-served with radiotherapy resources, other countries are facing important shortages of both equipment in general and especially machines capable of delivering high precision conformal treatments (IMRT, IGRT)
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FEMA's mission is to support our citizens and first responders to ensure that as a Nation we work together to build, sustain, and improve our capability to prepare for, protect against, respond to, recover from, and mitigate all hazards.
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The present thesis in focused on the minimization of experimental efforts for the prediction of pollutant propagation in rivers by mathematical modelling and knowledge re-use. Mathematical modelling is based on the well known advection-dispersion equation, while the knowledge re-use approach employs the methods of case based reasoning, graphical analysis and text mining. The thesis contribution to the pollutant transport research field consists of: (1) analytical and numerical models for pollutant transport prediction; (2) two novel techniques which enable the use of variable parameters along rivers in analytical models; (3) models for the estimation of pollutant transport characteristic parameters (velocity, dispersion coefficient and nutrient transformation rates) as functions of water flow, channel characteristics and/or seasonality; (4) the graphical analysis method to be used for the identification of pollution sources along rivers; (5) a case based reasoning tool for the identification of crucial information related to the pollutant transport modelling; (6) and the application of a software tool for the reuse of information during pollutants transport modelling research. These support tools are applicable in the water quality research field and in practice as well, as they can be involved in multiple activities. The models are capable of predicting pollutant propagation along rivers in case of both ordinary pollution and accidents. They can also be applied for other similar rivers in modelling of pollutant transport in rivers with low availability of experimental data concerning concentration. This is because models for parameter estimation developed in the present thesis enable the calculation of transport characteristic parameters as functions of river hydraulic parameters and/or seasonality. The similarity between rivers is assessed using case based reasoning tools, and additional necessary information can be identified by using the software for the information reuse. Such systems represent support for users and open up possibilities for new modelling methods, monitoring facilities and for better river water quality management tools. They are useful also for the estimation of environmental impact of possible technological changes and can be applied in the pre-design stage or/and in the practical use of processes as well.
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Concentrated winding permanent magnet machines and their electromagnetic properties are studied in this doctoral thesis. The thesis includes a number of main tasks related to the application of permanent magnets in concentrated winding open slot machines. Suitable analytical methods are required for the first design calculations of a new machine. Concentrated winding machines differ from conventional integral slot winding machines in such a way that adapted analytical calculation methods are needed. A simple analytical model for calculating the concentrated winding axial flux machines is provided. The next three main design tasks are discussed in more detail in the thesis. The magnetic length of the rotor surface magnet machines is studied, and it is shown that the traditional methods have to be modified also in this respect. An important topic in this study has been to evaluate and minimize the rotor permanent magnet Joule losses by using segmented magnets in the calculations and experiments. Determination of the magnetizing and leakage inductances for a concentrated winding machine and the torque production capability of concentrated winding machines with different pole pair numbers are studied, and the results are compared with the corresponding properties of integral slot winding machines. The thesis introduces a new practical permanent magnet motor type for industrial use. The special features of the machine are based on the option of using concentrated winding open slot constructions of permanent magnet synchronous machines in the normal speed ranges of industrial motors, for instance up to 3000 min-1, without excessive rotor losses. By applying the analytical equations and methods introduced in the thesis, a 37 kW 2400 min-1 12-slot 10-pole axial flux machine with rotor-surfacemounted magnets is designed. The performance of the designed motor is determined by experimental measurements and finite element calculations.
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In this paper studies based on Multilayer Perception Artificial Neural Network and Least Square Support Vector Machine (LS-SVM) techniques are applied to determine of the concentration of Soil Organic Matter (SOM). Performances of the techniques are compared. SOM concentrations and spectral data from Mid-Infrared are used as input parameters for both techniques. Multivariate regressions were performed for a set of 1117 spectra of soil samples, with concentrations ranging from 2 to 400 g kg-1. The LS-SVM resulted in a Root Mean Square Error of Prediction of 3.26 g kg-1 that is comparable to the deviation of the Walkley-Black method (2.80 g kg-1).
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Stunting and stem necrosis were noticed in soybeans (Glycine max) grown in 2000/2001 in West Central Brazil the same condition was also observed in the following year in plantations as far as 2,000 km from the initial area. Based on transmission (mechanical, graft, insect vector), purification and serology, electron microscopy and molecular studies the causal agent was determined to be a whitefly-borne carlavirus which is possibly related to Cowpea mild mottle virus (CpMMV).
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Tutkielmassa käsitellään matemaattisia ennustamismenetelmiä, jotka soveltuvat tyypin 1 diabeteksen ennustamiseen. Aluksi esitellään menetelmiä, jotka soveltuvat puuttuvia havaintoja sisältävien aineistojen paikkaamiseen. Paikattua aineistoa on mahdollista analysoida useilla tavallisilla tilastollisilla menetelmillä, jotka sopivat täydellisiin aineistoihin. Seuraavaksi pyritään mallintamaan aineistoa semiparametrisilla komponenttimalleilla (eng. mixture model), jolloin mallin muotoa ei ole tiukasti etukäteen rajoitettu. Sen jälkeen sovelletaan kolmea luokittelevaa ennustajaa: logistista regressiomallia, eteenpäinsyöttävää yhden piilotason neuroverkkoa ja SVM-menetelmää (eng. support vector machine). Esiteltäviä menetelmiä on sovellettu todelliseen aineistoon, joka on kerätty Turun yliopistossa käynnissä olevassa tutkimusprojektissa. Projektin tavoitteena on oppia ennustamaan ja ehkäisemään tyypin 1 diabetesta (Type 1 diabetes prediction and prevention project, lyh. DIPP-projekti). Erityisesti projektissa on pyritty löytämään uusia tuntemattomia taudinaiheuttajia. Tässä tutkielmassa paneudutaan sen sijaan kerätyn havaintoaineiston matemaattisiin analysointimenetelmiin. Parhaat ennusteet saatiin perinteisellä logistisella regressiomallilla. Tutkielmassa kuitenkin todetaan, että tulevaisuudessa on mahdollista löytää parempia ennustajia parantamalla muita edellä mainittuja menetelmiä. Erityisesti SVM-menetelmä ansaitsisi lisähuomiota, sillä tässä tutkielmassa sitä sovellettiin vain kaikkein yksinkertaisimmassa muodossa.
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A coupled system simulator, based on analytical circuit equations and a finite element method (FEM) model of the motor has been developed and it is used to analyse a frequency-converterfed industrial squirrel-cage induction motor. Two control systems that emulate the behaviour of commercial direct-torque-controlled (DTC) and vector-controlled industrial frequency converters have been studied, implemented in the simulation software and verified by extensive laboratory tests. Numerous factors that affect the operation of a variable speed drive (VSD) and its energy efficiency have been investigated, and their significance in the simulation of the VSD results has been studied. The dependency of the frequency converter, induction motor and system losses on the switching frequency is investigated by simulations and measurements at different speeds for both the vector control and the DTC. Intensive laboratory measurements have been carried out to verify the simulation results.
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This paper aims to assess the effectiveness of ASTER imagery to support the mapping of Pittosporum undulatum, an invasive woody species, in Pico da Vara Natural Reserve (S. Miguel Island, Archipelago of the Azores, Portugal). This assessment was done by applying K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and Maximum Likelihood (MLC) pixel-based supervised classifications to 4 different geographic and remote sensing datasets constituted by the Visible, Near-Infrared (VNIR) and Short Wave Infrared (SWIR) of the ASTER sensor and by digital cartography associated to orography (altitude and "distance to water streams") of which the spatial distribution of Pittosporum undulatum directly depends. Overall, most performed classifications showed a strong agreement and high accuracy. At targeted species level, the two higher classification accuracies were obtained when applying MLC and KNN to the VNIR bands coupled with auxiliary geographic information use. Results improved significantly by including ecology and occurrence information of species (altitude and distance to water streams) in the classification scheme. These results show that the use of ASTER sensor VNIR spectral bands, when coupled to relevant ancillary GIS data, can constitute an effective and low cost approach for the evaluation and continuous assessment of Pittosporum undulatum woodland propagation and distribution within Protected Areas of the Azores Islands.
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ABSTRACT We aimed in this work to study natural populations of copaiba (Copaifera multijuga Hayne) on the Monte Branco mountain at Porto Trombetas-PA, in order to support sustainable management and the exploitation of oleoresin from copaiba. We studied the population structure of copaiba on hillsides and valleys of the south face of Monte Branco, within Saracá Taquera National Forest, where bauxite ore was extracted in the biennium 2013-2014 by Mineração Rio do Norte (MRN). We produced a 100% forest inventory of the specie and of oleoresin extraction in order to quantify the potential production of the remaining area. The density of copaiba individuals with DBH > 30 cm was 0.33 individuals per hectare in the hillside and 0.25 individuals per hectare in the valley. Both environments presented a density of 0.28 individuals per hectare. The average copaiba oleoresin yield was 0.661±0.334 liters in the hillside and 0.765±0.280 liters in the valley. The average value of both environments together (hillside and valley) was 0.714±0.218 liters. From all individuals with DBH over 30 cm, 38 (58%) produced some amount of oleoresin, averaging 1.113±0.562 liters in the hillside, 1.329±0.448 liters in the valley and 1.190±0.355 liters in both environments together. The results show the need for planning the use of the surroundings of the study area in order to reach the required volume of copaiba to make feasible the sustainable management of oleoresin extraction in the region.
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The purpose of this work was evaluating the energetic demand of a seeder-fertilizer machine as a function of the type and handling of vegetal covering culture and of the fertilizer deposition shank depth. A Valtra BM100 tractor was used implemented to pull a high precision seeder-fertilizer machine with four ranks of seeding, spaced 0.9 m for maize culture. Experiment was conducted with design in randomized blocks in factorial plots, in the Laboratory of Machines and Agricultural Mechanization experimental area (LAMMA) of UNESP-Jaboticabal, using two covering cultures (black-mucuna and crotalaria), three handlings of this covering, two mechanical (straw crusher and roller knife) and one chemical (pulverization of herbicide), performed 120 days after seeding of covering cultures and three depths of fertilizer deposition shank, completing 18 treatments, with four repetitions, totaling 72 observations. Parameters of displacement speed, gliding, force on traction bar, peak force, power on pulling bar and fuel consumption were evaluated. It was possible to conclude that force on traction bar was less for depths of 0.11 and 0.14 m of fertilizer plough shank, the same occurring for peak force, power on traction bar and volumetric consumption. The specific consumption was lower at a depth of 0.17 m of fertilizer plough shank. Covering cultures and their handlings did not interfere in the performance of machines under inquiry.
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Coffee production was closely linked to the economic development of Brazil and, even today, coffee is an important product of the national agriculture. The State of Minas Gerais currently accounts for 52% of the whole coffee area in Brazil. Remote sensing data can provide information for monitoring and mapping of coffee crops, faster and cheaper than conventional methods. In this context, the objective of this study was to assess the effectiveness of coffee crop mapping in Monte Santo de Minas municipality, Minas Gerais State, Brazil, from fraction images derived from MODIS data, in both dry and rainy seasons. The Spectral Linear Mixing Model was used to derive fraction images of soil, coffee, and water/shade. These fraction images served as input data for the supervised automatic classification using the SVM - Support Vector Machine approach. The best results concerning Overall Accuracy and Kappa Index were obtained in the classification of the dry season, with 67% and 0.41, respectively.
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Statistical analyses of measurements that can be described by statistical models are of essence in astronomy and in scientific inquiry in general. The sensitivity of such analyses, modelling approaches, and the consequent predictions, is sometimes highly dependent on the exact techniques applied, and improvements therein can result in significantly better understanding of the observed system of interest. Particularly, optimising the sensitivity of statistical techniques in detecting the faint signatures of low-mass planets orbiting the nearby stars is, together with improvements in instrumentation, essential in estimating the properties of the population of such planets, and in the race to detect Earth-analogs, i.e. planets that could support liquid water and, perhaps, life on their surfaces. We review the developments in Bayesian statistical techniques applicable to detections planets orbiting nearby stars and astronomical data analysis problems in general. We also discuss these techniques and demonstrate their usefulness by using various examples and detailed descriptions of the respective mathematics involved. We demonstrate the practical aspects of Bayesian statistical techniques by describing several algorithms and numerical techniques, as well as theoretical constructions, in the estimation of model parameters and in hypothesis testing. We also apply these algorithms to Doppler measurements of nearby stars to show how they can be used in practice to obtain as much information from the noisy data as possible. Bayesian statistical techniques are powerful tools in analysing and interpreting noisy data and should be preferred in practice whenever computational limitations are not too restrictive.
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The Laboratory of Intelligent Machine researches and develops energy-efficient power transmissions and automation for mobile construction machines and industrial processes. The laboratory's particular areas of expertise include mechatronic machine design using virtual technologies and simulators and demanding industrial robotics. The laboratory has collaborated extensively with industrial actors and it has participated in significant international research projects, particularly in the field of robotics. For years, dSPACE tools were the lonely hardware which was used in the lab to develop different control algorithms in real-time. dSPACE's hardware systems are in widespread use in the automotive industry and are also employed in drives, aerospace, and industrial automation. But new competitors are developing new sophisticated systems and their features convinced the laboratory to test new products. One of these competitors is National Instrument (NI). In order to get to know the specifications and capabilities of NI tools, an agreement was made to test a NI evolutionary system. This system is used to control a 1-D hydraulic slider. The objective of this research project is to develop a control scheme for the teleoperation of a hydraulically driven manipulator, and to implement a control algorithm between human and machine interaction, and machine and task environment interaction both on NI and dSPACE systems simultaneously and to compare the results.