Classification of Parkinson’s Disease using MultiPass Lvq,Logistic Model Tree,K-Star for Audio Data set : Classification of Parkinson Disease using Audio Dataset

Parkinson's disease (PD) is a degenerative illness whose cardinal symptoms include rigidity, tremor, and slowness of movement. In addition to its widely recognized effects PD can have a profound effect on speech and voice.The speech symptoms most commonly demonstrated by patients with PD are reduced vocal loudness, monopitch, disruptions of voice quality, and abnormally fast rate of speech. This cluster of speech symptoms is often termed Hypokinetic Dysarthria.The disease can be difficult to diagnose accurately, especially in its early stages, due to this reason, automatic techniques based on Artificial Intelligence should increase the diagnosing accuracy and to help the doctors make better decisions. The aim of the thesis work is to predict the PD based on the audio files collected from various patients.Audio files are preprocessed in order to attain the features.The preprocessed data contains 23 attributes and 195 instances. On an average there are six voice recordings per person, By using data compression technique such as Discrete Cosine Transform (DCT) number of instances can be minimized, after data compression, attribute selection is done using several WEKA build in methods such as ChiSquared, GainRatio, Infogain after identifying the important attributes, we evaluate attributes one by one by using stepwise regression.Based on the selected attributes we process in WEKA by using cost sensitive classifier with various algorithms like MultiPass LVQ, Logistic Model Tree(LMT), K-Star.The classified results shows on an average 80%.By using this features 95% approximate classification of PD is acheived.This shows that using the audio dataset, PD could be predicted with a higher level of accuracy.

Identifiering av parametrar till ackumulatortanken Solus1050 från consolar - en metodbeskrivning

This report describes the work done creating a computer model of a kombi tank from Consolar. The model was created with Presim/Trnsys and Fittrn and DF were used to identify the parameters. Measurements were carried out and were used to identify the values of the parameters in the model. The identifications were first done for every circuit separately. After that, all parameters are normally identified together using all the measurements. Finally the model should be compared with other measurements, preferable realistic ones. The two last steps have not yet been carried out, because of problems finding a good model for the domestic hot water circuit.The model of the domestic hot water circuit give relatively good results for low flows at 5 l/min, but is not good for higher flows. In the report suggestions for improving the model are given. However, there was not enough time to test this within the project as much time was spent trying to solve problems with the model crashing. Suggestions for improving the model for the domestic circuit are given in chapter 4.4. The improved equations that are to be used in the improved model are given by equation 4.18, 4.19 and 4.22.Also for the boiler circuit and the solar circuit there are improvements that can be done. The model presented here has a few shortcomings, but with some extra work, an improved model can be created. In the attachment (Bilaga 1) is a description of the used model and all the identified parameters.A qualitative assessment of the store was also performed based on the measurements and the modelling carried out. The following summary of this can be given: Hot Water PreparationThe principle for controlling the flow on the primary side seems to work well in order to achieve good stratification. Temperatures in the bottom of the store after a short use of hot water, at a coldwater temperature of 12°C, was around 28-30°C. This was almost independent of the temperature in the store and the DHW-flow.The measured UA-values of the heat exchangers are not very reliable, but indicates that the heat transfer rates are much better than for the Conus 500, and in the same range as for other stores tested at SERC.The function of the mixing valve is not perfect (see diagram 4.3, where Tout1 is the outlet hot water temperature, and Tdhwo and Tdhw1 is the inlet temperature to the hot and cold side of the valve respectively). The outlet temperature varies a lot with different temperatures in the storage and is going down from 61°C to 47°C before the cold port is fully closed. This gives a problem to find a suitable temperature setting and gives also a risk that the auxiliary heating is increased instead of the set temperature of the valve, when the hot water temperature is to low.Collector circuitThe UA-value of the collector heat exchanger is much higher than the value for Conus 500, and in the same range as the heat exchangers in other stores tested at SERC.Boiler circuitThe valve in the boiler circuit is used to supply water from the boiler at two different heights, depending on the temperature of the water. At temperatures from the boiler above 58.2°C, all the water is injected to the upper inlet. At temperatures below 53.9°C all the water is injected to the lower inlet. At 56°C the water flow is equally divided between the two inlets. Detailed studies of the behaviour at the upper inlet shows that better accuracy of the model would have been achieved using three double ports in the model instead of two. The shape of the upper inlet makes turbulence, that could be modelled using two different inlets. Heat lossesThe heat losses per m3 are much smaller for the Solus 1050, than for the Conus 500 Storage. However, they are higher than those for some good stores tested at SERC. The pipes that are penetrating the insulation give air leakage and cold bridges, which could be a major part of the losses from the storage. The identified losses from the bottom of the storage are exceptionally high, but have less importance for the heat losses, due to the lower temperatures in the bottom. High losses from the bottom can be caused by air leakage through the insulation at the pipe connections of the storage.

Genetic heterogeneity of residual variance : estimation of variance components using double hierarchical generalized linear models

Background: The sensitivity to microenvironmental changes varies among animals and may be under genetic control. It is essential to take this element into account when aiming at breeding robust farm animals. Here, linear mixed models with genetic effects in the residual variance part of the model can be used. Such models have previously been fitted using EM and MCMC algorithms. Results: We propose the use of double hierarchical generalized linear models (DHGLM), where the squared residuals are assumed to be gamma distributed and the residual variance is fitted using a generalized linear model. The algorithm iterates between two sets of mixed model equations, one on the level of observations and one on the level of variances. The method was validated using simulations and also by re-analyzing a data set on pig litter size that was previously analyzed using a Bayesian approach. The pig litter size data contained 10,060 records from 4,149 sows. The DHGLM was implemented using the ASReml software and the algorithm converged within three minutes on a Linux server. The estimates were similar to those previously obtained using Bayesian methodology, especially the variance components in the residual variance part of the model. Conclusions: We have shown that variance components in the residual variance part of a linear mixed model can be estimated using a DHGLM approach. The method enables analyses of animal models with large numbers of observations. An important future development of the DHGLM methodology is to include the genetic correlation between the random effects in the mean and residual variance parts of the model as a parameter of the DHGLM.

Temperature Dynamics Investigation At Small And Shallow Lakes Using Hydrodynamic Model

A three-dimensional time-dependent hydrodynamic and heat transport model of Lake Binaba, a shallow and small dam reservoir in Ghana, emphasizing the simulation of dynamics and thermal structure has been developed. Most numerical studies of temperature dynamics in reservoirs are based on one- or two-dimensional models. These models are not applicable for reservoirs characterized with complex flow pattern and unsteady heat exchange between the atmosphere and water surface. Continuity, momentum and temperature transport equations have been solved. Proper assignment of boundary conditions, especially surface heat fluxes, has been found crucial in simulating the lake’s hydrothermal dynamics. This model is based on the Reynolds Average Navier-Stokes equations, using a Boussinesq approach, with a standard k − ε turbulence closure to solve the flow field. The thermal model includes a heat source term, which takes into account the short wave radiation and also heat convection at the free surface, which is function of air temperatures, wind velocity and stability conditions of atmospheric boundary layer over the water surface. The governing equations of the model have been solved by OpenFOAM; an open source, freely available CFD toolbox. As its core, OpenFOAM has a set of efficient C++ modules that are used to build solvers. It uses collocated, polyhedral numerics that can be applied on unstructured meshes and can be easily extended to run in parallel. A new solver has been developed to solve the hydrothermal model of lake. The simulated temperature was compared against a 15 days field data set. Simulated and measured temperature profiles in the probe locations show reasonable agreement. The model might be able to compute total heat storage of water bodies to estimate evaporation from water surface.

As mudanças na organização da produção na indústria gáfica do Grande ABC: um estudo sobre o segmento off set

O presente trabalho tem por objetivo caracterizar a indústria gráfica do ponto de vista da gestão, tecnologia, inovação e competição. A economia ao longo de sua história foi marcante por alguma situação peculiar que a caracterizasse. Em particular a partir da década de 1960 acompanhamos o crescimento em larga escala na região do Grande ABC onde, a indústria automobilística e seus fornecedores necessitaram de maior estrutura e apoio para as suas operações, provocando alterações nos modos de atuação das empresas industriais no país. Nessa mesma direção pelas necessidades criadas à época, a indústria gráfica na região do ABC também teve seu crescimento para atender a demanda e, criando o caráter da regionalidade e se fortalecendo economicamente. Entretanto a partir da década de 1980 com as crises econômicas e a abertura de mercado, houve uma redução nos postos de trabalho, mas as empresas também alteraram as formas de produzir. O trabalho de campo foi apoiado num referencial teórico baseado na revisão bibliográfica e um roteiro de entrevistas que orientou a coleta de dados. Na presente pesquisa foram realizadas entrevistas com os sujeitos relacionados e verificação de documentos. A análise realizada buscou confrontar os dados coletados e sistematizados com o quadro conceitual utilizado para a elaboração da pesquisa, possibilitando apurar as principais transformações verificadas no segmento estudado, bem como oferecendo embasamento para a tomada de decisão dos atores econômicos envolvidos com o desenvolvimento da indústria gráfica no Grande ABC.

Graphical models and point set matching

Point pattern matching in Euclidean Spaces is one of the fundamental problems in Pattern Recognition, having applications ranging from Computer Vision to Computational Chemistry. Whenever two complex patterns are encoded by two sets of points identifying their key features, their comparison can be seen as a point pattern matching problem. This work proposes a single approach to both exact and inexact point set matching in Euclidean Spaces of arbitrary dimension. In the case of exact matching, it is assured to find an optimal solution. For inexact matching (when noise is involved), experimental results confirm the validity of the approach. We start by regarding point pattern matching as a weighted graph matching problem. We then formulate the weighted graph matching problem as one of Bayesian inference in a probabilistic graphical model. By exploiting the existence of fundamental constraints in patterns embedded in Euclidean Spaces, we prove that for exact point set matching a simple graphical model is equivalent to the full model. It is possible to show that exact probabilistic inference in this simple model has polynomial time complexity with respect to the number of elements in the patterns to be matched. This gives rise to a technique that for exact matching provably finds a global optimum in polynomial time for any dimensionality of the underlying Euclidean Space. Computational experiments comparing this technique with well-known probabilistic relaxation labeling show significant performance improvement for inexact matching. The proposed approach is significantly more robust under augmentation of the sizes of the involved patterns. In the absence of noise, the results are always perfect.

The set of equilibria of first-price auctions

In this note I specify the class of functions that are equilibria of symmetric first-price auctions.