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.