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.

Brytmånens utformning vid trädfällning - Jämförande studier av böjmotstånd och gångjärnseffekt : Designing felling hinge in tree felling - Comparative studies of bending resistance and hinge effect

Vid trädfällning med motorsåg sparar man en så kallad brytmån som skall fungera som ett gång¬järn när trädet fälls. Om brytmånen går av tidigt finns en risk att trädet faller okontrolle¬rat. De rekommendationer som finns säger att brytmånens bredd skall göras proportionell mot trädets diameter. Genom att teoretiskt och praktiskt undersöka vilka krafter brytmånen utsätts för och vad den håller för har det varit möjligt att dra vissa slutsatser om hur en bra brytmån skall se ut. Ett viktigt resultat är att en bred brytmån (över 30-40 mm) är mycket trög att böja och inte fungerar i det avseendet att den går av redan vid små böjningar. Teoretiska be¬räkningar och praktiska försök visar att en relativt smal brytmån håller för belastningen vid rakt motlut även på stora träd. Som ny rekommendationen föreslås att brytmånens bredd inte bör vara mer än 30 mm. Av försöken kan man också dra slutsatsen att frusen ved är stel och brister tidigt, varför svår¬fällda träd inte bör fällas när veden är fryst.A felling hinge is used when felling trees by help of chain saw. If the hinge breaks early in the fall of the tree there is a great risk that the tree will fall without control. Present recommenda¬tions in Sweden say that the thickness of the felling hinge shall be made in proportion to the stem diameter. By use of theoretical and practical examinations of the forces stressing the felling hinge, and the strength of the wood itself, it has been possible to draw conclusions regarding the correct design of a felling hinge. One important result is that a thick felling hinge (over 30-40 mm) is very hard to bend and does not work well as it looses most of its strength already at a small forward bending angel. Theoretical calculations and practical tests show that a relatively narrow felling hinge will manage very well the forces when felling trees with lean opposite to the felling direction even for large trees. Our new recommendation is that the thickness of the felling hinge in normal Swedish conditions should not exceed 30 mm. Through the studies it can also be seen that frozen, brittle wood breaks at small bending angels. For that reason particularly difficult trees not should be felled when the wood is frozen.