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.

Frihet i handläggningsarbetet? : En studie om handläggarnas handlingsutrymme vid beslut i sjukförsäkringsärenden på Försäkringskassan

Syftet med vår uppsats var att få en djupare insikt i och kunskap om hur de människor som arbetar med försäkringsärenden på Försäkringskassan upplever och ser på sitt arbete. Våra frågeställningar söker svaret på hur handläggarna uppfattar sina möjligheter till egna initiativ i handläggningsarbetet. För att få svar på dessa frågor från ett ”inifrånperspektiv” har vi valt att hämta empirin från en fokusgruppintervju med fyra tjänstemän som arbetar med handläggning på en Försäkringskassa i Mellansverige. Vårt teoretiska utgångsläge var Johan Asplunds teori om den sociala responsiviteten och Roine Johanssons teori om organisatoriska begränsningar i kundrelaterat arbete. En annan utgångspunkt för vår studie har varit tidigare forskning inom områden som berör Försäkringskassan. Vi har genom vår studie kommit fram till att den teori som Roine Johansson tar upp om handläggningsutrymme bekräftas utifrån de slutsatser vi dragit från vår analys. Den sociala relationen som utspelas mellan handläggarna i det dagliga arbetet får sin förklaring genom Asplunds teori om den socialt responsiva människan och ger upphov till en intern policy som formar ärendehanteringen för lokalkontoret på ett specifikt sätt. Vi har kommit fram till att det finns ett handlingsutrymme i Försäkringskassan som grundar sig på interna överenskommelser och egna initiativ i arbetet. Detta bekräftas av Roine Johanssons teori om handlingsutrymme inom Försäkringskassans arbetsområde.

Prospective teachers’ conceptions of what characterize a gifted student in mathematics

This paper explores Swedish prospective teachers’ conceptions of what characterise a gifted student in mathematics. This was studied through a qualitative questionnaire focusing on attributions. The results show that a majority of the students attribute intrinsic motivation to gifted students, more often than extrinsic motivation. Other themes were other affective factors (e.g. being industrious), cognitive factors (e.g. easy to learn), and social factors such as good behaviour and background.

The effects of attitudes and personality traits on mode choice

We hypothesise that differences in people's attitudes and personality traits lead them to attribute varying importance to environmental considerations, safety, comfort, convenience and flexibility. Differences in personality traits call be revealed not only in the individuals' choice of transport, but also in other actions of their everyday lives-such as how much they recycle, whether they take precautions or avoid dangerous pursuits. Conditioning on a set of exogenous individual characteristics, we use indicators of attitudes and personality traits to form latent variables for inclusion in an, otherwise standard, discrete mode choice model. With a sample of Swedish commuters, we find that both attitudes towards flexibility and comfort, as well as being pro-environmentally inclined, influence the individual's choice of mode. Although modal time and cost still are important, it follows that there are other ways, apart from economic incentives, to attract individuals to the, from society's perspective, desirable public modes of transport. Our results should provide useful information to policy-makers and transportation planners developing sustainable transportation systems.