Rough set prediction capability was compared with actual auditor signaling rates for a large sample of United States companies from 1991 to 1997 time period. Prior bankruptcy prediction research was carefully reviewed to identify 11 possible predictive factors which had both significant theoretical support and were present in multiple studies. Rough sets theory was used to develop two different bankruptcy prediction models, each containing four variables from the 11 possible predictive variables. In contrast with prior rough sets theory research which suggested that rough sets theory offered significant bankruptcy predictive improvements for auditors, the rough sets models did not provide any significant comparative advantage with regard to prediction accuracy over the actual auditors' methodologies.

The high social costs associated with bankruptcy have spurred searches for better theoretical understanding and prediction capability. In this paper, we investigate a hybrid approach to bankruptcy prediction, using a genetic programming algorithm to construct a bankruptcy prediction model with variables from a rough sets model derived in prior research. Both studies used data from 291 US public companies for the period 1991 to 1997. The second stage genetic programming model developed in this research consists of a decision model that is 80% accurate on a validation sample as compared to the original rough sets model which was 67% accurate. Additionally, the genetic programming model reveals relationships between variables that are not apparent in either the rough sets model or prior research. These findings indicate that genetic programming coupled with rough sets theory can be an efficient and effective hybrid modeling approach both for developing a robust bankruptcy prediction model and for offering additional theoretical insights.

Radio propagation models provide an estimate of the power loss in a communication link caused by the surface of the ground, atmospheric refraction, foliage, and other environmental factors.  Many of the models rely on digital topographic databases to provide information about the terrain, and generally the databases are sparsely sampled relative to the electromagnetic wavelengths used for communication systems.  This work primarily develops a technique to evaluate the effects of that sparsity on the uncertainty of propagation models. That is accomplished by accurately solving the electromagnetic fields over many randomly  rough surfaces which pass through the sparse topographic data points, many possible communication links, all of which fit the underlying data, are represented.  The power variation caused by the different surface realizations is that due to the sparse sampling. Additionally, to verify that this solution technique is a good model, experimental propagation measurements were taken, and compared to the computations. / Master of Science

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第19121号 / 情博第567号 / 新制||情||100(附属図書館) / 32072 / 京都大学大学院情報学研究科複雑系科学専攻 / (主査)教授 木上 淳, 教授 磯 祐介, 教授 西村 直志 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

Atrial fibrillation is one of the most common types of heart arrhythmias, which can cause irregular, weak and fast atrial contractions up to 600 beats per minute. Atrial fibrillation has increased prevalence with age and is associated with increased risks of ischemia, as blood clots can form due to the weak contractions. During prolonged periods of atrial fibrillation, the atria can undergo a process called atrial remodelling. This causes electrophysiological and structural changes to the atria such as increased atrial size and changes to calcium ion densities. These changes themselves promotes the initiation and propagation of atrial fibrillation, which makes early detection crucial. Fortunately, atrial fibrillation can be detected on an electrocardiogram. Electrocardiograms measures the electrical activity of the heart during its cardiac cycle. This includes the initiation of the action potential, the depolarization of the atria and ventricles and their repolarization. On the electrocardiogram recording, these are seen as peaks and valleys, where each peak and valley can be traced back to one of these events. This means that during atrial fibrillation, the weak, irregular and fast atrial contractions can all be detected and measured. The aim of this project was to develop a machine learning model that could predict onset of atrial fibrillation, and that could classify ongoing atrial fibrillation. This was achieved by training one multiclass classification machine learning model using XGBoost, and three binary classification machine learning models using ROSETTA, on electrocardiogram recordings of people with and without atrial fibrillation. XGBoost is a tree boosting system which uses tree-like structures to classify data, while ROSETTA is a rule-based classification model which creates rules in an IF and THEN format to make decisions. The recordings were labelled according to three different classes: no atrial fibrillation, atrial fibrillation or preceding atrial fibrillation. The XGBoost model had a prediction accuracy of 99.3%, outperforming the three ROSETTA models and other atrial fibrillation classification and prediction models found. The ROSETTA models had high accuracies on the learning set, however, the predictions were subpar, indicating faulty settings for this type of data. The results in this project indicate that the models created can be used to accurately classify and predict onset of and ongoing atrial fibrillation, serving as a tool for early detection and verification of diagnosis.

No description available.

No description available.

Leken anses vara en viktig del av barnkulturen och det framhålls i både förskolans läroplan och forskning om hur leken är en betydelsefull del av barns utveckling och lärande. Bråklekar är en del av barnens lek och uppkommer vardagligen i förskolans verksamhet. Hur pedagoger bemöter och hanterar bråklekar kan variera vilket gjorde att vi intresserade oss för hur pedagoger förhåller sig till bråklekar i förskolan. Syftet med den här studien är att studera hur pedagoger förhåller sig till och hanterar bråklekar i förskolan. Frågeställningar som kommer besvaras är vad bråklekar är och hur de kommer till uttryck samt hur pedagogers förhållningssätt till bråklekar ser ut. Vi har valt att utgå ifrån en kvalitativ metod och utfört deltagande observationer samt intervjuer för att undersöka pedagogers förhållningssätt till bråklekar i förskolan. Resultatet i studien visar på att pedagogers förhållningssätt till bråklekar i förskolan är varierande och kan bero på pedagogers olika erfarenheter, kunskaper och intressen. Vi har kommit fram till att pedagoger har svårt för att arbeta med bråklekar i förskolan eftersom bråklekar är mindre omtyckta av föräldrar, pedagoger och samhället. Anledningen till att bråklekar uppkommer kan bero på att barnen får för lite stimulering och att miljön saknar utrymme inomhus på förskolan. Under utomhusobservationer upptäcktes att mindre konflikter uppstod och att pedagogerna tillät mer fysiska lekar jämfört med inomhus. / Playing is considered an important part of children's culture, and it is emphasized in both the pre-school curriculum and research on how play is an important part of children's development and learning. Rough and tumble is a part of children's play and occur everyday in pre-school activities. How pedagogues handle and deal with rough and tumble play can vary, which made us interested in how pedagogues relate to rough and tumble play in preschool. The purpose of this research is to study how pedagogues relate to and handle rough and tumble play in pre-school. Questions that will be answered are what rough and tumble is, how it looks like and how pedagogues approach to rough and tumble play. We have chosen to base our study on a qualitative method and conducted observations as well as interviews to investigate pedagogues approaches to rough and tumble play in pre-schools. The result of the study shows that pedagogues approach to rough and tumble play in pre-school is varied and may depend on pedagogues different experiences, knowledges and interests. We have come to the conclusion that pedagogues are struggling to work with rough and tumble play in preschool, because it is less popular with parents, educators and society. The reason for why rough and tumble play occur may be due to the fact that the children get too little stimulation and that the environment lacks space indoors at the preschool. During outdoor observations we discovered that less conflicts occurred and that the pedagogues allowed more physical play than indoors.

No abstract is provided. / Thesis / Master of Engineering (MEngr) / Scope and contents: This thesis describes an analytical study of the dynamics of a tractor-semitrailer vehicle. Two mathematical models; an articulated vehicle with self steering semitrailer and an articulated vehicle with a standard semitrailer, are developed to describe the longitudinal, lateral, vertical, pitching, rolling and yawing motions of the vehicle on a rough road surface. The natural frequencies of and the damped eigenvalues for both models are calculated. The steady state response of the vehicle components to the sinusoidal input profile of varying frequencies is calculated and the response curves are computer plotted in each case. For the self-steering semitrailer, the effect of varying the spring stiffness at the fifth wheel is studied. The dynamic loads imparted to the pavement due to the dynamic action of the vehicle in response to road irregularities, are also calculated. A discussion of the conclusions drawn from the analysis is given.

No description available.