No description available.

京都大学 / 0048 / 新制・論文博士 / 博士(理学) / 乙第13375号 / 論理博第1574号 / 新制||理||1666(附属図書館) / 京都大学大学院理学研究科 / (主査)教授 飯尾 能久, 教授 岩田 知孝, 教授 久家 慶子 / 学位規則第4条第2項該当 / Doctor of Science / Kyoto University / DGAM

Results from prospective studies examining associations between sleep duration and weight gain have been mixed. Melatonin has been hypothesized to mediate the association between sleep duration and weight/body composition. In cross-sectional studies, aMT6s has been shown to be inversely associated with weight/body fat percentage. We examined associations between baseline sleep duration, insomnia status, aMT6s levels with weight/body fat percentage through 6 years, utilizing a subset 690 women who participated in a breast cancer case-control study nested within the WHI-OS. Multi-variable and mixed-effects regression was used to calculate beta-coefficients and 95% confidence intervals. Cross-sectional analyses showed urinary aMT6s levels were inversely associated with BMI and body fat percentage. No associations were observed between sleep patterns and measures of adiposity. The prospective relationship between urinary aMT6 levels and weight/body fat percentage was complex. Age-adjusted mixed models show an association in the interaction term between year and aMT6s with body fat percentage (βinteraction:0.09, pinteraction:0.16, p=0.07), demonstrating the influence of baseline aMT6s and time on changes in outcome. Women with higher baseline aMT6s had a trajectory of increased body fat percentage and weight gain steepest between baseline and year 3, whereas women with lower baseline aMT6 levels had a trajectory of decreased body fat percent and weight between year 3 and year 6. The prospective association between melatonin levels and adiposity measures was unexpected. Future studies with objective measures of sleep and repeated measures of melatonin may shed light of possible explanations for our findings.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第23178号 / 工博第4822号 / 新制||工||1753(附属図書館) / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 山田 忠史, 教授 藤井 聡, 准教授 SCHMOECKER Jan-Dirk / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

No description available.

This thesis deals with lasers, their general theory and application. Then a theoretical part describes laser micromachining and engraving. Experimental part of thesis deals with several experiments performed by powered fibre laser which is not primarily intended for the field of micromachining. Experiments were mainly evaluated by several types of microscopes where the amount of removed material was appraised. By particular experiments removed material was in accordance with used working parameters of laser and a significant role plays machining material. It emerges from the experiments that for the field of laser micromachining and engraving shorter pulses are more suitable (minimal pulse duration was 1 ms in experiment) and it is connected even with a way of removing material. Applied powered laser can be used for micromachining in specific fields of production.

MAAS / MER Mathivha Centre for African Languages, Arts and Culture

The research concerning differences in duration of the Great Recession is limited and inconclusive. We define duration of crisis as the count of years lost due to the crisis, and estimate the determinants of crisis duration on the dataset of 54 developed and developing countries. This thesis contrasts with previous literature by employing Bayesian Model Averaging (BMA) to accommodate for the large amount of potential explanatory variables and to address model uncertainty. Moreover, an innovative measure of export competitiveness, which accounts for the changes in non-price factors such as quality, is used. The results bring suggestive evidence of positive impact of developed financial markets, high share of private consumption and improvements in export competitiveness. We also find positive effect of fiscal policy stimulus once it is controlled for the feedback loop of uncertainty which appears when heavily indebted countries finance fiscal stimulus through issuance of additional debt. Lastly, it needs to be concluded, that the results are not robust to all prior specifications. In particular, the more restrictive Beta binomial model prior shrinks the statistical significance of aforementioned results heavily. JEL Classification F12, F21, F23, H25, H71, H87 Keywords Great Recession, Crisis duration, Economic...

Background. Machine learning technology is used daily in many aspects of computers. Neural network is a machine learning technique. The importance of carsthat are self driving has increased in recent years and the research about it has alsoincreased. Some cars that are produced today already have an autopilot feature inthem. Objectives. In this thesis the objective is to find how the training duration of aneural network changes, when the track becomes harder and harder. Methods. To achieve this a small game and a neural network was developed inUnity. The neural network receive input from 5 sensors and gave 2 outputs, an angleand a velocity. The neural network will be trained in the game on 4 different tracks,each with one more obstacle than the last one. The neural network will generatetwenty cars that will drive simultaneously to the end of the track. If a car collidewith a wall, it gets destroyed. When all cars are destroyed a new generation is generated based on the 2 cars that got destroyed last. Results. The first track was finished in 8,3 seconds, the second track in 28,9 secondsand that is a 248% increase from the first track. The third track was finished in 44,5seconds and that is a 54% increase from the second track. Fourth track were finishedin 39,9 seconds and that was a 10,3% decrease in time. Conclusions. In conclusion the training duration increased from track 1 to track2. from track 2 to track 3 and 4 the increase is presumed to be because the trackis larger and because of the speed output from the neural network. The trainingduration does change, but the change corresponds with the change of the length ofthe track.

<p>U okviru ove disertacije razvijeno je više različitih modela trajanja glasova u srpskom jeziku primenom odgovarajućih metoda automatskog učenja. Izvršena je objektivna evaluacija razvijenih modela i njihovo međusobno poređenje na osnovu kvantitativnih pokazatelja kao što su RMSE(engl. root-mean-squared error), MAE (engl. mean absolute error) i CC (engl. correlation coefficient). Takođe je izvršeno poređenje modela za srpski jezik sa performansama modela razvijenih za druge jezike, pri čemu je uočeno da su performanse modela razvijenih u ovoj disertaciji uporedljive ili čak prevazilaze performanse modela koji su razvijeni za druge jezike.</p> / <p>In this dissertation several different phone duration models of the Serbain<br />language using appropriate machine learning algorithms were developed.<br />The objective evaluation of the models obtained and their mutual comparison<br />based on quantitative measures such as RMSE (root-mean-squared error),<br />MAE (mean absolute error) and CC (correlation coefficient) were performed.<br />The comparison of the models developed for the Serbian language with the<br />performances of the models developed for other languages is also carried<br />out. It was observed that the performances of the models developed in this<br />dissertation are comparable or even outperform the performances of the<br />models that have been developed for other languages.</p>