Recommender System (RS) has become one of the most important component for many companies, such as YouTube and Amazon. A recommender system consists of a series of algorithms which predict and recommend products to users. This report covers the selection of many open source recommender system projects, and movie predictions are made using the selected recommender system. Based on the predictions, a comparison was made between precision and an improved precision algorithm. The selected RS uses singular value decomposition in the field of collaborative filtering. Based on the recommendation results produced by the RS, the comparison between precision and the improved precision algorithms showed that the result of improved precision is slightly higher than precision in different cutoff values and different dimensions of eigenvalues. / Rekommendationssystem har blivit en av de viktigaste beståndsdelar för många företag, såsom YouTube och Amazon. Ett rekommendationssystem består av en serie av algoritmer som förutsäger och rekommenderar produkter till användare. Denna rapport omfattar valet av många öppen källkod rekommendationssystem projekt, och filmprognoser görs med det valda rekommendationssystemet. Baserat på filmprognoser, gjordes en jämförelse mellan precision och en förbättrad precision algoritmer. Det valda rekommendationssystemet använder singulärvärdesuppdelning som kollaborativ filtrering. Baserat på rekommendationsresultat som produceras av rekommendationssystemet, jämförelsen mellan precision och den förbättrade precisions algoritmer visade att resultatet av förbättrad precision är något högre än precision i olika brytvärden och olika dimensioner av egenvärden.

Climate variability is important to understand as its effects on groundwater are complex than surface water. Climate association between Groundwater Storage (GWS) and sea level changes have been missing from the Intergovernmental Panel on Climate Change, demanding a requisite study of their linkage and responses. The current dissertation is primarily focused on the ongoing issues that have not been focused on the previous literatures. Firstly, the study evaluated the effects of short-term persistence and abrupt shifts in sea level records along the US coast by utilizing popular robust statistical techniques. Secondly, the study evaluated the variability in groundwater due to variability in hydroclimatic variables like sea surface temperature (SST), precipitation, sea level, and terrestrial water storage. Moreover, a lagged correlation was also analyzed to obtain their teleconnection patterns. Lastly, the relationship between the groundwater rise and one of the most common short-term climate variability, ENSO was obtained. To accomplish the research goals the current dissertation was subdivided into three research tasks.The first task attempted to answer a major question, Is sea level change affected by the presence of autocorrelation and abrupt shift? This question reflects the importance of trend and shift detection analysis in sea level. The primary factor driving the global sea level rise is often related to climate change. The current study investigates the changes in sea level along the US coast. The sea level records of 59 tide gauge data were used to evaluate the trend, shift, and persistence using non-parametric statistical tests. Mann-Kendall and Pettitt’s tests were utilized to estimate gradual trends and abrupt shifts, respectively. The study also assessed the presence of autocorrelation in sea level records and its effect on both trend and shift was examined along the US coast. The presence of short-term persistence was found in 57 stations and the trend significance of most stations was not changed at a 95% confidence level. Total of 25 stations showed increasing shift between 1990–2000 that was evaluated from annual sea level records. Results from the current study may contribute to understanding sea level variability across the contiguous US. The second task dealt with variability in the Hydrologic Unit Code—03 region. It is one of the major U.S. watersheds in the southeast in which most of the variability is caused by Sea Surface Temperature (SST) variability in the Pacific and Atlantic Ocean, was identified. Furthermore, the SST regions were identified to assess its relationship with GWS, sea level, precipitation, and terrestrial water storage. Temporal and spatial variability were obtained utilizing the singular value decomposition statistical method. A gridded GWS anomaly from the Gravity Recovery and Climate Experiment (GRACE) was used to understand the relationship with sea level and SST. The negative pockets of SST were negatively linked with GWS. The identification of teleconnections with groundwater may substantiate temporal patterns of groundwater variability. The results confirmed that the SST regions exhibited El Niño Southern Oscillation patterns, resulting in GWS changes. Moreover, a positive correlation between GWS and sea level was observed on the east coast in contrast to the southwestern United States. The findings highlight the importance of climate-driven changes in groundwater attributing changes in sea level. Therefore, SST could be a good predictor, possibly utilized for prior assessment of variabilities plus groundwater forecasting. The primary goal of the third task is to better understand the effects of ENSO climate patterns on GWS in the South Atlantic-Gulf region. Groundwater issues are complex and different studies focused on groundwater depletion while few emphasized, “groundwater rise”. The current research is designed to develop an outline for assessing how climate patterns can affect groundwater fluctuation, which might lead to groundwater rise. The study assessed the effect of ENSO phases on spatiotemporal variability of groundwater using Spearman Rank Correlation. A significant positive correlation between ENSO and GWS was observed. An increasing trend was detected in GWS where most grids were observed in Florida by utilizing the non-parametric Mann-Kendall. A positive magnitude of the trend was also detected by utilizing Theil-Sen’s Slope method with high magnitude in the mid-Florida region. The highest GWS anomalies were observed in the peak of El Niño events and the lowermost GWS was observed during La Niña events. Furthermore, most of the stations were above normal groundwater conditions. This study provides a better understanding of the research gap between groundwater rise and ENSO.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第17968号 / 情博第512号 / 新制||情||91(附属図書館) / 30798 / 京都大学大学院情報学研究科数理工学専攻 / (主査)教授 中村 佳正, 教授 西村 直志, 准教授 山下 信雄 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

The current research investigates the use of solid-embedded thermocouples for determining accurate transient temperature measurements within a solid medium, with emphasis on measurements intended for use in inverse heat conduction problems. Metal casting experiments have been conducted to collect internal mold temperatures to be used, through inverse conduction methods, to estimate the heat exchange between a casting and mold. Inverse conduction methods require accurate temperature measurements for valid boundary estimates. Therefore, various sources of thermocouple measurement uncertainty are examined and some suggestions for uncertainty reduction are presented. Thermocouple installation induced bias uncertainties in experimental temperature data are dynamically corrected through the development and implementation of an embedded thermocouple correction (ETC) transfer function. Comparisons of experimental data to dynamically adjusted data, as well as the inverse conduction estimates for heat flux from each data set, are presented and discussed.

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Yes / Voltage instability problems in power system is an important issue that should be taken into consideration during the planning and operation stages of modern power system networks. The system operators always need to know when and where the voltage stability problem can occur in order to apply suitable action to avoid unexpected results. In this paper, a study has been conducted to identify the weakest bus in the power system based on multi-variable control, modal analysis, and Singular Value Decomposition (SVD) techniques for both static and dynamic voltage stability analysis. A typical IEEE 3-machine, 9-bus test power system is used to validate these techniques, for which the test results are presented and discussed.