京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第18701号 / 情博第551号 / 新制||情||97(附属図書館) / 31634 / 京都大学大学院情報学研究科知能情報学専攻 / (主査)教授 阿久津 達也, 教授 山本 章博, 教授 岡部 寿男 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

Sidewalks provide many community services, yet not much geospatial research exists regarding sidewalks, especially in Mississippi. The purpose of this thesis was to use geographic information systems to inventory and map sidewalks for Starkville, MS and to compare sidewalk availability and quality to 2010 US census block demographics. In Starkville, sidewalks served 28% of the census block population, which classifies the city as “Car-Dependent” according to a Walk Score criteria. Majority minority census blocks and majority white census blocks had similar proportions of sidewalks. However, 97% of “Excellent” quality and 64 more sections of ADA compliant sidewalks were within majority white census blocks or commercial census blocks. Residential census blocks, especially majority minority blocks, have 26% less connectivity and an overall less dense sidewalk network. Starkville sidewalks have greatly improved since initial construction, but it seems that the current sidewalk infrastructure still reflects historical settlement and zoning patterns.

No description available.

Indiana University-Purdue University Indianapolis (IUPUI) / Up-to-date and accurate information on soil properties is important for precision farming and environmental management. The spatial information of soil properties allows adjustments of fertilizer applications to be made based on knowledge of local field conditions, thereby maximizing agricultural productivity and minimizing the risk of environmental pollution. While conventional soil sampling procedures are labor-intensive, time-consuming and expensive, remote sensing techniques provide a rapid and efficient tool for mapping soil properties. This study aimed at examining the capacity of hyperspectral reflectance data for mapping soil organic matter (SOM), total nitrogen (N) and total phosphorus (P). Soil samples collected from Eagle Creek Watershed, Cicero Creek Watershed, and Fall Creek Watershed were analyzed for organic matter content, total N and total P; their corresponding spectral reflectance was measured in the laboratory before and after oven drying and in the field using Analytical Spectral Devices spectrometer. Hyperion images for each of the watersheds were acquired, calibrated and corrected and Hyperion image spectra for individual sampled sites were extracted. These hyperspectral reflectance data were related to SOM, total N and total P concentration through partial least squares (PLS) regressions. The samples were split into two datasets: one for calibration, and the other for validation. High PLS performance was observed during the calibration for SOM and total N regardless of the type of the reflectance spectra, and for total P with Hyperion image spectra. The validation of PLS models was carried out with each type of reflectance to assess their predictive power. For laboratory reflectance spectra, PLS models of SOM and total N resulted in higher R2 values and lower RMSEP with oven-dried than those with field-moist soils. The results demonstrate that soil moisture degrades the performance of PLS in estimating soil constituents with spectral reflectance. For in-situ field spectra, PLS estimated SOM with an R2 of 0.74, N with an R2 of 0.79, and P with an R2 of 0.60. For Hyperion image spectra, PLS predictive models yielded an R2 of 0.74 between measured and predicted SOM, an R2 of 0.72 between measured and predicted total N, and an R2 of 0.67 between measured and predicted total P. These results reveal slightly decreased model performance when shifting from laboratory-measured spectra to satellite image spectra. Regardless of the spectral data, the models for estimating SOM and total N consistently outperformed those for estimating total P. These results also indicate that PLS is an effective tool for remotely estimating SOM, total N and P in agricultural soils, but more research is needed to improve the predictive power of the model when applied to satellite hyperspectral imagery.

Charles University in Prague, Faculty of Pharmacy in Hradec Králové Department of Biophysics and Physical Chemistry Candidate: Iveta Voborníková Thesis supervisor: doc. Dipl.-Math. Erik Jurjen Duintjer Tebbens, Ph.D. Title of diploma thesis: Matrix computations for mixtures and solutions In this work, we determined drug concentrations from mixtures using multicompo- nent analysis without separating them. The condition was the knowledge of the molar absorption coefficients of individual drugs for certain wavelenghts. To do this, we used tools from matrix calculations, especially the Moore-Penrose inverse, and we were in- terested in whether we would achieve more accurate results using standard, square systems or overdetermined systems of linear equations. Based on the results, we came to the conclusion that there is no dependence between the accuracy of the results and the number of wavelengths used. Only in some cases did the results appear to be more accurate when using overdetermined systems with a higher number of wavelengths. Keywords: mixtures, solutions, linear systems, least squares problems, Moore-Penrose pseudoinverses 1

This thesis is a study of the spatial reconstruction of public space in the locality of Brno Bronx. The work includes several large urban and social problems. This is the solution of problems socially excluded areas, the issue of coexistence with ethnic minorities and on brownfields and solving the appropriate forms of gentrification problem area. The proposal addresses the biggest block permeability, which is lined streets of Bratislavská, Hvězdová, and Francouzská. It proposes a new structure of public spaces - squares, which are strung like beads on the newly proposed network of streets. Also engaged in the creation of public space in the vicinity of the former jail. The proposal by removing extensions provide a space for two new squares. Creative square and Square of Roma culture. With the completion of new buildings should be supported by a square and revealed the original appearance of the former jail.

Wireless communications systems are used today in a variety of milieux, with a recurring theme: users and applications regularly require higher throughput. Multiple antennas enable higher throughput and/or more robust performance than single-antenna communications, with no increase in power or frequency bandwidth. Systems are required which achieve the full potential of this "space-time" communication channel under the significant challenges of time-varying fading, multiple users, and the choice of appropriate coding schemes. This dissertation is focused on solutions to these problems. For the single-user case, there are many well-known coding techniques available; in the first part of this dissertation, the performance of two of these methods are analyzed. Trained and differential modulation are simple coding techniques for single-user time-varying channels. The performance of these coding methods is characterized for a channel having a constant specular component plus a time-varying diffuse component. A first- order auto-regressive model is used to characterize diffuse channel coefficients that vary from symbol to symbol, and is shown to lead to an effective SNR that decreases with time. A lower bound on the capacity of trained modulation is found for the specular/diffuse channel. This bound is maximized over the training length, training frequency, training signal, and training power. Trained modulation is shown to have higher capacity than differential coding, despite the effective SNR penalty of trained modulation versus differential methods. The second part of the dissertation considers the multi-user, multi-antenna channel, for which capacity-approaching codes were previously unavailable. Precoding with the channel inverse is shown to provide capacity that approaches a constant as the number of users and antennas simultaneously increase. To overcome this limitation, a simple encoding algorithm is introduced that operates close to capacity at sum-rates of tens of bits/channel-use. The algorithm is a variation on channel inversion that regularizes the inverse and uses a "sphere encoder" to perturb the data to reduce the energy of the transmitted signal. Simulation results are presented which support our analysis and algorithm development.

A dimensionally compatible system of equations for stand basal area, volume, and basal area and volume growth was derived using dimensional analysis. These equations are analytically and numerically consistent with dimensionally compatible individual tree volume and taper equations and share parameters with them. Parameters for the system can be estimated by fitting individual tree taper and volume equations or by fitting stand level basal area and volume equations. In either case the parameters are nearly identical. Therefore, parameters for the system can be estimated at the tree or stand level without changing the results. Data from a thinning study in loblolly pine (Pinus taeda L.) plantations established on cutover site-prepared lands were used to estimate the parameters. However, the developed system of equations is general and can be applied to other tree species in other locales. / Ph. D.

The field of personalized product recommendation systems has seen tremendous growth in recent years. The usefulness of the algorithms’ abilities to filter out data from vast sets has been shown to be crucial in today’s information-heavy online experience. Our goal is therefore to compare two recommender models, one based on Random Indexing, the other on Collaborative Filtering, in order to find out if one is better suited to the task than the other. We bring up relevant previous research to set the context for our study, its limitations and possibilities. We then explain the theories, models and algorithms underlying our two recommender systems and finally we evaluate them, partly through empirical data collection from our employer Kavall’s platform, and partly through analysing data from interviews. We judge that our study is scientifically relevant as it compares an algorithm that is rarely used in this context, Random Indexing, to a more established recommendation algorithm, Collaborative Filtering, and as such the result of this comparison might give useful insights into the further development of new or existing algorithms. While more testing is required, the study did show signs that Random Indexing does have the potential of outperforming Collaborative Filtering in some areas, and further development of the model might be a worthwhile endeavor. / Området för personliga produktrekommendationer har sett en enorm tillväxt under de senaste Åren. Användbarheten av algoritmernas förmåga att filtrera ut data ur stora uppsättningar har visat sig vara avgörande i dagens informationstunga onlineupplevelse. Vårt mål Är därför att jämföra två rekommendatormodeller, en baserad på Random Indexing, den andra på Collaborative Filtering, för att ta reda på om den ena Är bättre lämpad för uppgiften Än den andra. Vi tar upp relevant tidigare forskning för att sätta sammanhanget för vår studie, dess begränsningar och möjligheter. Vi förklarar sedan de teorier, modeller och algoritmer som ligger till grund för våra två rekommendationssystem och slutligen utvärderar vi dem, dels genom empirisk datainsamling från vår arbetsgivare Kavalls plattform, dels genom att analysera data från intervjuer. Vi bedömer att vår studie Är vetenskapligt relevant då den jämför en algoritm som sällan används i detta sammanhang, Random Indexing, med en mer etablerad rekommendationsalgoritm, Collaborative Filtering, och som sådan kan resultatet av denna jämförelse ge användbara insikter i den fortsatta utvecklingen av nya eller befintliga algoritmer. även om fler tester krävs, visade studien tecken på att Random Indexing har potentialen att överträffa Collaborative Filtering på vissa områden, och vidareutveckling av modellen kan vara ett givande åtagande.

A Kaizen event (KE) may be defined as a structured improvement project that uses a cross-functional team and specific improvement goals to improve a targeted work area or process in an accelerated time frame. KEs, also known as Rapid Improvement Events (RIEs), have been utilized within hospitals to achieve beneficial operations, stakeholder (i.e., social), financial, and clinical outcomes. Due to their potential to achieve positive results in a rapid timeframe, understanding the determinants of KE success within a hospital environment is a valuable research undertaking. To date there has been limited rigorous empirical quantitative research focused on identifying success factors (SFs) influencing socio-technical outcomes of hospital-based KEs. Hence, this empirical research study seeks to determine the critical success factors (CSFs) for KEs in hospitals. For the first phase of this research work, a comprehensive systematic literature review (SLR) was conducted to identify the success factors (SFs) for KEs in hospitals as reported in the literature. This SLR resulted in the identification of 54 unique success factors mapping to four broad success factor categories, KE Task Design, KE Team Design, Organization, and KE Process. Thereafter, the second phase, which involved the variable reduction process, was performed to determine the strength of effect, or importance, of the SFs in order to determine a feasible number of SFs to include in further empirical work. Two robust methods were applied; a Meta-synthesis Evaluation and an Expert Survey, to query the SFs and to determine high priority factors for the empirical study. As a result, a total of 30 factors were finalized for empirical study. Next, the last phase, the empirical study to investigate and determine the CSFs for KEs in hospitals, was executed using a retrospective field study survey research design. Specifically, a survey questionnaire was designed to elicit feedback on perceptual measures from targeted hospital KE facilitators/leaders on the criticality of SFs on socio-technical outcomes for KEs in hospitals. Sixty usable responses were obtained, which were subjected to Exploratory Factor Analysis (EFA) and Partial Least Squares-Structural Equation Modeling (PLS-SEM), which were used to identify latent factor constructs and to determine the significance of the SFs, respectively. The results of this study identified seven significant direct relationships. Kaizen Event Design Characteristics (KEDC) and Target Area Buy-in (TABI) were found to have significant direct effects with both dependent variables, Performance Impact (PI) and Growth in Kaizen Capabilities (KCG). In addition, KEDC also had a significant direct relationship with Performance Culture (PC) and Team Dynamics (TD), respectively. Also, PC has a significant direct relationship with TD. Furthermore, Logistic Regression was utilized to test the SFs impact on the one objective technical outcome measure in the study, Goal Attainment (GOALATT). This analysis revealed one significant negative relationship occurring between TD and GOALATT. Overall, the study's findings provide evidence-based results for informing hospital managers, leaders, and continuous improvement practitioners on the key factors or value-added practices that can be adopted in their hospital KE initiatives to achieve beneficial socio-technical outcomes, as well as overall hospital KE success. Furthermore, this research can enable academia/researchers to strategize more confirmatory analysis approaches for theory validation and generalizability. / Doctor of Philosophy / The focus of this research study is to identify the most significant factors for Kaizen events (KEs) in hospitals, referred herein as critical success factors (CSFs). A KE may be defined as a structured improvement project that uses a cross-functional team and specific improvement goals to improve a targeted work area or process in an accelerated time frame. The aim of the study is to ultimately improve KE practice in hospitals through increased understanding of CSFs that can be planned or designed into KE processes to increase the likelihood of successful event outcomes. Various research formulation, development, and testing techniques are applied to frame the research study according to the aims and objectives and to achieve targeted research outcomes. The overall research design encompasses a retrospective study approach, performing a large-scale field study using a survey questionnaire to empirically identify the CSFs for KEs in hospitals. To help frame the research, a systematic literature review (SLR) along with bibliometric analyses were conducted. To help refine and select the success factors for empirical study, a meta-synthesis evaluation and an expert survey study were conducted. Exploratory factor analysis (EFA) and partial least squares-structural equation modeling (PLS-SEM) along with mediation analyses (MA) were performed to identify key factors, determine the significance of those factors, and to understand the influential relationships of those factors to hospital KE success. Results from this study aim to inform healthcare managers, healthcare improvement practitioners, researchers, and other relevant stakeholders about the critical components needed to achieve hospital KE success. The dissertation is documented according to a "manuscript style," using a journal/conference paper format to organize and report on the key findings and results obtained from the investigation. The Introduction chapter is provided to introduce the research study topic, study significance, indicate the overall research aims and objectives, present the overall research approach and design methodology, and to enumerate the main publication outputs and outcomes from this dissertation work. The Conclusions chapter summarizes the overall research outcomes, key study findings, study limitations, and provides areas for future research.