Three-dimensional block matching using orthonormal tree-structured haar transform for multichannel images

Multichannel images, i.e., images of the same object or scene taken in different spectral bands or with different imaging modalities/settings, are common in many applications. For example, multispectral images contain several wavelength bands and hence, have richer information than color images. Multichannel magnetic resonance imaging and multichannel computed tomography images are common in medical imaging diagnostics, and multimodal images are also routinely used in art investigation. All the methods for grayscale images can be applied to multichannel images by processing each channel/band separately. However, it requires vast computational time, especially for the task of searching for overlapping patches similar to a given query patch. To address this problem, we propose a three-dimensional orthonormal tree-structured Haar transform (3D-OTSHT) targeting fast full search equivalent for three-dimensional block matching in multichannel images. The use of a three-dimensional integral image significantly saves time to obtain the 3D-OTSHT coefficients. We demonstrate superior performance of the proposed block matching

Economic effects analysis of public investment in road improvement works in Hokkaido. Simulation analysis based on a macro-econometric model of Hokkaido

The objective of this study is to clarify how public investment in road improvement projects over a given analytical period of time has affected Hokkaido`s economic structure on the whole in relation to the industrial economy, prefectural income, household consumption, and commodity prices, through a simulation analysis based on a macro-econometric model. More specifically, our goal is to model both the direct effects achieved through the use of improved roads including the reduction of time-distance coefficients, the reduction of transportation costs and market expansion, and the indirect effects such as enhancement of lifestyles and convenience and influence on other public projects including living area improvement and promotion of regional areas, and to identify these effects quantitatively. Taking data availability into consideration, this study covers a 21-year analysis period covering the years 1976 through 1996. In constructing a quantitative model, the effect flow to be modeled was examined from two perspectives: 1) an effect flow showing the effects of road improvement works on production efficiency and market efficiency; and 2) an effect flow showing the effects of road improvement works on living standards considering convenience and lifestyle improvement. Then we attempted building a model that could indicate the occurrence of these effects in both Flow and Stock contexts. As a result of the simulation analysis, it was clarified that application of road improvement works would bring about pronounced positive economic benefits in tertiary industries, particularly in the transportation-service and wholesale/retail sectors, and greatly expand the prefectural net product on the whole. It was also revealed that these expansion effects would stimulate an increase in the prefectural income and in private final consumption expenditure. Furthermore, a simulation analysis on the economic effects that the expansion of the express-highway network would have on Hokkaido`s entire economy revealed that there would be a large effect particularly on investment and production within the transportation/communication industry and also on the commercial output of the wholesale/retail industry.

Regional differences in the incidence of severe brain damage in survivors with cardiac disease and witnessed out-of-hospital cardiac arrest

Background: Brain damage can occur after out-of-hospital cardiac arrest (OHCA) leading to permanent disability.Aims: This study investigated the incidence of severe brain damage and associated risk factors in survivors with cardiac disease after OHCA.Methods: The Utstein database for Japan was used to identify 23,640 survivors with cardiac disease and witnessed OHCA between 2005 and 2012. Survivors were assessed at 1 month. Odds ratios (ORs) for the incidence of severe brain damage according to regional variables were determined with logistic regression analysis.Results: The incidence of severe brain damage was 37.3%. Automated external defibrillator use and cardiopulmonary resuscitation were associated with significant improvement in cerebral function; adrenaline administration and longer duration from request for transport until hospital arrival were associated with deterioration of cerebral function. Twenty of 47 prefectures showed significant ORs for the incidence of severe brain damage.Conclusion: Regional differences in the incidence of severe brain damage were found among survivors with cardiac disease and witnessed OHCA

Deep Recurrent Factor Model: Interpretable Non-Linear and Time-Varying Multi-Factor Model

A linear multi-factor model is one of the most important tools in equity portfolio management. The linear multi-factor models are widely used because they can be easily interpreted. However, financial markets are not linear and their accuracy is limited. Recently, deep learning methods were proposed to predict stock return in terms of the multi-factor model. Although these methods perform quite well, they have significant disadvantages such as a lack of transparency and limitations in the interpretability of the prediction. It is thus difficult for institutional investors to use black-box-type machine learning techniques in actual investment practice because they should show accountability to their customers. Consequently, the solution we propose is based on LSTM with LRP. Specifically, we extend the linear multi-factor model to be non-linear and time-varying with LSTM. Then, we approximate and linearize the learned LSTM models by LRP. We call this LSTM+LRP model a deep recurrent factor model. Finally, we perform an empirical analysis of the Japanese stock market and show that our recurrent model has better predictive capability than the traditional linear model and fully-connected deep learning methods.Comment: In AAAI-19 Workshop on Network Interpretability for Deep Learnin

Comparative Study of the Effectiveness of Oral Fluconazole and Intravaginal Clotrimazole in the Treatment of Vaginal Candidiasis

Objective: A study was carried out to compare 3 treatment regimens for vaginal candidiasis

Characterization of Elementary School Districts – A model study in Himeji City –

　この研究では，小学校の通学区域を国勢調査結果や住民基本台帳データのうち小学校の通 学区域（学区）別に編纂されているものを用いてそれらの類型化を試み，その結果を地図上 に表現した。そのような類型が生じる背景にある人口学的な性質を考察し，学校ごとに濃淡 がある児童生徒の種々の健康課題について，日常生活における背景を考察するためのツール としての可能性に言及した

Japanese and Korean Kindergartners’ Perspectives of Play Using Photos

The purpose of the study was to examine Japanese and Korean kindergarteners' perspectives by asking them to photograph play and explain why their photos represent play (photo elicitation interviews). The participants consisted of 50 kindergarteners on Japan’s main island and 50 kindergarteners in South Korea. Japanese and Korean kindergartners were provided with digital cameras and were asked to photograph their views of play without adult accompaniment. Afterwards, the children were asked to describe why their photos represented play. “Can you tell me why this means play to you?” The data were analyzed using content and thematic analyses and the photos were reviewed along with children’s responses. The thematic analysis of results revealed that Japanese and Korean kindergartners’ perceptions were related to interactions with other children, pretend play, schoolyards, and toys or props. The findings of this study indicated the ways in which Japanese and Korean children’s play perceptions were related to cultural and social contexts. Implications for early childhood education were also discussed