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Junko Ogawa(Junko Ogawa ),Seiko Mochida(Seiko Mochida ),Haruo Kimura(Haruo Kimura ),Aiping Liu(Aiping Liu ),Yoichi Sakakihara(Yoichi Sakakihara ) The Pacific Early Childhood Education Research Ass 2024 Asia-Pacific journal of research in early childhoo Vol.18 No.1
This study aimed to obtain implications on childrearing and childcare practices for achieving children's well-being through analyzing factors predicting children's well-being during the COVID-19 pandemic in eight Asian countries. We primarily focused on “resilience,” the ability to cope with and recover from difficult situations, which had been confirmed from previous studies as a positive factor towards children’s development in the context of hardships. We also chose other potential predictors referring to Bronfenbrenner’s ecological systems theory, including mothers’ concerns about COVID-19, household income, number of playmates, support from childcare facilities/schools, family environments, and children’s lifestyles, and examined how these predictor variables predict children’s well-being. We found that children’s resilience strongly predicted their well-being, which was common in all eight countries. Family factors and children's daily life factors were also associated with children's well-being. The country-specific analysis also indicated the importance of support from childcare facilities/schools on well-being. Well-being and resilience are both psychological constructs and often studied as important indicators of child health. Resilience has been spot-lighted as an effective protective factor for children experiencing adversities such as the COVID-19 pandemic. We have found that resilience was the strongest predictor of well-being among other factors even during the COVID-19 pandemic.
Universal Design with Robots for the Wide Use of Robots
Nobuto Matsuhira,Junko Hirokawa,Hideki Ogawa,Tatsuya Wada 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
Home use robots and service robots have been expected for the society of the aging and the falling birthrate. However, a lot of disturbance avoiding the robot’ activities exists in such an environment. Universal Design with Robots (UDRob<SUP>TM</SUP>) has been proposed to cope with these problems in our daily life environment using the concept of universal design. Here, interface designs for mobility, handling, and image processing are especially considered in the concept. Conceptual design of the robot system based on UDRob<SUP>TM</SUP> and the interaction design has been shown here.
Mobile Robot Global Localization Using Particle Filters
Guanghui Cen,Nobuto Matsuhira,Junko Hirokawa,Hideki Ogawa,Ichiro Hagiwara 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10
Mobile robot global localization is the problem of determining a robot’ pose in an environment by using sensor data, when the initial position is unknown. Particle filter based Probabilistic algorithm called Monte Carlo Localization is the current popular approach to solve the robot localization problem. In this paper we introduce the multi-sensor based Monte Carlo Localization (MCL) method which represents a robot’ belief by a set of weighted samples and use the Laser Range Finder (LRF) sensor to measurement update. We also proposed likelihood based particle filter to solve the kidnapped problem. The experiment results illustrate the efficiency and robustness of particle filter approach for our mobile robot.
Hideo Ichikawa,Eisuke Yasuda,Takashi Kumada,Kenji Takeshima,Sadanobu Ogawa,Akikazu Tsunekawa,Tatsuya Goto,Koji Nakaya,Tomoyuki Akita,Junko Tanaka 대한초음파의학회 2023 ULTRASONOGRAPHY Vol.42 No.1
Purpose: Quantitative elastography methods, such as ultrasound two-dimensional shear-wave elastography (2D-SWE) and magnetic resonance elastography (MRE), are used to diagnose liver fibrosis. The present study compared liver stiffness determined by 2D-SWE and MRE within individuals and analyzed the degree of agreement between the two techniques. Methods: In total, 888 patients who underwent 2D-SWE and MRE were analyzed. Bland-Altman analysis was performed after both types of measurements were log-transformed to a normal distribution and converted to a common set of units using linear regression analysis for differing scales. The expected limit of agreement (LoA) was defined as the square root of the sum of the squares of 2D-SWE and MRE precision. The percentage difference was expressed as (2D-SWEMRE)/ mean of the two methods×100. Results: A Bland-Altman plot showed that the bias and upper and lower LoAs (ULoA and LLoA) were 0.0002 (95% confidence interval [CI], -0.0057 to 0.0061), 0.1747 (95% CI, 0.1646 to 0.1847), and -0.1743 (95% CI, -0.1843 to -0.1642), respectively. In terms of percentage difference, the mean, ULoA, and LLoA were -0.5944%, 19.8950%, and -21.0838%, respectively. The calculated expected LoA was 17.1178% (95% CI, 16.6353% to 17.6002%), and 789 of 888 patients (88.9%) had a percentage difference within the expected LoA. The intraclass correlation coefficient of the two methods indicated an almost perfect correlation (0.8231; 95% CI, 0.8006 to 0.8432; P<0.001). Conclusion: Bland-Altman analysis demonstrated that 2D-SWE and MRE were interchangeable within a clinically acceptable range.