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Your search keyword '"Sakamoto, Maiko"' showing total 209 results
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209 results on '"Sakamoto, Maiko"'

2. Exploring Genetic Improvement of the Carbon Footprint of Web Pages

Author

Lyu, Haozhou, Gay, Gregory, Sakamoto, Maiko, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Arcaini, Paolo, editor, Yue, Tao, editor, and Fredericks, Erik M., editor

Published
2024
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9. Arsenic causing gallbladder cancer disease in Bihar

Author

Kumar, Arun, Ali, Mohammad, Raj, Vivek, Kumari, Arti, Rachamalla, Mahesh, Niyogi, Som, Kumar, Dhruv, Sharma, Ashok, Saxena, Amit, Panjawani, Ghanish, Jain, Preeti, Vidyarthi, Ajay, Kumar, Navin, Kumar, Mukesh, Niraj, Pintoo Kumar, Rahman, Md. Samiur, Bishwapriya, Akhouri, Kumar, Ranjit, Sakamoto, Maiko, Kumar, Santosh, Singh, Manisha, and Ghosh, Ashok Kumar

Published
2023
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11. A Recognition Model of Motion Primitives in VR-IADL Based on the Characteristics of MCI Patients and Elderly Adults

Author

Ando, Taisei, Yamaguchi, Takehiko, Giovannetti, Tania, Sakamoto, Maiko, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Duffy, Vincent G., editor, Gao, Qin, editor, Zhou, Jia, editor, Antona, Margherita, editor, and Stephanidis, Constantine, editor

Published
2022
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14. The role of social capital in community development: Insights from behavioral game theory and social network analysis.

Author

Sakamoto, Maiko

Subjects
SOCIAL network theory, SOCIAL capital, SOCIAL networks, SOCIAL network analysis, SOCIAL norms, SANITATION
Abstract

This study examined the multifaceted nature of Social Capital (SC) in community development projects by using Water, Sanitation, and Hygiene (WASH) interventions in three urban Bangladeshi slums as a case study. Despite its recognized importance, the ambiguity surrounding SC has led to mixed outcomes, necessitating a more theorized approach to quantitatively assess SC. To address this, a comprehensive methodology was developed, specifically crafted for a community development context and incorporating standard SC questions, social network analysis indices, and an adherence to social norms through behavioral game theory. The analysis revealed varied SC profiles, with one slum achieving successful community toilet management through strong reciprocal ties. The other slums faced challenges due to community division and weakened SC among key individuals. These findings underscore the necessity of tailoring interventions to community‐specific SC characteristics. The streamlined approach derived from the study provides guidance for both enhancing the effectiveness of community interventions and advancing sustainable development. [ABSTRACT FROM AUTHOR]

Published
2024
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15. Motion Primitive Segmentation Based on Cognitive Model in VR-IADL

Author

Ando, Taisei, Yamaguchi, Takehiko, Kohama, Norito, Sakamoto, Maiko, Giovannetti, Tania, Harada, Tetsuya, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Stephanidis, Constantine, editor, Kurosu, Masaaki, editor, Chen, Jessie Y. C., editor, Fragomeni, Gino, editor, Streitz, Norbert, editor, Konomi, Shin'ichi, editor, Degen, Helmut, editor, and Ntoa, Stavroula, editor

Published
2021
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20. A Preliminary Study on Reaching Position Estimation Model for the Subtle Action Disruption

Author

Miya, Yoshinobu, Yamaguchi, Takehiko, Giovannetti, Tania, Sakamoto, Maiko, Ohwada, Hayato, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Stephanidis, Constantine, editor, Antona, Margherita, editor, Gao, Qin, editor, and Zhou, Jia, editor

Published
2020
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21. Discriminative Model for Identifying Motion Primitives Based on Virtual Reality-Based IADL

Author

Iwashita, Yasuhiro, Yamaguchi, Takehiko, Giovannetti, Tania, Sakamoto, Maiko, Ohwada, Hayato, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Stephanidis, Constantine, editor, Antona, Margherita, editor, Gao, Qin, editor, and Zhou, Jia, editor

Published
2020
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22. Basic Study on Incidence of Micro-Error in Visual Attention-Controlled Environment

Author

Ando, Taisei, Yamaguchi, Takehiko, Giovannetti, Tania, Sakamoto, Maiko, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Stephanidis, Constantine, editor, Harris, Don, editor, Li, Wen-Chin, editor, Schmorrow, Dylan D., editor, Fidopiastis, Cali M., editor, Zaphiris, Panayiotis, editor, Ioannou, Andri, editor, Fang, Xiaowen, editor, Sottilare, Robert A., editor, and Schwarz, Jessica, editor

Published
2020
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26. Statistical Analysis of Micro-error Occurrence Probability for the Fitts’ Law-Based Pointing Task

Author

Gyoji, Hikaru, Giovannetti, Tania, Mis, Rachel, Vega, Caitlyn, Silva, Lorena, Shirotori, Atsuya, Nagasawa, Yuki, Sakamoto, Maiko, Harada, Tetsuya, Ohwada, Hayato, Yamaguchi, Takehiko, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Yamamoto, Sakae, editor, and Mori, Hirohiko, editor

Published
2019
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41. Effects of Using a Perforated Spoon on Salt Reduction When Consuming Ramen Noodles: A Randomized Crossover Study of Japanese Male University Students

Author

Sakamoto, Maiko Sugimoto, Eri Tajiri, Nana Nakashima, and Tatsuaki

Subjects
salt, salt reduction, diet, nudge, ramen, Japan
Abstract

Salt reduction is a public health priority for the Japanese population. We focused on the effect of salt reduction by changing eating utensils to reduce salt consumption. As a test meal, we used ramen, which is commonly eaten by Japanese individuals and has a high salt content. In this randomized crossover study, we hypothesized that eating ramen with a perforated spoon would reduce the quantity of ramen soup and salt consumed compared to using a regular spoon without holes. Soup intake, after-meal fullness, and deliciousness were compared between eating with chopsticks and a regular spoon, and with chopsticks and a perforated spoon. In total, 36 male university students (mean age, 20.7 [standard deviation, 1.8] years) were included in the analyses. The median salt intake (25th and 75th percentiles) was significantly lower with perforated spoons (1.8 [1.5, 4.3] g) than with regular spoons (2.4 [1.8, 4.8] g; p = 0.019). There were no significant differences in after-meal fullness or deliciousness for both spoon conditions (p > 0.05). For young men, the soup intake when eating ramen with a perforated spoon was lower than that with a regular spoon; this suggests a reduction in salt intake.

Published
2023
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49. Predicting the presence of E. coli in tap water using machine learning in Nepal.

Author

Kuroki, So, Ogata, Ryuji, and Sakamoto, Maiko

Subjects
ESCHERICHIA coli, MACHINE learning, DRINKING water, WATER pollution, WATER pipelines, WATER quality
Abstract

Within developing countries, a multitude of problems that affect the water supply process can result in the contamination of water taps. While machine learning applications have become popular for attaining efficient water quality predictions, acquiring the necessary data for modelling for developing countries is challenging. This study constructs water quality prediction models by machine learning with a pseudo‐pipeline network to complement the missing data of the water supply process. Using both water source and water tap quality information measured by the Government of Nepal, we apply the three machine learning models: support vector machine (SVM), random forest (RF) and LightGBM. Furthermore, we also apply a traditional statistical method—logistic regression (LR)—to the prediction of the Escherichia coli (E. coli) contamination in water taps. With some input variables (such as the length from the nearest sources) obtained from the pseudo‐pipeline network, the results show that SVM has stable and high accuracy for both the 26 cities (70%) and for the 25 cities except for Kathmandu (79%). LR performed a significantly lower accuracy for all cities (61%) than for 25 cities (79%). Additionally, we show that our method can be applied to other regions where a water quality survey has not yet been conducted. [ABSTRACT FROM AUTHOR]

Published
2023
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