Kengo Nakamura
Biographic Data
| ID | 8283250 |
|---|---|
| NAME | Kengo Nakamura |
| GIVEN NAMES | Kengo |
| FAMILY NAME | Nakamura |
| SIGNATURE | NAKAMURA K |
| AFFILIATIONS | Tohoku University |
| ORCID | 0000-0002-2304-1548 |
| VERIFIED | Yes |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 7 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Overview of the Special Issue “Progress of Earth and Data Sciences Research into Tsunami Deposits, and Contribution to Tsunami Disaster Prevention (Part I)
Preface of the Special Issue “Progress of Earth and Data Sciences Research into Tsunami Deposits, and Contribution to Tsunami Disaster Prevention (Part I)
Preface of the Special Issue “Progress of Earth and Data Sciences Research into Tsunami Deposits, and Contribution to Tsunami Disaster Prevention (Part II)
Estimating Layer Boundaries of Mixed-layer Tsunami Deposits with a XRF Core Scanner
From the perspective of disaster prevention, it is necessary to clarify the distribution and historical frequency of tsunami deposits. However, tsunami deposits are disturbed by earthquakes and tsunamis. Therefore, it is difficult to identify the layers of deposits. Layers deposited during disturbances are dated and grain-size distribution is measured. Using the results of geochemical data and principal component analyses with detailed elemental …
Overview of the Special Issue “Progress of Earth and Data Sciences Research into Tsunami Deposits, and Contribution to Tsunami Disaster Prevention (Part II)
Statistical Correlation for Geological Layers Using XRF Core Scan Data
A method is developed to quantitatively correlate geological layers based on similarities in the shape of the statistical frequency distribution of a large volume of multi-element count data obtained with an X-ray fluorescence (XRF) core scanner. A distance measure between probability distributions called Jensen–Shannon divergence is adopted as a criterion for similarities in statistical distributions with the assumption of a Gaussian distributio…
Machine Learning-based Geochemical Discrimination Method for Tsunami Deposits and a Simple Determination System
In order to establish a discrimination method for tsunami deposits, a machine learning analysis is conducted for geochemical data to determine paleo-tsunami deposits. Column samples containing tsunami deposits are collected at Noda village, Iwate prefecture, and Wakabayashi-ku, Sendai city, and the distribution of element concentrations are continuously measured. The model is trained by Multilayer perceptron using Noda samples as training data. C…
No prominent works on this page.
Overview of the Special Issue “Progress of Earth and Data Sciences Research into Tsunami Deposits, and Contribution to Tsunami Disaster Prevention (Part I)
Preface of the Special Issue “Progress of Earth and Data Sciences Research into Tsunami Deposits, and Contribution to Tsunami Disaster Prevention (Part I)
Preface of the Special Issue “Progress of Earth and Data Sciences Research into Tsunami Deposits, and Contribution to Tsunami Disaster Prevention (Part II)
Estimating Layer Boundaries of Mixed-layer Tsunami Deposits with a XRF Core Scanner
From the perspective of disaster prevention, it is necessary to clarify the distribution and historical frequency of tsunami deposits. However, tsunami deposits are disturbed by earthquakes and tsunamis. Therefore, it is difficult to identify the layers of deposits. Layers deposited during disturbances are dated and grain-size distribution is measured. Using the results of geochemical data and principal component analyses with detailed elemental …
Overview of the Special Issue “Progress of Earth and Data Sciences Research into Tsunami Deposits, and Contribution to Tsunami Disaster Prevention (Part II)
Statistical Correlation for Geological Layers Using XRF Core Scan Data
A method is developed to quantitatively correlate geological layers based on similarities in the shape of the statistical frequency distribution of a large volume of multi-element count data obtained with an X-ray fluorescence (XRF) core scanner. A distance measure between probability distributions called Jensen–Shannon divergence is adopted as a criterion for similarities in statistical distributions with the assumption of a Gaussian distributio…
Machine Learning-based Geochemical Discrimination Method for Tsunami Deposits and a Simple Determination System
In order to establish a discrimination method for tsunami deposits, a machine learning analysis is conducted for geochemical data to determine paleo-tsunami deposits. Column samples containing tsunami deposits are collected at Noda village, Iwate prefecture, and Wakabayashi-ku, Sendai city, and the distribution of element concentrations are continuously measured. The model is trained by Multilayer perceptron using Noda samples as training data. C…
earthquake and tectonic studies (7 works) · Geology (7 works) · Geology (7 works) · Geology and Paleoclimatology Research (6 works) · Earth science (4 works) · Emergency management (3 works) · Geochemistry and Geologic Mapping (3 works) · Geography (3 works) · Political science (3 works) · Disaster mitigation (2 works)