Hiromichi Nagao
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View article: SVR-DAS: A Machine-Learning-Based Method to Create Earthquake Catalogs from Seafloor Distributed Acoustic Sensing Measurements
SVR-DAS: A Machine-Learning-Based Method to Create Earthquake Catalogs from Seafloor Distributed Acoustic Sensing Measurements Open
Seafloor earthquake monitoring is one of the emergent research areas in seismology. Its importance relies on the continuous monitoring of earthquake activity near or on subduction zones, where large megathrust earthquakes are generated. In…
View article: Two-stage approach for earthquake detection using multiple clustering-based classification
Two-stage approach for earthquake detection using multiple clustering-based classification Open
SUMMARY Deep learning (DL) approach has gained attention for earthquake (EQ) detection. To alleviate the problem of training data shortage, transfer learning (TL) provides a useful framework to adapt pre-trained models, typically through t…
View article: PoViT-UQ: <i>P</i>-wave polarity and arrival time determination using vision transformer with uncertainty quantification
PoViT-UQ: <i>P</i>-wave polarity and arrival time determination using vision transformer with uncertainty quantification Open
SUMMARY Determining earthquake focal mechanisms is essential for understanding fault geometry and the stress field in the Earth's crust. When focal mechanisms are estimated using P-wave first-motion polarities, accurate polarity determinat…
View article: SegPhase: development of arrival time picking models for Japan’s seismic network using the hierarchical vision transformer
SegPhase: development of arrival time picking models for Japan’s seismic network using the hierarchical vision transformer Open
Seismic phase picking is a fundamental task in seismology that is crucial for event detection and earthquake cataloging; however, manual analysis is impractical given the scale of modern seismic networks. We present SegPhase, a novel seism…
View article: Seismic detection based on unsupervised station-wise phase picks using deep learning
Seismic detection based on unsupervised station-wise phase picks using deep learning Open
View article: MultiDLFormer: A Vision Transformer-Based Deep Learning Model for Detecting Deep Low-Frequency Earthquakes Across Multiple Stations
MultiDLFormer: A Vision Transformer-Based Deep Learning Model for Detecting Deep Low-Frequency Earthquakes Across Multiple Stations Open
View article: Adjoint‐Based Marker‐In‐Cell Data Assimilation for Constraining Thermal and Flow Processes From Lagrangian Particle Records
Adjoint‐Based Marker‐In‐Cell Data Assimilation for Constraining Thermal and Flow Processes From Lagrangian Particle Records Open
Geophysical problems often involve Lagrangian particles that follow surrounding flows and record information about the system, such as the pressure and temperature path recorded in metamorphic rocks. These Lagrangian particles can be usefu…
View article: SegPhase: Development of Arrival Time Picking Models for Japan’s Seismic Network Using the Hierarchical Vision Transformer
SegPhase: Development of Arrival Time Picking Models for Japan’s Seismic Network Using the Hierarchical Vision Transformer Open
We present SegPhase, a novel seismic arrival time picking model designed to efficiently process large-scale seismic data recorded by Japan’s dense seismic networks. SegPhase is implemented in three configurations to accommodate various obs…
View article: Oxygen optodes on oceanographic moorings: recommendations for deployment and in situ calibration
Oxygen optodes on oceanographic moorings: recommendations for deployment and in situ calibration Open
Increasing interest in the deployment of optical oxygen sensors, or optodes, on oceanographic moorings reflects the value of dissolved oxygen (DO) measurements in studies of physical and biogeochemical processes. Optodes are well-suited fo…
View article: Adjoint-based marker-in-cell data assimilation for constraining thermal and flow processes from Lagrangian particle records
Adjoint-based marker-in-cell data assimilation for constraining thermal and flow processes from Lagrangian particle records Open
Geophysical problems often involve Lagrangian particles that follow surrounding flows and record information about the system, such as the pressure and temperature path recorded in metamorphic rocks. These Lagrangian particles can be usefu…
View article: SegPhase: Development of Arrival Time Picking Models for Japan’s Seismic Network Using the Hierarchical Vision Transformer
SegPhase: Development of Arrival Time Picking Models for Japan’s Seismic Network Using the Hierarchical Vision Transformer Open
A seismic arrival time picking model, SegPhase, is introduced to automatically process a large amount of seismic data recorded by large dense seismic networks with different sampling frequencies and numbers of observed components. Three mo…
View article: Adjoint-based data assimilation for reconstruction of thermal convection in a highly viscous fluid from surface velocity and temperature snapshots
Adjoint-based data assimilation for reconstruction of thermal convection in a highly viscous fluid from surface velocity and temperature snapshots Open
SUMMARY It is a general problem in geoscience to estimate the time-series of velocity and temperature fields for a fluid based on limited observations, such as the flow velocity at the fluid surface and/or a temperature snapshot after flow…
View article: Seismic-phase detection using multiple deep learning models for global and local representations of waveforms
Seismic-phase detection using multiple deep learning models for global and local representations of waveforms Open
SUMMARY The detection of earthquakes is a fundamental prerequisite for seismology and contributes to various research areas, such as forecasting earthquakes and understanding the crust/mantle structure. Recent advances in machine learning …
View article: Detection of Deep Low-Frequency Tremors from Continuous Paper Records at a Station in Southwest Japan About 50 Years Ago Based on Convolutional Neural Network
Detection of Deep Low-Frequency Tremors from Continuous Paper Records at a Station in Southwest Japan About 50 Years Ago Based on Convolutional Neural Network Open
The establishment of the High Sensitivity Seismograph Network (Hi-net) in Japan has led to the discovery of deep low-frequency tremors. Since such tremors are considered to be associated with large earthquakes adjacent to tremors on the sa…
View article: Detection of Deep Low‐Frequency Tremors From Continuous Paper Records at a Station in Southwest Japan About 50 Years Ago Based on Convolutional Neural Network
Detection of Deep Low‐Frequency Tremors From Continuous Paper Records at a Station in Southwest Japan About 50 Years Ago Based on Convolutional Neural Network Open
Since deep low‐frequency tremors are considered to be associated with large earthquakes that occur adjacently on the same subducting plate interface, it is important to investigate tremors that occurred before the establishment of modern s…
View article: Seismic wavefield reconstruction based on compressed sensing using data-driven reduced-order model
Seismic wavefield reconstruction based on compressed sensing using data-driven reduced-order model Open
SUMMARY Reconstruction of the distribution of ground motion due to an earthquake is one of the key technologies for the prediction of seismic damage to infrastructure. Particularly, the immediate reconstruction of the spatially continuous …
View article: Seismic-phase detection using multiple deep learning models for global and local representations of waveforms
Seismic-phase detection using multiple deep learning models for global and local representations of waveforms Open
The detection of earthquakes is a fundamental prerequisite for seismology and contributes to various research areas, such as forecasting earthquakes and understanding the crust/mantle structure. Recent advances in machine learning technolo…
View article: Adjoint-based uncertainty quantification for inhomogeneous friction on a slow-slipping fault
Adjoint-based uncertainty quantification for inhomogeneous friction on a slow-slipping fault Open
SUMMARY Long-term slow-slip events (LSSEs) usually occur on a fault existing at the deep, shallow parts of subducting plates and substantially relate to adjacent megathrust fault motions. The dynamics of the LSSE largely depend on the inho…
View article: Observation Site Selection for Physical Model Parameter Estimation toward Process-Driven Seismic Wavefield Reconstruction
Observation Site Selection for Physical Model Parameter Estimation toward Process-Driven Seismic Wavefield Reconstruction Open
The ``big'' seismic data not only acquired by seismometers but also acquired by vibrometers installed in buildings and infrastructure and accelerometers installed in smartphones will be certainly utilized for seismic research in the near f…
View article: Detection of low-frequency earthquakes by the matched filter technique using the product of mutual information and correlation coefficient
Detection of low-frequency earthquakes by the matched filter technique using the product of mutual information and correlation coefficient Open
The matched filter technique is often used to detect microearthquakes such as deep low-frequency (DLF) earthquakes. It compares correlation coefficients (CC) between waveforms of template earthquakes and the observed data. Conventionally, …
View article: Detection of low-frequency earthquakes by matched filter technique using the product of mutual information and correlation coefficient
Detection of low-frequency earthquakes by matched filter technique using the product of mutual information and correlation coefficient Open
Matched filter technique is often used to detect microearthquakes such as deep low-frequency (DLF) earthquakes. It compares correlation coefficients (CC) between waveforms of template earthquakes and the observed data. Conventionally, the …
View article: Deepening of Data Assimilation and Its Application to Seismology
Deepening of Data Assimilation and Its Application to Seismology Open
1．はじめに
View article: Forecasting temporal variation of aftershocks immediately after a main shock using Gaussian process regression
Forecasting temporal variation of aftershocks immediately after a main shock using Gaussian process regression Open
SUMMARY Uncovering the distribution of magnitudes and arrival times of aftershocks is a key to comprehending the characteristics of earthquake sequences, which enables us to predict seismic activities and conduct hazard assessments. Howeve…
View article: Phase prediction method for pattern formation in time-dependent Ginzburg-Landau dynamics for kinetic Ising model without <i>a priori</i> assumptions of domain patterns
Phase prediction method for pattern formation in time-dependent Ginzburg-Landau dynamics for kinetic Ising model without <i>a priori</i> assumptions of domain patterns Open
We propose a phase prediction method for the pattern formation in the\nuniaxial two-dimensional kinetic Ising model with the dipole-dipole\ninteractions under the time-dependent Ginzburg-Landau dynamics. Taking the\neffects of the material…
View article: Convolutional Neural Network to Detect Deep Low-Frequency Tremors from Seismic Waveform Images
Convolutional Neural Network to Detect Deep Low-Frequency Tremors from Seismic Waveform Images Open
The installation of dense seismometer arrays in Japan approximately 20 years ago has led to the discovery of deep low-frequency tremors, which are oscillations clearly different from ordinary earthquakes. As such tremors may be related to …
View article: Development of Data-Driven System in Materials Integration
Development of Data-Driven System in Materials Integration Open
A Data-driven analysis system developed in the first-term SIP "Structural Material for Innovation" is briefly explained using several practical applications. The developed system is composed of two major systems: the data-driven prediction…
View article: Bayesian modeling of the equation-of-state for liquid iron in Earth's outer core
Bayesian modeling of the equation-of-state for liquid iron in Earth's outer core Open
Input data of Matsumura et al.
View article: Bayesian modeling of the equation-of-state for liquid iron in Earth's outer core
Bayesian modeling of the equation-of-state for liquid iron in Earth's outer core Open
Input data of Matsumura et al.
View article: Prediction of aftershocks with Gaussian process regression
Prediction of aftershocks with Gaussian process regression Open
Uncovering the distribution of magnitudes and arrival times of aftershocks is a key to comprehend the characteristics of the sequence of earthquakes, which enables us to predict seismic activities and hazard assessments. However, identifyi…
View article: Development of Data-Driven System in Materials Integration
Development of Data-Driven System in Materials Integration Open