The geoelectrical features of the Travale geothermal field (Italy), one most productive fields in world, have been investigated by means three-dimensional (3D) magnetotelluric (MT) data inversion. This study presents first resistivity model derived from derivative-based 3D MT We analyzed that acquired over past decades order to determine its dimensionality, directionality, and phase tensor prop...

Inversion is a fundamental step in magnetotelluric (MT) data routine analysis to retrieve subsurface geoelectrical model that can be used inform geological interpretations. To reduce the effect of non-uniqueness and local minimum trapping problems improve calculation speeds, data-driven mathematical method with deep neural network was developed estimate resistivity. In this study, learning (DL)...

We use the Random Matrix Theory (RMT) to study the probability distribution fun tion and moments of the wave power transmitted inside systems with ergodi wave motion. The results des ribe either open multi hannel systems or their losed ounterparts with lo al-in-spa e internal dissipation. We on entrate on the regime of broken time-reversal invarian e and employ two di erent analyti al approa he...

Abstract Subvolcanic hydrothermal systems can lead to eruptions as well unrest phenomena without an eruptive event. Historical and recent events, including ground inflation, demagnetization, a gradual decrease in the plume height, at Mt. Tokachidake, central Hokkaido, Japan, are related such subvolcanic system. This study investigates three-dimensional (3-D) resistivity structure of Tokachidake...

Transcranial magnetic studies typically rely on measures of active and resting motor threshold (i.e. AMT, RMT). Previous work has demonstrated that adaptive threshold hunting approaches are efficient for estimating RMT. To date, no study has compared motor threshold estimation approaches for measures of AMT, yet this measure is fundamental in transcranial magnetic stimulation (TMS) studies that...

S U M M A R Y Robust magnetotelluric response function estimators are now in standard use in electromagnetic induction research. Properly devised and applied, these have the ability to reduce the influence of unusual data (outliers) in the response (electric field) variables, but are often not sensitive to exceptional predictor (magnetic field) data, which are termed leverage points. A bounded ...

Controlled-source electromagnetic (CSEM) measurements are complementary data for magnetotelluric (MT) characterization although its methodology on land is not sufficiently developed and tested as in marine environments. Acquiring expertise CSEM crucial surveys places where MT cannot be performed due to high levels of cultural noise. To acquire that expertise, we perform experiments the Vallès f...

The Responsive MultiThreaded (RMT) Processor is a system LSI that integrates almost all functions for parallel/distributed real-time systems including robots, intelligent rooms/buildings, ubiquitous computing systems, and amusement systems. Concretely, the RMT Processor integrates real-time processing (RMT Processing Unit), real-time communication (Responsive Link II), computer I/O peripherals ...

AutoTutor is very different from previous intelligent tutoring systems. It interacts with students using free-form natural language dialog as human tutors do. It uses approximate natural language understanding techniques to compare student answers to a set of expected responses. Evaluations of AutoTutor have shown that it can be effective in increasing student learning for multiple domains. In ...

Research Methods Tutor (RMT) is a dialog-based intelligent tutoring system designed for use in conjunction with courses in psychology research methods. The current RMT system includes five topic sections: ethics, variables, reliability, validity, and experimental design. The tutor can be used in an “agent mode,” which utilizes synthesized speech and an interactive pedagogical agent, or in a “te...