다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

A wide variety of media can be used in learning, including distance learning, such as print, lectures, conference sections, tutors, pictures, video, sound, and computers. Any one instance of distance learning will make choices among these media, perhaps using several.

Multimedia in Learning

mental representations a dual coding approach is available in our digital library an online access to it is set as public so you can download it instantly. Our digital library saves in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the mental representations a dual coding approach is universally compatible with any devices to read.

Mental Representations A Dual Coding Approach

https://northumbria-test.eprints-hosting.org/id/document/266251

gprMax: Open source software to simulate electromagnetic wave propagation for Ground Penetrating Radar

[신간안내] Computational Electrodynamics (the finite difference time - domain method)

A three-dimensional (3-D) finite-difference time-domain (FDTD) algorithm is used in order to simulate ground penetrating radar (GPR) for landmine detection. Two bowtie GPR transducers are chosen for the simulations and two widely employed antipersonnel (AP) landmines, namely PMA-1 and PMN are used. The validity of the modeled antennas and landmines is tested through a comparison between numerical and laboratory measurements. The modeled AP landmines are buried in a realistically simulated soil. The geometrical characteristics of soil’s inhomogeneity are modeled using fractal correlated noise, which gives rise to Gaussian semivariograms often encountered in the field. Fractals are also employed in order to simulate the roughness of the soil’s surface. A frequency-dependent complex electrical permittivity model is used for the dielectric properties of the soil, which relates both the velocity and the attenuation of the electromagnetic waves with the soil’s bulk density, sand particles density, clay fraction, sand fraction, and volumetric water fraction. Debye functions are employed to simulate this complex electrical permittivity. Background features like vegetation and water puddles are also included in the models and it is shown that they can affect the performance of GPR at frequencies used for landmine detection (0.5–3 GHz). It is envisaged that this modeling framework would be useful as a testbed for developing novel GPR signal processing and interpretations procedures and some preliminary results from using it in such a way are presented.

https://northumbria-test.eprints-hosting.org/id/document/266329

A Realistic FDTD Numerical Modeling Framework of Ground Penetrating Radar for Landmine Detection

Very few researchers have developed numerical models of ground-penetrating radar (GPR) that include realistic descriptions of both the antennas and the subsurface. This is essential to be able to accurately predict responses from near-surface, near-field targets. We have developed a detailed 3D finite-difference time-domain models of two commercial GPR antennas — a Geophysical Survey Systems, Inc. (GSSI) 1.5-GHz antenna and a MALA Geoscience 1.2-GHz antenna — using simple analyses of the geometries and the main components of the antennas. Values for unknown parameters in the antenna models (due to commercial sensitivity) were estimated by using Taguchi’s optimization method, resulting in a good match between the real and modeled crosstalk responses in free space. Validation using a series of oil-in-water emulsions to simulate the electrical properties of real materials demonstrated that it was essential to accurately model the permittivity and dispersive conductivity. When accurate descriptions of the emu...

/pdf/creating-finite-difference-time-domain-models-of-commercial-1wg38esuzw.pdf

Creating finite-difference time-domain models of commercial ground-penetrating radar antennas using Taguchi's optimization method

https://northumbria-test.eprints-hosting.org/id/document/268151

A CUDA-based GPU engine for gprMax: open source FDTD electromagnetic simulation software

The simulation, or forward modeling, of ground penetrating radar (GPR) is becoming a more frequently used approach to facilitate the interpretation of complex real GPR data, and as an essential component of full-waveform inversion (FWI). However, general full-wave 3-D electromagnetic (EM) solvers, such as the ones based on the finite-difference time-domain (FDTD) method, are still computationally demanding for simulating realistic GPR problems. We have developed a novel near-real-time, forward modeling approach for GPR that is based on a machine learning (ML) architecture. The ML framework uses an innovative training method that combines a predictive principal component analysis technique, a detailed model of the GPR transducer, and a large data set of modeled GPR responses from our FDTD simulation software. The ML-based forward solver is parameterized for a specific GPR application, but the framework can be applied to many different classes of GPR problems. To demonstrate the novelty and computational efficiency of our ML-based GPR forward solver, we used it to carry out FWI for a common infrastructure assessment application—determining the location and diameter of reinforcement bars in concrete. We tested our FWI with synthetic and real data and found a good level of accuracy in determining the rebar location, size, and surrounding material properties from both data sets. The combination of the near-real-time computation, which is orders of magnitude less than what is achievable by traditional full-wave 3-D EM solvers, and the accuracy of our ML-based forward model is a significant step toward commercially viable applications of FWI of GPR.

/pdf/a-machine-learning-based-fast-forward-solver-for-ground-1n7pe628vk.pdf

Craig Warren

Papers

gprMax: Open source software to simulate electromagnetic wave propagation for Ground Penetrating Radar

A Realistic FDTD Numerical Modeling Framework of Ground Penetrating Radar for Landmine Detection

Creating finite-difference time-domain models of commercial ground-penetrating radar antennas using Taguchi's optimization method

A CUDA-based GPU engine for gprMax: open source FDTD electromagnetic simulation software

A Machine Learning-Based Fast-Forward Solver for Ground Penetrating Radar With Application to Full-Waveform Inversion