Input data used to generate one-dimensional burial history models, central Alberta, Canada

2005 ◽  
Author(s):  
Laura N.R. Roberts ◽  
Debra K. Higley ◽  
Mitchell E. Henry
Keyword(s):  
Input Data ◽  
Burial History ◽  
One Dimensional

A New Scan Conversion Algorithm for Ultrasound Compound Scanning

1985 ◽  
Vol 7 (3) ◽  
pp. 215-224 ◽  
Author(s):  
Seung-Woo Lee ◽  
Song-Bai Park
Keyword(s):  
Real Time ◽  
Input Data ◽  
Linear Interpolation ◽  
Reconstruction Error ◽  
Ultrasound Images ◽  
Two Dimensional ◽  
Spatial Compounding ◽  
One Dimensional ◽  
Conversion Algorithm ◽  
Scan Conversion

An improved scan conversion algorithm for ultrasound compound scanning is proposed. In this algorithm, the input data in the spatial domain is sampled by the concentric square raster sampling (CSRS) method, and the display pixel data are filled by one-dimensional linear interpolation. The reconstruction error of the proposed algorithm is much smaller than that of other algorithms, because only one-dimensional, rather than two-dimensional, interpolation is involved. This algorithm greatly simplifies implementation of a real-time digital scan converter (DSC) for spatial compounding of ultrasound images.

scholarly journals Hardware Design Rule Checker Using a CAM Architecture

VLSI Design ◽  
1996 ◽  
Vol 4 (2) ◽  
pp. 141-147
Author(s):  
Seokjin Kim ◽  
Ramalingam Sridhar
Keyword(s):  
Pattern Matching ◽  
Input Data ◽  
Hardware Implementation ◽  
Low Cost ◽  
Design Rule ◽  
Design Rules ◽  
One Dimensional ◽  
Content Addressable Memory ◽  
Logic Operations ◽  
Geometric Designs

This paper presents a hardware implementation of design rule checker using a specialized Content Addressable Memory(CAM) for the Manhattan geometric designs. Two dimensional relationships between rectangular objects in a design are checked with one dimensional design rules. The input data is processed by the pixel pre-processor in such a way that direct comparison between the input data and the stored rules in the CAM is possible. The comparison by the CAM reduces the number of memory references and logic operations of pattern matching and the simple architecture of the system enables a low cost implementation.

DATA PARALLEL VISUAL RECONSTRUCTION AND PARTITIONING ALGORITHMS

1993 ◽  
Vol 03 (03) ◽  
pp. 267-277
Author(s):  
PAUL C. XIROUCHAKIS ◽  
PEARL Y. WANG ◽  
OPHIR FRIEDER
Keyword(s):  
Input Data ◽  
Random Access ◽  
Reconstruction Problem ◽  
One Dimensional ◽  
Data Parallel ◽  
Distributed Array ◽  
Partitioning Algorithms ◽  
Visual Reconstruction ◽  
The One ◽  
Specific Implementation

Data parallel visual reconstruction and partitioning algorithms and the associated code are developed for a vector random access machine (V-RAM). Finite element algorithms are constructed for solving the one-dimensional visual reconstruction problem with the input data consisting of a symmetrical top hat loading for the modeling of interacting step discontinuities. The advantage of the V-RAM implementation is the general code applicability to a variety of architectures. A specific implementation is performed on a Distributed Array Processor (DAP) simulator on the VAX 6000–420. Execution times on the DAP simulator are obtained and are found to be in agreement with the algorithmic complexities of the V-RAM code.

scholarly journals INVERSE PROBLEM OF A ONE-DIMENSIONAL MODEL IN MULTILAYER HEAT CONDUCTION

2020 ◽  
Vol 19 (1) ◽  
pp. 42
Author(s):  
G. C. Oliveira ◽  
S. S. Ribeiroa ◽  
G. Guimarães
Keyword(s):  
Inverse Problem ◽  
Measurement Errors ◽  
Input Data ◽  
Temperature Measurements ◽  
Dimensional Model ◽  
One Dimensional ◽  
Ill Posed ◽  
Measurements Errors ◽  
Chip Chip

The inverse problem in conducting heat is related to the determination of the boundary condition, rate of heat generation, or thermophysical properties, using temperature measurements at one or more positions of the solid. The inverse problem in conducting heat is mathematically one of the ill-posed problems, because its solution extremely sensitive to measurement errors. For a well-placed problem the following conditions must be satisfied: the solution must exist, it must be unique and must be stable on small changes of the input data. The objective of the work is to estimate the heat flux generated at the tool-chip-chip interface in a manufacturing process. The term "estimation" is used because in the temperature measurements, errors are always present and these affect the accuracy of the calculation of the heat flow.

scholarly journals Formulation and analysis of a parabolic transmission problem on disjoint intervals

2012 ◽  
Vol 91 (105) ◽  
pp. 111-123 ◽  
Author(s):  
Bosko Jovanovic ◽  
Lubin Vulkov
Keyword(s):  
Boundary Value Problem ◽  
Weak Solutions ◽  
Parabolic Equations ◽  
Input Data ◽  
Boundary Value ◽  
Initial Boundary ◽  
Initial Boundary Value Problem ◽  
Well Posedness ◽  
One Dimensional ◽  
Initial Boundary Value

We investigate an initial-boundary-value problem for one dimensional parabolic equations in disjoint intervals. Under some natural assumptions on the input data we proved the well-posedness of the problem. Nonnegativity and energy stability of its weak solutions are also studied.

scholarly journals The initial analysis of the river Ibar temperature downstream of the lake Gazivode

2014 ◽  
Vol 18 (suppl.1) ◽  
pp. 73-80 ◽  
Author(s):  
Dragan Kalaba ◽  
Ivana Ivanovic ◽  
Dejan Cikara ◽  
Gordana Milentijevic
Keyword(s):  
Water Quality ◽  
Input Data ◽  
Temperature Data ◽  
Numerical Results ◽  
Measured Temperature ◽  
One Dimensional ◽  
Initial Analysis ◽  
Temperature Modeling ◽  
River Reach ◽  
The City

As a result of a very limited number of geometric and other input data, the temperature modeling of the river Ibar downstream of the lake Gazivode was started by analyzing one river reach between Pridvorica, secondary dam in the system Gazivode, and the city Kosovska Mitrovica. River reach was selected so that the numerical results can be compared with available measured temperature data. Water quality component of HEC-RAS one-dimensional hydraulic river model was used for temperature calculations.

Using One-Dimensional Linear Interpolation Method to Check Over-Fitting in Neural Network with Multi-Dimensional Inputs

2014 ◽  
Vol 496-500 ◽  
pp. 2228-2232 ◽  
Author(s):  
Bao Lien Hung ◽  
Hsin An Hung
Keyword(s):  
Neural Network ◽  
Input Data ◽  
Interpolation Method ◽  
Linear Interpolation ◽  
One Dimensional ◽  
Input And Output ◽  
The Neural Network ◽  
Neural Network Structure ◽  
Linear Interpolation Method ◽  
Fitting In

Neural networks are widely used to learn and predict the correlation between input and output. However, in the process of learning, the excessive reduction of errors may influence the validity of prediction, this phenomenon is called over-fitting. In order to address this problem, this study sequenced the input data into one-dimensional data for the neural network structure of multi-dimensional inputs, and used visual graphics to observe whether there is over-fitting. This method is called one-dimensional linear interpolation method. The result of example validation proved that the proposed method can provide specific graphical information effectively, and determine whether there is over-fitting.

scholarly journals An inverse problem of reconstructing the time-dependent coefficient in a one-dimensional hyperbolic equation

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
M. J. Huntul ◽  
Muhammad Abbas ◽  
Dumitru Baleanu
Keyword(s):  
Inverse Problem ◽  
Input Data ◽  
Time Dependent ◽  
One Dimensional ◽  
Noisy Input ◽  
Nonlinear Minimization ◽  
Ill Posed ◽  
Dependent Potential ◽  
The Stability ◽  
First Time

AbstractIn this paper, for the first time the inverse problem of reconstructing the time-dependent potential (TDP) and displacement distribution in the hyperbolic problem with periodic boundary conditions (BCs) and nonlocal initial supplemented by over-determination measurement is numerically investigated. Though the inverse problem under consideration is ill-posed by being unstable to noise in the input data, it has a unique solution. The Crank–Nicolson-finite difference method (CN-FDM) along with the Tikhonov regularization (TR) is applied for calculating an accurate and stable numerical solution. The programming language MATLAB built-in lsqnonlin is used to solve the obtained nonlinear minimization problem. The simulated noisy input data can be inverted by both analytical and numerically simulated. The obtained results show that they are accurate and stable. The stability analysis is performed by using Fourier series.

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