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Full-Text Articles in Engineering
A Novel Spatiotemporal Prediction Method Of Cumulative Covid-19 Cases, Junzhe Cai
A Novel Spatiotemporal Prediction Method Of Cumulative Covid-19 Cases, Junzhe Cai
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Prediction methods are important for many applications. In particular, an accurate prediction for the total number of cases for pandemics such as the Covid-19 pandemic could help medical preparedness by providing in time a sufficient supply of testing kits, hospital beds and medical personnel. This thesis experimentally compares the accuracy of ten prediction methods for the cumulative number of Covid-19 pandemic cases. These ten methods include two types of neural networks and extrapolation methods based on best fit linear, best fit quadratic, best fit cubic and Lagrange interpolation, as well as an extrapolation method from Revesz. We also consider the …
Designing A Bayer Filter With Smooth Hue Transition Interpolation Using The Xilinx System Generator, Zhiqiang Li, Peter Revesz
Designing A Bayer Filter With Smooth Hue Transition Interpolation Using The Xilinx System Generator, Zhiqiang Li, Peter Revesz
CSE Conference and Workshop Papers
This paper describes the design of a Bayer filter with smooth hue transition using the System Generator for DSP. We describe and compare experimentally two different designs, one based on a MATLAB implementation and the other based on a modification of the Bayer filter using bilinear interpolation.
Estimating The Flight Path Of Moving Objects Based On Acceleration Data, Peter Revesz
Estimating The Flight Path Of Moving Objects Based On Acceleration Data, Peter Revesz
CSE Conference and Workshop Papers
Inertial navigation is the problem of estimating the flight path of a moving object based on only acceleration measurements. This paper describes and compares two approaches for inertial navigation. Both approaches estimate the flight path of the moving object using cubic spline interpolation, but they find the coefficients of the cubic spline pieces by different methods. The first approach uses a tridiagonal matrix, while the second approach uses recurrence equations. They also require different boundary conditions. While both approaches work in O(n) time where n is the number of given acceleration measurements, the recurrence equation-based method can be easier updated …
Cubic Spline Interpolation By Solving A Recurrence Equation Instead Of A Tridiagonal Matrix, Peter Revesz
Cubic Spline Interpolation By Solving A Recurrence Equation Instead Of A Tridiagonal Matrix, Peter Revesz
CSE Conference and Workshop Papers
The cubic spline interpolation method is proba- bly the most widely-used polynomial interpolation method for functions of one variable. However, the cubic spline method requires solving a tridiagonal matrix-vector equation with an O(n) computational time complexity where n is the number of data measurements. Even an O(n) time complexity may be too much in some time-ciritical applications, such as continuously estimating and updating the flight paths of moving objects. This paper shows that under certain boundary conditions the tridiagonal matrix solving step of the cubic spline method could be entirely eliminated and instead the coefficients of the unknown cubic polynomials …
Decaf: A New Event Detection Logic For The Purpose Of Fusing Delineated-Continuous Spatial Information, Kerry Q. Hart
Decaf: A New Event Detection Logic For The Purpose Of Fusing Delineated-Continuous Spatial Information, Kerry Q. Hart
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Geospatial information fusion is the process of synthesizing information from complementary data sources located at different points in space and time. Spatial phenomena are often measured at discrete locations by sensor networks, technicians, and volunteers; yet decisions often require information about locations where direct measurements do not exist. Traditional methods assume the spatial phenomena to be either discrete or continuous, an assumption that underlies and informs all subsequent analysis. Yet certain phenomena defy this dichotomy, alternating as they move across spatial and temporal scales. Precipitation, for example, appears continuous at large scales, but it can be temporally decomposed into discrete …
Adaptive Interpolation Algorithms For Temporal-Oriented Datasets, Jun Gao
Adaptive Interpolation Algorithms For Temporal-Oriented Datasets, Jun Gao
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Spatiotemporal datasets can be classified into two categories: temporal-oriented and spatial-oriented datasets depending on whether missing spatiotemporal values are closer to the values of its temporal or spatial neighbors. We present an adaptive spatiotemporal interpolation model that can estimate the missing values in both categories of spatiotemporal datasets. The key parameters of the adaptive spatiotemporal interpolation model can be adjusted based on experience.