North Carolina State University

About: North Carolina State University is a education organization based out in Raleigh, North Carolina, United States. It is known for research contribution in the topics: Population & Thin film. The organization has 44161 authors who have published 101744 publications receiving 3456774 citations. The organization is also known as: NCSU & North Carolina State University at Raleigh.

Determining the Order of Differencing in Autoregressive Processes

Abstract: One way of handling nonstationarity in time series is to compute first differences and fit a model to the differenced series unless the differenced series also looks nonstationary. In that case, second- or higher-order differencing is done. To decide if the current degree of differencing is sufficient, one can look at the autocorrelation function for slow decay. A formal statistical test for the need to difference further is available if one is willing to assume that at most one more difference will render the series stationary. In this article, we present a proper sequence of statistical tests that allows the practitioner to handle cases in which a high order of differencing may be needed. The proper sequence is not the traditional sequence, which begins with a test for a single unit root.

Finite Difference Methods in Heat Transfer

Abstract: Finite Difference Methods in Heat Transfer presents a clear, step-by-step delineation of finite difference methods for solving engineering problems governed by ordinary and partial differential equations, with emphasis on heat transfer applications The finite difference techniques presented apply to the numerical solution of problems governed by similar differential equations encountered in many other fields Fundamental concepts are introduced in an easy-to-follow mannerRepresentative examples illustrate the application of a variety of powerful and widely used finite difference techniques The physical situations considered include the steady state and transient heat conduction, phase-change involving melting and solidification, steady and transient forced convection inside ducts, free convection over a flat plate, hyperbolic heat conduction, nonlinear diffusion, numerical grid generation techniques, and hybrid numerical-analytic solutions

Interferometer‐controlled scanning transmission X‐ray microscopes at the Advanced Light Source

Abstract: Two new soft X-ray scanning transmission microscopes located at the Advanced Light Source (ALS) have been designed, built and commissioned. Interferometer control implemented in both microscopes allows the precise measurement of the transverse position of the zone plate relative to the sample. Long-term positional stability and compensation for transverse displacement during translations of the zone plate have been achieved. The interferometer also provides low-distortion orthogonal x, y imaging. Two different control systems have been developed: a digital control system using standard VXI components at beamline 7.0, and a custom feedback system based on PC AT boards at beamline 5.3.2. Both microscopes are diffraction limited with the resolution set by the quality of the zone plates. Periodic features with 30 nm half period can be resolved with a zone plate that has a 40 nm outermost zone width. One microscope is operating at an undulator beamline (7.0), while the other is operating at a novel dedicated bending-magnet beamline (5.3.2), which is designed specifically to illuminate the microscope. The undulator beamline provides count rates of the order of tens of MHz at high-energy resolution with photon energies of up to about 1000 eV. Although the brightness of a bending-magnet source is about four orders of magnitude smaller than that of an undulator source, photon statistics limited operation with intensities in excess of 3 MHz has been achieved at high energy resolution and high spatial resolution. The design and performance of these microscopes are described.

Testing for Unit Roots in Seasonal Time Series

Abstract: Regression estimators of coefficients in seasonal autoregressive models are described. The percentiles of the distributions for time series that have unit roots at the seasonal lag are computed by Monte Carlo integration for finite samples and by analytic techniques and Monte Carlo integration for the limit case. The tabled distributions may be used to test the hypothesis that a time series has a seasonal unit root.