Far infrared maser communications technology

An optically pumped FIR laser was constructed and tested. Optimum operating conditions were determined with CH3OH as the lasing medium. The laser was found to operate equally well with flowing gas or in a sealed off configuration. The FIR cavity stability and pump laser stability were found to have significant problems. The absorption coefficient per unit pressure of 1-1 difluoroethylene at the P(22) and P(24) lines of the 10.4 micron CO2 band was measured. The FIR line pumped by P(22) occurs at approximately 890 microns, which may be in an atmospheric transmission window. It was found that significant Stark tuning of absorption lines of methanol and 1-1 difluoroethylene can be accomplished, even at the usual 100 to 300 mTorr operating pressures of FIR lasers. This means that the use of Stark tuning may enable more effective use of pump laser output

Application of NASTRAN for stress analysis of left ventricle of the heart

Knowing the stress and strain distributions in the left ventricular wall of the heart is a prerequisite for the determination of the muscle elasticity and contractility in the process of assessing the functional status of the heart. NASTRAN was applied for the calculation of these stresses and strains and to help in verifying the results obtained by the computer program FEAMPS which was specifically designed for the plane-strain finite-element analysis of the left ventricular cross sections. Adopted for the analysis are the true shape and dimensions of the cross sections reconstructed from multiplanar X-ray views of a left ventricle which was surgically isolated from a dog's heart but metabolically supported to sustain its beating. A preprocessor was prepared to accommodate both FEAMPS and NASTRAN, and it has also facilitated the application of both the triangular element and isoparameteric quadrilateral element versions of NASTRAN. The stresses in several crucial regions of the left ventricular wall calculated by these two independently developed computer programs are found to be in good agreement. Such confirmation of the results is essential in the development of a method which assesses the heart performance

Laser technology for communications Semiannual technical progress report, 1 Feb. - 31 Jul. 1970

Laser communication and Stark modulation of CO2 laser, competition between transitions in CO2 laser, and very high resolution inverted Lamb dip spectra of SF

Spectral Analysis of Elastic Waves Scattered by Objects with Smooth Surfaces

This is a summary of the research on NDE performed during the last two years by the authors and Professor W. Sachse and Messrs . S. Sancar and G. C. C. Ku of the Department of Theoretical and Applied Mechanics at Cornell University. The report is divided into three parts: (1) Theoretical Spectra-Results based on the method of wave function expansion and the method of transition matrix (T-matrix) will be presented for the scattering by a circular cylindrical, elliptic cylindrical, spherical, and spheroidal (prolate or oblate) inclusions in solids. Additional results for the scattering by two circular cylindrical inclusions will also be shown. (2) Interpretation of Spectra - Spectra of a fluid inclusion may be interpreted on the basis of the theory of normal modes, and those of a cavity from the principle of interference. Spectra for two cylindrical cavities exhibit new features which are related to the interferences of waves diffracted by each cavity. (3) Comparison with Experiments - Some of the theoretical spectra are compared with experimental results obtained by Professor W. Sachse and his associates

Faxen relations in solids - a generalized approach to particle motion in elasticity and viscoelasticity

A movable inclusion in an elastic material oscillates as a rigid body with six degrees of freedom. Displacement/rotation and force/moment tensors which express the motion of the inclusion in terms of the displacement and force at arbitrary exterior points are introduced. Using reciprocity arguments two general identities are derived relating these tensors. Applications of the identities to spherical particles provide several new results, including simple expressions for the force and moment on the particle due to plane wave excitation.Comment: 11 pages, 4 figure

New techniques in television to provide research in three-dimensional real-time or near real-time imagery and reduced cost systems for teleconferencing and educational uses, part 1

The results are presented of a continuing research and development program the objective of which is to develop a reduced bandwidth television system and a technique for television transmission of holograms. The result of the former is a variable frame rate television system, the operation of which was demonstrated for both black-and-white and color signals. This system employs a novel combination of the inexpensive mass storage capacity of a magnetic disc with the reliability of a digital system for time expansion and compression. Also reported are the results of a theoretical analysis and preliminary feasibility experiment of an innovative system for television transmission of holograms using relatively conventional TV equipment along with a phase modulated reference wave for production of the original interference pattern

Application of Deep Learning Long Short-Term Memory in Energy Demand Forecasting

The smart metering infrastructure has changed how electricity is measured in both residential and industrial application. The large amount of data collected by smart meter per day provides a huge potential for analytics to support the operation of a smart grid, an example of which is energy demand forecasting. Short term energy forecasting can be used by utilities to assess if any forecasted peak energy demand would have an adverse effect on the power system transmission and distribution infrastructure. It can also help in load scheduling and demand side management. Many techniques have been proposed to forecast time series including Support Vector Machine, Artificial Neural Network and Deep Learning. In this work we use Long Short Term Memory architecture to forecast 3-day ahead energy demand across each month in the year. The results show that 3-day ahead demand can be accurately forecasted with a Mean Absolute Percentage Error of 3.15%. In addition to that, the paper proposes way to quantify the time as a feature to be used in the training phase which is shown to affect the network performance