General Electric

About: General Electric is a company organization based out in Boston, Massachusetts, United States. It is known for research contribution in the topics: Turbine & Rotor (electric). The organization has 76365 authors who have published 110557 publications receiving 1885108 citations. The organization is also known as: General Electric Company & GE.

Syntax-Directed Transduction

Abstract: A transduction is a mapping from one set of sequences to another. A syntax-directed transduction is a particular type of transduction which is defined on the grammar of a context-free language and which is meant to be a model of part of the translation process used in many compilers. The transduction is considered from an automata theory viewpoint as specifying the input-output relation of a machine. Special consideration is given to machines called translators which both transduce and recognize. In particular, some special conditions are investigated under which syntax-directed translations can be performed on (deterministic) pushdown machines. In addition, some time bounds for translations on Turing machines are derived.

The performance of some correlation coefficients for a general bivariate distribution

Abstract: Association between two variables has in the past been measured or tested by several coefficients, among them (i) Product moment correlation coefficient. (ii) Spearman's rank correlation coefficient. (iii) Kendall's alternative rank coefficient T. (iv) Probability of concordance. The efficiency of each of these coefficients in detecting association between two variables is not in general known, but it is known that none is uniformly better than the others. Conjectures have been made that coefficients (ii) and (iii) behave in much the same way for reasonable distributions, but as pointed out by Daniels (1950) a sample ranking can be considered for which (ii) and (iii) have very different values. If the population is such that rankings of this type have appreciable probability, it would be expected that tests based on (ii) and (iii) would have different efficiencies. It would obviously be desirable if the performance of these coefficients could be studied for a fairly general class of distributions, in order to gain insight into the relationship between the coefficients. The class of bivariate distributions obtained from monotonic transformations of variates originally possessing a bivariate Normal distribution has been studied by Fieller, Hartley & Pearson (1957) by means of random samples of correlated Normal deviates. They concluded that for sample sizes 30 and 50 with correlation greater than 0-6 in the original bivariate normal distribution Kendall's coefficient was probably better than Spearman's. Correspondence with one of the authors, E. S. Pearson, indicates that the Fisher-Yates statistic mentioned in their paper is better than either rank correlation coefficient within this same field. Another such general class of distributions has been considered by Konijn (1958), namely, the class derived from linear combinations of two independent variables. It is the purpose of this paper first to propose a general class of bivariate distribution functions; secondly, to study how the various coefficients of association compare in efficiency with each other and with a maximum likelihood estimator of the parameter of association; and finally to use the general results to determine which are the best coefficients to use in a number of special cases. The efficiency measure used in this paper will be the asymptotic relative efficiency, in the neighbourhood of independence, as defined by Pitman (1948). The form of the bivariate distribution function proposed in this paper is an extension of an idea of Morgenstern; see, for example, Gumbel (1958). Morgenstern (1956) proposed F(x) G(y) [1+ c{1 F(x)} {I G(y)}] as a bivariate distribution function having F(x), G(y) as marginal distribution functions, and Gumbel noted that this differed from the bivariate normal distribution if F(x) =_ (x) and G(y) --4(y) where (D is the normal error function.

Thin Silicone Membranes-Their Permeation Properties and Some Applications

Abstract: While the permeation of gases through solid materials is often a nuisance and sometimes a hazard, in recent years several useful applications have been found for this phenomenon. For example, H, is purified by diffusion through Pd-Ag foils, 0, partial pressures are measured in instruments dependent on 0, permeating through a plastic membrane, and artificial lungs based on permeation of 0, and CO, through thin polymeric membranes are being developed. These applications are only the beginning, for recent advances in membrane technology portend uses as far afield as water desalination by reverse osmosis and the separation of azeotropes by membrane perm-vaporation. When one wishes to separate noncondensable gases by a membrane technique, his first consideration should be whether a silicone rubber membrane can be used. This stems from the unusually high permeability of silicone rubber, indicated in TABLE 1, a tabulation of 0, permeabilities in various membranes.

Reduction of Wind Turbine Noise using Optimized Airfoils and Trailing-Edge Serrations

Abstract: Acoustic field measurements were carried out on a 94-m-diam three-bladed wind turbine with one standard blade, one blade with trailing-edge serrations, and one blade with an optimized airfoil shape. A large horizontal microphone array, positioned at a distance of about one rotor diameter from the turbine, was used to locate and quantify the noise sources in the rotor plane and on the individual blades. The acoustic source maps show that for an observer at the array position, the dominant source for the baseline blade is trailing-edge noise from the blade outboard region. Because of convective amplification and directivity, practically all of this noise is produced during the downward movement of the blade, which causes the typical swishing noise during the passage of the blades. Both modified blades show a significant trailing-edge noise reduction at low frequencies, which is more prominent for the serrated blade. However, the modified blades also show tip noise at high frequencies, which is mainly radiated during the upward part of the revolution and is most important at low wind speeds due to high tip loading. Nevertheless, average overall noise reductions of 0.5 and 3.2 dB are obtained for the optimized blade and the serrated blade, respectively.

Selective gas sensing with a single pristine graphene transistor.

Abstract: We show that vapors of different chemicals produce distinguishably different effects on the low-frequency noise spectra of graphene. It was found in a systematic study that some gases change the electrical resistance of graphene devices without changing their low-frequency noise spectra while other gases modify the noise spectra by inducing Lorentzian components with distinctive features. The characteristic frequency fc of the Lorentzian noise bulges in graphene devices is different for different chemicals and varies from fc = 10–20 Hz to fc = 1300–1600 Hz for tetrahydrofuran and chloroform vapors, respectively. The obtained results indicate that the low-frequency noise in combination with other sensing parameters can allow one to achieve the selective gas sensing with a single pristine graphene transistor. Our method of gas sensing with graphene does not require graphene surface functionalization or fabrication of an array of the devices with each tuned to a certain chemical.