El Paso Corporation was a provider of natural gas and related energy products and was one of North America's largest natural gas producers until its acquisition by Kinder Morgan in 2012. It was headquartered in Houston, Texas. United States.Prior to the takeover by Kinder Morgan, the company owned North America's largest natural gas pipeline system which traveled from border-to-border and coast-to-coast. The system included Colorado Interstate Gas, El Paso Natural Gas, Southern Natural Gas, Tennessee Gas Pipeline, Cheyenne Plains Pipeline, Mojave Pipeline, Elba Express Pipeline, Young Gas Storage, Wyoming Interstate Company and Ruby Pipeline. The El Paso Corporation also owned fifty percent of Great Lakes Transmission and Florida Gas Transmission and employed 6,000 people. Florida Gas is part of Southern Natural Gas. In 1999 the company doubled in size when it merged with Birmingham, Alabama based natural gas giant Sonat. It went on to acquire Coastal Corporation in 2001.The company's major offices were located in Houston, Texas, Birmingham, Alabama and Colorado Springs, Colorado. The company's CEO at the time of sale to Kinder Morgan was Douglas L. Foshee. Wikipedia.
Dokken K.M.,Kansas State University |
Dokken K.M.,El Paso Corporation |
Davis L.C.,Kansas State University
Journal of Environmental Quality | Year: 2011
Infrared microspectroscopy (IMS) is emerging as an important analytical tool for the structural analysis of biological tissue. This report describes the use of IMS coupled to a synchrotron source combined with principal components analysis (PCA) to monitor the fate and effect of dinitrotoluenes in the roots of maize and sunflower plants. Infrared imaging revealed that maize roots metabolized 2,4-dinitrotoluene (DNT) and 2,6-DNT. The DNTs and their derivative aromatic amines were predominantly associated with epidermis and xylem. Both isomers of DNT altered the structure and production of pectin and pectic polysaccharides in maize and sunflower plant roots. Infrared peaks diagnostic for aromatic amines were seen at the 5 mg L-1 concentrations for both DNTs in maize and sunflower treated tissue. However, only infrared peaks for nitro groups, not aromatic amines, were present in the maize treated at 10 mg L-1. For sunflower, the 10 mg L-1 level was toxic and also produced very dark root systems making spectra difficult to obtain. Maize and sunflower seem unable to metabolize eff ectively at concentrations higher than about 5 mg L-1DNT in hydroponic solution. Based on the results of this study, IMS combined wiThPCA can be an eff ective means of determining the fate and metabolism of organic contaminants in plant tissue when isotopically labeled compounds are not available. © 2011 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. Source
Rivas-Perea P.,Baylor University |
Cota-Ruiz J.,Autonomous University of Ciudad Juarez |
Rosiles J.-G.,El Paso Corporation
International Journal of Machine Learning and Cybernetics | Year: 2014
This paper studies the problem of hyper-parameters selection for a linear programming-based support vector machine for regression (LP-SVR). The proposed model is a generalized method that minimizes a linear-least squares problem using a globalization strategy, inexact computation of first order information, and an existing analytical method for estimating the initial point in the hyper-parameters space. The minimization problem consists of finding the set of hyper-parameters that minimizes any generalization error function for different problems. Particularly, this research explores the case of two-class, multi-class, and regression problems. Simulation results among standard data sets suggest that the algorithm achieves statistically insignificant variability when measuring the residual error; and when compared to other methods for hyper-parameters search, the proposed method produces the lowest root mean squared error in most cases. Experimental analysis suggests that the proposed approach is better suited for large-scale applications for the particular case of an LP-SVR. Moreover, due to its mathematical formulation, the proposed method can be extended in order to estimate any number of hyper-parameters. © 2013 Springer-Verlag Berlin Heidelberg. Source
Carreon J.A.,El Paso Corporation |
Cabrera S.D.,University of Texas at El Paso
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2013
Detection and estimation of wideband radio frequency signals are major functions of persistent surveillance systems and rely heavily on high sampling rates dictated by the Nyquist-Shannon sampling theorem. In this paper we address the problem of detecting wideband signals in the presence of AWGN and interference with a fraction of the measurements produced by traditional sampling protocols. Our approach uses learned dictionaries in order to work with less restriction on the class of signals to be analyzed and Compressive Sensing (CS) to reduce the number of samples required to process said signals. We apply the K-SVD technique to design a dictionary, reconstruct using a recently developed signal-centric reconstruction algorithm (SSCoSaMP), then use maximum likelihood estimation to detect and estimate the carrier frequencies of wideband RF signals while assuming no prior knowledge of the frequency location. This solution relaxes the assumption that signals are sparse in a fixed/predetermined orthonormal basis and reduces the number of measurements required to detect wideband signals all while having comparable error performance to traditional detection schemes. Simulations of frequency hopping signals corrupted by additive noise and chirp interference are presented. Other experimental results are included to illustrate the flexibility of learned dictionaries whereby the roles of the chirps and the sinusoids are reversed. © 2013 SPIE. Source
El Paso Corporation | Date: 2015-06-01
Cartomizers, namely, combination electronic cigarette refill cartridges sold empty and atomizers, sold as a component of electronic cigarettes; Cartridges sold filled with chemical flavorings in liquid form for electronic cigarettes; Cartridges sold filled with propylene glycol for electronic cigarettes; Cartridges sold filled with vegetable glycerin for electronic cigarettes; Cases for electronic cigarettes and electronic cigarette accessories; Chemical flavorings in liquid form used to refill electronic cigarette cartridges; Electronic cigarette boxes; Electronic cigarette cases; Electronic cigarette liquid (e-liquid) comprised of flavorings in liquid form used to refill electronic cigarette cartridges; Electronic cigarettes.
El Paso Corporation | Date: 2015-02-23
Electronic cigarettes; Smokeless cigarette vaporizer pipe.