945,547 research outputs found

    Radar Investigation of Mars, Mercury, and Titan

    Get PDF
    Radar astronomy is the study of the surfaces and near surfaces of Solar System objects using active transmission of modulated radio waves and the detection of the reflected energy. The scientific goals of such experiments are surprisingly broad and include the study of surface slopes, fault lines, craters, mountain ranges, and other morphological structures. Electrical reflectivities contain information about surface densities and, to some extent, the chemical composition of the surface layers. Radar probes the subsurface layers to depths of the order of 10 wavelengths, providing geological mapping and determinations of the object’s spin state. Radar also allows one to study an object’s atmosphere and ionic layers as well as those of the interplanetary medium. Precise measurements of the time delay to surface elements provide topographic maps and powerful information on planetary motions and tests of gravitational theories such as general relativity. In this paper, we limit our discussion to surface and near-surface probing of Mercury, Mars, and Titan and review the work of the past decade, which includes fundamentally new techniques for Earth-based imaging. The most primitive experiments involve just the measurement of the total echo power from the object. The most sophisticated experiments would produce spatially resolved maps of the reflected power in all four Stokes’ parameters. Historically, the first experiments produced echoes from the Moon during the period shortly after World War II (see e.g. Evans 1962), but the subject did not really develop until the early 1960s when the radio equipment was sufficiently sensitive to detect echoes from Venus and obtain the first Doppler strip "maps" of that planet. The first successful planetary radar systems were the Continuous Wave (CW) radar at the Goldstone facility of the Caltech’s Jet Propulsion Laboratory and the pulse radar at the MIT Lincoln Laboratory. All of the terrestrial planets were successfully studied during the following decade, yielding the spin states of Venus and Mercury, a precise value of the astronomical unit, and a host of totally new discoveries concerning the surfaces of the terrestrial planets and the Moon. This work opened up at least a similar number of new questions. Although the early work was done at resolution scales on the order of the planetary radii, very rapid increases in system sensitivities improved the resolution to the order of 100 km, but always with map ambiguities. Recently, unambiguous resolution of 100 m over nearly the entire surface of Venus has been achieved from the Magellan spacecraft using a side-looking, synthetic aperture radar. Reviews of the work up to the Magellan era can be found in Evans (1962), Muhleman et al (1965), Evans & Hagfors (1968, see chapters written by G Pettengill, T Hagfors, and J Evans), and Ostro (1993). The radar study of Venus from the Magellan spacecraft was a tour de force and is well described in special issues of Science (volume 252, April 12, 1991) and in the Journal of Geophysical Research (volume 97, August 25 and October 25, 1992). Venus will not be considered in this paper even though important polarization work on that planet continues at Arecibo, Goldstone, and the Very Large Array (VLA). In this paper we review the most recent work in Earth-based radar astronomy using new techniques of Earth rotation, super synthesis at the VLA in New Mexico (operated by the National Radio Astronomy Observatory), and the recently developed "long-code" techniques at the Arecibo Observatory in Puerto Rico (operated by Cornell University). [Note: It was recently brought to our attention that the VLA software "doubles" the flux density of their primary calibrators. Consequently, it is necessary to half the radar power and reflectivity numerical values in all of our published radar results from the VLA/Goldstone radar.] The symbiotic relationship in these new developments for recent advances in our understanding of Mercury and Mars is remarkable. VLA imaging provides for the first time, unambiguous images of an entire hemisphere of a planet and the long-code technique makes it possible to map Mars and Mercury using the traditional range-gated Doppler strip mapping procedure [which was, apparently, developed theoretically at the Lincoln Laboratory by Paul Green, based on a citation in Evans (1962)]. Richard Goldstein was the first to obtain range-gated planetary maps of Venus as reported in Carpenter & Goldstein (1963). Such a system was developed earlier for the Moon as reported by Pettengill (1960) and Pettengill & Henry (1962). We first discuss the synthesis mapping technique

    A multiobjective model for passive portfolio management: an application on the S&P 100 index

    Get PDF
    This is an author's accepted manuscript of an article published in: “Journal of Business Economics and Management"; Volume 14, Issue 4, 2013; copyright Taylor & Francis; available online at: http://dx.doi.org/10.3846/16111699.2012.668859Index tracking seeks to minimize the unsystematic risk component by imitating the movements of a reference index. Partial index tracking only considers a subset of the stocks in the index, enabling a substantial cost reduction in comparison with full tracking. Nevertheless, when heterogeneous investment profiles are to be satisfied, traditional index tracking techniques may need different stocks to build the different portfolios. The aim of this paper is to propose a methodology that enables a fund s manager to satisfy different clients investment profiles but using in all cases the same subset of stocks, and considering not only one particular criterion but a compromise between several criteria. For this purpose we use a mathematical programming model that considers the tracking error variance, the excess return and the variance of the portfolio plus the curvature of the tracking frontier. The curvature is not defined for a particular portfolio, but for all the portfolios in the tracking frontier. This way funds managers can offer their clients a wide range of risk-return combinations just picking the appropriate portfolio in the frontier, all of these portfolios sharing the same shares but with different weights. An example of our proposal is applied on the S&P 100.García García, F.; Guijarro Martínez, F.; Moya Clemente, I. (2013). A multiobjective model for passive portfolio management: an application on the S&P 100 index. Journal of Business Economics and Management. 14(4):758-775. doi:10.3846/16111699.2012.668859S758775144Aktan, B., Korsakienė, R., & Smaliukienė, R. (2010). TIME‐VARYING VOLATILITY MODELLING OF BALTIC STOCK MARKETS. Journal of Business Economics and Management, 11(3), 511-532. doi:10.3846/jbem.2010.25Ballestero, E., & Romero, C. (1991). A theorem connecting utility function optimization and compromise programming. Operations Research Letters, 10(7), 421-427. doi:10.1016/0167-6377(91)90045-qBeasley, J. E. (1990). OR-Library: Distributing Test Problems by Electronic Mail. Journal of the Operational Research Society, 41(11), 1069-1072. doi:10.1057/jors.1990.166Beasley, J. E., Meade, N., & Chang, T.-J. (2003). An evolutionary heuristic for the index tracking problem. European Journal of Operational Research, 148(3), 621-643. doi:10.1016/s0377-2217(02)00425-3Canakgoz, N. A., & Beasley, J. E. (2009). Mixed-integer programming approaches for index tracking and enhanced indexation. European Journal of Operational Research, 196(1), 384-399. doi:10.1016/j.ejor.2008.03.015Connor, G., & Leland, H. (1995). Cash Management for Index Tracking. Financial Analysts Journal, 51(6), 75-80. doi:10.2469/faj.v51.n6.1952Corielli, F., & Marcellino, M. (2006). Factor based index tracking. Journal of Banking & Finance, 30(8), 2215-2233. doi:10.1016/j.jbankfin.2005.07.012Derigs, U., & Nickel, N.-H. (2004). On a Local-Search Heuristic for a Class of Tracking Error Minimization Problems in Portfolio Management. Annals of Operations Research, 131(1-4), 45-77. doi:10.1023/b:anor.0000039512.98833.5aDose, C., & Cincotti, S. (2005). Clustering of financial time series with application to index and enhanced index tracking portfolio. Physica A: Statistical Mechanics and its Applications, 355(1), 145-151. doi:10.1016/j.physa.2005.02.078Focardi, S. M., & Fabozzi 3, F. J. (2004). A methodology for index tracking based on time-series clustering. Quantitative Finance, 4(4), 417-425. doi:10.1080/14697680400008668Gaivoronski, A. A., Krylov, S., & van der Wijst, N. (2005). Optimal portfolio selection and dynamic benchmark tracking. European Journal of Operational Research, 163(1), 115-131. doi:10.1016/j.ejor.2003.12.001Hallerbach, W. G., & Spronk, J. (2002). The relevance of MCDM for financial decisions. Journal of Multi-Criteria Decision Analysis, 11(4-5), 187-195. doi:10.1002/mcda.328Jarrett, J. E., & Schilling, J. (2008). DAILY VARIATION AND PREDICTING STOCK MARKET RETURNS FOR THE FRANKFURTER BÖRSE (STOCK MARKET). Journal of Business Economics and Management, 9(3), 189-198. doi:10.3846/1611-1699.2008.9.189-198Roll, R. (1992). A Mean/Variance Analysis of Tracking Error. The Journal of Portfolio Management, 18(4), 13-22. doi:10.3905/jpm.1992.701922Rudolf, M., Wolter, H.-J., & Zimmermann, H. (1999). A linear model for tracking error minimization. Journal of Banking & Finance, 23(1), 85-103. doi:10.1016/s0378-4266(98)00076-4Ruiz-Torrubiano, R., & Suárez, A. (2008). A hybrid optimization approach to index tracking. Annals of Operations Research, 166(1), 57-71. doi:10.1007/s10479-008-0404-4Rutkauskas, A. V., & Stasytyte, V. (s. f.). Decision Making Strategies in Global Exchange and Capital Markets. Advances and Innovations in Systems, Computing Sciences and Software Engineering, 17-22. doi:10.1007/978-1-4020-6264-3_4Tabata, Y., & Takeda, E. (1995). Bicriteria Optimization Problem of Designing an Index Fund. Journal of the Operational Research Society, 46(8), 1023-1032. doi:10.1057/jors.1995.139Teresienė, D. (2009). LITHUANIAN STOCK MARKET ANALYSIS USING A SET OF GARCH MODELS. Journal of Business Economics and Management, 10(4), 349-360. doi:10.3846/1611-1699.2009.10.349-36

    Control, Process Facilitation, and Requirements Change in Offshore Requirements Analysis: The Provider Perspective

    Get PDF
    Process, technology, and project factors have been increasingly driving organizations to offshore early software development phases, such as requirements analysis. This emerging trend necessitates greater control and process facilitation between client and vendor sites. The effectiveness of control and facilitation has, however, not been examined within the context of requirements analysis and change. In this study, we examine the role of control and facilitation in managing changing requirements and on success of requirements gathering in the Indian offshore software development environment. Firms found that control by client-site coordinators had a positive impact on requirements analysis success while vender site-coordinators did not have similar influence. Process facilitation by client site-coordinators affected requirements phase success indirectly through control. The study concludes with recommendations for research and practice
    corecore