Industry application of behavioral science

One of the more significant errors in the history of science occurred during the “marginal revolution” in economics near the end of the nineteenth century. Rather than explicitly recognize in basic theory that the happiness we seek to maximize in life originates within oneself, the early theorists formulated their equations as though human satisfaction resided in external things-as in so much utility (economist's term for satisfaction) per pound of sugar. Over the past 125 years, economists have developed mainstream mathematical economics on this incorrect basis resulting in the ill-founded neoclassical Equilibrium Theory. Because of this error economic theory is fundamentally timeless. The present theory, in its canonical form, corrects the early marginalist's error by identifying utility (time-integrated pleasure) exclusively with the stream-of-consciousness attending (expected) mental and physical activity. Time is now explicit in basic theory, thereby allowing, for the first time, the substantive computer-modeling of time-dependent, small- and large-scale economic systems. Furthermore, this new approach is methodologically compatible with mainstream sociology and institutional economics, allowing increased interdisciplinary cooperation that may influence policy and thereby affect industry and markets. And safety engineering stands to benefit from the accommodation of neuropsychology in understanding human error in the supervision and control of technology     

The Radarsat Antarctic Mapping Mission

The Radarsat Earth-observation satellite was launched on November 4, 1995 aboard a Delta 2 rocket. Equipped with a sophisticated synthetic aperture radar (SAR), Radarsat can produce images of extraordinary clarity even through clouds, smog, haze, smoke, and darkness. The SAR has a variety of operating modes. It can be adjusted to produce swathes between 35 and 500 km in width, with ground resolutions from 100 m to as low as eight. In addition, the beam can be steered at angles up to 49° from the satellite's nadir vector, giving it the unique ability to image areas it is not directly overflying. In exchange for the launch, CSA agreed to provide NASA with access to the SAR data, and to execute a 180° yaw-around of Radarsat twice during its lifetime to map the Antarctic continent. Preliminary results from the first of these Antarctic Mapping Missions, dubbed AMM-1, are presented     

An interior point linear programming approach to two-scan dataassociation

We present an efficient two-scan data association method (TSDA) based on an interior point linear programming (LP) approach. In this approach, the TSDA problem is first formulated as a 3-dimensional assignment problem, and then relaxed to a linear program; the latter is subsequently solved by the highly efficient homogeneous, self-dual interior point LP algorithm. When the LP algorithm generates a fractional optimal solution, we use a technique similar to the joint probabilistic data association method (JPDA) to compute a weighted average of the resulting fractional assignments, and use it to update the states of the existing tracks generated by Kalman filters. Unlike the traditional single scan JPDA method, our TSDA method provides an explicit mechanism for track initiation. Extensive computer simulations have demonstrated that the new TSDA method is not only far more efficient in terms of low computational complexity, but also considerably more accurate than the existing single-scan JPDA method     

Analysis and results of the 1995 Yuma ground penetration SARmeasurements

In July and October 1995, a large-scale airborne SAR experiment was conducted in the Yuma Proving Ground, Yuma, Arizona, to investigate ground penetration radar phenomenology and buried target detection. This paper describes the Yuma experiment and measurement results for many tactical, utility, and environmental targets deployed in the test     

UWB radar detection of targets in foliage using alpha-stableclutter models

We address the problem of detection of targets obscured by a forest canopy using an ultrawideband (UWB) radar. The forest clutter observed in the radar imagery is a highly impulsive random process that is more accurately modeled with the recently proposed class of alpha-stable processes as compared with Gaussian, Weibull, and K-distribution models. With this more accurate model, segmentation is performed on the imagery into forest and clear regions. Further, a region-adaptive symmetric alpha stable (SαS) constant false-alarm rate (CFAR) detector is introduced and its performance is compared with the Weibull and Gaussian CFAR detectors. The results on real data show that the SαS CFAR performs better than the Weibull and Gaussian CFAR detectors in detecting obscured targets     

Intelligent control of a planning system for astronaut training

This work intends to design, analyze and solve, from the systems control perspective, a complex, dynamic, and multiconstrained planning system for generating training plans for crew members of the NASA-led International Space Station. Various intelligent planning systems have been developed within the framework of artificial intelligence. These planning systems generally lack a rigorous mathematical formalism to allow a reliable and flexible methodology for their design, modeling, and performance analysis in a dynamical, time-critical, and multiconstrained environment. Formulating the planning problem in the domain of discrete-event systems under a unified framework such that it can be modeled, designed, and analyzed as a control system will provide a self-contained theory for such planning systems. This will also provide a means to certify various planning systems for operations in the dynamical and complex environments in space. The work presented here completes the design, development, and analysis of an intricate, large-scale, and representative mathematical formulation for intelligent control of a real planning system for Space Station crew training. This planning system has been tested and used at NASA-Johnson Space Center     

Power management and distribution system for a more-electricaircraft (MADMEL)

A five-phase Power Management and Distribution System for a More-Electric Aircraft (MADMEL) program was awarded by the Air Force to Northrop/Grumman Military Aircraft Division in September 1991. The objective of the program is to design, develop, and demonstrate an advanced electrical power generation and distribution system for a More-Electric Aircraft (MEA). The MEA emphasizes the use of electrical power in place of hydraulics, pneumatic, and mechanical power to optimize the performance and life cycle cost of the aircraft. This paper presents an overview of the MADMEL program and a top-level summary of the program results, development and test of major components to date. In Phase I and Phase II studies, the electrical load requirements were established and the electrical power system architecture was defined for both near-term (NT-year 1996) and far-term (FT-year 2003) MEA application. The detailed design and specification for the Electrical Power System (EPS), its interface with the Vehicle Management System, and the test set-up were developed under Phase III. Phase IV, fabrication and testing of the subsystem level hardware, has been completed. Overall system level integration and testing, Phase V, is scheduled to be completed by September 1999     

A Method of Constructing a Pair of Pseudorandom Sequences with a Useful Crosscorrelation Function

The synthesizing of pseudorandom signals which possess an odd crosscorrelation function of useful characteristics is presented. The characteristics are applicable for signal tracking systems such as those associated with ranging instrumentation and spread-spectrum communication. Another property of these signals is that they possess a zero dc component which may be applied for radiating useful carrierless signals.     

A Parallel Adaptive 3D MHD Scheme for Modeling Coronal and Solar Wind Plasma Flows

A parallel adaptive mesh refinement (AMR) scheme is described for solving the governing equations of ideal magnetohydrodynamics (MHD) in three space dimensions. This solution algorithm makes use of modern finite-volume numerical methodology to provide a combination of high solution accuracy and computational robustness. Efficient and scalable implementations of the method have been developed for massively parallel computer architectures and high performance achieved. Numerical results are discussed for a simplified model of the initiation and evolution of coronal mass ejections (CMEs) in the inner heliosphere. The results demonstrate the potential of this numerical tool for enhancing our understanding of coronal and solar wind plasma processes. This revised version was published online in June 2006 with corrections to the Cover Date.     

Large-scale Coronal Heating, Clustering of Coronal Bright Points, and Concentration of Magnetic Flux

By combining quiet-region Fe XII coronal images from SOHO/EIT with magnetograms from NSO/Kitt Peak and from SOHO/MDI, we show that the population of network coronal bright points and the magnetic flux content of the network are both markedly greater under the bright half of the large-scale quiet corona than under the dim half. These results (1) support the view that the heating of the entire corona in quiet regions and coronal holes is driven by fine-scale magnetic activity (microflares, explosive events, spicules) seated low in the magnetic network, and (2) suggest that this large-scale modulation of the magnetic flux and coronal heating is a signature of giant convection cells. This revised version was published online in June 2006 with corrections to the Cover Date.