Timothy J. Dasey

Measurements of aircraft wake vortices at Memphis International Airport with a cw CO2 coherent laser radar

A CW-coherent laser radar using a 20-watt CO2 laser has been constructed and deployed for the measurement of wake-vortex turbulence. This effort is part of the NASA Terminal Area Productivity Program and has the goal of providing information to further the understanding of the motion and decay of wake vortices as influenced by the local atmospheric conditions. To meet this goal, vortex measurements are made with the lidar along with simultaneous measurements from a suite of meteorological sensors which include a 150 foot instrumented tower, a profiler/RASS, sodar and balloon soundings. The information collected also includes airline flight data and beacon data. The operation of the lidar during two field deployments at Memphis International Airport are described as well as examples of vortex motion and decay measurements in various atmospheric conditions.

Vortex and meteorological measurements at Dallas/Ft. Worth airport

As part of NASA’s Aircraft Vortex Spacing System (AVOSS), Lincoln Laboratory conducted meteorological and wake vortex data collections at Dallas/Ft. Worth (DFW) airport in 1997. A mobile continuous-wave coherent CO2 laser radar was utilized to detect and track vortices generated by landing aircraft. Associated meteorological data were acquired by an extensive array of weather sensors. The DFW deployment is described here along with a preliminary analysis of vortex data. Vortex measurements from a 1995 lidar deployment in Memphis are also included in the analysis.

Computational intelligence in biological sensing

This paper presents an alternative, computational intelligence based paradigm for biological attack detection. Conventional approaches to this difficult problem include sensor technologies and analytical modeling approaches. However, the processes that constitute the environmental background as well as those which occur as the result of an attack are extremely complex. This phenomenological complexity, in terms of both physics and biology aspects, is a challenge difficult to overcome by conventional approaches. In contrast to such approaches, the proposed approach is centered on automatic learning to discriminate between sensor signals that are in a normal range from those that are likely to represent a biological attack. It is argued that constructing machine learning methods robust enough to perform such a task is often more feasible than constructing an adequate model that could form a basis for bioattack detection. The paper discusses machine learning and multisensor information fusion methods in the context of biological attack detection in a subway environment, including recognition architecture and its components. However, the applicability of the proposed approach is much broader than the subway bioattack protection case, extending to a wide range of CBR defense applications.

Inner rehearsal modeling for cognitive robotics

This paper presents a biomimetic approach involving cognitive process modeling, for use in intelligent robot decisionmaking. The principle of inner rehearsal, a process believed to occur in human and animal cognition, involves internal rehearsing of actions prior to deciding on and executing an overt action, such as a motor action. The inner-rehearsal algorithmic approach we developed is posed and investigated in the context of a relatively complex cognitive task, an under-rubble search and rescue. The paper presents the approach developed, a synthetic environment which was also developed to enable its studies, and the results to date. The work reported here is part of a Cognitive Robotics effort in which we are currently engaged, focused on exploring techniques inspired by cognitive science and neuroscience insights, towards artificial cognition for robotics and autonomous systems.

A statistical analysis of approach winds at capacity-restricted airports

Since ambient wind speed and direction are the most important factors when considering the possibility of a lateral wake vortex encounter, wind behavior around airports with closely-spaced parallel (CSP) runways needs to be well understood before simultaneous approaches during restrictive weather could ever be used in an operational setting. This paper presents a statistical analysis of wind behavior for several major airports with CSP runways by using aircraft wind observations. Specifically, speed and direction characteristics of headwinds and crosswinds are examined, as well as correlations between the two wind components with respect to each other and with respect to altitude. The resulting data should prove useful for Monte Carlo simulations of new CSP approach procedures.

User-Customizable Health Pattern Detector Framework: Twitter Analysis Example

A general-purpose method for automatic detection algorithm reengineering based upon Twitter keyword queries using user relevance/irrelevance feedback has been demonstrated to have superior performance and versatility compared to more static detection methods. A demonstration of the capability with an initial user interface has been performed. An extension of the processing that includes initial query term expansion prior to application of the customized detection is being investigated.