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At least 883 records · Page 49

Automated Drug Identification for Urban Hospitals

Many urban hospitals are becoming overloaded with drug abuse cases requiring chemical analysis for identification of drugs. In this paper, the requirements for chemical analysis of body fluids for drugs are determined and a system model for automated drug analysis is selected. The system as modeled, would perform chemical preparation of samples, gas-liquid chromatographic separation of drugs in the chemically prepared samples, infrared spectrophotometric analysis of the drugs, and would utilize automatic data processing and control for drug identification. Requirements of cost, maintainability, reliability, flexibility, and operability are considered.

Shirley, Donna L.↗

Fractional System Identification: An Approach Using Continuous Order-Distributions

This paper discusses the identification of fractional- and integer-order systems using the concept of continuous order-distribution. Based on the ability to define systems using continuous order-distributions, it is shown that frequency domain system identification can be performed using least squares techniques after discretizing the order-distribution.

Hartley, Tom T.↗

Identification of Terrestrial Reflectance From Remote Sensing

Correcting for atmospheric effects is an essential part of surface-reflectance recovery from radiance measurements. Model-based atmospheric correction techniques enable an accurate identification and classification of terrestrial reflectances from multi-spectral imagery. Successful and efficient removal of atmospheric effects from remote-sensing data is a key factor in the success of Earth observation missions. This report assesses the performance, robustness and sensitivity of two atmospheric-correction and reflectance-recovery techniques as part of an end-to-end simulation of hyper-spectral acquisition, identification and classification.

Alter-Gartenberg, Rachel↗

Search for the Identification of 3EG J1835+5918: Evidence for a New Type of High-Energy Gamma-Ray Source

The EGRET source 3EG J1835+5918 is the brightest and most accurately positioned of the as-yet unidentified high-energy gamma-ray sources at high Galactic latitude (l, b = 89 deg, 25 deg). We present a multiwavelength study of the region around it, including X-ray, radio, and optical imaging surveys, as well as optical spectroscopic classification of most of the active objects in this area. Identifications are made of all but one of the ROSAT and ASCA sources in this region to a flux limit of approximately 5 x 10(exp -14) erg/sq cm s, which is 10(exp -4) of the gamma-ray flux. The identified X-ray sources in or near the EGRET error ellipse are radio-quiet QSOs, a galaxy cluster, and coronal emitting stars. We also find eight quasars using purely optical color selection, and we have monitored the entire field for variable optical objects on short and long time scales without any notable discoveries. The radio sources inside the error ellipse are all fainter than 4 mJy at 1.4 GHz. There are no flat-spectrum radio sources in the vicinity; the brightest neighboring radio sources are steep-spectrum radio galaxies or quasars. Since no blazar-like or pulsar-like candidate has been found as a result of these searches, 3EG J1835+5918 must be lacking one or more of the physically essential attributes of these known classes of gamma-ray emitters. If it is an AGN it lacks the beamed emission radio of blazars by at least a factor of 100 relative to identified EGRET blazars. If it is an isolated neutron star, it lacks the steady thermal X-rays from a cooling surface and the magnetospheric non-thermal X-ray emission that is characteristic of all EGRET pulsars. If a pulsar, 3EG J1835+5918 must be either older or more distant than Geminga, and probably an even more efficient or beamed gamma-ray engine. One intermittent ROSA T source falls on a blank optical field to a limit of B greater than 23.4, V greater than 23.3, and R greater than 22.5. In view of this conspicuous absence, RX J1836-2+5925 should be examined further as a candidate for identification with 3EG J1835+5918 and possibly the prototype of a new class of high-energy gamma-ray source.

Mirabal, N.↗

Aeroservoelastic Uncertainty Model Identification from Flight Data

Uncertainty modeling is a critical element in the estimation of robust stability margins for stability boundary prediction and robust flight control system development. There has been a serious deficiency to date in aeroservoelastic data analysis with attention to uncertainty modeling. Uncertainty can be estimated from flight data using both parametric and nonparametric identification techniques. The model validation problem addressed in this paper is to identify aeroservoelastic models with associated uncertainty structures from a limited amount of controlled excitation inputs over an extensive flight envelope. The challenge to this problem is to update analytical models from flight data estimates while also deriving non-conservative uncertainty descriptions consistent with the flight data. Multisine control surface command inputs and control system feedbacks are used as signals in a wavelet-based modal parameter estimation procedure for model updates. Transfer function estimates are incorporated in a robust minimax estimation scheme to get input-output parameters and error bounds consistent with the data and model structure. Uncertainty estimates derived from the data in this manner provide an appropriate and relevant representation for model development and robust stability analysis. This model-plus-uncertainty identification procedure is applied to aeroservoelastic flight data from the NASA Dryden Flight Research Center F-18 Systems Research Aircraft.

Brenner, Martin J.↗

Chemical Detection and Identification Techniques for Exobiology Flight Experiments

Exobiology flight experiments require highly sensitive instrumentation for in situ analysis of the volatile chemical species that occur in the atmospheres and surfaces of various bodies within the solar system. The complex mixtures encountered place a heavy burden on the analytical Instrumentation to detect and identify all species present. The minimal resources available onboard for such missions mandate that the instruments provide maximum analytical capabilities with minimal requirements of volume, weight and consumables. Advances in technology may be achieved by increasing the amount of information acquired by a given technique with greater analytical capabilities and miniaturization of proven terrestrial technology. We describe here methods to develop analytical instruments for the detection and identification of a wide range of chemical species using Gas Chromatography. These efforts to expand the analytical capabilities of GC technology are focused on the development of detectors for the GC which provide sample identification independent of the GC retention time data. A novel new approach employs Penning Ionization Electron Spectroscopy (PIES).

Kojiro, Daniel R.↗

The Attentional Blink Does Not Prevent Character Identification

The standard RSVP Attentional Blink (AB) paradigm was modified so that RT to the second target could be measured. Character distortion, intended to prolong the letter-identification processing stage, had a marked effect at long lags (baseline condition), but virtually no effect at short lags where AB interference occurred. According to locus-of-slack logic, this pattern of results indicates that the attentional blink causes a processing bottleneck at some stage subsequent to letter identification.

Ruthruff, Eric↗

Adaptive Identification and Control of Flow-Induced Cavity Oscillations

Progress towards an adaptive self-tuning regulator (STR) for the cavity tone problem is discussed in this paper. Adaptive system identification algorithms were applied to an experimental cavity-flow tested as a prerequisite to control. In addition, a simple digital controller and a piezoelectric bimorph actuator were used to demonstrate multiple tone suppression. The control tests at Mach numbers of 0.275, 0.40, and 0.60 indicated approx. = 7dB tone reductions at multiple frequencies. Several different adaptive system identification algorithms were applied at a single freestream Mach number of 0.275. Adaptive finite-impulse response (FIR) filters of orders up to N = 100 were found to be unsuitable for modeling the cavity flow dynamics. Adaptive infinite-impulse response (IIR) filters of comparable order better captured the system dynamics. Two recursive algorithms, the least-mean square (LMS) and the recursive-least square (RLS), were utilized to update the adaptive filter coefficients. Given the sample-time requirements imposed by the cavity flow dynamics, the computational simplicity of the least mean squares (LMS) algorithm is advantageous for real-time control.

Kegerise, M. A.↗

Analysis of Moessbauer Data from Mars: A Database and Artificial Neural Network for Identification of Iron-bearing Phases

The exploration of the planet Mars is one of the major goals within the Solar system exploration programs of the US-American space agency NASA and the European Space Agency ESA. In particular the search for water and life and understanding of the history of the surface and atmosphere will be the major tasks of the upcoming space missions to Mars. The miniaturized Moessbauer spectrometer MIMOS II has been selected for the NASA Mars-Exploration-Rover twin-mission to Mars in 2003 and the ESA 2003 Mars-Express Beagle 2 mission. Reduced in size and weight, in comparison to ordinary laboratory setup, the sensor head just weights approximately 400 g, with a volume of (50x50x90) cu mm, and holds two gamma-ray sources: the stronger for experiments and the weaker for calibrations. The collimator (in sample direction) also shields the primary radiation off the detectors. Around the drive four detectors are mounted. The detectors are made of Si-PIN-photodiodes in chip form (100 sq mm, thickness of 0.5 mm). The control unit is located in a separate electronics board. This board is responsible for the power supply, generation of the drive's velocity reference signal, read of the detector pulses to record the spectrum, data storage and communication with the host computer. After more than four decades from the discovery of the Moessbauer effect, more than 400 minerals were studied at different temperatures. Their Moessbauer parameters were reported in the literature, and have been recently collected in a data bank. Previous Mars-missions, namely Viking and Mars Pathfinder, revealed Si, Al, Fe, Mg, Ca, K, Ti, S and Cl to be the major constituents in soil and rock elemental composition of the red planet. More than 200 minerals already studied by Moessbauer spectroscopy contain significant amounts of these elements. A considerable number of Moessbauer studies were also carried out on meteorites and on Moon samples. Looking backward in the studies of the whole Moessbauer community, we have built a specific library containing Moessbauer parameters of those possible Mars minerals. The selected minerals, their Moessbauer parameter values (min. max. s.d and number of available data), main site substitution, behavior as a function of temperature and a ranking as expected to be found on Mars were organized. Mars-analogue Fe-bearing minerals not studied by Moessbauer spectroscopy are being collected and investigated. In addition, it an identification system based on Artificial Neural Networks (ANN) was implemented which enables fast and precise mineral identification from the experimental Moessbauer parameters at a given temperature.

P A de Souza Jr.↗

Development of a Digital Meteorite Identification Program at University of New Mexico (UNM) (Institute of Meteoritics) and Southwestern Indian Polytechnic Institute (SIPI)

Determining the origin and chemical composition of suspect extra terrestrial specimens has lead to meteorite identification research programs. Such programs, like the University of New Mexico-Southwestern Indian Polytechnic Institute partnership, are being inundated with many non-meteorites (meteor wrongs) sent in by interested individuals from all over the world. This meteorite identification program developed a spreadsheet that aids in identifying the types of minerals in a sample for physical properties, possible meteorite characteristics, minerals and rock properties, and possible man made characteristics. Samples that show meteorite distinctiveness are further analyzed via the Scanning Electron Microprobe (SEM).

Gakin, R.↗

Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control

An indirect adaptive system has been constructed for robust control of an aircraft with uncertain aerodynamic characteristics. This system consists of a multilayer perceptron pre-trained neural network, online stability and control derivative identification, a dynamic cell structure online learning neural network, and a model following control system based on the stochastic optimal feedforward and feedback technique. The pre-trained neural network and model following control system have been flight-tested, but the online parameter identification and online learning neural network are new additions used for in-flight adaptation of the control system model. A description of the modification and integration of these two stand-alone software packages into the complete system in preparation for initial flight tests is presented. Open-loop results using both simulation and flight data, as well as closed-loop performance of the complete system in a nonlinear, six-degree-of-freedom, flight validated simulation, are analyzed. Results show that this online learning system, in contrast to the nonlearning system, has the ability to adapt to changes in aerodynamic characteristics in a real-time, closed-loop, piloted simulation, resulting in improved flying qualities.

Hageman, Jacob↗

Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control

An indirect adaptive system has been constructed for robust control of an aircraft with uncertain aerodynamic characteristics. This system consists of a multilayer perceptron pre-trained neural network, online stability and control derivative identification, a dynamic cell structure online learning neural network, and a model following control system based on the stochastic optimal feedforward and feedback technique. The pre-trained neural network and model following control system have been flight-tested, but the online parameter identification and online learning neural network are new additions used for in-flight adaptation of the control system model. A description of the modification and integration of these two stand-alone software packages into the complete system in preparation for initial flight tests is presented. Open-loop results using both simulation and flight data, as well as closed-loop performance of the complete system in a nonlinear, six-degree-of-freedom, flight validated simulation, are analyzed. Results show that this online learning system, in contrast to the nonlearning system, has the ability to adapt to changes in aerodynamic characteristics in a real-time, closed-loop, piloted simulation, resulting in improved flying qualities.

Hageman, Jacob J.↗

Noninvasive identification of the total peripheral resistance baroreflex

We propose two identification algorithms for quantitating the total peripheral resistance (TPR) baroreflex, an important contributor to short-term arterial blood pressure (ABP) regulation. Each algorithm analyzes beat-to-beat fluctuations in ABP and cardiac output, which may both be obtained noninvasively in humans. For a theoretical evaluation, we applied both algorithms to a realistic cardiovascular model. The results contrasted with only one of the algorithms proving to be reliable. This algorithm was able to track changes in the static gains of both the arterial and cardiopulmonary TPR baroreflex. We then applied both algorithms to a preliminary set of human data and obtained contrasting results much like those obtained from the cardiovascular model, thereby making the theoretical evaluation results more meaningful. This study suggests that, with experimental testing, the reliable identification algorithm may provide a powerful, noninvasive means for quantitating the TPR baroreflex. This study also provides an example of the role that models can play in the development and initial evaluation of algorithms aimed at quantitating important physiological mechanisms.

Non-NASA Center↗

A forward model-based validation of cardiovascular system identification

We present a theoretical evaluation of a cardiovascular system identification method that we previously developed for the analysis of beat-to-beat fluctuations in noninvasively measured heart rate, arterial blood pressure, and instantaneous lung volume. The method provides a dynamical characterization of the important autonomic and mechanical mechanisms responsible for coupling the fluctuations (inverse modeling). To carry out the evaluation, we developed a computational model of the cardiovascular system capable of generating realistic beat-to-beat variability (forward modeling). We applied the method to data generated from the forward model and compared the resulting estimated dynamics with the actual dynamics of the forward model, which were either precisely known or easily determined. We found that the estimated dynamics corresponded to the actual dynamics and that this correspondence was robust to forward model uncertainty. We also demonstrated the sensitivity of the method in detecting small changes in parameters characterizing autonomic function in the forward model. These results provide confidence in the performance of the cardiovascular system identification method when applied to experimental data.

NASA Discipline Cardiopulmonary↗

System identification of dynamic closed-loop control of total peripheral resistance by arterial and cardiopulmonary baroreceptors

Prolonged exposure to microgravity in space flight missions (days) impairs the mechanisms responsible for defense of arterial blood pressure (ABP) and cardiac output (CO) against orthostatic stress in the post-flight period. The mechanisms responsible for the observed orthostatic intolerance are not yet completely understood. Additionally, effective counter measures to attenuate this pathophysiological response are not available. The aim of this study was to investigate the ability of our proposed system identification method to predict closed-loop dynamic changes in TPR induced by changes in mean arterial pressure (MAP) and right atrial pressure (RAP). For this purpose we designed and employed a novel experimental animal model for the examination of arterial and cardiopulmonary baroreceptors in the dynamic closed-loop control of total peripheral resistance (TPR), and applied system identification to the analysis of beat-to-beat fluctuations in the measured signals. Grant numbers: NAG5-4989. c 2001. Elsevier Science Ltd. All rights reserved.

Non-NASA Center↗

In-Flight System Identification

A method is proposed and studied whereby the system identification cycle consisting of experiment design and data analysis can be repeatedly implemented aboard a test aircraft in real time. This adaptive in-flight system identification scheme has many advantages, including increased flight test efficiency, adaptability to dynamic characteristics that are imperfectly known a priori, in-flight improvement of data quality through iterative input design, and immediate feedback of the quality of flight test results. The technique uses equation error in the frequency domain with a recursive Fourier transform for the real time data analysis, and simple design methods employing square wave input forms to design the test inputs in flight. Simulation examples are used to demonstrate that the technique produces increasingly accurate model parameter estimates resulting from sequentially designed and implemented flight test maneuvers. The method has reasonable computational requirements, and could be implemented aboard an aircraft in real time.

Morelli, Eugene A.↗

Evaluation of the Biolog automated microbial identification system

Biolog's identification system was used to identify 39 American Type Culture Collection reference taxa and 45 gram-negative isolates from water samples. Of the reference strains, 98% were identified to genus level and 76% to species level within 4 to 24 h. Identification of some authentic strains of Enterobacter, Klebsiella, and Serratia was unreliable. A total of 93% of the water isolates were identified.

NASA Program Environmental Health↗

Multimodality stereotactic brain tissue identification: the NASA smart probe project

Real-time tissue identification can benefit procedures such as stereotactic brain biopsy, functional neurosurgery and brain tumor excision. Optical scattering spectroscopy has been shown to be effective at discriminating cancer from noncancerous conditions in the colon, bladder and breast. The NASA Smart Probe extends the concept of 'optical biopsy' by using neural network techniques to combine the output from 3 microsensors contained within a cannula 2. 7 mm in diameter (i.e. the diameter of a stereotactic brain biopsy needle). Experimental data from 5 rats show the clear differentiation between tissues such as brain, nerve, fat, artery and muscle that can be achieved with optical scattering spectroscopy alone. These data and previous findings with other modalities such as (1) analysis of the image from a fiberoptic neuroendoscope and (2) the output from a microstrain gauge suggest the Smart Probe multiple microsensor technique shows promise for real-time tissue identification in neurosurgical procedures. Copyright 2000 S. Karger AG, Basel.

Non-programmatic↗