Browsing by Subject "Detectors"
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Item Application of a non-invasive scheme to detect geometrical irregularities in pipelines(Texas Tech University, 2002-05) Aydin, Bumin KaanThe purpose of the experiments performed is to investigate a non-intrasive method to detect defects in metal pipelines. An ultrasonic echo detection scheme is used. A generator produces pressure pulses that move along the pipeline. A detector monitors the pulses moving on the pipeline. Both the generator and the detector are external to the pipe and they do not need to be in contact with the pipe. The generator is a coil wrapped around the pipe. The coil is excited with a short duration, high current pulse. The magnetic pulse generated by the current causes local compression of the pipe. This local radial compression travels along the pipe as a pulse. The detector is a capacitor formed by a copper cylinder and the pipe itself. The diameter of the pipe changes as the pressure pulse passes by. The change of the diameter of the pipe causes a voltage change of the charged capacitor, which is amplified and analyzed to find reflected waves from any discontinuities, i.e., defects due to corrosion in the pipe. The locations of the defects are found by measuring the delay of the reflected waves. Measurements have been conducted successfully and are presented.Item Autonomous sensor and action model learning for mobile robots(2008-08) Stronger, Daniel Adam; Stone, Peter, 1971-Autonomous mobile robots have the potential to be extremely beneficial to society due to their ability to perform tasks that are difficult or dangerous for humans. These robots will necessarily interact with their environment through the two fundamental processes of acting and sensing. Robots learn about the state of the world around them through their sensations, and they influence that state through their actions. However, in order to interact with their environment effectively, these robots must have accurate models of their sensors and actions: knowledge of what their sensations say about the state of the world and how their actions affect that state. A mobile robot’s action and sensor models are typically tuned manually, a brittle and laborious process. The robot’s actions and sensors may change either over time from wear or because of a novel environment’s terrain or lighting. It is therefore valuable for the robot to be able to autonomously learn these models. This dissertation presents a methodology that enables mobile robots to learn their action and sensor models starting without an accurate estimate of either model. This methodology is instantiated in three robotic scenarios. First, an algorithm is presented that enables an autonomous agent to learn its action and sensor models in a class of one-dimensional settings. Experimental tests are performed on a four-legged robot, the Sony Aibo ERS-7, walking forward and backward at different speeds while facing a fixed landmark. Second, a probabilistically motivated model learning algorithm is presented that operates on the same robot walking in two dimensions with arbitrary combinations of forward, sideways, and turning velocities. Finally, an algorithm is presented to learn the action and sensor models of a very different mobile robot, an autonomous car.Item The development of a microbead array for the detection and amplification of nucleic acids(2006) Ali, Mehnaaz Fatima; McDevitt, John T.The focus of this doctoral thesis is on the development of a chip-based sensor array, composed of individually addressable agarose micro-beads, that is suitable for the real-time detection of DNA oligonucleotides. This research is consistent with recent trends in disease diagnostics following the miniaturization and integration of sample preparation and measurement steps towards portable devices capable of point of care analysis. Thus, the power and utility of this microbead array methodology for DNA detection is demonstrated here for the analysis of fluids containing a variety of similar short oligonucleotides. Hybridization times on the order of minutes with point mutation selectivity factors greater than 10,000 and limit of detection values of ~10-13 M are obtained readily with this microbead array system. These analytical characteristics, here exhibited are competitive with some of the best direct DNA detection methodologies before reported. As an extension of this work, an integrated self quenching based sensing system within the bead format has shown clear efficacy for the detection of HIV gag isolates and Bacillus anthracis (Sterne) purified strains and allows for the rapid detection of 100bp sequences with sensitivities in the subnanomolar range. Additionally, due to the tailored immobilization of specific sequences on each sensor element, the multiplexed detection of various sequences utilizing diverse strategies has been demonstrated. Use of the micro-bead array in tandem with the hybridization capabilities of molecular beacons, constitutes a powerful tool for the heterogeneous elucidation of specific sequences. Concomitantly, successful collaboration with the Chen group on the development of a miniaturized enzyme based nucleic acid amplification device has been reported. Purified strains of Bacillus anthracis (Sterne) have been successfully amplified by the miniaturized polymerase chain reaction (PCR) chip as seen by gel electrophoresis. One of the long term aims of this general area of research will be to couple the glass micro chip-based PCR amplification of oligonucleotides with the real-time detection capabilities of a bead based array. These efforts serve to establish some precedent for the bead-based microfluidics approach to be implemented in the context of genomics testing for the next generation of health care.Item Development of enzyme-based sensor arrays(2001-08) Curey, Theodore Edward; Shear, Jason B.Item Electromagnetic emissions reduction in a CAN transceiver system(Texas Tech University, 2004-05) Slayton, Jason RThis project deals with the emissions behavior of a Controller Area Network (CAN). CAN systems are widely used in automotive applications. Recently, CAN systems have expanded their applications to fields like medical, industrial automation and even high end home appliances. This paper discussed the important features of using CAN systems, one of which is the electromagnetic emissions behavior of the systems, especially in automotive applications. The motivation for the research discussed in this paper is to gain a better understanding of the effect different signals has on emissions. The most widely accepted solution to this problem is using a common mode capacitor on the signals. This reduces the variation of the common mode signal, which, in turn, reduces the emissions. This signal variation, along with other variations, was evaluated in this research. The objectives of this research are to quantify the effect each signal variation has on emissions.Item Electromagnetic interactions in the MINOS detectors(2004) Vahle, Patricia LaVern; Lang, KarolItem Experimental contributions to the theory and application of molecular recognition(2008-05) Hughes, Andrew Dike, 1980-; Anslyn, Eric V., 1960-Molecular recognition is a major branch of modern organic chemistry, and it resides at the forefront of supramolecular chemistry. Supramolecular chemistry refers to the study of the noncovalent intermolecular interaction that are crucial for biological processes, catalytic systems, the organization of crystalline or solution phase superstructures, and molecular recognition to name a few examples. The following dissertation reports research efforts from the Anslyn group into three topics of fundamental interest to the molecular recognition community: cooperativity, array sensing, and the development of highly selective sensors for minimally functionalized analytes. Chapter 1 is a review of the most fundamental points of molecular recognition as it applies to the experimental work that follows. Intermolecular association phenomena are driven by multiple discrete, noncovalent interactions, and cooperativity is a measure of the efficiency with which these interactions are employed in a given system. Cooperativity is poorly understood despite its ubiquity in biological and molecular recognition contexts. The first synthetic hostguest system exhibiting positive cooperativity in water is reported in Chapter 2. The utility of sensitive but unselective sensors when applied in an array format has recently come to light. Chapter 3 details an array of polyaromatic fluorophores dissolved in an aqueous surfactant solution that was used to sense nitrated explosives. This exceptionally unselective quenching process was able to detect and discriminate nitrated explosives such as RDX and TNT at concentrations as low as 19 [mu]M. Finally, Chapters 4 and 5 report different approaches to the sensing of enantiomeric excess in [alpha]-chiral alcohols using an indicator displacement paradigm. Chapter 4 explores unprecedented efforts to convert the Sharpless catalytic epoxidation system to the first Ti[superscript IV]-based molecular recognition system. Chapter 5 focuses upon a two-stage approach of derivatization of the [alpha]-chiral alcohol to a metal chelating ligand followed by employment of the derivative in an indicator displacement assay.Item Hadronic interactions in the MINOS detectors(2004) Kordosky, Michael Alan; Lang, KarolItem Measurement of inclusive forward neutral pion production in 200 GeV polarized proton-proton collisions at RHIC(2004) Wang, Yiqun; Hoffmann, Gerald W.; Moore, C. FredMeasurement of inclusive forward π 0 production in the first polarized pp collision at √ s = 200 GeV was achieved using a prototype Forward (neutral) Pion Detector. The invariant differential cross section was consistent with next-to-leading order perturbative QCD calculation. Large positive analyzing power was found for large Feynman-x (xF > 0.3). In addition, a new analysis program was developed for the upgraded Forward Pion Detector (FPD).Item Motion perception and the scene statistics of motion(2008-05) Tversky, Tal, 1971-; Miikkulainen, Risto; Geisler, Wilson S.Motion coding in the brain undoubtedly reflects the statistics of retinal image motion occurring in the natural environment. Measuring the statistics of motion in natural scenes is an important tool for building our understanding of how the brain works. Unfortunately, there are statistics that are either impossible or prohibitively difficult to measure. For this reason, it is useful to measure scene statistics in artificial movies derived from simulated environments. This is a novel and important methodological approach that allows us to ask questions about optimal coding that are impossible otherwise. This dissertation describes a course of research that develops this research methodology, the simulated scene statistical approach. This dissertation applied the artificial scene statistical approach to understanding the visual statistics of motion during navigation through forest environments. An environmental model of forest scenes was developed based on previously measured range and surface texture statistics. Spatiotemporal power spectra were measured in both simulated and natural scenes for the task of first person motion through a forest environment. These image statistics measurements helped validate the environmental model. Next, the environmental model was used to simulate across-domain statistics to study the ideal aperture size of motion sensors. It was found that across a variety of different scene conditions, the optimal aperture size of motion sensors increases with the speed to which the sensor is tuned. This is an important constraint for understanding both how the brain encodes motion as well as for designing computer motion detectors. This theoretical research inspired a psychophysical experiment estimating the receptive-field size of human foveal motion discrimination. It was found that for narrow-band stimuli the ideal aperture size increases with spatial frequency, but is unchanging with respect to velocity or temporal frequency. This dissertation shows an approach to the study of vision that has applications in psychophysics, neuroscience and computer vision. The emphasis on accurate and validated environmental models for simulating scene statistics can help improve our understanding of the structure and function of the human visual system and also help us build more accurate and robust computer vision systems.Item The design, construction and testing of a prototype B sensor(Texas Tech University, 1982-05) Shannon, ScottNot available