907 resultados para OPTICAL-DETECTION


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Auf Paulfallen basierende Experimente spielen eine wichtige Rolle in verschiedenen Bereichen der Physik, z.B. der Atomphysik zum Test theoretischer Modelle und der Massenspektroskopie. Die vorliegende Arbeit widmet sich beiden Themengebieten und gliedert sich entsprechend in zwei Teilbereiche: 1) Erdalkali-Ionen sind aufgrund ihrer Energieniveaus optimale Kandidaten für Laserspektroskopie-Experimente mit Ionenfallen und bestens geeignet, um mittels der spektroskopischen Daten die theoretischen Modelle zu testen. Lediglich für Ra+ fehlen bislang als einzigem Erdalkali-Ion diese Daten wie z.B. die Lebensdauern der metastabilen Niveaus. Diese wären auch von Interesse für bereits geplante Radium-Experimente zur Paritätsverletzung. Im ersten Teil dieser Arbeit wird der Aufbau eines Laser-Paulfallenexperiments zur Messung der Lebensdauer des 6D3/2 Zustands von 226Ra+ dokumentiert und es werden Testmessungen mit 138Ba+ vorgestellt. 2) Für die Verwendung der Paulfalle in der Massenspektroskopie und zur Analyse von Reaktionsprodukten ist die Kenntnis der Lage der im Speicherbereich auftretenden nichtlinearen Resonanzen wesentlich, ebenso wie deren Veränderung durch Dämpfung und Raumladung. Im zweiten Teil dieser Arbeit werden detaillierte Untersuchungen der Speicherung großer puffergasgekühlter Ionenwolken an zwei unterschiedlichen Paulfallen-Experimenten vorgestellt. Am ersten wurden 138Ba+-Ionenwolken kontinuierlich durch Laserspektroskopie bzw. über einen elektronischen Nachweis beobachtet, während das zweite N2+-Molekülionen automatisiert destruktiv nachwies. Am N2+-Experiment wurden zwei hochaufgelöste Messungen des ersten Speicherbereichs durchgeführt, die erstmals eine direkte Überprüfung der theoretisch berechneten Verläufe der Resonanzen mit experimentellen Daten erlauben. Die Nachweiseichung ermöglichte dabei zum ersten Mal die Angabe absoluter Ionenzahlen. Im Gegensatz zu vergleichbaren früheren Messungen wurden hierbei die sich überlagernden Speicherbereiche von 4 simultan gespeicherten Ionensorten beobachtet und zur Analyse der Resonanzen herangezogen. Die nichtlinearen Resonanzen wurden untersucht bei Variation von Puffergasdruck und Ionenzahl, wobei kollektive Resonanzen ohne zusätzliche externe Anregung beobachtet wurden. Die gemessenen Raumladungsverschiebungen wurden mit theoretischen Modellen verglichen. Bei Variation des Puffergasdrucks wurde mit Bariumionen die räumliche Ausdehnung der Ionenwolke gemessen und mit Stickstoffionen die Verschiebung des Punktes optimaler Speicherung bestimmt. Dabei wurde festgestellt, daß der zum Ioneneinfang optimale Puffergasdruck kleiner ist als der, bei dem die längsten Speicherdauern erzielt werden. Mit gespeicherten N2+-Ionen wurde die Position extern angeregter kollektiver und individueller Resonanzen im Frequenzspektrum bei Änderung der Parameter Ionenzahl, Puffergasdruck und Dauer der Anregung untersucht, ebenso wie die Resonanzform, die mit theoretischen Linienformen verglichen wurde. Bei Änderung der Fallenparameter wurden verstärkende Effekte zwischen nahen kollektiven Resonanzen festgestellt. Die Beobachtung, welche der im Frequenzspektrum vorher identifizierten Bewegungs-Resonanzen sich bei Variation der Fallenparameter a bzw. q überlagern, ermöglicht eine bislang nicht beschriebene einfache Methode der Bestimmung von nichtlinearen Resonanzen im Stabilitätsdiagramm.

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Atmosphärische Aerosolpartikel wirken in vielerlei Hinsicht auf die Menschen und die Umwelt ein. Eine genaue Charakterisierung der Partikel hilft deren Wirken zu verstehen und dessen Folgen einzuschätzen. Partikel können hinsichtlich ihrer Größe, ihrer Form und ihrer chemischen Zusammensetzung charakterisiert werden. Mit der Laserablationsmassenspektrometrie ist es möglich die Größe und die chemische Zusammensetzung einzelner Aerosolpartikel zu bestimmen. Im Rahmen dieser Arbeit wurde das SPLAT (Single Particle Laser Ablation Time-of-flight mass spectrometer) zur besseren Analyse insbesondere von atmosphärischen Aerosolpartikeln weiterentwickelt. Der Aerosoleinlass wurde dahingehend optimiert, einen möglichst weiten Partikelgrößenbereich (80 nm - 3 µm) in das SPLAT zu transferieren und zu einem feinen Strahl zu bündeln. Eine neue Beschreibung für die Beziehung der Partikelgröße zu ihrer Geschwindigkeit im Vakuum wurde gefunden. Die Justage des Einlasses wurde mithilfe von Schrittmotoren automatisiert. Die optische Detektion der Partikel wurde so verbessert, dass Partikel mit einer Größe < 100 nm erfasst werden können. Aufbauend auf der optischen Detektion und der automatischen Verkippung des Einlasses wurde eine neue Methode zur Charakterisierung des Partikelstrahls entwickelt. Die Steuerelektronik des SPLAT wurde verbessert, so dass die maximale Analysefrequenz nur durch den Ablationslaser begrenzt wird, der höchsten mit etwa 10 Hz ablatieren kann. Durch eine Optimierung des Vakuumsystems wurde der Ionenverlust im Massenspektrometer um den Faktor 4 verringert.rnrnNeben den hardwareseitigen Weiterentwicklungen des SPLAT bestand ein Großteil dieser Arbeit in der Konzipierung und Implementierung einer Softwarelösung zur Analyse der mit dem SPLAT gewonnenen Rohdaten. CRISP (Concise Retrieval of Information from Single Particles) ist ein auf IGOR PRO (Wavemetrics, USA) aufbauendes Softwarepaket, das die effiziente Auswertung der Einzelpartikel Rohdaten erlaubt. CRISP enthält einen neu entwickelten Algorithmus zur automatischen Massenkalibration jedes einzelnen Massenspektrums, inklusive der Unterdrückung von Rauschen und von Problemen mit Signalen die ein intensives Tailing aufweisen. CRISP stellt Methoden zur automatischen Klassifizierung der Partikel zur Verfügung. Implementiert sind k-means, fuzzy-c-means und eine Form der hierarchischen Einteilung auf Basis eines minimal aufspannenden Baumes. CRISP bietet die Möglichkeit die Daten vorzubehandeln, damit die automatische Einteilung der Partikel schneller abläuft und die Ergebnisse eine höhere Qualität aufweisen. Daneben kann CRISP auf einfache Art und Weise Partikel anhand vorgebener Kriterien sortieren. Die CRISP zugrundeliegende Daten- und Infrastruktur wurde in Hinblick auf Wartung und Erweiterbarkeit erstellt. rnrnIm Rahmen der Arbeit wurde das SPLAT in mehreren Kampagnen erfolgreich eingesetzt und die Fähigkeiten von CRISP konnten anhand der gewonnen Datensätze gezeigt werden.rnrnDas SPLAT ist nun in der Lage effizient im Feldeinsatz zur Charakterisierung des atmosphärischen Aerosols betrieben zu werden, während CRISP eine schnelle und gezielte Auswertung der Daten ermöglicht.

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The geometric characterization of low-voltage dielectric electro-active polymer (EAP) structures, comprised of nanometer thickness but areas of square centimeters, for applications such as artificial sphincters requires methods with nanometer precision. Direct optical detection is usually restricted to sub-micrometer resolution because of the wavelength of the light applied. Therefore, we propose to take advantage of the cantilever bending system with optical readout revealing a sub-micrometer resolution at the deflection of the free end. It is demonstrated that this approach allows us to detect bending of rather conventional planar asymmetric, dielectric EAP-structures applying voltages well below 10 V. For this purpose, we built 100 μm-thin silicone films between 50 nm-thin silver layers on a 25 μm-thin polyetheretherketone (PEEK) substrate. The increase of the applied voltage in steps of 50 V until 1 kV resulted in a cantilever bending that exhibits only in restricted ranges the expected square dependence. The mean laser beam displacement on the detector corresponded to 6 nm per volt. The apparatus will therefore become a powerful mean to analyze and thereby improve low-voltage dielectric EAP-structures to realize nanometer-thin layers for stack actuators to be incorporated into artificial sphincter systems for treating severe urinary and fecal incontinence.

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In practical forensic casework, backspatter recovered from shooters' hands can be an indicator of self-inflicted gunshot wounds to the head. In such cases, backspatter retrieved from inside the barrel indicates that the weapon found at the death scene was involved in causing the injury to the head. However, systematic research on the aspects conditioning presence, amount and specific patterns of backspatter is lacking so far. Herein, a new concept of backspatter investigation is presented, comprising staining technique, weapon and target medium: the 'triple contrast method' was developed, tested and is introduced for experimental backspatter analysis. First, mixtures of various proportions of acrylic paint for optical detection, barium sulphate for radiocontrast imaging in computed tomography and fresh human blood for PCR-based DNA profiling were generated (triple mixture) and tested for DNA quantification and short tandem repeat (STR) typing success. All tested mixtures yielded sufficient DNA that produced full STR profiles suitable for forensic identification. Then, for backspatter analysis, sealed foil bags containing the triple mixture were attached to plastic bottles filled with 10 % ballistic gelatine and covered by a 2-3-mm layer of silicone. To simulate backspatter, close contact shots were fired at these models. Endoscopy of the barrel inside revealed coloured backspatter containing typable DNA and radiographic imaging showed a contrasted bullet path in the gelatine. Cross sections of the gelatine core exhibited cracks and fissures stained by the acrylic paint facilitating wound ballistic analysis.

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We have revisited soliton transmission in the new context of coherent optical detection optimizing and comparing digital backward propagation and in-line optical filtering as a means to suppress soliton timing and phase jitter. We find that in-line optical filtering allows one to improve the reach of the soliton system by up to the factor of 2. Our results show that nonlinear propagation can lead to performance beyond the nonlinear Shannon limit.

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Food safety has always been a social issue that draws great public attention. With the rapid development of wireless communication technologies and intelligent devices, more and more Internet of Things (IoT) systems are applied in the food safety tracking field. However, connection between things and information system is usually established by pre-storing information of things into RFID Tag, which is inapplicable for on-field food safety detection. Therefore, considering pesticide residue is one of the severe threaten to food safety, a new portable, high-sensitivity, low-power, on-field organophosphorus (OP) compounds detection system is proposed in this thesis to realize the on-field food safety detection. The system is designed based on optical detection method by using a customized photo-detection sensor. A Micro Controller Unit (MCU) and a Bluetooth Low Energy (BLE) module are used to quantize and transmit detection result. An Android Application (APP) is also developed for the system to processing and display detection result as well as control the detection process. Besides, a quartzose sample container and black system box are also designed and made for the system demonstration. Several optimizations are made in wireless communication, circuit layout, Android APP and industrial design to realize the mobility, low power and intelligence.

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Person tracking systems to date have either relied on motion detection or optical flow as a basis for person detection and tracking. As yet, systems have not been developed that utilise both these techniques. We propose a person tracking system that uses both, made possible by a novel hybrid optical flow-motion detection technique that we have developed. This provides the system with two methods of person detection, helping to avoid missed detections and the need to predict position, which can lead to errors in tracking and mistakes when handling occlusion situations. Our results show that our system is able to track people accurately, with an average error less than four pixels, and that our system outperforms the current CAVIAR benchmark system.

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Object tracking systems require accurate segmentation of the objects from the background for effective tracking. Motion segmentation or optical flow can be used to segment incoming images. Whilst optical flow allows multiple moving targets to be separated based on their individual velocities, optical flow techniques are prone to errors caused by changing lighting and occlusions, both common in a surveillance environment. Motion segmentation techniques are more robust to fluctuating lighting and occlusions, but don't provide information on the direction of the motion. In this paper we propose a combined motion segmentation/optical flow algorithm for use in object tracking. The proposed algorithm uses the motion segmentation results to inform the optical flow calculations and ensure that optical flow is only calculated in regions of motion, and improve the performance of the optical flow around the edge of moving objects. Optical flow is calculated at pixel resolution and tracking of flow vectors is employed to improve performance and detect discontinuities, which can indicate the location of overlaps between objects. The algorithm is evaluated by attempting to extract a moving target within the flow images, given expected horizontal and vertical movement (i.e. the algorithms intended use for object tracking). Results show that the proposed algorithm outperforms other widely used optical flow techniques for this surveillance application.

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Motion has been examined in biology to be a critical component for obstacle avoidance and navigation. In particular, optical flow is a powerful motion cue that has been exploited in many biological systems for survival. In this paper, we investigate an obstacle detection system that uses optical flow to obtain range information to objects. Our experimental results demonstrate that optical flow is capable of providing good obstacle information but has obvious failure modes. We acknowledge that our optical flow system has certain disadvantages and cannot be solely used for navigation. Instead, we believe that optical flow is a critical visual subsystem used when moving at reason- able speeds. When combined with other visual subsystems, considerable synergy can result.

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Automated visual surveillance of crowds is a rapidly growing area of research. In this paper we focus on motion representation for the purpose of abnormality detection in crowded scenes. We propose a novel visual representation called textures of optical flow. The proposed representation measures the uniformity of a flow field in order to detect anomalous objects such as bicycles, vehicles and skateboarders; and can be combined with spatial information to detect other forms of abnormality. We demonstrate that the proposed approach outperforms state-of-the-art anomaly detection algorithms on a large, publicly-available dataset.

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Purpose: To investigate the correlations of the global flash multifocal electroretinogram (MOFO mfERG) with common clinical visual assessments – Humphrey perimetry and Stratus circumpapillary retinal nerve fiber layer (RNFL) thickness measurement in type II diabetic patients. Methods: Forty-two diabetic patients participated in the study: ten were free from diabetic retinopathy (DR) while the remainder suffered from mild to moderate non-proliferative diabetic retinopathy (NPDR). Fourteen age-matched controls were recruited for comparison. MOFO mfERG measurements were made under high and low contrast conditions. Humphrey central 30-2 perimetry and Stratus OCT circumpapillary RNFL thickness measurements were also performed. Correlations between local values of implicit time and amplitude of the mfERG components (direct component (DC) and induced component (IC)), and perimetric sensitivity and RNFL thickness were evaluated by mapping the localized responses for the three subject groups. Results: MOFO mfERG was superior to perimetry and RNFL assessments in showing differences between the diabetic groups (with and without DR) and the controls. All the MOFO mfERG amplitudes (except IC amplitude at high contrast) correlated better with perimetry findings (Pearson’s r ranged from 0.23 to 0.36, p<0.01) than did the mfERG implicit time at both high and low contrasts across all subject groups. No consistent correlation was found between the mfERG and RNFL assessments for any group or contrast conditions. The responses of the local MOFO mfERG correlated with local perimetric sensitivity but not with RNFL thickness. Conclusion: Early functional changes in the diabetic retina seem to occur before morphological changes in the RNFL.

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We propose the use of optical flow information as a method for detecting and describing changes in the environment, from the perspective of a mobile camera. We analyze the characteristics of the optical flow signal and demonstrate how robust flow vectors can be generated and used for the detection of depth discontinuities and appearance changes at key locations. To successfully achieve this task, a full discussion on camera positioning, distortion compensation, noise filtering, and parameter estimation is presented. We then extract statistical attributes from the flow signal to describe the location of the scene changes. We also employ clustering and dominant shape of vectors to increase the descriptiveness. Once a database of nodes (where a node is a detected scene change) and their corresponding flow features is created, matching can be performed whenever nodes are encountered, such that topological localization can be achieved. We retrieve the most likely node according to the Mahalanobis and Chi-square distances between the current frame and the database. The results illustrate the applicability of the technique for detecting and describing scene changes in diverse lighting conditions, considering indoor and outdoor environments and different robot platforms.

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In many parts of the world, uncontrolled fires in sparsely populated areas are a major concern as they can quickly grow into large and destructive conflagrations in short time spans. Detecting these fires has traditionally been a job for trained humans on the ground, or in the air. In many cases, these manned solutions are simply not able to survey the amount of area necessary to maintain sufficient vigilance and coverage. This paper investigates the use of unmanned aerial systems (UAS) for automated wildfire detection. The proposed system uses low-cost, consumer-grade electronics and sensors combined with various airframes to create a system suitable for automatic detection of wildfires. The system employs automatic image processing techniques to analyze captured images and autonomously detect fire-related features such as fire lines, burnt regions, and flammable material. This image recognition algorithm is designed to cope with environmental occlusions such as shadows, smoke and obstructions. Once the fire is identified and classified, it is used to initialize a spatial/temporal fire simulation. This simulation is based on occupancy maps whose fidelity can be varied to include stochastic elements, various types of vegetation, weather conditions, and unique terrain. The simulations can be used to predict the effects of optimized firefighting methods to prevent the future propagation of the fires and greatly reduce time to detection of wildfires, thereby greatly minimizing the ensuing damage. This paper also documents experimental flight tests using a SenseFly Swinglet UAS conducted in Brisbane, Australia as well as modifications for custom UAS.

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We propose and demonstrate a technique for electrical detection of polarized spins in semiconductors in zero applied magnetic fields. Spin polarization is generated by optical injection using circularly polarized light which is modulated rapidly using an electro-optic cell. The modulated spin polarization generates a weak time-varying magnetic field which is detected by a sensitive radio-frequency coil. Using a calibrated pickup coil and amplification electronics, clear signals were obtained for bulk GaAs and Ge samples from which an optical spin orientation efficiency of 4.8% could be determined for Ge at 1342 nm excitation wavelength. In the presence of a small external magnetic field, the signal decayed according to the Hanle effect, from which a spin lifetime of 4.6 +/- 1.0 ns for electrons in bulk Ge at 127 K was extracted.

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A Monte Carlo model of ultrasound modulation of multiply scattered coherent light in a highly scattering media has been carried out for estimating the phase shift experienced by a photon beam on its transit through US insonified region. The phase shift is related to the tissue stiffness, thereby opening an avenue for possible breast tumor detection. When the scattering centers in the tissue medium is exposed to a deterministic forcing with the help of a focused ultrasound (US) beam, due to the fact that US-induced oscillation is almost along particular direction, the direction defined by the transducer axis, the scattering events increase, thereby increasing the phase shift experienced by light that traverses through the medium. The phase shift is found to increase with increase in anisotropy g of the medium. However, as the size of the focused region which is the region of interest (ROI) increases, a large number of scattering events take place within the ROI, the ensemble average of the phase shift (Delta phi) becomes very close to zero. The phase of the individual photon is randomly distributed over 2 pi when the scattered photon path crosses a large number of ultrasound wavelengths in the focused region. This is true at high ultrasound frequency (1 MHz) when mean free path length of photon l(s) is comparable to wavelength of US beam. However, at much lower US frequencies (100 Hz), the wavelength of sound is orders of magnitude larger than l(s), and with a high value of g (g 0.9), there is a distinct measurable phase difference for the photon that traverses through the insonified region. Experiments are carried out for validation of simulation results.