In the Laboratory of the Experimental Biophotonics at Brno University of Technology, a new generation of the Coherence-Controlled Holographic Microscope (CCHM) is being developed. Because of the automation of certain microscope procedures, a fully motorized three axis computer controlled manipulator of the sample is to be employed. A fast and accurate lateral positioning in a range of several centimeters is required. For the focusing capability, very precise positioning in the optical axes is required as well. Initially, the basics of microscope manipulator design are presented. Then, commercially available solutions are introduced and compared with special focus on its possible implementation in the new generation of CCHM. However, due to the specific design of the new CCHM, available manipulators are not suitable. Therefore, a new optimized manipulator design is introduced in the second part of the thesis. A selection of its appropriate elements, especially actuators, is based on a review. For the new manipulator design, a technical documentation was made and a testing software was developed. A crucial part of the manipulator was assembled and tested.

This diploma thesis deals with precise design of Brokaw BandGap voltage reference comparing with MOS references. There is STEP BY STEP separation and analysis of proposed devices, using Monte Carlo analysis. There are also presented the methods for achieving a lower deviation of the output voltage for yielding device, which needs no trimming.

This thesis deals with monitoring shifts in the vicinity of the village Tetčice. The site is located at the interface of geomorphological units. Monitor the area is done in stages and methods of using GPS and precise leveling. Points tested are expected movements in places the earth's crust, which are stabilized on the pillars in order to avoid possible negative effects. The work builds on results from previous measurements.

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第18874号 / 医博第3985号 / 新制||医||1008(附属図書館) / 31825 / 京都大学大学院医学研究科医学専攻 / (主査)教授 渡邉 大, 教授 山田 亮, 教授 福山 秀直 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

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Many cities in Sweden are partly located on clay and because of that, some urban city centres are undergoing significant subsidence. To measure subsidence in cities, precise leveling has been the traditional technique, but the interest for the Persistent Scatter InSAR (PSI) technique has increased in the last years, in this application. With the PSI technique, a mm-accuracy can be obtained and the analyses can be done over large areas. In this study, a validation between the PSI and the precise leveling techniques was performed for a selection of buildings located in areas that are facing great subsidence. A correlation between the subsidence rate achieved in the PSI analyses and near-surface soil type was also done, to easier identify risk zones. The city of Uppsala was chosen as study area, because it is partly built on deep layers of clay and the consulting company Bjerking AB has established a leveling network with metal pegs on many buildings. One ascending and one descending PSI analysis was performed, with Sentinel-1 data from the period mid-2015 to mid-2019, and the PSI analyses were done in SARPROZ. After the PSI analyses, comparative permanent scatters (PS) points and metal pegs were identified creating validation pairs. 15 different validation pairs were identified in four different objects, which was one or two buildings. The PSI analyses showed that Uppsala is undergoing significant subsidence in some parts, with an annual rate of about 6 mm/year in the line-of-sight (LOS) direction, which corresponds to about 7.5 mm/year in the vertical direction. The areas of greatest deformation were exclusively found on postglacial clay. The standard deviation of the time series were calculated around their linear regression lines, which was a measure of how temporal coherent the points were. The mean of this standard deviation for the PS points in the 15 validation pairs was 1.5 mm. This standard deviation increased to 2.3 mm in the time series where the direction was transformed from LOS to vertical and where the movements were in respect to the benchmarks. Between the PSI and the precise leveling techniques, in the validation, the vertical subsidence rate differed less than 1 mm/year in all validation pairs and the mean of all differences was 0.56 mm/year. Based on these results, Sentinel-1 data can measure urban subsidence in a satisfactory way, when the PSI technique is applied.

[ES] Los sistemas de alerta temprana en tiempo real son instrumentos claves para vigilar posibles desastres geológicos como terremotos, tsunamis, actividades volcánicas, hundimiento del terreno o deslizamientos de ladera. Durante las últimas décadas, el número de personas afectadas por los diversos desastres geológicos ha aumentado de forma sustancial. Las consecuencias negativas de estos desastres afectan a la población y a las infraestructuras con diferentes niveles de gravedad, pudiendo llegar a tener un impacto elevado en pérdidas humanas y económicas. Sin embargo, los sistemas de alerta temprana tienen la capacidad de proporcionar avisos adecuados y confiables, lo que puede llevar a minimizar las pérdidas humanas y económicas. El método de Posicionamiento Puntual Preciso en tiempo real (RT-PPP) desempeña un papel importante como parte de los sistemas de alerta temprana; debido a su capacidad para proporcionar seguimiento en tiempo real, cobertura global y su capacidad de obtención de mediciones precisas en tiempo real adquiridas por un solo receptor. A pesar de esto, el método (RT-PPP) utiliza productos para la corrección de la órbita y los relojes de los satélites (productos SSR) que son sensibles de los errores de la tecnología GNSS. Como consecuencia, estos errores pueden afectar la disponibilidad y fiabilidad de los sistemas de alerta temprana basados en la técnica RT-PPP. Debido a estos errores, se pueden llegar a generar avisos falsos, algunos de estos errores son: largos tiempos de inicialización, falta de continuidad y exactitud en los resultados, mala calidad de corrección de órbita y reloj de los satélites, mala resolución de la ambigüedad, etc. Además, la mala geometría de los satélites y la latencia de los productos SSR afectan gravemente el rendimiento del posicionamiento PPP en tiempo real. Este trabajo de investigación, se enfoca, en una primera parte, en el análisis de los efectos y los métodos de mitigación de la latencia de los productos de corrección en tiempo real. El International GNSS Service (IGS) proporciona productos oficiales para materializar la técnica de PPP en tiempo real, estos productos contienen correcciones para las órbitas y los relojes de los satélites que se generan como combinación de los calculados en los diferentes centros de cálculo repartidos por el mundo. Este proceso de combinación aumenta la latencia y, por tanto, su impacto en la solución RT-PPP, afectando el desempeño de cualquier sistema de alerta temprana basada en RT-PPP. Así, en esta tesis, se usará el enfoque de Aprendizaje Automático para resolver el problema de la latencia, intentando predecir los valores de las correcciones en los productos SSR para el tiempo de la latencia. Se han utilizado los modelos de Support Vector Regression (SVR) y de media móvil integrada autorregresiva (ARIMA) para la predicción, necesitando, en el proceso, la implantación de ventanas deslizantes para entrenar y parametrizar los modelos de aprendizaje automático. En cuanto al desempeño del sistema RT-PPP de alerta temprana, este trabajo de investigación ha evaluado, estadísticamente, varios modelos de aprendizaje automático, entre ellos los métodos de Árbol de decisión, Random Forest, Máquina de vectores de soporte (SVM), K vecinos más cercanos, Regresión logística, y el modelo de boosting extremo por gradientes (XGB). El análisis de los resultados indica que los modelo de XGB y Random Forest muestran los resultados más coherentes y precisos con 97 y 99 porciento de precisión. Asimismo, el modelo XGB muestra menos tendencia a iniciar falsas alarmas con un 2,48 por ciento en comparación con el 16,28 por ciento del modelo Random Forest.A partir de los resultados de la investigación, se derivan un conjunto de pruebas estadísticas para evaluar el desempeño de los sistemas de alerta temprana establecidos. Estas pruebas estadísticas pueden evaluar la capacidad de los modelos de aprendizaje automático utilizados con a la detecciónde deformaciones. / [CA] Els sistemes d'alerta primerenca en temps real són instruments claus per vigilar possibles desastres geològics com ara terratrèmols, tsunamis, activitats volcàniques, enfonsament del terreny o lliscaments de vessant. Durant les darreres dècades, el nombre de persones afectades pels diversos desastres geològics ha augmentat de manera substancial. Les conseqüències negatives d'aquests desastres afecten la població i les infraestructures amb diferents nivells de gravetat i poden arribar a tenir un impacte elevat en pèrdues humanes i econòmiques. Tot i això, els sistemes d'alerta primerenca tenen la capacitat de proporcionar avisos adequats i fiables, la qual cosa pot portar a minimitzar les pèrdues humanes i econòmiques. El mètode de Posicionament Puntual Precís en temps real (RT-PPP) té un paper important com a part dels sistemes d'alerta primerenca; a causa de la seva capacitat per proporcionar seguiment en temps real, cobertura global i la seva capacitat d'obtenció de mesuraments precisos en temps real adquirits per un sol receptor.Tot i això, el mètode RT-PPP utilitza productes per a la correcció de l'òrbita i els rellotges dels satèl·lits (productes SSR) que són sensibles als errors de la tecnologia GNSS. Com a conseqüència, aquests errors poden afectar la disponibilitat i la fiabilitat dels sistemes d'alerta primerenca basats en la tècnica RT-PPP. A causa d'aquests errors, es poden arribar a generar avisos falsos, alguns d'aquests errors són: llargs temps d'inicialització, manca de continuïtat i exactitud als resultats, mala qualitat de correcció d'òrbita i rellotge dels satèl·lits, mala resolució de l'ambigüitat, etc. A més, la mala geometria dels satèl·lits i la latència dels productes SSR afecten greument el rendiment del posicionament PPP en temps real. Aquest treball de recerca s'enfoca, en una primera part, a l'anàlisi dels efectes i els mètodes de mitigació de la latència dels productes de correcció en temps real. L'International GNSS Service (IGS) proporciona productes oficials per materialitzar la tècnica de PPP en temps real, aquests productes contenen correccions per a les òrbites i els rellotges dels satèl·lits que es generen com a combinació dels calculats als diferents centres de càlcul repartits pel món. Aquest procés de combinació augmenta la latència i, per tant, el seu impacte en la solució RT-PPP, afectant l'exercici de qualsevol sistema d'alerta primerenca basada en RT-PPP. Així, en aquesta tesi, s'usarà l'enfocament d'aprenentatge automàtic (Machine Learning) per resoldre el problema de la latència, intentant predir els valors de les correccions en els productes SSR per al temps de la latència. S'han utilitzat els models de Support Vector Regression (SVR) i de mitjana mòbil integrada autoregressiva (ARIMA) per a la predicció, necessitant, en el procés, la implantació de finestres lliscants per entrenar i parametritzar els models d'aprenentatge automàtic. Els resultats de la investigació de la part de la latència han indicat que els models SVR i ARIMA podran mitigar la influència de la latència per als principals sistemes de navegació per satèl·lit (GPS i GLONASS) al voltant d'un vint per cent. El model SVR va mostrar una lleugera tendència a predir valors atípics; tot i això, el temps d'execució del SVR és significativament menor que el temps de processament del model ARIMA. Pel que fa a desenvolupament del sistema RT-PPP d'alerta primerenca, aquest treball de recerca ha avaluat, estadísticament, diversos models d'aprenentatge automàtic, entre ells els mètodes d'Arbre de Decisió, Random Forest, Màquina de Vectors de Suport (SVM), K veïns més propers, Regressió Logística, i el model de Boosting Extrem per gradients (XGB).L'anàlisi dels resultats indica que els models de XGB i Random Forest mostren els resultats més coherents i precisos amb 97i99 porcent de precisió respectivament. Així mateix, el model XGB mostra menys tendència a iniciar falses alarmes amb un 2,48% en comparació del 16,28% del model RF. / [EN] Real-Time Early Warning Systems are a critical approach implemented for monitoring geo-hazard disasters such as earthquakes, tsunamis, volcanic activities, and land subsidence. The Earth's population has experienced a substantial increasement, consequently exposing a growing number of people to the effects of various geo-hazard disasters. These influences could impact citizens and countries at different severity levels, reaching high costs in terms of human beings and economic losses. However, the early warning system's ability to initiate proper and reliable warnings significantly impacts in disaster cost reductions in terms of saving lives, reducing home and infrastructure damages, and mitigating economic losses. Real-Time Precise Point Positioning (RT-PPP) plays a significant role as part of the Early Warning Systems, due to its potential to provide real-time tracking and global coverage and its reliance on precise real-time measurements acquired from only one receiver. However, the RT-PPP approach applies State Space Representation (SSR) products that are highly sensitive to several GNSS error sources. As a result, the warning system's availability and reliability are negatively impacted. It may even be triggered to issue false warnings by factors such as long initialization times, convergence losses, due to poor quality of orbital and clock corrections, ambiguity resolutions, or/and multipath error. Furthermore, poor satellite geometry and the latency of SSR products severely affect the performance of real-time PPP positioning. In this research, we investigated the effect and mitigation of latency on real-time correction products. The International GNSS Services (IGS) provides official real-time products for RT-PPP; these products contain clock and orbit corrections, among others, and they are the main research concerns as the combination process increases the latency impact on both RT-PPP results and influences the early warning systems performance based on this positioning technique. In this research, investigations into the potentiality of using machine learning approaches to overcome latency problems were carried out. The research examines the Support Vector Regression (SVR) and Autoregressive Integrated Moving Average (ARIMA) machine learning models to predict the corrections broadcasted in SSR products that have a big capability in order to be used instead of the corrections impacted with latency The research results regarding latency showed that the SVR and ARIMA models could mitigate the latency influences for the primary navigation satellite systems GPS and GLONASS by around twenty percent. The SVR model showed a tendency to predict outliers; however, the execution time for the SVR is significantly faster than the ARIMA model processing time. Regarding the performance of the RT-PPP early warning system, the research statistically evaluates several machine learning models, including decision tree, random forest, support vector classifier, K nearest neighbors, logistic regression, and extreme gradient boosting models as machine learning approaches for establishing an early warning system. The extreme gradient boosting and random forest models were more accurate than the other utilized models, with 97 and 99 percent overall accuracy. At the same time, the extreme gradient boosting showed less tendency to initiate false alarms, with 2.48 percent compared to 16.28 percent for the random forest model. From the research findings, we derived a set of statistical assessments to evaluate the performance of the established early warning systems. These statistical assessments can evaluate the ability of the utilized machine learning models regarding deformation detections and the model's tendency to initiate false warnings. The study's results confirmed that extreme gradient boosting is the most effective machine learning technique for creating an early warning system. / Qafisheh, MWA. (2024). Establishing a Real-time Precise Point Positioning Early Warning System [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/206740

Precise measurements of both absolute frequencies and small frequency differences of atomic energy levels have played an important role in the development of physics. For example, high precision measurements of absolute frequencies of the 2S½ → 2P ½ transition (D1 line) of alkali atoms form an important link in the measurement of the fine structure constant, α. Similarly, precise interferometric measurements of the local gravitational acceleration (g) rely on the knowledge of the absolute frequencies of the 2S½ → 2P 3/2 transition (D2line) in alkali atoms. Difference frequency measurements of hyperfine structure and isotope shifts of atomic energy levels provide valuable information about the structure of the nucleus, which in turn helps in fine tuning the atomic wave functions used in theoretical calculations. The work reported in this thesis starts with the development and refinement of high precision measurement of absolute frequencies using a ring-cavity resonator. The measurement technique is relatively simple and cost-effective, but the accuracy is comparable to that achieved with the frequency comb technique (10¯11) when the accuracy is limited by the natural linewidth of the transition being measured. The technique combines the advantages of using tunable diode lasers to access atomic transitions with the fact that the absolute frequency of the D2 line in87Rb is known with an accuracy of 6 kHz. A frequency-stabilized diode laser locked to this line is used as a frequency reference, along with a ring-cavity resonator whose length is locked to the reference laser. For a given cavity length, an unknown laser locked to an atomic transition has a small frequency offset from the nearest cavity resonance. We use an acousto-optic modulator (AOM) to compensate for this frequency offset. The measured offset is combined with the cavity mode number to obtain a precise value for the frequency of The unknown laser. We have used this technique for absolute frequency measurements Of the D lines in133Cs and 6,7Li, and the 398.8nm line in Yb. We have also developed a technique to measure the ‘difference frequency’ of atomic energy levels using a single diode laser and an AOM. In this technique, the laser is first locked to a given hyperfine transition. The laser frequency is then shifted using the AOM to another hyperfine transition and the AOM frequency is locked to this difference. Thus the AOM frequency directly gives a measurement of the hyperfine interval. Applying this AOM technique we have measured the hyperfine interval of the D1 lines of all alkali atoms with high precision. We have further developed a technique of coheren-tcontrol spectroscopy (CCS) using co-propagating control and probe beam that is useful for highresolution spectroscopy. In this technique, the probe beam is locked to a transition and its absorption signal is monitored while the control beam is scanned through neighbouring transition. As the control comes into resonance with another transition, the probe absorption is reduced and the signal shows a Doppler free dip. This technique allows us to resolve transitions that are otherwise swamped by crossover resonances in conventional saturated absorption spectroscopy (SAS). We have applied this technique to measure hyperfine intervals in the D2 line of several alkali atoms. Thus, we were able to do high-precision measurements of both absolute and difference frequency of atomic transitions. The precision of the absolute frequency measurement is finally limited by the accuracy of 6 kHz with which the reference frequency is known. The nearby two photon transition in Rb, i.e. the 5S1/2→5D3/2 transition at 778 nm, is known with an accuracy of 1 kHz. In future, we hope to improve the accuracy of our technique using this transition as the reference. This thesis is organized as follows: In Chapter1,we give a brief introduction to our work.. We review the importance of frequency measurements and precision spectroscopy, followed by a comparison of the frequency comb and our ring cavity technique. In Chapter2, we describe measurements of the absolute frequency of the D lines of 133Cs using the ring cavity. We give a detailed discussion of the technique, the Possible sources of errors, and ways to check for the errors. The measurement of the absolute frequency of the D lines of Cs allows a direct comparison to frequency comb measurements, and thus acts as a good check on our technique. In Chapter 3, we describe the absolute frequency and isotope shift measurements in the 398.8 nm line in Yb. We probed this line by frequency doubling the output of a tunable Ti:Sapphire laser. We obtained< 60 kHz precision in our measurements and were able to resolve several discrepancies in previous measurements on this line. In Chapter 4, we describe the measurement of hyperfine structure in the D1 lines of alkali atoms. We used conventional saturated-absorption spectroscopy in a vapor cell to probe different hyperfine transitions and then used our AOM technique to measure the hyperfine interval with high precision. In Chapter 5 we discuss our measurements of hyperfine structure in the D2 lines of several alkali atoms. In the case of 23Na and 39K, the closely-spaced hyperfine transitions are not completely resolved in conventional saturatedabsorption spectroscopy due to the presence of cross over resonances. We have used coherent control spectroscopy to obtain crossover-free spectra and then measured the hyperfine intervals using an AOM. This technique was also used for high resolution spectroscopy in the D2 line of 133Cs. Finally, we describe our measurements of hyperfine structure in the D2 line of Rb using normal saturated absorption spectroscopy. Chapter 6, describes the relative and absolute frequency measurements in the D lines of6,7 Li at 670nm. High-precision measurements in lithium are of special interest because theoretical calculations of atomic properties in this simple three electron system are fairly advanced. Lithium spectroscopy poses an experimental challenge and we describe our efforts in doing highresolution spectroscopy on this system. Chapter 7 describes the hyperfine spectroscopy on the1P 1 state of 173Yb. Measurement of hyperfine structure in 173Yb has a problem because two of the hyperfine transitions overlap with the transition in 172Yb. In our earlier work (described in chapter 4), we had solved this problem by using multipeak fitting to the partially resolved spectrum. Here, we directly resolve the hyperfine transitions by using transverse laser cooling to selectively deflect the 173Yb isotope. In Chapter 8 , we give a broad conclusion to the work reported in this thesis and suggest future avenues of research to continue the work commenced here.