In today&amp / #8217 / s life, companies are faced with the problem of providing quality goods and services at competitive prices. Cost estimation is a very important process for a forging company, as each time a quote is sent to a customer, the company earns or loses money depending on the results of the particular estimate. However, determining pricing for customer quotes is a matter of time consuming, detailed number of tasks repeated each time. Cost estimation software might do those tedious calculations and assist the estimator step by step to reach to a cost estimate in relatively short time. In this study, an interactive cost estimation software named Forge Cost Estimator, which performs the early cost estimation for forgings, has been developed. The program is aimed to be used by the cost estimators in hot forging companies. The software has various databases, which include material, forging and machining equipment data. The cost items defined in the forging work breakdown structure can be estimated by using different modules of the software and summed up in an additive structure by using the bottom-up costestimation method. For calculating the forge volume quicker and easier, a new volume estimation system named Easy-Volume, which is based on the volume fragmentation method, is proposed. The software can also guide the user in selecting the convenient forging production line. The software is written in MS Visual Basic 6.0. The developed program has been tested in a forging company and satisfactory cost estimations for several forgings have been achieved.

Administration of nasal cannula therapy tasks providers with periodically monitoring their patients and adjusting settings according to patient needs. Conventionally, providers monitor a patient's oxygen demand using pulse oximetry and a qualitative assessment of the patient's work of breathing. The motivation for this research is to augment the traditional qualitative assessment of work of breathing with a quantitative measurement of a patient's tidal volume, the volume of air inhaled with each breath. This thesis presents a novel approach to measure tidal volume using a nasal cannula with built-in pressure sensors. Pressure waveforms obtained from continuous measurement of the pressure at the tip of the cannula are used to estimate nasal flowrates, and these nasal flowrates are time-integrated to estimate tidal volumes. Computational fluid dynamics (CFD) models were used to simulate fluid flow in a simplified nasal passage undergoing nasal cannula therapy. These simulations used a range of flow conditions characteristic of both low-flow and high-flow nasal cannula treatments. The simulations produced a transformation from cannula tip pressure to instantaneous nasal flowrate, and this transformation was evaluated using a matching empirical experiment. This empirical experiment used a matching physical geometry with a similar range of flow conditions, and the transformation obtained from CFD was able to estimate the actual tidal volumes with 85% accuracy. This study showed that continuous pressure measurement at the tip of a nasal cannula produces enough information to estimate nasal flowrates and tidal volumes. No similar studies were found during the literature review, so an accuracy of 85% is promising for this stage. If this technique could be made more accurate and deployed in an unobtrusive way, the resulting nasal cannula device could be used to continuously, comfortably monitor patients' tidal volumes. / Master of Science / Oxygen therapy is the most common prescription in hospitals across the United States, and the most common form of oxygen therapy is nasal cannula therapy. Administration of nasal cannula therapy requires providers to periodically assess their patients' oxygen saturations and work of breathing. Oxygen saturation can be quantitatively monitored using pulse oximetry but work of breathing must be qualitatively monitored using visual exams or walking tests. The motivation of this research is to augment this qualitative assessment with a quantitative metric. In our research, we chose the volume of inhaled air (the "tidal volume") as a proxy metric for a patient's work of breathing. This thesis presents our attempt to use a nasal cannula augmented with pressure sensors to estimate the tidal volume of a mannequin undergoing nasal cannula therapy. Our concept is that more intense inhalations/exhalations produce larger pressure swings at the tip of the nasal cannula. For this proof-of-concept study, a simplified nasal passage geometry was used. Pressure waveforms obtained from continuous measurement of the pressure at the tip of the cannula are used to estimate nasal flowrates, and these nasal flowrates are time-integrated to estimate tidal volumes. Computational fluid dynamics (CFD) simulations were used to predict how the cannula tip pressure changes as a function of nasal flowrates and cannula flowrates, then this relationship was tested using a matching empirical experiment. This matching empirical experiment showed that our technique of estimating tidal volumes was 85% accurate. This study showed that continuous pressure measurement at the tip of a nasal cannula produces enough information to estimate nasal flowrates and tidal volumes. No similar studies were found during the literature review, so an accuracy of 85% is promising for this stage. If this technique could be made more accurate and deployed in an unobtrusive way, the resulting nasal cannula device could be used to continuously, comfortably monitor patients' tidal volumes.

The methodology to quantify vegetation from airborne laser scanning (or LiDAR - Light Detection And Ranging) is somehow consolidated, but some concerns are still in the checklist of the scientific community. This thesis aims to bring some of those concerns and try to contribute with some results and insights. Four aspects were studied along this thesis. In the first study, the effect of threshold heights (minimum height and height break) in the quality of the set of metrics was investigated aiming the volume estimation of a eucalyptus plantation. The results indicate that higher threshold height may return a better set of metrics. The impact of threshold height was more evident in young stands and for canopy density metrics. In the second study, the stability of the LiDAR metrics between different LiDAR surveys over the same area was analyzed. This study demonstrated how the selection of stable metrics contributed to generate reliable models between different data sets. According to our results, the height metrics provided the greatest stability when used in the models, specifically the higher percentiles (>50%) and the mode. The third study was designed to evaluate the use of machine learning tools to estimate wood volume of eucalyptus plantations from LiDAR metrics. Rather than being limited to a subset of LiDAR metrics in attempting explain as much variability in a dependent variable as possible, artificial intelligence tools explored the complete metrics set when looking for patterns between LiDAR metrics and stand volume. The fourth and last study has focused upon several highly important forest typologies, and shown that it is possible to differentiate the typologies through their vertical profiles as derived from airborne laser surveys. The size of the sampling cell does have an influence on the behavior observed in analyses of spatial dependence. Each typology has its own specific characteristics, which will need to be taken into consideration in projects targeting monitoring, inventory construction, and mapping based upon airborne laser surveys. The determination of a converged vertical profile could be achieved with data representing 10 % of the area for all typologies, while for some typologies 2 % coverage was sufficient. / A metodologia para quantificar vegetação a partir de dados LiDAR (Light Detection And Ranging) está de certa forma consolidada, porém ainda existem pontos a serem esclarecidos que permanecem na lista da comunidade científica. Quatro aspectos foram estudos nesta tese. No primeiro estudo, foi investigado a influência das alturas de referência (altura mínima e altura de quebra) na qualidade do conjunto de métricas extraído visando estimação do volume de um plantio de eucalipto. Os resultados indicaram que valor mais altos de alturas de referência retornaram um conjunto de métricas melhor. O efeito das alturas de referência foi mais evidente em povoamentos jovens e para as métricas de densidade. No segundo estudo, avaliou-se a estabilidade de métricas LiDAR derivadas para uma mesma área sobrevoada com diferentes configurações de equipamentos e voo. Este estudo apresentou como a seleção de métricas estáveis pode contribuir para a geração de modelos compatíveis com diferentes bases de dados LiDAR. De acordo com os resultados, as métricas de altura foram mais estáveis que as métricas de densidade, com destaque para os percentis acima de 50% e a moda. O terceiro estudo avaliou o uso de máquinas de aprendizado para a estimação do volume em nível de povoamento de plantios de eucalipto a partir de métricas LiDAR. Ao invés de estarem limitados a um pequeno subconjunto de métricas na tentativa de explicar a maior parte possível da variabilidade total dos dados, as técnicas de inteligência artificial permitiram explorar todo o conjunto de dados e detectar padrões que estimaram o volume em nível de povoamento a partir do conjunto de métricas. O quarto e último estudo focou em sete áreas de diferentes tipologias florestais brasileiras, estudando os seus perfis verticais de dossel. O estudo mostrou que é possível diferenciar estas tipologias com base no perfil vertical derivado de levantamentos LiDAR. Foi observado também que o tamanho das parcelas possui diferentes níveis de dependência espacial. Cada tipologia possui características específicas que precisam ser levadas em considerações em projetos de monitoramento, inventário e mapeamento baseado em levantamentos LiDAR. O estudo mostrou que é possível determinar o perfil vertical de dossel a partir da cobertura de 10% da área, chegando a algumas tipologias em apenas 2% da área.

Interwell tracers help us understand flow patterns within the reservoir and in getting reliable information of the reservoir continuity. Thus, one can obtain different information about the reservoir barriers, fractures and productivity from the amount of tracer produced at each tracer. The main objective of this study is an attempt to model interwell connectivity by analytically calculating missing tracer data in oil fields for the next step of the calculation of swept volume. The feasibility of using analytical solutions to estimate early data and check differences was carried out. In general; all of these applications refer to the applicability and relative ease of using tracers in oil field. The idea is to determine if it is possible to get a good estimate of the swept pore volumes at an early time before the tracer flood is finished since it often takes a long time to capture the complete tracer tail and there is great value in being able to get an early estimate of the results Results indicate that the extrapolation of tracer tail and using the residence time distribution method give accurate sweep volume predictions without the need to wait for long times to get the full tracer profile. / text

The methodology to quantify vegetation from airborne laser scanning (or LiDAR - Light Detection And Ranging) is somehow consolidated, but some concerns are still in the checklist of the scientific community. This thesis aims to bring some of those concerns and try to contribute with some results and insights. Four aspects were studied along this thesis. In the first study, the effect of threshold heights (minimum height and height break) in the quality of the set of metrics was investigated aiming the volume estimation of a eucalyptus plantation. The results indicate that higher threshold height may return a better set of metrics. The impact of threshold height was more evident in young stands and for canopy density metrics. In the second study, the stability of the LiDAR metrics between different LiDAR surveys over the same area was analyzed. This study demonstrated how the selection of stable metrics contributed to generate reliable models between different data sets. According to our results, the height metrics provided the greatest stability when used in the models, specifically the higher percentiles (>50%) and the mode. The third study was designed to evaluate the use of machine learning tools to estimate wood volume of eucalyptus plantations from LiDAR metrics. Rather than being limited to a subset of LiDAR metrics in attempting explain as much variability in a dependent variable as possible, artificial intelligence tools explored the complete metrics set when looking for patterns between LiDAR metrics and stand volume. The fourth and last study has focused upon several highly important forest typologies, and shown that it is possible to differentiate the typologies through their vertical profiles as derived from airborne laser surveys. The size of the sampling cell does have an influence on the behavior observed in analyses of spatial dependence. Each typology has its own specific characteristics, which will need to be taken into consideration in projects targeting monitoring, inventory construction, and mapping based upon airborne laser surveys. The determination of a converged vertical profile could be achieved with data representing 10 % of the area for all typologies, while for some typologies 2 % coverage was sufficient. / A metodologia para quantificar vegetação a partir de dados LiDAR (Light Detection And Ranging) está de certa forma consolidada, porém ainda existem pontos a serem esclarecidos que permanecem na lista da comunidade científica. Quatro aspectos foram estudos nesta tese. No primeiro estudo, foi investigado a influência das alturas de referência (altura mínima e altura de quebra) na qualidade do conjunto de métricas extraído visando estimação do volume de um plantio de eucalipto. Os resultados indicaram que valor mais altos de alturas de referência retornaram um conjunto de métricas melhor. O efeito das alturas de referência foi mais evidente em povoamentos jovens e para as métricas de densidade. No segundo estudo, avaliou-se a estabilidade de métricas LiDAR derivadas para uma mesma área sobrevoada com diferentes configurações de equipamentos e voo. Este estudo apresentou como a seleção de métricas estáveis pode contribuir para a geração de modelos compatíveis com diferentes bases de dados LiDAR. De acordo com os resultados, as métricas de altura foram mais estáveis que as métricas de densidade, com destaque para os percentis acima de 50% e a moda. O terceiro estudo avaliou o uso de máquinas de aprendizado para a estimação do volume em nível de povoamento de plantios de eucalipto a partir de métricas LiDAR. Ao invés de estarem limitados a um pequeno subconjunto de métricas na tentativa de explicar a maior parte possível da variabilidade total dos dados, as técnicas de inteligência artificial permitiram explorar todo o conjunto de dados e detectar padrões que estimaram o volume em nível de povoamento a partir do conjunto de métricas. O quarto e último estudo focou em sete áreas de diferentes tipologias florestais brasileiras, estudando os seus perfis verticais de dossel. O estudo mostrou que é possível diferenciar estas tipologias com base no perfil vertical derivado de levantamentos LiDAR. Foi observado também que o tamanho das parcelas possui diferentes níveis de dependência espacial. Cada tipologia possui características específicas que precisam ser levadas em considerações em projetos de monitoramento, inventário e mapeamento baseado em levantamentos LiDAR. O estudo mostrou que é possível determinar o perfil vertical de dossel a partir da cobertura de 10% da área, chegando a algumas tipologias em apenas 2% da área.

Traveler information systems play a significant role in most travelers’ daily trips. These systems assist travelers in choosing the best routes to reach their destinations and possibly select suitable departure times and modes for their trips. Connected Vehicle (CV) technologies are now in the pilot program stage. Vehicle-to-Infrastructure (V2I) communications will be an important source of data for traffic agencies. If this data is processed properly, then agencies will be able to better determine traffic conditions, allowing them to take proper countermeasures to remedy transportation system problems under different conditions. This research focuses on developing methods to assess the potential of utilizing CV data to support the traveler information system data collection process. The results from the assessment can be used to establish a timeline indicating when an agency can stop investing, at least partially, in traditional technologies, and instead rely on CV technologies for traveler information system support. This research utilizes real-world vehicle trajectory data collected under the Next Generation Simulation (NGSIM) program and simulation modeling to emulate the use of connected vehicle data to support the traveler information system. NGSIM datasets collected from an arterial segment and a freeway segment are used in this research. Microscopic simulation modeling is also used to generate required trajectory data, allowing further analysis, which is not possible using NGSIM data. The first step is to predict the market penetration of connected vehicles in future years. This estimated market penetration is then used for the evaluation of the effectiveness of CV-based data for travel time and volume estimation, which are two important inputs for the traveler information system. The travel times are estimated at different market penetrations of CV. The quality of the estimation is assessed by investigating the accuracy and reliability with different CV deployment scenarios. The quality of volume estimates is also assessed using the same data with different future scenarios of CV deployment and partial or no detector data. Such assessment supports the identification of a timeline indicating when CV data can be used to support the traveler information system.

The main subject of this thesis is the development of new geometric tools and techniques for solving classic problems within the geometry of numbers and convex geometry. At a high level, the problems considered in this thesis concern the varied interplay between the continuous and the discrete, an important theme within computer science and operations research. The first subject we consider is the study of cutting planes for non-linear integer programs. Cutting planes have been implemented to great effect for linear integer programs, and so understanding their properties in more general settings is an important subject of study. As our contribution to this area, we show that Chvatal-Gomory closure of any compact convex set is a rational polytope. As a consequence, we resolve an open problem of Schrijver (Ann. Disc. Math. `80) regarding the same question for irrational polytopes. The second subject of study is that of ellipsoidal approximation of convex bodies. Different such notions have been important to the development of fundamental geometric algorithms: e.g. the ellipsoid method for convex optimization (enclosing ellipsoids), or random walk methods for volume estimation (inertial ellipsoids). Here we consider the construction of an ellipsoid with good "covering" properties with respect to a convex body, known in convex geometry as the M-ellipsoid. As our contribution, we give two algorithms for constructing M-ellipsoids, and provide an application to near-optimal deterministic volume estimation in the oracle model. Equipped with this new geometric tool, we move to the study of classic lattice problems in the geometry of numbers, namely the Shortest (SVP) and Closest Vector Problems (CVP). Here we use M-ellipsoid coverings, combined with an algorithm of Micciancio and Voulgaris for CVP in the ℓ₂ norm (STOC `10), to obtain the first deterministic 2^O(ⁿ) time algorithm for the SVP in general norms. Combining this algorithm with a novel lattice sparsification technique, we derive the first deterministic 2^O(ⁿ)(1+1/ϵ)ⁿ time algorithm for (1+ϵ)-approximate CVP in general norms. For the next subject of study, we analyze the geometry of general integer programs. A central structural result in this area is Kinchine's flatness theorem, which states that every lattice free convex body has integer width bounded by a function of dimension. As our contribution, we build on the work Banaszczyk, using tools from lattice based cryptography, to give a new and tighter proof of the flatness theorem. Lastly, combining all the above techniques, we consider the study of algorithms for the Integer Programming Problem (IP). As our main contribution, we give a new 2^O(ⁿ)nⁿ time algorithm for IP, which yields the fastest currently known algorithm for IP and improves on the classic works of Lenstra (MOR `83) and Kannan (MOR `87).

The ability to automatically estimate the volume of timber is becoming increasingly important within the timber industry. The large number of timber trucks arriving each day at Swedish timber terminals fortifies the need for a volume estimation performed in real-time and on-the-go as the trucks arrive. This thesis investigates if a volumetric integration of disparity maps acquired from a Multi-View Stereo (MVS) system is a suitable approach for automatic volume estimation of timber loads. As real-time execution is preferred, efforts were made to provide a scalable method. The proposed method was quantitatively evaluated on datasets containing two geometric objects of known volume. A qualitative comparison to manual volume estimates of timber loads was also made on datasets recorded at a Swedish timber terminal. The proposed method is shown to be both accurate and precise under specific circumstances. However, robustness is poor to varying weather conditions, although a more thorough evaluation of this aspect needs to be performed. The method is also parallelizable, which means that future efforts can be made to significantly decrease execution time.

<p>This thesis presents a complete and fully automatic method for estimating the volume of an airbag, through all stages of its inflation, with multiple synchronized high-speed cameras.</p><p>Using recorded contours of the inflating airbag, its visual hull is reconstructed with a novel method: The intersections of all back-projected contours are first identified with an accelerated epipolar algorithm. These intersections, together with additional points sampled from concave surface regions of the visual hull, are then Delaunay triangulated to a connected set of tetrahedra. Finally, the visual hull is extracted by carving away the tetrahedra that are classified as inconsistent with the contours, according to a voting procedure.</p><p>The volume of an airbag's visual hull is always larger than the airbag's real volume. By projecting a known synthetic model of the airbag into the cameras, this volume offset is computed, and an accurate estimate of the real airbag volume is extracted. </p><p>Even though volume estimates can be computed for all camera setups, the cameras should be specially posed to achieve optimal results. Such poses are uniquely found for different airbag models with a separate, fully automatic, simulated annealing algorithm.</p><p>Satisfying results are presented for both synthetic and real-world data.</p>

Kohlenmonoxid (CO) wird nach Einatmung weitgehend an Hämoglobin gebunden, eine minimale Bindung findet auch an Myoglobin statt. Die Kohlenmonoxid-Hämoglobinkonzentration (COHb) im Blut steigt nach Inhalation proportional zur inhalierten CO-Menge und zur Hämoglobinmasse an. Dieser Anstieg wird über die CO-Hämoxymetrie ermittelt und resultierend aus der CO-Verdünnung die Hämoglobinmenge berechnet. Über die Hämoglobinkonzentration und den Hämatokrit kann im Anschluss das Blutvolumen berechnet werden. Grundsätzlich ist dieses Verfahren seit über 100 Jahren bekannt und wird seit ca. 1995 als Routinemethode zur Blutvolumenbestimmung in der Sportmedizin verwendet. Es existieren darüber hinaus methodische Probleme durch die CO-Abatmung und die Evaluierung in großen Kollektiven. Die hier vorgestellte Methodik beinhaltet die Weiterentwicklung der CO-Methode zur Direktmessung im geschlossenen System. Die Probanden atmen dabei ein exakt definiertes Bolus-Volumen in einem geschlossenen Atmungssystem über 15 Minuten ein. Die maximale Arbeitsplatzkonzentration (MAK: COHb 5%), also die resultierende COHb-Konzentration im Blut bei einer CO-Langzeitexposition von 35 ppm, wird in der Regel nur leicht überschritten. Dazu wurden an 104 Probanden zwei Vergleichsmessungen in definiertem Abstand und an 20 Probanden Wiederholungsmessungen nach Blutspende zum Nachweis der Reliabilität und Validität durchgeführt. Zusätzlich ist die Abfallkinetik von COHb an 20 Probanden bestimmt worden. Im Ergebnis stellt sich methodenbedingt ein COHb-Steady-State nach 9 Minuten Rückatmung im geschlossenen System ein. Der Typical-Error der Messwiederholung der Methodik liegt bei 1,9% bzw. nach weiterer Modifizierung der Methodik bei 1,3%. Der Nachweis eines Blutverlustes von 490 ml im Rahmen einer Blutspende zeigt nur eine minimale Abweichung von 10 g Hämoglobinmasse zwischen gemessenem und kalkuliertem Verlust. Die Halbwertszeit von COHb wurde mit 135 min bestimmt. Die verwendete Methodik zeigt aufgrund der induzierten COHb-Steady-State-Kinetik Vorteile bei der Anwendung und Genauigkeit. Der Nachweis der Wiederholbarkeit und Messgenauigkeit konnte an einem hinreichend großen Kollektiv gezeigt werden. Bei Mehrfachanwendung bietet die Sensitivität der Methodik die Möglichkeit der Aufdeckung von Manipulationen des Blutes über Erythropoetin (EPO) oder Eigenbluttransfusion. Dabei bewegt sich die eingesetzte CO-Belastung während der Methode im Bereich des Konsums von wenigen Zigaretten.