936 resultados para Best available techniques


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In vielen Bereichen der industriellen Fertigung, wie zum Beispiel in der Automobilindustrie, wer- den digitale Versuchsmodelle (sog. digital mock-ups) eingesetzt, um die Entwicklung komplexer Maschinen m ̈oglichst gut durch Computersysteme unterstu ̈tzen zu k ̈onnen. Hierbei spielen Be- wegungsplanungsalgorithmen eine wichtige Rolle, um zu gew ̈ahrleisten, dass diese digitalen Pro- totypen auch kollisionsfrei zusammengesetzt werden k ̈onnen. In den letzten Jahrzehnten haben sich hier sampling-basierte Verfahren besonders bew ̈ahrt. Diese erzeugen eine große Anzahl von zuf ̈alligen Lagen fu ̈r das ein-/auszubauende Objekt und verwenden einen Kollisionserken- nungsmechanismus, um die einzelnen Lagen auf Gu ̈ltigkeit zu u ̈berpru ̈fen. Daher spielt die Kollisionserkennung eine wesentliche Rolle beim Design effizienter Bewegungsplanungsalgorith- men. Eine Schwierigkeit fu ̈r diese Klasse von Planern stellen sogenannte “narrow passages” dar, schmale Passagen also, die immer dort auftreten, wo die Bewegungsfreiheit der zu planenden Objekte stark eingeschr ̈ankt ist. An solchen Stellen kann es schwierig sein, eine ausreichende Anzahl von kollisionsfreien Samples zu finden. Es ist dann m ̈oglicherweise n ̈otig, ausgeklu ̈geltere Techniken einzusetzen, um eine gute Performance der Algorithmen zu erreichen.rnDie vorliegende Arbeit gliedert sich in zwei Teile: Im ersten Teil untersuchen wir parallele Kollisionserkennungsalgorithmen. Da wir auf eine Anwendung bei sampling-basierten Bewe- gungsplanern abzielen, w ̈ahlen wir hier eine Problemstellung, bei der wir stets die selben zwei Objekte, aber in einer großen Anzahl von unterschiedlichen Lagen auf Kollision testen. Wir im- plementieren und vergleichen verschiedene Verfahren, die auf Hu ̈llk ̈operhierarchien (BVHs) und hierarchische Grids als Beschleunigungsstrukturen zuru ̈ckgreifen. Alle beschriebenen Verfahren wurden auf mehreren CPU-Kernen parallelisiert. Daru ̈ber hinaus vergleichen wir verschiedene CUDA Kernels zur Durchfu ̈hrung BVH-basierter Kollisionstests auf der GPU. Neben einer un- terschiedlichen Verteilung der Arbeit auf die parallelen GPU Threads untersuchen wir hier die Auswirkung verschiedener Speicherzugriffsmuster auf die Performance der resultierenden Algo- rithmen. Weiter stellen wir eine Reihe von approximativen Kollisionstests vor, die auf den beschriebenen Verfahren basieren. Wenn eine geringere Genauigkeit der Tests tolerierbar ist, kann so eine weitere Verbesserung der Performance erzielt werden.rnIm zweiten Teil der Arbeit beschreiben wir einen von uns entworfenen parallelen, sampling- basierten Bewegungsplaner zur Behandlung hochkomplexer Probleme mit mehreren “narrow passages”. Das Verfahren arbeitet in zwei Phasen. Die grundlegende Idee ist hierbei, in der er- sten Planungsphase konzeptionell kleinere Fehler zuzulassen, um die Planungseffizienz zu erh ̈ohen und den resultierenden Pfad dann in einer zweiten Phase zu reparieren. Der hierzu in Phase I eingesetzte Planer basiert auf sogenannten Expansive Space Trees. Zus ̈atzlich haben wir den Planer mit einer Freidru ̈ckoperation ausgestattet, die es erlaubt, kleinere Kollisionen aufzul ̈osen und so die Effizienz in Bereichen mit eingeschr ̈ankter Bewegungsfreiheit zu erh ̈ohen. Optional erlaubt unsere Implementierung den Einsatz von approximativen Kollisionstests. Dies setzt die Genauigkeit der ersten Planungsphase weiter herab, fu ̈hrt aber auch zu einer weiteren Perfor- mancesteigerung. Die aus Phase I resultierenden Bewegungspfade sind dann unter Umst ̈anden nicht komplett kollisionsfrei. Um diese Pfade zu reparieren, haben wir einen neuartigen Pla- nungsalgorithmus entworfen, der lokal beschr ̈ankt auf eine kleine Umgebung um den bestehenden Pfad einen neuen, kollisionsfreien Bewegungspfad plant.rnWir haben den beschriebenen Algorithmus mit einer Klasse von neuen, schwierigen Metall- Puzzlen getestet, die zum Teil mehrere “narrow passages” aufweisen. Unseres Wissens nach ist eine Sammlung vergleichbar komplexer Benchmarks nicht ̈offentlich zug ̈anglich und wir fan- den auch keine Beschreibung von vergleichbar komplexen Benchmarks in der Motion-Planning Literatur.

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In food industry, quality assurance requires low cost methods for the rapid assessment of the parameters that affect product stability. Foodstuffs are complex in their structure, mainly composed by gaseous, liquid and solid phases which often coexist in the same product. Special attention is given to water, concerned as natural component of the major food product or as added ingredient of a production process. Particularly water is structurally present in the matrix and not completely available. In this way, water can be present in foodstuff in many different states: as water of crystallization, bound to protein or starch molecules, entrapped in biopolymer networks or adsorbed on solid surfaces of porous food particles. The traditional technique for the assessment of food quality give reliable information but are destructive, time consuming and unsuitable for on line application. The techniques proposed answer to the limited disposition of time and could be able to characterize the main compositional parameters. Dielectric interaction response is mainly related to water and could be useful not only to provide information on the total content but also on the degree of mobility of this ubiquitous molecule in different complex food matrix. In this way the proposal of this thesis is to answer at this need. Dielectric and electric tool can be used for the scope and led us to describe the complex food matrix and predict food characteristic. The thesis is structured in three main part, in the first one some theoretical tools are recalled to well assess the food parameter involved in the quality definition and the techniques able to reply at the problem emerged. The second part explains the research conducted and the experimental plans are illustrated in detail. Finally the last section is left for rapid method easily implementable in an industrial process.

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Oceans are key sources and sinks in the global budgets of significant atmospheric trace gases, termed Volatile Organic Compounds (VOCs). Despite their low concentrations, these species have an important role in the atmosphere, influencing ozone photochemistry and aerosol physics. Surprisingly, little work has been done on assessing their emissions or transport mechanisms and rates between ocean and atmosphere, all of which are important when modelling the atmosphere accurately.rnA new Needle Trap Device (NTD) - GC-MS method was developed for the effective sampling and analysis of VOCs in seawater. Good repeatability (RSDs <16 %), linearity (R2 = 0.96 - 0.99) and limits of detection in the range of pM were obtained for DMS, isoprene, benzene, toluene, p-xylene, (+)-α-pinene and (-)-α-pinene. Laboratory evaluation and subsequent field application indicated that the proposed method can be used successfully in place of the more usually applied extraction techniques (P&T, SPME) to extend the suite of species typically measured in the ocean and improve detection limits. rnDuring a mesocosm CO2 enrichment study, DMS, isoprene and α-pinene were identified and quantified in seawater samples, using the above mentioned method. Based on correlations with available biological datasets, the effects of ocean acidification as well as possible ocean biological sources were investigated for all examined compounds. Future ocean's acidity was shown to decrease oceanic DMS production, possibly impact isoprene emissions but not affect the production of α-pinene. rnIn a separate activity, ocean - atmosphere interactions were simulated in a large scale wind-wave canal facility, in order to investigate the gas exchange process and its controlling mechanisms. Air-water exchange rates of 14 chemical species (of which 11 VOCs) spanning a wide range of solubility (dimensionless solubility, α = 0:4 to 5470) and diffusivity (Schmidt number in water, Scw = 594 to 1194) were obtained under various turbulent (wind speed at ten meters height, u10 = 0:8 to 15ms-1) and surfactant modulated (two different sized Triton X-100 layers) surface conditions. Reliable and reproducible total gas transfer velocities were obtained and the derived values and trends were comparable to previous investigations. Through this study, a much better and more comprehensive understanding of the gas exchange process was accomplished. The role of friction velocity, uw* and mean square slope, σs2 in defining phenomena such as waves and wave breaking, near surface turbulence, bubbles and surface films was recognized as very significant. uw* was determined as the ideal turbulent parameter while σs2 described best the related surface conditions. A combination of both uw* and σs2 variables, was found to reproduce faithfully the air-water gas exchange process. rnA Total Transfer Velocity (TTV) model provided by a compilation of 14 tracers and a combination of both uw* and σs2 parameters, is proposed for the first time. Through the proposed TTV parameterization, a new physical perspective is presented which provides an accurate TTV for any tracer within the examined solubility range. rnThe development of such a comprehensive air-sea gas exchange parameterization represents a highly useful tool for regional and global models, providing accurate total transfer velocity estimations for any tracer and any sea-surface status, simplifying the calculation process and eliminating inevitable calculation uncertainty connected with the selection or combination of different parameterizations.rnrn

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Predictable coverage of multiple adjacent gingival recessions (MAGRs) is a major challenge for clinicians. Although several surgical techniques have been proposed to treat MAGR, it is still unclear as to what extent the proposed approaches may lead to predictable root coverage. The aim of this article is to identify the predictability of the available surgical techniques used to achieve complete root coverage (CRC) of Miller Class I, II, and III MAGRs.

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The Simulation Automation Framework for Experiments (SAFE) streamlines the de- sign and execution of experiments with the ns-3 network simulator. SAFE ensures that best practices are followed throughout the workflow a network simulation study, guaranteeing that results are both credible and reproducible by third parties. Data analysis is a crucial part of this workflow, where mistakes are often made. Even when appearing in highly regarded venues, scientific graphics in numerous network simulation publications fail to include graphic titles, units, legends, and confidence intervals. After studying the literature in network simulation methodology and in- formation graphics visualization, I developed a visualization component for SAFE to help users avoid these errors in their scientific workflow. The functionality of this new component includes support for interactive visualization through a web-based interface and for the generation of high-quality, static plots that can be included in publications. The overarching goal of my contribution is to help users create graphics that follow best practices in visualization and thereby succeed in conveying the right information about simulation results.

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The analysis of short segments of noise-contaminated, multivariate real world data constitutes a challenge. In this paper we compare several techniques of analysis, which are supposed to correctly extract the amount of genuine cross-correlations from a multivariate data set. In order to test for the quality of their performance we derive time series from a linear test model, which allows the analytical derivation of genuine correlations. We compare the numerical estimates of the four measures with the analytical results for different correlation pattern. In the bivariate case all but one measure performs similarly well. However, in the multivariate case measures based on the eigenvalues of the equal-time cross-correlation matrix do not extract exclusively information about the amount of genuine correlations, but they rather reflect the spatial organization of the correlation pattern. This may lead to failures when interpreting the numerical results as illustrated by an application to three electroencephalographic recordings of three patients suffering from pharmacoresistent epilepsy.

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Laurentide glaciation during the early Pleistocene (~970 ka) dammed the southeast-flowing West Branch of the Susquehanna River (WBSR), scouring bedrock and creating 100-km-long glacial Lake Lesley near the Great Bend at Muncy, Pennsylvania (Ramage et al., 1998). Local drill logs and well data indicate that subsequent paleo-outwash floods and modern fluvial processes have deposited as much as 30 meters of alluvium in this area, but little is known about the valley fill architecture and the bedrock-alluvium interface. By gaining a greater understanding of the bedrock-alluvium interface the project will not only supplement existing depth to bedrock information, but also provide information pertinent to the evolution of the Muncy Valley landscape. This project determined if variations in the thickness of the valley fill were detectable using micro-gravity techniques to map the bedrock-alluvium interface. The gravity method was deemed appropriate due to scale of the study area (~30 km2), ease of operation by a single person, and the available geophysical equipment. A LaCoste and Romberg Gravitron unit was used to collect gravitational field readings at 49 locations over 5 transects across the Muncy Creek and Susquehanna River valleys (approximately 30 km2), with at least two gravity base stations per transect. Precise latitude, longitude and ground surface elevation at each location were measured using an OPUS corrected Trimble RTK-GPS unit. Base stations were chosen based on ease of access due to the necessity of repeat measurements. Gravity measurement locations were selected and marked to provide easy access and repeat measurements. The gravimeter was returned to a base station within every two hours and a looping procedure was used to determine drift and maximize confidence in the gravity measurements. A two-minute calibration reading at each station was used to minimize any tares in the data. The Gravitron digitally recorded finite impulse response filtered gravity measurements every 20 seconds at each station. A measurement period of 15 minutes was used for each base station occupation and a minimum of 5 minutes at all other locations. Longer or multiple measurements were utilized at some sites if drift or other externalities (i.e. train or truck traffic) were effecting readings. Average, median, standard deviation and 95% confidence interval were calculated for each station. Tidal, drift, latitude, free-air, Bouguer and terrain corrections were then applied. The results show that the gravitational field decreases as alluvium thickness increases across the axes of the Susquehanna River and Muncy Creek valleys. However, the location of the gravity low does not correspond with the present-day location of the West Branch of the Susquehanna River (WBSR), suggesting that the WBSR may have been constrained along Bald Eagle Mountain by a glacial lobe originating from the Muncy Creek Valley to the northeast. Using a 3-D inversion model, the topography of the bedrock-alluvium interface was determined over the extent of the study area using a density contrast of -0.8 g/cm3. Our results are consistent with the bedrock geometry of the area, and provide a low-cost, non-invasive and efficient method for exploring the subsurface and for supplementing existing well data.

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Bone research is limited by the methods available for detecting changes in bone metabolism. While dual X-ray absorptiometry is rather insensitive, biochemical markers are subject to significant intra-individual variation. In the study presented here, we evaluated the isotopic labeling of bone using 41Ca, a long-lived radiotracer, as an alternative approach. After successful labeling of the skeleton, changes in the systematics of urinary 41Ca excretion are expected to directly reflect changes in bone Ca metabolism. A minute amount of 41Ca (100 nCi) was administered orally to 22 postmenopausal women. Kinetics of tracer excretion were assessed by monitoring changes in urinary 41Ca/40Ca isotope ratios up to 700 days post-dosing using accelerator mass spectrometry and resonance ionization mass spectrometry. Isotopic labeling of the skeleton was evaluated by two different approaches: (i) urinary 41Ca data were fitted to an established function consisting of an exponential term and a power law term for each individual; (ii) 41Ca data were analyzed by population pharmacokinetic (NONMEM) analysis to identify a compartmental model that describes urinary 41Ca tracer kinetics. A linear three-compartment model with a central compartment and two sequential peripheral compartments was found to best fit the 41Ca data. Fits based on the use of the combined exponential/power law function describing urinary tracer excretion showed substantially higher deviations between predicted and measured values than fits based on the compartmental modeling approach. By establishing the urinary 41Ca excretion pattern using data points up to day 500 and extrapolating these curves up to day 700, it was found that the calculated 41Ca/40Ca isotope ratios in urine were significantly lower than the observed 41Ca/40Ca isotope ratios for both techniques. Compartmental analysis can overcome this limitation. By identifying relative changes in transfer rates between compartments in response to an intervention, inaccuracies in the underlying model cancel out. Changes in tracer distribution between compartments were modeled based on identified kinetic parameters. While changes in bone formation and resorption can, in principle, be assessed by monitoring urinary 41Ca excretion over the first few weeks post-dosing, assessment of an intervention effect is more reliable approximately 150 days post-dosing when excreted tracer originates mainly from bone.

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In epidemiological work, outcomes are frequently non-normal, sample sizes may be large, and effects are often small. To relate health outcomes to geographic risk factors, fast and powerful methods for fitting spatial models, particularly for non-normal data, are required. We focus on binary outcomes, with the risk surface a smooth function of space. We compare penalized likelihood models, including the penalized quasi-likelihood (PQL) approach, and Bayesian models based on fit, speed, and ease of implementation. A Bayesian model using a spectral basis representation of the spatial surface provides the best tradeoff of sensitivity and specificity in simulations, detecting real spatial features while limiting overfitting and being more efficient computationally than other Bayesian approaches. One of the contributions of this work is further development of this underused representation. The spectral basis model outperforms the penalized likelihood methods, which are prone to overfitting, but is slower to fit and not as easily implemented. Conclusions based on a real dataset of cancer cases in Taiwan are similar albeit less conclusive with respect to comparing the approaches. The success of the spectral basis with binary data and similar results with count data suggest that it may be generally useful in spatial models and more complicated hierarchical models.

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As the performance gap between microprocessors and memory continues to increase, main memory accesses result in long latencies which become a factor limiting system performance. Previous studies show that main memory access streams contain significant localities and SDRAM devices provide parallelism through multiple banks and channels. These locality and parallelism have not been exploited thoroughly by conventional memory controllers. In this thesis, SDRAM address mapping techniques and memory access reordering mechanisms are studied and applied to memory controller design with the goal of reducing observed main memory access latency. The proposed bit-reversal address mapping attempts to distribute main memory accesses evenly in the SDRAM address space to enable bank parallelism. As memory accesses to unique banks are interleaved, the access latencies are partially hidden and therefore reduced. With the consideration of cache conflict misses, bit-reversal address mapping is able to direct potential row conflicts to different banks, further improving the performance. The proposed burst scheduling is a novel access reordering mechanism, which creates bursts by clustering accesses directed to the same rows of the same banks. Subjected to a threshold, reads are allowed to preempt writes and qualified writes are piggybacked at the end of the bursts. A sophisticated access scheduler selects accesses based on priorities and interleaves accesses to maximize the SDRAM data bus utilization. Consequentially burst scheduling reduces row conflict rate, increasing and exploiting the available row locality. Using a revised SimpleScalar and M5 simulator, both techniques are evaluated and compared with existing academic and industrial solutions. With SPEC CPU2000 benchmarks, bit-reversal reduces the execution time by 14% on average over traditional page interleaving address mapping. Burst scheduling also achieves a 15% reduction in execution time over conventional bank in order scheduling. Working constructively together, bit-reversal and burst scheduling successfully achieve a 19% speedup across simulated benchmarks.

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Target localization has a wide range of military and civilian applications in wireless mobile networks. Examples include battle-field surveillance, emergency 911 (E911), traffc alert, habitat monitoring, resource allocation, routing, and disaster mitigation. Basic localization techniques include time-of-arrival (TOA), direction-of-arrival (DOA) and received-signal strength (RSS) estimation. Techniques that are proposed based on TOA and DOA are very sensitive to the availability of Line-of-sight (LOS) which is the direct path between the transmitter and the receiver. If LOS is not available, TOA and DOA estimation errors create a large localization error. In order to reduce NLOS localization error, NLOS identifcation, mitigation, and localization techniques have been proposed. This research investigates NLOS identifcation for multiple antennas radio systems. The techniques proposed in the literature mainly use one antenna element to enable NLOS identifcation. When a single antenna is utilized, limited features of the wireless channel can be exploited to identify NLOS situations. However, in DOA-based wireless localization systems, multiple antenna elements are available. In addition, multiple antenna technology has been adopted in many widely used wireless systems such as wireless LAN 802.11n and WiMAX 802.16e which are good candidates for localization based services. In this work, the potential of spatial channel information for high performance NLOS identifcation is investigated. Considering narrowband multiple antenna wireless systems, two xvNLOS identifcation techniques are proposed. Here, the implementation of spatial correlation of channel coeffcients across antenna elements as a metric for NLOS identifcation is proposed. In order to obtain the spatial correlation, a new multi-input multi-output (MIMO) channel model based on rough surface theory is proposed. This model can be used to compute the spatial correlation between the antenna pair separated by any distance. In addition, a new NLOS identifcation technique that exploits the statistics of phase difference across two antenna elements is proposed. This technique assumes the phases received across two antenna elements are uncorrelated. This assumption is validated based on the well-known circular and elliptic scattering models. Next, it is proved that the channel Rician K-factor is a function of the phase difference variance. Exploiting Rician K-factor, techniques to identify NLOS scenarios are proposed. Considering wideband multiple antenna wireless systems which use MIMO-orthogonal frequency division multiplexing (OFDM) signaling, space-time-frequency channel correlation is exploited to attain NLOS identifcation in time-varying, frequency-selective and spaceselective radio channels. Novel NLOS identi?cation measures based on space, time and frequency channel correlation are proposed and their performances are evaluated. These measures represent a better NLOS identifcation performance compared to those that only use space, time or frequency.

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Reuse distance analysis, the prediction of how many distinct memory addresses will be accessed between two accesses to a given address, has been established as a useful technique in profile-based compiler optimization, but the cost of collecting the memory reuse profile has been prohibitive for some applications. In this report, we propose using the hardware monitoring facilities available in existing CPUs to gather an approximate reuse distance profile. The difficulties associated with this monitoring technique are discussed, most importantly that there is no obvious link between the reuse profile produced by hardware monitoring and the actual reuse behavior. Potential applications which would be made viable by a reliable hardware-based reuse distance analysis are identified.

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Determining how an exhaust system will perform acoustically before a prototype muffler is built can save the designer both a substantial amount of time and resources. In order to effectively use the simulation tools available it is important to understand what is the most effective tool for the intended purpose of analysis as well as how typical elements in an exhaust system affect muffler performance. An in-depth look at the available tools and their most beneficial uses are presented in this thesis. A full parametric study was conducted using the FEM method for typical muffler elements which was also correlated to experimental results. This thesis lays out the overall ground work on how to accurately predict sound pressure levels in the free field for an exhaust system with the engine properties included. The accuracy of the model is heavily dependent on the correct temperature profile of the model in addition to the accuracy of the source properties. These factors will be discussed in detail and methods for determining them will be presented. The secondary effects of mean flow, which affects both the acoustical wave propagation and the flow noise generation, will be discussed. Effective ways for predicting these secondary effects will be described. Experimental models will be tested on a flow rig that showcases these phenomena.

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Range estimation is the core of many positioning systems such as radar, and Wireless Local Positioning Systems (WLPS). The estimation of range is achieved by estimating Time-of-Arrival (TOA). TOA represents the signal propagation delay between a transmitter and a receiver. Thus, error in TOA estimation causes degradation in range estimation performance. In wireless environments, noise, multipath, and limited bandwidth reduce TOA estimation performance. TOA estimation algorithms that are designed for wireless environments aim to improve the TOA estimation performance by mitigating the effect of closely spaced paths in practical (positive) signal-to-noise ratio (SNR) regions. Limited bandwidth avoids the discrimination of closely spaced paths. This reduces TOA estimation performance. TOA estimation methods are evaluated as a function of SNR, bandwidth, and the number of reflections in multipath wireless environments, as well as their complexity. In this research, a TOA estimation technique based on Blind signal Separation (BSS) is proposed. This frequency domain method estimates TOA in wireless multipath environments for a given signal bandwidth. The structure of the proposed technique is presented and its complexity and performance are theoretically evaluated. It is depicted that the proposed method is not sensitive to SNR, number of reflections, and bandwidth. In general, as bandwidth increases, TOA estimation performance improves. However, spectrum is the most valuable resource in wireless systems and usually a large portion of spectrum to support high performance TOA estimation is not available. In addition, the radio frequency (RF) components of wideband systems suffer from high cost and complexity. Thus, a novel, multiband positioning structure is proposed. The proposed technique uses the available (non-contiguous) bands to support high performance TOA estimation. This system incorporates the capabilities of cognitive radio (CR) systems to sense the available spectrum (also called white spaces) and to incorporate white spaces for high-performance localization. First, contiguous bands that are divided into several non-equal, narrow sub-bands that possess the same SNR are concatenated to attain an accuracy corresponding to the equivalent full band. Two radio architectures are proposed and investigated: the signal is transmitted over available spectrum either simultaneously (parallel concatenation) or sequentially (serial concatenation). Low complexity radio designs that handle the concatenation process sequentially and in parallel are introduced. Different TOA estimation algorithms that are applicable to multiband scenarios are studied and their performance is theoretically evaluated and compared to simulations. Next, the results are extended to non-contiguous, non-equal sub-bands with the same SNR. These are more realistic assumptions in practical systems. The performance and complexity of the proposed technique is investigated as well. This study’s results show that selecting bandwidth, center frequency, and SNR levels for each sub-band can adapt positioning accuracy.

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Three-dimensional flow visualization plays an essential role in many areas of science and engineering, such as aero- and hydro-dynamical systems which dominate various physical and natural phenomena. For popular methods such as the streamline visualization to be effective, they should capture the underlying flow features while facilitating user observation and understanding of the flow field in a clear manner. My research mainly focuses on the analysis and visualization of flow fields using various techniques, e.g. information-theoretic techniques and graph-based representations. Since the streamline visualization is a popular technique in flow field visualization, how to select good streamlines to capture flow patterns and how to pick good viewpoints to observe flow fields become critical. We treat streamline selection and viewpoint selection as symmetric problems and solve them simultaneously using the dual information channel [81]. To the best of my knowledge, this is the first attempt in flow visualization to combine these two selection problems in a unified approach. This work selects streamline in a view-independent manner and the selected streamlines will not change for all viewpoints. My another work [56] uses an information-theoretic approach to evaluate the importance of each streamline under various sample viewpoints and presents a solution for view-dependent streamline selection that guarantees coherent streamline update when the view changes gradually. When projecting 3D streamlines to 2D images for viewing, occlusion and clutter become inevitable. To address this challenge, we design FlowGraph [57, 58], a novel compound graph representation that organizes field line clusters and spatiotemporal regions hierarchically for occlusion-free and controllable visual exploration. We enable observation and exploration of the relationships among field line clusters, spatiotemporal regions and their interconnection in the transformed space. Most viewpoint selection methods only consider the external viewpoints outside of the flow field. This will not convey a clear observation when the flow field is clutter on the boundary side. Therefore, we propose a new way to explore flow fields by selecting several internal viewpoints around the flow features inside of the flow field and then generating a B-Spline curve path traversing these viewpoints to provide users with closeup views of the flow field for detailed observation of hidden or occluded internal flow features [54]. This work is also extended to deal with unsteady flow fields. Besides flow field visualization, some other topics relevant to visualization also attract my attention. In iGraph [31], we leverage a distributed system along with a tiled display wall to provide users with high-resolution visual analytics of big image and text collections in real time. Developing pedagogical visualization tools forms my other research focus. Since most cryptography algorithms use sophisticated mathematics, it is difficult for beginners to understand both what the algorithm does and how the algorithm does that. Therefore, we develop a set of visualization tools to provide users with an intuitive way to learn and understand these algorithms.