This work proposes a new method for using reduced order models in lieu of high fidelity analysis during the sensitivity analysis step of gradient based design optimization. The method offers a reduction in the computational cost of finite difference based sensitivity analysis in that context. The method relies on interpolating reduced order models which are based on proper orthogonal decomposition. The interpolation process is performed using radial basis functions and Grassmann manifold projection. It does not require additional high fidelity analyses to interpolate a reduced order model for new points in the design space. The interpolated models are used specifically for points in the finite difference stencil during sensitivity analysis. The proposed method is applied to an airfoil shape optimization (ASO) problem and a transport wing optimization (TWO) problem. The errors associated with the reduced order models themselves as well as the gradients calculated from them are evaluated. The effects of the method on the overall optimization path, computation times, and function counts are also examined. The ASO results indicate that the proposed scheme is a viable method for reducing the computational cost of these optimizations. They also indicate that the adaptive step is an effective method of improving interpolated gradient accuracy. The TWO results indicate that the interpolation accuracy can have a strong impact on optimization search direction.

The Coastal and Marine Ecological Classification Standard (CMECS) provides a comprehensive framework of common terminology for organizing physical, chemical, biological, and geological information about marine ecosystems. Federally endorsed as a dynamic content standard, all federally funded data must be compliant by 2018; however, applying CMECS to deep sea datasets and underwater video have not been extensively examined. The presented research demonstrates the extent to which CMECS can be applied to deep sea benthic habitats, assesses the feasibility of applying CMECS to remotely operated vehicle (ROV) video data in near-real-time, and establishes best practices for mapping environmental aspects and observed deep sea habitats as viewed by the ROV’s forwardacing camera. All data were collected during 2014 in the Northern Gulf of Mexico by the National Oceanic and Atmospheric Administration’s (NOAA) ROV Deep Discoverer and ship Okeanos Explorer.

Southeast Louisiana is susceptible to the impact of subsidence due to natural and anthropogenic processes including sediment compaction and loading, fluid withdrawal, and faulting. Subsidence rates in Southeast Louisiana are higher than anywhere else in the United States, and the impact of subsidence rates on industrial complexes has not been studied. Spatial interpolation methods were analyzed to determine the best fit for subsidence rates and to create a predictive surface for the lower Mississippi River Industrial corridor (LMRIC). Empirical Bayesian kriging, ordinary kriging, universal kriging, and inverse distance weighted interpolation methods were applied to the 2004 National Oceanic and Atmospheric Administration (NOAA) published Technical Report #50 dataset and cross-validation methods were utilized to determine the accuracy of each method. The mean error and root mean square error were calculated for each interpolation method, then used to detect bias and compare the predicted value with the actual observation value. Cross-validation estimates are comparable for each method statistically and visually; however, the results indicate the empirical Bayesian kriging interpolation method is the most accurate of the methods using the lowest mean error and root mean square error scores. Digital elevation models for the years 2025, 2050, and 2075 were developed based on the predictive surface of subsidence rates using the results from the empirical Bayesian kriging interpolation method. Results indicate that by 2025, 31.4% of landmass in the LMRIC will be below 0 m NAVD88, with 40.4% below 0 m NAVD88 by 2050, and 51.8% by 2075. Subsidence rates in the LMRIC range from approximately 16 mm to less than one mm per year. Nine of the 122 industrial complexes located in the LMRIC are estimated to be below 0 m NAVD88 by the year 2075. Limited economic impacts can be inferred based on the number of facilities impacted; however, service disruptions due to subsidence impacting infrastructure surrounding these industrial complexes would have catastrophic economic impacts on a regional, state, and national level.

No description available.

Scientific visualization computer applications generate visual representations of large and complex sets of science data. These types of applications allow scientists to gain greater knowledge and insight into their data. For example, the visualization of environmental data is of particular interest to biologists when trying to understand how complex variables interact. Modern robotics and sensors have expanded the ability to collect environmental data, thus, the size and variety of these data-sets have likewise grown. Oftentimes, the collected data are deposited into files and databases where they sit in their separate and unique formats. Without easy to use visualization tools, it is difficult to understand and interpret the information within these data-sets. NORUS, the North America-Norway educational program, has a scientific focus on how climate-induced changes impact the living resources and ecosystems in the Arctic. In order to obtain the necessary science data, the NORUS program utilizes the Slocum Glider, a form of Autonomous Underwater Vehicle (AUV). This thesis aims to create a compelling, efficient, and easy to use interactive system for visualizing large sets of science data collected by the Slocum Glider. This goal is obtained through the implementation of various methods taken from scientific visualization, real time rendering, and scattered data interpolation. Methods include visualizations of the surrounding terrain, the ability to map various science data to glyphs, control over color mapping, scattered data interpolation and interactive camera control.

This document presents the results of the master thesis conducted from April 2019 to October 2019 under the direction of CNES engineer Eric Bourgeois, as part of the KTH Master of Science in Aerospace Engineering curriculum. Within the framework of development studies for the Callisto demonstrator, this master thesis aims at studying and developing possible guidance strategies for the boosted landing. Two main approaches are described in this document : • Adaptive pseudo-spectral interpolation • Convex optimization The satisfying results yielded give strong arguments for choosing the latter as part of the Callisto GNC systems and describe possible implementation strategies as well as complementary analyses that could be conducted. / Denna rapport presenterar resultaten av ett examensarbete som genomfördes från april till oktober 2019 under ledning av CNES-ingenjören Eric Bourgeois, som en del av en masterexamen i flyg- och rymdteknik från KTH, Kungliga tekniska högskolan. Inom ramen för utvecklingsstudier för bärraketen Callisto syftar detta arbete att studera och utveckla möjliga reglerstrategier för Callistos landing som kontrolleras med raketer. Två huvudsakliga metoder beskrivs: • Adaptiv pseudospektral interpolering • Konvex optimering Resultaten ger starka argument för att välja den senare av dessa två metoder för Callistos reglersystem och beskriver möjliga implementeringsstrategier samt vilka kompletterande analyser som bör genomföras

Small firearms can create sound levels exceeding the safe threshold of human hearing with even one shot. Understanding how the sound propagates will lead to better range and military drill design. This thesis describes errors associated with different predictive interpolation models for the M16A4. Before directly discussing potential sources of error, the thesis first seeks to validate the data acquired. This is done through waveform inspection with a focus on shot-to-shot consistency. Finding the standard deviation in level between a 10-shot volley provides a good baseline with which other sources of error can be compared to. For both peak and 8-hour A-weighted equivalent levels, the deviation tended to be 1-1.2 dB. With this constraint in mind, the thesis then discussions potential error of measurements along the radial arc. By comparing nearest neighbor microphones with measured values, it was determined that a finer resolution behind the shooter is most relevant. Second, radial propagation was plotted to justify potential decay rates for further plotting. A model of spherical spreading is reasonable, but overestimates the level at farther distances e.g. 50 m. Lastly the thesis focuses on interpolation mapping to predict levels around the range. The baseline model was created using a Cartesian interpolation scheme that uses ghost points to help limit potential artifacts. Leave-one-out analysis highlighted a necessity of microphone placement behind the shooter and other less important microphones. Use of symmetry across the firing direction provides excellent results, generally below the 1 dB standard deviation. In the end, a best-practices guideline is given, which reduces number of required microphones by half. Through these analyses, future measurements will be more effective in microphone placement. With these level maps, one will also be able to better determine potential hearing risks associated with small firearm use and even avoid them through better drill.

I denna studie har jag utforskat vilka kreativa möjligheter samt utmaningar det finns i musikskapande efter förgiven förlaga. Det som kallas Interpolation. Interpolation är en form av lånande, där låtskaparen implementerar en del av en redan inspelad låt i skapandet av något nytt. Arbetet rör sig inom populärmusik-genren där jag har försökt se hur jag kan använda interpolation som ett verktyg i mitt eget musikskapande. Jag har sett att användandet av interpolationer är allt oftare förekommande i den musiken jag själv lyssnar på och det var detta som inspirerade mig att genomföra denna undersökning, då jag ville få mer kunskap och utforska användandet av interpolationer. Studien genomförde jag genom att skriva och producera tre olika låtar med tre olika interpolationer. Interpolationerna hade olika infallsvinklar till det jag valde att interpolera med i respektive låt; melodi, text och sound (icke melodiskt). Under arbetets gång förde jag även en strukturerad loggbok, med syftet att skapa en förklaring av mitt praktiska arbete.Resultatet av studien har gett mig en bredare kunskap om begreppet interpolation och dess kreativa användningsområde inom musikskapande. Jag har i och med detta utökat min konstnärliga verktygslåda. Förutom de kreativa möjligheterna med interpolation har även studien gett mig insikt i andra användningsområden så som användandet av interpolation för att ”boosta” sin karriär som artist.

The ability to understand videos at the level of pixels plays a key role in a wide range of computer vision applications. For example, a robot or autonomous vehicle relies on classifying each pixel in the video stream into semantic categories to holistically understand the surrounding environment, and video editing software needs to exploit the spatiotemporal context of video pixels to generate various visual effects. Despite the great progress of Deep Learning (DL) techniques, applying DL-based vision models to process video pixels remains practically challenging, due to the high volume of video data and the compute-intensive design of DL approaches. In this thesis, we aim to design efficient and robust deep models for pixel-level video understanding of high-level semantics, mid-level grouping, and low-level interpolation. Toward this goal, in Part I, we address the semantic analysis of video pixels with the task of Video Semantic Segmentation (VSS), which aims to assign pixel-level semantic labels to video frames. We introduce methods that utilize temporal redundancy and context to efficiently recognize video pixels without sacrificing performance. Extensive experiments on various datasets demonstrate our methods' effectiveness and efficiency on both common GPUs and edge devices. Then, in Part II, we show that pixel-level motion patterns help to differentiate video objects from their background. In particular, we propose a fast and efficient contour-based algorithm to group and separate motion patterns for video objects. Furthermore, we present learning-based models to solve the tracking of objects across frames. We show that by explicitly separating the object segmentation and object tracking problems, our framework achieves efficiency during both training and inference. Finally, in Part III, we study the temporal interpolation of pixels given their spatial-temporal context. We show that intermediate video frames can be inferred via interpolation in a very efficient way, by introducing the many-to-many splatting framework that can quickly warp and fuse pixels at any number of arbitrary intermediate time steps. We also propose a dynamic refinement mechanism to further improve the interpolation quality by reducing redundant computation. Evaluation on various types of datasets shows that our method can interpolate videos with state-of-the-art quality and efficiency. To summarize, we discuss and propose efficient pipelines for pixel-level video understanding tasks across high-level semantics, mid-level grouping, and low-level interpolation. The proposed models can contribute to tackling a wide range of real-world video perception and understanding problems in future research.

Algorithms for automatic image registration and mosaicking are developed for a miniature Unmanned Aerial Vehicle (MINI-UAV) platform, assembled by Air-O-Space International (AOSI) L.L.C.. Three cameras onboard this MINI-UAV platform acquire images in a single frame simultaneously at green (550nm), red (650 nm), and near infrared (820nm) wavelengths, but with shifting and rotational misalignment. The area-based method is employed in the developed algorithms for control point detection, which is applicable when no prominent feature details are present in image scenes. Because the three images to be registered have different spectral characteristics, region of interest determination and control point selection are the two key steps that ensure the quality of control points. Affine transformation is adopted for spatial transformation, followed by bilinear interpolation for image resampling. Mosaicking is conducted between adjacent frames after three-band co-registration. Pre-introducing the rotation makes the area-based method feasible when the rotational misalignment cannot be ignored. The algorithms are tested on three image sets collected at Stennis Space Center, Greenwood, and Oswalt in Mississippi. Manual evaluation confirms the effectiveness of the developed algorithms. The codes are converted into a software package, which is executable under the Microsoft Windows environment of personal computer platforms without the requirement of MATLAB or other special software support for commercial-off-the-shelf (COTS) product. The near real-time decision-making support is achievable with final data after its installation into the ground control station. The final products are color-infrared (CIR) composite and normalized difference vegetation index (NDVI) images, which are used in agriculture, forestry, and environmental monitoring.