Synthetic X-ray or digitally reconstructed radiographs (DRRs) are simulated X-ray images projected from computed tomography (CT) data that are commonly used for CT and real X-Ray image registration. High-quality synthetic X-ray images can facilitate various applications such as guiding images for virtual reality (VR) simulation and training data for deep learning methods such as creating CT data from X-Ray images. It is challenging to generate high-quality synthetic X-ray images from CT slices, especially in various view angles, due to gaps between CT slices, high computational cost, and the complexity of algorithms. Most synthetic X-ray generation methods use fast ray-tracing in a situation where the image quality demand is low. We aim to improve image quality while maintaining good accuracy and use two steps; 1) to generate synthetic X-ray images from CT data and 2) to increase the resolution of the synthetic X-ray images. Our synthetic X-ray image generation method adopts a matrix-based projection method and dynamic multi-segment lookup tables, which shows better image quality and efficiency compared to conventional synthetic X-ray image generation methods. Our method is tested in a real-time VR training system for image-guided intervention procedures. Then we proposed two novel approaches to raise the quality of synthetic X-ray images through deep learning methods. We use a reference-based super-resolution (RefSR) method as a base model to upsampling low-resolution images into higher resolution. Even though RefSR can produce fine details by utilizing the reference image, it inevitably generates some artifacts and noise. We propose texture transformer super-resolution with frequency domain (TTSR-FD) which introduces frequency domain loss as a constraint to improve the quality of the RefSR results with fine details and without apparent artifacts. To the best of our knowledge, this is the first work that utilizes frequency domain as a part of loss functions in the field of super-resolution (SR). We observe improved performance in evaluating TTSR-FD when tested on our synthetic X-ray and real X-ray image datasets. A typical SR network is trained with paired high-resolution (HR) and low-resolution (LR) images, where LR images are created by downsampling HR images using a specific kernel. The same downsampling kernel is also used to create test LR images from HR images. As a result, most SR methods only perform well when the testing image is acquired using the same downsampling kernel used during the training process. We also propose TTSR-DMK, which uses multiple downsampling kernels during training to generalize the model and adopt a dual model that trains together with the main model. The dual model can form a closed-loop with the main model to learn the inverse mapping, which further improves the model’s performance. Our method works well for testing images produced by multiple kernels used during training. It can also help improve the model performance when testing images are acquired with kernels not used during training. To the best of our knowledge, we are the first to use the closed-loop method in RefSR. We have achieved: (i) synthetic X-ray image generation from CT data, which is based on a matrix-based projection and lookup tables ; (ii) TTSR-FD: synthetic X-ray image super-resolution using a novel frequency domain loss ; (iii) TTSR-DMK: an adaptation network to overcome the performance drop for testing data which do not match to downsampling kernels used in training. Our TTSR-FD results show improvements (PSNR from 37.953 to 39. 009) compared to the state-of-the-art methods TTSR. Our experiment with real X-Ray images using TTSR-FD can remove visible artifacts in the qualitative study even though PSNR is similar. Our proposed adaptation network, TTSR-DMK, improved model performance for multiple kernels even with unknown kernel situations.

ClueMaker (CM) is a Java desktop application used for data visualisation (via graph) by subjects like insurance companies (to unravel fraud activity), Czech organisation Hlí- dač Státu (to identify connections between subjects) or many others. This application currently uses a naive way to merge entities from different data sources (matching one field by exact string match). Goal of this thesis is to analyse, create and integrate a solution to CM, which would allow for merging entities based on entity similarity, and integrate such solution into the GUI of CM. Such solution should allow the user to merge two graph entities, show user the potentially same or very similar entities and allow for a global scan of the graph for potential merges. Furthermore, this solution should make use of data relationships within CM in addition to the attributes of entities. 1

京都大学 / 0048 / 新制・課程博士 / 博士(薬科学) / 甲第21043号 / 薬科博第86号 / 新制||薬科||9(附属図書館) / 京都大学大学院薬学研究科薬科学専攻 / (主査)教授 高須 清誠, 教授 竹本 佳司, 教授 大野 浩章 / 学位規則第4条第1項該当 / Doctor of Pharmaceutical Sciences / Kyoto University / DFAM

The insights from the 2008 financial crisis were that the banking sector was in need of change of regulation. The period from 2008 and onwards has involved several changes, of which capital requirements, MREL requirements and the resolution tool are three main regulations which have been introduced. The question being asked is whether we are now in a new macroeconomic regime, or whether the previous market regime which still prevails. To answer the question, the regulation that was added after 2008 is examined, as well as how these have motivated strengthening financial stability. The empirical evidence underlying the analysis consists of documents published by relevant authorities acting or working with regulation and/or supervision of the financial sector. The study has been carried out via an idea analysis where empirical ideas are used to answer the question of which macroeconomic regime currently prevails. The former regime is referred to as the market regime and is characterized by a belief in efficient markets through deregulation, independent central banks and a belief in a free market as the key to financial development. The regime that emerges shows both similarities and differences with the market regime. The fundamental political ideology that prevailed under the previous regime persists even today, but at the same time there are indications of a breaking point in the regime. Today's regime is more restrictive and the view of responsibility has clearly changed. Market regime thus still prevails but in a new guise, which was named neo-market regime to describe the differences between the period before 2008 and the period after.

Document incorrectly classified as a dissertation on title page (decision to classify as a thesis from NDSU Graduate School) / Organocatalysis is a field that has bloomed over the last decades. With the field’s promise of being able to mimic nature and afford products in a synergistic manner to traditional Lewis acid catalysis, several interesting discoveries have been made. Owing to the vastness of the field as it exists today, this document will focus on two main aspects; cinchona alkaloid (and derivatives) as used in common carbon-carbon bond forming reactions and kinetic resolution via 4-dimethyl aminopyridine-N-oxide derivative driven acylation. Kinetic resolution via organocatalysis has the potential to react one enantiomer of a racemic mixture without affecting the other. The highlight of this screening was an s factor of 9 which was produced using optimized conditions using a catalyst designated DMAPO-IV. There remains much to do in improving the system and elucidating the scope of this catalytic system this report details the efforts made thus far.

<p>  </p> <p>Personality pathology has been consistently linked with negative relationship outcomes, though little work has focused on interpersonal dynamics that might explain the association between the two. In the current study, we used Actor Partner Interdependence Modeling (APIM) with self-reported personality features from the Personality Inventory for the DSM-4+ for individuals in committed romantic relationships. Scores on the personality disorder scales were used to predict self-reported change in positive and negative affect across a conflict resolution task as well as variability in affective valance and arousal during the conflict resolution task as coded by third-party raters. In general, both positive and negative affect increased after the conflict resolution task as compared to before. Variability in emotional arousal appeared largely unrelated to PD features. The most consistent finding across models was that change in internal affect and variability in expressed affect was most related to men’s PD features but not women’s, with some exceptions. Taken together, results suggest that couples are likely to exhibit greater variability in affect during conflict in couples in which a male partner is high in PD features. </p>

The goal of super-resolution is to increase not only the size of an image, but also its apparent resolution, making the result more plausible to human viewers. Many super-resolution methods do well at modest magnification factors, but even the best suffer from boundary and gradient artifacts at high magnification factors. This thesis presents Bayesian edge inference (BEI), a novel method grounded in Bayesian inference that does not suffer from these artifacts and remains competitive in published objective quality measures. BEI works by modeling the image capture process explicitly, including any downsampling, and modeling a fictional recapture process, which together allow principled control over blur. Scene modeling requires noncausal modeling within a causal framework, and an intuitive technique for that is given. Finally, BEI with trivial changes is shown to perform well on two tasks outside of its original domain—CCD demosaicing and inpainting—suggesting that the model generalizes well.

Wilderness search and rescue can be assisted by video searchers in manned aircraft. The video searcher's primary task is to find clues on the ground. Due to altitude, it may be difficult to resolve details on the ground with a standard video camera. As the video streams at a constant frame rate, the searcher may become distracted by other tasks. While handling these tasks the searcher may miss important clues or spend extra time flying over the search area; either outcome decreases both the effectiveness of the video searcher and the chances of successfully finding missing persons. We develop an efficient software system that allows the video searcher to deal with distractions while identifying, resolving, and geolocating clues using mixed-resolution video. We construct an inexpensive camera rig that feeds video and telemetry to this system. We also develop a simple flight simulator for generating synthetic search video for simulation and testing purposes. To validate our methods we conduct a user study and a field trial. An analysis of the user study results suggests that our system can combine the video streams without loss of performance in the primary or secondary search task. The resulting gains in screen-space efficiency can then be used to present more information, such as scene context or larger-resolution images. Additionally, the field trial suggests that the software is capable of robustly operating in a real-world environment.

Computers have vastly expanded capabilities for storing, creating, and manipulating spatial data, yet viewing area is still generally constrained to a single monitor. With this viewing window limitation, panning and zooming are required to view the full details of a map or image and, because of the large sizes of typical database, usually only in small portions. Multiple monitor configurations provide an attainable, low cost way for individuals to create large, high-resolution desktop displays. This increased screen real estate is particularly useful for viewing and interpreting rich and complex geospatial datasets because both context and amount of detail can be simultaneously increased, reducing reliance on virtual navigation to obtain the desired balance between context and scale. To evaluate the utility of multiple monitor displays for geospatial data, this experiment involved a variety of map and image reading tasks using both raster and vector data under three different monitor conditions: one monitor (1280 x 1024 pixels), four monitors (2560 x 2048 pixels), and nine monitors (3840 x 3072 pixels). Fifty-seven subjects took the test on one of the three display configurations. A computer program captured each subject's performance by recording answers, mouse click locations, viewing areas, tool usage, and elapsed time. A post-experiment questionnaire obtained additional qualitative feedback about subjects' experience with the tasks and display configuration. Overall, subjects did perform more efficiently on the larger display configurations as evidenced by a reduction in test completion time and in the amount of virtual navigation (mouse clicks) used to finish the test. Tool usage also differed among monitor conditions with navigation tools (zooming and panning) dominating on the single monitor while selecting tools (tools used to provide answers) predominated on the nine monitor display. While overall test results indicated the effectiveness of the larger displays, task-level analyses showed that specific performance varied considerably from task to task. The larger displays were the most efficient on some tasks, while other tasks showed similar results among all displays or even the single monitor as the most efficient. The best performance improvements occurred between the one and four monitor conditions, with the nine monitor condition mostly providing only modest additional improvement. Subjects rated the four monitor display size as the most ideal. / Master of Science

Error correction codes are a means of including redundancy in a stream of information bits to allow the detection and correction of symbol errors during transmission. The birth of error correction coding showed that Shannon's channel capacity could be achieved when transmitting information through a noisy channel. Turbo codes are a very powerful form of error correction codes that bring the performance of practical coding even closer to Shannon's theoretical specifications. Bit-error-rate (BER) performance and power dissipation are two important measures of performance used to characterize communication systems. Subject to the law of diminishing returns, as the resolution of the analog-to-digital converter (ADC) in the decoder increases, BER improves, but power dissipation increases. The number of decoding iterations has a similar effect on the BER performance and power dissipation of turbo coded systems. This is significant since turbo decoding is typically practiced in a fixed iterative manner, where all transmitted frames go through the same number of iterations. This is not always necessary since certain "good" frames would converge to their final bits within a few iterations, and other "bad" frames never do converge. In this thesis, we investigate the technical feasibility of adapting the resolution of the ADC in the decoder, and the number of decoding iterations, in order to obtain the best trade-off possible between BER performance and power dissipation in a communication system. With the aid of computer-aided simulations, this thesis investigates the performance and practical implementation issues associated with incorporating a variable resolution ADC into the decoder structure of turbo codes. The possibility of further power conservation resulting from reduced decoding computation is also investigated with the use of a recently developed iterative stopping criterion. / Master of Science