315 research outputs found

    Low-Dose CT Using Denoising Diffusion Probabilistic Model for 20×\times Speedup

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    Low-dose computed tomography (LDCT) is an important topic in the field of radiology over the past decades. LDCT reduces ionizing radiation-induced patient health risks but it also results in a low signal-to-noise ratio (SNR) and a potential compromise in the diagnostic performance. In this paper, to improve the LDCT denoising performance, we introduce the conditional denoising diffusion probabilistic model (DDPM) and show encouraging results with a high computational efficiency. Specifically, given the high sampling cost of the original DDPM model, we adapt the fast ordinary differential equation (ODE) solver for a much-improved sampling efficiency. The experiments show that the accelerated DDPM can achieve 20x speedup without compromising image quality

    Refraction of nonlinear light beams in nematic liquid crystals

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    Optical spatial solitons in nematic liquid crystals, termed nematicons, have become an excellent test bed for nonlinear optics, ranging from fundamental effects to potential uses, such as designing and demonstrating all-optical switching and routing circuits in reconfigurable settings and guided-wave formats. Following their demonstration in planar voltage-assisted nematic liquid crystal cells, the spatial routing of nematicons and associated waveguides have been successfully pursued by exploiting birefringent walkoff, interactions between solitons, electro-optic controlling, lensing effects, boundary effects, solitons in twisted arrangements, refraction and total internal reflection and dark solitons. Refraction and total internal reflection, relying on an interface between two dielectric regions in nematic liquid crystals, provides the most striking results in terms of angular steering. In this thesis, the refraction and total internal reflection of self-trapped optical beams in nematic liquid crystals in the case of a planar cell with two separate regions defined by independently applied bias voltages have been investigated with the aim of achieving a broader understanding of the nematicons and their control. The study of the refraction of nematicons is then extended to the equivalent refraction of optical vortices. The equations governing nonlinear optical beam propagation in nematic liquid crystals are a system consisting of a nonlinear Schr¨odinger-type equation for the optical beam and an elliptic Poisson equation for the medium response. This system of equations has no exact solitary wave solution or any other exact solutions. Although numerical solutions of the governing equations can be found, it has been found that modulation theories give insight into the mechanisms behind nonlinear optical beam evolution, while giving approximate solutions in good to excellent agreement with full numerical solutions and experimental results. The modulation theory reduces the infinite-dimensional partial differential equation problem to a finite dynamical system of comparatively simple ordinary differential equations which are, then easily solved numerically. The modulation theory results on the refraction and total internal reflection of nematicons are in excellent agreement with experimental data and numerical simulations, even when accounting for the birefringent walkoff. The modulation theory also gives excellent results for the refraction of optical vortices of +1 topological charge. The modulation theory predicts that the vortices can become unstable on interaction with the nematic interface, which is verified in quantitative detail by full numerical solutions. This prediction of their azimuthal instability and their break-up into bright beams still awaits an experimental demonstration, but the previously obtained agreement of modulation theory models with the behaviour of actual nematicons leads us to expect the forthcoming observation of the predicted effects with vortices as well

    Using Analytical Hierarchy Process Methods in Cash Holding and Corporate Working Capital Management: an Asian Perspective

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    Cash holding behavior is an important financial behavior of the company, which reflects the company\u27s financial strategy and management strategy. What are the factors that affect corporate cash holdings? How does the change in these factors affect the change in corporate cash holdings? Starting from two aspects of national macroeconomic environmental factors and microeconomic environmental factors, this paper tries to analyze these factors and how they affect corporate cash holdings. Working Capital Management is an important part of the company\u27s financial management, which is closely related to the value creation of the company. What is the content of working capital management? How to manage the working capital effectively? This paper expounds the contents of working capital management from the perspective of process management, and expounds how to effectively manage working capital from the perspective of situational management. To link these two areas ids the goal of this study

    Sub-volume-based Denoising Diffusion Probabilistic Model for Cone-beam CT Reconstruction from Incomplete Data

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    Deep learning (DL) has emerged as a new approach in the field of computed tomography (CT) with many applicaitons. A primary example is CT reconstruction from incomplete data, such as sparse-view image reconstruction. However, applying DL to sparse-view cone-beam CT (CBCT) remains challenging. Many models learn the mapping from sparse-view CT images to the ground truth but often fail to achieve satisfactory performance. Incorporating sinogram data and performing dual-domain reconstruction improve image quality with artifact suppression, but a straightforward 3D implementation requires storing an entire 3D sinogram in memory and many parameters of dual-domain networks. This remains a major challenge, limiting further research, development and applications. In this paper, we propose a sub-volume-based 3D denoising diffusion probabilistic model (DDPM) for CBCT image reconstruction from down-sampled data. Our DDPM network, trained on data cubes extracted from paired fully sampled sinograms and down-sampled sinograms, is employed to inpaint down-sampled sinograms. Our method divides the entire sinogram into overlapping cubes and processes them in parallel on multiple GPUs, successfully overcoming the memory limitation. Experimental results demonstrate that our approach effectively suppresses few-view artifacts while preserving textural details faithfully

    A Graph-Based Collision Resolution Scheme for Asynchronous Unsourced Random Access

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    This paper investigates the multiple-input-multiple-output (MIMO) massive unsourced random access in an asynchronous orthogonal frequency division multiplexing (OFDM) system, with both timing and frequency offsets (TFO) and non-negligible user collisions. The proposed coding framework splits the data into two parts encoded by sparse regression code (SPARC) and low-density parity check (LDPC) code. Multistage orthogonal pilots are transmitted in the first part to reduce collision density. Unlike existing schemes requiring a quantization codebook with a large size for estimating TFO, we establish a \textit{graph-based channel reconstruction and collision resolution (GB-CR2^2)} algorithm to iteratively reconstruct channels, resolve collisions, and compensate for TFO rotations on the formulated graph jointly among multiple stages. We further propose to leverage the geometric characteristics of signal constellations to correct TFO estimations. Exhaustive simulations demonstrate remarkable performance superiority in channel estimation and data recovery with substantial complexity reduction compared to state-of-the-art schemes.Comment: 6 pages, 6 figures, submitted to IEEE GLOBECOM 202

    主要境界ベクトルを用いたテンプレート削減アルゴリズムとオンチップ学習VLSIへの実装

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    学位の種別: 課程博士審査委員会委員 : (主査)東京大学准教授 三田 吉郎, 東京大学教授 櫻井 貴康, 東京大学教授 浅田 邦博, 東京大学教授 相田 仁, 東京大学教授 相澤 清晴, 東京大学准教授 山崎 俊彦University of Tokyo(東京大学
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