158 research outputs found

    The effects of continuity of care on hospital utilization in patients with knee osteoarthritis: analysis of Nationwide insurance data

    Get PDF
    BACKGROUND: Korea's rapidly aging population has led to a rise in the prevalence of knee osteoarthritis (which reached upwards of 21.3% in 2017) in elderly people aged 65 years and over. Most patients with knee osteoarthritis require ongoing management in the community or through primary care. Continuity of care is a desirable attribute of primary care. However, previous studies on the association between continuity of care and health outcomes have focused on specific disease populations, particularly diabetes mellitus and hypertension. The objectives of this study were to determine whether there is an association between continuity of care for outpatients with knee osteoarthritis and health outcomes. METHODS: We conducted a cohort study using claims data from 2014. The study population included 131,566 patients. We measured hospital admission and medical costs during the final 3 months and the continuity of care by Most Frequent Provider Continuity (MFPC), Modified Modified Continuity Index (MMCI), and Continuity of Care (COC) index in the 9 preceding months, using multiple logistic regression analyses to determine which index best explains continuity. We evaluated the relationship between COC and hospital admissions, using negative binomial regression analysis due to over-dispersion. Finally, multiple regressions were used to examine the relationship between the COC and medical costs. RESULTS: We selected the COC index to determine the association between hospital admission and cost; the area under the receiver operating characteristic curve (AUC) of the COC was the largest (0.904), while those for the MFPC (0.894) and MMCI (0.893) were similar. The negative binomial regression analysis showed that continuity of care was significantly related to hospitalization, with the relative risk (RR) of hospital admission being low for patients with high continuity of care [RRโ€‰=โ€‰27.17 for those with the reference group COC (0.76-1.00); 95% CI, 3.09-3.51]. Continuity of care was significantly related to medical costs after considering other covariates. A higher COC index was associated with a lower cost. CONCLUSIONS: Higher continuity of care for knee osteoarthritis patients might decrease hospital admission and medical costs.ope

    ํฌ๋ผ์šฐ๋“œ์†Œ์‹ฑ ์‹œ์Šคํ…œ์—์„œ์˜ ๋น ๋ฅด๊ณ  ์‹ ๋ขฐ์„ฑ ๋†’์€ ์ถ”๋ก  ์•Œ๊ณ ๋ฆฌ์ฆ˜

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2021. 2. ์ •๊ต๋ฏผ.As the need for large scale labeled data grows in various fields, the appearance of web-based crowdsourcing systems gives a promising solution to exploiting the wisdom of crowds efficiently in a short time with a relatively low budget. Despite their efficiency, crowdsourcing systems have an inherent problem in that responses from workers can be unreliable since workers are low-paid and have low responsibility. Although simple majority voting can be a natural solution, various research studies have sought to aggregate noisy responses to obtain greater reliability in results. In this dissertation, we propose novel iterative massage-passing style algorithms to infer the groundtruths from noisy answers, which can be directly applied to real crowdsourcing systems. While EM-based algorithms get the limelight in crowdsourcing systems due to their useful inference techniques, our proposed algorithms draw faster and more reliable answers through an iterative scheme based on the idea of low-rank matrix approximations. We show that the performance of our proposed iterative algorithms are order-optimal, which outperforms majority voting and EM-based algorithms. Unlike other researches solving simple binary-choice questions (yes & no), our studies cover more complex task types which contain multiple-choice questions, short-answer questions, K-approval voting, and real-valued vector regression.๋‹ค์–‘ํ•œ ๋ถ„์•ผ์—์„œ ๋ผ๋ฒจ๋œ ๋น…๋ฐ์ดํ„ฐ๋ฅผ ํ•„์š”๋กœ ํ•˜๋Š” ํ˜„์žฌ, ์›น ๊ธฐ๋ฐ˜ ํฌ๋ผ์šฐ๋“œ์†Œ์‹ฑ ์„œ๋น„์Šค๋“ค์ด ์ถœ๋ฒ”ํ•˜๋ฉฐ ์ƒ๋Œ€์ ์œผ๋กœ ์ ์€ ์˜ˆ์‚ฐ๊ณผ ์งง์€ ์‹œ๊ฐ„์—๋„ ํšจ์œจ์ ์œผ๋กœ ์‚ฌ๋žŒ๋“ค์˜ ์ง€ํ˜œ๋ฅผ ํ™œ์šฉํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐฉ๋ฒ•๋“ค์ด ์ œ์‹œ๋˜๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฐฉ๋ฒ•๋“ค์˜ ํšจ์œจ์„ฑ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ํฌ๋ผ์šฐ๋“œ์†Œ์‹ฑ ์‹œ์Šคํ…œ์˜ ์„ ์ฒœ์ ์ธ ๋ฌธ์ œ์ ์€ ์ผ์„ ๋งก์€ ์‚ฌ๋žŒ๋“ค์˜ ์ ์€ ๋ณด์ƒ ๋ฐ ์ฑ…์ž„๊ฐ ๊ฒฐ์—ฌ๋กœ ์ธํ•ด ๊ทธ๋“ค์˜ ์‘๋‹ต์„ ์™„์ „ํžˆ ์‹ ๋ขฐํ•  ์ˆ˜ ์—†๋‹ค๋Š” ์ ์— ์žˆ๋‹ค. ์ด์— ๋‹ค์ˆ˜๊ฒฐ ๋ฐฉ์‹์ด ์ž์—ฐ์Šค๋Ÿฌ์šด ํ•ด๋ฒ•์œผ๋กœ ์‚ฌ์šฉ๋˜์ง€๋งŒ, ๋ณด๋‹ค ์‹ ๋ขฐ ๋†’์€ ๋‹ต์„ ์–ป์–ด๋‚ด๊ธฐ ์œ„ํ•ด ๋งŽ์€ ์—ฐ๊ตฌ๋“ค์ด ์ง„ํ–‰๋˜๊ณ  ์žˆ๋‹ค. ๋ณธ ๋ฐ•์‚ฌํ•™์œ„ ๋…ผ๋ฌธ์—์„œ๋Š” ํฌ๋ผ์šฐ๋“œ์†Œ์‹ฑ ์‹œ์Šคํ…œ์—์„œ ์ˆ˜๋งŽ์€ ์‚ฌ๋žŒ๋“ค๋กœ๋ถ€ํ„ฐ ๋ฐ›์€ ์‘๋‹ต๋“ค์„ ๋ชจ์•„ ์‹ ๋ขฐ์„ฑ ๋†’์€ ์‘๋‹ต์„ ์ถ”๋ก ํ•˜๋Š” ๋ฐ˜๋ณต์  ๋ฉ”์„ธ์ง€์ „๋‹ฌ ํ˜•ํƒœ์˜ ์•Œ๊ณ ๋ฆฌ์ฆ˜๋“ค์„ ์ œ์‹œํ•œ๋‹ค. ๋ณธ ์•Œ๊ณ ๋ฆฌ์ฆ˜๋“ค์€ ๋‚ฎ์€๋žญํฌ๊ทผ์‚ฌ์— ๊ธฐ๋ฐ˜ํ•œ ๋ฐ˜๋ณต ์ถ”๋ก  ๋ฐฉ๋ฒ•์œผ๋กœ, ๊ธฐ์กด์— ๊ฐ๊ด‘๋ฐ›๋˜ EM ์•Œ๊ณ ๋ฆฌ์ฆ˜๋“ค์— ๋น„ํ•ด ๋” ๋น ๋ฅด๊ณ  ์‹ ๋ขฐ์ ์ธ ์ •๋‹ต์„ ์ถ”๋ก ํ•ด๋‚ธ๋‹ค. ๋”๋ถˆ์–ด ๋ณธ ์•Œ๊ณ ๋ฆฌ์ฆ˜๋“ค์˜ ์ถ”๋ก  ์ •ํ™•๋„๊ฐ€ ์ตœ์ ์— ๋งค์šฐ ๊ทผ์ ‘ํ•˜๋ฉฐ ๋‹ค์ˆ˜๊ฒฐ ๋ฐฉ์‹ ๋ฐ EM ์•Œ๊ณ ๋ฆฌ์ฆ˜๋“ค์˜ ์ •ํ™•๋„๋ฅผ ์ƒํšŒํ•œ๋‹ค๋Š” ๊ฒƒ์„ ์ด๋ก ์  ์ฆ๋ช… ๋ฐ ์‹คํ—˜์  ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด ์ œ์‹œํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์‹ค์ œ ํฌ๋ผ์šฐ๋“œ์†Œ์‹ฑ์—์„œ ๋Œ€๋‹ค์ˆ˜์˜ ์‘๋‹ต ์œ ํ˜•์„ ์ฐจ์ง€ํ•˜๋Š” ๊ฐ๊ด€์‹ ์‘๋‹ต, ์ฃผ๊ด€์‹ ์‘๋‹ต, ๋ณต์ˆ˜ ์„ ํƒ ์‘๋‹ต, ๋ฐ ์‹ค์ˆ˜ ๊ฐ’ ์‘๋‹ต์˜ ์ถ”๋ก  ๋ฌธ์ œ๋ฅผ ๋‹ค๋ฃจ๋ฉฐ, ๊ธฐ์กด ์–‘์žํƒ์ผ ์‘๋‹ต ์ถ”๋ก  ๋ฌธ์ œ๋งŒ์„ ๋‹ค๋ฃจ๋Š” ๊ธฐ์กด ์—ฐ๊ตฌ๋“ค๊ณผ ํฐ ์ฐจ๋ณ„์„ฑ์„ ๊ฐ€์ง„๋‹ค.1 Introduction 1 2 Background 9 2.1 Crowdsourcing Systems for Binary-choice Questions 9 2.1.1 Majority Voting 10 2.1.2 Expectation Maximization 11 2.1.3 Message Passing 11 3 Crowdsourcing Systems for Multiple-choice Questions 12 3.1 Related Work 13 3.2 Problem Setup 16 3.3 Inference Algorithm 17 3.3.1 Task Allocation 17 3.3.2 Multiple Iterative Algorithm 18 3.3.3 Task Allocation for General Setting 20 3.4 Applications 23 3.5 Analysis of Algorithms 25 3.5.1 Quality of Workers 25 3.5.2 Bound on the Average Error Probability 27 3.5.3 Proof of the Error Bounds 29 3.5.4 Proof of Sub-Gaussianity 32 3.6 Experimental Results 36 3.6.1 Comparison with Other Algorithms 37 3.6.2 Adaptive Scenario 38 3.6.3 Simulations on a Set of Various D Values 41 3.7 Conclusion 43 4 Crowdsourcing Systems for Multiple-choice Questions with K-Approval Voting 45 4.1 Related Work 47 4.2 Problem Setup 49 4.2.1 Problem Definition 49 4.2.2 Worker Model for Various (D, K) 50 4.3 Inference Algorithm 51 4.4 Analysis of Algorithms 53 4.4.1 Worker Model 55 4.4.2 Quality of Workers 56 4.4.3 Bound on the Average Error Probability 58 4.4.4 Proof of the Error Bounds 59 4.4.5 Proof of Sub-Gaussianity 62 4.4.6 Phase Transition 67 4.5 Experimental Results 68 4.5.1 Performance on the Average Error with q and l 68 4.5.2 Relationship between Reliability and y-message 69 4.5.3 Performance on the Average Error with Various (D, K) Pairs 69 4.6 Conclusion 72 5 Crowdsourcing Systems for Real-valued Vector Regression 73 5.1 Related Work 75 5.2 Problem Setup 77 5.3 Inference Algorithm 78 5.3.1 Task Message 79 5.3.2 Worker Message 80 5.4 Analysis of Algorithms 81 5.4.1 Worker Model 81 5.4.2 Oracle Estimator 84 5.4.3 Bound on the Average Error Probability 86 5.5 Experimental Results 91 5.5.1 Real Crowdsourcing Data 91 5.5.2 Verification of the Error Bounds with Synthetic data 96 5.6 Conclusion 98 6 Conclusions 99Docto

    Ophthalmologic Manifestation of Inflammatory Bowel Disease: A Review

    Get PDF
    In patients with inflammatory bowel disease (IBD), ocular extraintestinal manifestations (EIM) are less common than EIM of other systems, but they are clinically important because they can lead to complications that can cause catastrophic damage to the visual acuity and ocular structure. Anterior uveitis and episcleritis are the most common ocular EIM. Involvement of the orbit, posterior segment, and optic nerve can also occur. A variety of treatments are available ranging from topical steroids to systemic immunosuppressive therapies. The treatment of IBD is also essential if the activity of inflammatory bowel disease affects the ocular symptoms.ope

    A Study on the Mitigation Methods of Financial Burden in Public Long-term Care Insurance System: Comparison of South Korea, Japan, and Germany

    Get PDF
    The rapidly aging trend of Korea is a major factor that threatens the sustainability of the long-term care insurance system. Therefore, looking at how Japan and Germany mitigated the financial burden when they managed similar long-term care insurance systems will provide important implications for improving the Korean system in the future. The study was conducted using the literature review method, and the "country" was set as a unit for the case analysis. The three countries selected are Korea, Japan, and Germany. Recently in Korea, the insurance premium rates of all subjects have been rapidly rising, which can exacerbate the issue of intergenerational equity. On the other hand, Japan has responded to the aggravating finances for long-term care insurance due to aging by raising coinsurance for selected groups like the wealthy elderly. Germany is selectively raising the insurance premium rates by additionally increasing the premium rate for childless recipients. A more preventive and quality-oriented care service plan can be promoted by referring to the recent changes in Japan and Germany. In addition, a more effective and selective increase in payment burden in Japan and Germany could be considered in response to a recent equity issue in Korea.ope

    Eupatilin ์ด methionine choline ๊ฒฐํ• ์‹์ด์— ์˜ํ•œ ๊ฐ„ ์†์ƒ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์˜ํ•™๊ณผ, 2014. 2. ์œค์ •ํ™˜.Introduction: The prevailing hypothesis in pathogenesis of nonalcoholic steatohepatitis (NASH) consists of two steps: excessive fat accumulation and hepatocyte injury by oxidative stress, abnormal cytokines, mitochondrial dysfunction, and/or endoplasmic reticulum (ER) stress. Eupatilin, a pharmacologically active ingredient found in Artemisia asiatica, has been established anti-oxidative, anti-inflammatory, and cytoprotective agents. In the present study, we evaluated whether eupatilin prevents the development of NASH in mice. Methods: C57BL/6 mice were fed methionic choline-deficient (MCD) diet with or without eupatilin (50 or 100 mg/kg per body weight) for 8 weeks. The effects of eupatilin on the development and progression of NASH and underlying mechanism were studied. Results: Eupatilin attenuated the liver injury and contributed to histological improvements, including non-alcoholic fatty liver disease activity score (NAS) through suppression of hepatic inflammation, oxidative stress, and ER stress. However, pharmacological effect of eupatilin was not sufficient to reduce the NAS less than 5, which corresponded to NASH. Conclusions: Modulation of oxidative and ER stress by eupatilin was not sufficient to eradicate development of NASH. However, eupatilin ameliorated hepatocyte injury and NAS. Further studies are needed to maximize the preventative effects of eupatilin in NASH by dose increase or combination therapy.Abstract i Contents iii List of tables iv List of figures v List of abbreviations and symbols vi Introduction 1 Materials and methods 3 Results 9 Discussion 20 References 23 ์š”์•ฝ (๊ตญ๋ฌธ ์ดˆ๋ก) 27Maste

    ๋ฐœ๊ด‘๋‹ค์ด์˜ค๋“œ ์‘์šฉ์„ ์œ„ํ•œ ๋‚˜๋…ธํŒจํ„ด๋œ ๊ธฐํŒ ์ƒ์˜ 3์กฑ ์งˆํ™”๋ฌผ ์—ํ”ผ์„ฑ์žฅ ์—ฐ๊ตฌ

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์žฌ๋ฃŒ๊ณตํ•™๋ถ€, 2018. 2. ์œค์˜์ค€.Group III-nitride has been regarded as one of the most promising material for optoelectronic device applications such as light-emitting diode (LED) and laser diode (LD) over past few decades. In order to realize highly efficient and reliable optoelectronic devices, high quality III-nitride epitaxial layers are required. A major problem in the epitaxial growth of III-nitride is that the use of native substrates is still limited due to lack of commercially available substrates. Therefore, III-nitride epitaxial layers are grown on foreign substrates such as sapphire and Si. However, large lattice mismatch and thermal mismatch between the III-nitride epitaxial layers and the substrates lead to several problems such as high-density dislocations, low light extraction efficiency (LEE), and residual film stress, thus hinder the realization of highly efficient III-nitride optoelectronic devices. Therefore, to obtain high quality III-nitride epitaxial layers that are less defective, less strained, and more effective to enhance the LEE is very important for various III-nitride LED applications. In this study, nano-patterned substrates have been proposed to obtain the high quality III-nitride layers for important epitaxial structures in the III-nitride LED applications such as GaN on Si substrate, AlN on sapphire substrate, and GaN on sapphire substrate. The epitaxial growth of III-nitrides on the nano-patterned substrates was investigated by metal-organic chemical vapor deposition. Firstly, for the case of GaN on Si substrate, nanoheteroepitaxy (NHE) of GaN on the AlN/Si(111) nanorod structure was investigated. Silica nanosphere lithography was employed to fabricate the periodic hexagonal nanorod array with a narrow gap of 30 nm between the nanorods. Fully coalesced GaN film was obtained over the nanorod structure and its threading dislocation density (TDD) was found to decrease down to half, compared to that of GaN grown on the planar AlN/Si(111) substrate. Transmission electron microscopy (TEM) revealed that threading dislocation (TD) bending and TD termination by stacking faults occurred near the interface between GaN and AlN/Si(111) nanorods, contributing to the TDD reduction. Moreover, the 70% relaxation of the tensile stress of the NHE GaN was confirmed by Raman and PL measurements compared to GaN on the planar AlN/Si(111) substrate. These results suggested that NHE on the AlN/Si(111) nanorods fabricated by nanosphere lithography is a promising technique to obtain continuous GaN layers with the improved crystalline quality and the reduced residual stress. Secondly, a nano-patterned AlN/sapphire substrate was developed to improve the performance of deep ultraviolet (DUV) LEDs, for the case of AlN on sapphire substrate. We demonstrated AlGaN-based DUV LEDs with periodic air-voids-incorporated nanoscale patterns enabled by nanosphere lithography and epitaxial lateral overgrowth (ELO). The nanoscale ELO on the nano-patterned substrate improved the crystal quality of overgrown epitaxial layers at relatively low growth temperature of 1050 oC and at small coalescence thickness. The air voids formed in the AlN epitaxial layer effectively relaxed the tensile stress during growth, so that crack-free DUV LED epitaxial layers were obtained on 4-in. sapphire substrate. In addition, the periodically embedded air-void nanostructure enhanced the LEE of DUV LEDs by breaking the total internal reflection that is particularly severe for the predominant anisotropic emission in AlGaN-based DUV LEDs. The light output power of the DUV LEDs on the nano-patterned substrate was enhanced by 67% at an injection current of 20 mA compared to that of the reference DUV LEDs. We attribute such a remarkable enhancement to the formation of embedded periodic air voids which cause simultaneous improvements in the crystal quality of epitaxial layers by ELO and LEE enabled by breaking the predominant in-plane guided propagation of DUV photons. Lastly, we proposed the ELO of GaN using the nano-cavity patterned sapphire substrate (NCPSS), which has hexagonally non-close-packed nano-cavity patterns on the sapphire substrates, to grow high quality GaN on sapphire substrate. The fabrication of the NCPSS was enabled by polystyrene coating followed by deposition of alumina and thermal annealing. The coalescence of GaN on the NCPSS was achieved by the formation of relatively large GaN islands and enhanced ELO of the GaN islands over several nano-cavity patterns. The TDD was significantly reduced from 2.4ร—10^8 /cm^2 to 6.9ร—10^7 /cm^2 by using the NCPSS. Dislocation behaviors that contribute to the reduction of TDD of the GaN layer were observed by TEM. Raman spectroscopy revealed that the compressive stress in the GaN layer was reduced by 21% due to the embedded nano-cavities. In addition, the diffuse reflectance of GaN on the NCPSS was enhanced by 54% ~ 62%, which is attributed to the increased probability of light extraction through effective light scattering by nano-cavities.Chapter 1 Introduction 1 1.1 III-nitride materials 1 1.1.1 General properties of III-nitride materials 1 1.1.2 III-nitride based LEDs 2 1.2 Epitaxial growth of III-nitrides 7 1.3 Substrate for III-nitride 10 1.3.1 Sapphire substrate 10 1.3.2 Si substrate 11 1.4 Problems of heteroepitaxial III-nitrides 16 1.4.1 Dislocation 16 1.4.2 Low light extraction efficiency 17 1.4.3 Film stress 18 1.5 Epitaxial growth of III-nitrides on patterned substrates 21 1.6 Thesis contents and organization 27 1.7 Bibliography 30 Chapter 2 Experiment and analysis 34 2.1 Growth process 34 2.1.1 Metal-organic chemical vapor deposition (MOCVD) 34 2.1.2 Atomic layer deposition (ALD) 34 2.2 Analysis tools 35 2.2.1 Scanning electron microscopy (SEM) 35 2.2.2 High-resolution X-ray diffraction (XRD) 35 2.2.3 Atomic force microscopy (AFM) 35 2.2.4 Photoluminescence (PL) 36 2.2.5 Cathodoluminescence (CL) 36 2.2.6 Micro-Raman spectroscopy 36 2.2.7 Transmission electron microscopy (TEM) 36 2.2.8 Light-current-voltage (L-I-V) measurement 37 Chapter 3 Nanoheteroepitaxy of GaN on AlN/Si(111) nanorods 38 3.1 Introduction: nanoheteroepitaxy of GaN on Si substrate 38 3.2 Experimental procedure 43 3.3 Results and discussion 46 3.3.1 Fabrication of AlN/Si(111) nanorods 46 3.3.2 Growth of GaN on AlN/Si(111) nanorods 53 3.3.3 Effect of nano-patterned substrate on GaN-on-Si structure 67 3.4 Summary 71 3.5 Bibliography 72 Chapter 4 AlGaN-based deep ultraviolet light-emitting diode on nano-patterned AlN/sapphire substrate 76 4.1 Introduction 76 4.1.1 Growth of AlxGa1-xN layer on patterned substrate 82 4.1.2 Technique for enhancing LEE 86 4.2 Experimental procedure 88 4.3 Results and discussion 92 4.3.1 Fabrication of nano-patterned AlN/sapphire substrate 92 4.3.2 Growth of AlxGa1-xN layers on nano-patterned AlN/sapphire substrate 97 4.3.3 Device fabrication and characterization 106 4.3.4 3-D finite-difference time-domain (FDTD) simulation: effect of embedded air void on light extraction 115 4.4 Summary 119 4.5 Bibliography 120 Chapter 5 Epitaxial lateral overgrowth of GaN on nano-cavity patterned sapphire substrate (NCPSS) 126 5.1 Introduction: growth of GaN with embedded voids 126 5.2 Experimental procedure 129 5.3 Results and discussion 132 5.3.1 Fabrication of NCPSS 132 5.3.2 Epitaxial lateral overgrowth of GaN on NCPSS 141 5.3.3 Structural and optical properties of GaN on NCPSS 151 5.4 Summary 163 5.5 Bibliography 164 Chapter 6 Conclusions 169Docto

    On-chip memory reduction in CNN hardware design for image super-resolution

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2019. 2. ์ดํ˜์žฌ.Single image super-resolution (SISR) ์„ ์œ„ํ•œ convolutional neural network (CNN) ๋Š” ์˜์ƒ ๋ถ„๋ฅ˜์šฉ CNN๊ณผ ๋‹ฌ๋ฆฌ ๊ณ ํ•ด์ƒ๋„์˜ ์˜์ƒ์„ ์ž…๋ ฅ ๋ฐ›์•„ ๊ณ ํ•ด์ƒ๋„์˜ ์ค‘๊ฐ„ ์—ฐ์‚ฐ ๊ฒฐ๊ณผ์ธ feature map์„ ์ƒ์„ฑ ํ•œ๋‹ค. SISR์šฉ CNN์„ ๊ฐ€์†ํ•˜๊ธฐ ์œ„ํ•œ ํ•˜๋“œ์›จ์–ด๋Š” ์ฃผ๋กœ ๋””์Šคํ”Œ๋ ˆ์ด ์žฅ์น˜์— ์ ์šฉ์ด ๋˜๋ฉฐ ์™ธ๋ถ€ ๋ฉ”๋ชจ๋ฆฌ ์ ‘๊ทผ์ด ๋ถˆ๊ฐ€๋Šฅํ•œ ์ŠคํŠธ๋ฆฌ๋ฐ ๊ตฌ์กฐ๋ฅผ ๊ฐ–๋Š”๋‹ค. ์ด๋Š” on-chip ๋ฉ”๋ชจ๋ฆฌ์˜ ์šฉ๋Ÿ‰์ด ์ œํ•œ์ ์ธ ํ•˜๋“œ์›จ์–ด์˜ ํŠน์„ฑ์ƒ ๊ตฌํ˜„์˜ ์–ด๋ ค์›€์„ ์•ผ๊ธฐํ•œ๋‹ค. ๊ธฐ์กด์˜ ์—ฐ๊ตฌ๋“ค์€ on-chip ๋ฉ”๋ชจ๋ฆฌ๋ฅผ ๊ฐ์†Œํ•˜๊ธฐ ์œ„ํ•ด ์„ฑ๋Šฅ ์ €ํ•˜ ๋˜๋Š” ์••์ถ• ๋ชจ๋“ˆ์„ ์ถ”๊ฐ€ํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ์„ฑ๋Šฅ ์ €ํ•˜ ์—†์ด SISR์šฉ CNN ํ•˜๋“œ์›จ์–ด์˜ on-chip ๋ฉ”๋ชจ๋ฆฌ ๊ฐ์†Œ ๋ฐ ํ•˜๋“œ์›จ์–ด๋ฅผ ์„ค๊ณ„ํ•˜๊ธฐ ์œ„ํ•œ ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. CNN ํ•˜๋“œ์›จ์–ด๋Š” VDSR (Very deep neural network for super-resolution) ๊ตฌ์กฐ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ๋‹ค. ๊ธฐ์กด CNN ํ•˜๋“œ์›จ์–ด์˜ SRAM์— ์ฝ๊ธฐ ๋ฐ ์“ฐ๊ธฐ ์ ‘๊ทผ์ด ๋™์‹œ์— ๋ฐœ์ƒํ•˜๋Š” ๋ž˜์Šคํ„ฐ ์Šค์บ” ์ˆœ์„œ๋ฅผ ๋ถ€๋ถ„์  ์ˆ˜์ง ์ˆœ์„œ๋กœ ๋ณ€๊ฒฝ ํ•จ์œผ๋กœ ์ฝ๊ธฐ ๋ฐ ์“ฐ๊ธฐ ์ ‘๊ทผ ํƒ€์ด๋ฐ์„ ๋ถ„๋ฆฌํ•œ๋‹ค. ๋ถ€๋ถ„์  ์ˆ˜์ง ์ˆœ์„œ๋Š” ๊ธฐ์กด์˜ CNN ํ•˜๋“œ์›จ์–ด๊ฐ€ ์‚ฌ์šฉํ•˜๋Š” ๋“€์–ผ ํฌํŠธ SRAM ๋Œ€์‹  ์‹ฑ๊ธ€ ํฌํŠธ SRAM์„ ์‚ฌ์šฉํ•˜๋„๋ก ํ•˜๋ฉฐ ์ด๋Š” on-chip ๋ฉ”๋ชจ๋ฆฌ๋ฅผ ์ ˆ๋ฐ˜์œผ๋กœ ๊ฐ์†Œํ•œ๋‹ค. ๋‘ ๋ฒˆ์งธ ๋ฐฉ๋ฒ•์œผ๋กœ VDSR์˜ ํ•„ํ„ฐ์˜ ํ˜•ํƒœ๋ฅผ ๋ณ€๊ฒฝํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ ์šฉํ•œ๋‹ค. On-chip ๋ฉ”๋ชจ๋ฆฌ์˜ ํฌ๊ธฐ๋Š” ์ปจ๋ณผ๋ฃจ์…˜ ํ•„ํ„ฐ์˜ ๋†’์ด์— ๋น„๋ก€ํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ VDSR์˜ ํ•„ํ„ฐ๋Š” ๋Œ€์นญ ๊ตฌ์กฐ ์ค‘ ๊ฐ€์žฅ ์ž‘์€ ํ•„ํ„ฐ ๋ชจ์–‘์ด๋ฏ€๋กœ ํ•ด๋‹น ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์ปจํ…์ŠคํŠธ ๋ณด์กด 1D ํ•„ํ„ฐ ๊ตฌ์„ฑ ๋ฐฉ๋ฒ• ๋ฐ ์ปจํ…์ŠคํŠธ๋ฅผ ๊ธฐ๋ฐ˜ํ•œ ์„ธ๋กœ ํ•„ํ„ฐ ๊ฐ์†Œ ๋ฐฉ๋ฒ•์„ ์ ์šฉํ•˜์—ฌ SRAM์˜ ํฌ๊ธฐ๋ฅผ ์ ˆ๋ฐ˜์œผ๋กœ ์ถ”๊ฐ€์ ์œผ๋กœ ๊ฐ์†Œํ•œ๋‹ค. CNN ํ•˜๋“œ์›จ์–ด ๊ตฌ์กฐ๊ฐ€ ํ™•์ • ๋œ ์ดํ›„ CNN์˜ SISR ์„ฑ๋Šฅ์„ ๊ฐœ์„  ํ•˜๊ธฐ ์œ„ํ•œ CNNํ•™์Šต ๋ฐฉ๋ฒ•์„ ์ž์—ฐ ์˜์ƒ (natural image)์™€ ํ…์ŠคํŠธ ์˜์ƒ (text image)์— ๋Œ€ํ•ด ๊ฐ๊ฐ ์ œ์•ˆํ•œ๋‹ค. SRGAN (Super-resolution generative adversarial networks) ๋Š” ํŒ๋ณ„์ž ๋„คํŠธ์›Œํฌ (discriminator network)๋กœ๋ถ€ํ„ฐ ๋ฐœ์ƒํ•˜๋Š” ์†์‹ค์œผ๋กœ SISR์šฉ CNN์ด ์‹ค์ œ ์˜์ƒ์ฒ˜๋Ÿผ ๋ณด์ด๋Š” ์ž์—ฐ ์˜์ƒ์„ ์ถœ๋ ฅํ•˜๋„๋ก ํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ SRGAN์€ ๊ณผ์„ ๋ช…ํ™”๋กœ ์ธํ•œ ์‹œ๊ฐ์  ๊ฒฐํ•จ์„ ๋ฐœ์ƒํ•˜๋Š” ๋ฌธ์ œ๊ฐ€ ์žˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ SRGAN์˜ ์‹œ๊ฐ์  ๊ฒฐํ•จ์„ ์ œ๊ฑฐํ•˜๋Š” ๋‘ ๊ฐ€์ง€ ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์ฒซ ๋ฒˆ์งธ๋Š” ํŒ๋ณ„์ž ๋„คํŠธ์›Œํฌ์˜ ๊ตฌ์กฐ๋ฅผ ๋ณ€๊ฒฝํ•˜์—ฌ ํŒ๋ณ„์ž ๋„คํŠธ์›Œํฌ ๋‚ด์—์„œ ์˜์ƒ์˜ ์„ธ๋ถ€ ์ •๋ณด ์†์‹ค์„ ๋ฐฉ์ง€ํ•˜๋Š” ํ•ด์ƒ๋„ ์œ ์ง€ ํŒ๋ณ„์ž ๋„คํŠธ์›Œํฌ ๊ตฌ์กฐ๋ฅผ ์ œ์•ˆ ํ•œ๋‹ค. ๋‘ ๋ฒˆ์งธ๋Š” ์ฝ˜ํ…ํŠธ ์†์‹ค์„ ๋ฐœ์ƒํ•˜๋Š” VGG ๋„คํŠธ์›Œํฌ์˜ ๊ตฌ์กฐ์ƒ ์˜์ƒ์˜ ์„ธ๋ถ€์ ์ธ ์ •๋ณด๋ฅผ ์†์‹คํ•˜๋Š” ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ํ•ด์ƒ๋„ ์œ ์ง€ ์ฝ˜ํ…ํŠธ ์†์‹ค ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ํ…์ŠคํŠธ ์˜์ƒ์€ ์ž์—ฐ ์˜์ƒ์ด ์•„๋‹Œ ํ•ฉ์„ฑ ์˜์ƒ์œผ๋กœ ์˜์ƒ ๋‚ด ํฐํŠธ์™€ ๋ฐฐ๊ฒฝ์˜ ์ƒ‰์ƒ ์กฐํ•ฉ์„ ๋‹ค์–‘ํ•˜๊ฒŒ ๋ณ€๊ฒฝ๋  ์ˆ˜ ์žˆ๋‹ค. ๊ธฐ์กด์˜ CNN ํ•™์Šต ๋ฐฉ๋ฒ•์€ ๋„คํŠธ์›Œํฌ์˜ ์ผ๋ฐ˜ํ™”๋ฅผ ์œ„ํ•ด ๋‹ค์–‘ํ•œ ์ข…๋ฅ˜์˜ ์˜์ƒ์„ ํ•™์Šต ์‹œํ‚ค๋Š” ๋ฐฉ๋ฒ•์„ ์‚ฌ์šฉํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋ชจ๋“  ์ข…๋ฅ˜์˜ ์ƒ‰์ƒ ์กฐํ•ฉ์„ CNN์— ํ•™์Šต ์‹œํ‚ค๋Š” ๊ฒƒ์€ ๋ถˆ๊ฐ€๋Šฅํ•˜๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ์˜์ƒ ์••์ถ•์— ์‚ฌ์šฉ๋˜๋Š” De-colorization ๋ฐฉ๋ฒ•์„ ์ฐจ์šฉํ•˜์—ฌ CNN์ด ํ•™์Šตํ•  ์˜์ƒ์„ ๊ฒ€์€ ํฐํŠธ์™€ ํฐ์ƒ‰ ๋ฐฐ๊ฒฝ์œผ๋กœ ์ด๋ฃจ์–ด์ง„ ์˜์ƒ์œผ๋กœ ํ•œ์ • ํ•จ์œผ๋กœ ํ•™์Šต๋˜์ง€ ์•Š์€ ์˜์ƒ์˜ ํฐํŠธ ๋ฐ ๋ฐฐ๊ฒฝ ์ƒ‰์ƒ ์กฐํ•ฉ์—๋„ ์‹œ๊ฐ์  ๊ฒฐํ•จ ์—†์ด SISR ์—ฐ์‚ฐ์„ ์ˆ˜ํ–‰ ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์•ˆ ํ•œ๋‹ค.Unlike convolutional neural network (CNN) for image classification, CNN for single image super-resolution (SISR) receives high-resolution image and generates feature maps which are high-resolution intermediate results. The hardware for accelerating the CNN for SISR is mainly applied to the display device, and the CNN hardware has a streaming architecture in which external memory access is impossible. This causes implementation difficulties due to the limited hardware capacity of the on-chip memory. This paper proposes two methods for designing CNN hardware for SISR using limited hardware resources. CNN hardware is based on a very deep neural network for super-resolution (VDSR) architecture. By using the partially-vertical order for the convolution layers, simultaneous read and write accesses to SRAM are prevented. The proposed order makes CNN use single-port SRAM instead of dual-port SRAM, and it reduces on-chip memory area by half. The second method is to change the shape of the filter in VDSR. The size of the on-chip memory is proportional to the height of the convolution filter. However, since the filter of VDSR is the smallest of the symmetric shape, it is impossible to reduce the filter height of the VDSR. To solve this problem, a method of constructing a context-preserving 1D filter and a method of decreasing a vertical filter based on the context are proposed. These proposed methods reduce the size of the SRAM in half. Two CNN training methods for SISR of natural image and that of text image are proposed. These methods improve SISR performance after the CNN hardware architecture is confirmed. SRGAN (super-resolution generative adversarial networks) is trained by the help of discriminator network to generate realistic natural images. However, SRGAN has the problem of causing visual defects due to over-sharpening. This paper proposes two methods to eliminate the visual defects of SRGAN. First, the resolution-preserving discriminator network structure is proposed. This discriminator network prevents detailed information loss in the network by changing the structure of it. Second, the resolution-preserving content loss is proposed to solve the problem of loss of detailed information of image due to the structure of VGG19 network that causes content loss. The text image is not a natural image but a synthetic image. The color combination of the font and the background in the image can be variously changed. The existing CNN learning method uses a method of learning various kinds of images to generalize the network. However, it is impossible to learn all kinds of color combinations on CNN. This paper uses the de-colorization method used in image compression to limit the image to be learned by CNN to a black font and a white background image. As a result, CNN performs SISR operation without visual flaws in the font and background color combination image of the trained image.์ œ 1 ์žฅ ์„œ ๋ก  1 1.1 ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ 1 1.2 ์—ฐ๊ตฌ์˜ ๋‚ด์šฉ 5 1.3 ๋…ผ๋ฌธ์˜ ๊ตฌ์„ฑ 8 ์ œ 2 ์žฅ ์ด์ „ ์—ฐ๊ตฌ 9 2.1 SISR CNN ์•Œ๊ณ ๋ฆฌ์ฆ˜ 9 2.2 ์ŠคํŠธ๋ฆฌ๋ฐ ๊ตฌ์กฐ์˜ SISR ํ•˜๋“œ์›จ์–ด 14 2.3 ๊ธฐ์กด CNN ํ•˜๋“œ์›จ์–ด์˜ on-chip ๋ฉ”๋ชจ๋ฆฌ ๊ฐ์†Œ ๋ฐฉ๋ฒ• 15 2.4 De-colorization 17 ์ œ 3 ์žฅ ์ปจ๋ณผ๋ฃจ์…˜ ๋‰ด๋Ÿด ๋„คํŠธ์›Œํฌ์˜ SRAM ๋ฉด์  ๊ฐ์†Œ๋ฅผ ์œ„ํ•œ ์—ฐ์‚ฐ ์ˆœ์„œ ๋ณ€๊ฒฝ 20 3.1 ๋ถ€๋ถ„์  ์ˆ˜์ง ์ˆœ์„œ ์ปจ๋ณผ๋ฃจ์…˜ ์—ฐ์‚ฐ 20 3.2 ifmap์„ ์ €์žฅํ•˜๊ธฐ ์œ„ํ•œ ๋ ˆ์ง€์Šคํ„ฐ 24 3.3 CNN์˜ ์ฒซ ๋ฒˆ์งธ ๋ฐ ๋งˆ์ง€๋ง‰ ์ปจ๋ณผ๋ฃจ์…˜ ๋ ˆ์ด์–ด SRAM ๊ตฌ์„ฑ 26 3.4 fmap์˜ SRAM ๋‹ค์ฑ„๋„ ๊ณต์œ ๋ฅผ ์œ„ํ•œ ๋ถ€๋ถ„์  ์ˆ˜์ง ์ˆœ์„œ 28 3.5 ๋ถ€๋ถ„์  ์ˆ˜์ง ์ˆœ์„œ์˜ ์ ์šฉ ๊ฐ€๋Šฅ CNN ๊ตฌ์กฐ 33 3.5 ์‹คํ—˜ ๊ฒฐ๊ณผ 36 ์ œ 4 ์žฅ ์˜์ƒ์˜ ์ปจํ…์ŠคํŠธ ๋ณด์กด์„ ์œ„ํ•œ ํ•„ํ„ฐ ์žฌ๊ตฌ์„ฑ ๋ฐ CNN ํ•˜๋“œ์›จ์–ด ์„ค๊ณ„ 42 4.1 SRAM ๊ฐ์†Œ๋ฅผ ์œ„ํ•œ ์ œ์•ˆ ์•Œ๊ณ ๋ฆฌ์ฆ˜ 43 4.2 SISR์šฉ CNN ํ•˜๋“œ์›จ์–ด ๊ตฌ์กฐ 49 4.3 ์‹คํ—˜ ๊ฒฐ๊ณผ 55 ์ œ 5 ์žฅ SISR์„ ์œ„ํ•œ ํ•ด์ƒ๋„ ๋ณด์กด ์ƒ์‚ฐ์  ์ ๋Œ€ ์‹ ๊ฒฝ๋ง ๊ตฌ์กฐ 64 5.1 ํ•ด์ƒ๋„ ๋ณด์กด ํŒ๋ณ„ ์‹ ๊ฒฝ๋ง ๊ตฌ์กฐ 64 5.2 ํ•ด์ƒ๋„ ๋ณด์กด ์ฝ˜ํ…ํŠธ ์†์‹ค 68 5.3 ์‹คํ—˜ ๊ฒฐ๊ณผ 70 ์ œ 6 ์žฅ De-colorization์„ ์ ์šฉํ•œ text SISR 84 6.1 Text de-colorization์„ ์ ์šฉํ•œ CNN ํ•™์Šต 84 6.2 ์‹คํ—˜ ๊ฒฐ๊ณผ 86 ์ œ 7 ์žฅ ๊ฒฐ๋ก  95 ์ฐธ๊ณ ๋ฌธํ—Œ 98 Abstract 105Docto

    Clinical features and long-term treatment outcome of posterior scleritis

    Get PDF
    Background: To analyze the clinical characteristics and long-term treatment outcomes of patients with posterior scleritis. Methods: This retrospective, observational case series analyzed medical records of 14 patients diagnosed with infectious or non-infectious posterior scleritis between May 2005 and March 2020 at Severance Hospital and Gangnam Severance Hospital. Results: A total of 12 patients with non-infectious and two with infectious posterior scleritis were treated. Conjunctival injection (85.7%) was the most common symptom, followed by pain on eyeball movement (57.1%), and decreased visual acuity (42.9%). Anterior uveitis (64.3%) was the most common associated clinical finding. In five eyes (35.7%), immunosuppressive agents were administered in addition to corticosteroids to control the inflammation. Recurrence was noted in three eyes (21.4%), all of them showing non-infectious scleritis. The final visual acuity of the patients did not show significant change compared to that at the first visit (P=0.878). Conclusions: Most posterior scleritis patients were of non-infectious type and some needed additional immunosuppressive treatment. In patients with a history of ocular surgery or trauma, especially with the presence of pus-containing nodules, infectious posterior scleritis should always be considered. Since impaired vision does not improve significantly after treatment of posterior scleritis, prompt diagnosis and aggressive treatment are recommended.ope

    Therapeutic Effect of High Viscosity Silicone Oil for Treatment of Refractory Macular Hole: A Case Report

    Get PDF
    Purpose: To report a case of recurrent macular hole that formed after vitrectomy for proliferative vitreoretinopathy with retinal detachment and was successfully treated using high viscosity silicone oil (HVSO). Case summary: A 48-year-old man visited our clinic for blurred vision in his left eye. Best corrected visual acuity (BCVA) was 20/1,000 in his left eye. A horseshoe tear at 2 oโ€™clock and bullous retinal detachment (RD), involving macula was found on fundus exam. The patient underwent pars plana vitrectomy (PPV), inner limiting membrane (ILM) peeling, and sulphurhexafluoride (SF6) injection. After 3 weeks, a macular hole was found in his left eye. He underwent additional PPV, autologous ILM transplantation, autologous platelet concentrate injection, and 20% SF6 gas injection. However, the hole remained 5 weeks after the second operation. Thus, he underwent an additional gas injection using perfluoropropane. When the macular hole still had not resolved, a third SF6 gas injection was performed. Three weeks later, the hole was still present and the patient underwent a fourth operation using HVSO. Two months after the last operation, the hole was completely closed, and was maintained at 8 months without any complications from emulsification. The oil was removed, and the hole remained closed for 3 years. BCVA at the last follow up was 20/1,000. Conclusions: We successfully treated chronic refractory macular hole using HVSO, which occurred secondary to vitrectomy for RD. Based on this case, HVSO might be an alternative to traditional gas tamponade for treating chronic refractory macular hole after vitrectomy for RD.ope
    • โ€ฆ
    corecore