310 research outputs found

    Probabilistic Estimation of Incomplete Map Using Gaussian Process

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐ๊ณตํ•™๋ถ€, 2013. 8. ์˜ค์„ฑํšŒ.Gaussian process is a powerful probabilistic estimation tool which is used widely in engineering fields such as Computer vision, Robotics and sensor networks, etc. This thesis implemented an estimation algorithm of the total map with sparse sensing data using Gaussian Process. In the implemented algorithm, two kinds of kernel functions are applied to the spatial Gaussian Process modelsquared exponential kernel and neural network kernel. The performance of the proposed algorithm was verified by the experiments with a simple mobile sensor network. To construct a simple mobile sensor network based on ROS (Robot Operating System) platform, a two wheeled mobile robot (Pioneer3DX) and a two dimensional laser scanner (SICKlms200) are used.1 Introduction 1 1.1 Mobile Sensor Network 1.2 Simulataneous Localization and Mapping (SLAM) 1.3 Occupancy Grid Map 2 Related Work 2.1 Mapping 2.2 Sensing and Locating 2.3 Probabilistic Solution for Mapping Problem 3 Gaussian Process (GP) 3.1 Weight-space View 3.1.1 The Standard Linear Model 3.1.2 Projections of Inputs into Feature Space 3.2 Function-space View 3.2.1 Prediction with Noise-free Observations 3.2.2 Prediction using Noisy Observations 3.3 Varying Hyperparameters 4 GP Applied to Mapping Problem 4.1 Overview of Contextual Mapping 4.2 Training Hyperparameters 5 Experimental results 5.1 The Mapping Problem in a Real Indoor Environment 5.2 GP Estimation for Single Frame of Laser Scanner 5.2.1 The given Training Data 5.2.2 Selecting a Kernel Function 5.2.3 Optimizing Hyper-parameters 5.2.4 Estimation 5.3 The Estimation Problem in a Simulated Environment 6 Conclusion 6.1 Contribution of GP for Mapping Problem 6.2 Future WorksMaste

    ๋™์–‘์˜ ํํ—ˆ๋ฅผ ์„ฑ์  ๋Œ€์ƒํ™”ํ•˜๊ธฐ: ๋ชจ๋ ˆ๋…ธ ๋‘๋ž€์˜ ใ€Ž๋ง˜๋ธŒ๋ฃจใ€, ์ฝœ๋กฌ๋น„์•„ ๋Œ€๋Œ€, ํ•œ๊ตญ์ „์Ÿ, ํ”ผ์นด์†Œ, (๋งˆ๋ฆด๋ฆฐ) ๋จผ๋กœ ๋…ํŠธ๋ฆฐ

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    ์ฝœ๋กฌ๋น„์•„ ์ž‘๊ฐ€ ๋ผํŒŒ์—˜ ์›€๋ฒ ๋ฅดํ†  ๋ชจ๋ ˆ๋…ธ ๋‘๋ž€(Rafael Humberto Moreno-Durรกn, 1946~2005)์˜ ์†Œ์„ค ใ€Ž๋ง˜๋ธŒ๋ฃจใ€(Mambrรบ, 1996)๋Š” ํ•œ๊ตญ์ „์Ÿ ๋•Œ ์—ฐํ•ฉ๊ตฐ์˜ ์ผ๋ถ€๋กœ ํŒŒ๋ณ‘๋˜์—ˆ๋˜ ์•ฝ 1,500๋ช…์˜ ๊ตฐ์ธ๋“ค๋กœ ๊ตฌ์„ฑ๋œ ์ฝœ๋กฌ๋น„์•„ ๋Œ€๋Œ€์— ๋Œ€ํ•œ ์„ธ๋ฐ€ํ•œ ์กฐ์‚ฌ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์“ด ์ž‘ํ’ˆ์ด๋‹ค. ์ด ์†Œ์„ค์€ ๊ด‘๋ฒ”์œ„ํ•œ ์—ญ์‚ฌ์ , ์ €๋„๋ฆฌ์ฆ˜์  ์กฐ์‚ฌ์˜ ๊ฒฐ๊ณผ๋กœ ์ž‘๊ฐ€๋Š” ์ฐธ์ „๊ตฐ์ธ ์ธํ„ฐ๋ทฐ์™€ ์ฆ์–ธ์œผ๋กœ ์ •๋ณด๋ฅผ ๋ชจ์•˜๊ณ , ๊ณผ๊ฑฐ์— ๋Œ€ํ•œ ๊ทธ๋“ค์˜ ์ด์•ผ๊ธฐ๋ฅผ 1990๋…„๋Œ€์˜ ์‹œ์ ์—์„œ ํ—ˆ๊ตฌ์ ์œผ๋กœ ์žฌ๊ตฌ์„ฑํ–ˆ๋‹ค. ํ™”์ž๋Š” ์—ฌ์„ฏ ๋ช…์ด๋ฉฐ, ๊ทธ ์ค‘ ํ•œ ๋ช…์€ ์ฝœ๋กฌ๋น„์•„ ์—ญ์‚ฌํ•™์ž๋กœ ์•„๋ฒ„์ง€๋Š” ํ•œ๊ตญ์ „์— ์ฐธ์ „ํ•ด ์˜์›…์œผ๋กœ ์ฃฝ์€ ์ธ๋ฌผ์ด๋‹ค. ์—ญ์‚ฌํ•™์ž๊ฐ€ ํ•œ๊ตญ์— ์žˆ๋Š” ์•„๋ฒ„์ง€ ๋ฌด๋ค์„ ์ฒ˜์Œ ๋ฐฉ๋ฌธํ•˜๋Š” ๊ฒƒ์ด ์†Œ์„ค์˜ ๋ฐฐ๊ฒฝ์  ์ƒํ™ฉ์ด๋ฉฐ, ๋ชจ๋“  ํ™”์ž์˜ ๋ชฉ์†Œ๋ฆฌ๋Š” ๋ช…ํ™•ํžˆ ์–ธ๊ธ‰๋˜์–ด ์žˆ์ง€๋Š” ์•Š์ง€๋งŒ ๊ทธ์˜ ์—ฐ๊ตฌ๋ฅผ ํšŒ์ƒํ•œ ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค. ํ•œ๊ตญ์ „์Ÿ์— ๋Œ€ํ•œ ์ฝœ๋กฌ๋น„์•„ ๊ตญ๊ฐ€ ์ฐจ์›์˜ ๊ณต์‹ ๊ด€์ ๊ณผ๋Š” ๋‹ฌ๋ฆฌ ์ž‘ํ’ˆ์€ ์†Œ์„ค ์† ๊ตฐ์ธ๋“ค์˜ ์˜์›…์  ํ–‰์ ์— ๋Œ€ํ•ด ์ด์•ผ๊ธฐํ•˜์ง€ ์•Š์œผ๋ฉฐ, ์˜คํžˆ๋ ค ํ•œ๋ฐ˜๋„์˜ ๊ฒฝํ—˜์— ๋Œ€ํ•œ ์Œ์šธํ•˜๊ณ  ํ™˜๋ฉธ์ ์ธ ์‹œ๊ฐ์„ ๋ณด์—ฌ์ค€๋‹ค

    ์ „์‹ ์„ฑ ํ™๋ฐ˜์„ฑ ๋‚ญ์ฐฝ ํ™˜์ž์˜ ๊ณจ์ˆ˜ ๋‚ด ๋ฉด์—ญ์„ธํฌ ๋ฐ ์„ธํฌ ์ž์‚ด์— ๋Œ€ํ•œ ๋ถ„์„

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์˜ํ•™๊ณผ, 2014. 2. ์ด์€๋ด‰.Objectives: To examine the immune cell profile in the bone marrow (BM) of systemic lupus erythematosus (SLE) patients and to assess its clinical relevance. Methods: Sixteen BM samples from 14 SLE patients were compared with seven healthy control samples. The numbers of CD4+ T cells, CD8+ T cells, B cells, plasmacytoid dendritic cells (pDC), macrophages and plasma cells in the BM, and the levels of interleukin-6 (IL-6) expression, were examined by immunohistochemistry. The number of apoptotic cells (active caspase-3+) in the BM was also measured. The association between immune cell subsets and clinical features was also investigated. Results: CD4+ T cells, macrophages and plasma cells were more common in the BM of SLE patients than in healthy controls (1.82ยฑ1.45% vs. 0.26ยฑ0.12%, p=0.00116.35ยฑ7.17% vs. 8.04ยฑ1.38%, p=0.004and 9.72ยฑ5.64% vs. 3.44ยฑ0.64%, p<0.001, respectively). Greater numbers of CD4+ T cells and macrophages were associated with high-grade BM damage. The percentage of apoptotic cells in BM specimens from SLE patients was significantly higher than that in controls (2.47ยฑ1.35% vs. 0.19ยฑ0.22%, p<0.001) and was positively correlated with the number of pDCs (r=0.606, p=0.013). Increased numbers of plasma cells and high IL-6 expression were correlated with anti-double stranded DNA (dsDNA) antibody levels and the SLE disease activity index (r=0.538, p=0.031 and r=0.581, p=0.013, respectively). Conclusion: BM samples from SLE patients showed a distinct immune cell profile and increased numbers of apoptotic cells. This, coupled with a correlation with disease activity, suggest that the BM may play a critical role in the pathogenesis of SLE.CONTENTS Abstract โ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆi Contents โ€ฆii List of tables and figuresโ€ฆโ€ฆโ€ฆiii List of abbreviations โ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆiv Introduction 1 Patients and Methods 2 Results 5 Discussion 20 References 24 Abstract in Korean 30Maste

    How Large are Local Human Capital Spillovers?: Evidence from Korea

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    This paper examines the empirical magnitude of local human capital spillovers in Korea during the 1980s and mid-1990s. Local human capital spillovers exists if plants in regions with a higher level of human capital can produce more given their own amount of input (Moretti 2004c). In particular, this paper explores an educational reform in South Korea which exogenously induced a large amount of variation in regional human capital levels. Using annually collected plant level data, I explore the effect of changes in the regional human capital levels induced by this reform on plant productivity in Korea. My results suggest that this effect is limited. I find a positive correlation between a regional level of human capital and plant productivity. However, after further addressing endogeneity using an instrumental variable, the effect of the overall regional human capital level on productivity decreases and becomes statistically insignificant

    ๋น„ํŒ์  ์œ ํŠœ๋ธŒ ์ฝ๊ธฐ

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