47 research outputs found

    Geometric Structures on Points inside a Simple Polygon

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    Doctor๋‹ค๊ฐ ๊ณต๊ฐ„์—์„œ ๋‘ ์  ์‚ฌ์ด์˜ ๊ฑฐ๋ฆฌ๋Š” ๋‘ ์ ์„ ์—ฐ๊ฒฐํ•˜๋ฉฐ ๋‹ค๊ฐ ๊ณต๊ฐ„์˜ ๋‚ด๋ถ€์— ํฌํ•จ๋œ ๊ฐ€์žฅ ์งง์€ ๊ฒฝ๋กœ์˜ ๊ธธ์ด๋กœ ์ •์˜๋œ๋‹ค. ์œ ํด๋ฆฌ๋“œ ๊ณต๊ฐ„์—์„œ ์ •์˜๋œ ๊ธฐํ•˜ํ•™์  ๊ตฌ์กฐ๋“ค์€ ์ด ์ •์˜๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ๋‹ค๊ฐ ๊ณต๊ฐ„์œผ๋กœ ํ™•์žฅ๋œ๋‹ค. ๋ณธ ํ•™์œ„ ๋…ผ๋ฌธ์—์„œ๋Š” ๋ณด๋กœ๋…ธ์ด ๋‹ค์ด์–ด๊ทธ๋žจ (Voronoi diagram) ๊ณผ ์ปจ๋ฒก์Šค ํ— (Convex hull) ์„ ๋น„๋กฏํ•œ ๊ธฐ๋ณธ์ ์ธ ๊ธฐํ•˜ํ•™์  ๊ตฌ์กฐ๋ฅผ ๋‹ค๊ฐ ๊ณต๊ฐ„์—์„œ ๊ณ„์‚ฐํ•˜๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์‹œํ–ˆ๋‹ค. ์ฒซ์งธ, ์ตœ๊ทผ์ ‘์  ๋ณด๋กœ๋…ธ์ด ๋‹ค์ด์–ด๊ทธ๋žจ๊ณผ (Nearest-point Voronoi diagram) ์ตœ์žฅ ๋ณด๋กœ๋…ธ์ด ๋‹ค์ด์–ด๊ทธ๋žจ (Farthest-point Voronoi diagram)์„ ๊ตฌํ•˜๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ๊ฐœ์„ ๋œ ์ˆ˜ํ–‰์‹œ๊ฐ„์„ ์ œ์‹œํ–ˆ๋‹ค. ๋‹ค๊ฐ ๊ณต๊ฐ„์˜ ๋ณต์žก๋„๊ฐ€ mm ์ด๊ณ  ์ž…๋ ฅ ์ ์˜ ์ˆ˜๊ฐ€ nn ์ธ ๊ฒฝ์šฐ, ๊ธฐ์กด์— ์•Œ๋ ค์ง„ ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ O(nlogโกn+mlogโกm)O(n\log n+m\log m) ์˜ ์ˆ˜ํ–‰ ์‹œ๊ฐ„์„ ๊ฐ–๋Š”๋‹ค. ๊ธฐ์กด์— ์•Œ๋ ค์ง„ ์ˆ˜ํ–‰ ์‹œ๊ฐ„์˜ ํ•˜ํ•œ์€ ฮฉ(n+mlogโกm)\Omega(n+m\log m) ์ด๋ฏ€๋กœ ๋‘ ๋ณด๋กœ๋…ธ์ด ๋‹ค์ด์–ด๊ทธ๋žจ์„ ๊ตฌํ•˜๋Š” ์ตœ์  ์ˆ˜ํ–‰ ์‹œ๊ฐ„์— ๋Œ€ํ•œ ๊ฐ€์žฅ ์ž˜ ์•Œ๋ ค์ง„ ์ƒํ•œ๊ณผ ํ•˜ํ•œ ์‚ฌ์ด์—๋Š” ์ฐจ์ด๊ฐ€ ์กด์žฌํ•œ๋‹ค. ๋ณธ ํ•™์œ„ ๋…ผ๋ฌธ์—์„œ๋Š” ๊ธฐ์กด ์ˆ˜ํ–‰ ์‹œ๊ฐ„๋ณด๋‹ค ๊ฐœ์„ ๋œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์‹œํ•จ์œผ๋กœ์จ ์ƒํ•œ๊ณผ ํ•˜ํ•œ์˜ ์ฐจ์ด๋ฅผ ์ค„์˜€๋‹ค. ๋˜ํ•œ ์ œ์‹œ๋œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ m\leq n/\polylog n ์ธ ๊ฒฝ์šฐ ์ตœ์ ์ด๋ฉฐ ๊ธฐ์กด ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ mโ‰ฅnm\geq n ์ธ ๊ฒฝ์šฐ ์ตœ์ ์ด๋ผ๋Š” ์ ์„ ๋ณด์˜€๋‹ค. ๋”ฐ๋ผ์„œ n/\polylog n< m < n ์ธ ๊ฒฝ์šฐ๋ฅผ ์ œ์™ธํ•œ ๋ชจ๋“  ๊ตฌ๊ฐ„์—์„œ ์ตœ์  ์ˆ˜ํ–‰ ์‹œ๊ฐ„์ด ฮ˜(n+mlogโกm)\Theta(n+m\log m) ์ด๋ผ๋Š” ์ ์„ ์ฆ๋ช…ํ–ˆ๋‹ค. ๋‘˜์งธ, ๋™์  ๋‹ค๊ฐ ๊ณต๊ฐ„์—์„œ์˜ ์ปจ๋ฒก์Šค ํ— (Convex hull) ์„ ์œ ์ง€ํ•˜๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜๊ณผ ์œ„์น˜ ์ฐพ๊ธฐ ์งˆ์˜ (Point location query) ์— ๋‹ตํ•˜๋Š” ์ž๋ฃŒ ๊ตฌ์กฐ๋ฅผ ์ œ์‹œํ–ˆ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋Š” ์„ ๋ถ„์˜ ์ž…๋ ฅ๊ณผ ์ ์˜ ์‚ญ์ œ๋งŒ์„ ํ—ˆ์šฉํ•˜๋Š” ๋™์  ๋‹ค๊ฐ ๊ณต๊ฐ„์— ํ•œํ•˜์—ฌ ์ปจ๋ฒก์Šค ํ—์„ ์œ ์ง€ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋ณธ ํ•™์œ„ ๋…ผ๋ฌธ์—์„œ ์ œ์‹œ๋œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ์„ ๋ถ„์˜ ์‚ญ์ œ์™€ ์ ์˜ ์ž…๋ ฅ ๋ชจ๋‘๋ฅผ ํ—ˆ์šฉํ•˜๋Š” ๋™์  ๋‹ค๊ฐ ๊ณต๊ฐ„์—์„œ ์ปจ๋ฒก์Šค ํ—์„ ์œ ์ง€ํ•˜๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ตฌํ•˜๋Š” ์ตœ์ดˆ์˜ ๊ฒฐ๊ณผ์ด๋‹ค. ๋™์  ๊ณต๊ฐ„์—์„œ์˜ ์œ„์น˜ ์ฐพ๊ธฐ ์งˆ์˜ ๋ฌธ์ œ๋Š” ๋งŽ์ด ์—ฐ๊ตฌ ๋˜์—ˆ์ง€๋งŒ, ์ด๋“ค์€ ๋™์  ๊ณต๊ฐ„์ด ์—ฐ๊ฒฐ๋œ ๊ฒฝ์šฐ์—์„œ๋งŒ ๋™์ž‘ํ•œ๋‹ค. ์ผ๋ฐ˜์ ์ธ ๋™์  ๊ณต๊ฐ„์—์„œ ์œ„์น˜ ์ฐพ๊ธฐ ์งˆ์˜๋ฅผ ํ—ˆ์šฉํ•˜๋Š” ์ž๋ฃŒ ๊ตฌ์กฐ๋ฅผ ์ฐพ๋Š” ๋ฌธ์ œ๋Š” ์˜ค๋žœ ์‹œ๊ฐ„ ์ค‘์š”ํ•œ ๋ฌธ์ œ๋ผ๊ณ  ์–ธ๊ธ‰ ๋˜์—ˆ์ง€๋งŒ, ๊ฑฐ์˜ ์—ฐ๊ตฌ๊ฐ€ ๋˜์ง€ ์•Š์•˜๋‹ค. ๋ณธ ํ•™์œ„ ๋…ผ๋ฌธ์€ ์ด์— ๋Œ€ํ•œ ํšจ์œจ์ ์ธ ์ž๋ฃŒ ๊ตฌ์กฐ๋ฅผ ์ œ์‹œํ–ˆ๋‹ค.In this thesis, we consider a few fundamental geometric structures inside a simple polygon including Voronoi diagrams and convex hulls. Although the problems of computing several geometric structures in a simple polygon are well studied even as early as the 1980s, the optimal running times for computing Voronoi diagrams inside a simple polygon are not known. Also, the geometric structures in a simple polygon under dynamic settings have received less attention than the ones under the static setting. The first part of the thesis considers the geodesic nearest-point and geodesic farthest-point Voronoi diagrams inside a simple polygon. For the nearest-point and the farthest-point Voronoi diagrams, algorithms for computing them inside a simple polygon are given by Papadopoulou and Lee and Aronov et al, respectively. However, there are gaps between these running times and the best known lower bounds. In this thesis, we reduce these gaps by presenting faster algorithms for computing the nearest-point and farthest-point Voronoi diagrams. This is the first improvement on these problems since the early 1990s. The second part of the thesis considers geometric structures under dynamic settings. Previously, an algorithm for maintaining the geodesic convex hull was known only for a semi-dynamic setting. and it was open whether the geodesic convex hull can be maintained in the fully dynamic setting. We present the first nontrivial algorithm for maintaining the geodesic convex hull in the fully dynamic setting. Also, we consider the point location on dynamic general subdivisions which are not necessarily connected. Although there are several results on dynamic connected subdivisions, little is known for dynamic general subdivisions. Thus our result is the first nontrivial result on this problem

    An Analysis of the Current Status of Distance Education Provided by Virtual Universities and Suggestions for Improving Quality

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    โ… . ์„œ๋ก  โ…ก. ํ‰์ƒํ•™์Šต์ฒด์ œ์—์„œ์˜ ์›๊ฒฉ๋Œ€ํ•™์˜ ๊ธฐ๋Šฅ ๋ฐ ์ผ๋ฐ˜ ํ˜„ํ™ฉ 1. ์›๊ฒฉ๋Œ€ํ•™์˜ ๊ธฐ๋Šฅ 2. ์›๊ฒฉ๋Œ€ํ•™์˜ ์ผ๋ฐ˜ ํ˜„ํ™ฉ โ…ข. ์›๊ฒฉ๋Œ€ํ•™ ๊ต์œก์˜ ์‹คํƒœ 1. ์กฐ์‚ฌ ๊ฐœ์š” 2. ์‹คํƒœ ๋ถ„์„ โ…ฃ. ๋ฌธ์ œ์  ๋ฐ ๊ฐœ์„  ๋ฐฉ์•ˆ 1. ๋ฌธ์ œ์  2.๊ฐœ์„ ๋ฐฉ์•ˆ ์ฐธ๊ณ ๋ฌธํ—Œ AbstractThe purpose of this study is to explain the needs of distance education in the lifelong learning society, to analyze the current status of distance education of virtual universities through survey and to deduce the problems which virtual universities in Korea have. Finally, it provides recommendations on how to improve the quality of distance education provided by virtual university. A survey was performed through E-mail. A total 90 students enrolled in cyber universities in Seoul gave responded to the survey. The items of survey consist of personal characteristics of respondents and their perceptions of cyber education which they received. This paper suggests the following in order to improve the quality of cyber education: 1. The school board and educational administrators should come up with specific plans to encourage the participation of the people who are under financial difficulties. 2. The distance educators and educational administrators should develop a specialized curriculum for improving the studentโ€™s job skills. 3. The school board should secure teachers who are well organized and the better qualified as distance educators. 4. The distance educators should try to improve the quality of their instruction

    Womenโ€™s Vocational Training & Reentry to Job Market

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    ๋ณธ ์—ฐ๊ตฌ๋Š” ์—ฌ์„ฑ๊ฐ€์กฑ๋ถ€์˜ e-์ƒˆ์ผ์‹œ์Šคํ…œ ๊ตฌ์ง์ž ๋“ฑ๋ก์ •๋ณด ๋ฐ ์ง์—…ํ›ˆ๋ จ ์ •๋ณด์™€ ๊ณ ์šฉ๋ณดํ—˜ DB ์ทจ์—…์ž ์ •๋ณด๋ฅผ ํ™œ์šฉํ•˜์—ฌ, ๊ฒฝ๋ ฅ๋‹จ์ ˆ ์—ฌ์„ฑ๋“ค์˜ ๊ณ ์šฉ ์„ฑ๊ณผ๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ์ฝ•์ŠคํšŒ๊ท€๋ถ„์„ ๊ฒฐ๊ณผ, ๋‹จ์ˆœ ์ง์—… ์•Œ์„  ์„œ๋น„์Šค๋ฅผ ํ†ตํ•ด ์ทจ์—…ํ•œ ์—ฌ์„ฑ์— ๋น„ํ•ด, ์ถ”๊ฐ€์ ์œผ๋กœ ์ธํ„ด ์„œ๋น„์Šค๋ฅผ ๊ฒฝํ—˜ํ•  ๊ฒฝ์šฐ์—๋Š” ์‹ค์—… ์œ„ํ—˜๋ฅ ์ด 40%๊นŒ์ง€ ๋‚ฎ์•„์ง€๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋˜ํ•œ ๊ทผ๋กœ๊ธฐ๊ฐ„์ด ๊ธธ์–ด์ง์— ๋”ฐ๋ผ, ๊ฒฝ๋ ฅ์„ ์•ˆ์ •์ ์œผ๋กœ ์œ ์ง€ํ•  ํ™•๋ฅ ์€ 40๋Œ€ ์—ฌ์„ฑ์ธต์—์„œ๋Š” ์ข‹์€ ํŽธ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋‚˜, 50๋Œ€๋Š” ์˜คํžˆ๋ ค ๋ถˆ๋ฆฌํ•œ ๊ฒƒ์œผ๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค. ์—…์ข…๋ณ„๋กœ๋Š” ์ „ํ†ต์ ์œผ๋กœ ์—ฌ์„ฑ ์ทจ์—…๋น„์ค‘์ด ๊ฐ€์žฅ ๋†’์€ ์ œ์กฐ์—…์— ๋น„ํ•ด, ์‚ฌํšŒ์„œ๋น„์Šค์—…์œผ๋กœ ์ทจ์—…ํ• ์ˆ˜๋ก ์‹ค์—… ์œ„ํ—˜๋ฅ ์ด ์•ฝ 25% ์ด์ƒ ๋‚ฎ์•„์กŒ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด, ์ •๋ถ€์˜ ์ทจ์—…์ง€์›์„œ๋น„์Šค๊ฐ€ ์ง์—… ์•Œ์„  ๊ธฐ๋Šฅ๋งŒ ์ˆ˜ํ–‰ํ•˜๊ธฐ ๋ณด๋‹ค๋Š” ์ง์—…ํ›ˆ๋ จ์ด๋‚˜ ์ธํ„ด ๋“ฑ์˜ ๋ถ€๊ฐ€ ์„œ๋น„์Šค ๊ฒฐํ•ฉ์„ ๋Š˜๋ฆด์ˆ˜๋ก ๊ณ ์šฉ์œ ์ง€ ํšจ๊ณผ๋ฅผ ๋†’์ด๋Š” ๊ฒƒ์œผ๋กœ ํ™•์ธ๋˜์–ด, ์ฐจํ›„ ๋ณด๋‹ค ๋งŽ์€ ๊ตฌ์ง์—ฌ์„ฑ๋“ค์—๊ฒŒ ๋‹ค์–‘ํ•œ ์„œ๋น„์Šค๊ฐ€ ๊ฒฐํ•ฉ๋œ ํŒจํ‚ค์ง€ํ˜• ์ทจ์—…์ง€์›์„œ๋น„์Šค๋ฅผ ์ง€์›ํ•  ํ•„์š”๊ฐ€ ์žˆ์Œ์„ ์‹œ์‚ฌํ–ˆ๋‹ค.This research analyzes the result of vocational training for career-interrupted women based on the internal data on e-Saeil System released by the Ministry of Employment and Labor. Cox regression analysis reveals that women who have internship experience and are provided with employment insurance by their employers have 30-40% lower unemployment risk compared to those without. On the other hand, women who solely rely on vocational training have a 6% higher unemployment risk. The study confirms that vocational training alone has an apparent limitation in helping women over 50 years of age to stay employed, calling for further research on vocational training dedicated to women as well as a realignment of the general vocational training scheme
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