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    B5G ์ดˆ๊ณ ๋ฐ€๋„ ๋„คํŠธ์›Œํฌ์—์„œ ์œ ์—ฐํ•œ ์ด๋™์„ฑ ๊ด€๋ฆฌ ๊ธฐ๋ฒ•

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ •๋ณด๊ณตํ•™๋ถ€, 2022. 8. ๋ฐ•์„ธ์›….์ฐจ์„ธ๋Œ€ ๋ชจ๋ฐ”์ผ ์ด๋™ํ†ต์‹ ์„ ์œ„ํ•œ ์ƒˆ๋กœ์šด ์„œ๋น„์Šค์™€ ์–ดํ”Œ๋ฆฌ์ผ€์ด์…˜์ด ๋“ฑ์žฅํ•จ์— ๋”ฐ๋ผ, ์‚ฌ์šฉ์ž๋“ค์€ ๊ธฐ์กด ์‹œ์Šคํ…œ ๋Œ€๋น„ ๋” ๋†’์€ ์ „์†ก ์†๋„๋ฅผ ์š”๊ตฌํ•œ๋‹ค. ๋”๋ถˆ์–ด ์‚ฌ์šฉ์ž๋“ค์€ ๋†’์€ ๋ฐ์ดํ„ฐ ์ „์†ก ์†๋„๋ฅผ ์•ˆ์ •์ ์œผ๋กœ ๋ณด์žฅ ๋ฐ›๊ธฐ๋ฅผ ์›ํ•œ๋‹ค. ๋ชจ๋ฐ”์ผ ๋„คํŠธ์›Œํฌ ์‚ฌ์šฉ์ž์˜ ๋ฐ์ดํ„ฐ ํŠธ๋ž˜ํ”ฝ์ด ์ฆ๊ฐ€ํ• ์ˆ˜๋ก ๋„คํŠธ์›Œํฌ์˜ ๋ฐ€์ง‘๋„๋ฅผ ์ฆ๊ฐ€์‹œํ‚ค๋Š” ์ดˆ๊ณ ๋ฐ€๋„ ๋„คํŠธ์›Œํฌ (ultra-dense network)์— ๋Œ€ํ•œ ๊ด€์‹ฌ์ด ๋†’์•„์ง€๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋Ÿฌํ•œ ์ดˆ๊ณ ๋ฐ€๋„ ๋„คํŠธ์›Œํฌ ํ™˜๊ฒฝ์—์„œ๋Š” ๊ธฐ์กด ๋„คํŠธ์›Œํฌ ๋Œ€๋น„ ํ•ธ๋“œ์˜ค๋ฒ„๊ฐ€ ์ž์ฃผ ๋ฐœ์ƒํ•˜๊ฒŒ ๋˜๊ณ , ์ด๋กœ ์ธํ•ด ๋„คํŠธ์›Œํฌ ์„ฑ๋Šฅ์ด ์ œํ•œ๋˜๋Š” ๋ฌธ์ œ๊ฐ€ ๋“œ๋Ÿฌ๋‚˜๊ณ  ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ์ดˆ๊ณ ๋ฐ€๋„ ๋„คํŠธ์›Œํฌ์˜ ์„ฑ๋Šฅ์„ ๊ทน๋Œ€ํ™”ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ํšจ์œจ์ ์ธ ์ด๋™์„ฑ ๊ด€๋ฆฌ์˜ ์ค‘์š”์„ฑ์ด ์–ด๋Š๋•Œ๋ณด๋‹ค ๋ถ€๊ฐ๋˜๊ณ  ์žˆ๋‹ค. ๋ณธ ํ•™์œ„๋…ผ๋ฌธ์—์„œ๋Š” ์ดˆ๊ณ ๋ฐ€๋„ ๋„คํŠธ์›Œํฌ ํ™˜๊ฒฝ์—์„œ ํšจ์œจ์ ์ธ ์ด๋™์„ฑ ๊ด€๋ฆฌ๋ฅผ ์œ„ํ•˜์—ฌ ๋‹ค์Œ์˜ ์„ธ ๊ฐ€์ง€ ์ „๋žต์„ ๊ณ ๋ คํ•œ๋‹ค. 1) MIAB (mobile integrated access and backhaul) ๋„คํŠธ์›Œํฌ์—์„œ์˜ ์ด๋™์„ฑ ๊ด€๋ฆฌ, 2) ๋”ฅ๋Ÿฌ๋‹ ๊ธฐ๋ฐ˜ ์žฅ์• ๋ฌผ ์˜ˆ์ธก์„ ํ†ตํ•œ ์‚ฌ์ „์ ์ธ ํ•ธ๋“œ์˜ค๋ฒ„, 3) ๋‹ค์ค‘ ์—ฐ๊ฒฐ ํ™˜๊ฒฝ์—์„œ์˜ ๊ฐ•์ธํ•œ ์ด๋™์„ฑ ๊ด€๋ฆฌ. ์ฒซ์งธ๋กœ, MIAB ๋„คํŠธ์›Œํฌ์—์„œ ์‚ฌ์šฉ์ž์˜ QoS (quality-of-service)์— ์‹ฌ๊ฐํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ํ•ธ๋“œ์˜ค๋ฒ„ ์ง€์—ฐ ์‹œ๊ฐ„์„ ๊ฐ์†Œ์‹œํ‚ค๊ธฐ ์œ„ํ•œ ํ•ธ๋“œ์˜ค๋ฒ„ ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. MIAB ๋„คํŠธ์›Œํฌ ํ™˜๊ฒฝ์—์„œ ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋Š” intra-gNB ํ•ธ๋“œ์˜ค๋ฒ„, inter-gNB ํ•ธ๋“œ์˜ค๋ฒ„, ๋ถ€๋ชจ MIAB ๋…ธ๋“œ ํ•ธ๋“œ์˜ค๋ฒ„์˜ ์„ธ ๊ฐ€์ง€ ํ•ธ๋“œ์˜ค๋ฒ„ ์ผ€์ด์Šค๋ฅผ ๋ถ„๋ฅ˜ํ•˜๊ณ , ๋ถ€๋ชจ MIAB ๋…ธ๋“œ์™€ ์ž๋…€ MIAB ๋…ธ๋“œ์˜ ์†๋„์— ๋”ฐ๋ฅธ ๊ฐ ํ•ธ๋“œ์˜ค๋ฒ„ ์ผ€์ด์Šค ๋ฐœ์ƒ ํ™•๋ฅ  ๋ชจ๋ธ์„ ์ œ์‹œํ•˜์˜€๋‹ค. ๋˜ํ•œ, ์ƒํ–ฅ๋งํฌ ์ปจํŠธ๋กค ํ”Œ๋ ˆ์ธ ๋ฐ์ดํ„ฐ ์ „์†ก ์ง€์—ฐ ์‹œ๊ฐ„์„ ๋ถ„์„ํ•˜์˜€๋‹ค. ์ œ์•ˆํ•˜๋Š” ํ•ธ๋“œ์˜ค๋ฒ„ ๊ธฐ๋ฒ•์€ ์ €์ง€์—ฐ ์ƒํ–ฅ๋งํฌ ์ปจํŠธ๋กค ํ”Œ๋ ˆ์ธ ๋ฐ์ดํ„ฐ ์ „์†ก ๊ธฐ๋ฒ•๊ณผ ์ž๋…€ MIAB ๋…ธ๋“œ์˜ RACH-less ํ•ธ๋“œ์˜ค๋ฒ„ ๊ธฐ๋ฒ•์„ ํฌํ•จํ•œ๋‹ค. ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•ด ์ œ์•ˆํ•˜๋Š” MIAB ํ•ธ๋“œ์˜ค๋ฒ„ ๊ธฐ๋ฒ•์ด ๊ธฐ์กด ํ•ธ๋“œ์˜ค๋ฒ„ ๊ธฐ๋ฒ• ๋Œ€๋น„ ํ•ธ๋“œ์˜ค๋ฒ„ ์ง€์—ฐ ์‹œ๊ฐ„ ๋ฐ ์˜ค๋ฒ„ํ—ค๋“œ ์„ฑ๋Šฅ๋ณด๋‹ค ๋งค์šฐ ๋›ฐ์–ด๋‚œ ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋‹ค์Œ์œผ๋กœ ์•ˆ์ •์ ์ธ ์ด๋™์„ฑ ๊ด€๋ฆฌ๋ฅผ ์œ„ํ•œ ์žฅ์• ๋ฌผ ์˜ˆ์ธก ๊ธฐ๋ฐ˜์˜ ์‚ฌ์ „ ํ•ธ๋“œ์˜ค๋ฒ„ (BAPH) ๊ธฐ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. BAPH๋Š” ๋”ฅ๋Ÿฌ๋‹ ๊ธฐ๋ฒ•์„ ํ™œ์šฉํ•˜์—ฌ ์žฅ์• ๋ฌผ๊ณผ ์ฐจ๋Ÿ‰์˜ ์ด๋™์„ฑ์„ ์˜ˆ์ธกํ•˜๊ณ , ํŠน์ • ์ฐจ๋Ÿ‰์ด ๊ธฐ์ง€๊ตญ๊ณผ LoS (line-of-sight)์— ์žˆ๋Š”์ง€๋ฅผ ์˜ˆ์ธกํ•œ๋‹ค. ์˜ˆ์ธก๋œ ์ฐจ๋Ÿ‰์˜ ๋ฏธ๋ž˜ ์œ„์น˜์™€ ์žฅ์• ๋ฌผ์˜ ๋ฏธ๋ž˜ ์œ„์น˜ ์ •๋ณด๋ฅผ ์ด์šฉํ•˜์—ฌ gNB์™€ RLF (radio link failure)๋ฅผ ๊ฒช๊ธฐ ์ด์ „ ์‹œ์ ์— ๋‹ค๋ฅธ gNB๋กœ ํ•ธ๋“œ์˜ค๋ฒ„๋ฅผ ์ˆ˜ํ–‰ํ•œ๋‹ค. ์ œ์•ˆํ•˜๋Š” ์‚ฌ์ „ ํ•ธ๋“œ์˜ค๋ฒ„ ๊ธฐ๋ฒ•์˜ ์„ฑ๋Šฅ์„ ๋‹ค์–‘ํ•œ ๋„๋กœ ํ™˜๊ฒฝ ๋ฐ ์ฐจ๋Ÿ‰ ์†๋„๋ฅผ ๋ฐ˜์˜ํ•œ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•ด ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ๋‹ค์ค‘ ์—ฐ๊ฒฐ ๋„คํŠธ์›Œํฌ์˜ ์žฅ์ ์„ ์ตœ๋Œ€๋กœ ๋Œ์–ด๋‚ด๊ธฐ ์œ„ํ•œ ์•ˆ์ •์ ์ธ ํ•ธ๋“œ์˜ค๋ฒ„ ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์•ต์ปค BS์™€ ์•กํ‹ฐ๋ธŒ BS ์ง‘ํ•ฉ์ด ๊ฐ ๋ชจ๋ฐ”์ผ ๊ธฐ๊ธฐ๋งˆ๋‹ค ์„ค์ •๋˜๋Š” ์‚ฌ์šฉ์ž ์ค‘์‹ฌ ์ดˆ๊ณ ๋ฐ€๋„ ๋„คํŠธ์›Œํฌ (UUDN)์„ ๊ณ ๋ คํ•œ๋‹ค. ์•ต์ปค BS๋Š” ์ฃผ๋ณ€ BS๋“ค์˜ RACH ์˜ค์ผ€์ŠคํŠธ๋ ˆ์ด์…˜์„ ํ†ตํ•˜์—ฌ ๋ชจ๋ฐ”์ผ ๊ธฐ๊ธฐ๊ฐ€ ํ•ธ๋“œ์˜ค๋ฒ„๋ฅผ ์œ„ํ•ด ์ „์†กํ•˜๋Š” RACH ํ”„๋ฆฌ์•ฐ๋ธ”์„ ๋‹ค์ˆ˜์˜ BS๊ฐ€ ๋ฐ›์„ ์ˆ˜ ์žˆ๋„๋ก ํ•œ๋‹ค. ๋˜ํ•œ ํ•ธ๋“œ์˜ค๋ฒ„ ๊ณผ์ •์—์„œ ํ•˜๋‚˜์˜ ์•กํ‹ฐ๋ธŒ BS์— RLF๊ฐ€ ๋ฐœ์ƒํ•˜๋Š” ๊ฒฝ์šฐ ํ•ธ๋“œ์˜ค๋ฒ„ ๊ณผ์ •์„ ์ง€์†ํ•˜์—ฌ ๋น ๋ฅด๊ฒŒ RLF๋ฅผ ๋ณต๊ตฌํ•˜๋Š” ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•ด ์ œ์•ˆํ•˜๋Š” ํ•ธ๋“œ์˜ค๋ฒ„ ๊ธฐ๋ฒ•์ด RLF ์ง€์† ์‹œ๊ฐ„์„ ํ˜„์žฌ ํ•ธ๋“œ์˜ค๋ฒ„ ๊ธฐ๋ฒ• ๋Œ€๋น„ ์ค„์ด๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€์œผ๋ฉฐ, ์—ฐ๊ฒฐ ์ˆ˜๊ฐ€ ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒฝ์šฐ์— RLF ์ง€์† ๊ธฐ๊ฐ„์„ ๋” ๊ฐ์†Œ์‹œํ‚ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์š”์•ฝํ•˜๋ฉด, ์ฐจ์„ธ๋Œ€ ๋ชจ๋ฐ”์ผ ๋„คํŠธ์›Œํฌ์—์„œ ์ด๋™์„ฑ ๊ด€๋ฆฌ์™€ ๊ด€๋ จ๋œ ์ƒˆ๋กœ์šด ๋„คํŠธ์›Œํฌ ๊ตฌ์กฐ ๋ฐ ํ”„๋กœํ† ์ฝœ์— ๋Œ€ํ•œ ๋ฌธ์ œ๋ฅผ ์ œ๊ธฐํ•œ๋‹ค. ํ˜„์žฌ ์ด๋™์„ฑ ๊ด€๋ฆฌ ๊ธฐ๋ฒ•์ด ๊ณ ์ด๋™์„ฑ ํ™˜๊ฒฝ์ด๋‚˜ ์ดˆ๊ณ ๋ฐ€๋„ ๋„คํŠธ์›Œํฌ ํ™˜๊ฒฝ์—์„œ ๋„คํŠธ์›Œํฌ์˜ ์„ฑ๋Šฅ์„ ์ €ํ•˜์‹œํ‚ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋”ฐ๋ผ์„œ ์ฐจ์„ธ๋Œ€ ๋ชจ๋ฐ”์ผ ๋„คํŠธ์›Œํฌ ์‹œ์Šคํ…œ์—์„œ์˜ ์ƒˆ๋กœ์šด ์ด๋™์„ฑ ๊ด€๋ฆฌ ๊ธฐ๋ฒ• ๋ฐ ์ „๋žต์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆํ•˜๋Š” ๋ชจ๋“  ์ด๋™์„ฑ ๊ด€๋ฆฌ ๊ธฐ๋ฒ•์€ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด ์„ฑ๋Šฅ์„ ํ‰๊ฐ€๋˜์—ˆ๋‹ค.As new services and applications for next-generation mobile communication emerge, users of mobile communication systems require a higher data rate than the existing system. In addition, mobile communication users want a high data rate to be reliably guaranteed anytime, anywhere. As data traffic of mobile network users increases, ultra-dense networks (UDN) that increase network density are in the limelight. However, in such a UDN environment, handovers (HOs) occur more frequently than in the existing mobile network system, which limits network performance. Therefore, to maximize the performance of the UDN, the importance of efficient mobility management is being emphasized more than ever. In this dissertation, the following three strategies are considered for efficient mobility management in the UDN environment: 1) Mobility management in mobile integrated access and backhaul (MIAB) networks, 2) Proactive HO through blockage prediction based on deep learning technology, 3) Reliable HO using the anchor node in the multi-connectivity environment. First, we propose a novel handover (HO) scheme for the MIAB network to reduce handover interruption time (HIT) and radio link failure (RLF) that have a significant impact on users' quality of service (QoS). We investigate HO cases that cover intra-gNB HO, inter-gNB HO, and parent MIAB node HO and develop their probabilistic models according to the velocities of the parent MIAB node and the child MIAB node. In addition, we investigate the latency in uplink (UL) control plane (CP) data transmission and each HO case for the baseline MIAB network. Our proposed HO scheme consists of low-latency UL CP data transmission with semi-persistent resource pre-allocation and RACH-less HO procedure for child MIAB nodes. Through simulation, we verify our proposed MIAB HO scheme outperforms the baseline HO scheme in terms of HO delay and HO overhead. Second, we propose the blockage-aware proactive HO (BAPH) scheme to support reliable mobility management. BAPH leverages a deep neural network (DNN) to predict the mobility of blockages and which BSs will be in the line-of-sight (LoS) with the vehicle device. With the predicted future blockage locations, the network supports proactive HO to the target gNB before radio link failure (RLF) occurs with the current serving gNB. We evaluate the performance of the proposed proactive HO scheme through simulations in various road environments. Finally, a reliable HO scheme that fully leverages the advantage of the multi-connectivity network is proposed. We consider a user-centric UDN (UUDN) architecture composed of an anchor BS and active BSs set for each UE. The anchor BS orchestrates the RACH of neighbor BSs that are not included in the active BS set for the target UE so that multiple target BSs can receive the RACH preamble transmitted by the UE. In addition, we propose a fast RLF recovery scheme that allows the existing HO process to continue when RLF occurs in the serving BS included in the active BS set. Through simulation, the performance of the proposed HO scheme is verified that the RLF duration of the UE is reduced compared to the current HO scheme even when the number of connections increases in a multi-connectivity environment. In summary, we claim issues in the new network architecture and protocols for the next-generation mobile networks related to mobility management. We demonstrate that the existing mobility management schemes limit the network performance in high-mobility environments and UDN environments. Therefore, we propose new mobility management schemes and strategies for the future mobile network system. All the proposed mobility management schemes are evaluated with simulation results.1 Introduction 1 1.1 Vision of B5G and Challenges 1 1.1.1 Vision of B5G Networks and Services 1 1.1.2 Research Trends and Challenges 2 1.2 Motivation 3 1.3 Main Contributions 5 1.3.1 Mobile Integrated Access and Backhaul Handover 5 1.3.2 Blockage Prediction-based Proactive Handover 6 1.3.3 Mobility Management in Distributed User-centric Ultra-dense Network 7 1.4 Organization of the Dissertation 7 2 Mobility Management of Multi-hop Mobile Integrated Access and Backhaul Network 9 2.1 Introduction 9 2.1.1 Contributions 11 2.1.2 Organization 12 2.2 Preliminary Study 12 2.2.1 IAB Network and Moving Cells 12 2.2.2 5G NR Handover 13 2.2.3 Motivation 14 2.3 System Model 15 2.3.1 Network Model 15 2.3.2 Communication Model 15 2.3.3 Directional Beamforming Model 16 2.3.4 Handover Model 18 2.4 Analysis of Mobility Management in MIAB Networks 18 2.4.1 UL CP Data Transmission Latency 19 2.4.2 Handover Latency 21 2.4.3 Handover Probability 23 2.5 Proposed Mobile IAB Handover Scheme 27 2.5.1 Low-Latency UL CP Data Transmission Scheme 27 2.5.2 Inter-gNB Handover Scheme 29 2.6 Performance Evaluation 31 2.6.1 HO Probability 33 2.6.2 Handover Latency 34 2.6.3 Effective Spectral Efficiency 37 2.7 Summary 41 3 Blockage-aware Proactive Handover for mmWave V2I Communications 42 3.1 Introduction 42 3.2 Preliminaries and Motivation 44 3.2.1 Effect of Blockages in mmWave Systems 44 3.2.2 DNN based Network Prediction 46 3.2.3 Motivation 46 3.3 Analysis on Blockage Effect 47 3.4 Proposed BAPH System 51 3.4.1 System Architecture 51 3.4.2 Communication Model 51 3.4.3 Deep Learning-based Location Prediction 52 3.4.4 Unobserved Blockage Detection and Estimation 54 3.4.5 Proactive Handover Process 57 3.6 Performance Evaluation 58 3.7 Summary 62 4 Anchor Node Based Reliable Handover in User-centric Ultra-dense Network 64 4.1 Introduction 64 4.2 Motivation 65 4.2.1 HO Process in 5G NR 65 4.2.2 HO Failure in the Baseline HO Scheme 66 4.3 Proposed Distributed User-centric Ultra-Dense Network Architecture 69 4.4 Anchor Node-based Mobility Management 71 4.5 Performance Evaluation 73 4.6 Summary 75 5 Concluding Remarks 76 5.1 Research Contributions 76 5.2 Future Research Directions 77 Abstract (In Korean) 85๋ฐ•

    Impact of Ocean Acidification on Oceanic Dimethysilfide Productionitle

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    A glimpse of the future ocean: mesocosm perturbation experiments

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    ์น˜์•„์šฐ์‹ํ™œ์„ฑ๊ตฐ๊ณผ ๋ฌด๊ฒฝํ—˜๊ตฐ์˜ ์„ธ๊ท ์ด์˜ ์„ฑ์ƒ์— ๊ด€ํ•œ ๋น„๊ต์—ฐ๊ตฌ

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    ์น˜์˜ํ•™๊ณผ/๋ฐ•์‚ฌ[์˜๋ฌธ] [ํ•œ๊ธ€] ์„œ์šธ ๋งˆํฌ๊ตฌ J๊ตญ๋ฏผํ•™๊ต์™€ ๊ฒฝ๊ธฐ๋„ ์šฉ์ธ๊ตฐ์˜ G๊ตญ๋ฏผํ•™๊ต ์•„๋™128๋ช…์„ ๋Œ€์ƒ์œผ๋กœ ํ•œ ์กฐ์‚ฌ์— ์„œ, ์น˜์•„์šฐ์‹ ํ™œ์„ฑ๊ตฐ๊ณผ ์น˜์•„์šฐ์‹ ๋ฌด๊ฒฝํ—˜ ๊ตฐ์œผ๋กœ ๋‚˜๋ˆ  dental plaque์— ์กด์žฌํ•˜๋Š” ์„ธ๊ท  ์ด ์ˆ˜ ๋ฐ ์œ ์‚ฐ์ƒ์„ฑ๊ท ์ˆ˜์™€ S. mutans์ˆ˜๋ฅผ ๋น„๊ต ๊ด€์ฐฐํ•œ ๊ฒฐ๊ณผ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ๊ฒฐ๋ก ์„ ์–ป์—ˆ๋‹ค. 1) ๋„์‹œ ๋ฐ ๋†์ดŒ์—์„œ ์„ธ๊ท  ์ด์ˆ˜๋Š” ๋ชจ๋‘ ใ‰ฎ ์น˜์•„์šฐ์‹ ํ™œ์„ฑ๊ตฐ์ด ๋ฌด๊ฒฝํ—˜ ๊ตฐ๋ณด๋‹ค ๋†’์€ ์ˆ˜์˜ ๊ท ์„ ๊ฐ€์ง€๊ณ  ์žˆ์—ˆ์œผ๋ฉฐ, ใ‰ฏ ํ˜ธ๊ธฐ์„ฑ ์„ธ๊ท ๋ณด๋‹ค ํ˜๊ธฐ์„ฑ ์„ธ๊ท ์ด ๋” ๋งŽ์ด ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. 2) ์œ ์‚ฐ์ƒ์„ฑ๊ท  ์ˆ˜์˜ ๋น„๊ต๋Š” ๋„์‹œ ๋ฐ ๋†์ดŒ์—์„œ ๋ชจ๋‘ ์น˜์•„์šฐ์‹ ํ™œ์„ฑ๊ตฐ์ด ๋ฌด๊ฒฝํ—˜ ๊ตฐ๋ณด๋‹ค ๋งŽ์€ ๊ท ์ˆ˜๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์—ˆ์œผ๋ฉฐ , ๋„์‹œ์˜ ๊ฒฝ์šฐ, ๋†’์€ ๊ท ์ˆ˜[10**7 ๊ท ์ˆ˜/plaque(g)]๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ์•„๋™์ด ์žˆ์—ˆ์œผ๋‚˜ ๋†์ดŒ์— ์„œ๋Š” ๊ทธ๋Ÿฐ ๊ฒฝ์šฐ๊ฐ€ ๊ด€์ฐฐ๋˜์ง€ ์•Š์•˜๋‹ค. 3) S.mutans๊ท  ์ˆ˜์˜ ๋น„๊ต๋Š” ๋„์‹œ ๋ฐ ๋†์ดŒ ๊ณตํžˆ ์น˜์•„์šฐ์‹ ํ™œ์„ฑ๊ตฐ์—์„œ ๋†’์€์ˆ˜์˜ S.mutans ๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ์•„๋™์ด ๋งŽ์•˜๋‹ค. THE STUDY ON THE BACTERIAL COUNTS OF DENTALPLAGUE OF CARIES FREE AND CARIES ACTIVE CHILDREN Kee Taek Lee, D.D.S., M.S.D. Dept. of Dental Science, Graduate School, Yonsei University (Directed by Professor Chung Suck Lee, D.D.S., Ph.D.) The counts of viable bacteria, lactic acid producing bacteria and S. mutans of dental plaque of the school children in urban and rural area were studied. The results were then comparatively analysed with their dental caries and residential ares. The findings, were summarized as follow; 1. Viable bacterial counts of dental plaque of the children in urban and rural area were. a. Higher in the children who had active caries. b. Frequency of the anaerobic bacteria were higher than aerobic bacteia. 2. The bacterial counts of lactic acid producers in caries active children were also higher than caries free children, in urban and rural area but the children who had higher lactic acid producer [10**7 bacterial counts/plaque (g)] was not found in rural area. 3. The bacterial counts of S.mutans were also found to be much higher in caries active children regadless their residency.restrictio

    Contribution of organic matter to the titration of alkalinity

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