• Title/Summary/Keyword: 적응과 완화

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Comparative Analysis on Climate Adaptation and Mitigation Plans of 8 Pilot Cities (국내 기후변화 시범도시의 완화와 적응계획 비교연구)

  • Choi, Joon-Sung
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.8
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    • pp.5664-5672
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    • 2015
  • The purpose of this paper is to draw main characteristics of local climate change plans of 8 pilot cities through a serious of comparative analyses. The results of the analyses on the mitigation plans and the adaptation plans are the followings; Firstly, climate change plans have two types of distinctive frameworks. Secondly, vision, objectives, and main strategies are composed of main key words. The key words of mitigation plans are low carbon, GHG, green city, energy, and green growth. Adaptation, ecosystem, healthy, safe, disaster, water are the key words that frequently shown in adaptation plan. Thirdly, the mitigation plans tend to place emphasis on transportation and common area. The adaptation plans tend to weigh on water control and forestry. The main characteristics of both mitigation plans and adaptation plans of 8 pilot cities are summarized and policy implications are suggested.

Palliative Radiotherapy (증상완화목적의 방사선치료)

  • Lee, Chang-Geol
    • Journal of Hospice and Palliative Care
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    • v.12 no.1
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    • pp.1-4
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    • 2009
  • The aim of palliative radiotherapy (RT) is to control cancer-related local symptoms with minimal radiation reaction. About one third of all radiation treatments are given with palliative intent. Indications for RT in symptom palliation are as follows: Pain from bone metastasis, pressure symptom from brain and spinal cord, obstruction of bronchus, esophagus, superior vena cava and malignant cancer bleeding from bronchus, urinary tract, uterine cervix and rectum. In hospice palliative care, RT is very effective for symptom palliation and improvement of quality of life without influence on survival.

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An Adaptive Gradient-Projection Image Restoration Using Local Constraints (국부 제약 정보를 이용한 Cradient-Projection 적응 영상 복원 기법)

  • 김지희;송원선;한헌수;홍민철
    • Proceedings of the IEEK Conference
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    • 2001.09a
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    • pp.649-652
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    • 2001
  • 본 논문에서는 공간 영역의 제약 정보를 이용한 적응 영상 복원 방식을 제안한다. 공간 영역의 제약 정보로는 국부 정보의 평균, 분산 및 최대 값을 이용하였다. 반복 기법을 이용하여 매 반복 해에서 얻어진 복원 영상으로부터 상기 제약 정보를 설정하게 되고, 위의 제약 정보는 임의의 입력 값에 의해 정의되는 매개 변수와 더불어 복원 영상의 국부 완화 정도를 결정하게 된다. 제안된 방식을 이용하여 복원 영상을 얻기 위해 비적응 복원 방식보다 빠른 수렴 속도를 갖게 됨을 알 수 있었다. 또한, 국부적으로 제어된 완화 정도를 지닌 복원 영상을 얻을 수 있었다.

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An Adaptive Image Restoration Algorithm Using Local Constraints (공간 제약 정보를 이용한 적응 영상 복원 기법)

  • 송원선;김지희;홍민철
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2001.11b
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    • pp.139-142
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    • 2001
  • 본 논문에서는 공간 영역의 제약 정보를 이용한 적응 영상 복원 방식을 제안한다. 공간 영역의 제약 정보로는 국부 정보의 평균, 분산 및 최대 값을 이용하였다 반복 기법을 이용하여 매 반복 해에서 얻어진 복원 영상으로부터 상기 제약 정보를 설정하게 되고, 위의 제약 정보는 임의의 입력 값에 의해 정의되는 매개 변수와 더불어 복원 영상의 국부 완화 정도를 결정하게 된다. 제안된 방식을 이용하여 복원 영상을 얻기 위해 비적응 복원 방식보다 빠른 수렴 속도를 갖게 됨을 알 수 있었다. 또한, 국부적으로 제어된 완화 정도를 지닌 복원 영상을 얻을 수 있었다.

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Green Infrastructure Types and Effects for Climate Change (기후변화 대응을 위한 녹색기반시설의 유형과 효과)

  • Kim, Seung Hyun
    • Journal of Climate Change Research
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    • v.2 no.3
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    • pp.191-201
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    • 2011
  • This study investigates how green infrastructure, including natural and open space such as forests, rivers, parks, and streets, could effectively counteract climate change in terms of mitigation and adaption, respectively. As a result, green infrastructure, such as forests, parks, vegetable gardens, roof gardens, pedestrian walkways, bike lanes, etc, could effectively mitigate climate change: 1) Carbon storage and sequestration; 2) Fossil fuel substitution; 3) Material substitution; 4) Food production 5) Reducing the need to travel by car. Secondly, green infrastructure, such as rivers, tree-lined streets, farmland, wetlands, dunes, wind ways, etc, could adapt to climate change: 1) Managing high temperatures; 2) Managing water supply; 3) Managing ravine flooding; 4) Managing costal flooding; 5) Managing surface water; 6) Reducing soil erosion; 7) Helping other species to adapt.

A Study on Eliminating the Error-Smoothing Filter from HARF Algorithm (HARF 알고리즘에서의 오차 완화 필터 제법에 관한 연구)

  • 신윤기;이종각
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.20 no.4
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    • pp.1-9
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    • 1983
  • In designing the adaptive recursive filter using the MRAS hyperstable output-error identifier, the most crucial point is the design of the error-smoothing filter In this paper, it is shown that by modifyins the HARF algorithm properly, we can obtain an algorithm which requires no error-smoothing filter and has relatively high convergence rate.

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An Adaptive Gradient-Projection Image Restoration using Spatial Local Constraints and Estimated Noise (국부 공간 제약 정보 및 예측 노이즈 특성을 이용한 적응 Gradient-Projection 영상 복원 방식)

  • Hong, Min-Cheol
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.10C
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    • pp.975-981
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    • 2007
  • In this paper, we propose a spatially adaptive image restoration algorithm using local and statistics and estimated noise. The ratio of local mean, variance, and maximum values with different window size is used to constrain the solution space, and these parameters are computed at each iteration step using partially restored image. In addition, the additive noise estimated from partially restored image and the local constraints are used to determine a parameter for controlling the degree of local smoothness on the solution. The resulting iterative algorithm exhibits increased convergence speed when compared to the non-adaptive algorithm. In addition, a smooth solution with a controlled degree of smoothness is obtained without a prior knowledge about the noise. Experimental results demonstrate that the proposed algorithm requires the similar iteration number to converge, but there is the improvement of SNR more than 0.2 dB comparing to the previous approach.

An Adaptive Gradient-Projection Image Restoration Algorithm with Spatial Local Constraints (공간 영역 제약 정보를 이용한 적응 Gradient-Projection 영상 복원 방식)

  • 송원선;홍민철
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.3C
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    • pp.232-238
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    • 2003
  • In this paper, we propose a spatially adaptive image restoration algorithm using local statistics. The local mean, variance, and maximum values are utilized to constrain the solution space, and these parameters are computed at each iteration step using partially restored image. A parameter defined by the user determines the degree of local smoothness imposed on the solution. The resulting iterative algorithm exhibits increased convergence speed when compared to the non-adaptive algorithm. In addition, a smooth solution with a controlled degree of smoothness is obtained. Experimental results demonstrate the capability of the proposed algorithm.

Palliative Sedation for Terminal Cancer Patient (말기 암 환자에서 완화적 진정 증례 토론)

  • Kim, Do-Yeun
    • Journal of Hospice and Palliative Care
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    • v.11 no.2
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    • pp.106-110
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    • 2008
  • Palliative sedation has been used in patients who undergo intractable suffering at the end of life. Its implementation, however, may be complicated due to resistance of clinicians and barrier of bioethical issues. Here, we present 50-year-old man with stomach cancer and multiple bone metastasis who was treated with palliative chemotherapy and radiotherapy. He suffered from refractory pain on the whole body even after standard analgesics and multidisplinary effort to relieve. Upon shared decision for sedation, he was given midazolam until discharge. Literature reviews reveal cases similar to the present case.

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MRF-based Adaptive Noise Detection Algorithm for Image Restoration (영상 복원을 위한 MRF 기반 적응적 노이즈 탐지 알고리즘)

  • Nguyen, Tuan-Anh;Hong, Min-Cheol
    • Journal of Korea Multimedia Society
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    • v.16 no.12
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    • pp.1368-1375
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    • 2013
  • In this paper, we presents a spatially adaptive noise detection and removal algorithm. Under the assumption that an observed image and the additive noise have Gaussian distribution, the noise parameters are estimated with local statistics, and the parameters are used to define the constraints on the noise detection process, where the first order Markov Random Field (MRF) is used. In addition, an adaptive low-pass filter having a variable window sizes defined by the constraints on noise detection is used to control the degree of smoothness of the reconstructed image. Experimental results demonstrate the capability of the proposed algorithm.