• Title/Summary/Keyword: 지표 열

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Effect of Heat Stress of Extreme Heat Lever on Muscle functionand Muscle Injury Markers in Elderly Women (열 스트레스가 여성노인들의 근기능 및 근손상에 미치는 영향)

  • Park, Sok;Lee, Chone Ho;Back, Seung Ok;Shin, Yong Up;Kim, Jung Suk;Cho, Young Wung;Lee, Young Jun
    • 한국노년학
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    • v.30 no.3
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    • pp.793-802
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    • 2010
  • The purpose of this study was to examine the influence of extreme heat on muscle function and muscle injury marker in elderly women. The subjects of this study were eight post-menopausal elderly women without any metabolic disease. All eight subjects were asked to perform the knee joint isokinetic exercise using isokinetic equipment (cybex) in the laboratory and experimental temperature within laboratory was adjusted to two conditions: extreme heat temperature(33±0.5℃) and normal temperature(20±0.5℃) maintained in 50±3% humidity conditions. Each experimental exercise was monitored and analyzed the change of HSP70, LDH and CK. Muscular functions (peak torque, total work, percentage of peak torque body weight, fatigue index, average power and total work) were significant differences at exercise between temperatural conditions (p<.05). In extreme heat temperature, muscular injury markers (HSP70, LDH and CK) were increased, threfore resulted in significantly higher than normal temperature(p<.05). These results show that extreme heat temperature can decrease muscle function in elderly women.

Nonlinear Time Series Prediction Modeling by Weighted Average Defuzzification Based on NEWFM (NEWFM 기반 가중평균 역퍼지화에 의한 비선형 시계열 예측 모델링)

  • Chai, Soo-Han;Lim, Joon-Shik
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.4
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    • pp.563-568
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    • 2007
  • This paper presents a methodology for predicting nonlinear time series based on the neural network with weighted fuzzy membership functions (NEWFM). The degree of classification intensity is obtained by bounded sum of weighted fuzzy membership functions extracted by NEWFM, then weighted average defuzzification is used for predicting nonlinear time series. The experimental results demonstrate that NEWFM has the classification capability of 92.22% against the target class of GDP. The time series created by NEWFM model has a relatively close approximation to the GDP which is a typical business cycle indicator, and has been proved to be a useful indicator which has the turning point forecasting capability of average 12 months in the peak point and average 6 months in the trough point during 5th to 8th cyclical period. In addition, NEWFM measures the efficiency of the economic indexes by the feature selection and enables the users to forecast with reduced numbers of 7 among 10 leading indexes while improving the classification rate from 90% to 92.22%.

A Study on the Developing of Evaluation Indicators of Special Libraries (전문도서관 평가지표 개발에 관한 연구)

  • Park, Hee-Sook;Jeong, Dong-Youl
    • Journal of the Korean Society for Library and Information Science
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    • v.42 no.3
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    • pp.11-43
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    • 2008
  • The purpose of this study is to develop evaluation indicators for special libraries. Finally. overall nine evaluation areas including library management. human resources. information resources, finance resources. facility resources. information uses. information services. information sharing and library specialities and 70 evaluation indicators in consideration of the special libraries' characteristics and environments were developed based on the results of the survey of the experts and librarians of the special libraries and on the application of statistical analysis.

Measurement of 2D surface deformation on the Seguam volcano of Alaska using DInSAR Multi-track time-series techniques (DInSAR 멀티 트랙 시계열 기법을 이용한 알라스카 시구암 화산의 2차원 지표변위 관측)

  • Lee, Seul-Ki;Lee, Chang-Wook
    • Korean Journal of Remote Sensing
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    • v.30 no.6
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    • pp.719-730
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    • 2014
  • Small BAseline Subset (SBAS) technique using multi master interferograms can be effective to detect surface deformation in forest area. In this paper, The analysis reveals area of 2-dimension surface deformation at Seguam Island in Aleutian Arc., Alaska. We acquired ERS-1/2 data from track 201 and 473 datasets on Seguam Island from 1992 to 2008. This study analyze surface deformation applying Differential Interferometry Synthetic Aperture Radar (DInSAR) and SBAS time series method using two adjacent tracks. As a results, it was calculated that subsidence -1~2 cm in LOS direction and - 2~3 cm in vertical direction. The horizontal direction was repeated contraction and expansion. The observation of 2-dimension displacements explained the volcanic activity on Seguam island. Also, it is believed to be used for basic data to estimate movements of magma source.

Transition of Four Major Social Safety Indexes by Time Series Data Analysis (시계열 자료 분석을 통한 4대 사회안전지표 변화 추이)

  • Song, Chang Geun;Jang, Hyun-ju;Lee, Kum-Jin
    • Journal of the Society of Disaster Information
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    • v.11 no.4
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    • pp.634-638
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    • 2015
  • Four major social safety indexes including industrial accident, traffic accident, fire, and violent crime were selected, and transition of those values by time series data analysis since 2003 was presented. Comparing with the 2003 figure, the index of industrial accident was reduced by 27.8%, which was the most improved safety index. The indicators describing the traffic accident and violent crime rate were reduced by approximately 12%. However, the fire safety index showed an increase of 40% compared with the base year because national fire classification system was changed so that minor fire is also included in the counting since 2006.

A Fusion of the Period Characterized and Hierarchical Bayesian Techniques for Efficient Cluster Analysis of Time Series Data (시계열자료의 효율적 군집분석을 위한 구간특징화와 계층적 베이지안 기법의 융합)

  • Jung, Young-Ae;Jeon, Jin-Ho
    • Journal of Digital Convergence
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    • v.13 no.7
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    • pp.169-175
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    • 2015
  • An effective way to understand the dynamic and time series that follows the passage of time, as valuation is to establish a model to analyze the phenomena of the system. Model of the decision process is efficient clustering information of the total mass of the time series data of the relevant population been collected in a particular number of sub-groups than to look at all a time to an understand of the overall data through each community-specific model determination. In this study, a sub-grouping of the group and the first of the two process model of each cluster by determining, in the following in sub-population characterized by a fusion with heuristic Bayesian clustering techniques proposed a process which can reduce calculation time and cost was confirmed by experiments using actual effectiveness valuation.

Monitoring of Volcanic Activity of Augustine Volcano, Alaska Using TCPInSAR and SBAS Time-series Techniques for Measuring Surface Deformation (시계열 지표변위 관측기법(TCPInSAR와 SBAS)을 이용한 미국 알라스카 어거스틴 화산활동 감시)

  • Cho, Minji;Zhang, Lei;Lee, Chang-Wook
    • Korean Journal of Remote Sensing
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    • v.29 no.1
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    • pp.21-34
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    • 2013
  • Permanent Scatterer InSAR (PSInSAR) technique extracts permanent scatterers exhibiting high phase stability over the entire observation period and calculates precise time-series deformation at Permanent Scatterer (PS) points by using single master interferograms. This technique is not a good method to apply on nature environment such as forest area where permanent scatterers cannot be identified. Another muti-temporal Interferometric Synthetic Aperture Radar (InSAR), Small BAseline Subset (SBAS) technique using multi master interferograms with short baselines, can be effective to detect deformation in forest area. However, because of the error induced from phase unwrapping, the technique sometimes fails to estimate correct deformation from a stack of interferograms. To overcome those problems, we introduced new multi-temporal InSAR technique, called Temporarily Coherence Point InSAR (TCPInSAR), in this paper. This technique utilizes multi master interferograms with short baseline and without phase unwrapping. To compare with traditional multi-temporal InSAR techniques, we retrieved spatially changing deformation because PSs have been found enough in forest area with TCPInSAR technique and time-series deformation without phase unwrapping error. For this study, we acquired ERS-1 and ERS-2 SAR dataset on Augustine volcano, Alaska and detected deformation in study area for the period 1992-2005 with SBAS and TCPInSAR techniques.

Detecting Surface Changes Triggered by Recent Volcanic Activities at Kīlauea, Hawai'i, by using the SAR Interferometric Technique: Preliminary Report (SAR 간섭기법을 활용한 하와이 킬라우에아 화산의 2018 분화 활동 관측)

  • Jo, MinJeong;Osmanoglu, Batuhan;Jung, Hyung-Sup
    • Korean Journal of Remote Sensing
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    • v.34 no.6_4
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    • pp.1545-1553
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    • 2018
  • Recent eruptive activity at Kīlauea Volcano started on at the end of April in 2018 showed rapid ground deflation between May and June in 2018. On summit area Halema'uma'u lava lake continued to drop at high speed and Kīlauea's summit continued to deflate. GPS receivers and electronic tiltmeters detected the surface deformation greater than 2 meters. We explored the time-series surface deformation at Kīlauea Volcano, focusing on the early stage of eruptive activity, using multi-temporal COSMO-SkyMed SAR imagery. The observed maximum deformation in line-of-sight (LOS) direction was about -1.5 meter, and it indicates approximately -1.9 meter in subsiding direction by applying incidence angle. The results showed that summit began to deflate just after the event started and most of deformation occurred between early May and the end of June. Moreover, we confirmed that summit's deflation rarely happened since July 2018, which means volcanic activity entered a stable stage. The best-fit magma source model based on time-series surface deformation demonstrated that magma chambers were lying at depths between 2-3 km, and it showed a deepening trend in time. Along with the change of source depth, the center of each magma model moved toward the southwest according to the time. These results have a potential risk of including bias coming from single track observation. Therefore, to complement the initial results, we need to generate precise magma source model based on three-dimensional measurements in further research.

Comparison and Analysis of Lengths of Longest Common Subsequence and Maximal Common Subsequence (최장 공통 부분 서열과 극대 공통 부분 서열의 길이 비교 및 분석)

  • Lee, DongYeop;Na, Joong Chae
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.11a
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    • pp.15-18
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    • 2021
  • 최장 공통 부분 서열(Longest Common Subsequence, LCS)은 서열 유사도(Similarity)를 측정하기 위한 주요 지표 중 하나로 특별한 가정이 없는 한 두 문자열의 LCS 를 계산하기 위해서는 두 문자열의 길이의 곱에 비례하는 시간이 필요하다. 최근 최장(longest)이라는 조건을 극대(maximal)로 완화한 극대 공통 부분 서열(Maximal Common Subsequence, MCS)이 제시되었고, 두 문자열의 MCS 를 선형에 가까운 시간에 찾는 알고리즘이 개발되었다. 극대는 최장을 보장하지 않기 때문에 두 문자열의 MCS 길이는 LCS 길이와 달리 유일하지 않을 수 있고, LCS 길이가 매우 길어도 길이가 1인 MCS가 존재할 수도 있다. 본 논문에서는 기존 알고리즘에 의해 계산되는 MCS 의 효용성을 알아보기 위해, DNA 등 여러 종류의 실제 데이터와 랜덤 생성된 데이터에 대해 LCS 와 MCS 의 길이를 비교했다. MCS 길이는 LCS 길이 대비 실제 데이터에서 32.1 ~ 60.2%, 랜덤 데이터에서는 27.5 ~ 62.9%로 나타났다. 이 비율은 문자열을 이루고 있는 알파벳 수가 많을수록, 문자열의 길이가 길어질수록 감소했다.

Identification of Contaminated pixels in 10-day NDVI Image (정규식생지수(NDVI) 산출시 발생하는 노이즈 제거에 관한 연구)

  • Yeom Jong-Min;Han Kyung-Soo;Kim Young-Seup
    • Proceedings of the KSRS Conference
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    • 2006.03a
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    • pp.113-116
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    • 2006
  • 지표 변수는 지면 근처의 기후변화 및 상태를 파악하는데 중요한 역할을 하기 때문에, 충분히 높은 정확성을 가진 값이 산출되어야 한다. 하지만 이러한 지표 변수는 구름과 눈, 그리고 강수등에 의해서 그 값이 변화하게 된다. 이러한 오차 값을 줄이기 위해 구름제거, 지리보정, 대기보정 등의 위성 전처리 과정이 수행되었다. 하지만 위성 전처리 과정을 수행한 이후에도 정규식생지수 시계열 자료에는 여전히 노이즈가 남아 있기 때문에 이전에 연구에서는 이동 평균등과 같은 다양한 방법으로 노이즈를 제거하고자 하였다. 하지만 이동평균 방법은 참값에 가까운 최고값도 제거하기 때문에 문제점을 가지고 있다. 본 연구에서는 다중 다항회귀식을 이용하여 정규식생지수 시계열 자료 산출시 발생하는 노이즈를 제거 하였다.

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