• Asian Pacific Journal of Cancer Prevention
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• 제16권14호
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• pp.5829-5834
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• 2015

Objective: To describe and analyze the epidemiological characteristics of lung cancer mortality in China from 1991 to 2013, forecast the future five-year trend and provide scientific evidence for prevention and management of lung cancer. Materials and Methods: Mortality data for lung cancer in China from 1991 to 2013 were used to describe epidemiological characteristics. Trend surface analysis was applied to analyze the geographical distribution of lung cancer. Four models, curve estimation, time series modeling, gray modeling (GM) and joinpoint regression, were performed to forecast the trend for the future. Results: Since 1991 the mortality rate of lung cancer increased yearly. The rate for males was higher than that for females and rates in urban areas were higher than in rural areas. In addition, our results showed that the trend will continue to increase in the ensuing 5 years. The mortality rate increased from age 45-50 and peaked in the group of 85 years old. Geographical analysis indicated that people living in northeast China provinces and the coastal provinces in eastern China had a higher mortality rate for lung cancer than those living in the centre or western Chinese provinces. Conclusions: The standardized mortality rate of lung cancer has constantly increased from 1991 to 2013, and been predicted to continue in the ensuing 5 years. Further efforts should be concentrated on education of the general public to increase prevention and early detection. Much better prevention and management is needed in high mortality areas (northeastern and eastern parts of China) and high risk populations (45-50-year-olds).

• 한국수자원학회논문집
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• 제48권6호
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• pp.479-489
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• 2015

본 연구에서는 도시하천 유역의 신뢰성 높은 수문해석을 위해 지역적 성향을 고려한 도달시간 및 저류상수 공식을 개발하였다. 이를 위해 국내 대표 도시하천 유역인 중랑천, 탄천, 안양천, 홍제천 내 13개 유역을 대상으로 지역적 성향이 없는 유역특성인자와 지역적 성향이 있는 도시 및 강우특성인자를 분석하였으며, 단계적 다중회귀분석을 통하여 공식을 개발하였다. 개발된 공식은 국내외 경험식들과 함께 도시하천 유역에 대해 정확도를 비교 평가하였다. 분석결과 본 연구에서 개발한 공식의 계산값이 다른 경험식들에 비해 더욱 정확하게 모의하였으며 오차합, 평균오차, 평균제곱근오차 또한 가장 낮은 것으로 나타났다. 본 연구는 도시하천 유역이라는 지역적 성향을 고려하여 공식을 개발함으로써 기존 국내외 경험식들보다 더 나은 결과를 제시하였다는 측면에서 가치가 있다고 판단된다.

• 중환자간호학회지
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• 제17권2호
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• pp.25-41
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• 2024

Purpose : This study aimed to investigate changes in critical nursing activities from 2009 to 2020 and explore the relationship between nurse staffing and such activities in intensive care units. Methods : A total of 446,445 adult patients admitted to intensive care units in tertiary and general hospitals from 2009 to 2020 were identified using the National Health Insurance claims database. The Critical Nursing Activities Index was calculated based on the following critical nursing activities: ventilator, extracorporeal membrane oxygenation (ECMO), and continuous renal replacement therapy (CRRT). Trend analysis was performed to analyze changes in critical nursing activities over 12 years and to assess linear trends across different staffing levels. Results : The annual utilization days for ventilators, ECMO, and CRRT, as well as the Critical Nursing Activities Index significantly increased over the study period (p-for-trend<.001) in tertiary and general hospitals, except for ventilator use in general hospitals. Ventilator, ECMO, and CRRT utilization exhibited a significant upward trend with higher nurse staffing levels (Bonferroni adjusted p-for-trend<.001). The Critical Nursing Activities Index was significantly higher in hospitals with higher staffing levels compared to those with lower staffing levels (Bonferroni adjusted p <.05). Conclusion : The findings underscore the need for improved nurse staffing levels in intensive care units. Government policies should ensure that staffing levels align with critical nursing activities among critically ill patients to uphold the quality of care.

• 대한공간정보학회지
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• 제20권1호
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• pp.93-99
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• 2012

본 연구는 행정중심복합도시 건설에 따라 이에 편입되는 지역과 그 주변지역을 포함한 공주시를 대상으로 지가의 시공간적 변화패턴을 파악하는데 목적이 있다. 이를 위해 2000년, 2005년, 2010년을 기준시점으로 209개의 동/리별 평균지가를 산출하여 GIS데이터를 구축하였다. 분석방법으로는 크게 3가지 측면으로 구분할 수 있다. 먼저 공간통계기법의 일종인 크리깅 보간에 의한 5년 단위의 지가변화 추이를 파악하였다. 둘째, 동서축과 남북축의 방향별 변화패턴을 알아보기 위해 경향분석(trend analysis)을 실시하였다. 셋째, 시점별 지가중심점의 이동 방향을 살펴보기 위해 지가를 가중치로 하여 가중평균중심점(weighted mean center)을 산출하였다. 그 결과 지목(Land Category)별 지가변화추세는 행정중심복합도시에 편입되는 동부지역에서 높은 성장세를 보이는 것으로 나타났고, 중심점의 이동방향 역시 동북부지역으로 편중되는 현상을 보였다.

• 대기
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• 제31권2호
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• pp.157-170
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• 2021

To investigate the effect of snowfall on the traffic of general roads in Gangwon-do, case analysis was performed in Gangneung, Pyeongchang, and Chuncheon using ASOS (Automated Synoptic Observing System) snowfall data and VDS (Vehicle Detector System) traffic data. First, we analyzed how much the traffic volume and speed decrease in snowfall cases on regional roads compared to non-snow cases, and the characteristics of monthly reduction due to snowfall were investigated. In addition, Pearson correlation analysis and regression analysis were performed to quantitatively grasp the effect of snowfall on traffic volume and speed, and sensitivity tests for snowfall intensity and cumulative snowfall were performed. The results showed that the amount of snowfall caused decrease both in the traffic volume and speed from usual (non-snowfall) condition. However, the trend was different by region: The decrease rate in traffic volume was in the order of Gangneung (17~22%), Chuncheon (14~17%), and Pyeongchang (11~14%). The decrease rate in traffic speed was in the order of Chuncheon (9~10%), Gangneung (8~9%), Pyeongchang (5~6%). No significant results were found in the monthly decrease rate analysis. In all regions, traffic volume and speed showed a negative correlation with snowfall. It was confirmed that the greater the amount of traffic entering the road, the greater the slope of the trend line indicating the change in snowfall due to the traffic volume. As a result of the sensitivity test for snowfall intensity and cumulative snowfall, the snowfall information at intervals of 6-hours was the most significant.

• 인간식물환경학회지
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• 제24권5호
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• pp.451-460
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• 2021

Background and objective: The prolonged COVID-19 pandemic has had significant impacts on mental health, which has emerged as a major public health issue around the world. This study aimed to analyze trends and network structure of 'grow-your-own (GYO)' through Instagram, one of the most influential social media platforms, to encourage and sustain home gardening activities for promotion of emotional support and physical health. Methods: A total of 6,388 posts including keyword hashtags '#gyo' and '#growyourown' on Instagram from June 13, 2020 to April 13, 2021 were collected. Word embedding was performed using Word2Vec library, and 7 clusters were identified with K-means clustering: GYO, garden and gardening, allotment, kitchen garden, sustainability, urban gardening, etc. Moreover, we conducted social network analysis to determine the centrality of related words and visualized the results using Gephi 0.9.2. Results: The analysis showed that various combinations of words, such as #growourrownfood, #growourrownveggies, and #growwhatyoueat revealed preference and interest of users in GYO, and appeared to encourage their activities on Instagram. In particular, #gardeningtips, #greenfingers, #goodlife, #gardeninglife, #gardensofinstagram were found to express positive emotions and pride as a gardener by sharing their daily gardening lives. Users were participating in urban gardening through #allotment, #raisedbeds, #kitchengarden and we could identify trends toward self-sufficiency and sustainable living. Conclusion: Based on these findings, it is expected that the trend data of GYO, which is a form of urban gardening, can be used as the basic data to establish urban gardening plans considering each characteristic, such as the emotions and identity of participants as well as their dispositions.

• 정보보호학회논문지
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• 제25권6호
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• pp.1399-1410
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• 2015

기업들은 다가오는 데이터 경쟁시대를 이해하고 이에 대비해야 한다며 가트너는 기업의 생존 패러다임에 많은 변화를 요구하고 있다. 또한 통계 알고리즘 기반의 예측분석을 통한 비즈니스 성공 사례들이 발표되면서, 과거 데이터 분석에 따른 사후 조치에서 예측 분석에 의한 선제적 대응으로의 전환은 앞서가고 있는 기업의 필수품이 되어 가고 있다. 이러한 경향은 보안 분석 및 로그 분석 분야에도 영향을 미치고 있으며, 실제로 빅데이터화되고 있는 대용량 로그에 대한 분석과 지능화, 장기화되고 있는 보안 분석에 빅데이터 분석 프레임워크를 활용하는 사례들이 속속 발표되고 있다. 그러나 빅데이터 로그 분석 시스템에 요구되는 모든 기능 및 기술들을 하둡 기반의 빅데이터 플랫폼에서 수용할 수 없는 문제점들이 있어서 독자적인 플랫폼 기반의 빅데이터 로그 분석 제품들이 여전히 시장에 공급되고 있다. 본 논문에서는 이러한 독자적인 빅데이터 로그 분석 시스템을 위한 실시간 및 비실시간 예측 분석 엔진을 탑재하여 사이버 공격에 선제적으로 대응할 수 있는 프레임워크를 제안하고자 한다.

• Advances in environmental research
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• 제6권4호
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• pp.265-279
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• 2017

The climate change has made adverse effects on land surface temperature for many regions of the world. Several climatic studies focused on different downscaling techniques for climatological parameters of different regions. For statistical downscaling of any hydrological parameters, conventional Neural Network Models were used in common. However, it seems that in any modeling study, uncertainty is a vital aspect when making any predictions about the performance. In this paper, Gamma Test is performed to determine the data length selection for training to minimize the uncertainty in model development. Another measure to improve the data quality and model development are wavelet transforms. Hence, Gamma Test with Wavelet decomposed Feedforward Neural Network (GT-WNN) model is developed and tested for downscaled land surface temperature of Patna Urban, Bihar. The results of GT-WNN model are compared with GT-FFNN and conventional Feedforward Neural Network (FFNN) model. The effectiveness of the developed models is illustrated by Root Mean Square Error and Coefficient of Correlation. Results showed that GT-WNN outperformed the GT-FFNN and conventional FFNN in downscaling the land surface temperature. The land surface temperature is forecasted for a period of 2015-2044 with GT-WNN model for Patna Urban in Bihar. In addition, the significance of the probable changes in the land surface temperature is also found through Mann-Kendall (M-K) Test for Summer, Winter, Monsoon and Post Monsoon seasons. Results showed an increasing surface temperature trend for summer and winter seasons and no significant trend for monsoon and post monsoon season over the study area for the period between 2015 and 2044. Overall, the M-K test analysis for the annual data shows an increasing trend in the land surface temperature of Patna Urban.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2017년도 춘계학술대회
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• pp.543-546
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• 2017

최근, 데이터 분석을 통해 새로운 이슈를 선제적으로 확인하고 이를 통해 기술 발전을 이끌어 내고 있다. 이러한 새로운 이슈에 대해서 미디어 보도가 결정적인 역할을 하며, 특히 과학 기술에 대한 사회적 인식 형성에 큰 영향을 끼치고 있다. 이에 따라 200여개의 뉴스 기사를 중심으로 키워드 분석과 감성 분석, 2가지 데이터 분석을 바탕으로 미래 정보통신의 주요 기술(Machine Learning & Blockchains)을 확인한다. 본 분석 결과를 바탕으로 향후 정보통신 주요 기술을 지속적으로 발전하는데 길잡이 역할을 할 것으로 예상한다.

• 한국농공학회논문집
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• 제54권5호
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• pp.141-153
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• 2012

In this study, we estimated probable precipitation amounts at the target year (2020, 2030, 2040) of 55 weather stations in Korea using the 24 hour annual maximum precipitation data from 1973 through 2009 which should be useful for management of agricultural reservoirs. Not only trend tests but also non-stationary tests were performed and non-stationary frequency analysis were conducted to all of 55 sites. Gumbel distribution was chosen and probability weighted moment method was used to estimate model parameters. The behavior of the mean of extreme precipitation data, scale parameter, and location parameter were analyzed. The probable precipitation amount at the target year was estimated by a non-stationary frequency analysis using the linear regression analysis for the mean of extreme precipitation data, scale parameter, and location parameter. Overall results demonstrated that the probable precipitation amounts using the non-stationary frequency analysis were overestimated. There were large increase of the probable precipitation amounts of middle part of Korea and decrease at several sites in Southern part. The non-stationary frequency analysis using a linear model should be applicable to relatively short projection periods.