본 연구는 산림자원으로 활용 가능한 활엽수림(혼효림 포함)의 상층 교목성 수종을 대상으로 유사한 수종구성을 갖는 산림 유형 분류를 통해 활엽수림의 효율적 산림관리 기반 구축을 위해 실시하였다. 제7차 국가산림자원조사 고정표본점(3,994지점) 중 2,291지점의 임분 현황 자료를 기반으로 클러스터분석, 지표종분석, 다중판별분석 등 다양한 다변량 통계분석 기법을 이용하여 산림 유형을 분류하였다. 활엽수림의 산림 유형은 신갈나무-피나무림, 신갈나무-당단풍나무림, 신갈나무-물푸레나무림, 신갈나무-굴참나무림, 신갈나무-소나무림, 졸참나무-굴참나무림, 소나무-신갈나 무림, 소나무-굴참나무림, 밤나무-아까시나무림, 상수리나무-소나무림 등 10개로 구분되었다. 신갈나무와 기타 활엽수림, 신갈나무가 우점하는 참나무 림, 주요 참나무류 수종과 소나무의 혼효림 형태로 구성된 것으로 파악되었다. 조사된 102종의 수종 중 점유비율이 높은 신갈나무, 굴참나무 및 소나무가 산림유형 분류에 중요한 역할을 한 것으로 나타났다.

Most of the drinking water dams managed by the local governments in Korea are earthfill dams, and these dams have almost no geotechnical property information necessary for seismic performance evaluation. Nevertheless, in the rough planning stage for improving seismic safety for these dams, it is necessary to classify their relative seismic hazard against earthquakes and conduct an additional ground investigation. The zero seismic failure probability curve is a curve suggested in this study in which the probability of failure due to an earthquake becomes ‘0’ regardless of the geotechnical properties of the earthfill dam. By examining the method and procedure for calculating failure probability due to an earthquake suggested in previous researches, the zero seismic failure probability curves for an earthquake in 1,000-year and 2,400-year return periods in Korea were presented in the form of a hyperbola on the plane of the dam height versus freeboard ratio (ratio of freeboard to dam height), respectively. The distribution characteristics of the dam height and the freeboard ratio of 81 Korean earthfill dams were presented. The two proposed zero seismic failure probability curves are shown on the plane of the dam height versus freeboard ratio, and the relative seismic hazard of 81 dams can be classified into three groups using these curves as boundaries. This study presented the method of classifying the relative seismic hazard and the classification result.

In this study, we perform a statistical investigation of the kinematic classification of 4,264 coronal mass ejections (CMEs) from 1996 to 2015 observed by SOHO/LASCO C3. Using the constant acceleration model, we classify these CMEs into three groups: deceleration, constant velocity, and acceleration motion. For this, we devise three different classification methods using fractional speed variation, height contribution, and visual inspection. The main results of this study can be summarized as follows. First, the fractions of three groups depend on the method used. Second, about half of the events belong to the groups of acceleration and deceleration. Third, the fractions of three motion groups as a function of CME speed are consistent with one another. Fourth, the fraction of acceleration motion decreases as CME speed increases, while the fractions of other motions increase with speed. In addition, the acceleration motions are dominant in low speed CMEs whereas the constant velocity motions are dominant in high speed CMEs.

멤브레인은 분리 기술 및 다양한 사용처에 따라서 유기물, 액체, 용질, 증기, 기체, 이온 또는 전자 등 다양한 물질 을 선택적으로 분리할 수 있다. 멤브레인은 크게 대칭막과 비대칭막으로 나누며, 기공의 유무에 따라 다공성과 비다공성으로 분류된다. 또한 멤브레인의 계면은 분자적으로 균일하거나, 또는 화학적으로 또는 물리적으로 불균일할 수 있다. 제조기술로 는 용융 압출 제조법, 연신법, 템플레이트 침출법, 트랙-에치법, 용액 캐스팅법, 상전이법 및 용액 코팅법 등이 있다. 제조된 멤브레인은 정밀여과, 한외여과, 나노여과, 역삼투, 기체분리 및 에너지 분야와 같은 다양한 응용 분야에 적용될 수 있다. 본 총설에서는 멤브레인의 분류 및 종류에 따른 제조 방법에 대한 튜토리얼을 제공한다.

Understanding the characteristics of reservoir water quality is fundamental in reservoir ecosystem management. The water quality of reservoirs is affected by various factors including hydro-morphology of reservoirs, land use/cover, and human activities in their catchments. In this study, we classified 83 major reservoirs in South Korea based on nine physicochemical factors (pH, dissolved oxygen, chemical oxygen demand, total suspended solid, total nitrogen, total phosphorus, total organic carbon, electric conductivity, and chlorophyll-a) measured for five years (2015~2019). Study reservoirs were classified into five main clusters through hierarchical cluster analysis. Each cluster reflected differences in the water quality of reservoirs as well as hydromorphological variables such as elevation, catchment area, full water level, and full storage. In particular, water quality condition was low at a low elevation with large reservoirs representing cluster I. In the comparison of eutrophication status in major reservoirs in South Korea using the Korean trophic state index, in some reservoirs including cluster IV composed of lagoons, the eutrophication was improved compared to 2004~2008. However, eutrophication status has been more impaired in most agricultural reservoirs in clusters I, III, and V than past. Therefore, more attention is needed to improve the water quality of these reservoirs.

The water consumption data of individual consumers must be analyzed and forecast to establish an effective water demand management plan. A k-mean cluster model that can monitor water use characteristics based on hourly water consumption data measured using automated meter reading devices and demographic factors is developed in this study. In addition, the quantification model that can estimate the daily water consumption is developed. K-mean cluster analysis based on the four clusters shows that the average silhouette coefficient is 0.63, also the silhouette coefficients of each cluster exceed 0.60, thereby verifying the high reliability of the cluster analysis. Furthermore, the clusters are clearly classified based on water usage and water usage patterns. The correlation coefficients of four quantification models for estimating water consumption exceed 0.74, confirming that the models can accurately simulate the investigated demographic data. The statistical significance of the models is considered reasonable, hence, they are applicable to the actual field. Because the use of automated smart water meters has become increasingly popular in recent year, water consumption has been metered remotely in many areas. The proposed methodology and the results obtained in this study are expected to facilitate improvements in the usability of smart water meters in the future.

본 연구는 다양한 결실기로 육성한 산초나무 5개의 신품종(한초 915호, 한초 930호, 한초 10호, 한초 1020호, 한초 1030호)에 대해 잎과 가시의 형태적 특성을 조사하여 비교하였다. 조사는 질적 특성과 양적 특성으로 구분하여 실시하였으며, 양적 특성은 일원배치 분산분석(One-Way ANOVA)과 Scheffe의 다중검증(Scheffe's multiple range test)으로 품종 간 차이를 확인하였다. 또한 요인분석을 이용하여 조사한 특성의 기여도를 확인하였다. 그 결과 잎 길이에서는 유의한 차이를 확인하지 못했으나, 정소엽의 거치 수, 소엽의 수, 가시의 크기에서 품종 간 유의한 차이가 있었으며, 요인분석도 유사한 결과를 확인 하였다. 또한 비가중평균결합(Unweighted pair-group method using arithmetic averages) 군집분석을 수지도(dendrogram)로 확인한 결과, 한초 1020호와 1030호가 근접하고, 한초 915호와 930호가 근접하였으나 개화기와 결실기에서 뚜렷한 차이로 품종이 구분되는 것을 확인할 수 있었다.

This study is about the production of radiation sources of simulated concrete and soil reference materials to verify the validity of the quality establishment and measurement of the detector (HPGe) of the radioactive soil and concrete waste classification system, which is being developed to quickly and accurately classify nuclear decommissioning waste. Specific activity of gamma nucleus among radioactive wastes is evaluated using gamma spectroscopy. At this time, in order to verify the validity and reliability of measuring equipment, it shall be a standardized substance of the same medium as nuclear decommissioning waste (chemical ingredients, particles, density, etc.) in order to correct the energy and efficiency of gamma nuclide analysis equipment. The CRM used for the detector’s energy correction used a 1 L Marinelli beaker standard correctional radiation source consisting of 10 radioactive isotopes. In order to correct efficiency, in accordance with the production and certification process of the Korea Standards and Research Institute, it has produced artificial simulated radioactive concrete similar to nuclear decommissioning waste (30% for cement, 60% for regulation and 10% for bentonite). The radioactive homogeneity of the simulated concrete reference materials was evaluated using dispersion analysis (ANOVA) in accordance with ISO Guide 35, while 137Cs and 60Co of concrete reference materials were able to obtain homogeneous measurements both in and between bottles. The self-absorption rate of the simulated concrete reference material was determined by the MCNP computer simulation measurement method, and the self-absorption correction coefficients of 137Cs and 60Co were assessed at 0.995 and 0.996, respectively, and the standard value for the radiation of the simulated concrete reference material was calculated on the weighted average of the measurements of 20 samples. The uncertainty about the reference value was calculated by combining measurement uncertainty (Type B evaluation), bottle to bottle standard deviation, and uncertainty within bottle by modifying the formula suggested in ISO Guide 35. The concentration of 137Cs and 60Co of reference materials was divided into high-speed measurement mode and precision measurement mode in consideration of the self-disposal standard. The reference value and uncertainty of expansion among reference materials for high-speed measurement mode were rated at 1,032.7 ± 64.0 Bq·kg−1and 1,083.7 Bq·kg−1, respectively. The standard value and expansion uncertainty for 137Cs and 60Co among reference materials for precision measurement mode were rated at 113.7 ± 10.0 Bq·kg−1 and 122.3 ± 10.3 Bq·kg−1, respectively.

Comprehensive identification and systematic classification of all features, events and processes (FEP) that influence on the performance of a high-level radioactive waste disposal system is essential for safety assessment. Nuclear energy agency (NEA) has been developing and updating the standardized generic FEP list, so-called NEA international FEP list, which may be used as the basis to develop project-specific FEP lists to reflect diverse system and site characteristics in different countries. On the basis, Finland and Sweden have recently got licenses to construct spent nuclear fuel deep disposal facilities. Also in Korea, timely construction of a high-level radioactive waste disposal facility is an urgent issue for stable operation of nuclear power plants. For this end, a FEP list that properly considers for system and site characteristics of Korean high-level radioactive waste disposal facility needs to be developed. In this study, the most recent NEA international FEP list published in 2019 was comprehensively reviewed with focus on the structure of the classification system and the physicochemical mechanisms associated with the key elements. The obtained results will be used for the comparative analysis of domestic and oversea project-specific FEP lists and for the development of a generic FEP list relevant to Korean high-level radioactive waste disposal system.

Along with the current rapid development of technology, object classification is being researched, developed, and applied to security systems, autonomous driving, and other applications. A common technique is to use vision cameras to collect data of objects in the surrounding environment. Along with many other methods, LiDAR sensors are being used to collect data in space to detect and classify objects. By using the LiDAR sensors, some disadvantages of image sensors with the negative influence on the image quality by weather and light condition will be covered. In this study, a volumetric image descriptor in 3D shape is developed to handle 3D object data in the urban environment obtained from LiDAR sensors, and convert it into image data before using deep learning algorithms in the process of object classification. The study showed the potential possibility of the proposal and its further application.

골목상권은 상권 경쟁력 확보와 상권 내 점포의 안정적 운영 측면에서 중요한 공간적 영역으로 인식되어 왔고, 코로나 이후 상권 측면에서도 골목상권은 중요한 연구 대상으로 제기되고 있다. 지금까지 골목상권 연구는 서울시와 같은 대도시 골목상권 을 중심으로 진행되어 왔다. 이에 본 연구는 청주시를 사례로 소상공인 개별 데이터와 GIS 기법을 활용하여 중소도시에 적합한 골목상권 영역 설정 방법을 제안하고, 이를 토대로 골목상권 유형을 분류하고 주요 특성을 살펴보고자 하였다. 골목상권 영역 설정은 데이터 전처리 과정을 거쳐, 생활밀착형 업종 점포를 추출하고 도로명주소 내 ‘길’ 단위 점포를 추출하여 골목상권 영역을 설정하였다. 골목상권 유형은 개폐업률에 의해 성장형-순환형-정체형-쇠퇴형으로 분류하고, 네 유형의 골목상권 분포를 지도화하 고 상권별 주요 특성을 살펴보았다. 본 연구에서 제안한 골목상권 영역 설정 방법과 유형 분류는 앞으로 세밀한 골목상권의 이해와 공간 단위에서의 골목상권 변화에 활용되기를 기대한다. 또한 본 연구의 성과는 상권의 이해와 변화 예측을 넘어 골목상권 활성화를 위한 정책 수립의 출발점이 될 수 있다.

The rapid development of computer vision and deep learning has enabled these technologies to be applied to the automated classification and counting of microscope images, thereby relieving of some burden from pathologists in terms of performing tedious microscopic examination for analysis of a large number of slides for pathological lesions. Recently, the use of these digital methods has expanded into the field of medical image analysis. In this study, the Inception-v3 deep learning model was used for classification of chondrocytes from knee joints of rats. Knee joints were extracted, fixed in neutral buffered formalin, decalcified, processed and embedded in paraffin, and hematoxylin and eosin (H&E) stained. The H&E stained slides were converted into whole slide imaging (WSI), and the images were cropped to 79 × 79 pixels. The images were divided into training (60.42%) and test (39.58%) sets (46,349 and 30,360 images, respectively). Then, images containing chondrocytes were classified by Inception-v3 and accuracy was calculated. We visualized the images containing chondrocytes in WSIs by adding colored dots to patches. When images of chondrocytes in knee joints were evaluated, the accuracy was within the range of 91.20 ± 8.43%. Therefore, it is considered that the Inception-v3 deep learning model was able to distinguish chondrocytes from non-chondrocytes in knee joints of rats with a relatively high accuracy. The above results taken together confirmed that this deep learning model could classify the chondrocytes and this promising approach will provide pathologists a fast and accurate analysis of diverse tissue structures.

곤충은 주변환경에 적응하며 발육과 번식을 통해 진화하여 왔다. 온도발육모형을 이용하여 곤충과 응애 분류군별 공통고유최적온도, 발육 최적온도, 산란최적온도를 산출하기 위해 112편의 논문에서 응애류 14종, 딱정벌레목 8종, 파리목 5종, 노린재목 31종, 벌목 7종, 나비목 18종, 메뚜기목 1목, 다듬이벌레목 5종, 총채벌레목 5종의 온도발육과 산란자료를 분석하였다. 분석을 통하여 총채벌레목을 제외하고 공통고유최적온 도는 발육최적온도보다는 산란최적온도와 차이가 적었다. 본 종설을 통해 공통고유최적온도는 발육최적온도보다는 산란최적온도와 밀접한 관계 가 있을 가능성이 높음을 제안하였다.

본 연구는 치유농업 산업의 분류체계 구축을 통해 치유농업 산업의 범위에 근거한 현황을 분석하여 향후 치유농업 정책수립에 활용하고자 수행하였다. 분류체계는 한국표준산업분류체계를 기반으로 하였으며, 치유농업 산업의 개념과 특징을 반영하여 특수분류체계를 구성하였다. 이러한 분류체계를 통해 치유농장을 대상으로 운영 및 경영 현황을 조사함으로써 국내 치유농업의 산업적 구성과 비중을 분석하였다. 국내 치유농장의 사업 비중은 전체 매출액 중 치유농업 산업이 47.8%, 투입재 산업 40.4%, 파생 산업은 11.9%를 차지하였다. 소분류기준 매출액이 가장 많은 분야는 공동체 서비스 교육, 정신적 재활치료, 치유농업 농산물 재배업 순이었다. 치유농장의 81.1%가 치유농업 운영을 위해 시설을 건설하였는데 그 종류로는 조경 및 공원, 녹지 조성이 77.9%로 가장 많았다. 한편 매출액이나 종사자 규모로 살펴본 결과, 국내 치유농장은 매우 영세하게 운영되는 것으로 나타났다. 본 조사 결과, 현재까지 치유농업 산업이 정부 주도의 사업으로써 도입되고 있는 수준이라는 점에서 산업 현황자료로서 한계점을 가지고 있다고 본다. 그러나 향후 치유농업의 효율적인 사업경영을 위한 정책 마련의 기초자료로서 유용하게 활용될 수 있으리라 여겨지며, 한편 치유농업법에 따른 정기적 실태조사 추진의 방법적 기반을 마련했다고 평가된다.

본 연구는 메꽃과 6종의 식물에 대해 신속하고 비파괴적으로 분류하기 위해 근적외선 (Vis-NIR) 스펙트럼을 이용하였고 데이터의 전처리와 머신러닝 기술을 적용하였다. 전국적으로 분포하는 메꽃과 6종에 대해 야외에서 휴대용 분광기를 이용하여 판별하였다. 식물의 잎의 표면에서 400~1,075 nm의 근적외선 스펙트럼 (1.5 nm)을 수집하였 다. 수집된 스펙트럼 데이터는 3가지의 전처리와 raw데이터를 이용하였고 4종류의 머신러닝 모델을 적용하여 높은 판별 정확도를 확인하였다. 전처리와 머신러닝 모델의 조합을 통해 분석된 판별의 정확도는 43~99%의 범위로 분석되었고, standard normal variate 전처리와 support vector machine 머신러닝 모델의 조합에서 판별 정확도가 98.6% 로 가장 높게 나타났다. 본 연구에서 수집된 스펙트럼은 식물의 성장단계, 다양한 측정 지역 및 잎에서의 측정 위치 등과 같은 요인과 더불어 데이터 분석을 위한 조건으로 최 적의 전처리와 머신러닝 기술을 적용한다면 메꽃과 식물의 야외에서의 정확한 분류가 가능하고 이들 식물의 효과적인 관리와 모니터링에 활용할 수 있을 것으로 판단되었다.

Chinese characters spread to the Korean peninsula, forming a huge Chinese character document, unearthed inscriptions, handwritten copies and manuscripts in volume. Investigating the changes in the use of characters in their documents, most of them inherited the normal and popular characters in China. Until the Li Dynasty of Korea, regional popular characters gradually became characteristics. Especially in pen-based and block-printed editions, there are many variants of folk characters, and the types include province variants, understanding variants, symbol variants, cursive variants, and vulgar variants. The article examines the regional variations of “邊” “懷” “竄” “儒” “滅” “釋” “辭” “聲” “樂” in Korean historical documents.