• KIEAE Journal
• /
• v.12 no.6
• /
• pp.93-98
• /
• 2012

The concerns on high ozone concentration phenomenon is significantly growing in Seoul metropolitan area including the industry complex area, like Shiwha Banwol area. The aims of this research is the analysis of relationship between high concentrations of $O_3$ and solar radiation parameters in atmosphere. The understanding of the effects of solar radiation intensity, humidity, high air temperature on ozone concentration in a day is very useful to provide a direction for reducing of the high ozone concentration to a local government or a metropolitan government. The correlation analysis between maximum ozone concentration and various meteorological parameters in 2009 - 2011 carried out using IBM's SPSS program. The results showed that the mean correlations coefficient (R) between daily Ozone maximum and solar radiation resulted R = 0.64 during 2011. May - September in 10 air pollution stations. In case of correlations between daily ozone maximum and relative humidity showed negative correlation R = -0.61. The correlation analysis with mean air temperature during 1-3 PM resulted R = 0.29. This low correlation coefficient could be corrected by using of categorized data of ozone concentration. The daily maximum ozone concentration is more dependent on peak solar radiation and high air temperature during 1-3 PM than its simple daily maximum values. The results of this research would be used to develop the high ozone alert system around Seoul metropolitan area. This correlation analysis could be partially integrated to prediction of ozone peak concentration in connection with other methods like classification and regression tree(CART).

• Korean Journal of Environment and Ecology
• /
• v.15 no.4
• /
• pp.330-343
• /
• 2002

To investigate the vegetation structure of mountain ridge from Pijae to Doraegijae in Baekdudaegan, forty-three sites(size 500$m^2$) were set up and surveyed By using TWINSPAN classification. the plant community was divided into five groups, those are mixed forest on sub-alpine zone. Quercus mongolica - Acer pseudo-sieboldianum community, Q. mongolica-Pinus densiflora community, and Larix leptolepis forest. Quercus mongolica was found as a major woody plant species in the ridge area. And partly the subalpine zone in low elevation was occupied by deciduous tree species and mixed a few conifer such as Abies nephrolepis and Taxus cuspidata etc.. Species diversity index(Area 1,000$m^2$) in the showed calculated 2.0149~3.0139 and it was similar to those of the ridge area of the national parks in Beakdudaegan.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2010.05a
• /
• pp.1615-1619
• /
• 2010

토양수분은 토양입자에 포함되어 있는 물을 의미하는 것으로 지표면과 대기간의 에너지 균형과 물 순환을 조절하는데 중요한 요소이다. 본 연구에서는 토양수분 산정을 위하여 2003년 1월부터 2008년 12월까지의 MODIS(Moderate Resolution Imaging Spectroradiometer) 위성관측 자료로부터 획득한 정규식생지수(NDVI: Normalized Difference Vegetation Index)자료와 지표면 온도자료, 우리나라 76개소 기상관측소 중에 자료의 보유기간이 30년 이하인 관측소와 섬 지역들을 제외한 57개 지점의 강수량, 토양온도 자료 및 우리나라 전역에 대한 토지피복, 유효토심자료를 이용하여 데이터 마이닝(Data Mining) 기법의 하나인 CART(Classification And Regression Tree) 기법을 이용하여 토양수분을 산정하였다. 먼저 신뢰성 높은 토양수분 관측 자료를 가진 용담댐 유역의 6개 지점에 대하여 토양수분을 산정하여 적용 가능성을 분석하였다. 3개 지점의 토양수분 관측치는 토양수분 산정 모형 수립에 사용하였으며 검증에 사용된 1개 지점의 토양수분의 관측치와 추정치 간의 상관계수를 확인한 결과 전체적인 토양수분의 거동을 잘 나타내고 있어 토양수분 추정 모형의 적용가능성을 확인하였다. 이를 이용하여 용담댐 유역의 토양수분 분포와 우리나라 전역에 대한 토양수분 분포도를 추정하였다. 신뢰할 수 있는 지상관측 토양수분 관측치가 다양한 지상조건에 대하여 존재하지 않는 한계가 있음에도 불구하고 제시된 토양수분산정 방법은 제한된 가용자료를 사용한 우리나라 전역의 토양수분 산정에 있어 합리적인 접근법이라 판단된다.

• ALGAE
• /
• v.28 no.4
• /
• pp.307-330
• /
• 2013

The genus Cryptomonas is easily recognized by having two flagella, green brownish color, and a swaying behavior. They have relatively simple morphology, and limited diagnostic characters, which present a major difficulty in differentiating between species of the genus. To understand species delineation and phylogenetic relationships among Cryptomonas species, the nuclear-encoded internal transcribed spacer 2 (ITS2), partial large subunit (LSU) and small subunit ribosomal DNA (rDNA), and chloroplast-encoded psbA and LSU rDNA sequences were determined and used for phylogenetic analyses, using Bayesian and maximum likelihood methods. In addition, nuclear-encoded ITS2 sequences were predicted to secondary structures, and were used to determine nine species and four unidentified species from 47 strains. Sequences of helix I, II, and IIIb in ITS2 secondary structure were very useful for the identification of Cryptomonas species. However, the helix IV was the most variable region across species in alignment. The phylogenetic tree showed that fourteen species were monophyletic. However, some strains of C. obovata had chloroplasts with pyrenoid while others were without pyrenoid, which used as a key character in few species. Therefore, classification systems depending solely on morphological characters are inadequate, and require the use of molecular data.

• Parasites, Hosts and Diseases
• /
• v.42 no.3
• /
• pp.129-135
• /
• 2004

We compared the DNA sequences of the genus Metagonimus: M. yokogawai, M. takahashii, and M. miyatai. We obtained 288 D1 ribosomal DNA (rDNA) and mitochondrial cytochrome c oxidase subunit I (mtCOI) fragments from the adult worms by PCR, that were cloned and sequenced. Phylogenetic relationships inferred from the nucleotide sequences of the 28S D1 rDNA and mtCOI gene. M. takahashii and M. yokogawai are placed in the same clade supported by DNA sequence and phylogenie tree analysis in 28S D1 rDNA and mtCOI gene region. The above findings tell us that M. takahashii is closer to M. yokogawai than to M. miyatai genetically. This phylogenetic data also support the nomination of M. miyatai as a separate species.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.29 no.4
• /
• pp.1-20
• /
• 2021

Due to the recent rapid increase in passenger and cargo air transport demand, the capacity of Jeju International Airport has been approaching its limit. Even though in COVID-19 crisis which has started from Nov 2019, Jeju International Airport still suffers from strong demand in terms of air passenger and cargo transportation. However, it is an undeniable fact that the delay has also increased in Jeju International Airport. In this study, we analyze the correlation between weather and delayed departure operation based on both datum collected from the historical airline operation information and aviation weather statistics of Jeju International Airport. Adopting machine learning techniques, we then analyze weather condition Jeju International Airport and construct a delay prediction model. The model presented in this study is expected to play a useful role to predict aircraft departure delay and contribute to enhance aircraft operation efficiency and punctuality in the Jeju International Airport.

• Journal of Forest and Environmental Science
• /
• v.37 no.4
• /
• pp.269-279
• /
• 2021

This study was carried out to introduce the forest cover types of the Baekdudaegan inhabiting the number of native tree species. In order to understand the vegetation distribution characteristics of the Baekdudaegan, a vegetation survey was conducted on the major 20 mountains of the Baekdudaegan. The vegetation data were collected from 3,959 sample points by the point-centered quarter method. Each mountain was classified into 4-7 forests by using various multivariate statistical methods such as cluster analysis, indicator species analysis, multiple discriminant analysis, and species composition analysis. The forests were classified mainly according to the relative abundance of Quercus mongolica. There was a total of 111 classified forests and these forests were integrated into the following nine forest cover types using the percentage similarity index and by clustering according to vegetation type: 1) Mongolian oak, 2) Mongolian oak and other deciduous, 3) Oaks (Mixed Quercus spp.), 4) Korean red pine, 5) Korean red pine and oaks, 6) ash, 7) mixed mesophytic, 8) subalpine zone coniferous, and 9) miscellaneous forest. Forests grouped within the subalpine zone coniferous and miscellaneous classifications were characterized by similar environmental conditions and those forests that did not fit in any other category, respectively.

• Journal of the Korea Safety Management & Science
• /
• v.23 no.4
• /
• pp.93-104
• /
• 2021

In this paper, we propose a method for diagnosing overload and working load of collaborative robots through performance analysis of machine learning algorithms. To this end, an experiment was conducted to perform pick & place operation while changing the payload weight of a cooperative robot with a payload capacity of 10 kg. In this experiment, motor torque, position, and speed data generated from the robot controller were collected, and as a result of t-test and f-test, different characteristics were found for each weight based on a payload of 10 kg. In addition, to predict overload and working load from the collected data, machine learning algorithms such as Neural Network, Decision Tree, Random Forest, and Gradient Boosting models were used for experiments. As a result of the experiment, the neural network with more than 99.6% of explanatory power showed the best performance in prediction and classification. The practical contribution of the proposed study is that it suggests a method to collect data required for analysis from the robot without attaching additional sensors to the collaborative robot and the usefulness of a machine learning algorithm for diagnosing robot overload and working load.

• The Plant Pathology Journal
• /
• v.37 no.3
• /
• pp.243-257
• /
• 2021

Bacillus pumilus is the causal agent of trunk bulges disease affecting rubber and rubberwood quality and yield production. In this study, B. pumilus and other closely related species were included in B. pumilus group, as they shared over 99.5% similarity from 16S rRNA analysis. Multilocus sequence analysis (MLSA) of five housekeeping genes and repetitive elements-based polymerase chain reaction (rep-PCR) using REP, ERIC, and BOX primers conducted to analyze the diversity and systematic relationships of 20 isolates of B. pumilus group from four rubber tree plantations in Peninsular Malaysia (Serdang, Tanah Merah, Baling, and Rawang). Multi rep-PCR results revealed the genetic profiling among the B. pumilus group isolates, while MLSA results showed 98-100% similarity across the 20 isolates of B. pumilus group species. These 20 isolates, formerly established as B. pumilus, were found not to be grouped with B. pumilus. However, being distributed within distinctive groups of the B. pumilus group comprising of two clusters, A and B. Cluster A contained of 17 isolates close to B. altitudinis, whereas Cluster B consisted of three isolates attributed to B. safensis. This is the first MLSA and rep-PCR study on B. pumilus group, which provides an in-depth understanding of the diversity of these rubber-pathogenic isolates in Malaysia.

• Steel and Composite Structures
• /
• v.42 no.6
• /
• pp.733-745
• /
• 2022

This study proposed a robust artificial intelligence (AI) model based on the social behaviour of the imperialist competitive algorithm (ICA) and artificial neural network (ANN) for modelling the deflection of reinforced concrete beams, abbreviated as ICA-ANN model. Accordingly, the ICA was used to adjust and optimize the parameters of an ANN model (i.e., weights and biases) aiming to improve the accuracy of the ANN model in modelling the deflection reinforced concrete beams. A total of 120 experimental datasets of reinforced concrete beams were employed for this aim. Therein, applied load, tensile reinforcement strength and the reinforcement percentage were used to simulate the deflection of reinforced concrete beams. Besides, five other AI models, such as ANN, SVM (support vector machine), GLMNET (lasso and elastic-net regularized generalized linear models), CART (classification and regression tree) and KNN (k-nearest neighbours), were also used for the comprehensive assessment of the proposed model (i.e., ICA-ANN). The comparison of the derived results with the experimental findings demonstrates that among the developed models the ICA-ANN model is that can approximate the reinforced concrete beams deflection in a more reliable and robust manner.