• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.371-371
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• 2019

우리나라는 홍수기(6~9월)에 집중되는 기상패턴과 하천 중하류부에 발달된 도시의 개발특성으로 인하여 가장 중요한 자연재해 중 하나로 홍수 및 도시침수가 거론되고 있다. 과거 집중호우로 침수 피해가 발생한 사례를 살펴보면, 피해가 발생하는 지역은 지방하천 및 소하천을 중심으로 형성된 도시지역이다. 중앙 지방 정부는 수차례 침수 피해를 겪으며 사후관리가 아닌 재난예방 및 사전관리 등의 방안 마련을 강조하고 있다. 하지만 기후변화에 의한 기상의 불확실성으로 치수 중심의 물관리 및 중 소하천의 하천 특성으로 여전히 홍수 발생에 대비할 수 있는 골든타임 확보 등에 어려움을 겪고 있다. 이러한 어려움을 극복하기 위해 사전 예방적 차원에서의 홍수대응 방안으로 중 소하천을 담당하는 지자체 중심의 홍수피해 저감 방안이 필요하다. 본 연구에서는 A 지자체를 대상으로 모니터링 대상 경계를 설정하여 우량 알람 기준을 예비알람, 주요 관측지점에 대해 강우에 따른 수위 상승 정도를 홍수대응 기준인 직접알람과 연계함으로써 예방적 재난대응 체계를 구축하였다. 모니터링 대상 지역은 해당 지자체를 포함하면서 유역 개념을 적용하여 만경강유역 전체로 설정하였다. 만경강 유역 내 유관기관(지자체, 환경부, K-water, 기상청 등)이 관할하는 우량국(41개소) 및 수위국(28개소), 저수용량이 30만톤 이상이 되는 농어촌공사 저수지(7개소)를 고려하여 홍수분석 모형(COSFIM)을 구축하였다. 해당 모형은 2018년 8월 호우사상에 대해 주요 수위관측 지점에서 $R^2$가 0.8 이상의 우수한 검증 결과를 보였다. 구축된 모형을 통해 예상강우량별 하천 내 수위지점별 최고수위, 최대유량, 도달시간 등 예상 조견표를 제시하여 호우 발생시 지자체 담당자가 참고할 수 있도록 제시하였다. 또한 수위지점별 홍수대응 기준은 평시, 관심, 주의, 경계, 심각 단계로 구분하여 담당자가 수위별 위험 정도를 인지할 수 있도록 지점별 도달되는 수위의 위험 정보를 알람기준으로 제시하였다. 홍수분석 모형은 상류에 위치한 주요시설물의 운영현황을 연계하고 있어 실제 강우 발생 시 기상예보를 고려하여 하천 내 수위관측 지점별 수위 상승 정도를 예상함으로써 사전에 홍수에 대비할 수 있는 단계별 시간 확보에 활용 가능하다. 향후 홍수대응기준은 하천 환경 변화를 반영하여 지속적인 보완이 필요하며 유관기관과의 수문자료 공유체계 확대로 예방적 차원의 홍수 대응 체계가 구축되어야 할 것이다.

• Journal of Digital Convergence
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• v.19 no.9
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• pp.217-228
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• 2021

The purpose of this study is to analyze drum performance techniques, focusing on the representative artists of funk music, who had a revival starting in the 1970s. The purpose of this study is to analyze the creativity shown in David Garibaldi's playing technique, which had a great influence on drum majors with his funk drum playing technique. As a research method, 'James Brown', 'Earth, Wind & Fire' and 'Tower of Power' with David Garibaldi as drummer were selected as representative bands. For the study period, the drum performance was examined by selecting two representative songs from among the songs released between 1965 and 1975, when the development of the corresponding funk music began. David Garibaldi's creative performance in this study is as follows. First, we tried to create a new rhythm in the form of changing the beat or resting the beat out of the frame of contemporary drum performance. Second, the 'Paradiddle', 'Accent', and 'Swiss Army triplet' rudiment techniques were applied to the entire drum kit, bringing innovation to the rhythm. Third, the samba pattern of Latin rhythm and the form of 'Afro-Cuban' were grafted onto funk music. Fourth, the idea of Unison Rhythm obtained from the structure of Latin music was applied to funk music. Based on this study, it is hoped that research on drum performance techniques of various genres will be conducted.

• Food Engineering Progress
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• v.15 no.2
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• pp.122-129
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• 2011

In this study, discrimination of salted cuttle fish and salted mitra squid was carried out using electronic nose based on mass spectrometer. Intensities of each fragment from salted cuttlefish by electronic nose were completely different from those of salted mitra squid. Each sample was analyzed, and discriminant function analysis (DFA) was used for the discrimination of similar products. DFA plot indicated a significant separation of each salted cuttlefish and mitra squid ($r^2$= 0.8789, F= 162.13). Electronic nose based on mass spectrometer could be used as an efficient method for discrimination of Economically Motivated Authentication (EMA) foods.

• Korean Journal of Microbiology
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• v.55 no.2
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• pp.103-111
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• 2019

DNA methylation is involved in diverse processes in bacteria, including maintenance of genome integrity and regulation of gene expression. CcrM, the DNA methyltransferase conserved in Alphaproteobacterial species, carries out $N^6$-adenine or $N^4$-cytosine methyltransferase activities using S-adenosyl methionine as a co-substrate. Celeribacter marinus IMCC12053 from the Alphaproteobacterial group was isolated from a marine environment. Single molecule real-time sequencing method (SMRT) was used to detect the methylation patterns of C. marinus IMCC12053. Gibbs motif sampler program was used to observe the conversion of adenosine of 5'-GANTC-3' to $N^6$-methyladenosine and conversion of $N^4$-cytosine of 5'-GpC-3' to $N^4$-methylcytosine. Exocyclic DNA methyltransferase from the genome of strain IMCC12053 was chosen using phylogenetic analysis and $N^4$-cytosine methyltransferase was cloned. IPTG inducer was used to confirm the methylation activity of DNA methylase, and cloned into a pQE30 vector using dam-/dcm- E. coli as the expression host. The genomic DNA and the plasmid carrying methylase-encoding sequences were extracted and cleaved with restriction enzymes that were sensitive to methylation, to confirm the methylation activity. These methylases protected the restriction enzyme site once IPTG-induced methylases methylated the chromosome and plasmid, harboring the DNA methylase. In this study, cloned exocyclic DNA methylases were investigated for potential use as a novel type of GpC methylase for molecular biology and epigenetics.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.121-132
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• 2018

Weather is an important factor affecting roadway transportation in many aspects such as traffic flow, driver 's driving patterns, and crashes. This study focuses on the relationship between weather and road surface condition and develops a model to estimate the road surface condition using machine learning. A road surface sensor was attached to the probe vehicle to collect road surface condition classified into three categories as 'dry', 'moist' and 'wet'. Road geometry information (curvature, gradient), traffic information (link speed), weather information (rainfall, humidity, temperature, wind speed) are utilized as variables to estimate the road surface condition. A variety of machine learning algorithms examined for predicting the road surface condition, and a two - stage classification model based on 'Random forest' which has the highest accuracy was constructed. 14 days of data were used to train the model and 2 days of data were used to test the accuracy of the model. As a result, a road surface state prediction model with 81.74% accuracy was constructed. The result of this study shows the possibility of estimating the road surface condition using the existing weather and traffic information without installing new equipment or sensors.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.75-80
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• 2018

The smart city is developing an energy system efficiently through a common management of the city resource for the growth and a low carbon social. However, the smart city doesn't counter a verification effectively about a anomaly pattern detection when existing security technology (authentication, integrity, confidentiality) is used by fixed security key and key deodorization according to generated big data. This paper is proposed the "security nonce generation based on security nonce generation" for anomaly pattern detection of the adversary and a safety of the key is high through the key generation of the KDC (Key Distribution Center; KDC) for improvement. The proposed scheme distributes the generated security nonce and authentication keys to each facilities system by the KDC. This proposed scheme can be enhanced to the security by doing the external pattern detection and changed new security key through distributed security nonce with keys. Therefore, this paper can do improving the security and a responsibility of the smart city platform management data through the anomaly pattern detection and the safety of the keys.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.661-670
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• 2021

Research trends can be usefully used to determine the importance of research topics by period, identify insufficient research fields, and discover new fields. In this study, research trends of urban spaces, where various problems are occurring due to population concentration and urbanization, were analyzed by topic modeling. The analysis target was the abstracts of papers listed in the Korea Citation Index (KCI) published between 2002 and 2019. Topic modeling is an algorithm-based text mining technique that can discover a certain pattern in the entire content, and it is easy to cluster. In this study, the frequency of keywords, trends by year, topic derivation, cluster by topic, and trend by topic type were analyzed. Research in urban regeneration is increasing continuously, and it was analyzed as a field where detailed topics could be expanded in the future. Furthermore, urban regeneration is now becoming a regular research field. On the other hand, topics related to development/growth and energy/environment have entered a stagnation period. This study is meaningful because the correlation and trends between keywords were analyzed using topic modeling targeting all domestic urban studies.

• Food Engineering Progress
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• v.22 no.4
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• pp.381-385
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• 2018

Various rheological methods to measure the hardness of instant cooked rice by a texture analyzer were investigated and compared. Specifically, instant white rice samples with a wide range of hardness were subjected to four different rheological tests with disk, cylinder, rod, and cone probe whose results were inter-correlated. All the measurements demonstrated that the hardness of instant rice was reduced with increasing moisture content and showed negatively linear relationships. Out of the four tests applied in this study, the highest coefficient of correlation ($R^2=0.9268$) was observed distinctly in the cone probe test, where both compressive and shear forces can be applied to deform individual rice grains. However, the cylinder probe test had the lowest coefficient of correlation ($R^2=0.7247$) because it may be ineffective in causing direct deformation of individual rice grains. Furthermore, when the hardness values (N) were converted to stress (Pa), highly linear correlations ($R^2{\approx}0.99$) were observed between the tests with similar probe geometry and force application.

• Korean Journal of Environment and Ecology
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• v.36 no.2
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• pp.202-216
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• 2022

Animals exhibit certain behaviors and movement patterns as they react to their internal needs, external stimuli, and surrounding environments. They have a bounded range in which they mostly spend their time, and it is referred to as a home range. Based on the fact that the home range is a critical area for the survival and preservation of species, there has been a growing body of research on developing more precise home range estimation methods to use the estimated ranges as a ground for establishing an effective conservation policy since the early 1940s. Recent rapid advancements in telemetry technology that resulted in the presence of autocorrelation between locations with short time intervals revealed the limitations of the existing estimators. Many novel estimators have been developed to compensate for it by incorporating autocorrelation in calculating home ranges. However, studies on the animal home range are still in their early stage in Korea, and newly developed methodologies have not yet been adopted. Therefore, this study aims to introduce the foreign home range estimation methods and foster domestic research activities on home ranges. Firstly, we compared and contemplated seven estimators by categorizing them into geometrical and statistical methodologies and then divided them into estimators that assume independent observations and those that consider autocorrelation in each category. After that, the home ranges of black-tailed gulls (Larus crassirostris) were calculated using GPS tracking data for the month of June and derived home range estimators by applying the methodology introduced in this study. We analyzed and compared the results to discuss the strengths and weaknesses of each method. Lastly, we proposed a guideline that can help researchers choose an appropriate estimator for home range calculation based on the animal location data characteristics and analysis purpose.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.203-213
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• 2021

A vehicle crash occurs due to various factors such as the geometry of the road section, traffic, and driver characteristics. A safety performance function has been used in many studies to estimate the relationship between vehicle crash and road factors statistically. And depends on the purpose of the analysis, various characteristic variables have been used. And various characteristic variables have been used in the studies depending on the purpose of analysis. The existing domestic studies generally reflect the average characteristics of the sections by quantifying the traffic volume in macro aggregate units such as the ADT, but this has a limitation that it cannot reflect the real-time changing traffic characteristics. Therefore, the need for research on effective aggregation units that can flexibly reflect the characteristics of the traffic environment arises. In this paper, we develop a safety performance function that can reflect the traffic characteristics in detail with an aggregate unit for one hour in addition to the daily model used in the previous studies. As part of the present study, we also perform a comparison and evaluation between models. The safety performance function for daily and hourly units is developed using a negative binomial regression model with the number of accidents as a dependent variable. In addition, the optimal negative binomial regression model for each of the hourly and daily models was selected, and their prediction performances were compared. The model and evaluation results presented in this paper can be used to determine the risk factors for accidents in the highway section considering the dynamic characteristics. In addition, the model and evaluation results can also be used as the basis for evaluating the availability and transferability of the hourly model.