• 한국산림과학회지
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• 제84권2호
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• pp.258-265
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• 1995

본(本) 연구(硏究)는 경상북도(慶尙北道) 울진군(蔚珍群) 불영계곡 일대(一帶)에서 토지극상(土地極相)을 형성(形成)하고 있는 소나무림(林)을 대상(對象)으로 임분(林分)의 재생(再生) 과정(過程)을 밝히고자 하였다. 소나무 임분(林分)은 수고(樹高)가 12-5m 정도(程度)이며, 상층목(上層木)은 개체(個體)가 중심(中心)이 되어 임의적으로 분포(分布)하고 있으며, 하층목(下層木)은 집중반(集中斑)으로 분포(分布)하고 있다. 상층목(上層木)은 주로 60-80년(年) 정도(程度)의 정점을 갖는 단봉형(單峰型)의 분포(分布)를 나타내고 있으며, 이들 임분(分布)의 수평적(水平的) 분포(分布)는 대체로 동령적(同齡的) 집단(集團)을 보여주고 있다. 상층목(上層木)의 초기(初期) 25년(年) 동안의 비대생장(肥大生長) 속도(速度)는 중(中) 하층목(下層木) 보다 빠르다. 소나무림(林)의 재생(再生) 과정(過程)은 임내(林內)에 gap이 형성(形成)된 이후(以後)에 집중적(集中的)으로 발생(發生)한 후생(後生)한 추수(推樹)가 성장(成長)하여 그 중(中)의 몇 개체(個體)가 임관(林冠)을 형성(形成)하는 것으로 추정(推定)된다.

• 한국작물학회지
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• 제49권5호
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• pp.419-422
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• 2004

Soybean is a major source of protein meal in the world. Kunitz trypsin inhibitor (KTI) protein is responsible for the inferior nutritional quality of unheated or incompletely heated soybean meal. The objective of this research was to identify RAPD markers linked to KTI protein allele using bulked segregant analysis. Cultivar Jinpumkong2 (TiTi) was crossed with C242 (titi, absence of KTI protein) and F. seeds were planted. The $F_1$. plants were grown in the greenhouse to produce $F_2$ seeds. Each $F_2$ seed from $F_1$. plants was analysed electrophoretically to determine the presence of the KTI protein band. The present and absent bulks contained twenty individuals each, which were selected on the basis of the KTI protein electrophoresis, respectively. Total 94 $F_2$ individuals were constructed and 1,000 Operon random primers were used to identify RAPD primers linked to the Ti locus. The presence of KTI protein is dominant to the lack of a KTI protein and Kunitz trypsin inhibit protein band is controlled by a single locus. Four RAPD primers (OPAC12, OPAR15, OPO12, and OPC08) were linked to the Ti locus. RAPD primer OPO12 was linked to Ti locus, controlling kunitz trypsin inhibitor protein at a distance of 16.0 cM. This results may assist in study of developing fine map including Ti locus in soybean.

• Smart Structures and Systems
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• 제26권2호
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• pp.175-184
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• 2020

Conventional Monte Carlo simulation-based methods for seismic risk assessment of water networks often require excessive computational time costs due to the hydraulic analysis. In this study, an Artificial Neural Network-based surrogate model was proposed to efficiently evaluate the flow-based system reliability of water distribution networks. The surrogate model was constructed with appropriate training parameters through trial-and-error procedures. Furthermore, a deep neural network with hidden layers and neurons was composed for the high-dimensional network. For network training, the input of the neural network was defined as the damage states of the k-dimensional network facilities, and the output was defined as the network system performance. To generate training data, random sampling was performed between earthquake magnitudes of 5.0 and 7.5, and hydraulic analyses were conducted to evaluate network performance. For a hydraulic simulation, EPANET-based MATLAB code was developed, and a pressure-driven analysis approach was adopted to represent an unsteady-state network. To demonstrate the constructed surrogate model, the actual water distribution network of A-city, South Korea, was adopted, and the network map was reconstructed from the geographic information system data. The surrogate model was able to predict network performance within a 3% relative error at trained epicenters in drastically reduced time. In addition, the accuracy of the surrogate model was estimated to within 3% relative error (5% for network performance lower than 0.2) at different epicenters to verify the robustness of the epicenter location. Therefore, it is concluded that ANN-based surrogate model can be utilized as an alternative model for efficient seismic risk assessment to within 5% of relative error.

• Asian Pacific Journal of Cancer Prevention
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• 제16권13호
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• pp.5445-5451
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• 2015

Fascin-1 (FSCN1) is an actin-bundling protein that induces cell membrane protrusions, increases cell motility, and is overexpressed in various human epithelial cancers, including esophageal squamous cell carcinoma (ESCC). We analyzed various protein-protein interactions (PPI) of differentially-expressed genes (DEGs), in fascin knockdown ESCC cells, to explore the role of fascin overexpression. The node-degree distributions indicated these PPI sub-networks to be characterized as scale-free. Subcellular localization analysis revealed DEGs to interact with other proteins directly or indirectly, distributed in multiple layers of extracellular membrane-cytoskeleton/ cytoplasm-nucleus. The functional annotation map revealed hundreds of significant gene ontology (GO) terms, especially those associated with cytoskeleton organization of FSCN1. The Random Walk with Restart algorithm was applied to identify the prioritizations of these DEGs when considering their relationship with FSCN1. These analyses based on PPI network have greatly expanded our comprehension of the mRNA expression profile following fascin knockdown to future examine the roles and mechanisms of fascin action.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.438-441
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• 2007

Recently, due to molecular biology and engineering technology, DNA microarray makes people watch thousands of genes and the state of variation from the tissue samples of living body. With DNA Microarray, it is possible to construct a genetic group that has similar expression patterns and grasp the progress and variation of gene. This paper practices Cluster Analysis which purposes the discovery of biological subgroup or class by using gene expression information. Hence, the purpose of this paper is to predict a new class which is unknown, open leukaemia data are used for the experiment, and MCL (Markov CLustering) algorithm is applied as an analysis method. The MCL algorithm is based on probability and graph flow theory. MCL simulates random walks on a graph using Markov matrices to determine the transition probabilities among nodes of the graph. If you look at closely to the method, first, MCL algorithm should be applied after getting the distance by using Euclidean distance, then inflation and diagonal factors which are tuning modulus should be tuned, and finally the threshold using the average of each column should be gotten to distinguish one class from another class. Our method has improved the accuracy through using the threshold, namely the average of each column. Our experimental result shows about 70% of accuracy in average compared to the class that is known before. Also, for the comparison evaluation to other algorithm, the proposed method compared to and analyzed SOM (Self-Organizing Map) clustering algorithm which is divided into neural network and hierarchical clustering. The method shows the better result when compared to hierarchical clustering. In further study, it should be studied whether there will be a similar result when the parameter of inflation gotten from our experiment is applied to other gene expression data. We are also trying to make a systematic method to improve the accuracy by regulating the factors mentioned above.

• 대한원격탐사학회지
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• 제36권1호
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• pp.67-81
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• 2020

The rapid climatic changes being caused by global warming are resulting in abnormal weather conditions worldwide, which in some regions have increased the frequency of landslides. This study was aimed to analyze and compare the landslide susceptibility using the Frequency Ratio (FR), Statistical Index, Weight of Evidence, Certainty Factor, and Index of Entropy (IoE) at Woomyeon Mountain in South Korea. Through the construction of a landslide inventory map, 164 landslide locations in total were found, of which 50 (30%) were reserved to validate the model after 114 (70%) had been chosen at random for model training. The sixteen landslide conditioning factors related to topography, hydrology, pedology, and forestry factors were considered. The results were evaluated and compared using relative operating characteristic curve and the statistical indexes. From the analysis, it was shown that the FR and IoE models were better than the other models. The FR model, with a prediction rate of 0.805, performed slightly better than the IoE model with a prediction rate of 0.798. These models had the same sensitivity values of 0.940. The IoE model gave a specific value of 0.329 and an accuracy value of 0.710, which outperforms the FR model which gave 0.276 and 0.680, respectively, to predict the spatial landslide in the study area. The generated landslide susceptibility maps can be useful for disaster and land use planning.

• 디지털융복합연구
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• 제14권11호
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• pp.125-133
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• 2016

최근 들어 '뭇지마 범죄' 등 각종 범죄가 지속적으로 증가하고 있다. 정부의 범죄 예방 노력과 이에 관한 연구 등에도 불구하고 범죄가 증가하고 있어 다른 접근법이 필요한 상황이다. 이에 본 연구는 빅데이터를 분석하여 대안을 제안하고자 하였다. 연구 목적 달성을 위해 본 연구는 막대그래프와 버블차드 및 버블차드를 활용한 시각화와 연관분석 등을 수행하였다. 여러 변수와 범죄와의 관계 분석을 위해 성남시, 사이버경찰청 등의 데이터를 분석하였다. 분석 결과, CCTV의 수는 범죄율을 감소시키는데 효과적이나 보안등의 수는 연관성이 크지 않은 것으로 나타났다. 또 시간대별로, 요일별로 다른 유형의 범죄가 집중되는 것을 알 수 있었으며, 외국인의 증가도 범죄의 증가와 관련이 있는 것으로 파악되었다. 이러한 분석 결과를 토대로 범죄율 감소를 위한 방안을 제시하였다.

• 한국임상수의학회지
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• 제28권3호
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• pp.291-296
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• 2011

돼지에서 medetomidine-ketamine (MK) 합제에 대한 마취효과와 이 합제에 대한 atipamezole (MKA) 과 yohimbine (MKY)의 길항효과를 비교하였다. 24 마리 Landrace - Yorkshire 혼혈 종 돼지를 사용하였다. Medetomidineketamine 는 한 주사기로 근육주사 하였고 atipamezole 과 yohimbine 은 마취 후 20 분에 정맥 주사 하였다. 평균마취시간, 평균흉와시간, 평균기립시간 및 평균보행시간은 MKA와 MKY군에서 MK군보다 유의적으로 짧았다. 그러나 MKA군과 MKY군간의 유의적인 차이는 없었다. 평균혈압은 MKA와 MKY군에서 MK군보다 유의적으로 낮았다. 결론적으로 Medetomidine-ketamine 에 의한 마취 및 혈압 상승 효과는 atipamezole과 yohimbine 에 의해 안전하고 빠르게 길항되었다. 따라서 atipamezole과 yohimbine은 돼지에서 Medetomidine-ketamine 마취를 길항하는 데 안전하고 효과적으로 사용될 수 있다.

• 한국광학회지
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• 제25권5호
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• pp.273-278
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• 2014

일련의 국부영역으로부터 이차미분값을 획득하여 전체 형상을 복원하는 측정법을 제안하였다. 측정시 기울기가 제거된 국부형상에 대해 곡률과 이차미분이 동일시 되는 점을 이용하여, 3개의 이차미분값으로부터 직교하는 2방향을 따라 3차원형상을 복원할 수 있는 알고리즘을 구현하였다. 임의로 발생시킨 Zernike다항식의 계수로 자유곡면형상을 생성시키고, 구현된 알고리즘을 적용함으로써 검증과정을 수행하였다. 적용한 결과 최대 0.8 mm Sag를 갖는 직경 200 mm영역의 자유곡면형상에 대해 RMS 19 nm 형상복원오차를 갖고 복원됨을 확인하였다. 측정오차에 대한 복원오차 민감도를 진단하기 위해 SNR(Signal-to-Noise Ratio) 16의 가우시언 랜덤 노이즈를 부여한 후, 복원되는 형상의 오차를 진단한 결과, 197 nm의 형상복원오차가 발생함을 확인하였다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2011년도 추계학술대회
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• pp.241-244
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• 2011

최근 인터넷 기술의 발전으로 인해 웹 서비스의 이용시간 및 장소에 대한 제약 없이 바로 접속할 수 있는 편리성이 제공되어 사용자가 급증하였다. 웹서비스에서는 일반적으로 ID/Password 인증방식을 사용하고 있으며, 사용자인증 후 웹서버에 저장된 사용자의 개인정보를 확인할 수 있다. 이를 보호하기 위해 웹 서비스 공급자는 다양한 보안 기법들을 제공하고 있다. 그러나 사용자가 키보드를 통해서 개인정보를 입력하는 순간에 공격자가 Keyboard hooking 을 이용하여 개인정보가 탈취되는 사건이 최근 발생되고 있다. 이에 본 논문에서는 Keyboard hooking 방지를 위해 패스워드 입력 시 CAPTCHA로 구성된 문자들이 특정 Map상 무작위로 배치되어 이를 마우스나 터치를 통해 입력되는 방법을 제안한다.