• Journal of Information Processing Systems
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• 제16권4호
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• pp.795-808
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• 2020

Due to the poor evaluation indexes such as detection accuracy and recall rate when Yolov3 network detects aircraft in remote sensing images, in this paper, we propose a remote sensing image aircraft detection method based on machine vision. In order to improve the target detection effect, the Inception module was introduced into the Yolov3 network structure, and then the data set was cluster analyzed using the k-means algorithm. In order to obtain the best aircraft detection model, on the basis of our proposed method, we adjusted the network parameters in the pre-training model and improved the resolution of the input image. Finally, our method adopted multi-scale training model. In this paper, we used remote sensing aircraft dataset of RSOD-Dataset to do experiments, and finally proved that our method improved some evaluation indicators. The experiment of this paper proves that our method also has good detection and recognition ability in other ground objects.

• 한국암반공학회:학술대회논문집
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• 한국암반공학회 2008년도 국제학술회의
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• pp.43-51
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• 2008

Currently an increasing number of urban tunnels with small overburden are excavated according to the principle of the New Austrian Tunneling Method (NATM). For rational management of tunnels from planning to construction and maintenance stages, prediction, control and monitoring of displacements of and around the tunnel have to be performed with high accuracy. Computational method tools, such as finite element method, have been and are indispensable tool for tunnel engineers for many years. It is, however, a commonly acknowledged fact that determination of input parameters, especially material properties exhibiting nonlinear stress-strain relationship, is not an easy task even for an experienced engineer. Use and application of the acquired tunnel information is important for prediction accuracy and improvement of tunnel behavior on construction. Artificial Neural Network (ANN) model is a form of artificial intelligence that attempts to mimic behavior of human brain and nervous system. The main objective of this paper is to perform the deformation analysis in NATM tunnel by means of numerical simulation and artificial neural network (ANN) with field database. Developed ANN model can achieve a high level of prediction accuracy.

• 디지털산업정보학회논문지
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• 제18권3호
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• pp.83-95
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• 2022

A technology can be newly formed through technological convergence achieved by the intersection of two or more technological fields. As the complexity of technology development increases, related interest is increasing. Researches have been carried out on the concept, related indicators and analysis of technology convergence including method of social networks. This paper intends to suggest an analysis method of technology convergence using social networks based on the company's possessing technologies. According to the similarity of technologies among companies, a social network was constructed and the technology convergence was analyzed using k-core, a social network subgroup method. Using the result of k-core, base and element technologies for convergence was identified with their relations. Using the suggested method, technology convergence was analyzed on real technology data of defense-industry companies. When the minimum technology similarity is 0, the overall technology convergence relations between technology elements can be identified. In the scope of data in this paper, technologies of defense S/W, aircraft structure and structural materials are identified as important base technology for convergence.

• Human Ecology Research
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• 제60권4호
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• pp.625-643
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• 2022

The purpose of this study was to explore the trends and core keywords of the secondary school home economics teacher selection test using content analysis and text network analysis. The sample comprised texts of the secondary school home economics teacher 1st selection test for the 2017-2022 school years. Determination of frequency of occurrence, generation of word clouds, centrality analysis, and topic modeling were performed using NetMiner 4.4. The key results were as follows. First, content analysis revealed that the number of questions and scores for each subject (field) has remained constant since 2020, unlike before 2020. In terms of subjects, most questions focused on 'theory of home economics education', and among the evaluation content elements, the highest percentage of questions asked was for 'home economics teaching·learning methods and practice'. Second, the network of the secondary school home economics teacher selection test covering the 2017-2022 school years has an extremely weak density. For the 2017-2019 school years, 'learning', 'evaluation', 'instruction', and 'method' appeared as important keywords, and 7 topics were extracted. For the 2020-2022 school years, 'evaluation', 'class', 'learning', 'cycle', and 'model' were influential keywords, and five topics were extracted. This study is meaningful in that it attempted a new research method combining content analysis and text network analysis and prepared basic data for the revision of the evaluation area and evaluation content elements of the secondary school home economics teacher selection test.

• 한국정보통신학회논문지
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• 제24권10호
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• pp.1394-1397
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• 2020

The urine test used as a basic test method of in vitro diagnosis for health care has been used for a long time to be simple and convenient. The urine test method is using a color that appears depending on the change in the ion concentration that reacts over time buried in the standard color test paper(Strips) with a urine sample applied to some reaction reagents. In this paper, it was proposed a neural network algorithm to obtain a suitable and reproducibility and accuracy classifier suitable for the urine analysis system. The experimental results were compared with the visual colorimetric analysis, and the neural network algorithm showed better results.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 추계학술대회 논문집 전력기술부문
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• pp.244-246
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• 2008

EMTP-RV is the very powerful program to analyze the dynamic operation of the power system. To use this package in the large complex power system, it is very important to simplify the power system to simple equivalent network. In our study the 100 MVA STATCOM is placed at 345kV "MIGUM" which is the one of the 345kV substations of the Korean Electric Power System that is consist of more than 1000 bus. MIGUM substation is connected with 7 separated transmission lines to main Korean Electric power system. We developed a new method to simplify the network except the substation that we want to analysis. The power system outside the 345kV substation is modeled into the equivalent network. The loop network outside the substation can be modeled to simplified Thevenin equivalent network. The proposed method is applied to IEEE-14 Reliability Test System and the results shows the effectiveness of the method.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.849-850
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• 2006

This thesis presents a new analysis method of Vegas network model in single link single source and a new version of Vegas for expanding asymptotically stable region. Actually since original Vegas model is difficult to analysis, we use a modified Vegas network model. Since there is a few tools to analyze nonlinear system with delay, developing other methods is very important and useful. We used state space model in discrete time. Using by Jury's criterion, we could find asymptotically stable region of Vegas network model. And it was a if and only if condition. Moreover, we proposed a new version of Vegas algorithm. To expand asymptotically stable region we modified the original Vegas model. The new analysis method and new Vegas algorithm were justified by ns-2 simulation. And as compare with other result, we could know our method has many advantages.

• 한국IT서비스학회지
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• 제21권3호
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• pp.89-103
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• 2022

The purpose of this study is to explore professors' perception of blended learning. For this purpose, the reflective journals written by 56 university professors was analyzed using the keyword network analysis method. The results of this study are as follows: First, as a result of keyword frequency analysis for the blended learning, the keywords showed the highest frequency in the order of (1) 'instructional design', 'student', 'instructional method', 'learning objective' in the area of learning, (2) 'importance', 'instruction', 'feeling', 'student' in the area of feeling, and (3) 'semester', 'plan', 'weekly', and 'instruction' in the area of action plan. Second, the results of analyzing the degree, closeness centrality, and betweenness centrality of network connection are as follows. (1) The keywords 'instruction', 'instructional method', 'instructional design', and 'learning objective' in the area of learning, (2) the keywords 'instruction', 'importance', and 'necessity' in the area of feeling, and (3) 'instruction', 'plan', and 'semester' in the area of action plan showed high values in degree, closeness centrality, and betweenness centrality. Based on the research results, implications for blended learning and professors' perception were discussed.

• 한국수자원학회논문집
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• 제41권4호
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• pp.405-412
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• 2008

본 연구에서는 지역빈도해석 기법 중 하나인 FORGEX 기법을 이용하여 확률강우량을 추정하였다. 기존의 원형 네트워크와 1:1.5, 1:2의 비율을 갖는 타원형 네트워크가 한국의 강우자료에 적합한 방법인지를 판단하기 위해 3 가지 경우를 비교 분석하였다. 이 분석을 위해서 남한지역의 376개 지점의 연최대강우자료를 추출하고, 이 자료들을 연최대자료의 중간값으로 표준화하였다. 네트워크는 분석 대상 지점을 중심으로 형성되며, pooled points와 netmax 자료를 각 네트워크에서 매년 추출한다. 그리고 성장곡선(growth curve)을 유도하고 주어진 재현기간에 따른 확률강우량을 추정한다. 지점빈도해석과 지역빈도해석의 대표적인 기법인 홍수지수법(index flood method), FORGEX 기법이 적용되었고, 이를 통해 얻은 결과를 비교 분석하였다. 또한 36개 지점에 원형과 타원형 네트워크를 이용한 FORGEX 기법을 적용하였고, 그 결과를 비교 분석하였다. 결과적으로 대상지점의 지점빈도해석으로 구한 확률강우량과 지역빈도해석으로 구한 확률강우량의 차이가 적을 때 원형과 타원형 네트워크의 추정된 확률강우량의 차이도 적었다. 그러나 지점빈도해석의 결과와 홍수지수법 결과의 차이가 클 때 원형과 타원형 네트워크로 추정된 확률강우량의 차이도 컸다. 타원형 네트워크가 더 많은 지점을 포함할 때, 타원으로부터 추정된 확률강우량 값은 원으로 구해진 값보다 높은 정확도를 보였다. 그리고 타원의 비율이 1:2일 때가 1:1.5보다 홍수지수법으로 구한 확률강우량 값에 가까웠다. 그러므로 1:2 비율의 타원을 적용한 FORGEX 기법이 한국의 지역빈도해석에 적합한 방법이라 할 수 있다.

• 산업경영시스템학회지
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• 제20권44호
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• pp.81-92
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• 1997

The purpose of this paper is to develop a method of paramatric analysis that can be applied to an optimal solution of a maximum flow problem. We first define the transformed network corresponding to a given network. In such a network, we conduct paramatric analysis by determining changes in the optimal solution precipitated by changes in the capacity as the arc capacity varies from 0 to infinite. By this method we can easily calculate not only the characteristic region where the given optimal solution remains unchanged, but also the characteristic region where the value of the maximal flow gradually increases or decreases. The proposed method is demonstrated by numerical example.