• KIPS Transactions on Computer and Communication Systems
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• v.1 no.3
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• pp.181-186
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• 2012

PMU based power grid monitoring and control system, WAMAC (Wide Area Monitoring And Control) system is required system design for accurate power data without error and loss through a system-wide. In the paper, we propose system design that measured data from PMU transmitted without loss to PDC and DSM server. and we propose a method to verify the real-time "data has been transmitted accurately". Verification system has been designed to reflect the WAMAC system. Therefore the WAMAC can enhance the reliability of the analysis of the data, and it can monitor lossless real-time trend data.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.933-933
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• 2012

최근 들어 우리나라를 포함한 전 세계적으로 극심한 기후변화와 기상이변으로 집중호우에 의한 피해가 급증하고 있으며, 기상재해에 따른 강우-유출 현상에 관한 정확한 해석이 필요하게 되었다. 국내의 경우에도 1990년 중반부터 매년 국지적 집중호우나 이상호우로 인해 재산 및 인명피해가 속출하고 있다. 대상유역으로 선정한 우이천 유역 또한 강북구의 대표적인 상습침수지역으로 피해 받고 있는 상황이며, 이를 예방하기 위해 홍수범람도 작성, 재해지도 작성 등의 지리정보시스템 기법 및 각종 수해대책이 활발하게 진행되고 있지만 아직은 미비한 실정이다. 본 연구에서는 우이천 유역에 대한 강우-유출 해석을 위한 분포형 모형인 Vflo$^{TM}$의 적용성을 검토 분석하는 데에 의의를 두었다. 또한 각 격자크기별로 유출량의 변화를 타 모형과의 비교를 통하여 적정성을 검토하였다. 이를 위해 대상유역의 1:1000 수치지형도를 이용하여 50m, 100m, 150m, 200m의 DEM을 생성하였고 ArcGIS 프로그램의 Hydro툴을 이용하였다. DEM을 보간하기 전 총 세 곳의 Sink를 발견하여 조정한 후 Filling하였으며 수치지형도와 정밀토양도로부터 초기 입력자료를 생성한 후 ASCII 파일로 변환하여 분포형 모형에 적용하였다. 또한 VfloTM 를 통해 구성한 격자망을 실제 흐름 방향을 고려하여 최종 유출구로 흐를 수 있도록 격자망을 재구성하였으며, 강우의 공간적 분포 방법으로 Cokriging 기법을 사용하였다. 분석 결과 격자 크기가 작은 경우 오히려 첨두유량이 작게 산정되었는데 이는 배수계통의 변화 및 수치지형도와는 다른 지표면 특성으로 인한 것으로 사료된다. 또한 배수구역의 최적화 결과 전반적으로 실측치와 유사한 값을 나타내었으며, 타 모형과 비교한 결과 비슷하거나 조금 나은 결과를 보였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.406-406
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• 2019

최근 전세계적으로 기후변화로 인해 가뭄의 발생 가능성이 높아지고 있으며 그에 대한 인적피해와 경제적 손실로 인한 피해액은 증가하는 추세이다. 특히, 국내의 충남지역은 최근 강수량이 평년대비 75% 수준으로 감소하고 있으며, 지속적인 가뭄이 발생하여 용수 확보에 어려움을 겪고 있다. 또한, 2015년에는 강수량 감소로 인해 보령댐을 상수원으로 사용하고 있는 충남 서북부지역 8개 시군에 용수 공급에 큰 차질이 있었다. 지속적인 가뭄상황이 반복되면서 정부 지자체 공공기관 등에서는 가뭄의 규모 및 단계에 따른 공간적 범위를 표출하는 가뭄 모니터링과 가뭄 전망 시스템을 구축하여 운영하고 있다. 다만 하천과 저수지를 연계하여 지역적 특성을 고려한 중규모 지역에 대한 가뭄전망 시스템은 부족한 실정이다. 이를 해결하고자 하천과 저수지에 대한 실시간 유출 및 물수지 분석기술을 이용하여 미래 무강수 조건에서 일단위 공급가능량, 공급량, 부족량, 잉여공급량, 가뭄위험등급을 전망하는 DOS(Drought Outlook System)을 개발하였다. 본 시스템은 지속적인 가뭄이 발생하고 있는 충남 서북부지역 8개 시군에 대한 436개의 하천유역을 구성하고 129개의 저수지를 대상으로 구축하였다. 기상자료는 기상청 ASOS 일 관측자료를 실시간으로 수집하여 티센법 기반의 436개 유역평균 일단위 강우량과 잠재증발산량을 산정하고 미래 90일에 대해서는 무강우와 평균 잠재증발산량을 적용하였다. TANK 모델과 물수지분석을 통해 과거 400일과 미래 90일에 대한 일단위 하천유량, 저수량, 부족량, 가뭄위험등급 등을 산정하여 매일 14시에 GIS기반 웹시스템에 표출된다. 본 시스템을 통해 하천유역 및 저수지에 대한 미래의 물공급 변화 및 가뭄위험 변화를 판단하고 추정할 수 있으며 추후 타지역 확장을 통해 전국에 대한 가뭄위험을 전망하고 가뭄대책수립에 기여 할 수 있을 것으로 판단된다.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.789-802
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• 2022

The purpose of this study is to present implications for effective operation of domestic school-based mental health services by comparing those in Singapore the United States, Australia. Based on reviewing the public data and previous article, researchers conducted a comparative study on the background, history, goal, and managing process of overseas and domestic organizations. The result of comparison in overseas cases suggests that the foundation of school-based mental health project was laid with the national health plan and detailed frame work for implementation. It was also discussed that domestic school-based mental health project is still in introduction stage, while foreign services were delivered efficiently through the leading agency and the cooperation between government ministries and institutions were active. It suggests that cooperation between government ministries, preparation of an effective operating system, and various approaches for students, guardians and teachers are need for domestic school-based mental health project.

• Smart Media Journal
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• v.11 no.9
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• pp.64-74
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• 2022

A number of studies related to underwater robots are being conducted to utilize marine resources. However, unlike ordinary drones, underwater robots have a problem that it is not easy to locate because the medium is water, not air. The monitoring and positioning program of underwater robots, an existing study for identifying underwater locations, has difficulty in locating and monitoring in small spaces because it aims to be utilized in large spaces. Therefore, in this paper, we propose a three-dimensional positioning program for continuous monitoring and command delivery in small spaces. The proposed program consists of a multi-dimensional positioning monitoring function and a ability to control the path of travel through a three-dimensional screen so that the depth of the underwater robot can be identified. Through the performance evaluation, a robot underwater could be monitored and verified from various angles with a 3D screen, and an error within the assumed range was verified as the difference between the set path and the actual position is within 6.44 m on average.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.2
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• pp.259-266
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• 2023

Global climate change is increasing, and the damage and scale of localized torrential rains are increasing. Pre-flood analysis simulation results should be derived from rainfall data through rainfall forecasts to prevent flood damage. In addition, it is necessary to control the use and management of flood response disaster prevention facilities through immediate decision-making. However, methods using spills and flood models such as XPSWMM and GATE2018 are limited due to professional usability and complex analytical procedures. Prototype (flood disaster prevention facility simulator) of this study is developed by calculating rainfall (short-term and long-term) using CBD software development methods. It is also expected to construct administrator and user-centric interfaces and provide GIS and visible data (graphs, charts, etc.).

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.63-65
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• 2023

본 논문에서는 FDG-PET 영상을 사용하는 딥러닝 네트워크를 이용하여 직장암 환자의 치료 후 완치를 예측하는 연구를 수행하였다. 직장암은 흔한 악성 종양 중 하나이지만 병리학적으로 완전하게 치료되는 가능성이 매우 낮아, 치료 후의 반응을 예측하고 적절한 치료 방법을 선택하는 것이 중요하다. 따라서 본 연구에서는 FDG-PET 영상에 합성곱 신경망(CNN)모델을 활용하여 딥러닝 네트워크를 구축하고 직장암 환자의 치료반응을 예측하는 연구를 진행하였다. 116명의 직장암 환자의 FDG-PET 영상을 획득하였다. 대상군은 2cm 이상의 종양 크기를 가지는 환자를 대상으로 하였으며 치료 후 완치된 환자는 21명이었다. FDG-PET 영상은 전신 영역과 종양 영역으로 나누어 평가하였다. 딥러닝 네트워크는 2차원 및 3차원 영상입력에 대한 CNN 모델로 구성되었다. 학습된 CNN 모델을 사용하여 직장암의 치료 후 완치를 예측하는 성능을 평가하였다. 학습 결과에서 평균 정확도와 정밀도는 각각 0.854와 0.905로 나타났으며, 모든 CNN 모델과 영상 영역에 따른 성능을 보였다. 테스트 결과에서는 3차원 CNN 모델과 종양 영역만을 이용한 네트워크에서 정확도가 높게 평가됨을 확인하였다. 본 연구에서는 CNN 모델의 입력 영상에 따른 차이와 영상 영역에 따른 딥러닝 네트워크의 성능을 평가하였으며 딥러닝 네트워크 모델을 통해 직장암 치료반응을 예측하고 적절한 치료 방향 결정에 도움이 될 것으로 기대한다.

• The Journal of the Petrological Society of Korea
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• v.22 no.1
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• pp.49-62
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• 2013

The Dongmakgol Tuff is divided into 8 lithofacies based on their grain size and depositional structures: massive tuff breccia(TBm), welded tuff and lapilli tuff(LTw), rheomorphic tuff and lapilli tuff(LTr), massive lapilli tuff(LTm), stratified lapilli tuff(LTs), gradedly bedded lapilli tuff(LTg), crudely bedded lapilli tuff(LTb) and massive fine tuff(Tm). They can be divided into 3 pyroclastic rock group based on their constituents of the lithofacies. The lower group(LI) is composed of LTm, LTw and LTr, which are interpreted to have resulted from emplacement of voluminous pyroclastic flows due to ignimbrite-form eruption to boiling-over eruption. The middle group(LT+MI) consists of LTs, LTg and LTm associated with Tm in the lower part, and of LTm, LTw and LTr in the middle and upper parts; these suggest that started with deposition of pyroclastic surges from phreatoplinian eruption by poor eternal water, passed through emplacement of pyroclastic flows from ignimbrite-form eruption and ended with deposition of voluminous pyroclastic flows from boiling-over eruption. The upper group(lUT+uUT+UI) is composed of LTs, LTg and Tm in the lowermost, TBm, LTb, LTb and Tm in the lower part, and LTm and LTw in the middle and upper part, suggesting that began with deposition of surges from phreatoplinian eruption, passed through deposition of pumice- and ash-fallouts from plinian eruption and transformed into emplacement of pyroclastic flows due to boiling-over eruption. As result, eruptive processes in the Dongmakgol Tuff approximately began with phreatoplinian or/and plinian eruption, transformed into ignimbrite-forming eruption and proceeded into boiling-over eruption in each volcanism, but proceeded presumably without phreatoplinian or plinian eruption in the earlier stage of 1st volcanism.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.30-43
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• 2018

Many studies have been carried out to retrieve images using colors, shapes, and textures which are characteristic of images. In addition, there is also progress in research related to the disease images of the crop. In this paper, to be a help to identify the disease occurred in crops grown in the agricultural field, we propose a similarity-based crop disease search system using the diseases image of horticulture crops. The proposed system improves the similarity retrieval performance compared to existing ones through the combination descriptor without using a single descriptor and applied the weight based calculation method to provide users with highly readable similarity search results. In this paper, a total of 13 Descriptors were used in combination. We used to retrieval of disease of six crops using a combination Descriptor, and a combination Descriptor with the highest average accuracy for each crop was selected as a combination Descriptor for the crop. The retrieved result were expressed as a percentage using the calculation method based on the ratio of disease names, and calculation method based on the weight. The calculation method based on the ratio of disease name has a problem in that number of images used in the query image and similarity search was output in a first order. To solve this problem, we used a calculation method based on weight. We applied the test image of each disease name to each of the two calculation methods to measure the classification performance of the retrieval results. We compared averages of retrieval performance for two calculation method for each crop. In cases of red pepper and apple, the performance of the calculation method based on the ratio of disease names was about 11.89% on average higher than that of the calculation method based on weight, respectively. In cases of chrysanthemum, strawberry, pear, and grape, the performance of the calculation method based on the weight was about 20.34% on average higher than that of the calculation method based on the ratio of disease names, respectively. In addition, the system proposed in this paper, UI/UX was configured conveniently via the feedback of actual users. Each system screen has a title and a description of the screen at the top, and was configured to display a user to conveniently view the information on the disease. The information of the disease searched based on the calculation method proposed above displays images and disease names of similar diseases. The system's environment is implemented for use with a web browser based on a pc environment and a web browser based on a mobile device environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.1-8
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• 2020

In recent years, due to the exponential increase in internet data, many fields such as deep learning have developed, but side effects generated as commercial advertisements, such as viral marketing, have been discovered. This not only damages the essence of the internet for sharing high-quality information, but also causes problems that increase users' search times to acquire high-quality information. In this study, we define advertisement as "a text that obscures the essence of information transmission" and we propose a model for filtering information according to that definition. The proposed model consists of advertisement filtering and advertisement filtering performance improvement and is designed to continuously improve performance. We collected data for filtering advertisements and learned document classification using KorBERT. Experiments were conducted to verify the performance of this model. For data combining five topics, accuracy and precision were 89.2% and 84.3%, respectively. High performance was confirmed, even if atypical characteristics of advertisements are considered. This approach is expected to reduce wasted time and fatigue in searching for information, because our model effectively delivers high-quality information to users through a process of determining and filtering advertisement paragraphs.