• 한국농공학회:학술대회논문집
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• 한국농공학회 2000년도 학술발표회 발표논문집
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• pp.384-389
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• 2000

A artificial neural network model was developed to analyze and forecast the flow fluctuation at small streams in the Balan watershed. Backpropagation neural networks were found to perform very well in forecasting daily streamflows. In order to deal with slow convergence and an appropriate structure, two algorithms were proposed for speeding up the convergence of the backpropagation method, and the Bayesian Information Criterion(BIC) was proposed for obtaining the optimal number of hidden nodes. From simulations using daily flows at the HS#3 watershed of the Balan Watershed Project, which is 412,5 ㏊ in size and relatively steep in landscape, it was found that those algorithms perform satisfactorily.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.1045-1048
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• 2000

This paper presents the application of the wavelet transform analysis and the neural network method to the phonocardiogram (PCG) signal. Heart sound is a acoustic signal generated by cardiac valves, myocardium and blood flow and is a very complex and nonstationary signal composed of many source. Heart sound can be discriminated normal heart sound and heart murmur. Murmurs have broader frequency bandwidth than the normal ones and can occur at random position of cardiac cycle. In this paper, we classified the group of heart sound as normal heart sound(NO), pre-systolic murmur(PS), early systolic murmur(ES), late systolic murmur(LS), early diastolic murmur(ED). And we used the wavelet transform to shorten artifacts and strengthen the low level signal. The ANN system was trained and tested with the back- propagation algorithm from a large data set of examples-normal and abnormal signals classified by expert. The best ANN configuration occurred with 15 hidden layer neurons. We can get the accuracy of 85.6% by using the proposed algorithm.

• Journal of Information Technology Applications and Management
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• 제24권3호
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• pp.93-105
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• 2017

Demands of cosmetics are affected not only by the well-known elements such as brand, price, and customer's consumption capacity, but also by some latent factors, for example, weather and air environment. Due to complexity and dynamic changes of the above factors, their influences can hardly be estimated in an accurate way by the traditional approaches such as survey and questionnaires. Through modeling and statistical analysis of big data, this article studied the impacts of weather condition and air quality on customer flow and sales of the cosmetics distributors in China, and found several hidden influencing factors. It provided a big-data based method for the analysis of unconventional factors on cosmetics marketing in the changing weather condition and air environment.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2001년도 봄 학술발표논문집 Vol.28 No.1 (A)
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• pp.769-771
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• 2001

침입의 궁극적 목표는 루트 권한의 획득이라고 할 수 있는데 최근 유행하고 있는 버퍼플로우(Buffer Over flow)등이 대표적이다. 최근 날로 다양화되는 이런 침입방법들에 대응하기 위해 비정상행위 탐지기법 연구가 활발한데 대표적인 방법으로는 통계적 기법과 전문가시스템, 신경망 등을 들 수 있다. 본 논문에서 제안하는 침입탐지시스템은 권한 이동 관련 이벤트의 추출 기법을 이용하여 Solaris BSM 감사 기록에서 추출된 정보 이벤트들을 수집한 후 은닉 마르코프 모델(HMM)로 모델링하여 정상행위 모델들을 만든다. 추론 및 판정시에는 이미 만들어진 정상행위 모델을 사용하여 새로 입력된 사용자들의 시퀀스를 비교 평가하고, 이를 바탕으로 정상 권한이동과 침입시의 권한이동의 차이를 비교하여 침입여부를 판정한다. 실험결과 HMM만을 사용한 기존 시스템에 비해 유용함을 알 수 있었다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.354-354
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• 2022

딥러닝(Deep Learning)은 일반적으로 인공신경망(Artificial Neural Network) 를 의미하는데, 이에 따른 결과는 데이터의 양, 변수, 학습모델의 학습횟수, 은닉층(Hidden Layer)의 개수 등 여러 요소로 인해 결정된다. 본 연구에서는 물리적 장기유출 모형인 SWAT의 결과를 참값으로 LSTM모형의 매개변수인 은닉층 갯수와 학습횟수등의 시나리오를 바탕으로 검보정을 수행하였으며, 최적의 목적함수를 갖는 매개변수를 도출하였다. 이를 이용하여 유량지속곡선을 도출한결과를 SWAT의 결과와 비교해본 결과 매우 높은 상관성을 도출하였으며 이를 통해 수자원분야에서 인공신경망의 활용 가능성을 확인하였다.

• KSBB Journal
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• 제16권5호
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• pp.452-458
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• 2001

생물공정에서 암모니아 농도를 제거하기 위해 NN 제어기를 개발하였고 기존의 PID 제어기와 비교하였다. 특히, 생물반응기내 암모니아 농도를 온라인 모니터링하기 위해 암모니아-FIA 장치를 사용하였으며, 이 장치의 분석 오차, 분석 시료의 체류 시간 등의 제어 특성에 대한 영향 computer simulation을 통해 비교, 고찰하였다. 또한 computer simulation에 의해 생물공정에 적합한 인공 신경망 제어구조를 고찰하였고, 3-2-1 구조의 NN 제어기가 PID 제어기보다 우수함을 알수 있었다. 3-2-1 구조의 NN 제어기를 이용하여 모사 생물공정 및 yeast 발효공정에서 암모니아 농도를 제어하여 그 특성을 고찰하였다. 본 연구로부터 미생물의 비선형성장 특성을 가진 생물공정에서 기질의 농도를 제어하기 위해서는 3-2-1 구조의 인공 신경망 제어기가 적합함을 알 수 있었다.

• 한국산업정보학회논문지
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• 제17권1호
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• pp.31-38
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• 2012

Next generation cellular applications and smart phone usage generate very heavy wireless data traffic. It becomes ineluctable for mobile network operators to have multiple core network entities such as Serving Gateway and Packet Data Network Gateway in 4G-LTE to share this high traffic generated. A typical configuration consists of multiple serving gateways behind a load-balancer which would determine which serving gateway would service a end-users'request. Such hardware is expensive, has a rigid policy set, and is a single point of failure. Another perspective of today's increasingly high data traffic is that besides it is being widely accepted that the high bandwidth L TE provides is creating bottlenecks for service providers by the increasing user bandwidth demands without creating any corresponding revenue improvements, a hidden problem that is also passively advancing on the newly emerging 4G-LTE that may need more immediate attention is the network signaling traffic, also known as the control-plane traffic that is generated by the applications developed for smartphones and tablets. With this as starting point, in this paper, we propose a solution, by a new approach considering OpenFlow switch connected to a controller, which gains flexibility in policy, costs less, and has the potential to be more robust to failure with future generations of switches. This also solves the problem of scaling the control-plane traffic that is imperative to preserve revenue and ensure customer satisfaction. Thus, with the proposed architecture with OpenFlow, mobile network operators could manipulate the traffic generated by the control-plane signaling separated from the data-plane, besides also reducing the cost in installing multiple core-network entities.

• 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.

• 대한원격탐사학회지
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• 제18권1호
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• pp.1-12
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• 2002

Landslide prediction modeling has been regarded as one of the important environmental applications in GIS. While, landslide stability in a certain area as collateral process for prediction modeling can be characterized by DEM-based hydrological features such as flow-direction, flow-accumulation, flow-length, wetness index, and so forth. In this study, Slope-Area plot methodology followed by stability index mapping with these hydrological variables is firstly performed for stability analysis with actual landslide occurrences at Boeun area, Korea, and then Landslide prediction modeling based on likelihood ratio model for landslide potential mapping is carried out; in addition, KOMPSAT EOC imagery is used to detect the locations and scalped scale of Landslide occurrences. These two tasks are independently processed for preparation of unbiased criteria, and then results of those are qualitatively compared. As results of this case study, land stability analysis based on DEM-based hydrological variables directly reflects terrain characteristics; however, the results in the form of land stability map by landslide prediction model are not fully matched with those of hydrologic landslide analysis due to the heuristic scheme based on location of existed landslide occurrences within prediction approach, especially zones of not-investigated occurrences. Therefore, it is expected that the resets on the space-robustness of landslide prediction models in conjunction with DEM-based landslide stability analysis can be effectively utilized to search out unrevealed or hidden landslide occurrences.

• 비교문화연구
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• 제21권
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• pp.165-188
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• 2010

One of the things that should be done first in establishing the cosmic life culture is to reflect on the old human-oriented culture. If the cosmic life culture absolutizes everything except for humans according to the logic of reason, its foundation will weaken or eventually get lost. Separating humans from the universe is just like separating life from it. Given that all life, whether it is humans or the earth, originated from the universe, such an effort for separation merely values an individual life by excluding all life or whole life. When the human body and the cosmic chi' blood are not in an active flow, it means there is a problem with life. What is in the greatest need in such a case is the sincere human mind that follows the principle of cosmic life. It is like the sincerity found in the pasonri singer, who mellows all the hardships and difficulties in the world out and create songs out of them like the shadow. It is the pansori singer's shadow that changes the universe. It is only when the extreme force of human mind communicates with that of the universe that the cosmic life or cosmic life culture can be created. In that sense, it is urgent to create life out of the universe inside me and create a universe out of all life in and outside me. It is such a grave plan in human history in that it involves finding the "Sanal" which is the core of life living hidden inside the body whose life force gradually goes away or inside the universe, and creating the culture of Bokseung in which it bursts out. The most important thing in life is the flow, and the mankind is currently standing in the life flow of the massive universe's chaosmos. The greatest task the mankind is currently faced with is to think over how to deal with the period of Big Chaos in the massive universe's chaosmos reversely and establish the cosmic life culture anew.