• 대한원격탐사학회지
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• 제37권5_1호
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• pp.1061-1070
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• 2021

본 연구에서는 국내 농업지역에 대한 작물재배지역의 분류를 위하여 FC-DenseNet 모델에 attention gate를 적용하여 딥러닝 모델의 성능을 향상시키고자 하였다. Attention gate는 특징맵의 공간/분광적 중요도에 따른 가중치를 추가적으로 학습하여 딥러닝 모델의 학습을 용이하게 하고, 모델의 성능을 향상시킬 수 있다. Attention gate를 FC-DenseNet의 스킵 연결 부분에 추가한 딥러닝 모델을 이용하여 양파 및 마늘 지역의 작물분류를 수행하였다. PlanetScope 위성영상을 이용하여 훈련자료를 제작하였으며, 훈련자료의 불균형 문제를 해결하기 위하여 전처리 과정을 적용하였다. 다양한 평가자료를 이용하여 작물재배분류 결과를 평가한 결과, 제안된 딥러닝 모델은 기존의 FC-DenseNet과 비교하여 효과적으로 양파 및 마늘 지역을 분류할 수 있는 것을 확인하였다.

• The Korean Journal of Ecology
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• 제9권1호
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• pp.41-50
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• 1986

The net primary production in the Korean peninsula was estimated by Miami model, Montreal model and Kira's model, based on 148 meteorological data. The modes in frequency distribution of the values calculated by Montreal and Miami model were found at 1,500g/m2/yr. class and at one step high class in 100g. interval, while by Kira's madel at 1,700g/m2/yr. class. The relationships between values by Miami model(X) and those by Motreal model (Ym) and Kira's model(Yk) can be expressed as follows: Ym=0.365X+944.7, Yk=0.462 X+1006.9 and Yk=1.282Ym-211.5. The total amount of the net primary production in 218,583.4km2, 98.9% of the whole area(220,951 km2) of the Korean Peninsula, was estimated as 290,691,407 tons/yr. by Miami model, 310,751,566 tons/yr by Montreal model and 352,071,901 tons/yr by Kira's model. Therefore, it is reasonable that the organic substance over 300 million-tons is added yearly in the Korean Peninsula, because only 1.1% of the whole area no calculated. In additiion, the net primary production amount of Han-river basin was estimated as ca. 38 million-tons, whether calculated with the meteorological data in level of the Korean Peninsula or with more detail data.

• 전자공학회논문지B
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• 제33B권12호
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• pp.84-94
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• 1996

In this work, a fuzzy petri net model for modeling a general form of fuzzy production system which consists of chaining fuzzy production rules and so requires multistage reasoning process is presented. For the obtained fuzzy petri net model, the net will be transformed into some matrices, and also be systematically led to an algebraic form of a state equation. Since it is fond that the approximate reasoning process in fuzzy systems corresponds to the dynamic behavior of the fuzzy petri net, it is further shown that the multistage reasoning process can be carried out by executing the state equation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 추계학술대회 논문집 학회본부
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• pp.136-138
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• 1997

This paper proposes a design method to improve the performance of Indirect Adaptive Controllers using a CP net. This hybrid control architecture consists of Indirect Adaptive Controllers and CP net Controller. The performance of a single Adaptive Controller, multi Adaptive Controllers and the proposed model is compared by control problems. The simulation results show that the proposed model is superior to the others in most cases, in regard of not only learning speed but also control problems.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2008년도 제38차 하계학술발표논문집 16권1호
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• pp.11-16
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• 2008

본 논문은 온톨로지(ontology) 작성에 사용되는 RDF(Resource Description Framework) 모델을 CPN(Colored Petri Net) 모델로 변환하여 표현하는 방법을 제안하고, 페트리 넷 시뮬레이션으로 RDF의 의미를 해석하여 RDF 질의문에 답할 수 있음을 보인다. 또한, 어떠한 RDF 모델도 CPN 모델로의 변환이 가능하다는 제안 방법의 완전성과 무결성을 소개하고, 제안한 방법으로 구축된 CPN 모델에서 RDF 질의에 대해 정확하게 결과를 구하는 방법을 제시한다.

• 한국멀티미디어학회논문지
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• 제22권12호
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• pp.1347-1355
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• 2019

Deep learning approach based on convolution neural network (CNN) has extensively studied in the field of computer vision. However, periocular feature extraction using CNN was not well studied because it is practically impossible to collect large volume of biometric data. This study uses the ResNet model which was trained with the ImageNet dataset. To overcome the problem of insufficient training data, we focused on the training of multi-layer perception (MLP) having simple structure rather than training the CNN having complex structure. It first extracts features using the pretrained ResNet model and reduces the feature dimension by principle component analysis (PCA), then trains a MLP classifier. Experimental results with the public periocular dataset UBIPr show that the proposed method is effective in person authentication using periocular region. Especially it has the advantage which can be directly applied for other biometric traits.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2002년도 봄 학술발표회 논문집
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• pp.139-146
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• 2002

The characteristics and prediction model for the shear strength of unsaturated residual soils was studied. In order to investigate the influence of the net normal stress on the shear strength, unsaturated triaxial tests and SWCC tests were carried out varying the net normal stress, and the experimental data for unsaturated shear strength tests were compared with predicted shear strength envelopes using existing prediction models. It was shown that the soil - water characteristic curve and the shear strength of the unsaturated soil varied with the change of the net normal stress. Therefore, to achieve a truly descriptive shear strength envelope for unsaturated soils, tile effect of the normal stress on the contribution of matric suction to the shear strength has to be taken into consideration. In this paper, a modified prediction model for the unsaturated shear strength was proposed.

• 한국정밀공학회지
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• 제14권1호
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• pp.168-173
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• 1997

A process planning system that generates alternative process plans offers multiple process plans for a part, thereby provides the flexibility to cope with the changes in shop floor status. In this paper, we intro- duce the concept of process net as a model for the generation of alternative process plans. We also show the usefulness of process net model in generating alternative process plans by implementing the developed sys- tem to construct process net, and devising an algorithm to generate alternative process plans for rotational parts.

• 한국멀티미디어학회논문지
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• 제20권8호
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• pp.1447-1455
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• 2017

In a trawl-net simulation, it is very important to process the physical phenomenons resulting from real collisions between a net and fishes. However, because it is very difficult to reconstruct the surface with mass points, many researchers have generally detect the collision using an approximation model employing a sphere, a cube or a cylinder. These approaches occur often result in inaccurate movements of a fish due to the difference between a real-net and a designed-net. So, many systems have manually adjusted a net surface based on actual measurements of mass points. These methods are very inefficient because it needs much times in an adjustment and also causes more incorrect inputs according to a rapid increment in the number of points. Therefore, in this paper, we propose a reconstruction method that it semi-automatically reconstructed trawl-net surfaces using the equation of motion at each mass point in a mass-spring model. To get an easy start in a beginning step of the spread, it enables users to get interactive adjustment on each mass point. We had designed a trawl-net model using geometrical structures of trawl-net and then automatically reconstructed the trawl-net surface using scale-space meshing techniques. Last, we improve the accuracy of reconstructed result by correction user interaction.

• 스마트미디어저널
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• 제11권5호
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• pp.26-37
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• 2022

본 논문에서는 시설재배 작물 중 딸기의 초기 병해를 방제하고자 이미지를 자동으로 취득하고, EfficientNet 모델을 활용해 병해를 분석하여 농민에게 병해 여부를 알려주고, 전문가를 통한 병해 진단 서비스를 제안한다. 딸기 생육단계의 이미지를 취득하고, 학습된 EfficientNet 모델을 활용해 병해 진단 분석결과를 농민의 애플리케이션으로 전송 후 전문가의 피드백을 신속하게 받을 수 있다. 데이터 세트로는 실제 시설재배를 운영하는 농민을 섭외하여 시스템을 이용해 이미지를 취득하였고, 핸드폰으로 촬영한 이미지의 초안을 활용하여 데이터가 부족한 문제를 해결했다. 실험 결과 EfficientNet B0부터 B7까지의 정확도는 유사하여 추론 속도가 가장 빠른 B0를 채택했다. 성능향상을 위해 ImageNet으로 사전학습 된 모델을 사용해 Fine-tuning 했고, 100 Epoch부터 급격한 성능향상을 확인했다. 제안하는 서비스는 초기 병해를 빠르게 탐지하여 생산량을 증대시킬 것으로 기대한다.