• Journal of Astronomy and Space Sciences
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• v.19 no.4
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• pp.319-326
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• 2002

Laboratory tests have been carried out for investigation of the spectroscopic characteristics at visible wavelength of 12 common satellite materials used in satellite bus and payload. The obtained spectral data show that the materials can be classified and identified since their spectral features and albedos distinctly differ among them. It is suggested that the result of the laboratory tests for the satellite materials can be used for the predictions of material types, material composition ratios, sizes, and masses in comparison with the spectral data obtained from observations of new satellites or space debris.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.2
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• pp.27-32
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• 2018

One of the crucial issues in mobile edge cloud computing environments is to monitor mobile devices. Due to the inherit properties of mobile devices, they are prone to unstable behavior that leads to failures. In order to satisfy the service level agreement (SLA), the mobile edge cloud administrators should take appropriate measures through a monitoring scheme. In this paper, we propose a monitoring scheme of mobile devices based on artificial intelligence in mobile edge cloud computing environments. The proposed monitoring scheme is able to measure faults of mobile devices based on previous and current monitoring information. To this end, we adapt the hidden markov chain model, one of the artificial intelligence technologies, to monitor mobile devices. We validate our monitoring scheme based on the hidden markov chain model. The proposed monitoring scheme can also be used in general cloud computing environments to monitor virtual machines.

• Korean Journal of Environmental Agriculture
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• v.18 no.1
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• pp.77-82
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• 1999

Three floating islands have been constructed for water quality improvement for a polluted irrigation reservoir. Each floating island consists of 10 segments. Each segment hay an area of $16m^2$(4×4m) and is made of wood frames and floats(polystyrene foam). We planted three species of aquatic macrophytes(Typha angustifolia, Zizania latifolia, and Phragmites australis) in floating island on June, 1998. They grew very well without death. We would like to evaluate Phragmites australis is the most suitable aquatic macrophyte that could be planted in a floating island because it maintained the best balance of its root and shoot among them. During their grown period, net primary productivity of Typha angustifolia was $962gDM/m^2$, Zizania latifolia was $1,115gDM/m^2$, and Phragmites australis was $523gDM/m^2$. From these data, it would be estimated to 5.0Kg uptake of nitrogen by aquatic macrophytes and phosphorus 0.8Kg in 3 floating islands. The floating islands worked well as a habitat of fish and prawns. Many kinds of insect lived on the floating islands. The floating island has not only the function of water quality treatment but also several advantages: improvement of landscape and species diversity; low cost of maintenance; low technology; unnecessary of energy; less susceptible to variations in pollutant loading. It could be evaluated a good measure of water quality improvement for an irrigation reservoir. However, it should be intensively studied to develop more light, strong, durable and low-priced frames for efficient floating islands.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.522-526
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• 1998

본 논문은 가정용 배전반 시스템을 디지털식으로 구현하고, 기존의 디지털식 배전반 시스템에 없는 월 수요전력량 예측과 화재발생의 원인 중에 하나인 옥내 전선선로의 결함을 신경회로망으로 검출하여 차단하는 인공지능형 가정용 배전반 시스템을 하드웨어로 구현하고 실험하였으며, 그 결과를 제시하였다.

• Korean Journal of Organic Agriculture
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• v.24 no.4
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• pp.759-771
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• 2016

We compared the fruit set and the quality of the 'Niitaka' pear (Pyrus pyrifolia Nakai) among flowers pollinated by two bee species (Apis mellifera and Bombus terrestris) and pollinated artificial. The artificial pollination rate was 1.3 to 1.9 times higher than the bee pollination rate. Moreover, the artificially pollinated flowers produced fruit that was 5 to 10% higher in weight, 2 to 3% larger in size, and had a higher fruit shape index (L/D) than fruit pollinated by the bees. On economic analysis, net profit from insect pollinator was 93.5 to 97.1% of net profit from artificial pollination. Therefore, artificial pollination is more efficient than bee pollination in 'Niitaka' pear. However, regarding fruit quality and net profit, these results suggest that bee pollination can be an good alternative to artificial pollination in 'Niitaka' pear.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.116-116
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• 2012

하천유역 내의 인자를 이용하여 댐의 하천유량(stream flow)을 예측하는 일은 수문특성의 연구와 자연재해에 대한 대비 및 수공구조물과 방재시설의 설계 시 중요한 역할을 한다. 이러한 연구는 과거부터 활발히 이루어졌으며, 아직도 보다 높은 정확도의 결과를 얻기 위해 많은 연구들이 이루어지고 있다. 특히 기존의 유역 내 자료를 통해 비선형적 모델인 인공신경망(artificial neural network)을 이용한 하천유량을 예측하는 연구 역시 활발히 이루어지고 있다. 본 연구의 목적은 여러 유역인자들 중 하천유량에 가장 영향을 미치는 변수를 추출하고 보다 정확한 예측모델을 구축하는 것이다. 기존의 입력자료 선정기법중의 하나인 상호정보량(mutual information)과 수문기상자료의 비선형 동역학적 성분을 추출하는 웨이블렛 변환(wavelet transform)을 사용하여 인공신경망에 적용시켰다. 인공신경망을 적용하는 경우, 수문자료에 있어서 변수의 선택과 자료의 상태가 강우예측의 결과에 큰 영향을 미친다. 이러한 변수의 선택에 있어서 상호정보량을 바탕으로 한 인공신경망 입력변수 선택기법이 많이 사용되고 있다. 일반적으로 시계열자료는 경향성(trend), 주기성(periodicity) 및 추계학적 성분(stochastic component)의 선형조합으로 가정될 수 있으며, 특히 경향성과 주기성은 시계열 모형을 위해 제거되어야 할 결정론적 성분으로 취급한다. 즉. 수문 기상자료에 포함되어 있는 경향성과 주기성과 같은 비선형 동역학적 잡음(nonlinear dynamical noise)을 제거하고 입력자료의 카오스적 거동을 보이는 성분을 분리하기 위해 웨이블렛 변환을 사용하였다. 대상유역은 한강 유역에 포함되어 있는 충주댐으로 선택하였다. 유역 내 다양한 인자들과 하천유량사이의 상호정보량을 구해 영향력이 가장 큰 변수를 추출하고, 그 자료를 웨이블렛 변환을 적용하여 인공신경망의 입력자료로 사용하였다. 본 논문에서는 위와 같은 과정을 이용해 추정한 하천유량 결과와 기존의 방법인 상호정보량을 이용해 인공신경망을 적용한 결과를 실제자료와 비교하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.45-45
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• 2018

오염물의 혼합거동을 해석하기 위해 물리기반 모델을 이용하는 경우 모델을 구축하고 운용하는데 많은 시간과 재정이 소요되며 현장검증을 통한 검증이 반드시 필요하다. 하지만 데이터 기반 모델의 경우 축적된 데이터만으로도 예측을 수행할 수 있으며 물리기반모델에 비해 결정해야할 입력인자가 적어 모델운용이 용이하다는 장점이 있다. 다양한 데이터 모델 중 인공신경망(ANN) 모델은 데이터가 가지는 불확실성 및 비정상성, 복잡한 상호관련성에 효과적으로 대응할 수 있는 모델로 수자원 및 환경 분야에서 자주 사용되고 있다. 본 연구에서는 인공신경망 모델을 이용하여 지천유입이 있는 대하천의 수질인자 (pH, 전기전도도, DO, chl-a)를 예측하였다. 다른 데이터기반 모델과 같이 인공신경망 모델 또한 수집된 데이터 질에 크게 영향을 받으며, 내부 입력인자의 선택이 모델의 예측 결과에 큰 영향을 미친다. 이러한 인공신경망 모델의 특성을 바탕으로 예측모형의 정확도를 향상하기 위해서는 크게 데이터 처리부분과 모델구축 부분에서의 접근이 필요하다. 본 연구에서는 데이터 처리 과정에서 연구대상지점의 각각의 수질인자가 가지는 분포 특성을 유지하기 위해 층화표츨추출법을 이용하여 데이터를 구성하였다. 모델의 구축 과정에서는 초기가중치 값의 영향을 줄이기 위해 앙상블기법을 사용하였으며, 좀 더 견고하고 정확한 결과를 예측하기 위해 탄력적 역전파알고리즘을 추가하였다. 추가적으로 합류 후 본류의 미 계측지역 수질 예측 정확도 향상을 위해 본류의 수질인자뿐만 아니라 지류의 수질인자를 입력자료로 사용하여 모의를 수행하였다. 또한 동일 구간에서 수행한 현장추적자실험 자료를 이용하여 수질인자의 분포특성을 비교, 검증하였다. 개발된 모델을 이용하여 낙동강과 금호강 합류부 하류의 수질인자를 예측한 결과 지류의 수질인자를 입력자료로 추가한 경우 예측의 정확도가 증가하였으며, 현장실험 자료를 통해 밝혀진 오염물의 거동현상을 인공신경망 모델로도 동일하게 재현하는 것으로 나타났다. 본 연구에서 제안한 인공신경모델을 이용한다면 물리기반 수치모델을 대체하여 지천으로 유입된 오염물의 거동을 정확하고 효율적으로 파악할 수 있을 것이다.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.227-235
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• 2024

In the era of the information revolution, the need for artificial intelligence convergence education is emerging in the trend of global change. Therefore, in this paper, a physical computing programming education method that combines artificial intelligence was developed and applied. The control group was provided with physical computing programming education that did not converge with artificial intelligence, and the experimental group developed and applied a physical computing programming education method that fused artificial intelligence to analyze the impact on elementary school students' computing thinking ability. As a result, it was confirmed that physical computing programming education fused with artificial intelligence had a more positive effect on enhancing elementary school students' computational thinking skills compared to physical computing programming education without artificial intelligence.

• Journal of Radiation Protection and Research
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• v.36 no.2
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• pp.79-85
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• 2011

OThe purpose of this article was to measure and compare the value of the metal artifact reduction (MAR) algorithm by Dual energy(kVp switching) CT (Computed Tomography) for non using MAR and we introduced new variable Dual energy CT applications through a clinical scan. The used equipment was GE Discovery 750HD with Dual-Energy system(kVp switching). CT scan was performed on the neck and abdomen area subject for patients. Studies were from Dec 20 2010 to Feb 10 2011 and included 25 subject patients with prosthesis. We were measured the HU (Hounsfield Unit) and noise value at metal artifact appear(focal loss of signal and white streak artifact area) according to the using MAR algorithm. Statistical analyses were performed using the paired sample t-test. In patient subject case, the statistical difference of showing HU was p=0.01 and p=0.04 respectively. At maximum black hole artifact area and white streak artifact area according to the using MAR algorithm. However noise was p=0.05 and p=0.04 respectively; and not the affected black hole and white streak artifact area. Dual Energy CT with the MAR algorithm technique is useful reduce metal artifacts and could improve the diagnostic value in the diagnostic image evaluation of metallic implants area.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.241-249
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• 2022

Artificial intelligence is applied not only to the daily life of individuals but also to all industries, and it is no wonder that the age of artificial intelligence has arrived. Therefore it is important to understand the factors that influence the acceptance of AI. This study analyzes whether "AI Effect" which recognizes that commercialized or familiar artificial intelligence is no longer artificial intelligence, affects the acceptance of artificial intelligence and proposes an acceptance plan based on the results. Two experiments were conducted. The first experiment was conducted on 105 adults in the result it was found that 32.4% (34 people) had AI Effect, AI Effect existed in 43.6% (24 people) of women and 20% (10 people) of men, that is, the proportion of AI Effect exsitence in women is about twice as high.and AI Effect exists when the level of AI knowledge is low. The second experiment was conducted 240 adults and 85 participants with AI Effect were selected. We found the group that recognized experience of AI accepted AI more actively. Understanding of AI Effect is expected to suggest companies' views in order to enhance AI capabilities and acceptance. In addition, future studies are expected on considering individual differences or related to acceptance attitudes.