• 우주기술과 응용
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• 제2권2호
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• pp.67-80
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• 2022

최근의 우주개발기술 선진국들은 우주의 평화적 이용이라는 보편적 가치를 넘어서 자국의 이익을 극대화하기 위한 발판으로 우주의 전략적 활용에 더욱 더 집중하고 있으며, 조기경보 위성과 같이 지상에서 발사된 화염 정보를 이용하여 우주로 발사된 발사체의 실시간 감시와 궤적 추적 기능 등을 담당하는 위성들을 지속적으로 개발해 오고 있다. 본 연구에서는 이러한 조기경보 위성에서 발사체의 궤적을 실시간으로 추정할 수 있는 알고리즘을 진화연산이라는 인공지능 기법을 적용하여 제안하고, 이러한 비행 궤적 추정 알고리즘을 비행 궤적 추정 시스템의 시뮬레이터를 통하여 임의의 발사체 비행 궤적에 적용함으로써 제안된 방법의 성능과 특징을 입체적으로 확인하고자 한다.

• Nuclear Engineering and Technology
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• 제54권4호
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• pp.1374-1381
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• 2022

Under the influence of nuclear radiation, the reliability of steam generators (SGs) is an important factor in the efficiency and safety of nuclear power plant (NPP) reactors. Motion planning that remotely manipulates an SG mobile tube-inspection robot to inspect SG heat transfer tubes is the mainstream trend of NPP robot development. To achieve motion planning, conditional traversal is usually used for base position optimization, and then the A^* algorithm is used for path planning. However, the proposed approach requires considerable processing time and has a single expansion during path planning and plan paths with many turns, which decreases the working speed of the robot. Therefore, to reduce the calculation time and improve the efficiency of motion planning, modifications such as the matrix method, improved parent node, turning cost, and improved expanded node were proposed in this study. We also present a comprehensive evaluation index to evaluate the performance of the improved algorithm. We validated the efficiency of the proposed method by planning on a tube sheet with square-type tube arrays and experimenting with Model SG.

• Journal of Nutrition and Health
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• 제55권1호
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• pp.1-9
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• 2022

In the past few decades, great progress has been made on understanding the interaction between nutrition and health status. But despite this wealth of knowledge, health problems related to nutrition continue to increase. This leads us to postulate that the continuing trend may result from a lack of consideration for intra-individual biological variation on dietary responses. Precision nutrition utilizes personal information such as age, gender, lifestyle, diet intake, environmental exposure, genetic variants, microbiome, and epigenetics to provide better dietary advices and interventions. Recent technological advances in the artificial intelligence, big data analytics, cloud computing, and machine learning, have made it possible to process data on a scale and in ways that were previously impossible. A big data platform is built by collecting numerous parameters such as meal features, medical metadata, lifestyle variation, genome diversity and microbiome composition. Sophisticated techniques based on machine learning algorithm can be used to integrate and interpret multiple factors and provide dietary guidance at a personalized or stratified level. The development of a suitable machine learning algorithm would make it possible to suggest a personalized diet or functional food based on analysis of intra-individual metabolic variation. This novel precision nutrition might become one of the most exciting and promising approaches of improving health conditions, especially in the context of non-communicable disease prevention.

• Nuclear Engineering and Technology
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• 제55권6호
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• pp.2222-2229
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• 2023

Radon and radon progeny being natural radioactive pollutants, seriously affect the health of uranium miners. Radon reduction by ventilation is an essential means to improve the working environment. Firstly, the relational model is built between the radon exhalation rate of the loose body and the ventilation parameters in the stope with radon percolation-diffusion migration dynamics. Secondly, the model parameters of radon exhalation dynamics are uncertain and described by triangular membership functions. The objective functions of the left and right equations of the radon exhalation model are constructed according to different possibility levels, and their extreme value intervals are obtained by the immune particle swarm optimization algorithm (IPSO). The fuzzy target and fuzzy constraint models of radon exhalation are constructed, respectively. Lastly, the fuzzy aggregation function is reconstructed according to the importance of the fuzzy target and fuzzy constraint models. The optimal control decision with different possibility levels and importance can be obtained using the swarm intelligence algorithm. The case study indicates that the fuzzy aggregation function of radon exhalation has an upward trend with the increase of the cut set, and fuzzy optimization provides the optimal decision-making database of radon treatment and prevention under different decision-making criteria.

• Advances in concrete construction
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• 제16권6호
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• pp.317-325
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• 2023

Strength prediction and correlation of concrete is done using experimental and analytical methods. Main objective is to correlate the experimental and simulated values of compressive strength of concrete mix using Fly Ash (FA) and Silica Fume (SF) by partial replacement of cement in concrete. Mix proportion was determined using IS method for M40grade concrete. Hundred and forty-seven cubes were cast and tested using Universal Testing Machine (UTM). Genetic Algorithm (GA) model was developed using C++ program to simulate the compressive strength of concrete for various proportions of FA and SF replacements individually at 3% increments. Experiments reveal that 12 percent silica fume replacement produced maximum compressive strength of 35.5 N/mm², 44.5 N/mm² and 54.8 N/mm² moreover 9 percent fly ash replacement produced a maximum strength of 31.9 N/mm², 37.6 N/mm² and 51.8 N/mm² during individual material replacement of concrete mix. Correlation coefficient for each curing period of fly ash and silica fume replaced mix were acquired using trend lines. The correlation coefficient is found to be approximately 0.9 in FA and SF replaced mix irrespective of the mix proportion and age of concrete. A higher and positive correlation was found between the experimental and simulated values irrespective of the curing period in all the replacements.

• 한국콘텐츠학회논문지
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• 제20권7호
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• pp.66-85
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• 2020

본 연구의 목적은 AI 기술 특허(전체)와 주요 신문에 나타난 AI 보도 프레임을 바탕으로 AI 발달과정 추세를 예측하고 이를 기술·설명하는 것이다. 이를 위해 지난 9년간 출원된 한국과 미국 기술특허 요약문과 국내 주요 신문의 AI(Artificial Intelligence) 뉴스 텍스트를 분석하였다. 본 연구는 빅데이터를 활용한 토픽모델링과 시계열회귀분석이 사용되었으며, 추가로 네트워크 의제 상관분석과 회귀분석 기법이 사용되었다. 본 연구결과는 다음과 같다. 첫째, Topic 모델링 분석결과, AI 기술특허 요약문에서는 인공지능, 알고리즘 5G(Hot AI 기술) 등의 순으로 확인되었으며, AI 뉴스보도에서는 산업 적용, 데이터 활용과 시장 적용 등의 순으로 확인되어 AI의 사회문화 보도 경향을 나타냈다. 둘째, 시계열회귀분석결과, 상승추세 토픽으로는 사회문화적으로 AI 일상적·문화적 이용과 산업적용 시작이 도출되었다. 하락추세토픽으로는 시스템, 하드웨어 기술 중심으로 나타났다. 셋째, 상관관계와 회귀관계를 활용한 QAP 분석 결과, AI 기술특허와 뉴스 보도 프레임 간의 상관관계는 높은 것으로 나타났다. 이를 통해 AI 발달에서 AI 기술특허와 뉴스 보도 프레임이 미디어 담론의 결정요인에 의해 사회적으로 구성되는 것을 알 수 있었다.

• 전기학회논문지
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• 제66권5호
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• pp.757-764
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• 2017

As the reduction of greenhouse gases(GHGs) emission has become a global issue, the microgrid markets are growing rapidly. With the sudden changes in the market, Korean government suggested a new business model called 'Self-Sufficient Energy Islands'. Its main concern is a stand-alone microgrid composed of Distributed Energy Resources(DERs) such as Renewable Energy Sources(RESs), Energy Storage System(ESS) and Fuel Cell, in order to minimize the emission of GHGs. According to these trend, this paper is written to propose an optimal sizing method of DERs in a stand-alone microgrid by using Genetic Algorithm(GA), one of the representative stochastic methods. It is to minimize the net present cost with the variables, size of RESs and ESS. In the process for optimization, the sunless days are considered as additional constraints. Through the case study analysis, the size of DERs installed in a microgrid system has been computed using the proposed method in MATLAB. And the result of MATLAB is compared with that of HOMER(Hybrid Optimization of Multiple Energy Resources), a well-known energy modeling software.

• 한국자동차공학회논문집
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• 제11권1호
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• pp.128-136
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• 2003

In today's design trend of vehicle structure, crush zone is fiequently reinforced by adding a box-shaped sub-frame in order to avoid an excessive deformation against a high-speed offset barrier such as EU Directive 96/97 EC, IIHS offset test. That kind of vehicle structure design results in a relatively monotonic crash pulse for airbag ECU(Electronic Control Unit) located at non-crush zone. As for an angular crash event, the measured crash signal using a single-axis accelerometer in a longitudinal direction is usually weaker than that of frontal barrier crash. Therefore, it is not so easy task to achieve a satisfactory crash discrimination performance for offset and angular crash events. In this paper, we introduce a new crash discrimination algorithm using an electronic X-Y 2-axis accelerometer in order to improve crash discrimination performance especially for those crash events. The proposed method uses a crash signal in lateral direction(Y-axis) as well as in longitudinal direction(X-axis). A crash severity measure obtained from Y-axis acceleration is used to improve the discrimination between fire and no-fire events. The result obtained by the proposed measure is logically ORed with an existing algorithm block using X-axis crash signal. Simulation and pulse injection test have been conducted to verify the performance of proposed algorithm by using real crash data of a 2,000cc passenger vehicle.

• Spatial Information Research
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• 제12권1호
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• pp.101-110
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• 2004

GPS 관측기법을 지적측량에 도입하기 위하여 GPS를 이용한 새로운 지적측량 모형(Model)을 정립하는 연구와 관련 기술들을 개발하는 연구가 활발히 진행되고 있다. 이와 같은 추세에 발맞추어 GPS 자료처리 및 기준점 성과산출과 관련하여 국내·외 측량 관련 상용 GPS 자료처리 소프트웨어의 현황 및 성능을 파악하고, 자료처리 알고리즘을 분석하여, 우리 실정에 적합한 GPS 자료처리 소프트웨어를 개발하는 것을 본 연구의 목적으로 한다. 본 연구에서는 국내ㆍ외의 전문 업체, 기관(대학)이 보유하고 있는 상용 소프트웨어 현황 분석 및 자료처리 방법에 따른 오차 발생을 연구하여 기선해석, 망 조정, 좌표변환 등에 관련된 전문 소프트웨어 기능을 비교 분석하여 자료처리 산출성과의 정확도를 향상시키는 방향을 모색한다. 또한 기존 GPS 자료처리 소프트웨어에 적용된 알고리즘을 분석하고 지적측량성과 산출에 최적인 알고리즘을 연구하여 새로운 지적기준점 성과 산출을 위한 지적측량 성과계산 소프트웨어를 개발한다.

• 제어로봇시스템학회논문지
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• 제11권5호
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• pp.435-444
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• 2005

This paper presents a lane-departure identification (LDI) algorithm for a traveling vehicle on a structured road. The algorithm makes up for the weak points of the former method based on EDF[1] by introducing a Lane Boundary Pixel Extractor (LBPE), the well known Hough transform, and liner regression. As a filter to extract pixels expected to be on lane boundaries, the LBPE plays an important role in enhancing the robustness of LDI. Utilizing the pixels from the LBPE the Hough transform provides the lane-related parameters composed of orientation and distance, which are used in the LDI. The proposed LDI is based on the fact the lane-related parameters of left and right lane boundaries are symmetrical as for as the optical axis of a camera mounted on a vehicle is coincident with the center of lane; as the axis deviates from the center of lane, the symmetrical property is correspondingly lessened. In addition, the LDI exploits a linear regression of the lane-related parameters of a series of successive images. It plays the key role of determining the trend of a vehicle's traveling direction and minimizing the noise effect. Except for the two lane-related parameters, the proposed algorithm does not use other information such as lane width, a curvature, time to lane crossing, and of feet between the center of a lane and the optical axis of a camera. The system performed successfully under various degrees of illumination and on various road types.