• Proceedings of the Korean Society of Computer Information Conference
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• 2018.01a
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• pp.7-8
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• 2018

본 논문에서는 CNN 기반의 소음을 이용한 원동 구동장치 진단시스템(PHM)을 제안한다. 이 시스템은 구동장치로부터 발생된 소리로부터 특징데이터를 추출하여 이를 학습한 후 실시간으로 구동장치의 상태를 진단하는 것을 목적으로 하며, 딥러닝 기술을 이용하여 특정 장치에 종속되지 않고 학습할 데이터에 따라 적용 대상이 쉽게 가변 할 수 있도록 설계하였다. 본 논문에서는 실제 적용될 현장에서 발생할 수 있는 예측외의 소음환경에 유연하게 대처하기 위해 딥러닝 모델 중 CNN을 적용한 시스템을 설계하였으며, 제안된 시스템과 이전 연구에서 제안된 DNN 기반의 기계진단시스템을 학습데이터의 환경과 다른 처리배제가 필요한 소음환경에서 비교 실험하여 제안된 시스템이 새로운 환경적응 성능향상에 대하여 우수한 결과를 얻었음을 확인하였다.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.6
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• pp.2048-2061
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• 1991

As compared with other cutting types, the ball end milling process causes a complexity in cutting system and a falling-off of machinability. In order to increase the productivity and efficiency in th NC machining of sculptured surfaces, this study carried out the qualitative linearized evaluation about the ball end milling system and applied their practical expressions to the technological processor at the cutter path planning stage. The evaluated expressions were proved to be adequate for practical use from an accuracy point of view and the estimation models were applied to sculptured surface machining processes for finding variable machining conditions. Consequently, it was recognized that variable machining conditions bring about the dispersion of force system and the reduction of machining time by more than 50%.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.142-149
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• 2015

Most of the mono-camera based lane detection systems are fragile on poor illumination conditions. In order to compensate limitations of single sensor utilization, lane information fusion system using multiple lane sensors is an alternative to stabilize performance and guarantee high precision. However, conventional fusion schemes, which only concerns object detection, are inappropriate to apply to the lane information fusion. Even few studies considering lane information fusion have dealt with limited aids on back-up sensor or omitted cases of asynchronous multi-rate and coverage. In this paper, we propose a lane information fusion scheme utilizing multiple lane sensors with different coverage and cycle. The precise lane information fusion is achieved by the proposed fusion framework which considers individual ranging capability and processing time of diverse types of lane sensors. In addition, a novel lane estimation model is proposed to synchronize multi-rate sensors precisely by up-sampling spare lane information signals. Through quantitative vehicle-level experiments with around view monitoring system and frontal camera system, we demonstrate the robustness of the proposed lane fusion scheme.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11a
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• pp.65-68
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• 2003

본 논문에서는 가장 최근의 동영상 표준인 H.264에서 가변 블록 움직임 예측 시 인접한 블록과의 상관성을 분석하여 병합 절차를 추가함으로써 매크로블록의 최종 모드를 결정하는 시간을 줄이기 위한 알고리즘을 제안한다. H.264에서는 매크로블록의 모드를 결정하기 위하여 총 7가지 모드를 사용하여 움직임 예측은 실시함으로써 부호화 효율을 극대화시킨 반면 이러한 움직임 예측이 부호화기의 복잡도를 높이는 주요 요인으로 현재 커다란 단점으로 지적되고 있다. 본 논문에서는 $8{\times}8$ 움직임 예측이 끝난 후 인접한 두 블록 사이의 거리론 임계값(Threshold)과 비교하여 다음 모드의 움직임 예측의 실시 여부를 먼저 절정함으로써 필요한 움직임 예측에 소비되는 시간을 단축시켰다. 여기서 실험 조건으로 명시하고 있는 것은 대표적인 단일모드 중에서 수행 성능이 가장 좋은 $8{\times}8$ 모드를 기본모드로 사용하고 병합 시 $16{\times}16$ 모드 쪽으로 상향식(bottom-up) 방법의 병합을 수행해 나아간다 모의실험을 통해 수행 성능과 전체 부호화 시간 측면을 본 논문에서 제안한 방법과 4가지 모드인 $16{\times}16,\;16{\times}8,\;8{\times}16,\;8{\times}8$ 모드를 모두 사용한 경우, $8{\times}8$ 단일모드를 사용한 경우를 비교하였다. 실험 결과 $8{\times}8$ 단일모드보다 수행 성능이 향상되었으며, 시간 단축 면에서 제안한 방법이 4가지 모드인 $16{\times}16,\;16{\times}8,\;8{\times}16,\;8{\times}8$ 모드를 모두 사용한 경우와 $8{\times}8$ 단일모드를 사용한 경우보다 계산 시간이 감소하였음을 확인하였다.행중인 MoIM-Messge서버의 네트워크 모듈로 다중 쓰레드 소켓폴링 모델을 적용하였다.n rate compared with conventional face recognition algorithms. 아니라 실내에서도 발생하고 있었다. 정량한 8개 화합물 각각과 총 휘발성 유기화합물의 스피어만 상관계수는 벤젠을 제외하고는 모두 유의하였다. 이중 톨루엔과 크실렌은 총 휘발성 유기화합물과 좋은 상관성 (톨루엔 0.76, 크실렌, 0.87)을 나타내었다. 이 연구는 톨루엔과 크실렌이 총 휘발성 유기화합물의 좋은 지표를 사용될 있고, 톨루엔, 에틸벤젠, 크실렌 등 많은 휘발성 유기화합물의 발생원은 실외뿐 아니라 실내에도 있음을 나타내고 있다.>10)의 $[^{18}F]F_2$를 얻었다. 결론: $^{18}O(p,n)^{18}F$ 핵반응을 이용하여 친전자성 방사성동위원소 $[^{18}F]F_2$를 생산하였다. 표적 챔버는 알루미늄으로 제작하였으며 본 연구에서 연구된 $[^{18}F]F_2$가스는 친핵성 치환반응으로 방사성동위원소를 도입하기 어려운 다양한 방사성의 약품개발에 유용하게 이용될 수 있을 것이다.었으나 움직임 보정 후 영상을 이용하여 비교한 경우, 결합능 변화가 선조체 영역에서 국한되어 나타나며 그 유의성이 움직임 보정 전에 비하여 낮음을 알 수 있었다. 결론: 뇌활성화 과제 수행시에 동반되는 피험자의 머리 움직임에 의하여 도파민 유리가 과대평가되었으며 이는 이 연구에서 제안한 영상정합을 이용한 움직임 보정기법에 의해서 개선되었다. 답이 없는 문제, 문제 만들기, 일반화가 가능한 문제 등으로 보고, 수학적 창의성 중 특히 확산적 사고에 초점을 맞추어 개방형 문제가 확산적 사고의 요소인 유창성, 독창성, 유연성 등에 각각 어떤 영향을 미치는지 20주의 프로그램을 개발, 진행하여 그 효과를 검증하고자 한다. 개방형 문

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.693-700
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• 2019

This paper studies on the optimum design space of solar power plant, application of efficiency improvement facility using various examples, lack of power cost, lack of land development and difficulty of permission. We analyze economic factors and profitability by deriving analysis factors according to the conditions of construction examples and variables by applying efficient facilities that can utilize idle space of individuals and public more efficiently through various cases.

• Journal of IKEEE
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• v.26 no.4
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• pp.568-576
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• 2022

Automatic modulation classification(AMC) is a core technique in Software Defined Radio(SDR) platform that enables smart and flexible spectrum sensing and access in a wide frequency band. In this study, we propose a simple yet accurate deep learning-based method that allows AMC for variable-size radio signals. To this end, we design a classification architecture consisting of two Convolutional Neural Network(CNN)-based models, namely main and small models, which were trained on radio signal datasets with two different signal sizes, respectively. Then, for a received signal input with an arbitrary length, modulation classification is performed by augmenting the input samples using a self-replicating padding technique to fit the input layer size of our model. Experiments using the RadioML 2018.01A dataset demonstrated that the proposed method provides higher accuracy than the existing methods in all signal-to-noise ratio(SNR) domains with less computation overhead.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.1
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• pp.53-59
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• 2010

The spatial variability in the food chain structure of an estuarine environment(Nanakita estuarine, Japan) was investigated using stable carbon and nitrogen isotope. Potential organic matter sources(TP:Terrstrial Plant, MPOM:Marine particulate organic matter, BMA:Benthic microalgae, EPOM:Estuarine particulate organic matter), sedimentary organic matter and benthic invertebrates(Nuttallia olivacea and Nereidae) were sampled at four locations with different tidal flat types(e.g. sanddy, sanddy-muddy and muddy). The main objective of the present study was to determine food sources of Nuttallia olivacea and Nereidae along with small-scale spatial variability within the community of benthic invertebrates. TP(${\delta}^{13}C=-26.6{\pm}0.76$ and ${\delta}^{15}N=2.7{\pm}0.31$) and EPOM(${\delta}^{13}C=-25.5{\pm}0.13$ and ${\delta}^{15}N=5.2{\pm}0.46$) were isotopically distinct from BMA(${\delta}^{13}C=-16.3$ and ${\delta}^{15}N=6.2$) and MPOM(${\delta}^{13}C=-19.6{\pm}0.08$ and ${\delta}^{15}N=8.9{\pm}1.70$). ${\delta}^{13}C$ values of sedimentary organic matter showed a distinct gradient in the range of -27.4 to -22.8‰ with a declining trend from the upstream to the downstream stations. The stable carbon and nitrogen isotope values of benthic invertebrates in the study site was -22.8 to -18.4‰ for ${\delta}^{16}C$ and 8.1 to 11.9‰ or ${\delta}^{15}N$, respectively. Mixing model(Isosource) calculations based on stable isotope measurements showed that benthic invertebrates of Nuttallia olivacea and Nereidae were found to be dominated by MPOM and BMA in stations. Whereas, TP and EPOM showed little influence to benthic invertebrates. The current result suggests that the different contribution for benthic invertebrates should be affected by both seasonal variation and physical factor among stations.

• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.69-75
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• 2018

The key technology of Industry 4.0, Smart factory is evaluated as the driving force of our economic development hereafter and a lot of researches have been established. Various entities including devices, products and managers exist in smart factory, but roles of these entities may be continuous or variable and can become extinct not long after. Existing methods for access control are not suitable to adapt to the variable environment. If we don't consider certain security level, important industrial data can be the targets of attacks. We need a new access control method satisfying desired level of efficiency and security without excessive system loads. In this paper, we propose a new RBAC-PAC which extend AC defined for PKC to the authority attribute of roles. We distribute PACs for roles through block chain method to provide the efficient access control. We verified that RBAC-PAC is more efficient in the smart factory with large number of entities which need a frequent permission update.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.3 s.43
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• pp.1-8
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• 2005

This paper describes a new objective methodology of seismic building damage assessment which is called Advanced Component Method(ACM). ACM is a major attempt to replace the conventional loss estimation procedure, which is based on subjective measures and the opinions of experts, with one that objectively measures both earthquake intensity and the response ol buildings. First, response of typical buildings is obtained analytically by nonlinear seismic static analysis, push-over analyses. The spectral displacement Is used as a measure of earthquake intensity in order to use Capacity Spectrum Method and the damage functions for each building component, both structural and non-structural, are developed as a function of component deformation. Examples of components Include columns, beams, floors, partitions, glazing, etc. A repair/replacement cost model is developed that maps the physical damage to monetary damage for each component. Finally, building response, component damage functions, and cost model were combined probabilistically, using Wonte Carlo simulation techniques, to develop the final damage functions for each building type. Uncertainties in building response resulting from variability in material properties and load assumptions were incorporated in the Latin Hypercube sampling technique. The paper also presents and compares ACM and conventional building loss estimation based on historical damage data and reported loss data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.612-622
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• 2003

This paper studied and proposed a XML document storing-and-retrieval framework based on a variant k-ary complete tree and a RDF metadata, which is composed of an effective storing module to store xml documents, a retrieving module to retrieve xml documents, and a connecting module to make this system intemperate in the web environment. In this storing module, DTD independent DOM based decomposition model using a method of addressing unique ill using a variant k-ary complete tree is adopted and is implemented. Query Processing Module includes a XPath query process and a content based retrieval function using word index for content information. To retrieve more exactly data, a structural retrieval using RDF metadata is adopted and implemented. In order to implement effectively XML document storing and retrieval system in the web environment, API using XML-RPC, API using HTTP's GET, PUT, POST and API using SOAP have been adopted and implemented.