• The KIPS Transactions:PartA
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• v.17A no.3
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• pp.159-166
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• 2010

In this paper, to obtain the Minimum Spanning Tree (MST) from the graph with several nodes having the same weight, I applied both Bor$\dot{u}$vka and Kruskal MST algorithms. The result came out to such a way that Kruskal MST algorithm succeeded to obtain MST, but not did the Prim MST algorithm. It is also found that an algorithm that chooses Inter-MSF MWE in the $2^{nd}$ stage of Bor$\dot{u}$vka is quite complicating. The $1^{st}$ stage of Bor$\dot{u}$vka has an advantage of obtaining Minimum Spanning Forest (MSF) with the least number of the edges, and on the other hand, Kruskal MST algorithm has an advantage of always obtaining MST though it deals with all the edges. Therefore, this paper suggests an Hybrid MST algorithm which consists of the merits of both Bor$\dot{u}$vka's $1^{st}$ stage and Kruskal MST algorithm. When applied additionally to 6 graphs, Hybrid MST algorithm has a same effect as that of Kruskal MST algorithm. Also, comparing the algorithm performance speed and capacity, Hybrid MST algorithm has shown the greatest performance Therefore, the suggested algorithm can be used as the generalized MST algorithm.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10b
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• pp.1163-1166
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• 2001

최근의 네트워크는 유선에서 무선으로 발전하고 있다. 무선 네트워크 기술은 여러 가지가 있다. 그 중 좁은 영역에서 사용하고 개인적인 용도로 알맞은 것이 블루투스(Bluetooth)이다. 블루투스 기술 표준은 데이터를 전송하는 단순한 통신 방법만을 정의한 것이 아니라, 몇 가지 응용에 대한 표준도 정의되어 있다. 이 응용은 모든 블루투스 기기가 전부 구현해야 하는 것이 아니라, 그 중 기기에 알맞은 것만을 선택해서 구현을 할 수 있도록 되어 있다. 그렇다면 블루투스 기기에서 다른 기기가 제공하는 서비스가 무엇인지를 알아낼 수 있는 방법이 필요하게 된다. 다른 기기의 서비스를 알아내는데 사용되는 블루투스 기술이 SDP 계층 (Service Discovery Protocol Layer) 이다. SDP 계층은 프로토콜만으로 작동 가능한 것이 아니라, 블루투스 기기에서 제공 가능한 서비스와 서비스 속성을 정의한 내부 데이터베이스를 참조해서 작동하게 된다. 이 내부 데이터베이스는 블루투스를 구현하는 사람마다 모두 다르게 구현하고 있다. 그래서 블루투스 서비스와 서비스 속성에 관한 정보는 글과 간단한 도표로만 정의되고 있는 상황이다. 블루투스 서비스와 서비스 속성 정보를 글과 도표가 아닌 XML을 이용한 문서로 표현을 하는 방법이 나타났었다. 그러나 블루투스 기기에서 직접 서비스와 서비스 속성을 기술한 XML 문서를 바탕으로 SDP를 작동시키는 것은 블루투스 기기에 XML 파서를 포함시켜야 한다는 것을 말한다. 대체로 작은 CPU 성능과 적은 메모리를 가지고 있는 블루투스 기기에서는 XML 파서를 포함하는 근 부담이 된다. 이에 본 논문에서는 보편적으로 사용될 수 있는 블루투스 서비스와 서비스 속성을 기술한 XML 문서에서 블루투스 기기에 적합한 내부 정보를 생성하는 생성기를 설계하고 구현을 하였다.보다는 현저히 낮았다. 총 휘발성 유기화합물읜 농도는 실내가 실외 보다 높았다(I/O ratio 2.5). BTEX의 상대적 함량도 실내가 실외보다 높아 실내에도 발생원이 있음을 암시하고 있다. 자료 분석결과 유치원 실내의 벤젠은 실외로부터 유입되고 있었고, 톨루엔, 에틸벤젠, 크실렌은 실외뿐 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 사

• Journal of Korean Society of Archives and Records Management
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• v.15 no.2
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• pp.165-179
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• 2015

Archives have historical and academic values. That is why the study of preservation conditions and the environment for the effective management of various records progress. However, materials such as paper and adhesives will inevitably cause biological damages. These damages spread into the inner side of archives, which would make it impossible to recover. For example, archival records from Malaysia and Oman are easily exposed to biological damage because of these countries' hot and humid climate. As such, once records are damaged, disinfection operations are customary in these areas. Methyl bromide (MeBr) and ethylene oxide (EtO) were used in the disinfection process as they showed good insecticidal effect. However their antibacterial effect are negligible. As such, the need for an environmental-friendly fumigator was evident. An environmental-friendly fumigator is designed to improve storage stability. Such equipment is expected to contribute to prevention of damages to cultural heritages through its use of vaporization technology, maintenance of a disinfection space (chamber), and self-generation of nitrogen.

• Journal of Advanced Navigation Technology
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• v.15 no.4
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• pp.523-535
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• 2011

The precipitable water vapor (PW) was estimated using Global Navigation Satellite System (GNSS) from several GNSS stations within the Korean Peninsula. Nearby radiosonde sites covering the GNSS stations were used for the comparison and validation of test results. GNSS data recorded under typical and severe weather conditions were used to generalize our approach. Based on the analysis, we have confirmed that the derived PW values from the GNSS observables were well agreed on the estimates from the radiosonde observables within 10 mm level. Assuming that the GNSS observables could be a good weather monitoring tool, we further tested the performance of the current WAAS tropospheric delay model, UNB3, in the Korean Peninsula. Especially, the wet zenith delays estimated from the GNSS observables and from UNB3 delay model were compared. Test results showed that the modelled approach for the troposphere (i.e., UNB3) did not perform well especially under the wet weather conditions in the Korean Peninsula. It was suggested that a new model or a near real-time model (e.g., based on regional model from GNSS or numerical weather model) would be highly desirable for the Korean WA-DGNSS to minimize the effects of the tropospheric delay and hence to achieve high precision vertical navigation solutions.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.10
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• pp.773-782
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• 2020

The development of joint FE models for deep learning neural network (DLNN)-based hybrid FEA is presented. Material models of bolts and bearings in the front axle of tractor, showing complex behavior induced by various tightening conditions, were replaced with DLNN models. Bolts are modeled as one-dimensional Timoshenko beam elements with six degrees of freedom, and bearings as three-dimensional solid elements. Stress-strain data were extracted from all elements after finite element analysis subjected to various load conditions, and DLNN for bolts and bearing were trained with Tensorflow. The DLNN-based joint models were implemented in the ABAQUS user subroutines where stresses from the next increment are updated and the algorithmic tangent stiffness matrix is calculated. Generalization of the trained DLNN in the FE model was verified by subjecting it to a new loading condition. Finally, the DLNN-based FEA for the front axle of the tractor was conducted and the feasibility was verified by comparing with results of a static structural experiment of the actual tractor.

• Ecology and Resilient Infrastructure
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• v.7 no.2
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• pp.114-125
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• 2020

Despite the various artificial neural networks that have been developed, most of the discharge models in previous studies have been developed using deep neural networks. This study aimed to develop a discharge model using a convolution neural network (CNN), which was used to solve classification problems. Furthermore, the applicability of CNN was evaluated. The photographs (pictures or images) for input data to CNN could not clearly show the characteristics of the study area as well as precipitation. Hence, the model employed in this study had to use numerical images. To solve the problem, the CN of NRCS was used to generate images as input data for the model. The generated images showed a good possibility of applicability as input data. Moreover, a new application of CN, which had been used only for discharge prediction, was proposed in this study. As a result of CNN training, the model was trained and generalized stably. Comparison between the actual and predicted values had an R² of 0.79, which was relatively high. The model showed good performance in terms of the Pearson correlation coefficient (0.84), the Nash-Sutcliffe efficiency (NSE) (0.63), and the root mean square error (24.54 ㎥/s).

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.3
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• pp.137-145
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• 2014

We present a design sensitivity analysis(DSA) method for multiscale problems based on bridging scale decomposition. In this paper, we utilize a bridging scale method for the coupled system analysis. Since the analysis of full MD systems requires huge amount of computational costs, a coupled system of MD-level and continuum-level simulation is usually preferred. The information exchange between the MD and continuum levels is taken place at the MD-continuum boundary. In the bridging scale method, a generalized Langevin equation(GLE) is introduced for the reduced MD system and the GLE force using a time history kernel is applied at the boundary atoms in the MD system. Therefore, we can separately analyze the MD and continuum level simulations, which can accelerate the computing process. Once the simulation of coupled problems is successful, the need for the DSA is naturally arising for the optimization of macro-scale design, where the macro scale performance of the system is maximized considering the micro scale effects. The finite difference sensitivity is impractical for the gradient based optimization of large scale problems due to the restriction of computing costs but the analytical sensitivity for the coupled system is always accurate. In this study, we derive the analytical design sensitivity to verify the accuracy and applicability to the design optimization of the coupled system.

• Fire Science and Engineering
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• v.32 no.1
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• pp.16-23
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• 2018

In a closed-compartment with various configurations, the correlation that can predict the maximum heat release rate (HRR) with the changes in internal volume and fire growth rate was investigated numerically. The volume of the compartment was controlled by varying the length ratio based on the bottom surface shape of the ISO 9705 fire room, where the ceiling height was fixed to 2.4 m. As a main result, the effect of a change in ceiling height on the maximum HRR was examined by a comparison with a previous study that considered the change in ceiling height. In addition, a more generalized correlation equation was proposed that could predict the maximum HRR in closed-compartments regardless of the changes in ceiling height. This correlation had an average error of 7% and a maximum error of 19% for various fire growth rates when compared with the numerical results. Finally, the applicability of the proposed correlation to representative fire compartments applied to the domestic performance-based design (PBD) was examined. These results are expected to provide useful information on predicting the maximum HRR caused by flashover in closed-compartments as well as the input information required in a fire simulation.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.4
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• pp.116-124
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• 2015

The objective of this study is to evaluate the effects of the replacement levels of grinded fly-ash on the repaired mortar based on a polymer. The main parameters are the curing temperature and replacement levels of grinded fly-ash. The curing temperature and the replacement levels of grinded fly-ash are varied at $40^{\circ}C$, $20^{\circ}C$ and $5^{\circ}C$, and between 0% and 35% of the total binder by weight, respectively. The flow in fresh mortar and compressive strengths according to ages, the relationship of stress-strain, elastic modulus and modulus rupture in hardened mortar, as well as scanning the electron microscopy and the X-ray diffraction of mortar, were measured, respectively. The test results showed that the flow, elastic modulus and modulus rupture are great in mortar specimens with 20~30% of the replacement levels of grinded fly-ash. In addition, compressive strengths according to ages were affected by the replacement levels of grinded fly-ash and the curing temperature indicated that the strength development ratio of mortar with 20% of the replacement levels of grinded fly-ash was greater than others. In the prediction of the compressive strength specified by the ACI 209 code, the strength development at an early and late age can be generalized by the functions of the replacement levels of grinded fly-ash and the curing temperature. In the analysis of scanning the electron microscopy and the X-ray diffraction, the number and intensity of peaks increased and the form of CSH gels on the surface of the particle of grinded fly-ash was observed.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.1
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• pp.19-29
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• 2003

This paper presents a novel hybrid classifier for face recognition with artificially generated virtual training samples. We utilize both the nearest neighbor approach in feature angle space and a connectionist model to obtain a synergy effect by combining the results of two heterogeneous classifiers. First, a classifier called the nearest feature angle (NFA), based on angular information, finds the most similar feature to the query from a given training set. Second, a classifier has been developed based on the recall of stored frontal projection of the query feature. It uses a frontal recall network (FRN) that finds the most similar frontal one among the stored frontal feature set. For FRN, we used an ensemble neural network consisting of multiple multiplayer perceptrons (MLPs), each of which is trained independently to enhance generalization capability. Further, both classifiers used the virtual training set generated adaptively, according to the spatial distribution of each person's training samples. Finally, the results of the two classifiers are combined to comprise the best matching class, and a corresponding similarit measure is used to make the final decision. The proposed classifier achieved an average classification rate of 96.33% against a large group of different test sets of images, and its average error rate is 61.5% that of the nearest feature line (NFL) method, and achieves a more robust classification performance.