• Journal of the Korea institute for structural maintenance and inspection
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• v.22 no.6
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• pp.197-205
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• 2018

Recently, remodeling is increasing due to aging of buildings. Therefore, the importance of quality control of structures has been raised, and interest in safety diagnosis and evaluation of structures has been increasing. In order to accurately diagnose old buildings, a diagnostic evaluation technique is needed to evaluate the defects of structures in advance. In addition, as the safety diagnostic criteria for reconstruction are improved and the weight of structural safety is increased, researches on safety diagnosis techniques of structures that are faster and more reliable are needed. In this study, we tried to estimate the compressive strength by examining the correlation between ultrasonic pulse velocity and compressive strength of a 1 story structure consisting of vertical and horizontal members of reinforced concrete using ultrasonic pulse velocity method, which is one of the nondestructive testing methods. The purpose of this study is to examine the applicability in the field. As a result, the estimated average error rate of the compressive strength of the structure using the ultrasonic pulse velocity method was 28.7%, which confirmed the applicability in the field. However, in order to increase the accuracy of the estimation, the necessity of the reliable diagnostic method using the composite nondestructive testing method was confirmed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.158-167
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• 2017

This paper presents the technology rating methodology that is applicable to defense R&D technology. First, a technology profitability index was developed using multiple regression analysis to forecast the revenue from technology transfer. Secondly, the technology evaluation index was derived using hierarchical analysis with expert opinion. Finally, the weighted average of the technology profitability index and technology evaluation index were calculated to derive the technology rating. This study is significant in that it is first attempt to evaluate defense R&D technology by rating. If the defense R&D technology rating methodology is applied in practice, it can contribute to efficient R&D budget allocation. In addition, it will help in the vitalization of technology transfer in the defense R&D sector.

• Journal of KIISE:Software and Applications
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• v.31 no.5
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• pp.595-604
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• 2004

Automatic analysis of concepts or semantic relations from text documents enables not only an efficient acquisition of relevant information, but also a comparison of documents in the concept level. We present a multiple cause model-based approach to text analysis, where latent topics are automatically extracted from document sets and similarity between documents is measured by semantic kernels constructed from the extracted topics. In our approach, a document is assumed to be generated by various combinations of underlying topics. A topic is defined by a set of words that are related to the same topic or cooccur frequently within a document. In a network representing a multiple-cause model, each topic is identified by a group of words having high connection weights from a latent node. In order to facilitate teaming and inferences in multiple-cause models, some approximation methods are required and we utilize an approximation by Helmholtz machines. In an experiment on TDT-2 data set, we extract sets of meaningful words where each set contains some theme-specific terms. Using semantic kernels constructed from latent topics extracted by multiple cause models, we also achieve significant improvements over the basic vector space model in terms of retrieval effectiveness.

• Journal of KIISE:Information Networking
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• v.37 no.5
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• pp.409-414
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• 2010

The applications based on geographical location are increasing rapidly in wireless sensor networks (WSN). Recently, various localization algorithms have been proposed but the majority of algorithms rely on the specific hardware to measure the distance from the signal sources. In this paper, we propose the Weighted Multiple Rings Localization(WMRL). We assume that each deployed anchor node may periodically emit the successive beacon signals of the different power level. Then, the beacon signals form the concentric rings depending on their emitted power level, theoretically. The proposed algorithm defines the different weighting factor based on the ratio of each radius of ring. Also, If a sensor node may listen, it can find the innermost ring of the propagated signal for each anchor node. Based on this information, the location of a sensor node is derived by a weighted sum of coordinates of the surrounding anchor nodes. Our proposed algorithm is fully distributed and does not require any additional hardwares and the unreliable distance indications such as RSSI and LQI. Nevertheless, the simulation results show that the WMRL with two rings twice outperforms centroid algorithm. In the case of WMRL with three rings, the accuracy is approximately equal to WCL(Weighted Centroid Localization).

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.982-982
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• 2012

본 연구에서는 우리나라의 중 소규모 유역의 수문학적 위험도 분석을 위하여 한강유역을 대상으로 통합위험지수(IRI: Integrated Risk Index)를 산정하였으며, El Ni$\tilde{n}$o-Southern Oscillation (ENSO)에 의한 대규모 대기순환 패턴의 변화가 한강 유역의 통합위험지수 변화에 미치는 영향을 평가하였다. ENSO자료는 전통적인 El Ni$\tilde{n}$o에 해당하는 Cold-tongue (CT) El Ni$\tilde{n}$o와 중앙태평양 부근의 이상적인 해수면 온도 상승에 의한 Warm-pool (WP) El Ni$\tilde{n}$o, 그리고 해수면 온도가 이상적으로 낮게 관측되는 La Ni$\tilde{n}$a 기간으로 구분하였으며, 각 기간 중 가장 강한 ENSO가 발생한 해(CT El Ni$\tilde{n}$o, 1998; WP El Ni$\tilde{n}$o, 2005; La Ni$\tilde{n}$a, 2000)를 대상으로 통합위험지수를 산정하였다. 통합위험지수는 수문학적 요인(Hydrologic Components), 사회 경제적 요인(Socio-Economic Components)과 생태적 요인(Ecological Components)으로 구분하였고, 엔트로피(entropy) 기법을 통하여 각 인자와 요인별 가중치를 적용하였다. 중권역별 통합위험지수의 평가는 5개의 계급구간(Very High, High, Medium, Low, Very Low)으로 구분하였다. 분석결과, CT El Ni$\tilde{n}$o해의 유역평균 IRI 값은 0.58, WP El Ni$\tilde{n}$o해의 IRI 값은 0.57로 비슷한 결과를 보였으나, La Ni$\tilde{n}$a해에는 IRI 값이 0.41로 낮게 나타났다. CT와 WP El Ni$\tilde{n}$o해에는 한강 서쪽일부 중권역에서 통합위험지수가 높게 나타났으며, La Ni$\tilde{n}$a해에는 한강 중 동부 대부분 유역에서 낮게 분석되었다. 향후 유역별 통합위험지수 산정과 더불어 서로 다른 형태의 ENSO에 따른 수자원 변동 예측이 이루어진다면, 수자원의 효율적인 관리와 안정적인 용수공급에 도움을 줄 것으로 사료되며, 이는 유역별 수자원의 취약성 평가 및 위험도 분석을 위한 기초자료로 활용이 가능하리라 사료된다.

• Journal of Korea Water Resources Association
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• v.53 no.8
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• pp.583-595
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• 2020

In this study, using the RCP scenario for Hyoja Drainage subbasin of Cheonggyecheon, we analyzed the change with the Historical and Future rainfall calculated from five GCMs models. As a result of analyzing the average rainfall by each GCMs model, the future rainfall increased by 35.30 to 208.65 mm from the historical rainfall. Future rainfall increased 1.73~16.84% than historical rainfall. In addition, the applicability of LID element technologies such as porous pavement, infiltration trench and green roof was analyzed using the SWMM model. And the applied weight and runoff for each LID element technology are analyzed. As a result of the analysis, although there was a difference for each GCMs model, the runoff increased by 2.58 to 28.78%. However, when single porous pavement and Infiltration trench were applied, Future rainfall decreased by 3.48% and 2.74%, 8.04% and 7.16% in INM-CM4 and MRI-CGCM3 models, respectively. Also, when the two types of LID element technologies were combined, the rainfall decreased by 2.74% and 2.89%, 7.16% and 7.31%, respectively. This is less than or similar to the historical rainfall runoff. As a result of applying the LID elemental technology, it was found that applying a green roof area of about 1/3 of the urban area is the most effective to secure the lag time of runoff. Moreover, when applying the LID method to the old downtown area, it is desirable to consider the priority order in the order of economic cost, maintenance, and cityscape.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.287-296
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• 2015

Recent navigation systems provide quick guide services, based on processing real-time traffic information and past traffic information by applying predictable pattern for traffic information. However, the current pattern for traffic information predicts traffic information by processing past information that it presents an inaccuracy problem in particular circumstances(accidents and weather). So, this study presented a more precise predictive traffic information system than historical traffic data first by analyzing route search data which the drivers ask in real time for the quickest way then by grasping traffic congestion levels of the route in which future drivers are supposed to locate. First results of this study, the congested route from Yang Jae to Mapo, the analysis result shows that the accuracy of the weighted value of speed of existing commonly congested road registered an error rate of 3km/h to 18km/h, however, after applying the real predictive traffic information of this study the error rate registered only 1km/h to 5km/h. Second, in terms of quality of route as compared to the existing route which allowed for an earlier arrival to the destination up to a maximum of 9 minutes and an average of up to 3 minutes that the reliability of predictable results has been secured. Third, new method allows for the prediction of congested levels and deduces results of route searches that avoid possibly congested routes and to reflect accurate real-time data in comparison with existing route searches. Therefore, this study enabled not only the predictable gathering of information regarding traffic density through route searches, but it also made real-time quick route searches based on this mechanism that convinced that this new method will contribute to diffusing future traffic flow.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.41-49
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• 2021

All application programs, including malware, call the Application Programming Interface (API) upon execution. Recently, using those characteristics, attempts to detect and classify malware based on API Call information have been actively studied. However, datasets containing API Call information require a large amount of computational cost and processing time. In addition, information that does not significantly affect the classification of malware may affect the classification accuracy of the learning model. Therefore, in this paper, we propose a method of extracting a essential feature set after reducing the dimensionality of API Call information by applying various feature selection methods. We used CICAndMal2020, a recently announced Android malware dataset, for the experiment. After extracting the essential feature set through various feature selection methods, Android malware classification was conducted using CNN (Convolutional Neural Network) and the results were analyzed. The results showed that the selected feature set or weight priority varies according to the feature selection methods. And, in the case of binary classification, malware was classified with 97% accuracy even if the feature set was reduced to 15% of the total size. In the case of multiclass classification, an average accuracy of 83% was achieved while reducing the feature set to 8% of the total size.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.331-343
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• 2019

The purpose of this study is to observe the trends of heart age of Koreans by using the predictor of heart age of the Framingham Heart Study. The subjects were 20,012 adults aged 30~74 years who were enrolled in the Korean National Health and Nutrition Examination Survey from 2005~2013. They filled in the determinants data and they had no history of cardiovascular disease (CVD). The heart age was calculated using a non-laboratory based model of prediction. The difference of heart age and chronological age, and the rate of excessive heart age over 10 years were calculated. The annual trend, the difference according to gender, the age bracket and geographic region, the heart age were all evaluated. Data analysis performed using the SAS program (version 9.3). Complex designed analysis was done. The heart age showed differences according to gender, age bracket and geographic region. The heart age is a useful comprehensive indicator for predicting the CVD events in the near future. So, it could be used for the purposes of exercising caution and guidance on CVD for administering medical care. It is strongly recommended to use heart age as an indicator for customized medical management to focus efforts on relatively vulnerable subjects and their factors for CVD. Further study on Koreans' customized heart age is needed.

• Journal of Climate Change Research
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• v.4 no.1
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• pp.11-26
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• 2013

This study examined the applicability of robust decision making (RDM) over standard decision making (SDM) by comparing each result of water supply planning under climate change uncertainties for a Korean dam case. RDM determines the rank of alternatives using the regret criterion which derives less fluctuating alternatives under the risk level regardless of scenarios. RDM and SDM methods were applied to assess hypothetic scenarios of water supply planning for the Andong dam and Imha dam basins. After generating various climate change scenarios and six assumed alternatives, the rank of alternatives was estimated by RDM and SDM respectively. As a result, the average difference in the rank of alternatives between RDM and SDM methods is 0.33~1.33 even though the same scenarios and alternatives were used to be ranked by both of RDM and SDM. This study has significance in terms of an attempt to assess a new approach to decision making for responding to climate change uncertainties in Korea. The effectiveness of RDM under more various conditions should be verified in the future.