• Korean Journal of Ecology and Environment
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• v.38 no.4 s.114
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• pp.482-493
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• 2005

The objective of this research was to evaluate an sampling effect of fish species and individual number on sampling techniques of electrofishing and conventional capture methods of cast net and kick net in 38 stream sites sampled during June - September, 2005. For the study, sampling gears were categorized as three types of electrofishing method (EM), conventional sampling technique (CM), and the combined technique (CT) of the electrofishing and the conventional method to compare statistical differences. Major differences of species composition between the CM and EM method were found in some benthic species of Misgurnus mizolepis and Iksookimia koreensis along with lithophilic species of Pungtungia herzi. These species were predominated in the EM rather than the CM, indicating that conventional sampling can underestimate the abundance of benthic or lithophilic species. In contrast ,individual number of typical water column species such as Zacco platypus and Zacco temmincki were more sampled by the CM, so that these fish populations were community overestimated. Also, t-tests on the types of sampling gear from various watersheds of Chogang Stream, Yugu Stream, Daejeon Stream, and Gap Stream showed that total individual numbers and species number in each stream were significantly (t values = 2.806-6.896, p values<0.05, n = 5-14) greater in the CT than the CM. Similar statistical significance (p<1.001, n = (10-24) on sampling seasons were observed during the monsoon and postmonsoon. These results indicate that if the electrofishing is not added to the conventional gears, the abundance of fish population and community can be underestimated and some benthic or lithophilic species may be excluded from the analysis, resulting in overall errors including sampling, fish fauna, and final judgement of community abundance. Overall our results strongly suggest that new application of electrofishing method along with the conventional sampling gears reduce sampling bias on underestimation of the real fish populations and communities.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.48-51
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• 2011

사장교에서 케이블은 하중을 지지하는 주요 부재로, 케이블 장력은 사장교의 건전성과 안전도 평가에 있어서 매우 중요한 변수이다. 케이블 장력을 추정하기 위한 대표적인 방법으로는 로드셀을 이용한 직접법과 진동 계측 자료를 이용한 간접법 등이 있으며, 최근에는 자기장-응력 관계를 이용한 EM(Elasto-Magnetic) 센서 측정법이 개발되어 케이블 장력 추정에 적용되었다. 본 논문에서는 세 가지 장력 추정 기법을 실제 시공중인 사장교에 적용하여, 그 성능을 상호 비교하였다. 본 연구는 한국의 KAIST와 미국 Northeastern 대학교의 공동연구로 수행되었다. 대상 교량은 부산 화명동과 김해 초정리를 연결하기 위해 현재 건설중인 화명대교이다. 화명대교의 교량 형식은 2주탑 콘크리트 사장교 (주탑 경간장 270m, 총 사장교 구간장 500m)이며, 사장재로는 MS (Multi-Strand) 형 케이블이 사용되었다. 실험 당시 화명대교는 중앙경간의 폐합 후 선형관리를 위한 장력조정작업을 수행하였으며, 케이블 재긴장시의 정확한 장력관리를 위하여 로드셀을 이용한 Lift-off test방법으로 케이블의 장력을 측정하였다. 이와 동시에 두 개의 케이블을 대상으로 진동 가속도 센서와 EM 센서를 설치하고 장력 계측을 수행하였으며, 재긴장 단계별 장력 변화치를 지속적으로 계측하였다. 계측된 결과를 바탕으로 케이블 장력 추정 기법의 정확성 및 실교량에서의 활용성을 비교하였다.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.305-306
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• 2008

실계통에서 운영되는 에너지관리시스템(EMS)의 계통해석 기능을 수행하기 위해서는 대규모 자료의 처리가 불가피하며 이에 따른 메모리의 사용에 대한 효율성, 즉 물리적인 자원의 제약성도 고려되어한 한다. 이러한 이유로 인하여 대규모 자료처리가 요구되는 실시간 시스템의 개발에서는 데이터에 대한 저장의 효율성과 접근의 용이성을 제공할 수 있는 자료설계 (Database Design)가 매우 중요하다 [1]. 이를 위하여 EMS에서는 고속의 연산속도에 대한 요구를 만족하며, 효율적이고 빠른 데이터 처리가 가능한 데이터저장기법이 적용된다. 본 논문에서는 상업용 EMS와 현재 개발중인 한국형EMS에서 적용되고 있는 자료저장기법인 연결형데이터저장기법 (Linked List Data Storage Scheme)에 대한 기능원리와 실제 적용에 대하여 소개하고자 한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.335-342
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• 2016

When dynamics changes occurred in an existing Bayesian Network (BN), the related parameters embedding on the BN have to be updated to new parameters adapting to changed patterns. In this case, these parameters have to be updated with the consideration of the causalities in the BN. This research suggests a framework for updating parameters dynamically using Expectation Maximization (EM) algorithm and Harmony Search (HS) algorithm among several Meta-Heuristics techniques. While EM is an effective algorithm for estimating hidden parameters, it has a limitation that the generated solution converges a local optimum in usual. In order to overcome the limitation, this paper applies HS for tracking the global optimum values of Maximum Likelihood Estimators (MLE) of parameters. The proposed method suggests a learning and propagation framework of BN with dynamic changes for overcoming disadvantages of EM algorithm and converging a global optimum value of MLE of parameters.

• Journal of the Korea institute for structural maintenance and inspection
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• v.22 no.2
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• pp.115-123
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• 2018

In a long-span bridge, the cables are important elements that support the load of the bridge. Accordingly, the cable tension is a very important variable in evaluating the health and safety of the bridge. The most popular methods of estimating the cable tensions are the direct method, which directly measures the cable stresses using load cells, hydraulic jacking devices, etc., and the vibration method, which inverses the tensions using the cable shapes and the measured dynamic characteristics. Studies on the use of the electromagnetic (EM) sensor, which detects the magnetic field variations caused by the change in the stress of the steel in the cable, are increasing. In this study, the lift-off test, the EM sensor, and the vibration method (Vision-based System and Accelerometer) were used to measure cable tension, and their results were compared and analyzed.

• The Journal of the Convergence on Culture Technology
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• v.2 no.1
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• pp.93-98
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• 2016

As information technologies are rapidly developed recently, social networking services through a variety of mobile devices and smart screen is becoming popular. SNS is a social networking based services which is online forms from existed offline. SNS can also be used differently which is confused with the online community. A modelling algorithm is a variety of techniques, which are assocoation, clustering, neural networks, and decision trees, etc. By utilizing this technique, it is necessary to study to effectively using the large number of materials. In this paper, we evaluate in particular the performance of the algorithm based on the results of the clustering using Facebook Insights data for the EM algorithm to be evaluated as a good performance in clustering. Through this analysis it was based on the results of the application of the experimental data of the change and the South Australian state library according to the performance of the EM algorithm.

• Journal of Service Research and Studies
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• v.5 no.2
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• pp.25-33
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• 2015

As Data mining is a method of extracting the information based on the large data, the technique has been used in many application areas to deal with data in particular. However, the status of the algorithm that can deal with the healthcare data are not fully developed. In this paper, One of clustering algorithm, the EM and DBSCAN are used for performance comparison. It could be analyzed using by the same data. To do this, EM and DBSACN algorithm are changing performance according to the variables in Health expenditure database. Based on the results of the experimental data, We analyze more precise and accurate results using by Kernel Filtering. In this study, we tried comparison of the performance for the algorithm as well as attempt to improve the performance. Through this work, we were analyzed the comparison result of the application of the experimental data and of performance change according to expansion algorithm. Especially, Collects data from the various cluster using the medical record, it could be recommended the effective spending on medical services.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.487-489
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• 2003

전문용어란 전문분야의 개념이 언어적으로 표현된 형태이다. 전문분야마다 분야 특성 적인 개념이 사용되므로, 전문용어는 전문분야를 특성화하는 단위로 사용된다. 따라서 전문분야문서에 대한 자연언어처리에서 전문용어를 효과적으로 처리하는 것은 매우 중요하다. 전문용어 추출은 분야 특성적인 전문용어를 해당 분야 문서에서 파악하는 작업을 말한다. 본 논문에서는 기계학습방법을 이용한 전문용어 자동 추출 기법을 제안한다. 본 논문의 기법은 전문분야 사전과 전문분야 문서를 이용하여 문서에서 나타나는 전문용어의 특성을 파악하고 이를 이용하여 전문용어를 추출한다. 본 논문의 기법은 70,000단어 수준의 영어 의학분야 300개 문서에 대하여 약 77%의 정확률로 전문용어를 추출하였다.

• The Journal of Korea Robotics Society
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• v.11 no.3
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• pp.156-162
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• 2016

For the underwater localization, acoustic sensor systems are widely used due to greater penetration properties of acoustic signals in underwater environments. On the other hand, the good penetration property causes multipath and interference effects in structured environment too. To overcome this demerit, a localization method using the attenuation of electro-magnetic(EM) waves was proposed in several literatures, in which distance estimation and 2D-localization experiments show remarkable results. However, in 3D-localization application, the estimation difficulties increase due to the nonuniform (doughnut like) radiation pattern of an omni-directional antenna related to the depth direction. For solving this problem, we added a depth sensor for improving underwater 3D-localization with the EM wave method. A micro scale pressure sensor is located in the mobile node antenna, and the depth data from the pressure sensor is calibrated by the curve fitting algorithm. We adapted the depth(z) data to 3D EM wave pattern model for the error reduction of the localization. Finally, some experiments were executed for 3D localization with the fast calculation and less errors.

• Korean Journal of Remote Sensing
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• v.24 no.4
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• pp.341-349
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• 2008

This study proposes new automatic thresholding method, which is important step for detecting binary change/non-change information using satellite images. Result value through pixel-based similarity measurement is calculated cumulatively with regular interval, and thresholding is pointed at the steep slope position. The proposed method is assessed in comparison with expectation-maximization algorithm and coner method using synthetic images, ALI images, and Hyperion images. Throughout the results, we validated that our method can guarantee the similar accuracy with previous algorithms. It is simpler than EM algorithm, and can be applied to the binormal histogram unlike the coner method.