• ETRI Journal
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• v.33 no.4
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• pp.537-546
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• 2011

This paper introduces an automated method for building height recovery through the integration of high-resolution satellite images and digital vector maps. A cross-correlation matching method along the vertical line locus on the Ikonos images was deployed to recover building heights. The rational function models composed of rational polynomial coefficients were utilized to create a stereopair of the epipolar resampled Ikonos images. Building footprints from the digital maps were used for locating the vertical guideline along the building edges. The digital terrain model (DTM) was generated from the contour layer in the digital maps. The terrain height derived from the DTM at each foot of the buildings was used as the starting location for image matching. At a preset incremental value of height along the vertical guidelines derived from vertical line loci, an evaluation process that is based on the cross-correlation matching of the images was carried out to test if the top of the building has reached where maximum correlation occurs. The accuracy of the reconstructed buildings was evaluated by the comparison with manually digitized 3D building data derived from aerial photographs.

• ETRI Journal
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• v.33 no.2
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• pp.210-218
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• 2011

Battiti's mutual information feature selector (MIFS) and its variant algorithms are used for many classification applications. Since they ignore feature synergy, MIFS and its variants may cause a big bias when features are combined to cooperate together. Besides, MIFS and its variants estimate feature redundancy regardless of the corresponding classification task. In this paper, we propose an automated greedy feature selection algorithm called conditional mutual information-based feature selection (CMIFS). Based on the link between interaction information and conditional mutual information, CMIFS takes account of both redundancy and synergy interactions of features and identifies discriminative features. In addition, CMIFS combines feature redundancy evaluation with classification tasks. It can decrease the probability of mistaking important features as redundant features in searching process. The experimental results show that CMIFS can achieve higher best-classification-accuracy than MIFS and its variants, with the same or less (nearly 50%) number of features.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.346-351
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• 1998

Cutting process has been automated due to progress of CNC and CAD/CAM, but polishing process has been only depended on experiential knowledge of expert. Polishing work for a curved surface die demands simple and repetitive operations but requires much time for its high precision. Therefore it is operated in the handiwork by skilled worker. However the workers intend to avoid gradually polishing work because of the poor environments such as dust and noise. In order to reduce the polishing time and solve the problem of shortage of skilled workers, it has been done some research for an automation of polishing. To automate the polishing process, a 2 axes polishing robot which is attached to a 3 axes machining center has been developed by our previous research. This automatic polishing robot is able to keep the polishing tool normal on the curved surface of die. Therefore its performance of polishing is improved because of always keeping the tool normal on the surface. In this paper, the smaller sized polishing robot is developed to improve polishing performance. And the controller for 2 axes polishing robot is developed. The controller is composed of TMS320C31 with high speed which is 40-ns instruction cycle time, RAM memory with 64K words, digital input with 64 bits, digital output with 32 bits, and D/A converter with 4 channels, which is 12 bits resolution. To evaluate polishing performance of this developed robot, polishing experiment for shadow mask was carried out.

• Journal of the Korea Safety Management & Science
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• v.13 no.1
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• pp.189-193
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• 2011

The current standard cost for recycling applied under the Extended Producer Responsibility(EPR) institution, is not coping with continuously increased number of obligatory subject items as well as a variety of variable cost changing factors regarding the recycling treatment cost caused by price fluctuation such as increased material and labor cost entirely across the society; changes in recycling treatment process following the developing technologies; and changes in the required work forces and equipments followed by the trends of automated facilities. Despite such various cost fluctuation factors, the current EPR is not coping with the trends, making the re-calculation process difficult, which causes differences between the real treatment cost for recycling. In this study, the analysis was made on main factors affecting on the related cost and the related price changing index was calculated, by conducting the influence evaluation on the standard cost factors of the current standard cost for recycling. Through theses results, more objective standard will be set for the re-calculation of standard cost for recycling to greatly contribute to setting up the midterm and long-term strategies in the future towards efficient institution.

• Korean Institute of Interior Design Journal
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• no.29
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• pp.273-280
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• 2001

In architecture, each project participant must maintain organic relationship with others. However, current practices are rather procedural and discrete than organic, which result in considerable inefficiencies. The cool-downs of Korean construction market also force the architects to be familiar with the new construction methods and systems. This research mainly focuses on the pre-development stage of such systems, analysing relationships between the information of architectural design and other parts of construction information like structure, construction, environment, and so forth. The result of analysis can be organized into attributes of members in a physical building, which can be modeled in a 3D system. The resulting model can be used for automated generation of drawing, Bill of Materials, finite element meshes for structural analysis and energy analysis, etc. by extracting meaningful information from it. Hence, the purpose of this research is to analysis the relationship among domain-specific information (e.g. structural engineering, construction detail, energy evaluation) that are represented in drawings, and to represent the attributes of the information relevantly so that they can be applied to each unit task that forms the whole project. Therefore, an object oriented methodology is introduced to compose design informations in three dimension, and expressing properties of building factors and materials, and to construct a database for computers to recognize architecture informations.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.203-206
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• 1996

During the electromyographic evaluation, the presence and site of lession may be predicted by a detection of denervation potentials such as fibrllation potentials or positive sharp waves in the group of muscles. Currently, clinicians diagnose the neuropathy by detecting fibrillation potentials during EMG tests, and sometimes it is not easy to distinguish between denervation potentials and endplate spikes. The purpose of this study was to find statistically significant parameters for the quantitative distinction between denervation potentials and endplate spikes. Endplate spikes and denervation potentials from the EDB muscle of 10 patients were extracted. Also, EMG signals were classified by experienced clinicians, and were collected using a 12 bit ADC with a sampling rate of 20KHz for the duration of 400msec. In order to find statistically significant parameters, positive and negative peaks were used for analysis. As a results, standard deviation of the endplate spikes and denervation potentials showed more significant difference than others specially for the positive sharp waves. It was concluded that the results of this study could be used to develope an automated system of a EMG analysis.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.21-21
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• 2019

본 연구에서는 국내 주요 종관기상관측장비(Automated Surface Observing System; ASOS)의 강수 자료에 CSEOF 분석(Cyclo-stationary Empirical Orthogonal Function Analysis)을 적용하여 주요 성분(principle component)을 추출한 후 이를 분석하여 국내 강수의 계절적 순환 특성을 평가고자 하였다. ASOS 자료로는 전국 131개의 ASOS 중에 40년 이상의 월 강수량 자료가 구축되어 있는 47개 지점의 자료를 이용하였다. 수집한 자료의 기간은 1978년부터 2018년까지이다. 강수 자료의 월별 공간적인 강수 분포 특성을 파악하기 위해 시간적인 순환성을 고려한 CSEOF 분석을 수행하였다. 강수자료의 주성분을 추출해본 결과, CSEOF 분석의 경우 첫 번째 CSEOF 외의 다른 CSEOF들의 원자료 설명 비율 또한 작지 않게 나타나 다양한 강수 변동 특성을 평가할 수 있음을 확인하였다. 8월의 2nd CSEOF는 한반도 전체의 강수가 감소하는 것으로 나타났으며, 이는 라니냐가 7-8월 한반도 강수에 미치는 영향과 유사하다. 아울러 9월의 2nd CSEOF 결과 또한 남부를 중심으로 전체적으로 감소하는 경향이 나타남. 이는 엘리뇨 발생 시 9월의 강수 패턴과 비슷한 것으로 확인되었다. 뿐만 아니라, 우리나라에 영향을 미친 주요 태풍과 CSEOF의 상관관계도 검증할 수 있었으며, 장마와의 관계도 발견할 수 있었다. 향후, CSEOF 분석 결과에 해석방법이 개발된다면, 보다 다각적인 측면에서의 강수 계절적 순환 특성 평가가 이루어 질 수 있을 것으로 기대한다.

• Journal of the Korean institute of surface engineering
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• v.54 no.5
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• pp.278-284
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• 2021

Corrosion of steel plate is common phenomenon which results in the gradual destruction caused by a wide variety of environments. Corrosion monitoring is the tracking of the degradation progress for a long period of time. Corrosion on steel plate appears as a discoloration and any irregularities on the surface. In this study, we developed a quantitative evaluation method of the rust formed on steel plate by using k-means clustering from the corroded area in a given image. The k-means clustering for automated corrosion detection was based on the GrabCut segmentation and Gaussian mixture model(GMM). Image color of the corroded surface at cut-edge area was analyzed quantitatively based on HSV(Hue, Saturation, Value) color space.

• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.189-198
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• 2021

In this paper, we introduce the software/hardware system that can reliably calculate the distance from sensor to the model regardless of point cloud density. As the 3d point cloud map is widely adopted for SLAM and computer vision, the accuracy of point cloud map is of great importance. However, the 3D point cloud map obtained from Lidar may reveal different point cloud density depending on the choice of sensor, measurement distance and the object shape. Currently, when measuring map accuracy, high reflective bands are used to generate specific points in point cloud map where distances are measured manually. This manual process is time and labor consuming being highly affected by Lidar sparsity level. To overcome these problems, this paper presents a hardware design that leverage high intensity point from three planar surface. Furthermore, by calculating distance from sensor to the device, we verified that the automated method is much faster than the manual procedure and robust to sparsity by testing with RGB-D camera and Lidar. As will be shown, the system performance is not limited to indoor environment by progressing the experiment using Lidar sensor at outdoor environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3756-3777
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• 2019

Recent internet development is helping malware researchers to generate malicious code variants through automated tools. Due to this reason, the number of malicious variants is increasing day by day. Consequently, the performance improvement in malware analysis is the critical requirement to stop the rapid expansion of malware. The existing research proved that the similarities among malware variants could be used for detection and family classification. In this paper, a Cross-Platform Malware Variant Classification System (CP-MVCS) proposed that converted malware binary into a grayscale image. Further, malicious features extracted from the grayscale image through Combined SIFT-GIST Malware (CSGM) description. Later, these features used to identify the relevant family of malware variant. CP-MVCS reduced computational time and improved classification accuracy by using CSGM feature description along machine learning classification. The experiment performed on four publically available datasets of Windows OS and Android OS. The experimental results showed that the computation time and malware classification accuracy of CP-MVCS was higher than traditional methods. The evaluation also showed that CP-MVCS was not only differentiated families of malware variants but also identified both malware and benign samples in mix fashion efficiently.