• 한국정보처리학회논문지
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• 제7권8호
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• pp.2565-2574
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• 2000

오차확산법은 연속계조 영상을 중간조 영상으로 생성시 우수한 재현성을 보인다. 그러나 표시오차의 전력스펙트럼 분석에서 경계정보의 재현성이 다소 떨어지는 특성을 보인다. 이를 개선하기 위해 원영상의 현재화소와 로컬 평균간의 차이정보를 이용하는 경계강조 오차확산법을 제안한다. 제안한 기법은 원영상이 현재화소와 로컬 평균과의 차이정보 및 이를 활용하는 필터의 가중치 함수로 구성된다. 첫째, 원영상의 차이정보는 현재 화소와 이의 인접화소(5x5)의 로컬 평균과의 차이이다. 둘째, 필터의 가중치 함수는 차이정보의 크기를 포함하는 함수와 이의 부호로 구성된다. 제안한 기법을 적용한 중간조 영상은 경계가 강조되어 시각적으로 선명한 결과를 보인다. 환상 평균 전력 스펙트럼 밀도를 이용한 표시오차, 경계상관도 및 로컬 평균 일치도의 평가함수로 제안한 경계강조 오차확산법과 기존의 경계강조 오차확산법의 특성을 비교한다.

• 정보보호학회논문지
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• 제20권4호
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• pp.109-115
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• 2010

차분 전력 분석(Differential Power Analysis, DPA) 기법은 암호화 과정 중 발생하는 누설정보를 이용하는 효과적인 부채널 공격(side-channel attack, SCA) 종의 하나로 알려져 있다. 그러나 공격에 사용되는 누설 전력 신호에는 암호화와 관련이 없는 동작에 의해 야기된 전력 신호가 함께 포함되어 있으며, 이로 인해 공격의 효율성이 크게 저하된다. 따라서 본 논문에서는 차분 전력 분석 기법의 공격 성능을 향상시키기 위해, 측정된 전력 신호로부터 암호화 과정에 관련된 부분만을 추출하는 전처리 방법을 제안한다. 모의실험 결과를 통해 제안된 전처리 방법을 적용한 차분 전력 분석 공격은 기존의 차분 전력 분석 공격에 비해 매우 적은 수의 누설 전력 신호만으로도 암호화 알고리즘에 사용된 비밀 키를 찾을 수 있음을 보인다.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1996년도 봄 학술발표회 논문집
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• pp.270-274
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• 1996

Until recently pre & post-processing of finite element model has been heavily relied on expensive graphic peripheral devices. But today, with the aid of inexpensive microcomputers, very effective pre & postprocessor graphics has been developed. In this study, Pre & Post processor(MASSPRE, MASSPOST) of prediction analysis of thermal stress in mass concrete structure is developed. The developed pre & post processors are raise to the efficiency in making input data for the main program and analysis of the results produced by the main program. This MASSPOST presents a stress contour graph, volume slice, time-temperature history graph, time-stress history graph, etc.

• 대한기계학회논문집B
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• 제32권1호
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• pp.70-77
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• 2008

A pre-processing program based on the OOP(object-oriented programming) concept has been developed. The program consists of the input of a 2D or 3D flow problem to a CFD program by means of an user-friendly interface and the subsequent transformation of this input into a form suitable for the solver(PowerCFD) using unstructured cell-centered method. User-friendly GUI(graphic user interface) has been built on the base of MFC(Microsoft Foundation Class). The program is organized as modules by classes based on VTK(Visualization ToolKit)-library, and these classes are made to function through inheritance and cooperation which is an important and valuable concept of object-oriented programming. The major functions of this program are introduced and demonstrated, which include mesh generation, boundary settings, solver settings, generation of grid connectivity and geometric data etc.

• Journal of Information Processing Systems
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• 제18권2호
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• pp.282-291
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• 2022

This research applies a pre-trained bidirectional encoder representations from transformers (BERT) handwriting recognition model to predict foreign Korean-language learners' writing scores. A corpus of 586 answers to midterm and final exams written by foreign learners at the Intermediate 1 level was acquired and used for pre-training, resulting in consistent performance, even with small datasets. The test data were pre-processed and fine-tuned, and the results were calculated in the form of a score prediction. The difference between the prediction and actual score was then calculated. An accuracy of 95.8% was demonstrated, indicating that the prediction results were strong overall; hence, the tool is suitable for the automatic scoring of Korean written test answers, including grammatical errors, written by foreigners. These results are particularly meaningful in that the data included written language text produced by foreign learners, not native speakers.

• 대한임베디드공학회논문지
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• 제11권5호
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• pp.277-285
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• 2016

Moving object detection system has been an emerging research field in various advanced driver assistance systems (ADAS) and surveillance system. In this paper, we propose two optical flow based moving object detection methods at dynamic scenes. Both proposed methods consist of three successive steps; pre-processing, foreground segmentation, and post-processing steps. Two proposed methods have the same pre-processing and post-processing steps, but different foreground segmentation step. Pre-processing calculates mainly optical flow map of which each pixel has the amplitude of motion vector. Dense optical flows are estimated by using Farneback technique, and the amplitude of the motion normalized into the range from 0 to 255 is assigned to each pixel of optical flow map. In the foreground segmentation step, moving object and background are classified by using the optical flow map. Here, we proposed two algorithms. One is Gaussian mixture model (GMM) based background subtraction, which is applied on optical map. Another is adaptive thresholding based foreground segmentation, which classifies each pixel into object and background by updating threshold value column by column. Through the simulations, we show that both optical flow based methods can achieve good enough object detection performances in dynamic scenes.

• 한국소음진동공학회논문집
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• 제21권3호
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• pp.220-226
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• 2011

This paper presents the novel work for source localization of serial multiple impacts in a plate sructure. It is difficult to identify the source of serial multiple impacts with the current source localization techenology(SLT) because of the overlapping of dispersive wave induced by multiple impacts and the reflaction from the edge of the plate. In this paper, the new method is suggested for source localization. The method is developed based on the SLT with pre-signal processing such as some limitation for the selection of three sensors, the frequency range for TFA and impact time interval. Results from numerical simulation and experiment in isotropic plate structure are presented, which show the capability of the proposed method.

• 제어로봇시스템학회논문지
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• 제14권12호
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• pp.1278-1285
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• 2008

An optimization-based real-time joint angle extraction method of human elbow is proposed by processing the biomedical signal of surface EMG (electromyogram) measured at the center point of biceps brachii. The EMG signal is known as non-stationary (time-varying) signal, but we assume that it is quasi-stationary because a physical or physiological system has limitations in the rate at which it can change its characteristics. Based on the assumption, a pre-processing method to obtain pre-angle values from raw EMG signal is firstly suggested, and then an optimization method to minimize the error between the pre-angle and real joint angle is proposed in this paper. Finally, we suggest the experimental results showing the effectiveness of the proposed algorithm.

• 한국표면공학회:학술대회논문집
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• 한국표면공학회 2014년도 추계학술대회 논문집
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• pp.293-293
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• 2014

The applicability of graphene has been demonstrated in the electronic fields. But, high performance of graphene is limited by the contact resistance (Rc) at the metal-graphene interface. Recently, Rc was found to be improved by forming edge-contacted graphene via theoretical simulation. Based on the differences between the surface and edge contacts at the M-G interface, we demonstrate "edge-contacted" graphene through the use of a controlled plasma processing technique that generates the edge structure of the bond and significantly reduces the contact resistance. The contact resistance attained by using pre-plasma processing was of $270{\Omega}{\cdot}{\mu}m$. Mechanisms of pre-plasma process leading to low Rc was revealed by SEM and Raman spectroscopy. In the end, controlled pre-plasma processing enabled to fabricate CVD-graphene field effect transistors with an enhanced adhesion and improved carrier mobility.

• 자동차안전학회지
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• 제13권2호
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• pp.35-41
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• 2021

In this study, improved path tracking control algorithm based on pure pursuit algorithm is newly proposed by using improved lane detection algorithm through real time post-processing with interpolation methodology. Since the original pure pursuit works well only at speeds below 20 km/h, the look-ahead distance is implemented as a sigmoid function to work well at an average speed of 45 km/h to improve tracking performance. In addition, a smoothing filter was added to reduce the steering angle vibration of the original algorithm, and the stability of the steering angle was improved. The post-processing algorithm presented has implemented more robust lane recognition system using real-time pre/post processing method with deep learning and estimated interpolation. Real time processing is more cost-effective than the method using lots of computing resources and building abundant datasets for improving the performance of deep learning networks. Therefore, this paper also presents improved lane detection performance by using the final results with naive computer vision codes and pre/post processing. Firstly, the pre-processing was newly designed for real-time processing and robust recognition performance of augmentation. Secondly, the post-processing was designed to detect lanes by receiving the segmentation results based on the estimated interpolation in consideration of the properties of the continuous lanes. Consequently, experimental results by utilizing driving guidance line information from processing parts show that the improved lane detection algorithm is effective to minimize the lateral offset error in the diverse maneuvering roads.