• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2565-2574
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• 2000

The error diffusion method is good for reproducing continuous image to binary image. However the reproduction of edge characteristic is weak in power spectrum analysis of display error. In this paper. we present an edge-enhanced error-diffusion method which include pre-processing algorithm for edge characteristic enhancement. Pre-processing algorithm consists of the difference value between current pixel and local average of original image and weighting function of pre-filter. First. it is obtained the difference value between current pixel and the local average of peripheral pixels(5x5) in original image. Second, weighting function of pre-filter is composed by function including absolute value and sign of difference value. The improved Error diffusion algorithm using pre-processing algorithm, present a good result visually which edge characteristic is enhanced. The performance of the proposed algorithm is compared with that of the conventional edge-enhanced error diffusion by measuring the RAPSD of display error, the egde correlation and the local average accordance.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.4
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• pp.109-115
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• 2010

Differential Power Analysis (DPA) is well known as one of efficient physical side-channel attack methods using leakage power consumption traces. However, since the power traces usually include the components irrelevant to the encryption, the efficiency of the DPA attack may be degraded. To enhance the performance of DPA, we introduce a pre-processing technique which extracts the encryption-related parts from the measured power consumption signals. Experimental results show that the DPA attack with the use of the proposed pre-processing method detects correct cipher keys with much smaller number of signals compared to that of the conventional DPA attack.

• Proceedings of the Korea Concrete Institute Conference
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• 1996.04a
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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.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.32 no.1
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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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• v.18 no.2
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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.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.5
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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.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.3
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.12
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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.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2014.11a
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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.

• Journal of Auto-vehicle Safety Association
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• v.13 no.2
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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.