• Journal of Korea Water Resources Association
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• v.51 no.11
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• pp.1031-1041
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• 2018

ANFIS-based methodology for improving GloSea5 ensemble weather forecast is developed and evaluated in this study. The proposed method consists of two steps: pre & post processing. For ensemble prediction of GloSea5, weights are assigned to the ensemble members based on Optimal Weighting Method (OWM) in the pre-processing. Then, the bias of the results of pre-processed is corrected based on Model Output Statistics (MOS) method in the post-processing. The watershed of the Chungju multi-purpose dam in South Korea is selected as a study area. The results of evaluation indicated that the pre-processing step (CASE1), the post-processing step (CASE2), pre & post processing step (CASE3) results were significantly improved than the original GloSea5 bias correction (BC_GS5). Correction performance is better the order of CASE3, CASE1, CASE2. Also, the accuracy of pre-processing was improved during the season with high variability of precipitation. The post-processing step reduced the error that could not be smoothed by pre-processing step. It could be concluded that this methodology improved the ability of GloSea5 ensemble weather forecast by using ANFIS, especially, for the summer season with high variability of precipitation when applied both pre- and post-processing steps.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.07a
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• pp.319-322
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• 2001

The proposed system was composed of pre-processor which was executing binary/high-pass filtering and post-processor which ranged from statistic data to prediction. In post-processor work, step one was filter process of image, step two was image recognition, and step three was destruction degree/time prediction. After these processing, we could predict image of the last destruction timestamp. This research was produced variation value according to growth of tree pattern. This result showed improved correction, when this research was applied image Processing. Pre-processing step of original image had good result binary work after high pass- filter execution. In the case of using partial discharge of the image, our research could predict the last destruction timestamp. By means of experimental data, this Prediction system was acquired ${\pm}$3.2% error range.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.206-211
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• 2021

Internet users are increasingly invited to express their opinions on various subjects in social networks, e-commerce sites, news sites, forums, etc. Much of this information, which describes feelings, becomes the subject of study in several areas of research such as: "Sensing opinions and analyzing feelings". It is the process of identifying the polarity of the feelings held in the opinions found in the interactions of Internet users on the web and classifying them as positive, negative, or neutral. In this article, we suggest the implementation of a sentiment analysis tool that has the role of detecting the polarity of opinions from people about COVID-19 extracted from social media (tweeter) in the Arabic language and to know the impact of the pre-processing phase on the opinions classification. The results show gaps in this area of research, first of all, the lack of resources when collecting data. Second, Arabic language is more complexes in pre-processing step, especially the dialects in the pre-treatment phase. But ultimately the results obtained are promising.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.14 no.1
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• pp.26-33
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• 2001

The proposed system was composed of pre-processor which was executing binary/high-pass filtering and post-processor which ranged from statistic data to prediction. In post-processor work, step one was filter process of image, step two was image recognition, and step three was destruction degree/time prediction. After these processing, we could predict image of the last destruction timestamp. This research was produced variation value according to growth of tree pattern. This result showed improved correction, when this research was applied image Processing. Pre-processing step of original image had good result binary work after high pas- filter execution. In the case of using partial discharge of the image, our research could predict the last destruction timestamp. By means of experimental data, this prediction system was acquired $\pm$3.2% error range.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.5
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• pp.74-86
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• 2002

This paper proposes a VLSI architecture for high-speed data processing of the differential phase detectors with the decision feedback. To improve the BER performance of the conventional differential phase detection, DF-DPD, DPD-RGPR and DFDPD-SA have been proposed. These detection methods have the architecture feedbacking the detected phase to reduce the noise of the previous symbol as phase reference. However, the feedback of the detected phase results in lower data processing speed than that of the conventional differential phase detection. In this paper, the VLSI architecture was proposed for high-speed data processing of the differential phase detectors with decision feedback. The Proposed architecture has the pre-calculation method to previously calculate the results on 'N'th step at 'M-1'th step and the pre-decision feedback method to previously feedback the predicted phases at 'M-1'th step. The architecture proposed in this paper was implemented to RTL using VHDL. The simulation results show that the Proposed architecture obtains the high-speed data processing.

• 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.

• KCI Concrete Journal
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• v.12 no.2
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• pp.3-10
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• 2000

A computer program, named NEO-PCBRG, for the analysis and design of prestressed con-crete(PSC) bridges was developed using the finite element method. NEO-PCBRG can predict the response of PSC bridges throughout the various stages of construction and service. NEO-PCBRG has both pre- and post-processing capabilities. Pre-processing refers to all the neces- sary steps required to prepare a virtual prototype, more commonly termed a varied model for analysis. Post-processing here stands for the step in which the results from the analysis are reviewed and interpreted. In order to allow for the easy and convenient execution of the entire procedure, NEO-PCBRG was developed using computer graphics in the Visual Basic pro- gramming language. In conclusion, this study presents a new software architecture for analy-sis using the user-oriented design technique.

• 한국지구물리탐사학회:학술대회논문집
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• 2006.06a
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• pp.253-258
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• 2006

The Korean peninsula has been known to be very difficult to acquire clean MT and GDS data due to its highly industrialization and civilization. In this environment, a pre-screening step selecting data segments with a proper S/N ration is an essential one. This study modified the automatic pre-screening step based on the spectral power of electromagnetic field (RMP) taking account of the situation of the Korean Peninsula. The modified RMP technique was applied to MT data measured at seven sites located in middle part of the peninsula. In the whole sense, the RMP technique considerably improved the connectivity of apparent resistivity and phase curves around the period of 10 sec. In addition, the results processed by the RMP technique showed a very little difference with those derived from manual editing, and the superior performance of it is found especially in the connectivity of apparent resistivity curve.

• Journal of Satellite, Information and Communications
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• v.11 no.2
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• pp.14-17
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• 2016

This paper describes the implementation of automatic number-braille converter based on image processing for the blind people. The algorithm is consists of four main steps. First step is binary image conversion of the input image obtained by the camera. the second step is segmentation operation by means of dilation and labelling of the character. Next step is calculation of cross-correlation between segmented text image and pre-defined text-pattern image. The final step is generation of brail output which is relevant to input image. The computer simulation result was showing 91.8% correct conversion rate for arabian numbers which is printed in A4-sheet and practical possibility was also confirmed by using implemented automatic number-braille converter based on DSP image processing board.

• Journal of Information Processing Systems
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• v.6 no.3
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• pp.335-346
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• 2010

The present study investigates the difficulty of solving the mathematical problem, namely the DLP (Discrete Logarithm Problem) for ephemeral keys. The DLP is the basis for many public key cryptosystems. The ephemeral keys are used in such systems to ensure security. The DLP defined on a prime field $Z^*_p of random prime is considered in the present study. The most effective method to solve the DLP is the ICM (Index Calculus Method). In the present study, an efficient way of computing the DLP for ephemeral keys by using a new variant of the ICM when the factors of p-1 are known and small is proposed. The ICM has two steps, a pre-computation and an individual logarithm computation. The pre-computation step is to compute the logarithms of a subset of a group and the individual logarithm step is to find the DLP using the precomputed logarithms. Since the ephemeral keys are dynamic and change for every session, once the logarithms of a subset of a group are known, the DLP for the ephemeral key can be obtained using the individual logarithm step. Therefore, an efficient way of solving the individual logarithm step based on the newly proposed precomputation method is presented and the performance is analyzed using a comprehensive set of experiments. The ephemeral keys are also solved by using other methods, which are efficient on random primes, such as the Pohlig-Hellman method, the Van Oorschot method and the traditional individual logarithm step. The results are compared with the newly proposed individual logarithm step of the ICM. Also, the DLP of ephemeral keys used in a popular password key exchange protocol known as Chang and Chang are computed and reported to launch key recovery attack.