• Title/Summary/Keyword: error performance

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Improvement of Endoscopic Image using De-Interlacing Technique (De-Interlace 기법을 이용한 내시경 영상의 화질 개선)

  • 신동익;조민수;허수진
    • Journal of Biomedical Engineering Research
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    • v.19 no.5
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    • pp.469-476
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    • 1998
  • In the case of acquisition and displaying medical Images such as ultrasonography and endoscopy on VGA monitor of PC system, image degradation of tear-drop appears through scan conversion. In this study, we compare several methods which can solve this degradation and implement the hardware system that resolves this problem in real-time with PC. It is possible to represent high quality image display and real-time processing and acquisition with specific de-interlacing device and PCI bridge on our hardware system. Image quality is improved remarkably on our hardware system. It is implemented as PC-based system, so acquiring, saving images and describing text comment on those images and PACS networking can be easily implemented.metabolism. All images were spatially normalized to MNI standard PET template and smoothed with 16mm FWHM Gaussian kernel using SPM96. Mean count in cerebral region was normalized. The VOls for 34 cerebral regions were previously defined on the standard template and 17 different counts of mirrored regions to hemispheric midline were extracted from spatially normalized images. A three-layer feed-forward error back-propagation neural network classifier with 7 input nodes and 3 output nodes was used. The network was trained to interpret metabolic patterns and produce identical diagnoses with those of expert viewers. The performance of the neural network was optimized by testing with 5~40 nodes in hidden layer. Randomly selected 40 images from each group were used to train the network and the remainders were used to test the learned network. The optimized neural network gave a maximum agreement rate of 80.3% with expert viewers. It used 20 hidden nodes and was trained for 1508 epochs. Also, neural network gave agreement rates of 75~80% with 10 or 30 nodes in hidden layer. We conclude that artificial neural network performed as well as human experts and could be potentially useful as clinical decision support tool for the localization of epileptogenic zones.

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Oil Spill Visualization and Particle Matching Algorithm (유출유 이동 가시화 및 입자 매칭 알고리즘)

  • Lee, Hyeon-Chang;Kim, Yong-Hyuk
    • Journal of the Korea Convergence Society
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    • v.11 no.3
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    • pp.53-59
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    • 2020
  • Initial response is important in marine oil spills, such as the Hebei Spirit oil spill, but it is very difficult to predict the movement of oil out of the ocean, where there are many variables. In order to solve this problem, the forecasting of oil spill has been carried out by expanding the particle prediction, which is an existing study that studies the movement of floats on the sea using the data of the float. In the ocean data format HDF5, the current and wind velocity data at a specific location were extracted using bilinear interpolation, and then the movement of numerous points was predicted by particles and the results were visualized using polygons and heat maps. In addition, we propose a spill oil particle matching algorithm to compensate for the lack of data and the difference between the spilled oil and movement. The spilled oil particle matching algorithm is an algorithm that tracks the movement of particles by granulating the appearance of surface oil spilled oil. The problem was segmented using principal component analysis and matched using genetic algorithm to the point where the variance of travel distance of effluent oil is minimized. As a result of verifying the effluent oil visualization data, it was confirmed that the particle matching algorithm using principal component analysis and genetic algorithm showed the best performance, and the mean data error was 3.2%.

Stock Prediction Model based on Bidirectional LSTM Recurrent Neural Network (양방향 LSTM 순환신경망 기반 주가예측모델)

  • Joo, Il-Taeck;Choi, Seung-Ho
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.11 no.2
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    • pp.204-208
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    • 2018
  • In this paper, we proposed and evaluated the time series deep learning prediction model for learning fluctuation pattern of stock price. Recurrent neural networks, which can store previous information in the hidden layer, are suitable for the stock price prediction model, which is time series data. In order to maintain the long - term dependency by solving the gradient vanish problem in the recurrent neural network, we use LSTM with small memory inside the recurrent neural network. Furthermore, we proposed the stock price prediction model using bidirectional LSTM recurrent neural network in which the hidden layer is added in the reverse direction of the data flow for solving the limitation of the tendency of learning only based on the immediately preceding pattern of the recurrent neural network. In this experiment, we used the Tensorflow to learn the proposed stock price prediction model with stock price and trading volume input. In order to evaluate the performance of the stock price prediction, the mean square root error between the real stock price and the predicted stock price was obtained. As a result, the stock price prediction model using bidirectional LSTM recurrent neural network has improved prediction accuracy compared with unidirectional LSTM recurrent neural network.

A Study on the Safety Handling Method of KCG's Water Jet Propulsion Ship (해양경찰 Water Jet 추진함정의 안전 조함법 연구)

  • Yun, Chong-Gum;Pak, Chae-Hong;Park, Deuk-Jin;Jung, Cho-Yeong
    • Journal of Navigation and Port Research
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    • v.41 no.6
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    • pp.373-380
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    • 2017
  • Operational errors caused by human factors, which is the major cause of marine accidents, include lack of knowledge, misunderstanding knowledge, and inadequate procedures. Recently, the type of propulsion mounted on KCG cutters has been diversified. In particular, the water jet propulsion unit, which was mainly installed in small boats, have been gradually expanded to medium and large size Coast Guard cutters, reaching 50% of the total. Axes types are divided into 2 to 4, and the bucket types are divided into Double Reverse Bucket(DRB) and Single Reverse Bucket(SRB); in these, the backward and steering control methods are completely different. Diversification of these operating systems can increase factors causing human error by the ships' operators. However, there is a lack of research on the maneuvering methods, considering the inherent active characteristics of each type of water jet. In this paper, we analyze the sideway method suitable for the condition of Coast Guard Exclusive wharf without assistance, based on the astern performance of each type. Then, a ship handling simulator was used for the experiment; they compared and verified through interviews of captains.

Analysis of GPS Galileo Time Offset Effects on Positioning (GPS Galileo Time Offset (GGTO)의 항법해 영향 분석)

  • Joo, Jung-Min;Cho, Jeong-Ho;Heo, Moon-Beom
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37C no.12
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    • pp.1310-1317
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    • 2012
  • The Global Navigation Satellite System (GNSS) like US Global Positioning System (GPS) and EU Galileo are based on providing precise time and frequency synchronized ranging signals. Because of the exploitation of very precise timing signals these GNSS are used to provide both navigation and time distribution services. Moreover, because the positioning accuracy will improve as more satellites become available, we should expect that a combination of Galileo and GPS will provide better performance than those of both systems separately. However, Galileo will not use the same time reference as GPS and thus, a time difference arises - the GPS-Galileo Time Offset (GGTO). The navigation solution calculated by receivers using signals from both navigation systems will consequently contain a supplementary error if the GGTO is not accounted for. In this paper, we compared GPS Time (GPST) with Galileo Sytem Time (GST) and analyzed the effects of GGTO on positioning accuracy by simulation test. And then we also analyzed the characteristics of two representative GGTO correction methods such as the navigation message based method at system level and the estimation method at user level and propose the conceptual design of the novel correction method being capable of preventing previous method's problems.

Medical Image Compression Using JPEG International Standard (JPEG 표준안을 이용한 의료 영상 압축)

  • Ahn, Chang-Beom;Han, Sang-Woo;Kim, Il-Yoen
    • Proceedings of the KIEE Conference
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    • 1993.07a
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    • pp.504-506
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    • 1993
  • The Joint Photographic Experts Group (JPEG) standard was proposed by the International Standardization Organization (ISO/SC 29/WG 10) and the CCITT SG VIII as an international standard for digital continuous-tone still image compression. The JPEG standard has been widely accepted in electronic imaging, computer graphics, and multi-media applications, however, due to the lossy character of the JPEG compression its application in the field of medical imaging has been limited. In this paper, the JPEG standard was applied to a series of head sections of magnetic resonance (MR) images (256 gray levels, $256{\times}256$ size) and its performance was investigated. For this purpose, DCT-based sequential mode of the JPEG standard was implemented using the CL550 compression chip and progressive and lossless coding was implemented by software without additional hardware. From the experiment, it appears that the compression ratio of about 10 to 20 was obtained for the MR images without noticeable distortion. It is also noted that the error signal between the reconstructed image by the JPEG and the original image was nearly random noise without causing any special-pattern-related artifact. Although the coding efficiency of the progressive and hierarchical coding is identical to that of the sequential coding in compression ratio and SNR, it has useful features In fast search of patient Image from huge image data base and in remote diagnosis through slow public communication channel.

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Evaluation of the Accuracy of Grounding Impedance Measurement of Grounding Grid (접지그리드의 접지임피던스 측정의 정확도 평가)

  • Choi, Jong-Hyuk;Choi, Young-Chul;Jeong, Dong-Cheol;Kim, Dong-Seong;Lee, Bok-Hee
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.23 no.12
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    • pp.146-153
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    • 2009
  • Recently, the common grounding systems are adapted in most large structures. Since the ground resistance is insufficient to evaluate the performance of grounding systems, it is needed to measure grounding impedance. Even though the methods of measuring grounding impedance of large grounding systems are presented in IEEE standard 81.2, but they have not been described in detail. In this paper, we present the accurate method of measuring grounding impedance based on the revised fall-of-potential method and measurement errors due to earth mutual resistance and ac mutual coupling depending on locating test electrodes at remote earth were examined for the 15[m]$\times$15[m] grounding grid. As a result, the measurement error due to earth mutual resistance is decreased when the distance to auxiliary electrodes increased. To get rid of measurement errors due to mutual coupling, the potential lead should be installed at a right angle to the current lead. When the angle between the potential and the current leads is an acute angle or an obtuse angle, the mutual couple voltage is positive or negative, respectively. Generally, the measurement errors due to mutual coupling with an obtuse angle route are lower than those with an acute angle route.

Improving Recall for Context-Sensitive Spelling Correction Rules using Conditional Probability Model with Dynamic Window Sizes (동적 윈도우를 갖는 조건부확률 모델을 이용한 한국어 문맥의존 철자오류 교정 규칙의 재현율 향상)

  • Choi, Hyunsoo;Kwon, Hyukchul;Yoon, Aesun
    • Journal of KIISE
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    • v.42 no.5
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    • pp.629-636
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    • 2015
  • The types of errors corrected by a Korean spelling and grammar checker can be classified into isolated-term spelling errors and context-sensitive spelling errors (CSSE). CSSEs are difficult to detect and to correct, since they are correct words when examined alone. Thus, they can be corrected only by considering the semantic and syntactic relations to their context. CSSEs, which are frequently made even by expert wiriters, significantly affect the reliability of spelling and grammar checkers. An existing Korean spelling and grammar checker developed by P University (KSGC 4.5) adopts hand-made correction rules for correcting CSSEs. The KSGC 4.5 is designed to obtain very high precision, which results in an extremely low recall. Our overall goal of previous works was to improve the recall without considerably lowering the precision, by generalizing CSSE correction rules that mainly depend on linguistic knowledge. A variety of rule-based methods has been proposed in previous works, and the best performance showed 95.19% of average precision and 37.56% of recall. This study thus proposes a statistics based method using a conditional probability model with dynamic window sizes. in order to further improve the recall. The proposed method obtained 97.23% of average precision and 50.50% of recall.

A Water Surface Detection Method by Correlation Analysis of Watermark Images with Time Interval (시차가 있는 수위표 이미지의 상관분석을 통한 수면측정기법)

  • Seo, Myoung-Bae;Lee, Chan-Joo;Kim, Dong-Gu
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.1
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    • pp.470-477
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    • 2013
  • The aim of this study is to suggest a detection method of water surface location and its evaluation results of application for same vertical position in two successive images with time interval including both staff gauge and water surface. A specific rectangular inspection area is defined from the top of watermark and then the correlation coefficients for the inspection area of the same position of two images with short time interval is calculated. Accordingly, it is possible to identify differences between changing area and fixed area of pixel density by the water flow. The photographs taken in the laboratory were analyzed in order to validate the proposed technique. As the result of the experiment, it is identified that characteristic of correlation coefficients depends on the size of the inspection area. In the case that the inspection area is within the entire width of the watermark, water surface characteristic according to correlation coefficients is clearly noticeable. Thus, it is identified that the proposed technique can be utilized to search water surfaces. Besides, using corelation analysis of two images with time interval, it is identified that error range between 10 and 42cm was reduced in the level of 2.6cm or less in the contaminated photo of existing image stage gauge. Therefore, it is expected that the suggested method can be utilized to enhance image stage gauge performance improving the previous water surface detection method.

Development of a Simulation Prediction System Using Statistical Machine Learning Techniques (통계적 기계학습 기술을 이용한 시뮬레이션 결과 예측 시스템 개발)

  • Lee, Ki Yong;Shin, YoonJae;Choe, YeonJeong;Kim, SeonJeong;Suh, Young-Kyoon;Sa, Jeong Hwan;Lee, JongSuk Luth;Cho, Kum Won
    • KIPS Transactions on Software and Data Engineering
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    • v.5 no.11
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    • pp.593-606
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    • 2016
  • Computer simulation is widely used in a variety of computational science and engineering fields, including computational fluid dynamics, nano physics, computational chemistry, structural dynamics, and computer-aided optimal design, to simulate the behavior of a system. As the demand for the accuracy and complexity of the simulation grows, however, the cost of executing the simulation is rapidly increasing. It, therefore, is very important to lower the total execution time of the simulation especially when that simulation makes a huge number of repetitions with varying values of input parameters. In this paper we develop a simulation service system that provides the ability to predict the result of the requested simulation without actual execution for that simulation: by recording and then returning previously obtained or predicted results of that simulation. To achieve the goal of avoiding repetitive simulation, the system provides two main functionalities: (1) storing simulation-result records into database and (2) predicting from the database the result of a requested simulation using statistical machine learning techniques. In our experiments we evaluate the prediction performance of the system using real airfoil simulation result data. Our system on average showed a very low error rate at a minimum of 0.9% for a certain output variable. Using the system any user can receive the predicted outcome of her simulation promptly without actually running it, which would otherwise impose a heavy burden on computing and storage resources.