• Title/Summary/Keyword: statistic technique

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Robust Blind Image Watermarking Using an Adaptive Trimmed Mean Operator

  • Hyun Lim;Lee, Myung-Eun;Park, Soon-Young;Cho, Wan-Hyun
    • Proceedings of the IEEK Conference
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    • 2001.09a
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    • pp.231-234
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    • 2001
  • In this paper, we present a robust watermarking technique based on a DCT-domain watermarking approach and an order statistic(OS) filter. The proposed technique inserts one watermark into each of four coefficients within a 2 ${\times}$ 2 block which is scanned on DCT coefficients in the zig-zag ordering from the medium frequency range. The detection algorithm uses an adaptive trimmed mean operator as a local estimator of the embedded watermark to obtain the desired robustness in the presence of additive Gaussian noise and JPEG compression attacks. The performance is analyzed through statistical analysis and numerical experiments. It is shown that the robustness properties against additive noise and JPEG compression attacks are more enhanced than the previous techniques.

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An Approach for the Automatic Box-Jenkins Modelling

  • Park, Sung-Joo;Hong, Chang-Soo;Jeon, Tae-Joon
    • Journal of Korean Institute of Industrial Engineers
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    • v.10 no.1
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    • pp.17-25
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    • 1984
  • The use of Box-Jenkins technique is still very limited due to the high level of knowledge required in comprehending the technique and the cumbersome iterative procedure which requires a large amount of cost and time. This paper proposes a method of automating the univariate Box-Jekins modelling to overcome the limitations of subjective identification in iterative procedure by using Variate Difference method, D-statistic and Pattern Recognition algorithm combined with Akaike's Information Criterion. The results of the application to real data show that the average performance of automatic modelling procedure is better or not worse, at least, than those of the existing models which have been manually set up and reported in the literature.

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A Simulation Analysis of Abnormal Traffic-Flooding Attack under the NGSS environment

  • Kim, Hwan-Kuk;Seo, Dong-Il
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1568-1570
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    • 2005
  • The internet is already a part of life. It is very convenient and people can do almost everything with internet that should be done in real life. Along with the increase of the number of internet user, various network attacks through the internet have been increased as well. Also, Large-scale network attacks are a cause great concern for the computer security communication. These network attack becomes biggest threat could be down utility of network availability. Most of the techniques to detect and analyze abnormal traffic are statistic technique using mathematical modeling. It is difficult accurately to analyze abnormal traffic attack using mathematical modeling, but network simulation technique is possible to analyze and simulate under various network simulation environment with attack scenarios. This paper performs modeling and simulation under virtual network environment including $NGSS^{1}$ system to analyze abnormal traffic-flooding attack.

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Video Segmentation Using New Combined Measure (새로운 결합척도를 이용한 동영상 분할)

  • 최재각;이시웅;남재열
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.40 no.1
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    • pp.51-62
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    • 2003
  • A new video segmentation algorithm for segmentation-based video coding is proposed. The method uses a new criterion based on similarities in both motion and brightness. Brightness and motion information are incorporated in a single segmentation procedure. The actual segmentation is accomplished using a region-growing technique based on the watershed algorithm. In addition, a tracking technique is used in subsequent frames to achieve a coherent segmentation through time. Simulation results show that the proposed method is effective in determining object boundaries not easily found using the statistic criterion alone.

A practical neuro-fuzzy model for estimating modulus of elasticity of concrete

  • Bedirhanoglu, Idris
    • Structural Engineering and Mechanics
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    • v.51 no.2
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    • pp.249-265
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    • 2014
  • The mechanical characteristics of materials are very essential in structural analysis for the accuracy of structural calculations. The estimation modulus of elasticity of concrete ($E_c$), one of the most important mechanical characteristics, is a very complex area in terms of analytical models. Many attempts have been made to model the modulus of elasticity through the use of experimental data. In this study, the neuro-fuzzy (NF) technique was investigated in estimating modulus of elasticity of concrete and a new simple NF model by implementing a different NF system approach was proposed. A large experimental database was used during the development stage. Then, NF model results were compared with various experimental data and results from several models available in related research literature. Several statistic measuring parameters were used to evaluate the performance of the NF model comparing to other models. Consequently, it has been observed that NF technique can be successfully used in estimating modulus of elasticity of concrete. It was also discovered that NF model results correlated strongly with experimental data and indicated more reliable outcomes in comparison to the other models.

The Development of SPC System by the use of Graphic Program (그래픽프로그램을 이용한 SPC 시스템 개발)

  • 이관훈;송병석;천성일;장현덕;홍원식;김경묵;오영환
    • Proceedings of the Korean Reliability Society Conference
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    • 2000.04a
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    • pp.123-129
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    • 2000
  • SPC is the quality improvement technique of gathering since Motorola of U.S.A. have used SPC technique as a statistical process control method for promoting 6-sigma quality improvement strategy in 1988. In Korea, small and medium-sized enterprises are needed building of a system for statistical production control . In the present study, the methods of building SPC system with a moderate cost using a graphic programs of easy-to-use and high flexibility for small and medium-sized enterprises were inquired. The SPC system which enables statistic marking (maximum, minimum, mean, standard deviation, process capability index) and graph marking (X-Y coordinates and histogram) using LabVIEW 5.0, the graphic program by National Instrument Co., Ltd. was implemented in this study.

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Analysis of Determinant Factors of Land Price in Rural Area Using a Hedonic Land Price Model and Spatial Econometric Models (헤도닉분석기법과 공간계량경제모형을 이용한 농촌지역 지가의 영향인자 분석)

  • Suh, Kyo
    • Journal of Korean Society of Rural Planning
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    • v.11 no.3 s.28
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    • pp.11-17
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    • 2005
  • Land prices reflect not only the uses of land, but the potential uses as well(Plantinga, 2002) so land values can be applied to very effective indices for deciding regional status and growing potential. The purpose of this study is to deduce determinant factors of regional land prices. Principal determinants of regional land prices are analyzed with a hedonic technique and spatial econometric models based on 2001 statistic data of Korea except large cities. The results provide the followings. 1. The spatial effect of rural regions are very little with adjacent regions. 2. The common index of land price is population density and other determinant factors are different depending on land uses.

Implementation and Experimental Results of Neural Network and Genetic Algorithm based Spam Filtering Technique (신경망과 운전자 알고리즘을 이용한 스팸 메일 필터링 기법에 구현과 성능평가)

  • Kim Bum-Bae;Choi Hyoung-Kee
    • The KIPS Transactions:PartC
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    • v.13C no.2 s.105
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    • pp.259-266
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    • 2006
  • As the volume of spam has increased to extreme levels, many anti-spam filtering techniques have been proposed. Among these techniques, the machine-Loaming filtering technique is one of the most popular filtering techniques. In this paper, we propose a machine-learning spam filtering technique based on the neural network, the genetic algorithm and the $X^2$-statistic. This proposed filtering technique is designed to overcome the problems in existing filtering techniques, and to achieve high spam filtering accuracy. It is able to classify spam and legitimate emil with 95.25 percent and 95.31 percent accuracy. This accuracy of the sum filtering is 7.75 percent and the 12.44 percent higher than rule-based filtering and the Bayesian filtering technique, respectively.

A Study on the Use of Inferential Statistics in Library and Information Science Research (국내외 문헌정보학분야 연구에서 추론통계 사용에 관한 연구)

  • Ro, Jung-Soon
    • Journal of the Korean Society for Library and Information Science
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    • v.40 no.1
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    • pp.119-138
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    • 2006
  • This Study analyzed the use of statistics in 1,768 research articles published in 2001-2004 in 4 korean & 6 English core journals in the field of library and information science. Korean journals made significantly less use of descriptive and inferential statistics. Of the 663 inferential statistics used in 345 of the 1768 articles, the most frequently used inferential technique was multivariate analysis. There was significant difference in inferential methods used in Korean & English journals, also in traditional library science journals and information science journals.

Long-Term Maximum Power Demand Forecasting in Consideration of Dry Bulb Temperature (건구온파를 오인한 장기최대전력수요예측에 관한 연구)

  • 고희석;정재길
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.34 no.10
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    • pp.389-398
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    • 1985
  • Recently maximum power demand of our country has become to be under the great in fluence of electric cooling and air conditioning demand which are sensitive to weather conditions. This paper presents the technique and algorithm to forecast the long-term maximum power demand considering the characteristics of electric power and weather variable. By introducing a weather load model for forecasting long-term maximum power demand with the recent statistic data of power demand, annual maximum power demand is separated into two parts such as the base load component, affected little by weather, and the weather sensitive load component by means of multi-regression analysis method. And we derive the growth trend regression equations of above two components and their individual coefficients, the maximum power demand of each forecasting year can be forecasted with the sum of above two components. In this case we use the coincident dry bulb temperature as the weather variable at the occurence of one-day maximum power demand. As the growth trend regression equation we choose an exponential trend curve for the base load component, and real quadratic curve for the weather sensitive load component. The validity of the forecasting technique and algorithm proposed in this paper is proved by the case study for the present Korean power system.

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