• Title/Summary/Keyword: Minimum statistics

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A bivariate extension of the two-parameter exponential distribution (위치모수를 가지는 이변량지수분포의 개발)

  • 홍연웅
    • The Korean Journal of Applied Statistics
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    • v.11 no.1
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    • pp.185-192
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    • 1998
  • A bivariate extension of the two-parameter exponential distribution is proposed as a model for certain problems in system level life testing. In particular, it applies to two-component shared parallel systems having a minimum guarantee time. Various statistical properties of the model are investigated, including maximum likelihood estimators (MLEs), modified MLEs, and unbiased estimators of the parameters and their distributions.

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Unrelated question model with quantitative attribute by simple cluster sampling (단순집락추출법에 의한 양적속성의 무관질문모형)

  • 이기성;홍기학
    • The Korean Journal of Applied Statistics
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    • v.11 no.1
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    • pp.141-150
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    • 1998
  • In this paper, we developed one-stage cluster randomized response model for obtaining quantitative data by using the Greenberg et al. model(1971) when the population was made up of sensitive quantitative clusters. We obtained the minimum variance by calculating the cluster's size and the optimum number of sample clusters under the some given constant cost. We compared the efficiency of our model with the Greenberg et al. model by simple random sampling.

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Statistical Modeling on Weather Parameters to Develop Forest Fire Forecasting System

  • Trivedi, Manish;Kumar, Manoj;Shukla, Ripunjai
    • The Korean Journal of Applied Statistics
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    • v.22 no.1
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    • pp.221-235
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    • 2009
  • This manuscript illustrates the comparative study between ARIMA and Exponential Smoothing modeling to develop forest fire forecasting system using different weather parameters. In this paper, authors have developed the most suitable and closest forecasting models like ARIMA and Exponential Smoothing techniques using different weather parameters. Authors have considered the extremes of the Wind speed, Radiation, Maximum Temperature and Deviation Temperature of the Summer Season form March to June month for the Ranchi Region in Jharkhand. The data is taken by own resource with the help of Automatic Weather Station. This paper consists a deep study of the effect of extreme values of the different parameters on the weather fluctuations which creates forest fires in the region. In this paper, the numerical illustration has been incorporated to support the present study. Comparative study of different suitable models also incorporated and best fitted model has been tested for these parameters.

LINEAR PRESERVERS OF SYMMETRIC ARCTIC RANK OVER THE BINARY BOOLEAN SEMIRING

  • Beasley, LeRoy B.;Song, Seok-Zun
    • Journal of the Korean Mathematical Society
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    • v.54 no.4
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    • pp.1317-1329
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    • 2017
  • A Boolean rank one matrix can be factored as $\text{uv}^t$ for vectors u and v of appropriate orders. The perimeter of this Boolean rank one matrix is the number of nonzero entries in u plus the number of nonzero entries in v. A Boolean matrix of Boolean rank k is the sum of k Boolean rank one matrices, a rank one decomposition. The perimeter of a Boolean matrix A of Boolean rank k is the minimum over all Boolean rank one decompositions of A of the sums of perimeters of the Boolean rank one matrices. The arctic rank of a Boolean matrix is one half the perimeter. In this article we characterize the linear operators that preserve the symmetric arctic rank of symmetric Boolean matrices.

Splitting and Merging Algorithm Based on Local Statistics of Sub-Regions in Document Image

  • Thapaliya, Kiran;Park, Il-Cheol;Kwon, Goo-Rak
    • Journal of information and communication convergence engineering
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    • v.9 no.5
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    • pp.487-490
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    • 2011
  • This paper presents splitting and merging algorithm based on adaptive thresholding. The algorithm first divides the image into blocks, and then compares each block using the calculated thresholding value. The blocks which are same are merged using the certain threshold value and different blocks are split unless it satisfies the threshold value. When the block has been merged, maximum and minimum block sizes are determined then the average block size is determined. After the average block size is determined the average intensity and standard deviation of average block is calculated. The process of thresholding is applied to binarize the image. Finally, the experimental results show that the proposed method distinguishes clearly the background with text in the document image.

POD Analysis for modeling wind pressures and wind effects of a cylindrical shell roof

  • Li, Fanghui;Chen, Xinzhong
    • Wind and Structures
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    • v.30 no.6
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    • pp.559-573
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    • 2020
  • This paper presents a study on the effectiveness of the proper orthogonal decomposition (POD) technique for reconstruction of wind pressure field as applied to a cylindrical shell roof based on simultaneously measured wind pressure data. The influence of wind loading mode truncation on the statistics of dynamic pressures and wind load effects are investigated. The results showed that truncation of higher wind loading modes can have more noticeable influence on the maximum and minimum pressures that the standard derivation (STD) values. The truncation primarily affects the high-frequency content of the pressures. Estimation of background response using wind loading modes is more effective than the use of traditional structural modal analysis.

Comparison of the BOD Forecasting Ability of the ARIMA model and the Artificial Neural Network Model (ARIMA 모형과 인공신경망모형의 BOD예측력 비교)

  • 정효준;이홍근
    • Journal of Environmental Health Sciences
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    • v.28 no.3
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    • pp.19-25
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    • 2002
  • In this paper, the water quality forecast was performed on the BOD of the Chungju Dam using the ARIMA model, which is a nonlinear statistics model, and the artificial neural network model. The monthly data of water quality were collected from 1991 to 2000. The most appropriate ARIMA model for Chungju dam was found to be the multiplicative seasonal ARIMA(1,0,1)(1,0,1)$_{12}$, model. While the artificial neural network model, which is used relatively often in recent days, forecasts new data by the strength of a learned matrix like human neurons. The BOD values were forecasted using the back-propagation algorithm of multi-layer perceptrons in this paper. Artificial neural network model was com- posed of two hidden layers and the node number of each hidden layer was designed fifteen. It was demonstrated that the ARIMA model was more appropriate in terms of changes around the overall average, but the artificial neural net-work model was more appropriate in terms of reflecting the minimum and the maximum values.s.

A study on the iverse modeling of communication channel by HOS (HOS를 이용한 통신 채널의 역 모델링에 관한 연구)

  • 임성각;진용옥
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.5
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    • pp.1274-1282
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    • 1996
  • This paper deals with an inverse modeling of nonminimum phase communication channel utilizing the HOS (High Order Statistics) of the received signal. After the communication channel is separated into the minimum phase and maximum phase components, the inverse modeling is performed independently. The performance superiority is confirmed by monte-carlo computer simulation in comparison with the traditional CMA (Constant Modulus Algorithm) method. By utilizing the proposed algorithm employing the HOS of the received signal, the inverse frequency characteristics of the channel can be obtained withoug transmitted signal in digital communication. This algorithm is required in preprocessing or postprocessing in order to remove the channel effect, and effective in the self adaptive equalizer which can minimize the bit error rate or symbol error rate in the recovry of received signal.

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Noise Suppression Using Normalized Time-Frequency Bin Average and Modified Gain Function for Speech Enhancement in Nonstationary Noisy Environments

  • Lee, Soo-Jeong;Kim, Soon-Hyob
    • The Journal of the Acoustical Society of Korea
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    • v.27 no.1E
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    • pp.1-10
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    • 2008
  • A noise suppression algorithm is proposed for nonstationary noisy environments. The proposed algorithm is different from the conventional approaches such as the spectral subtraction algorithm and the minimum statistics noise estimation algorithm in that it classifies speech and noise signals in time-frequency bins. It calculates the ratio of the variance of the noisy power spectrum in time-frequency bins to its normalized time-frequency average. If the ratio is greater than an adaptive threshold, speech is considered to be present. Our adaptive algorithm tracks the threshold and controls the trade-off between residual noise and distortion. The estimated clean speech power spectrum is obtained by a modified gain function and the updated noisy power spectrum of the time-frequency bin. This new algorithm has the advantages of simplicity and light computational load for estimating the noise. This algorithm reduces the residual noise significantly, and is superior to the conventional methods.

The Status of Accident and Prevention Measures for Ladles (래들에 의한 재해발생 실태와 예방대책)

  • Choi, Seung Ju;Shin, Woon Chul
    • Journal of the Korea Safety Management & Science
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    • v.16 no.3
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    • pp.201-207
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    • 2014
  • This study is aimed to improve safety of ladle in the metal products manufacturing industry. Burns may occur from spills, spatters or eruptions of hot metal from ladles during pouring or transporting. According to the statistics of occupational accidents about the ladle, many victims were exposed to or contacted with extreme temperatures. The many fatal injuries occurred as a result of unexpected discharging of molten metal due to tipping over ladles. To prevent ladles from turning over, the trunnion axis shall be located below the center of gravity of the ladle at all operating condition. For this purpose, the equation is proposed to calculate the minimum location of a trunnion axis for definite static stability when tilting.