• ETRI Journal
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• 제36권2호
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• pp.329-332
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• 2014

In this letter, the problem of estimating the physical layer (PL) scrambling code sequence of DVB-S2 is studied. We present the first ever scheme to estimate the scrambling sequence. The scheme is based on hypothesis testing. By analyzing the PL scrambling process, we construct a new sequence equivalent to the scrambling sequence. We then use hypothesis testing to estimate the new sequence. The threshold for the hypothesis testing is also discussed. The experiment results show that the performance of our estimation scheme can work even under high BER.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권3호
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• pp.1393-1405
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• 2017

It is well known that duty-cycling control by dynamically adjusting the polling interval according to the traffic loads can effectively achieve power saving in wireless sensor networks. Thus, there has been a significant research effort in developing polling interval adaptation schemes. Especially, Dynamic Low Power Listening (DLPL) scheme is one of the most widely adopted open-looping polling interval adaptation techniques in wireless sensor networks. In DLPL scheme, if consecutive idle (busy) samplings reach a given fixed threshold, the polling interval is increased (decreased). However, due to the trial-and-error based approach, it may significantly deteriorate the system performance depending on given threshold parameters. In this paper, we propose a novel DLPL scheme, called SDL (Sequential hypothesis testing based Dynamic LPL), which employs sequential hypothesis testing to decide whether to change the polling interval conforming to various traffic conditions. Simulation results show that SDL achieves substantial power saving over state-of-the-art DLPL schemes.

• Journal of the Korean Data and Information Science Society
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• 제28권1호
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• pp.217-225
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• 2017

This article deals with the problem of multiple hypothesis testing for the shape parameter in the generalized exponential distribution. We propose Bayesian hypothesis testing procedures for multiple hypotheses of the shape parameter with the noninformative prior. The Bayes factor with the noninformative prior is not well defined. The reason is that the most of the noninformative prior can be improper. Therefore we study the default Bayesian multiple hypothesis testing methods using the fractional and intrinsic Bayes factors with the reference priors. Simulation study is performed and an example is given.

• Structural Engineering and Mechanics
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• 제26권5호
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• pp.499-516
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• 2007

An experimental method denoted as Impulse Method is proposed as a cost-effective non-destructive technique for the on-site evaluation of concrete elastic modulus in existing structures: on the basis of Hertz's quasi-static theory of elastic impact and with the aid of a simple portable testing equipment, it makes it possible to collect series of local measurements of the elastic modulus in an easy way and in a very short time. A Hypothesis Testing procedure is developed in order to provide a statistical tool for processing the data collected by means of the Impulse Method and assessing the possible occurrence of significant variations in the elastic modulus without exceeding some prescribed error probabilities. It is based on a particular formulation of the renowned sequential probability ratio test and reveals to be optimal with respect to the error probabilities and the required number of observations, thus further improving the time-effectiveness of the Impulse Method. The results of an experimental investigation on different types of plain concrete prove the validity of the Impulse Method in estimating the unknown value of the elastic modulus and attest the effectiveness of the proposed Hypothesis Testing procedure in identifying significant variations in the elastic modulus.

• 대한안전경영과학회지
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• 제15권1호
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• pp.283-292
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• 2013

This paper aims to propose a new steps of hypothesis testing using analysis process and improvement process in the six sigma DMAIC. The six sigma implementation models proposed in this paper consist of six steps. The first step is to establish a research hypothesis by specification directionality and FBP(Falsibility By Popper). The second step is to translate the research hypothesis such as RHAT(Research Hypothesis Absent Type) and RHPT(Research Hypothesis Present Type) into statistical hypothesis such as $H_0$(Null Hypothesis) and $H_1$(Alternative Hypothesis). The third step is to implement statistical hypothesis testing by PBC(Proof By Contradiction) and proper sample size. The fourth step is to interpret the result of statistical hypothesis test. The fifth step is to establish the best conditions of product and process conditions by experimental optimization and interval estimation. The sixth step is to draw a conclusion by considering practical significance and statistical significance. Important for both quality practitioners and academicians, case analysis on six sigma projects with implementation guidelines are provided.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2006년도 춘계학술대회 학술발표 논문집 제16권 제1호
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• pp.199-202
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• 2006

We propose some properties of fuzzy p-value and fuzzy significance level to the test statistics for the fuzzy hypotheses testing. Appling the principle of agreement index, we suggest two method for fuzzy hypothesis testing by fuzzy rejection region and fuzzy p-value with fuzzy hypothesis $H_{f,0}$.

• Journal of the Korean Data and Information Science Society
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• 제23권6호
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• pp.1299-1308
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• 2012

This article deals with the problem of testing the equality of the scale parameters in nonregular Pareto distributions.We propose Bayesian hypothesis testing procedures for the equality of the scale parameters under the noninformative prior. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be de ned up to a multiplicative constant. So we propose the default Bayesia hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and a real data example are provided.

• Journal of the Korean Data and Information Science Society
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• 제25권2호
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• pp.465-472
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• 2014

This article deals with the problem of testing the equality of the scale parameters in the half logistic distributions. We propose Bayesian hypothesis testing procedures for the equality of the scale parameters under the noninformative priors. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be dened up to a multiplicative constant. Thus we propose the default Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and an example are provided.

• 한국과학교육학회지
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• 제19권1호
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• pp.117-127
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• 1999

최근의 보고에 따르면 우리 나라 학생들은 학년이 높아질수록 과학적 수준은 반대로 떨어지는 경향을 보이고 있지만 고등학교 이후 집단의 과학적 추론능력에 대한 연구는 체계적으로 이루어지지 않고 있다. 특히 가설검정능력과 관련된 과학적 추론은 가장 고등한 인지기능의 하나로 여겨지고 있고, 또 창의적이고 비판적인 사고에 매우 중요하다고 보고되어 왔다. 따라서 본 연구는 우리나라 대학생들의 과학적 추론 능력을 조사하고, 이를 미국 대학생들의 과학적 추론 능력과 비교하여 분석하였다. 아울러 본 연구는 가설 검정능력이 과학적 추론능력의 다른 하위요소에 비해 고등한 추론기능이라는 가설도 검정하였다. 고등학교 이후의 과학적 추론에 대한 경향을 조사하기 위하여 본 연구는 한국의 대학생 774명과 미국의 대학생 568명에게 과학적 추론 검사를 실시하여서 비교 분석하였고, 이 자료를 토대로 가설검정능력이 과학적 추론의 다른 하위요소에 비해 고등한 추론이라는 가설도 검정하였다. 본 연구에 사용된 과학적 추론 검사는 보존논리, 비례논리, 변인통제, 확률논리, 상관논리, 그리고 가설검정기능에 관련된 127개의 과제로 구성되어 있다. 본 연구의 결과는 한국 대학생들이 비례 및 확률논리를 평가하는 과제에 대해서는 미국 학생들보다 월등하게 높은 접수를 기록하였고, 보존이나 변인통제, 그리고 상관논리를 평가하는 과제에 대해서는 반대의 경향을 나타내었다. 또한 가설검정 능력을 평가하는 문항에서는 양국 모두 다른 과학적 추론 과제에 비해서 뚜렷하게 낮은 점수를 보여주었다. 본 연구는 이들 결과에 대해서 본 연구의 목적과 관련해서 논의하였고 이의 교육적 적용에 대해서도 논의하였다.

• 한국멀티미디어학회논문지
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• 제10권12호
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• pp.1559-1565
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• 2007

The many target-detection methods that use forward-looking infrared (FUR) images can deal with large targets measuring $70{\times}40$ pixels, utilizing their shape features. However, detection small targets is difficult because they are more obscure and there are many target-like objects. Therefore, few studies have examined how to detect small targets consisting of fewer than $30{\times}10$ pixels. This paper presents a small target detection method using clutter rejection with stochastic hypothesis testing for FLIR imagery. The proposed algorithm consists of two stages; detection and clutter rejection. In the detection stage, the mean of the input FLIR image is first removed and then the image is segmented using Otsu's method. A closing operation is also applied during the detection stage in order to merge any single targets detected separately. Then, the residual of the clutters is eliminated using statistical hypothesis testing based on the t-test. Several FLIR images are used to prove the performance of the proposed algorithm. The experimental results show that the proposed algorithm accurately detects small targets (Jess than $30{\times}10$ pixels) with a low false alarm rate compared to the center-surround difference method using the receiver operating characteristics (ROC) curve.