• Journal of the Society of Naval Architects of Korea
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• v.52 no.1
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• pp.88-95
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• 2015

For the frequency-domain spectral fatigue analysis, the probability density function of stress range needs to be estimated based on the stress spectrum only, which is a frequency domain representation of the response. The probability distribution of the stress range of the narrow-band spectrum is known to follow the Rayleigh distribution, however the PDF of wide-band spectrum is difficult to define with clarity due to the complicated fluctuation pattern of spectrum. In this paper, efforts have been made to figure out the links between the probability density function of stress range to the structural response of wide-band Gaussian random process. An artificial neural network scheme, known as one of the most powerful system identification methods, was used to identify the multivariate functional relationship between the idealized wide-band spectrums and resulting probability density functions. To achieve this, the spectrums were idealized as a superposition of two triangles with arbitrary location, height and width, targeting to comprise wide-band spectrum, and the probability density functions were represented by the linear combination of equally spaced Gaussian basis functions. To train the network under supervision, varieties of different wide-band spectrums were assumed and the converged probability density function of the stress range was derived using the rainflow counting method and all these data sets were fed into the three layer perceptron model. This nonlinear least square problem was solved using Levenberg-Marquardt algorithm with regularization term included. It was proven that the network trained using the given data set could reproduce the probability density function of arbitrary wide-band spectrum of two triangles with great success.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.3
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• pp.19-28
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• 2015

With the aim of developing a smartphone-based point-of-care device that is small, inexpensive, and easy to handle by non-expert, we designed a fluorescence smartscope for counting particles and a DC motor-controlled particle positioning system. Our smartscope can count the number of fluorescent particles and fluorescently-stained white blood cells through a phone camera with an adaptor containing a LED, a ball lens and optical filters and an application running on a smartphone. The motor was controlled wirelessly via Bluetooth with an Android smartphone. We found that axial spinning of a helical microfluidic channel allows arrangement of particles having size similar to the white blood cells. The motor-controlled particle positioning system can minimize time-consuming manual processes and automate sample preparation process and thus, if integrated with the smartscope, it can be used for a point-of-care testing device based on a smartphone.

• Journal of Radiation Protection and Research
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• v.34 no.2
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• pp.55-64
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• 2009

In a pressurized heavy water reactor (PHWR), radiation workers who have access to radiation controlled areas submit their urine samples to health physicists periodically; internal radiation exposure is evaluated by the monitoring of these urine samples. Internal radiation exposure at PHWRs accounts for approximately 20 $\sim$ 40% of total radiation exposure; most internal radiation exposure is attributed to tritium. Carbon-14 is not a dominant nuclide in the radiation exposure of workers, but it is one potential nuclide to be necessarily monitored. Carbon-14 is a low energy beta emitter and passes relatively easily into the body of workers by inhalation because its dominant chemical form is radioactive carbon dioxide ($^{14}CO_2$). Most inhaled carbon-14 is rapidly exhaled from the worker's body, but a small amount of carbon-14 remains inside the body and is excreted by urine. In this study, a method for dual analysis of tritium and carbon-14 in urine samples of workers at nuclear power plants is developed and a method for internal dose assessment using its excretion rate result is established. As a result of the developed dual analysis of tritium and carbon-14 in urine samples of radiation workers who entered the high radiation field area at a PHWR, it was found that internal exposure to carbon-14 is unlikely to occur. In addition, through the urine counting results of radiation workers who participated in the open process of steam generators, it was found that the likelihood of internal exposure to either tritium or carbon-14 is extremely low at pressurized water reactors (PWRs).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.935-941
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• 2020

People estimation is important to provide IoT services. Most people counting technologies use camera or sensor data. However, the conventional technologies have the disadvantages of invasion of privacy and the need to install extra infrastructure. This paper proposes a method for estimating the number of people using a Wi-Fi AP. We use channel state information of Wi-Fi and analyze that using deep learning technology. It can be achieved by pre-installed Wi-Fi infrastructure that reduce cost for people estimation and privacy infringement. The proposed algorithm uses a k-binding data for pre-processing process and a 1D-CNN learning model. Two APs were installed to analyze the estimation results of six people. The result of the accurate number estimation was 64.8%, but the result of classifying the number of people into classes showed a high result of 84.5%. This algorithm is expected to be applicable to estimate the density of people in a small space.

• Journal of the Korean Data and Information Science Society
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• v.5 no.2
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• pp.59-74
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• 1994

The hazard ratio may be useful as a descriptive measure to compare the hazard experience of a treatment group with that of a control group. In this paper, we propose a kernel estimator of hazard ratio with censored survival data. The uniform consistency and asymptotic normality of the proposed estimator are proved by using counting process approach. In order to assess the performance of the proposed estimator, we compare the kernel estimator with Cox estimator and the generalized rank estimators of hazard ratio in terms of MSE by Monte Carlo simulation.

• Journal of the Korean Data and Information Science Society
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• v.5 no.2
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• pp.29-44
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• 1994

본 연구는 누적위험률함수에 대한 베이지안 추정량을 이용하여 생존함수의 추정량을 제안하고, counting process 이론과 martingale 이론을 이용하여 대표본하에서 제안된 추정량의 일양적 일치성과 점근적 정규성을 밝힌다. 또한 모의실험을 통하여 추정량들의 효율성을 편의와 평균제곱오차의 측면에서 비교하고자 한다.

• Communications for Statistical Applications and Methods
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• v.3 no.3
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• pp.195-204
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• 1996

Some rank tests for comparing r treatments against ordered alternatives are proposed when some of data are randomly cemsored, which are the weighted logrank tests based on pairwise-ranking scheme. The covariances of the proposed test statistics are explicitly obtained from the results of the counting process theory and the test procedures are illustrated by a numerical example. Simulation studies are also performed for comparing with the other well-known tests.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.370-373
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• 1989

It has been reported that the formation of conductive carbon path is mainly affected by scintillation. In this paper, mechanisms of tracking deterioration are reviewed by counting light pulse with IR photodiode. The influence of applied voltage and molecular composition of materials in the tracking breakdown is also reviewed by the Number of Pulse curve.

• Journal of the Korean Data and Information Science Society
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• v.3 no.1
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• pp.79-90
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• 1992

We consider hazard ratio as a descriptive measure to compare the hazard experience of a treatment group with that of a control group with censored survival data. In this paper, we propose a kernel estimator of hazard ratio. The uniform consistency and asymptotic normality of a kernel estimator are proved by using counting process approach via martingale theory and stochastic integrals.

• Education of Primary School Mathematics
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• v.5 no.2
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• pp.111-119
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• 2001

Over the years, the benefits of instructional manipulatives in mathematics education have been verified by classroom practice and educational research. The purpose of this paper is to introduce how the instructional material, specifically, geoboard could be used and integrated in elementary mathematics classroom in order to develop student's mathematical concepts and process in terms of the following areas: (1) Number '||'&'||' Operation : counting, fraction '||'&'||' additio $n_traction/multiplication (2) Geometry : geometric concepts (3) Geometry : symmetry '||'&'||' motion (4) Measurement : area '||'&'||' perimeter (5) Probability '||'&'||' Statistics : table '||'&'||' graph (6) Pattern : finding patterns Further, future study will continue to foster how manipulatives will enhance children's mathematics knowledge and influence on their mathematics performance.