• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.709-720
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• 2017

In healthcare and medical research, many important variables have a measurement error such as body mass index and laboratory data. It is also not easy to collect samples of large size because of high cost and long time required to collect the target patient satisfied with inclusion and exclusion criteria. Beside, the demand for solving a complex scientific problem has highly increased so that a semiparametric regression approach could be of substantial value solving this problem. To address the issues of measurement error, small domain and a scientific complexity, we conduct a multivariable Bayesian smoothing under structural measurement error covariate in this article. Specifically we enhance our previous model by incorporating other useful auxiliary covariates free of measurement error. For the regression spline, we use a radial basis functions with fixed knots for the measurement error covariate. We organize a fully Bayesian approach to fit the model and estimate parameters using Markov chain Monte Carlo. Simulation results represent that the method performs well. We illustrate the results using a national survey data for application.

• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.241-246
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• 2020

Hadoop is a framework to process large data sets in a distributed way across clusters of nodes. It has been a popular platform to process big data, but in recent years, other platforms became competitive ones depending on the characteristics of the application. Spark is one of distributed platforms to enable real-time data processing and improve overall processing performance over Hadoop by introducing in-memory processing instead of disk I/O. Whereas Hadoop is designed to work on Java and data analysis is processed using Java API, Spark provides a variety of APIs with Scala, Python, Java and R. In this paper, the goal is to find out whether the APIs of different programming languages af ect the performances in Spark. We chose two popular APIs: Python and Scala. Python is easy to learn and is used in AI domain in a wide range. Scala is a programming language with advantages of parallelism. Our experiment shows much faster processing with Scala API than Python API. For the performance issues on AI-based analysis, further study is needed.

• Wind and Structures
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• v.36 no.6
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• pp.367-377
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• 2023

This study proposes a few-shot learning model for extrapolating the wind pressure of scaled experiments to full-scale measurements. The proposed ML model can use scaled experimental data and a few full-scale tests to accurately predict the remaining full-scale data points (for new specimens). This model focuses on extrapolating the prediction to different scales while existing approaches are not capable of accurately extrapolating from scaled data to full-scale data in the wind engineering domain. Also, the scaling issue observed in wind tunnel tests can be partially resolved via the proposed approach. The proposed model obtained a low mean-squared error and a high coefficient of determination for the mean and standard deviation wind pressure coefficients of the full-scale dataset. A parametric study is carried out to investigate the influence of the number of selected shots. This technique is the first of its kind as it is the first time an ML model has been used in the wind engineering field to deal with extrapolation in wind performance prediction. With the advantages of the few-shot learning model, physical wind tunnel experiments can be reduced to a great extent. The few-shot learning model yields a robust, efficient, and accurate alternative to extrapolating the prediction performance of structures from various model scales to full-scale.

• Journal of KIISE:Databases
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• v.33 no.4
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• pp.396-408
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• 2006

Moving object databases manage a large amount of past location data which are accumulated as the time goes. To retrieve fast the past location of moving objects, we need index structures which consider features of moving objects. The KDB-tree has a good performance in processing range queries. Although we use the KDB-tree as an index structure for moving object databases, there has an over-split problem in the spatial domain since the feature of moving object databases is to increase the time domain. Because the over-split problem reduces spatial regions in the MBR of nodes inverse proportion to the number of splits, there has a problem that the cost for processing spatial-temporal range queries is increased. In this paper, we propose the dynamic split strategy of the KDB-tree to process efficiently the spatial-temporal range queries. The dynamic split strategy uses the space priority splitting method for choosing the split domain, the recent time splitting policy for splitting a point page to maximize the space utilization, and the last division policy for splitting a region page. We compare the performance of proposed dynamic split strategy with the 3DR-tree, the MV3R-tree, and the KDB-tree. In our performance study for range queries, the number of node access in the MKDB-tree is average 30% less than compared index structures.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.7 s.361
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• pp.17-22
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• 2007

OFDM (Orthogonal Frequency Division Multiplexing) is a special case of multicarrier transmission, where a single data stream is transmitted over a number of lower-rate subcarrier. One of the main reasons to use OFDM is to increase robustness against frequency-selective fading or narrowband interference. Unfortunately, an OFDM signal consists of a number of independently modulated subcarriers, which can give a large PAPR (Peak-to-Average Power Ratio) when added up coherently. In this paper, we investigate the performance of a simple PAPR reduction scheme, which requires no change of a receiver structure or no additional information transmission. The approach we employed is clipping in the time and frequency domains. The time-domain clipping is carried out with a predetermined clipping level while the frequency-domain clipping is done within EVM (Error Vector Magnitude). This approach is suboptimal with lower computational complexity compared to the optimal method. This evaluation is carried out on the OFDM system with an nonlinear amplifier. The simulation results demonstrated that the PAPR reduction algorithm is one of ways to reduce the effects of the nonlinear distortion of an HPA (High Power Amplifier).

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.1
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• pp.98-105
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• 2013

This paper presents a finite-difference time-domain(FDTD) simulation and a data processing technique for radar sensing of the internal structure of a wall using an ultra-wide band antenna. We first designed an ultra-wide band anti-podal vivaldi antenna with a frequency range of 0.3~7 GHz which is chosen to be relatively low after considering the characteristics of wave attenuation, wall penetration, and range resolution. In this study the two-dimensional FDTD technique was used to simulate a wall-penetration-radar experiment under practical conditions. The next, the measured radiation pattern of the practical antenna is considered as an equivalent source in the FDTD simulation, and the reflection data of a concrete wall and targets are obtained by using the simulation. Then, a data processing technique has been applied to the FDTD reflection data to get a radar image for remote sensing of the internal structure of the wall. We compared the two different source excitations in the FDTD simulation; (1) commonly-used isotropic point sources and (2) polynomial curve fitting sources of the measured radiation pattern. As a result, when we apply the measured antenna pattern into the FDTD simulation, we could obtain about 2.5 dB higher signal to noise level than using a plane wave incidence with isotropic sources.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.93-106
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• 2021

Blenderbot 2.0 is a dialogue model representing open domain chatbots by reflecting real-time information and remembering user information for a long time through an internet search module and multi-session. Nevertheless, the model still has many improvements. Therefore, this paper analyzes the limitations and errors of BlenderBot 2.0 from three perspectives: model, data, and dialogue. From the data point of view, we point out errors that the guidelines provided to workers during the crowdsourcing process were not clear, and the process of refining hate speech in the collected data and verifying the accuracy of internet-based information was lacking. Finally, from the viewpoint of dialogue, nine types of problems found during conversation and their causes are thoroughly analyzed. Furthermore, practical improvement methods are proposed for each point of view, and we discuss several potential future research directions.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.6 s.52
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• pp.115-123
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• 2006

This paper presents long-term dynamic characteristics of a cable-stayed bridge where installed SHM (Structural Health Monitoring) system. Modal parameters such as natural frequencies and mode shapes are identified by modal analysis using three dimensional finite element model. The developed baseline model has a good correlation with measured natural frequencies identified from field ambient vibrations. By statistical data processing between measured natural frequencies and temperatures, it is demonstrated that the natural frequency is in linearly inverse proportion to the temperature. The estimation of temperature effects against frequency variations is performed. Mode shapes are identified from the TDD (Time Domain Decomposition) technique for ambient vibration measurements. Finally, these results demonstrate that the TDD method can apply to identify modal parameters of a cable-stayed bridge.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.36D no.2
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• pp.81-89
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• 1999

Among various wavelength conversion technologies, that using the cross-gain modulation in laser diode makes it possible to deal with the high speed signal quite simply and efficiently. In this paper, presented was the applicability of an improved time-domain large-signal dynamic model as a CAD tool to analyzed the characteristics of SSGDBR(Superstructure Grating Distributed Bragg Reflector) laser diodes used for wavelength converters. Using this model, it was shown that this kind of wavelength converter can provide the widely tunable wavelength conversion of the high speed data above 10 Gbps. We also investigated the effect of input optical power and the bias current on the characteristics of the device such as extinction ration and eye diagram. The modeling results show very similar trend to the experimental reports.

• Journal of Physiology & Pathology in Korean Medicine
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• v.34 no.1
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• pp.30-36
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• 2020

This study aimed to investigate heart rate variability (HRV) characteristics of cold pattern with repeated measurement data. Participants were taken from a Daejeon University cohort study from 2015 to 2018. Forty-seven of the participants studied displayed cold pattern while 23 showed signs of non-cold pattern. HRV was measured in supine position for 5 minutes at each year, and an 8-item cold pattern questionnaire was used for the diagnosis of cold pattern. SDNN (standard deviation of the NN intervals) and RMSSD (the square root of the mean squared differences of successive NN intervals) were used as time domain analysis, and TP (total power), VLF (power in very low frequency range), LF (power in low frequency range), HF (power in high frequency range), LF norm (LF power in normalized units), HF norm (HF power in normalized units) and LF/HF were used as frequency domain analysis. In the Mann-Whitney U test, LF norm, HF norm, and LF/HF showed differences between the cold pattern group and non-cold pattern group at every measurement, and in the independent t-test, the differences were also observed at three points except for the baseline (2015). In the repeated measures ANOVA, the interaction effects were not observed in all HRV parameters, but the time period effects were observed in SDNN, RMSSD, TP, VLF, LF and HF. There were significant differences between those two groups in LF norm, HF norm and LF/HF. This study suggests that LF norm, HF norm and LF/HF might be a useful indicator of cold pattern properties.