• 한국지구물리탐사학회:학술대회논문집
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• 한국지구물리탐사학회 2007년도 공동학술대회 논문집
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• pp.81-86
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• 2007

Spectral features of the seismic wave propagation from Odaesan Earthquake were evaluated based on the commonly treated random error between the observed data and the prediction values by the stochastic point-source ground-motion spectral model regarding the source, path and site effects. Radiation pattern of the error according to azimuth angle was found to be similar to the theoretical estimate. It was also observed that the spatial distribution of the errors was correlated with the geological map and the Q0 map which are indicatives of seismic boundaries.

• 한국전산구조공학회논문집
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• 제23권6호
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• pp.627-633
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• 2010

This paper presents a method for identifying the parameter set of inelastic constitutive equations, which is based on an Evolutionary Algorithm. The advantage of the method is that appropriate parameters can be identified even when the measured data are subject to considerable errors and the model equations are inaccurate. The design of experiments suited for the parameter identification of a material model by Chaboche under the uniaxial loading and stationary temperature conditions was first considered. Then the parameter set of the model was identified by the proposed method from a set of experimental data. In comparison to those by other methods, the resultant stress-strain curves by the proposed method correlated better to the actual material behaviors.

• 말소리와 음성과학
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• 제3권1호
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• pp.15-22
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• 2011

The purposes of this study are (1) to investigate the correlation between English word-final stop and the duration of vowels before word-final stop and (2) to suggest a way to detect pronunciation errors and teach the pronunciation of English word-final stops. For these purposes, 18 Korean speakers' production was recorded and analysed using Speech Analyzer and their production was compared with that of native English speakers. In addition, two native English speakers evaluated the subjects' pronunciation. The major findings are the voicing dependent effect of the English vowels produced by native Korean speakers is lower than that of native English speakers; Korean speakers release English word-final stops less than native English speakers; and the pronunciation of English word-final stops and the duration of adjacent vowels are closely related in that the pronunciation score of final stops and the ratio of vowels between the vowels before voiced stops and voiceless stops are correlated. In addition, this study concludes with pedagogical suggestions that may be useful for English pronunciation teaching.

• 산업경영시스템학회지
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• 제34권4호
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• pp.57-65
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• 2011

Monitoring auto correlated processes is prevalent in recent manufacturing environments. As a proactive control for manufacturing processes is emphasized especially in the semiconductor industry, it is natural to monitor real-time status of equipment through sensor rather than resultant output status of the processes. Equipment's sensor data show various forms of correlation features. Among them, considerable amount of sensor data, statistically autocorrelated, is well represented by Box-Jenkins autoregressive moving average (ARMA) model. In this paper, we present a design method of statistical process control (SPC) used for monitoring processes represented by the ARMA model. The proposed method shows benefits in the power of detecting process changes, and considers robustness to ARMA modeling errors simultaneously. We prove benefits through Monte carlo simulation-based investigations.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2001년도 추계학술대회 논문집
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• pp.262-265
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• 2001

In order to investigate the water tree degradation behavior on XLPE cable, direct voltage of 200 to 800V has been applied to the material at 50$^{\circ}C$∼100$^{\circ}C$, and the water tree property has been correlated with voltage and temperature in this study. The leakage current was shown to increase as temperature increased and the Ohm's law was generally satisfied in this experiment though some experimental errors were found. The leakage current was shown to decrease and reach to the stable state with time. It was also shown that the time for the stabilization of leakage current was lessened as voltage increased

• East Asian Economic Review
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• 제25권4호
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• pp.403-424
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• 2021

AdaBoost tweaks the sample weight for each training set used in the iterative process, however, it is demonstrated that it provides more correlated errors as the boosting iteration proceeds if models' accuracy is high enough. Therefore, in this study, we propose a novel way to improve the performance of the existing AdaBoost algorithm by employing heterogeneous models and a stochastic twist. By employing the heterogeneous ensemble, it ensures different models that have a different initial assumption about the data are used to improve on diversity. Also, by using a stochastic algorithm with a decaying convergence rate, the model is designed to balance out the trade-off between model prediction performance and model convergence. The result showed that the stochastic algorithm with decaying convergence rate's did have a improving effect and outperformed other existing boosting techniques.

• 한국통신학회논문지
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• 제37C권11호
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• pp.1084-1093
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• 2012

멀티홉 네트워크에서 TPSN, RBS, FTSP와 같은 기존의 시간 동기화(TS : Tims Synchronization) 방법들은 네트워크의 홉수가 증가 할 경우 TS 오류 또한 증가하게 된다는 단점을 가지고 있다. 이는 멀티홉 네트워크를 통해 구현되는 passive multistatic 레이더 시스템 및 무선 센서 네트워크 노드들 간의 시간 동기화 오류를 증가시켜 시스템 정확도를 저하시키는 중요한 원인이 된다. 따라서 이 논문에서는 동시 협동 전송(CCT : Concurrent Cooperative Transmission)과 반협동 스펙트럼 융합 전송(SCSF : Semi-Cooperative Spectrum Fusion)의 두 종류의 CT (Cooperative Transmission)을 이용한 시간 동기화 방법을 제안하고자 한다. CT를 이용하면 시간 정보가 전달되는 데에 필요한 홉수를 줄여 결과적으로 TS 오류를 줄일 수 있다는 장점을 가지게 된다. CCT는 협동하고 있는 노드들이 디지털하게 인코딩된 동일한 메시지를 각각의 직교한(orthogonal) 채널을 통해서 동시에 전송하면, 수신노드는 이를 수신하여 통합하여 디코딩함으로써 diversity gain을 얻는 전송방식이다. 반면 SCSF는 각각의 노드들이 상관성 있는 아날로그 데이터를 스펙트럼에 실어 동시에 전송하는 방식이다. 이 논문에서는 이 두 가지의 전송방식을 융합한 아날로그 및 디지털 협동 전송 시간 동기화 프로토콜, 즉 CANDI 프로토콜을 제안하고, 이 프로토콜이 멀티홉 네트워크에서 기존의 시간 동기화 방식인 TPSN과 비교하여 상당히 큰 격차로 시간 오류를 줄이는 것을 시뮬레이션을 통해서 증명하고자 한다.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2004년도 GIS/RS 공동 춘계학술대회 논문집
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• pp.493-498
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• 2004

The objective of the present study is to compare various conventional and recently evolved satellite image-processing techniques and to ascertain the best possible technique that can identify and position of aquaculture farms accurately in and around the Younggwang coastal area. Several conventional techniques performed to extract such information fiom the Landsat-TM imagery do not seem to yield better information about the aquaculture farms, and lead to misclassification. The large errors between the actual and extracted aquaculture farm information are due to existence of spectral confusion and inadequate spatial resolution of the sensor. This leads to possible occurrence of mixture pixels or 'mixels' of the source of errors in the classification techniques. Understanding the confusing and mixture pixel problems requires the development of efficient methods that can enable more reliable extraction of aquaculture farm information. Thus, the more recently evolved methods such as the step-by-step partial spectral end-member extraction and linear spectral unmixing methods are introduced. The farmer one assumes that an end-member, which is often referred to as 'spectrally pure signature' of a target feature, does not appear to be a spectrally pure form, but always mix with the other features at certain proportions. The assumption of the linear spectral unmxing is that the measured reflectance of a pixel is the linear sum of the reflectance of the mixture components that make up that pixel. The classification accuracy of the step-by-step partial end-member extraction improved significantly compared to that obtained from the traditional supervised classifiers. However, this method did not distinguish the aquaculture ponds and non-aquaculture ponds within the region of the aquaculture farming areas. In contrast, the linear spectral unmixing model produced a set of fraction images for the aquaculture, water and soil. Of these, the aquaculture fraction yields good estimates about the proportion of the aquaculture farm in each pixel. The acquired proportion was compared with the values of NDVI and both are positively correlated (R$^2$ =0.91), indicating the reliability of the sub-pixel classification.ixel classification.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• 제26권3호
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• pp.183-189
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• 2015

Objectives : The aim of this study was to investigate Korean Wechsler Intelligence profiles and specific abilities related to attention problem of children with attention-deficit hyperactivity disorder (ADHD). Methods : The Korean Wechsler Intelligence Scale for Children-fourth edition (K-WISC-IV) and Advanced Test of Attention (ATA) were administered to 91 children and adolescents (age $8.5{\pm}2.6$ years, 73 boys) with ADHD. Pearson correlation and independent t-tests were used. Results : The means of Working Memory Index (WMI) and Processing Speed Index (PSI) showed a score of low average in K-WISC-IV. WMI scores for the K-WISC-IV showed clinically significant correlations with omission errors, commission errors, and response time variability on auditory ATA. PSI scores also showed significant correlations with response time and variability on visual ATA. In addition, significantly lower digit span backward scores were observed in hyperactive-impulsive/combined subtypes compared to inattentive subtype (t=3.60, p<.001). Conclusion : Children with ADHD showed significantly lower scores in WMI and PSI which were clinically correlated with ATA scores, and hyperactive-impulsive/combined subtypes showed poorer working memory functions in WMI. Follow-up studies are proposed.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.277-282
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• 2006

It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. A Kalman filter can perform optimally only when its dynamic model is correctly defined and the noise statistics for the measurement and process are completely known. It is found that estimated Kalman filter states could be influenced by several factors, including vehicle dynamic variations, filter tuning results, and environment changes, etc., which are difficult to model. Neural networks can map input-output relationships without apriori knowledge about them; hence a proper designed neural network is capable of learning and extracting these complex relationships with enough training. This paper presents a GPS/INS integrated system that combines Kalman filtering and neural network algorithms to improve navigation solutions during GPS outages. An Extended Kalman filter estimates INS measurement errors, plus position, velocity and attitude errors etc. Kalman filter states, and gives precise navigation solutions while GPS signals are available. At the same time, a multi-layer neural network is trained to map the vehicle dynamics with corresponding Kalman filter states, at the same rate of measurement update. After the output of the neural network meets a similarity threshold, it can be used to correct INS measurements when no GPS measurements are available. Selecting suitable inputs and outputs of the neural network is critical for this hybrid method. Detailed analysis unveils that some Kalman filter states are highly correlated with vehicle dynamic variations. The filter states that heavily impact system navigation solutions are selected as the neural network outputs. The principle of this hybrid method and the neural network design are presented. Field test data are processed to evaluate the performance of the proposed method.