• 한국포장학회지
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• 제16권1호
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• pp.9-18
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• 2010

For screening test of the non-volatile compounds which migrate from food packaging materials into foodstuffs, the traditional high performance liquid chromatography (HPLC) systems suffer from the lack of universal detector with high sensitivity and universality and high efficiency HPLC separation column which provides complete separation of complex mixtures into all individual substances. In this work, the use possibility of online two-dimensional liquid chromatography (2D-LC) system coupled with a charged aerosol detector (CAD), a universal detector, was reviewed. 2D-LC system permits to improve peak capacity and resolving power for complex mixtures. Charged aerosol detector (CAD) offers a new feasibility for detection of any non-volatile compounds with high sensitivity and constant response factor in a calibration range. The combination of size exclusion chromatography (SEC) and normal phase HPLC (NP-HPLC) is most frequently used for the separation of the natural and synthetic polymers which are mainly used as raw materials for the manufacture of food packaging materials. However, there is no commercial software available for data acquisition and handling and therefore the quantification in 2D-LC analysis is still rare.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2006년도 6th International Meeting on Information Display
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• pp.925-928
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• 2006

With the high sustain frequency at 250 kHz, a three-dimensional diagnostics of excited xenon atoms was investigated by the emission and absorption microscopic spectroscopy for plasma display panels, spatiotemporally. As a typical feature of the emissions, a broad discharge peak was observed on the temporal cathode and a sharp one was monitored on the anode, at the high frequency. However, the discharge starts from the cathode edge, actually, that is a discharge space on the floated address (or data) electrode. Spatially, the dense emission and absorption peak were observed in the discharge space between the sustain electrodes gap. Overall, the microdischarge at high sustain frequency showed priming dominant characteristics.

• 한국생산제조학회지
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• 제6권3호
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• pp.44-51
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• 1997

Unsteady-state temperature distributions and thermal deformations of the spindle of a high precision lathe are studied in this paper. Three dimensional model is built for analysis, and the amount of heat generation of bearing and the thermal characteristic values including heat transfer coefficient are estimated. Temperature distributions and thermal deformations of a model are analyzed using the finite element method and the thermal boundary values. Numerical results are compared with the measured data. The results show that the thermal deformations and the temperature distributions of the dpindle of a high precision lathe can be reasonably estimated using the three dimensional model and the finite element method.

• 한국컴퓨터정보학회논문지
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• 제28권12호
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• pp.191-199
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• 2023

본 논문에서는 자율협력주행을 위한 인프라로써 제작된 5가지 센서 전용 시설물들에 대해 라이다로 취득한 포인트 클라우드 데이터로부터 시설물들의 특징을 추출하는 방법을 제안한다. 자율주행차량에 장착된 영상 취득 센서의 경우에는 기후 환경 및 카메라의 특성 등으로 인해 취득 데이터의 일관성이 낮기 때문에 이를 보완하기 위해서 라이다 센서를 적용했다. 또한, 라이다로 기존의 다른 시설물들과의 구별을 용이하게 하기 위해서 고휘도 반사지를 시설물의 용도별로 디자인하여 부착했다. 이렇게 개발된 5가지 센서 전용 시설물들과 데이터 취득 시스템으로 취득한 포인트 클라우드 데이터로부터 측정 거리별 시설물의 특징을 추출하는 방법으로 해당 시설물에 부착된 고휘도 반사지의 평균 반사강도을 기준으로 특징 포인트들을 추출하여 DBSCAN 방법으로 군집화한 후 해당 포인트들을 투영법으로 2차원 좌표로 변경했다. 거리별 해당 시설물의 특징은 3차원 포인트 좌표, 2차원 투영 좌표, 그리고 반사강도로 구성되며, 추후 개발될 시설물 인식을 위한 모형의 학습데이터로 활용될 예정이다.

• 한국통신학회논문지
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• 제39A권5호
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• pp.215-219
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• 2014

In holographic data storage (HDS), a high transmission rate is accomplished through the use of a charge coupled device array for reading two-dimensional (2D) pixel image data. Although HDS has many advantages in terms of storage capacity and data transmission rates, it also features problems, such as 2D intersymbol interference (ISI) by neighboring pixels and interpage interference (IPI) by multiple images stored in the same holographic volume. Modulation codes can be used to remove these problems. We introduce a 2D 8/9 error-correcting modulation code. The proposed modulation code exploits the trellis-coded modulation scheme, and the code rate is larger (about 0.889) than that of the conventional 6/8 balanced modulation code (an increase of approximately 13.9%). The performance of the bit error rate (BER) with the proposed scheme was improved compared with that of the 6/8 balanced modulation code and the simple 8/9 code without the trellis scheme.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -2
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• pp.798-801
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• 2002

This paper proposes unsupervised classification of multiple attributes via five-layer autoassociative neural network with bottleneck layer. In the conventional methods, high dimensional data are compressed into low dimensional data at bottleneck layer and then feature extraction is performed (Fig.1). In contrast, in the proposed method, analog data is compressed into digital data. Furthermore bottleneck layer is divided into two segments so that each attribute, which is a discrete value, is extracted in corresponding segment (Fig.2).

• Communications for Statistical Applications and Methods
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• 제29권1호
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• pp.41-51
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• 2022

We forecast the US oil consumption level taking advantage of google trends. The google trends are the search volumes of the specific search terms that people search on google. We focus on whether proper selection of google trend terms leads to an improvement in forecast performance for oil consumption. As the forecast models, we consider the least absolute shrinkage and selection operator (LASSO) regression and the structured regularization method for large vector autoregressive (VAR-L) model of Nicholson et al. (2017), which select automatically the google trend terms and the lags of the predictors. An out-of-sample forecast comparison reveals that reducing the high dimensional google trend data set to a low-dimensional data set by the LASSO and the VAR-L models produces better forecast performance for oil consumption compared to the frequently-used forecast models such as the autoregressive model, the autoregressive distributed lag model and the vector error correction model.

• 대한전자공학회논문지TC
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• 제49권7호
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• pp.1-5
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• 2012

자기 저장장치의 한계가 보이는 현 시점에서 홀로그래픽 저장장치는 빠른 데이터 전송율과 높은 기록밀도를 가지고 차세대 광 저장장치의 매력적인 후보로 떠오르고 있다. 본 논문에서는 HDSS (Holographic data storage system)의 채널 환경에서 발생하는 2차원 심볼간 간섭효과와 픽셀 어긋남 문제로 인해 발생하는 비트 오검출 문제를 효율적으로 해결하기 위해서 축약 사상 이론 (contraction mapping theorem) 기반의 반복 2차원 등화 기법을 제안한다. 제안하는 기법의 성능을 평가하기 위해 다양한 홀로그래픽 채널 환경을 구성하고 모의 실험을 수행하여 제안하는 기법의 BER 성능을 측정하여 기존의 threshold detection 기법과 비교함으로써 제안 기법의 우수성을 확인하였다.

• 전기학회논문지
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• 제63권6호
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• pp.797-803
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• 2014

In this paper, 3D face recognition system is designed by using polynomial based on RBFNNs. In case of 2D face recognition, the recognition performance reduced by the external environmental factors such as illumination and facial pose. In order to compensate for these shortcomings of 2D face recognition, 3D face recognition. In the preprocessing part, according to the change of each position angle the obtained 3D face image shapes are changed into front image shapes through pose compensation. the depth data of face image shape by using Multiple Point Signature is extracted. Overall face depth information is obtained by using two or more reference points. The direct use of the extracted data an high-dimensional data leads to the deterioration of learning speed as well as recognition performance. We exploit principle component analysis(PCA) algorithm to conduct the dimension reduction of high-dimensional data. Parameter optimization is carried out with the aid of PSO for effective training and recognition. The proposed pattern classifier is experimented with and evaluated by using dataset obtained in IC & CI Lab.

• Communications for Statistical Applications and Methods
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• 제23권3호
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• pp.259-268
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• 2016

High-dimensional survival data with large numbers of predictors has become more common. The analysis of such data can be facilitated if the dimensions of predictors are adequately reduced. Recent studies show that a method called sliced inverse regression (SIR) is an effective dimension reduction tool in high-dimensional survival regression. However, it faces incapability in implementation due to a double categorization procedure. This problem can be overcome in the right-censoring type by transforming the observed survival time and censoring status into a single variable. This provides more flexibility in the categorization, so the applicability of SIR can be enhanced. Numerical studies show that the proposed transforming approach is equally good to (or even better) than the usual SIR application in both balanced and highly-unbalanced censoring status. The real data example also confirms its practical usefulness, so the proposed approach should be an effective and valuable addition to usual statistical practitioners.