• 천문학회보
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• 제41권1호
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• pp.36.2-37
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• 2016

We study the long-term radio variability of 43 radio bright AGNs by exploiting the data base of the University of Michigan Radio Astronomy Observatory (UMRAO) monitoring program. The UMRAO database provides high quality lightcurves spanning 25 - 32 years in time at three observing frequencies, 4.8, 8, and 14.5 GHz. We model the periodograms (temporal power spectra) of the observed lightcurves as simple power-law noise (red noise, spectral power $P(f){\propto}f^{-{\beta}}$ using Monte Carlo simulations, taking into account windowing effects (red-noise leak, aliasing). The power spectra of 39 (out of 43) sources are in good agreement with the models, yielding a range in power spectral index (${\beta}$) from ${\approx}1$ to ${\approx}3$. We find a strong anti-correlation between ${\beta}$ and the fractal dimension of the lightcurves, which provides an independent check of the quality of our modelling of power spectra. We fit a Gaussian function to each flare in a given lightcurve to obtain the flare duration. We discover a correlation between ${\beta}$ and the median duration of the flares. We use the derivative of a lightcurve to obtain a characteristic variability timescale which does not depend on the assumed functional form of the flares, incomplete fitting, and so on. We find that, once the effects of relativistic Doppler boosting on the observed timescales are corrected, the variability timescales of our sources are proportional to the black hole mass to the power of ${\alpha}=1.70{\pm}0.49$. We see an indication for AGNs in different regimes of accretion rate, flat spectrum radio quasars and BL Lac objects, having different scaling relations with ${\alpha}{\approx}1$ and ${\approx}2$, respectively. We find that modelling the periodograms of four of our sources requires the assumption of broken powerlaw spectra. From simulating lightcurves as superpositions of exponential flares we conclude that strong overlap of flares leads to featureless simple power-law periodograms of AGNs at radio wavelengths in most cases (The paper is about to be submitted to ApJ).

• 지구물리
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• 제2권1호
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• pp.57-64
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• 1999

지표 부근의 수직변위 단층을 굴절파 자료로부터 신속하게 인지하기 위한 효과적 방법을 모색하기 위하여, 컴퓨터 모델링을 통하여 GRM 해석법의 특성을 분석하였다. 속도분석 함수가 수진점 사이 거리인 XY값에 따라 단층 부근에서 형태가 변하는 특성을 이용하여, XY값이 적정값보다 큰 경우와 작은 경우의 속도분석 함수값의 차이를 수평 1차 미분하여 구한 함수를 구하였으며 ''구배변화 지시자''로 명명하였다. 굴절면 경사가 작을수록, XY값의 차이가 클수록 구배변화 지시자의 최대치 진폭이 증가하고 진동거리가 짧아져 단층의 위치를 정확하게 지시하는 것으로 분석된다. 이러한 특성을 갖는 구배변화 지시자는 굴절법으로 얻어진 탄성파 자료를 이용하여 지표 근처의 고경사 단층 위치 및 분포 상태를 파악하는데 효과적으로 사용될 수 있을 것으로 기대된다.

• 농업과학연구
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• 제45권4호
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• pp.823-837
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• 2018

The objective of this study was to evaluate the firmness and the sweetness index (SI) of tomatoes with a hyperspectral imaging (HSI) technique within the wavelength range of 1000 - 1550 nm. The hyperspectral images of 95 tomatoes were acquired with a push-broom hyperspectral reflectance imaging system, from which the mean spectra of each tomato were extracted from the regions of interest. The reference firmness and sweetness index of the same sample was measured and calibrated with their corresponding spectral data by partial least squares (PLS) regression with different preprocessing methods. The calibration model developed by PLS regression based on the Savitzky-Golay second-derivative preprocessed spectra resulted in a better performance for both the firmness and the SI of the tomatoes compared to models developed by other preprocessing methods. The correlation coefficients ($R_{pred}$) were 0.82, and 0.74 with a standard error of prediction of 0.86 N, and 0.63, respectively. Then, the feature wavelengths were identified using a model-based variable selection method, i.e., variable importance in projection, from the PLS regression analyses. Finally, chemical images were derived by applying the respective regression coefficients on the spectral image in a pixel-wise manner. The resulting chemical images provided detailed information on the firmness and the SI of the tomatoes. The results show that the proposed HSI technique has potential for rapid and non-destructive evaluation of firmness and the sweetness index of tomatoes.

• Advances in nano research
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• 제10권4호
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• pp.359-371
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• 2021

A tumor immune interaction is a main topic of interest in the last couple of decades because majority of human population suffered by tumor, formed by the abnormal growth of cells and is continuously interacted with the immune system. Because of its wide range of applications, many researchers have modeled this tumor immune interaction in the form of ordinary, delay and fractional order differential equations as the majority of biological models have a long range temporal memory. So in the present work, tumor immune interaction in fractional form provides an excellent tool for the description of memory and hereditary properties of inter and intra cells. So the interaction between effector-cells, tumor cells and interleukin-2 (IL-2) are modeled by using the definition of Caputo fractional order derivative that provides the system with long-time memory and gives extra degree of freedom. Moreover, in order to achieve more efficient computational results of fractional-order system, a discretization process is performed to obtain its discrete counterpart. Furthermore, existence and local stability of fixed points are investigated for discrete model. Moreover, it is proved that two types of bifurcations such as Neimark-Sacker and flip bifurcations are studied. Finally, numerical examples are presented to support our analytical results.

• Biomolecules & Therapeutics
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• 제30권3호
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• pp.232-237
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• 2022

Autism spectrum disorder (ASD) having core characteristics of social interaction problems and repetitive behaviors and interests affects individuals at varying degrees and comorbidities, making it difficult to determine the precise etiology underlying the symptoms. Given its heterogeneity, ASD is difficult to treat and the development of therapeutics is slow due to the scarcity of animal models that are easy to produce and screen with. Based on the theory of excitation/inhibition imbalance in the brain with ASD which involves glutamatergic and/or GABAergic neurotransmission, a pharmacologic agent to modulate these receptors might be a good starting point for modeling. N-methyl-D-aspartic acid (NMDA) is an amino acid derivative acting as a specific agonist at the NMDA receptor and therefore imitates the action of the neurotransmitter glutamate on that receptor. In contrast to glutamate, NMDA selectively binds to and regulates the NMDA receptor, but not other glutamate receptors such as AMPA and kainite receptors. Given this role, we aimed to determine whether NMDA administration could result in autistic-like behavior in adolescent mice. Both male and female mice were treated with saline or NMDA (50 and 75 mg/kg) and were tested on various behavior experiments. Interestingly, acute NMDA-treated mice showed social deficits and repetitive behavior similar to ASD phenotypes. These results support the excitation/inhibition imbalance theory of ASD and that NMDA injection can be used as a pharmacologic model of ASD-like behaviors.

• Coupled systems mechanics
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• 제10권6호
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• pp.509-520
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• 2021

Fiber-reinforced concrete (FRC) is a composite material where small fibers made from steel or polypropylene or similar material are embedded into concrete matrix. In a material model each constituent should be adequately described, especially the interface between the matrix and fibers that is determined with the 'bond-slip' law. 'Bond-slip' law describes relation between the force in a fiber and its displacement. Bond-slip relation is usually obtained from tension laboratory experiments where a fiber is pulled out from a matrix (concrete) block. However, theoretically bond-slip relation could be determined from bending experiments since in bending the fibers in FRC get pulled-out from the concrete matrix. We have performed specially designed laboratory experiments of three-point beam bending with an intention of using experimental data for determination of material parameters. In addition, we have formulated simple layered model for description of the behavior of beams in the three-point bending test. It is not possible to use this 'forward' beam model for extraction of material parameters so an inverse model has been devised. This model is a basis for formulation of an inverse model that could be used for parameter extraction from laboratory tests. The key assumption in the developed inverse solution procedure is that some values in the formulation are known and comprised in the experimental data. The procedure includes measured data and its derivative, the formulation is nonlinear and solution is obtained from an iterative procedure. The proposed method is numerically validated in the example at the end of the paper and it is demonstrated that material parameters could be successfully recovered from measured data.

• Earthquakes and Structures
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• 제27권1호
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• pp.17-29
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• 2024

The traditional double story isolated structure is a derivative of the base isolated and inter-story isolated structures, while the new double story isolated structure represents a novel variation derived from the traditional double story isolated structure. In order to investigate the seismic response of the new double story isolated structure, a comprehensive structural model was developed. Concurrently, models for the basic fixed, base isolated, inter-story isolated, and traditional double story isolated structures were also established for comparative analysis. The nonlinear dynamic time-history response of the new double story isolated structure under rare earthquake excitations was analyzed. The findings of the study reveal that, in comparison to the basic fixed structure, the new double story isolated structure exhibits superior performance across all evaluated aspects. Furthermore, when compared to the base isolated and inter-story isolated structures, the new double story isolated structure demonstrates significant reductions in inter-story shear force, top acceleration, and inter-frame displacement. The horizontal displacement of the new double story isolated structure is primarily localized within the two isolation layers, effectively dissipating the majority of input seismic energy. In contrast to the traditional double story isolated structure, the new design minimizes displacements within the inter-isolation layer situated in the central part of the frame, as well as mitigates the overturning forces acting on the lower frame column. Consequently, this design ensures the structural integrity of the core tube, thereby preventing potential collapse and structural damage.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1247-1247
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• 2001

Constituents of animal biofluids such as milk, blood and urine contain information specifically related to metabolic and health status of the ruminant animals. Some changes in composition of biofluids can be attributed to disease response of the animals. Mastitis is a major problem for the global dairy industry and causes substantial economic losses from decreasing milk production and reducing milk quality. The purpose of this study was to investigate potential of NIRS combined with multivariate analysis for cow's mastitis diagnosis based on NIR spectra of milk, blood and urine. A total of 112 bulk milk, urine and blood samples from 4 Holstein cows were analyzed. The milk samples were collected from morning milking. The urine samples were collected before morning milking and stored at -35$^{\circ}C$ until spectral analysis. The blood samples were collected before morning milking using a catheter inserted into the carotid vein. Heparin was added to blood samples to prevent coagulation. All milk samples were analyzed for somatic cell count (SCC). The SCC content in milk was used as indicator of mastitis and as quantitative parameter for respective urine and blood samples collected at same time. NIR spectra of blood and milk samples were obtained by InfraAlyzer 500 spectrophotometer, using a transflectance mode. NIR spectra of urine samples were obtained by NIR System 6500 spectrophotometer, using 1 mm sample thickness. All samples were divided into calibration set and test set. Class variable was assigned for each sample as follow: healthy (class 1) and mastitic (class 2), based on milk SCC content. SIMCA was implemented to create models of the respective classes based on NIR spectra of milk, blood or urine. For the calibration set of samples, SIMCA models (model for samples from healthy cows and model for samples from mastitic cows), correctly classified from 97.33 to 98.67% of milk samples, from 97.33 to 98.61% of urine samples and from 96.00 to 94.67% of blood samples. From samples in the test set, the percent of correctly classified samples varied from 70.27 to 89.19, depending mainly on spectral data pretreatment. The best results for all data sets were obtained when first derivative spectral data pretreatment was used. The incorrect classified samples were 5 from milk samples,5 and 4 from urine and blood samples, respectively. The analysis of changes in the loading of first PC factor for group of samples from healthy cows and group of samples from mastitic cows showed, that separation between classes was indirect and based on influence of mastitis on the milk, blood and urine components. Results from the present investigation showed that the changes that occur when a cow gets mastitis influence her milk, urine and blood spectra in a specific way. SIMCA allowed extraction of available spectral information from the milk, urine and blood spectra connected with mastitis. The obtained results could be used for development of a new method for mastitis detection.

• 지능정보연구
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• 제16권2호
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• pp.19-32
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• 2010

학계와 금융파생상품 가격결정이나 변동성매매와 같은 실무영역 모두에서 주식시장의 변동성은 중요한 역할을 한다. 본 연구는 GARCH 모형에 기초하여 한국주식시장의 변동성을 정확히 예측함으로써 변동성매매시스템의 성과를 높일 수 있는 새로운 방법을 제시하였다. 특히, 여러 연구 자료에서 밝혀지고 있는 변동성 비대칭성개념을 도입하였다. 최근 새로 개발된 한국주식시장 변동성 지수인 VKOSPI를 변동성 대용값으로 사용한다. VKOSPI는 KOSPI 200 지수옵션의 가격을 이용하여 계산된 값으로서 옵션딜러들의 변동성 예측치를 반영하고 있다. KOSPI 200 옵션시장은 1997년 시작되었으며, 발전을 거듭하여 현재 하루 거래량이 1,000만 계약을 넘어서면서 세계 최고의 지수옵션시장으로 발전하였다. 이러한 옵션시장에 반영된 변동성을 분석하는 것은 투자자들에게 좋은 투자정보를 제공하게 될 것이다. 특히, 변동성 대용값으로 VKOSPI를 사용하면 다른 변동성 대용치를 사용할 때 발생하는 통계적 추정의 문제를 피해 갈 수 있다. 본 연구는 2003년부터 2006년의 KOSPI 200 지수 일별자료를 대상으로 최우도추정방법(MLE)을 이용하여 GARCH 모형을 추정한다. 비대칭 GARCH 모형으로는 Glosten, Jagannathan, Runke의 GJR-GARCH 모형, Nelson의 EGARCH 모형, 그리고 Ding, Granger, Engle의 PARCH모형을 포함하며 대칭 GARCH 모형은 (1, 1) GARCH 모형을 이용한다. 2007년부터 2009년까지의 KOSPI 200 지수 일별자료를 대상으로 반복적 계산과정을 통해 내일의 변동성 예측값과 오르고 내리는 변화방향을 예측하였다. 분석 결과 시장변동성과 예기치 않은 주가변동 사이에는 음의 상관관계가 존재하며, 음의 주가변동은 동일한 크기의 양의 주가변동보다 훨씬 더 큰 변동성의 증가를 가져옴을 알 수 있다. 즉, 한국 주식시장에도 변동성 비대칭성이 존재함을 보여주었다. GARCH 모형을 이용하여 내일의 VKOSPI의 등락방향을 예측하고 이를 이용하여 변동성 매매시스템을 개발하였다. 내일의 변동성이 상승할 것으로 예측되면 스트래들매수전략을 이용하고 반대로 변동성이 하락할 것으로 예측되면 스트래들 매도전략을 이용한다. 변동성의 변화방향성을 맞춘 경우에는 VKOSPI 변동분을 더하고 틀린 경우에는 변동분을 뺀 누적합을 이용하여 변동성매매전략의 총수익을 계산한다. 모형추정용 자료구간의 경우 통계적 기준인 MSPE 기준으로는 PARCH 모형의 적합도가 가장 높고, 예측방향의 적중도를 재는 MCP 기준으로는 EGARCH 모형이 가장 높은 값을 보여주었다. 테스트용 자료구간의 경우에는 PARCH 모형이 모형적합도와 내일의 변동성 등락방향 예측에서 가장 좋은 결과를 보여주었다. 모형추정용 자료구간의 경우 GARCH 모형 전체에서 매매이익을 기록하고 있고 테스트용 자료구간의 경우에는 EGARCH 모형을 제외한 GARCH 모형들이 매매이익을 보여주었다. 본 연구에서 나타난 변동성의 군집과 비대칭성 현상으로부터 변동성에 비선형성이 존재함을 알 수 있었으며, 비선형성에서 좋은 결과를 보이고 있는 인공지능시스템과 비대칭 GARCH 모형을 결합한다면 제안된 변동성매매시스템의 성과를 많이 개선할 수 있을 것으로 판단된다.

• 한국식품저장유통학회지
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• 제19권1호
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• pp.95-103
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• 2012

본 연구는 원유의 실시간 휴대용품질측정 시스템 개발을 위한 기초 연구로서 원유 시료의 온도에 따른 가시광선-근적외선 스펙트럼을 측정하였으며, 다양한 수학적 전처리방법을 적용하여 유성분 예측모델을 개발하였다. 스펙트럼 측정은 원유 시료 180개에 대해 스펙트럼의 수학적 전처리 방법으로 평활화, 정규화, MSC, 1차 및 2차 미분을 사용하였고 예측모델은 부분최소자승법을 이용하였다. 유성분을 분석한 결과 함량 범위와 평균은 지방이 각각 2.44~6.42%, 4.05%, 단백질은 각각 2.44~4.28%, 3.35%, 무지고형분은 각각 7.85~9.57%, 8.76%로 나타났다. 또한 유당의 함량 범위와 평균은 각각 3.93~5.24%, 4.74%였으며 요소태질소의 경우에는 각각 4.6~15.1 mg/dl, 10.27 mg/dl로 대부분 권장 기준을 만족하였다. 원유 시료의 온도에 따른 스펙트럼은 1,400~2,500 nm에서 큰 차이를 보였으며 온도가 상승함에 따라 흡광도가 높아지는 것을 알 수 있었다. 원유 시료의 온도에 따른 유성분 예측모델을 400~2,500 nm의 영역에서 개발하였으며 예측성능은 지방과 무지고형분의 경우 온도변화와 무관하였다. 단백질과 유당, 요소태질소의 예측성능은 온도가 낮을수록 급격히 감소하여 스펙트럼 측정 시 원유 시료의 온도를 $40^{\circ}C$로 유지하는 것이 필요함을 알 수 있다. $40^{\circ}C$의 원유 스펙트럼에 대해 수학적 전처리를 수행한 결과 평활화를 수행하여 측정 장치 자체의 노이즈를 감소시킬 수 있었고 정규화를 수행하여 기준선을 일치시킬 수 있었다. 또한 MSC를 수행하여 빛의 산란에 의한 영향을 제거하여 스펙트럼간의 차이를 감소시킬 수 있었고 1차 및 2차 미분을 수행한 결과 기준선 일치와 기존 스펙트럼에서 나타나지 않았던 파장영역에 대한 분석이 가능함을 알수 있다. 다중회귀분석의 stepwise 방법을 이용하여 최적 파장영역을 선정하고 유성분 예측모델을 개발한 결과 요소태질소를 제외하고 대부분 근적외선 영역에서 우수한 상관관계를 보여주었다. 지방과 단백질은 원시 스펙트럼의 검증부 결정계수가 각각 0.93, 0.92에서 정규화를 수행한 결과 각각 0.98, 0.92로 원시 스펙트럼의 결과가 우수하여 큰 개선이 없었으나 RPD는 각각 4.10, 3.41에서 5.47, 3.73으로 높아져 정밀도가 향상됨을 알 수 있다. 무지고형분과 유당의 예측모델은 원시 스펙트럼의 경우 각각 0.82, 0.75로 예측모델로 사용하기에는 어려웠으나 각각 평활화와 MSC를 수행하였을 때 검증부 결정계수가 0.90, 0.80으로 크게 개선되어 유성분 예측모델의 신뢰성 향상에 기여할 수 있을 것으로 판단된다. 요소태질소의 경우 가시광선 영역에서 가장 우수한 상관관계를 보여주었으나 검증부 결정계수, 오차, RPD가 각각 0.61, 1.56%, 1.58로 다른 성분에 비해 매우 낮게 나타났다. 이를 개선하기 위해 수학적 전처리를 수행하였으나 크게 개선되지 않았으므로 요소태질소의 신뢰성 있는 모델을 개발하기 위해서는 부분최소자승법 외에 다양한 알고리즘의 적용이 필요할 것으로 판단된다.