Earticle

최근 소아나 노인 등 상대적으로 의약품 부작용에 취약한 특수환자집단을 대상으로 모델링 및 시뮬레이션 같 은 계량약리 기법을 활용한 안전사용정보 개발 연구가 활발히 진행되고 있다. 특히 제한된 수의 약동∙약력학 시험 결 과로부터 최적의 용법∙용량을 제안하는 집단 약동학 기법이나 유효성 임상 결과가 없더라도 성인과 소아의 약물반응 차이를 비교∙확인 후 적응증을 외삽하는데 활용가능하며, 항생제나 항암제 등의 허가변경에 적용된 사례를 확인 할 수 있다. 미국 FDA나 일본 PMDA 등 해외 규제기관들이 계량약리 관련 가이드라인을 활발히 발표하고 있으며, ICH 역 시 모델-기반 신약 개발 전문가 위원회(MIDD DG) 논의 결과에 따라 관련 가이드라인 제∙개정을 계획하고 있다. 이 러한 국제적 추세에 발맞추어 대한민국 식품의약품안전처 역시 취약계층 대상 의약품 안전사용 근거 마련 연구를 수행하고 있으며 이에 대한 연구 및 기술적 지원을 지속 할 예정이다.

Recently, studies using pharmacometric techniques such as modeling and simulation are being actively conducted to generate the evidences for the safe use of medicines in special population, such as children and the elderly, who are relatively vulnerable to adverse effects. Major examples are the population pharmacokinetic analysis to suggest the optimal dosage from a limited number of pharmacokinetic-pharmacodynamic study results and the extrapolation of indication according to comparing differences in drug responses between adults and children even without clinical trials for efficacy, and these methods were applied to some cases of supplemental applications for antibiotics and anticancer drugs. Regulatory agencies including US FDA and Japan PMDA published continually the guidelines related with pharmacometrics, and the ICH is also planning to enact new guidelines or revise existing guidelines based on the ‘model-informed drug development expert group’ activities. In line with this global trend, the Ministry of Food and Drug Safety is also supporting research to establish scientific grounds for the safe use of medicines in vulnerable groups, and plans to continue research and technical support for this.

영상 인페인팅(image inpainting)은 영상에서 훼손된 부분을 복원하거나 영상 내의 불필요한 문자나 특정 물체를 제거한 후 삭제된 영역을 자연스럽게 채우기 위해 널리 사용되는 기법이다. 예제기반 인페인팅은 비어있는 영역에서 어떤 부분부터 채울 것인지를 결정하는 패치 우선순위 결정과 결정된 패치를 어떤 패치로 채울 것인지 결정하는 패치탐색의 두 부분으로 구성되어 있다. 기존 예제기반 인페인팅에서는 패치 내의 알고 있는 영역의 화소 값만을 이용하여 유사패치를 탐색한다. 이는 패치의 일부분만 이용하여 비교하게 되므로 비교 대상이 아닌 영역에 상관성이 없는 화소 값을 갖는 패치가 선택될 수 있다. 이를 개선하기 위해 본 논문에서는 패치외삽을 이용한 예제기반 인페인팅 방식을 제안한다. 제안 방식은 우선순위가 결정된 패치에 대해 패치 내 이미 알고 있는 영역의 화소 값을 이용하여 패치 내 비어있는 영역의 화소 값을 외삽 방식으로 예측치를 구하여 채운 후 유사 패치를 탐색한다. 실험 결과를 통해 제안방식이 기존 예제기반 인페인팅 방식에 비해 자연스러운 결과 영상을 얻을 수 있음을 보여준다.

Image inpainting is the widely used technique to restore a damaged region or to fill a hole in an image. The exemplar-based technique effectively generates new texture by copying colour values of the most correlated patch in the source into the empty region of the current patch. In traditional exemplar-based synthesis, the patch correlation is computed using only the already filled pixels of the current patch. Thus, by ignoring the correlation between the hole regions of the two patches, an undesirable patch which is highly correlated with the current patch in the already filled area but considerably dissimilar in the area to be filled can be selected, which results in bad texture propagation. To avoid such problems, a new exemplar-based inpainting method using patch extrapolation is proposed. The empty part of the current patch is extrapolated beforehand, and then the complete patch is used for finding its exemplar. Experimental results show that the proposed method provides more natural synthesis results than the conventional ones.

The coverage area of GNSS regional ionospheric correction model is mainly determined by the disribution of GNSS ground monitoring stations. Outside the coverage area, GNSS users may receive ionospheric correction signals but the correction does not contain valid correction information. Extrapolation of the correction information can extend the coverage area to some extent. Three interpolation methods, Kriging, biharmonic spline and cubic spline, are tested to evaluate the extrapolation accuracy of the ionospheric delay corrections outside the correction coverage area. IGS (International GNSS Service) ionosphere map data is used to simulate the corrections and to compute the extrapolation error statistics. Among the three methods, biharmonic method yields the best accuracy. The estimation error has a high value during Spring and Fall. The error has a high value in South and East sides and has a low value in North side.

일반적으로 풍화암에 근입된 현장타설말뚝은 지지력이 매우 크므로 많은 경우에 설계하중만을 검증한 다음 극한하중을 확인하기 전에 재하시험을 종료한다. 그러나 만일 미완성 하중-침하 곡선으로부터 신뢰할 수 있는 극한하중의 예측이 가능하다면 설계의 질적인 향상뿐만 아니라 경제적인 면에서도 크게 기여를 할 수 있을 것이라고 생각된다. 본 연구의 목적은 극한하중을 얻지 못한 말뚝 재하시험의 하중-침하 곡선으로부터 외삽법을 이용하여 추정한 극한하중의 신뢰성 판단 방법을 제안 하는데 있다. 이를 위해 극한하중이 구해진 10본의 말뚝을 3개 현장에 걸쳐서 수집하였다. 그리고 이 10개의 하중-침하 곡선으로부터 Davisson 방법을 이용하여 구한 실제 계측 극한하중의 25%, 50%, 60%, 70%, 80%, 그리고 90%에 해당하는 하중-침하 곡선 자료만이 확보되었다고 가상하고 각각의 자료에 대하여 쌍곡선 방법으로 외삽한 다음, 극한하중을 새로이 결정하였다. 이렇게 결정된 외삽 극한하중의 신뢰성을 통계분석을 통하여 평가하였다. 그 결과, 확보하였다고 가상한 하중-침하 곡선의 최대 침하량 대 외삽 극한하중에서의 침하량 비가 0.6 이상인 경우, 외삽으로 예측한 극한하중은 실제 계측 극한하중보다 평균적으로 20% 이내에서 보수적인 값을 나타내었다. 또한, 항타말뚝의 정재하시험 자료에 대하여 본 논문에서 제안한 방법으로 분석하여 동일한 결과를 확인하였다.

In general, a drilled shaft embedded in weathered rock has a large load bearing capacity. Therefore, most of the load tests are performed only up to the load level that confirms the pile design load capacity, and stopped much before the ultimate load of the pile is attained. If a reliable ultimate load value can be extracted from the premature load test data, it will be possible to greatly improve economic efficiency as well as pile design quality. The main purpose of this study is to propose a method for judging the reliability of the ultimate load of piles that is obtained from extrapolated load test data. To this aim, ten static load test data of load-displacement curves were obtained from testing of piles to their failures from 3 different field sites. For each load-displacement curve, loading was assumed as 25%, 50%, 60%, 70%, 80%, and 90% of the actual pile bearing capacity. The limited known data were then extrapolated using the hyperbolic function, and the ultimate capacity was re-determined for each extrapolated data by the Davisson method (1972). Statistical analysis was performed on the reliability of the re-evaluated ultimate loads. The results showed that if the ratio of the maximum-available displacement to the predicted displacement exceeds 0.6, the extrapolated ultimate load may be regarded as reliable, having less than a conservative 20% error on average. The applicability of the proposed method of judgment was also verified with static load test data of driven piles.

다양한 전자전 상황에서 단위 위협체에 대하여 전자전 모델링과 시뮬레이션을 수행할 수 있는 통합 전자전 시뮬레이터의 개발 필요성이 대두되고 있다. 본 논문에서는 전자전 상황에서 전자정보 수집신호의 변수를 기반으로 전자파신호를 발산하는 레이더 위협을 역추정하기 위한 시뮬레이션 시스템의 구성요소를 분석하고, 역추정 모델을 점진적으로 유지할 수 있는 방법을 제안한다. 또한, 실험을 통하여 점진적 역추정 모델 갱신 기법의 유효성 및 개별 역추정결과의 통합 기법을 평가한다. 개별 역추정 모델의 생성을 위하여 의사결정트리, 베이지안 분류기, 인공신경망 및유클리디안 거리 측정방식과 코사인 유사도 측정방식을 활용하는 군집화 알고리즘을 이용하였다. 첫 번째 실험에서레이더 위협체에 대한 역추정 모델을 구축하기 위한 위협 예제의 크기를 점진적으로 증가시키면 역추정 모델의 정확도는 향상되었으며, 이러한 과정이 반복되면 역추정 모델에 대한 정확도는 일정한 값으로 수렴하였다. 두 번째 실험에서는 개별 역추정 모델의 결과를 통합하기 위하여 투표, 가중투표 및 뎀스터-쉐이퍼 알고리즘을 이용하였으며, 역추정 모델의 통합 결과는 뎀스터-쉐이퍼 알고리즘에 의한 역추정 정확도가 가장 좋은 성능을 보였다.

Various electronic warfare situations drive the need to develop an integrated electronic warfare simulator that can perform electronic warfare modeling and simulation on radar threats. In this paper, we analyze the components of a simulation system to reversely model the radar threats that emit electromagnetic signals based on the parameters of the electronic information, and propose a method to gradually maintain the reverse extrapolation model of RF threats. In the experiment, we will evaluate the effectiveness of the incremental model update and also assess the integration method of reverse extrapolation models. The individual model of RF threats are constructed by using decision tree, naive Bayesian classifier, artificial neural network, and clustering algorithms through Euclidean distance and cosine similarity measurement, respectively. Experimental results show that the accuracy of reverse extrapolation models improves, while the size of the threat sample increases. In addition, we use voting, weighted voting, and the Dempster-Shafer algorithm to integrate the results of the five different models of RF threats. As a result, the final decision of reverse extrapolation through the Dempster-Shafer algorithm shows the best performance in its accuracy.

본 논문은 통합전자전 상황에서 전자정보 수집신호의 변수를 분석하여 전자파 신호를 발산하는 레이더 및 위협체계를 역변환으로 모델링하는 기법을 다루고자 한다. 전자전 수신기가 위협체로부터 수신한 변수 중 가장 중요한 속성을 1-rule 알고리즘을 통하여 파악하였으며, 베이지안 분류 알고리즘, 의사결정 트리 학습 알고리즘 및 인공 신경망알고리즘을 사용하여 위협체를 추정할 수 있는 프로토타입을 구축하였다. 다양한 통합전자전 상황에서 생성한 규칙을 기반으로 역변환 모델을 구축하고 새로운 데이터가 주어지면 모델링한 위협체로 분류한다. 실험에서 베이지안 분류 알고리즘, 의사결정 트리 학습 알고리즘 및 인공 신경망 알고리즘을 각각 적용하여 학습 곡선을 생성하였으며, 학습 곡선에서 최적의 성능을 나타내는 역변환 모델을 실험적으로 정립하였다.

This paper proposes a method to model the reverse extrapolation of RF threats through the attributes representing RF threats in an integrated electronic warfare situation. Using 1-rule algorithm, the most important attribute figuring out the threat could be assured among the attributes which a receiver collected. And also, we build a prototype which estimates threats using three machine learning algorithms, i.e., naive Bayesian classifier, decision tree, and artificial neural network. In various integrated electronic warfare situations, we tested our reverse extrapolation model based on the outputs of machine learning algorithms, where new test data were given to identify a threat. We also generated learning curves for each algorithm, and experimentally decided their optimal reverse extrapolation models. To verify the prototype of our model compiled, we evaluated the accuracy of reverse extrapolation models and the resulting performance showed more than 99% of accuracy.

본 논문에서는 앙상블 학습 기법을 이용하여 전자파 신호를 발산하는 RF(Radio Frequency) 위협체를 역추정하 는 방법에 관하여 논한다. 기존 연구에서 레이더 위협을 생성하고 실제 전자전 상황을 모델링 할 수 있는 시뮬레이 터에 대하여 연구 및 구현하였다. 개발 중인 전자전 시뮬레이터는 다양한 기계학습 알고리즘을 통하여 생성한 모델 을 사용하여 RF 위협체에 대한 역추정 정확도를 실시간으로 제시한다. 본 논문은 구현한 시뮬레이터를 활용하여 RF 위협체의 수집신호변수를 생성 및 수신하며, 앙상블 학습 기법을 이용하여 생성한 역추정 모델에 의하여 위협체 를 역으로 식별하는 방법을 제안한다. 실험에서 다양한 기계학습 알고리즘으로 생성한 모델과 메타 학습 방법론인 앙상블 학습 기법을 적용한 모델을 이용하여 RF 위협체에 대한 역추정 정확도를 측정하고 실험결과를 분석하였다.

In this paper, we discuss a method using an ensemble learning technique for the reverse extrapolation of RF (Radio Frequency) threats that emit electromagnetic signals. We have studied and implemented a simulator that is capable of generating radar threats and modeling the actual electronic warfare situations. The simulator presents the reverse extrapolation accuracy of RF threats in real time. Based upon the electronic warfare signal variables of RF threats in our simulator, we propose a method to reversely identify RF threats through models compiled using ensemble learning techniques. We have measured and analyzed the reverse extrapolation accuracy of the models of RF threats, which are generated by basic machine learning algorithms and by ensemble learning algorithms as a meta-learning framework.

Up to now, plenty of CAD softwares have no function of extension for non-circular curves. Intelligent extension-technology for non-circular curves was studied in this article based on a principle of trend extrapolation. Four kinds of intelligent extension-models were built. These models include quadratic extension-model, cubic extension-model, exponential extension-model, and Gompertz extension-model. Moreover, some methods identifying and choosing for extension-models were discussed, respectively. Several applications of intelligent extension for non-circular curves were offered, which shows us that some curves can be extended for a long distance accurately while they are consistent with the type of extension-models; on the other hand, extension-models built can be available for approximate extension for a short distance while the shapes of non-circular curves are arbitrary. The theories in this paper, as core technologies and key generic problems, can be used for existing CAD softwares to upgrade or develop secondarily.

In this review, we describe the absorption rates (Caco-2 cell permeability) and hepatic/plasma pharmacokinetics of 53 diverse chemicals estimated by modeling virtual oral administration in rats. To ensure that a broad range of chemical structures is present among the selected substances, the properties described by 196 chemical descriptors in a chemoinformatics tool were calculated for 50,000 randomly selected molecules in the original chemical space. To allow visualization, the resulting chemical space was projected onto a two-dimensional plane using generative topographic mapping. The calculated absorbance rates of the chemicals based on cell permeability studies were found to be inversely correlated to the no-observed-effect levels for hepatoxicity after oral administration, as obtained from the Hazard Evaluation Support System Integrated Platform in Japan (r = -0.88, p < 0.01, n = 27). The maximum plasma concentrations and the areas under the concentration-time curves (AUC) of a varied selection of chemicals were estimated using two different methods: simple one-compartment models (i.e., high-throughput toxicokinetic models) and simplified physiologically based pharmacokinetic (PBPK) modeling consisting of chemical receptor (gut), metabolizing (liver), and central (main) compartments. The results obtained from the two methods were consistent. Although the maximum concentrations and AUC values of the 53 chemicals roughly correlated in the liver and plasma, inconsistencies were apparent between empirically measured concentrations and the PBPK-modeled levels. The lowest-observed-effect levels and the virtual hepatic AUC values obtained using PBPK models were inversely correlated (r = -0.78, p < 0.05, n = 7). The present simplified PBPK models could estimate the relationships between hepatic/plasma concentrations and oral doses of general chemicals using both forward and reverse dosimetry. These methods are therefore valuable for estimating hepatotoxicity.

In this paper, we consider approximation of eigenelements of a two dimensional compact integral operator with a smooth kernel by discrete collocation and iterated discrete collocation methods. By choosing numerical quadrature appropriately, we obtain convergence rates for gap between the spectral subspaces, and also we obtain superconvergence rates for eigenvalues and iterated eigenvectors. We then apply Richardson extrapolation to obtain further improved error bounds for the eigenvalues. Numerical examples are presented to illustrate theoretical estimates.

In this paper asymptotic error expansions for mixed finite element approximations to a class of second order elliptic optimal control problems are derived under rectangular meshes, and the Richardson extrapolation of two different schemes and interpolation defect correction can be applied to increase the accuracy of the approximations. As a by-product, we illustrate that all the approximations of higher accuracy can be used to form a class of a posteriori error estimators of the mixed finite element method for optimal control problems.

While the retrial phenomenon plays an important role in communication networks and should not be ignored, retrial systems do not present an exact analytic solution, so approximate techniques are required. To the best of our knowledge, all the existing techniques are based on computing the steady states probabilities. We propose another approach based on the relative state values which appear in the Howard equations. The results of the numerical evaluation carried out show that this solution outperforms previous approaches in terms of both accuracy and computation time.

Investigation of the numerical solution of singularly perturbed turning point problems dates back to late 1970s. However, due to the presence of layers, not many high order schemes could be developed to solve such problems. On the other hand, one could think of applying the convergence acceleration technique to improve the performance of existing numerical methods. However, that itself posed some challenges. To this end, we design and analyze a novel fitted operator finite difference method (FOFDM) to solve this type of problems. Then we develop a fitted mesh finite difference method (FMFDM). Our detailed convergence analysis shows that this FMFDM is robust with respect to the singular perturbation parameter. Then we investigate the effect of Richardson extrapolation on both of these methods. We observe that, the accuracy is improved in both cases whereas the rate of convergence depends on the particular scheme being used.

Food webs have received global attention as next-generation biomonitoring tools; however, it remains challenging because revealing trophic links between species is costly and laborious. Although a link-extrapolation method utilizing published trophic link data can address this difficulty, it has limitations when applied to construct food webs in domestic streams due to the lack of information on endemic species in global literature. Therefore, this study aimed to develop a link extrapolation-based food web model adapted to Korean stream ecosystems. We considered taxonomic similarity of predation and dominance of generalists in aquatic ecosystems, designing taxonomically higher-level matching methods: family matching for all fish (Family), endemic fish (Family-E), endemic fish playing the role of consumers (Family-EC), and resources (Family-ER). By adding the commonly used genus matching method (Genus) to these four matching methods, a total of five matching methods were used to construct 103 domestic food webs. Predictive power of both individual links and food web indices were evaluated by comparing constructed food webs with corresponding empirical food webs. Results showed that, in both evaluations, proposed methods tended to perform better than Genus in a data-poor environment. In particular, Family-E and Family-EC were the most effective matching methods. Our model addressed domestic data scarcity problems when using a link-extrapolation method. It offers opportunities to understand stream ecosystem food webs and may provide novel insights into biomonitoring.

Radiation detection systems working at high count rates suffer from the overlapping of their output electric pulses, known as pulse pile-up phenomenon, resulting in spectrum distortion and degradation of the energy resolution. Pulse tail extrapolation is a pile-up correction method which tries to restore the shifted baseline of a piled-up pulse by extrapolating the overlapped part of its preceding pulse. This needs a mathematical model which is almost always nonlinear, fitted usually by a nonlinear least squares (NLS) technique. NLS is an iterative, potentially time-consuming method. The main idea of the present study is to replace the NLS technique by an integration-based non-iterative method (NIM) for pulse tail extrapolation by an exponential model. The idea of linear extrapolation, as another non-iterative method, is also investigated. Analysis of experimental data of a NaI(Tl) radiation detector shows that the proposed non-iterative method is able to provide a corrected spectrum quite similar with the NLS method, with a dramatically reduced computation time and complexity of the algorithm. The linear extrapolation approach suffers from a poor energy resolution and throughput rate in comparison with NIM and NLS techniques, but provides the shortest computation time.