• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제26권2호
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• pp.108-120
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• 2022

We considered qualitative behaviour of the generalization of Einstein's model of Brownian motion when the key parameter of the time interval of free jump degenerates. Fluids will be characterised by number of particles per unit volume (density of fluid) at point of observation. Degeneration of the phenomenon manifests in two scenarios: a) flow of the fluid, which is highly dispersing like a non-dense gas and b) flow of fluid far away from the source of flow, when the velocity of the flow is incomparably smaller than the gradient of the density. First, we will show that both types of flows can be modeled using the Einstein paradigm. We will investigate the question: What features will particle flow exhibit if the time interval of the free jump is inverse proportional to the density and its gradient ? We will show that in this scenario, the flow exhibits localization property, namely: if at some moment of time t₀ in the region, the gradient of the density or density itself is equal to zero, then for some T during time interval [t₀, t₀ + T] there is no flow in the region. This directly links to Barenblatt's finite speed of propagation property for the degenerate equation. The method of the proof is very different from Barenblatt's method and based on the application of Ladyzhenskaya - De Giorgi iterative scheme and Vespri - Tedeev technique. From PDE point of view it assumed that solution exists in appropriate Sobolev type of space.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권9호
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• pp.2458-2482
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• 2023

Medical image segmentation techniques based on convolution neural networks indulge in feature extraction triggering redundancy of parameters and unsatisfactory target localization, which outcomes in less accurate segmentation results to assist doctors in diagnosis. In this paper, we propose a multi-level semantic-rich encoding-decoding network, which consists of a Pooling-Conv-Former (PCFormer) module and a Cbam-Dilated-Transformer (CDT) module. In the PCFormer module, it is used to tackle the issue of parameter explosion in the conservative transformer and to compensate for the feature loss in the down-sampling process. In the CDT module, the Cbam attention module is adopted to highlight the feature regions by blending the intersection of attention mechanisms implicitly, and the Dilated convolution-Concat (DCC) module is designed as a parallel concatenation of multiple atrous convolution blocks to display the expanded perceptual field explicitly. In addition, MultiHead Attention-DwConv-Transformer (MDTransformer) module is utilized to evidently distinguish the target region from the background region. Extensive experiments on medical image segmentation from Glas, SIIM-ACR, ISIC and LGG demonstrated that our proposed network outperforms existing advanced methods in terms of both objective evaluation and subjective visual performance.

• Asian Pacific Journal of Cancer Prevention
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• 제16권5호
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• pp.2003-2007
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• 2015

Background: Elevated serum alpha-fetoprotein (AFP) levels in adults are considered abnormal. This parameter is used mostly in the diagnosis and follow-up of hepatocellular carcinomas and yolk sac tumors. Among the other rare tumors accompanied with elevated serum AFP levels, gastric cancer is the most common. In this study, we evaluated the follow-up and comparison of the treatment and marker response of patients with metastatic gastric cancer who had elevated serum AFP levels. Materials and Methods: We performed a retrospective study, including all consecutive patients with advanced gastric cancer, who received systemic chemotherapy with elevated AFP level. Results: Seventeen metastatic gastric cancer patients with elevated AFP levels at the time of diagnosis were evaluated. Fourteen (82.4%) were males and three (17.6%) were females. The primary tumor localization was the gastric body in 8 (76.4%), cardia in 7 (41.2%), and antrum in 2 (11.8%). Hepatic metastasis was observed in 13 (76.4%) at the time of diagnosis. When the relationship of AFP levels and carcinoembryonic antigen (CEA) response of the patients with their radiologic responses was evaluated, it was found that the radiologic response was compatible with AFP response in 16 (94.1%) patients and with CEA response in 12 (70.6%); however, in 5 (29.4%) patients no accordance was observed between radiological and CEA responses. Conclusions: Follow-up of AFP levels in metastatic gastric cancer patients with elevated AFP levels may allow prediction of early treatment response and could be more useful than the CEA marker for follow-up in response evaluation.

• 대한화학회지
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• 제41권9호
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• pp.488-494
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• 1997

리튬 이온과 소듐 이온을 전기화학적, 화학적인 방버으로 2차원 층상구조의 $FeMoO_4Cl$에 층간 삽입시켰다. $FeMoO_4Cl$에 대한 충방전 곡선에서 넓은 고용체 영역이 관찰되는데, 알칼리 금속이 층간삽입되므로써 발생하는 단위세포 크기의 변화와 전자의 국부화 현상으로 인한 것이다. 리튬이 층간삽입된 경우. $LiFeMoO_4Cl$ 조성 근처에서 좁은 $Li_xFeMoO_4Cl$($0.95{\leq}x{\leq}1.06$) 고용체 영역이 형성된다. Armand 모델을 이용하여 OCV 곡선 fitting을 수행한 결과, 리튬의 층간삽입에 따른 충방전 곡선의 변화는 층간삽입 과정에서 일어나는 이 물질의 전자적, 구조적 변화에 의한 것임을 알 수 있었다.

• 정보처리학회논문지C
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• 제16C권5호
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• pp.615-620
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• 2009

오늘날 무선 장비들이 센서네트워크를 비롯한 매우 다양한 분야에서 광범위하게 사용되고 있다. 무선으로 연결된 센서들은 다양한 임무 수행을 위하여 많은 분야에서 활용되고 있다. 이런 임무를 수행하는데 있어 각 센서의 위치정보는 매우 중요한 시스템 관리의 요소가 된다. 센서노드간 거리 측정은 신호의 도착시간차(Time of Arrival; ToA), 신호세기(Received Signal Strength: RSS), 신호각도(Angle of Arrival: AoA)에 기반을 둔 방법 등이 있다. 무선 센서네트워크에 배치되어 있는 각 센서노드간 정확한 거리 식별을 위해 기존의 거리 측정 방법을 보완하여 거리 오차를 줄이는 ToA기반의 RSS보정 방법을 제안한다. 구체적으로 초음파를 통한 거리측정 값에 맵(RF-MAP)을 통해 보정한 RSS값을 가중치로 보정하여 기존의 거리 측정 방법보다 측정오차를 감소시킬 수 있었다. 실험을 통해 본 연구 방법이 기존 ToA보다 실내($5m{\times}7m$)에서 평균 0.1cm, 실외($10m{\times}10m$) 평균 0.6cm 측정 오차를 줄일 수 있음을 확인 할 수 있었다.

• 제어로봇시스템학회논문지
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• 제19권6호
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• pp.569-575
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• 2013

This paper proposes a method for PDR (Pedestrian Dead-Reckoning) using a low cost IMU. Generally, GPS has been widely used for localization of pedestrians. However, GPS is disabled in the indoor environment such as in buildings. To solve this problem, this research suggests the PDR scheme with an IMU attached to the pedestrian's waist. However, despite the fact many methods have been proposed to estimate the pedestrian's position, but their results are not sufficient. One of the most important factors to improve performance is, a new calibration method that has been proposed to obtain the reliable sensor data. In addition to this calibration, the PDR method is also proposed to detect steps, where estimation schemes of step length, attitude, and heading angles are developed. Peak and zero crossings are detected to count the steps from 3-axis acceleration values. For the estimation of step length, a nonlinear step model is adopted to take advantage of using one parameter. Complementary filter and zero angular velocity are utilized to estimate the attitude of the IMU module and to minimize the heading angle drift. To verify the effectiveness of this scheme, a real-time system is implemented and demonstrated. Experimental results show an accuracy of below 1% and below 3% in distance and position errors, respectively, which can be achievable using a high cost IMU.

• 한국전산구조공학회논문집
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• 제21권1호
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• pp.73-82
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• 2008

본 논문에서는 구조손상 탐색을 위해 매개변수 부 집합 선택에 의한 새로운 정규화 방법을 제안하였다. Residual function을 위해 동적 residual force 벡터를 이용하였다. 과거에는 Residual function으로서 기본 동적 특성치(고유치와 고유모드)를 이용하여 단일구조손상은 탐색할 수 있었지만 다중구조손상 위치를 탐색하기에는 한계가 있었을 뿐 아니라 고유모드와 고유치의 상이한 기여도 때문에 가중치를 적용해야 하는 어려움이 있었다. 본 논문에서 제안된 방법은 고유모드의 불완전한 계측을 보완하기 위하여 모델 확장법을 적용하였다. 제안된 구조손상 탐색법은 다중구조손상 위치를 동시에 찾아 낼 수 있는 장점을 가지고 있다. 2차원 평면 트러스 구조를 이용하여 제안된 방법의 효용성을 검증하였다.

• 한국지진공학회논문집
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• 제7권4호
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• pp.81-87
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• 2003

본 논문에서는 Shannon의 샘플링 이론을 이용하여 제한된 수의 센서에서 얻은 모드형상으로 정확한 모드형상을 재생성하고, 이렇게 재생성한 모드형상을 이용하여 구조물에 발생한 손상을 탐지할 수 있는지의 가능성에 대해 조사하였다. 우선 시간 영역에서의 Shannon의 샘플링 이론을 검토하였고, 이를 공간영역으로 확대하였다. 공간영역으로 확대한 Shannon의 샘플링 이론은 그 효용성을 확인하기 위하여 단순보의 모드형상을 해석적으로 구한 후 최소한으로 제한된 수의 샘플 데이터로 모드형상을 재생하였고 이를 원래의 모드형상과 비교하였다. 이렇게 하여 얻은 결과를 바탕으로 구조물의 모드형상을 추출하는 동적실험에서 필요한 최적 가속도계의 위치를 구할 수 있는 간단한 관계식을 제안하였다. 제안된 관계식과 공간영역으로 확대한 Shannon의 샘플링 이론의 실용성은 연속 2스팬으로 구성된 실험실 빔 구조물의 손상 전과 후의 모드형상에 적용하여 손상을 탐지함으로써 입증하였다.

• 한국음향학회지
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• 제26권8호
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• pp.375-380
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• 2007

잔향실은 사용 목적과 주어진 공간에 따라 적절한 크기와 형태를 갖도록 설계, 시공된다. 그러나 일반 공작물과는 달리 정확한 설계도에 따른 시공이 어렵기 때문에 완공후에는 실제 치수를 측정하여 체적과 표면적 등을 확인하는 것이 중요하다. 이러한 값들은 잔향실을 이용하여 측정하는 건축재료의 음향특성 계산에 직접 사용될 뿐만 아니라 체적 불확도는 음향특성의 불확도 산출에도 중요한 요소이기 때문에 정확하게 계산하여야 한다. 본 논문에서는 잔향실 완공 후, Total Station으로 각 꼭지점의 좌표를 측정하여 이로부터 잔향실의 체적과 불확도를 산출하는 방법을 제시하였다. 잔향실의 체적을 계산한 결과 설계값과 약 5 %의 차이가 나는것을 확인할 수 있었으며, 잔향실 체적의 확장불확도를 평가한 결과 전체 체적의 약 2 %정도인 것을 확인하였다.

• Structural Monitoring and Maintenance
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• 제2권1호
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• pp.77-93
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• 2015

The idea of using measured dynamic characteristics for damage detection is attractive because it allows for a global evaluation of the structural health and condition. However, vibration-based damage detection for complex structures such as long-span cable-supported bridges still remains a challenge. As a suspension or cable-stayed bridge involves in general thousands of structural components, the conventional damage detection methods based on model updating and/or parameter identification might result in ill-conditioning and non-uniqueness in the solution of inverse problems. Alternatively, methods that utilize, to the utmost extent, information from forward problems and avoid direct solution to inverse problems would be more suitable for vibration-based damage detection of long-span cable-supported bridges. The auto-associative neural network (ANN) technique and the probabilistic neural network (PNN) technique, that both eschew inverse problems, have been proposed for identifying and locating damage in suspension and cable-stayed bridges. Without the help of a structural model, ANNs with appropriate configuration can be trained using only the measured modal frequencies from healthy structure under varying environmental conditions, and a new set of modal frequency data acquired from an unknown state of the structure is then fed into the trained ANNs for damage presence identification. With the help of a structural model, PNNs can be configured using the relative changes of modal frequencies before and after damage by assuming damage at different locations, and then the measured modal frequencies from the structure can be presented to locate the damage. However, such formulated ANNs and PNNs may still be incompetent to identify damage occurring at the deck members of a cable-supported bridge because of very low modal sensitivity to the damage. The present study endeavors to enhance the damage identification capability of ANNs and PNNs when being applied for identification of damage incurred at deck members. Effort is first made to construct combined modal parameters which are synthesized from measured modal frequencies and modal shape components to train ANNs for damage alarming. With the purpose of improving identification accuracy, effort is then made to configure PNNs for damage localization by adapting the smoothing parameter in the Bayesian classifier to different values for different pattern classes. The performance of the ANNs with their input being modal frequencies and the combined modal parameters respectively and the PNNs with constant and adaptive smoothing parameters respectively is evaluated through simulation studies of identifying damage inflicted on different deck members of the double-deck suspension Tsing Ma Bridge.