• Earthquakes and Structures
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• 제22권2호
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• pp.185-201
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• 2022

Structural Health Monitoring (SHM) is used to provide reliable information about the structure's integrity in near realtime following extreme incidents such as earthquakes, considering the inevitable aging and degradation that occurs in operating environments. This paper experimentally investigates an integrated wireless sensor network (Wi-SN) based monitoring technique for damage detection in concrete structures. An effective SHM technique can be used to detect potential structural damage based on post-earthquake data. Two novel methods are proposed for damage detection in reinforced concrete (RC) building structures including: (i) Jerk Energy Method (JEM), which is based on time-domain analysis, and (ii) Modal Contributing Parameter (MCP), which is based on frequency-domain analysis. Wireless accelerometer sensors are installed at each story level to monitor the dynamic responses from the building structure. Prior knowledge of the initial state (immediately after construction) of the structure is not required in these methods. Proposed methods only use responses recorded during ambient vibration state (i.e., operational state) to estimate the damage index. Herein, the experimental studies serve as an illustration of the procedures. In particular, (i) a 3-story shear-type steel frame model is analyzed for several damage scenarios and (ii) 2-story RC scaled down (at 1/6th) building models, simulated and verified under experimental tests on a shaking table. As a result, in addition to the usual benefits like system adaptability, and cost-effectiveness, the proposed sensing system does not require a cluster of sensors. The spatial information in the real-time recorded data is used in global damage identification stage of SHM. Whereas in next stage of SHM, the damage is detected at the story level. Experimental results also show the efficiency and superior performance of the proposed measuring techniques.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제15권3호
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• pp.145-153
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• 2009

궤적(trajectory) 데이타는 실세계 어디에서든지 쉽게 찾아볼 수 있다. 최근 들어, 위성, 센서, RFID, 비디오 및 무선 통신 기술의 발전으로 말미암아 이동 객체를 체계적으로 추적하고, 많은 양의 궤적데이타를 수집할 수 있게 되었다. 이에 따라, 궤적 데이타의 분석에 대한 필요성이 점차 증대되고 있다. 본 논문에서는 대규모 궤적 데이타를 위한 마이닝 툴을 개발한다. 본 마이닝 툴에서는 가장 널리 사용되는 마이닝 연산인 집단화(clustering), 분류(classification), 이상치 발견(outlier detection)을 제공한다. 궤적 집단화는 공통적인 이동 패턴을 발견하며, 궤적 분류는 궤적에 기반하여 이동 객체의 범주를 예측하며, 궤적 이상치 발견은 나머지 궤적들과 크게 다르거나 일관적이지 않은 궤적을 발견한다. 본 마이닝 툴의 가장 큰 장점은 데이타 마이닝 도중에 부분 궤적 정보를 활용한다는 점이다. 본 마이닝 툴의 우수성은 다양한 실제 궤적 데이타 셋을 사용하여 입증되었다. 본 논문의 결과로 궤적 데이타 마이닝을 위한 실용적인 소프트웨어를 개발하였고 많은 실제 응용에 적용될 수 있을 것이라 사료된다.

• Smart Structures and Systems
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• 제18권3호
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• pp.501-523
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• 2016

Electromechanical impedance (EMI) based structural health monitoring is performed by measuring the variation in the impedance due to the structural local damage. The impedance signals are acquired from the piezoelectric patches that are bonded on the structural surface. The impedance variation, which is directly related to the mechanical properties of the structure, indicates the presence of local structural damage. Two traditional EMI-based damage detection methods are based on calculating the difference between the measured impedance signals in the frequency domain from the baseline and the current structures. In this paper, a new structural damage detection approach by analyzing the time domain impedance responses is proposed. The measured time domain responses from the piezoelectric transducers will be used for analysis. With the use of the Time Frequency Autoregressive Moving Average (TFARMA) model, a damage index based on Singular Value Decomposition (SVD) is defined to identify the existence of the structural local damage. Experimental studies on a space steel truss bridge model in the laboratory are conducted to verify the proposed approach. Four piezoelectric transducers are attached at different locations and excited by a sweep-frequency signal. The impedance responses at different locations are analyzed with TFARMA model to investigate the effectiveness and performance of the proposed approach. The results demonstrate that the proposed approach is very sensitive and robust in detecting the bolt damage in the gusset plates of steel truss bridges.

• 융합보안논문지
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• 제23권2호
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• pp.85-94
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• 2023

북한에 의한 위협이 증대되고 있는 엄중한 안보 상황에서 우리 군은 첨단기술을 활용한 GOP 과학화 경계시스템의 성능개량 사업을 통해 병력 절감 효과를 추구하고 있다. GOP 과학화 경계시스템이 인구절벽에 따른 병역자원 감소에 대한 효과적인 대안이 되기 위해서는 높은 탐지 및 식별률이 보장되어야 하고, 오탐율을 획기적으로 개선함으로써 병력의 개입이 최소화되어야 한다. 그런데, 현(現) GOP 과학화 경계시스템의 경우 양호한 기상환경에서는 비교적 높은 탐지 및 식별률을 보장하지만, 강우 및 안개 등의 악천후 상황에서의 성능은 다소 부족한 것으로 알려져 있다. 이를 극복할 수 있는 대안으로 악천후 시에도 물체를 탐지할 수 있는 레이더 기반 경계시스템이 하나의 대안으로 제시되고 있는데, 본 논문은 2021년 신속시범획득사업을 통해00사단에서 운용 중인 레이더 기반 AI 과학화 경계시스템의 악천후 상황에서의 효과성을 검증하고 이를 통해 향후 GOP 과학화 경계시스템의 발전 방향을 제시한다.

• 산업경영시스템학회지
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• 제46권4호
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• pp.312-320
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• 2023

Recently, there has been an increasing attempt to replace defect detection inspections in the manufacturing industry using deep learning techniques. However, obtaining substantial high-quality labeled data to enhance the performance of deep learning models entails economic and temporal constraints. As a solution for this problem, semi-supervised learning, using a limited amount of labeled data, has been gaining traction. This study assesses the effectiveness of semi-supervised learning in the defect detection process of manufacturing using the MixMatch algorithm. The MixMatch algorithm incorporates three dominant paradigms in the semi-supervised field: Consistency regularization, Entropy minimization, and Generic regularization. The performance of semi-supervised learning based on the MixMatch algorithm was compared with that of supervised learning using defect image data from the metal casting process. For the experiments, the ratio of labeled data was adjusted to 5%, 10%, 25%, and 50% of the total data. At a labeled data ratio of 5%, semi-supervised learning achieved a classification accuracy of 90.19%, outperforming supervised learning by approximately 22%p. At a 10% ratio, it surpassed supervised learning by around 8%p, achieving a 92.89% accuracy. These results demonstrate that semi-supervised learning can achieve significant outcomes even with a very limited amount of labeled data, suggesting its invaluable application in real-world research and industrial settings where labeled data is limited.

• 융합보안논문지
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• 제23권5호
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• pp.135-142
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• 2023

생활 폐기물 쓰레기는 기후 변화, 자원 부족, 환경 오염을 불러오는 대표적인 문제로서, 이러한 문제를 해결하기 위해 지능적으로 쓰레기를 분류하는 방식을 연구하였고, 전통적인 분류 알고리즘부터 기계학습, 신경망에 이르기까지 많은 연구가 진행되고 있다. 그러나, 다양한 환경과 조건에서 쓰레기를 분류하기에는 여전히 데이터셋이 부족하고, 신경망 네트워크 구성 복잡도가 증가하며, 성능 측면에서도 실생활에 적용하기에 아직 미흡하다. 따라서 본 논문에서는 신속한 분류와 정확도 향상을 위해 i-YOLOX를 제안하고, 네트워크 매개변수, 검출속도, 정확도 등을 평가한다. 이를 위해 17개의 폐기물 범주를 포함하는 10,000개의 가정용 쓰레기 대상 샘플로 데이터 세트를 구성하고, YOLOX 구조에 Involution 채널 컨볼루션 연산자와 CBAM(Convolution Branch Attention Module)을 도입하여 i-YOLOX를 구성하고, 기존의 YOLO 구조와 성능을 비교한다. 실험 결과 복잡한 장면에서 쓰레기 객체 검출 속도와 정확도가 기존의 신경망에 비해 향상되어, 제안한 i-YOLOX 구조가 생활 폐기물 다중 객체 검출과 분류에 효과적임을 확인하였다.

• Asian Pacific Journal of Cancer Prevention
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• 제15권8호
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• pp.3383-3389
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• 2014

Background: Prostate cancer is rapidly increasing in Korea and professional societies have requested adding prostate specific antigen (PSA) testing to the National Cancer Screening Program (NCSP), but this started a controversy in Korea and neutral evidence on this issue is required more than ever. The purpose of this study was to provide economic evidence to the decision makers of the NCSP. Materials and Methods: A cost-utility analysis was performed on the adoption of PSA screening program among men aged 50-74-years in Korea from the healthcare system perspective. Several data sources were used for the cost-utility analysis, including general health screening data, the Korea Central Cancer Registry, national insurance claims data, and cause of mortality from the National Statistical Office. To solicit the utility index of prostate cancer, a face-to-face interview for typical men aged 40 to 69 was conducted using a Time-Trade Off method. Results: As a result, the increase of effectiveness was estimated to be very low, when adopting PSA screening, and the incremental cost effectiveness ratio (ICER) was analyzed as about 94 million KRW. Sensitivity analyses were performed on the incidence rate, screening rate, cancer stage distribution, utility index, and treatment costs but the results were consistent with the base analysis. Conclusions: Under Korean circumstances with a relatively low incidence rate of prostate cancer, PSA screening is not cost-effective. Therefore, we conclude that adopting national prostate cancer screening would not be beneficial until further evidence is provided in the future.

• Investigative Magnetic Resonance Imaging
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• 제19권1호
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• pp.37-46
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• 2015

Purpose: This report compared the diagnostic effectiveness between ultrasmall superparamagnetic iron oxide (USPIO) and gadolinium (Gd) based magnetic resonance imaging (MRI) for differentiation of axillary status in breast cancer patients. Materials and Methods: The present authors performed a meta-analysis of previous studies that compared USPIO or Gd based MRI with histological diagnosis after surgery or biopsy. We searched PubMed, EMBASE, Cochrane Library, ScienceDirect, SpringerLink, Ovid databases and references of articles to identify studies reporting data until December 2013. Pooled sensitivity and specificity were calculated for every study; summary receiver operating characteristic and subgroup analysis was done. Analyses of study quality and heterogeneity were also assessed. Results: There were 14 publications that met the criteria for inclusion in our meta-analysis. USPIO based MRI showed 0.83 (95% CI: 0.75-0.89) and 0.97 (95% CI: 0.94-0.98) for pooled sensitivity and specificity, respectively. Gd based MRI represented pooled sensitivity and specificity of 0.61 (95% CI: 0.55-0.67) and 0.90 (95% CI: 0.87-0.92) for each. Overall weighted area under the curve for USPIO and Gd based MRI were 0.9563 and 0.9051, respectively. Conclusion: USPIO based MRI had a tendency toward high pooled sensitivity and specificity in detection of axillary metastases for breast cancer. This result may mean that USPIO based MRI could be used as complementary modality to differentiate axillary status more precisely, and assist in the decision-making process regarding possible invasive procedures, such as sentinel node biopsy.

• Nuclear Engineering and Technology
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• 제54권10호
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• pp.3604-3613
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• 2022

The Physical Protection System (PPS) plays an important role and must effectively deal with various adversary attacks in nuclear security. In specific single adversary path scenarios, we can calculate the PPS effectiveness by EASI (Estimated Adversary Sequence Interruption) through Probability of Interruption (P_I) calculation. EASI uses a single value of the probability of detection (P_D) and the probability of alarm communications (P_C) in the PPS. In this study, we develop a multi-path analysis code based on EASI to evaluate the effectiveness of PPS. Our quantification method for P_I considers the variability and uncertainty of P_D and P_C value by Monte Carlo simulation. We converted the 2-D scheme of the nuclear facility into an Adversary Sequence Diagram (ASD). We used ASD to find the adversary path with the lowest probability of interruption as the most vulnerable paths (MVP). We examined a hypothetical facility (Hypothetical National Nuclear Research Facility - HNNRF) to confirm our code compared with EASI. The results show that implementing the variability extension can estimate the P_I value and its associated uncertainty. The multi-path analysis code allows the analyst to make it easier to assess PPS with more extensive facilities with more complex adversary paths. However, the variability of the P_D value in each protection element allows a significant decrease in the PI value. The possibility of this decrease needs to be an important concern for PPS designers to determine the P_D value correctly or set a higher standard for PPS performance that remains reliable.

• 대한원격탐사학회지
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• 제33권6_3호
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• pp.1223-1232
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• 2017

본 연구는 KOMPSAT 광학영상을 이용하여 광범위지역에 대한 도시개발 변화를 탐지하는 방법론을 제시한다. 다른 시기에 취득된 KOMPSAT 영상 간의 방사적인 불일치를 최소화하기 위해서, 본 연구에서는 광범위지역에 대한 변화탐지에 적합한 영역별 간이 방사보정을 전처리과정으로 적용하였다. 도시개발에 대한 변화탐지 결과정확도를 향상시키기 위해서, 환경부에서 제공하는 중분류 토지피복도를 이용하여 수계, 산림과 같은 비관심지역을 제거하였다. 대표적인 변화탐지 기법인 분광변화벡터분석(Change Vector Analysis, CVA) 기법을 적용하여 도시개발에 의해 발생한 변화를 탐지하였다. 제안 기법에 대한 적용을 위해 세종시를 연구지역으로 선정하였으며, 2007년 5월과 2016년 5월에 KOMPSAT-2호로 취득한 영상과 2014년 3월에 KOMPSAT-3호로 취득한 영상을 조합하여 총 세 실험지역을 구축하였다. 2007년 5월 KOMPSAT-2호 영상과 2014년 3월 KOMPSAT-3호 영상으로 구성된 실험지역에 대한 변화탐지 정확도 평가를 수행한 결과, 약 91.00%의 변화탐지 전체정확도를 보였다. 본 연구를 통해 넓은 지역에 대량으로 발생한 도시개발 변화를 효과적으로 탐지할 수 있음을 확인하였다.