• Journal of Korean Society for Atmospheric Environment
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• 제20권E1호
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• pp.29-33
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• 2004

In environmental studies, decisions are often made on the analytical data indicating certain contaminants as being 'detected' or 'non-detectible.' Since detection limits are analytical method specific, one has to first review the concepts and definitions associated with analytical method systems and specifications. In this study, the experimental analytical values for a series of low level standards (for an ionic species) were used as an example to estimate two different method detection limits (MDL). The scores of EPA's MDL and Pallesen's MDL determined by real analytical scores are 0.0575 and 0.0561 mg/L, respectively for our nitrate data. These scores determined by two different MDL models are roughly similar, while there are apparent differences between two methods with respect to statistical and systematical procedure. However, determination of MDL for one's laboratory provides some practical applications which helps to assure one's regulating authorities that one's measured scores are accurate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권3호
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• pp.980-998
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• 2023

In Low Earth Orbit (LEO) satellite networks, satellites operate fast and the inter-satellite link change period is short. In order to sense the spectrum state in LEO satellite networks in real-time, a space-based satellite network intelligent spectrum sensing algorithm based on artificial neural network (ANN) is proposed, while Geosynchronous Earth Orbit (GEO) satellites are introduced to make fast and effective judgments on the spectrum state of LEO satellites by using their stronger arithmetic power. Firstly, the visibility constraints between LEO satellites and GEO satellites are analyzed to derive the inter-satellite link building matrix and complete the inter-satellite link situational awareness. Secondly, an ANN-based energy detection (ANN-ED) algorithm is proposed based on the traditional energy detection algorithm and artificial neural network. The ANN module is used to determine the spectrum state and optimize the traditional energy detection algorithm. GEO satellites are used to fuse the information sensed by LEO satellites and then give the spectrum decision, thereby realizing the inter-satellite spectrum state sensing. Finally, the sensing quality is evaluated by the analysis of sensing delay and sensing energy consumption. The simulation results show that our proposed algorithm has lower complexity, the sensing delay and sensing energy consumption compared with the traditional energy detection method.

• 한국전산구조공학회논문집
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• 제19권3호
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• pp.313-322
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• 2006

구조물의 진동 자료를 이용하는 유전알고리즘(GA) 기반 손상검색기법에 있어, 사용되는 모드 특징의 선택은 손상검색 결과의 정확도를 높이는데 중요하다. 본 연구의 목적은 고유진동수와 모드변형에너지를 이용하여 손상검색의 정확도를 높이는 것이다. 이와 같은 연구 목적을 달성하기 위하여 다음과 같은 연구를 수행하였다. 먼저, 모드 변형에너지를 유도하고 고유진동수와 모드변형에너지를 이용하는 새로운 GA 기반 손상검색기법을 제안하였다. 다음으로 제안된 기법의 효율성을 검증하기 위하여 양단 자유보의 손상시나리오를 제시하고, 손상시나리오에 따른 진동모드 실험을 실시하였다. 마지막으로 실험 자료를 바탕으로 제안된 기법과 기존의 고유진동수와 모드형상을 이용하는 기법으로 손상검색을 실시하여 결과를 비교하였다.

• 전기학회논문지
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• 제62권7호
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• pp.994-1002
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• 2013

This study suggests a generalized availability and safety evaluation model to evaluate the influences to the system's fault tolerant capabilities depending on automatic fault detection function such as the automatic periodic testings. The conventional evaluation model of automatic fault detection function deals only with the self diagnostics, and supposes that the fault detection coverage of self diagnostics is always constant. But all of the fault detection methods could be degraded. For example, the periodic surveillance test has the potential human errors or test equipment errors, the self diagnostics has the potential degradation of built-in logics, and the automatic periodic testing has the potential degradation of automatic test facilities. The suggested evaluation models have incorporated the loss or erroneous behaviors of the automatic fault detection methods. The availability and the safety of each module of the safety grade platform have been evaluated as they were applied the automatic periodic test methodology and the fault tolerant evaluation models. The availability and safety of the safety grade platform were improved when applied the automatic periodic testing. Especially the fault tolerant capability of the processor module with a weak self-diagnostics and the process parameter input modules were dramatically improved compared to the conventional cases. In addition, as a result of the safety evaluation of the digital reactor protection system, the system safety of the digital parts was improved about 4 times compared to the conventional cases.

• 한국음향학회지
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• 제28권5호
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• pp.447-453
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• 2009

이 논문은 음성 에너지를 최대화 하여 낮은 SNR환경에서 음성 존재 여부를 판단하고 정확한 끝점을 검출하는 방법에 대한 것이다. 전통적인 VAD (Voice Activity Detection) 알고리듬은 잡음의 추정치를 이용해 음성과 비음성 구간을 선택하여 낮은 SNR환경이나 비안정 잡음환경에서는 정확하지 못한 문턱값으로 인해 부정확한 끝점검출을 하였다. 또한 잡음의 시간적 변화를 반영하기 위해 비교적 큰 분석 구간을 두어 계산량이 증가함에 따라 실제 응용에 적합하지 않은 단점이 있다. 이 논문은 잡음환경에서 정확한 음성 구간의 검출을 위해 심리음향 모델에 기반 한 바크 스케일 필터 뱅크를 이용하여 주어진 프레임에서 음성 에너지를 최대화 시키고 잡음을 억제하는 SEM-VAD (Speech Energy Maximization-Voice Activity Detection) 방법을 제안하였다. 다양한 잡음환경, SNR 15 dB, 10 dB 5 dB 0 dB 상황에서 실험한 결과 SNR의 변화에 안정적인 문턱값을 얻었고, 음성 검출을 위한 실험에서 자동차 잡음 환경에 대한 PHR (Pause Hit Rate)은 모든 잡음 환경에서 100%의 정확도를 보였고, FAR (False Alarm Rate)는 SNR 15 dB와 10 dB에서는 0%, SNR 5 dB에서 5.6% SNR 0 dB에서 9.5%의 성능을 보였다.

• Nuclear Engineering and Technology
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• 제54권10호
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• pp.3833-3840
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• 2022

A method for calibrating the energy scale and detection efficiency of stilbene scintillators is presented herein. This method can be used to quantitatively analyze the Compton continuum of gamma-ray spectra obtained using such scintillators. First, channel-energy calibration was conducted by fitting a semi-empirical equation for the Compton continuum to the acquired energy spectrum and a new method to evaluate the intrinsic detection efficiency, called intrinsic Compton efficiency, of stilbene scintillators was proposed. The validity of this method was verified by changing experimental conditions such as the number of sources being measured simultaneously and the detector-source distance. According to the energy calibration, the standard error for the estimated Compton edge position was ±1.56 keV. The comparison of the intrinsic Compton efficiencies calculated from the single- and two-source spectra showed that the mean absolute difference and the mean absolute percentage difference are 0.031 %p and 0.557%, respectively, demonstrating reasonable accuracy of this method. The feasibility of the method was confirmed for an energy range of 0.5-1.5 MeV, showing that stilbene scintillators can be used to quantitatively analyze gamma rays in mixed-radiation fields.

• 전기전자학회논문지
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• 제20권4호
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• pp.367-372
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• 2016

외부 지역에서 침투하는 외부침입자에 대한 침입탐지를 위한 기초적인 연구 수행을 위하여 광섬유 ROTDR (Rayleigh Optical Time Domain Reflectometer) 센서를 설계 및 기초 연구를 수행하였다. 외부침입자를 탐지하기 위한 센서는 침입 탐지판을 제작하여 모래 속에 매설하여 실내에서 모형을 설치하여 침입탐지 실험을 수행하였다. ROTDR센서의 신호 분석은 검출정도에 따른 신호의 특성을 분석하였다. 광섬유 ROTDR 센서는 크게 20kg, 40kg, 60kg, 그리고 80kg 등의 무게별로 4등급으로 구분하여 넓은 영역에 걸쳐 외부 침입자를 감시하기 위한 장거리용을 사용하였다. 결과 본 논문에서의 광섬유 센서는 사회중요 기반시설의 외부침입자 감시용 실시간 모니터링의 응용에 가능함을 확인 하였다.

• Nuclear Engineering and Technology
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• 제52권2호
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• pp.456-460
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• 2020

In this research, a radiation detection backpack to be used discreetly or by a wide range of users was developed using array silicon-photomultiplier (SiPM) and CsI (Tl), and its characteristics were evaluated. The R-squared value, which indicates the responsiveness of a detector based on the signal intensity, was determined to be 0.981, indicating a good linear responsivity. The energy resolutions for gamma radiation energies of Co-57 (122 keV), Ba-133 (356 keV), Cs-137 (662 keV), and Co-60 (1332 keV) were found to be 13.40, 10.50, 6.77, and 3.16%, respectively. These results confirm good energy resolution characteristics. Furthermore, in the case of mixed sources, the gamma radiation peaks were readily distinguishable, and the R-squared value for energy linearity was calculated to be 0.999, demonstrating an exceptional energy linearity. Further research based on the results of this study would enable the commercialization of lightweight SiPM-based wireless radiation detection backpacks that can be used for longer durations by replacing the photomultiplier tube, which is mainly used as the optical sensor in existing radiation detection backpacks.

• IEIE Transactions on Smart Processing and Computing
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• 제5권5호
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• pp.327-330
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• 2016

Currently, the world's elderly population continues to grow at a dramatic rate. As the number of senior citizens increases, detection of someone falling has attracted increasing attention for visual surveillance systems. This paper presents a novel fall-detection algorithm using motion estimation and an integrated spatiotemporal energy map of the object region. The proposed method first extracts a human region using a background subtraction method. Next, we applied an optical flow algorithm to estimate motion vectors, and an energy map is generated by accumulating the detected human region for a certain period of time. We can then detect a fall using k-nearest neighbor (kNN) classification with the previously estimated motion information and energy map. The experimental results show that the proposed algorithm can effectively detect someone falling in any direction, including at an angle parallel to the camera's optical axis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권8호
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• pp.3769-3789
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• 2018

Social pedestrian groups are the basic elements that constitute a crowd; therefore, detection of such groups is scientifically important for modeling social behavior, as well as practically useful for crowd video understanding. A social group refers to a cluster of members who tend to keep similar motion state for a sustained period of time. One of the main challenges of social group detection arises from the complex dynamic variations of crowd patterns. Therefore, most works model dynamic groups to analysis the crowd behavior, ignoring the existence of stationary groups in crowd scene. However, in this paper, we propose a novel unified framework for detecting social pedestrian groups in crowd videos, including dynamic and stationary pedestrian groups, based on spatiotemporal-oriented energy measurements. Dynamic pedestrian groups are hierarchically clustered based on energy flow similarities and trajectory motion correlations between the atomic groups extracted from principal spatiotemporal-oriented energies. Furthermore, the probability distribution of static spatiotemporal-oriented energies is modeled to detect stationary pedestrian groups. Extensive experiments on challenging datasets demonstrate that our method can achieve superior results for social pedestrian group detection and crowd video classification.