• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2003년도 춘계학술대회 논문집
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• pp.141-148
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• 2003

This paper presents a rotating ann test for assessment of an underwater hybrid navigation system for a semi-autonomous underwater vehicle. The navigation system consists of an inertial measurement unit (IMU), an ultra-short baseline (USBL) acoustic navigation sensor and a doppler velocity log (DVL) accompanying a magnetic compass. The errors of inertial measurement units increase with time due to the bias errors of gyros and accelerometers. A navigational system model is derived to include the error model of the USBL acoustic navigation sensor and the scale effect and bias errors of the DVL, of which the state equation composed of the navigation states and sensor parameters is 25 in the order. The conventional extended Kalman filter was used to propagate the error covariance, update the measurement errors and correct the state equation when the measurements are available. The rotating ann tests are conducted in the Ocean Engineering Basin of KRISO, KORDI to generate circular motion in laboratory, where the USBL system was absent in the basin. The hybrid underwater navigation system shows good tracking performance against the circular planar motion. Additionally this paper checked the effects of the sampling ratio of the navigation system and the possibility of the dead reckoning with the DVL and the magnetic compass to estimate the position of the vehicle.

• 한국소프트웨어감정평가학회 논문지
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• 제16권2호
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• pp.127-133
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• 2020

인공지능의 활용성이 다양해지면서 소형 휴대용기기에 알고리즘을 탑재하려는 요구가 증가하고 있다. 또한 임베디드 시스템이 고성능화하면서 운영체제는 물론 고속연산 및 머신러닝의 알고리즘 구현이 가능해 지고 있다. 그러나 반복연산과 방대한 학습데이터를 처리하는 머신러닝알고리즘의 특성으로 네트워크 연결에 의한 클라우드 환경에 의존하고 있다. 임베디드 시스템에서의 독자적인 운영을 위해서는 저 전력화 및 최적화 알고리즘에 의한 빠른 실행이 요구된다. 본 연구에서는 스마트 제어를 목적으로 임베디드 시스템에 에너지 측정용 센서를 연결하고, 실시간 측정 및 모니터링 시스템으로 측정정보를 데이터베이스로 저장하는 장치를 구현하였다. 연속적으로 측정되어 저장된 데이터는 학습 알고리즘에 적용하여, 최적화 전력제어에 활용가능하며, 에너지 측정에 요구되는 다양한 센서의 인터페이스가 가능한 시스템을 구성하였다.

• Smart Structures and Systems
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• 제31권1호
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• pp.1-11
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• 2023

Assessment of the compressive strength of concrete plays a major role during formwork removal and in the prestressing process. In concrete, temperature changes occur due to hydration which is an influencing factor that decides the compressive strength of concrete. Many methods are available to find the compressive strength of concrete, but the maturity method has the advantage of prognosticating strength without destruction. The temperature-time factor is found using a LM35 temperature sensor through the IoT technique. An experimental investigation was carried out with 56 concrete cubes, where 35 cubes were for obtaining the compressive strength of concrete using a universal testing machine while 21 concrete cubes monitored concrete's temperature by embedding a temperature sensor in each grade of M25, M30, M35, and M40 concrete. The mathematical prediction model equation was developed based on the temperature-time factor during the early age compressive strength on the 1^st, 2^nd, 3^rd and 7^th days in the M25, M30, M35, and M40 grades of concrete with their temperature. The 14^th, 21^st and 28^th day's compressive strength was predicted with the mathematical predicted equation and compared with conventional results which fall within a 2% difference. The compressive strength of concrete at any desired age (day) before reaching 28 days results in the discovery of the prediction coefficient. Comparative analysis of the results found by the predicted mathematical model show that, it was very close to the results of the conventional method.

• Structural Engineering and Mechanics
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• 제54권2호
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• pp.257-289
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• 2015

Shear connectors are generally used to link the slab and girders together in slab-on-girder bridge structures. Damage of shear connectors in such structures will result in shear slippage between the slab and girders, which significantly reduces the load-carrying capacity of the bridge. Because shear connectors are buried inside the structure, routine visual inspection is not able to detect conditions of shear connectors. A few methods have been proposed in the literature to detect the condition of shear connectors based on vibration measurements. This paper proposes a different dynamic condition assessment approach to identify the damage of shear connectors in slab-on-girder bridge structures based on power spectral density transmissibility (PSDT). PSDT formulates the relationship between the auto-spectral densities of two responses in the frequency domain. It can be used to identify shear connector conditions with or without reference data of the undamaged structure (or the baseline). Measured impact force and acceleration responses from hammer tests are analyzed to obtain the frequency response functions at sensor locations by experimental modal analysis. PSDT from the slab response to the girder response is derived with the obtained frequency response functions. PSDT vectors in the undamaged and damaged states can be compared to identify the damage of shear connectors. When the baseline is not available, as in most practical cases, PSDT vectors from the measured response at a reference sensor to those of the slab and girder in the damaged state can be used to detect the damage of shear connectors. Numerical and experimental studies on a concrete slab supported by two steel girders are conducted to investigate the accuracy and efficiency of the proposed approach. Identification results demonstrate that damages of shear connectors are identified accurately and efficiently with and without the baseline. The proposed method is also used to evaluate the conditions of shear connectors in a real composite bridge with in-field testing data.

• 환경영향평가
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• 제24권4호
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• pp.367-374
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• 2015

해수 표층 수온은 원자력발전소의 온배수 영향을 조사하기 위해서 위성원격탐사에 의해 관측되는 가장 중요한 정보들 중 하나이다. 하지만 Landsat 7 위성과 Landsat 8 위성의 열적외선 센서로부터 추출한 표층수온과 실측치를 비교한 연구는 부족하다. Landsat 8 위성은 표층수온을 추출하기 위해 열적외선 센서에 두 개의 분리된 밴드를 가지고 있지만, Landsat 7은 한 개의 밴드를 사용하고 있다. 그럼에도 불구하고 본 연구에서는 Landsat 7 ETM+센서가 Landsat 8 TIRS 보다 표층수온의 보정에 유용하다는 것을 제시하였다. 본 연구에서는 Landsat 114-36 지역의 15개 위성자료를 가지고 ENVI와 IDL을 이용한 표층수온 알고리즘을 처리하였다. 국립해양조사원으로부터 수집한 표층수온 실측자료와 위성에서 추출한 표층수온을 비교하였고, 위성관측 시계열 자료와 측정지점의 실측자료를 통해 정확도를 비교하였다.

• 대한공간정보학회지
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• 제18권2호
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• pp.119-129
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• 2010

라이다데이터를 이용한 다양한 활용알고리즘이 개발되고 있지만, 대부분의 제안된 알고리즘은 정성적인 검증만이 수행되고 있다. 알고리즘의 객관적이고 정량적인 검증을 위해서는 대상에 대한 참값(true value)을 알아야 하지만, 라이다데이터는 데이터 특성상 참값을 알기 어렵다. 본 연구에서는 모의 라이다데이터는 분할 알고리즘의 성능을 평가할 수 있는 참값을 가지고 있다는 점에 착안하여, 모의 라이다데이터를 이용하여 분할 알고리즘의 성능을 보다 객관적/정량적으로 평가해보고자 하였다. 이를 위해 먼저, 1) 분할 알고리즘의 결과를 객관적으로 가늠할 수 있는 정량적인 평가요소들을 정의하고, 2) 3차원 도시모델을 입력 데이터로 모의 라이다데이터를 생성한 후, 3) 분할알고리즘을 적용하여 객체표면을 나타내는 평면패치를 생성하였다. 마지막으로 4) 성능평가지표를 기준으로 생성된 패치에 대한 분석을 자동화하여 수행하였다.

• 한국군사과학기술학회지
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• 제22권6호
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• pp.735-744
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• 2019

One of the key factors for recognition performance in the automatic target recognition for synthetic aperture radar imagery(SAR-ATR) system is reliability of the SAR target database. To achieve optimal performance, the database should be constructed using the images obtained under the same operating condition as the SAR sensor. However, it is impractical to have the extensive set of real-world SAR images, and thus those from the electro magnetic prediction tool with 3-D CAD models are suggested as an alternative where their reliability can be always questionable. In this paper, a method for similarity assessment between target SAR images is presented inspired by the fact that a target SAR image is mainly characterized by the features of scattering centers. The method is demonstrated using a variety of examples and quantitatively measures the similarity related to reliability. Its assessment performance is further compared with that of the existing metric, structural similarity(SSIM).

• Smart Structures and Systems
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• 제24권3호
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• pp.319-332
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• 2019

Structural health monitoring (SHM) is of great importance to super high-rise buildings. The Shanghai Tower is currently the tallest building in China, and a complete SHM system was simultaneously constructed at the beginning of the construction of the tower. Due to the variety of sensor types and the large number of measurement points in the SHM system, an online automatic structural health assessment method with few computations and no manual intervention is needed. This paper introduces a structural health assessment method for the Shanghai Tower that uses the coefficients of an autoregressive (AR) time series model as structural state indicators. An analysis of collected data indicates that the coefficients of the AR model are affected by environmental factors, and the principal component analysis method is used to remove the influence of environmental factors. Finally, the control chart method is used to track the changes in structural state indicators, and a plan for online automatic structure health state evaluation is proposed. This method is applied to long-term acceleration and inclination data from the Shanghai Tower and successfully identifies the changes in the structural state. Overall, the structural state indicators of the Shanghai Tower are stable, and the structure is in a healthy state.

• 한국환경보건학회지
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• 제48권3호
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• pp.131-137
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• 2022

Public interest has been increasing the focus on the management of exposure to pollutants and the related health effects. This study reviewed exposure assessment methodologies and addressed future directions. Exposure can be assessed by direct (exposure monitoring) or indirect approaches (exposure modelling). Exposure modelling is a cost-effective tool to assess exposure among individuals, but direct personal monitoring provides more accurate exposure data. There are several population exposure models: stochastic human exposure and dose simulation (SHEDS), air pollutants exposure (APEX), and air pollution exposure distributions within adult urban population in Europe (EXPOLIS). A South Korean population exposure model is needed since the resolution of ambient concentrations and time-activity patterns are country specific. Population exposure models could be useful to find the association between exposure to pollutants and adverse health effects in epidemiologic studies. With the advancement of sensor technology and the internet of things (IoT), exposure assessment could be applied in a real-time surveillance system. In the future, environmental health services will be useful to protect and promote human health from exposure to pollutants.

• 대기
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• 제19권2호
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• pp.213-226
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• 2009

In order to investigate the characteristics of Changma over the Korean peninsula, KEOP-2007 IOP (Intensive Observing Period) was conducted from 15 June 2007 to 15 July 2007. KEOP-2007 IOP is high spatial and temporal radiosonde observations (RAOB) which consisted of three special stations (Munsan, Haenam, and Ieodo) from National Institute of Meteorological Research, five operational stations (Sokcho, Baengnyeongdo, Pohang, Heuksando, and Gosan) from Korea Meteorological Administration (KMA), and two operational stations (Osan and Gwangju) from Korean Air Force (KAF) using four different types of radiosonde sensors. The error statistics of the sensor of radiosonde were investigated using quality control check. The minimum and maximum error frequency appears at the sensor of RS92-SGP and RS1524L respectively. The error frequency of DFM-06 tends to increase below 200 hPa but RS80-15L and RS1524L show vice versa. Especially, the error frequency of RS1524L tends to increase rapidly over 200 hPa. Systematic biases of radiosonde show warm biases in case of temperature and dry biases in case of relative humidity compared with ECMWF (European Center for Medium-Range Weather Forecast) analysis data and precipitable water vapor from GPS. The maximum and minimum values of systematic bias appear at the sensor of DFM-06 and RS92-SGP in case of temperature and RS80-15L and DFM-06 in case of relative humidity. The systematic warm and dry biases at all sensors tend to increase during daytime than nighttime because air temperature around sensor increases from the solar heating during daytime. Systematic biases of radiosonde are affected by the sensor type and the height of the sun but random errors are more correlated with the moisture conditions at each observation station.