• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.20-20
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• 2022

최근 국내 기후변화와 산업화로 인한 오염물 배출량 증가로 인해 하천 및 호소에 남조류 과대 성장이 빈번히 발생한다. 과거에 비해 녹조현상의 빈도가 잦아졌으며, 지속기간이 증가하였다. 조류 발생 시 현장에서 채수한 샘플을 통해 검경 및 chlorophyll-a 분석을 진행하여 조류의 정성·정량적 평가를 진행한다. 이러한 분석결과는 녹조 발생에 대한 기초자료로 활용되고 있다. 하지만 현장 시료 샘플을 통한 조류 검경의 경우 단일지점에 대한 분석으로 인해 하천 및 호소의 전체적인 대표성을 나타내기엔 한계가 있고, 많은 인력과 시간이 소요된다. 또한 chlorophyll-a는 녹조류와 높은 관련성이 있어 유해남조류에 대한 집중 분석에는 한계가 발생한다. 이러한 한계점을 통해 국내·외로 조류 연구에 분광 스펙트럼을 활용한 원격탐사 기법 적용되고 있으며, 남조류 농도를 분석하기 위해 남조류의 보조 색소인 phycocyanin을 활용한 연구가 진행되고 있다. 본 연구에서는 분광스펙트럼을 활용한 phycocyanin 분석을 진행하였다. 분광 스펙트럼을 측정하기 위해 점(point) 단위의 고해상도 분광방사계를 활용하였으며, phycocyanin 측정을 위해서 형광 센서를 활용하였다. 현장에서 형광센서 및 분광방사계를 동시에 측정하여 데이터를 취득하였으며, 분광 스펙트럼 특성상 노이즈 및 이상치가 발생하기 때문에 전처리 과정을 통해 이를 보완하였다. phycocyanin 분석을 위해 다중 스펙트럼을 활용한 분광지수를 활용했으며, 이를 통해 phycocyanin 분석에 있어 최적의 분광지수를 제시하고자 한다. 본 연구 결과는 고해상도 점(point)단위 분석으로 향후 선단위, 면단위 하천 조류-스펙트럼 분석에 있어 기초자료로 활용될 것으로 판단된다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.137-147
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• 2023

LiDAR is used in autonomous driving and various industrial fields to measure the size and distance of an object. In addition, the sensor also provides intensity images based on the amount of reflected light. This has a positive effect on sensor data processing by providing information on the shape of the object. LiDAR guarantees higher performance as the resolution increases but at an increased cost. These conditions also apply to LiDAR intensity images. Expensive equipment is essential to acquire high-resolution LiDAR intensity images. This study developed artificial intelligence to improve low-resolution LiDAR intensity images into high-resolution ones. Therefore, this study performed parameter analysis for the optimal super-resolution neural network model. The super-resolution algorithm was trained and verified using 2,500 LiDAR intensity images. As a result, the resolution of the intensity images were improved. These results can be applied to the autonomous driving field and help improve driving environment recognition and obstacle detection performance

• Journal of Korean Society of Disaster and Security
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• v.16 no.4
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• pp.129-136
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• 2023

A special offshore bridge with a high pylon has special structural features.Special offshore bridges have inspection blind spots that are difficult to visually inspect. To solve this problem, safety inspection methods using drones are being studied. In this study, image data of the pylon of a special offshore bridge was acquired using a drone. In addition, an artificial intelligence algorithm was developed to detect damage to the pylon surface. The AI algorithm utilized a deep learning network with different structures. The algorithm applied the stacking ensemble learning method to build a model that formed the ensemble and collect the results.

• Journal of Environmental Impact Assessment
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• v.33 no.2
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• pp.84-98
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• 2024

This study proposed a prediction equation for the estimation of blasting vibaration and blasting noise, utilizing 320 datasets for the blasting vibration and blasting noise acquired during urban blasting works in the Incheon, Suwon, Wonju, and Yangsan regions. The proposed blasting vibration prediction equation, derived from regression analysis, indicated correlation coefficients of 0.879 and 0.890 for SRSD and CRSD, respectively, with an R² value exceeding 0.7. In the case of the blasting noise prediction equation, stepwise regression analysis yielded a correlation coefficient of 0.911 between the prediction values and real measurements for the blasting nosie, and further analysis to determine the constant value revealed a correlation coefficient of 0.881, with an R² value also exceeding 0.7. These results suggest the feasibility of applying the proposed prediction equations when environmental impact assessments or education environment evaluation according to urban development or apartment construction projects is performed.

• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.103-113
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• 2023

The river confluence is a section in which two rivers with different topographical and hyrodynamic characteristics are combined into one, and it is a section in which rapid flow, inflow of sediments, and hydrological topographic changes occur. In the confluence section, the flow of fluid occurs due to the difference in density due to the type of material or temperature difference, which is called a density flow. It is necessary to accurately measure and observe the confluence section including a certain section of the main stream and tributaries in order to understand the mixing behavior of the water body caused by the density difference. A comprehensive analysis of this water mixture can be obtained by obtaining flow field and flow rate information, but there is a limit to understanding the mixing of water bodies with different physical properties and water quality characteristics of rivers flowing with stratigraphic flow. Therefore, this study attempts to grasp the density flow through the water temperature distribution in the confluence section. Among the extensive data of the river, vertical data and water surface data were acquired, and through this, the stratification phenomenon of the confluence was to be confirmed. It was intended to analyze the mixed pattern of the confluence by analyzing the water mixing pattern according to the water temperature difference using the vertical data obtained by measuring the repair volume by installing the ADCP on the side of the boat and measuring the real-time concentration using YSI. This study can supplement the analysis results of the existing water quality measurement in two dimensions. Based on the comparative analysis, it will be used to investigate the current status of stratified sections in the water layer and identify the mixing characteristics of the downstream section of the river.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1361-1371
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• 2021

Among smart city services, the crime and disaster prevention sector accounted for the highest 24% in 2018. The most important platform for providing real-time situation information is CCTV (Closed-Circuit Television). Therefore, it is essential to create the actual CCTV surveillance coverage to maximize the usability of CCTV. However, the amount of CCTV installed in Korea exceeds one million units, including those operated by the local government, and manual identification of CCTV coverage is a time-consuming and inefficient process. This study proposed a method to efficiently construct CCTV's actual surveillance coverage and reduce the time required for the decision-maker to manage the situation. For this purpose, first, the exterior orientation parameters and focal lengths of the pre-installed CCTV cameras, which are difficult to access, were calculated using the point cloud data of the MMS (Mobile Mapping System), and the FOV (Field of View) was calculated accordingly. Second, using the FOV result calculated in the first step, CCTV's actual surveillance coverage area was constructed with 1 m, 2 m, 3 m, 5 m, and 10 m grid interval considering the occluded regions caused by the buildings. As a result of applying our approach to 5 CCTV images located in Uljin-gun, Gyeongsnagbuk-do the average re-projection error was about 9.31 pixels. The coordinate difference between calculated CCTV and location obtained from MMS was about 1.688 m on average. When the grid length was 3 m, the surveillance coverage calculated through our research matched the actual surveillance obtained from visual inspection with a minimum of 70.21% to a maximum of 93.82%.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.1
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• pp.53-62
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• 2017

In this paper, we present the score classification accuracy of BBS(Berg Balance Scale) which is the most commonly used balance evaluation tool using machine learning. Data acquisition was performed using the Noraxon system and an inertial sensor of Noraxon system was attached to the body in 8 locations (left and right ankle, left and right upper buttocks, left and right wrists, back, forehead). Based on the 3-axis accelerometer of the inertial sensor, the feature vector STFT(Short Time Fourier Transform) and SAM(Signal Area Magnitude) were extracted. Then, the items of the BBS were divided into static movement and dynamic movement depending on the operation characteristics, and the feature vectors were selected according to the sensor attachment positions which affect the score for each item of the BBS. Feature vectors selected for each item of BBS were classified using GMM(Gaussian Mixture Model). As a result of the accuracy calculation for 40 subjects, 55.5%, 72.2%, 87.5%, 50%, 35.1%, 62.5%, 43.3%, 58.6%, 60.7%, 33.3%, 44.8%, 89.2%, 51.8%, 85.1%, respectively.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.165-165
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• 2017

모돈은 사육 특성상 제한된 파일롯 공간 안에 장시간 머물기 때문에 과중한 몸무게에 의한 지제 이상, 섭식 등의 불량, 수면상태의 불량 등을 지속적으로 관찰해야 하는 대상이다. 측면에 다수의 초음파 센서를 설치하여 기립의 상태 및 운동 시 몸체 궤적의 특성을 분석하여 종합적으로 모돈의 행동 특성을 정량화 하고자 하였다. 이 과정에서 계측 신호의 값을 대수적으로 비교하는 방식에 한계가 있음을 발견하였고, 이를 해결하고자 10 Hz/Ch 내외의 시계열 상대거리 궤적 신호를 주파수 도메인으로 변경하여 분석을 수행하였다. 일정 주파수에 집중되어 있는 주파수 값의 크기 변화(파워 스펙트럼 밀도)를 기준으로 모돈의 움직임의 정상 상태 유무 판별이 가능하였다. 단, 이러한 분석은 계측 데이터를 일괄 처리 방식으로 분석하는 방법으로 도출이 되었으므로, 계측과 정량 분석을 동시에 수행하기 위한 개선이 필요하였다. 계측 시스템에서 사용한 마이크로 프로세서는 Nucleo-446(STMelectronics, CA, USA)로 180 Mhz의 클럭 속도로 작동하나, 총 100 Hz 내외의 16비트 계측 신호에 대해 추가적으로 FFT 등의 주파수 변환 신호 처리를 수행하기에는 연산 능력이 부족하였다. 한편, 주파수 분석의 주기를 1분 단위로 할 경우 처리해야할 정보의 크기는 $100{\times}60{\times}5{\times}2Byte$ 이므로 1분 내에 해당 연산을 종료할 수 있는 추가의 연산 장치가 필요하였다. 계측과 주파수 도메인 변환 연산을 동시에 수행하기 위하여 1 Ghz의 연산능력을 가진 ARM A9 계열의 초소형 멀티코어 AP인 NanoPi Neo Air(Friendlyarm, Guangzhou, China)을 선정하였다. 4개의 코어를 각각 계측, Median 필터링, Smoothing 연산, FFT 분석에 사용하여 1분 단위, 2분 단위, 5분 단위의 주파수 분석을 동시에 수행하였다. 병렬 연산 라이브러리는 오픈 소스인 MPICH(www.mpich.org)를 이용하였다. 상대적으로 여유있는 자원을 보유하고 코어를 실시간으로 결정하여 다수의 모돈 개체 동시 모니터링을 위한 네트워크 연결 역할을 동시에 수행하도록 하였다. 1주일 내외의 요인 실험 수행 결과, 약 70 Mbyte의 데이터가 축적이 되었으며, 1분 단위, 2분 단위, 5분 단위의 주파수 도메인 변환 후 결과를 동시에 취득할 수 있었다. 일부 주파수 도메인 상의 파워 밀도 값이 모돈의 행동 특성에 분석에 유효한 정보를 제공함을 발견하였다. 모돈사 내 현장 보급이 가능한 초소형 AP와 멀티 코어 기반 병렬 처리 기법을 이용한 현장 진단 시스템 개발 연구를 지속적으로 수행할 것이다.

• Korean Journal of Applied Biomechanics
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• v.18 no.1
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• pp.213-226
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• 2008

E. H. KIM, E. S. CHOI, D, H. NAM, S. S. KIM, J. W. CHUNG and T. W. KIM, The Instrumenfal Development for Pulling . Reaping Training & Measuring in Judo.Korean Jiurnal of Sport Biomechanics, Vol. 18, No. 1, pp. 213-226, 2008. The purpose of this study was to develop a judo-doll uke(partner : doll-uke) for training and measurement applicable to pulling, pushing and reaping in judo. In Judo the most common techniques consist of the pulling, pushing and sweep which all need to be practiced with a partner. So the research needs to develop a measurement system that can be used to evaluate the forces involved with these techniques. Also the Doll-Uke must be developed so that judokas can train alone. After the manufacture of Doll-Uke the usefulness of it must be evaluated. The height of a Doll-Uke is l70cm and its weight is 50kg. Doll-Uke was developed with a trunk angle of 55 and the lower extremities of an angle of 45. The Doll-Uke can also measure the forces developed during the pulling, pushing and sweep. Due to the ability of the system to measure the forces while preforming Judo techniques feedback can be provided to the Judokas to improve their performance.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.2
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• pp.1-9
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• 2008

As the security requirements of mobile phones have been increasing, there have been extensive researches using one biometric feature (e.g., an iris, a fingerprint, or a face image) for authentication. Due to the limitation of uni-modal biometrics, we propose a method that combines face and iris images in order to improve accuracy in mobile environments. This paper presents four advantages and contributions over previous research. First, in order to capture both face and iris image at fast speed and simultaneously, we use a built-in conventional mega pixel camera in mobile phone, which is revised to capture the NIR (Near-InfraRed) face and iris image. Second, in order to increase the authentication accuracy of face and iris, we propose a score level fusion method based on SVM (Support Vector Machine). Third, to reduce the classification complexities of SVM and intra-variation of face and iris data, we normalize the input face and iris data, respectively. For face, a NIR illuminator and NIR passing filter on camera are used to reduce the illumination variance caused by environmental visible lighting and the consequent saturated region in face by the NIR illuminator is normalized by low processing logarithmic algorithm considering mobile phone. For iris, image transform into polar coordinate and iris code shifting are used for obtaining robust identification accuracy irrespective of image capturing condition. Fourth, to increase the processing speed on mobile phone, we use integer based face and iris authentication algorithms. Experimental results were tested with face and iris images by mega-pixel camera of mobile phone. It showed that the authentication accuracy using SVM was better than those of uni-modal (face or iris), SUM, MAX, NIN and weighted SUM rules.