• 한국지하수토양환경학회지:지하수토양환경
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• 제28권spc호
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• pp.18-39
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• 2023

Rapid development of geophysical exploration and hydrogeologic monitoring techniques has yielded remarkable increase of datasets related to groundwater systems. Increased number of datasets contribute to understanding of general aquifer characteristics such as groundwater yield and flow, but understanding of complex heterogenous aquifers system is still a challenging task. Recently, applications of data science technique have become popular in the fields of geophysical explorations and monitoring, and such attempts are also extended in the groundwater field. This work reviewed current status and advancement in utilization of data science in groundwater field. The application of data science techniques facilitates effective and realistic analyses of aquifer system, and allows accurate prediction of aquifer system change in response to extreme climate events. Due to such benefits, data science techniques have become an effective tool to establish more sustainable groundwater management systems. It is expected that the techniques will further strengthen the theoretical framework in groundwater management to cope with upcoming challenges and limitations.

• Smart Structures and Systems
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• 제10권4_5호
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• pp.411-426
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• 2012

The Canton Tower (formerly named Guangzhou New TV Tower) of 610 m high has been instrumented with a long-term structural health monitoring (SHM) system consisting of over 700 sensors of sixteen types. Under the auspices of the Asian-Pacific Network of Centers for Research in Smart Structures Technology (ANCRiSST), an SHM benchmark problem for high-rise structures has been developed by taking the instrumented Canton Tower as a host structure. This benchmark problem aims to provide an international platform for direct comparison of various SHM-related methodologies and algorithms with the use of real-world monitoring data from a large-scale structure, and to narrow the gap that currently exists between the research and the practice of SHM. This paper first briefs the SHM system deployed on the Canton Tower, and the development of an elaborate three-dimensional (3D) full-scale finite element model (FEM) and the validation of the model using the measured modal data of the structure. In succession comes the formulation of an equivalent reduced-order FEM which is developed specifically for the benchmark study. The reduced-order FEM, which comprises 37 beam elements and a total of 185 degrees-of-freedom (DOFs), has been elaborately tuned to coincide well with the full-scale FEM in terms of both modal frequencies and mode shapes. The field measurement data (including those obtained from 20 accelerometers, one anemometer and one temperature sensor) from the Canton Tower, which are available for the benchmark study, are subsequently presented together with a description of the sensor deployment locations and the sensor specifications.

• Journal of Chest Surgery
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• 제56권5호
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• pp.336-345
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• 2023

Background: The objective of this study was to demonstrate the safety, efficacy, and feasibility of intraoperative monitoring of the recurrent laryngeal nerves during thoracoscopic and robotic 3-field esophagectomy. Methods: This retrospective analysis details our initial experience using intraoperative nerve monitoring (IONM) during minimally invasive 3-field esophagectomy. Data were obtained from a prospectively maintained database and electronic medical records. The study included all patients who underwent minimally invasive (video-assisted thoracic surgery/robotic) transthoracic esophagectomy with neck anastomosis. The patients were divided into those who underwent IONM during the study period and a historical cohort who underwent 3-field esophagectomy without IONM at the same institution. Appropriate statistical tests were used to compare the 2 groups. Results: Twenty-four patients underwent nerve monitoring during minimally invasive 3-field esophagectomy. Of these, 15 patients underwent thoraco-laparoscopic operation, while 9 received a robot-assisted procedure. In the immediate postoperative period, 8 of 24 patients (33.3%) experienced vocal cord paralysis. Relative to a historical cohort from the same institution, who were treated with surgery without nerve monitoring in the preceding 5 years, a 26% reduction was observed in the nerve paralysis rate (p=0.08). On follow-up, 6 of the 8 patients with vocal cord paralysis reported a return to normal vocal function. Additionally, patients who underwent IONM exhibited a higher nodal yield and a decreased frequency of tracheostomy and bronchoscopy. Conclusion: The use of IONM during minimally invasive 3-field esophagectomy is safe and feasible. This technique has the potential to decrease the incidence of recurrent nerve palsy and increase nodal yield.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2012년도 전력전자학술대회 논문집
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• pp.619-620
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• 2012

This paper proposes a model of the real time monitoring system based on Ubiquitous Sensor Network (USN) for the detection and prediction of landslides. For this purpose, the real time monitoring system with tilting sensor and USN was set up and the performance was conducted. The performance was accomplished by conducting both field examinations and the experimental evaluation of the monitoring system. The results of this study show that the movements detected by the sensor module coincide with the actual displacement of field and the data measured from the sensor modules through USN transfer to the monitoring system without errors.

• 지질공학
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• 제7권2호
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• pp.139-149
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• 1997

전기비저항 모니터링을 이용하여 충적층 지하수위의 변동을 감지 할 수 있는지의 여부가 연구되었다. 연구는 유한요소법을 이용한 전기비저항 수치 모델링 시험과 20일간의 장기 양수 시험이 수행된 금강 정동리 지역의 현장 자료를 이용하여 수행되었다. 수치 모델링 시험 및 현장 자료 획득은 전극 기본 간격이 4m인 21개의 고정전극을 이용하였으며, 전극배열은 "변형 웨너 배열"과 쌍극자 배열을 이용하였다. 현장 장기 양수 시험에서 관측된 수위 변화를 단순화하여 지하 2차원 비저항 모델로 사용한 사용한 결과, 겉보기 전기비저항의 변화 양상은 수위 변화보다 둔감한 변화 양상을 보여 주며, 수위 변화가 있는 부분뿐만 아니라하부 결정질 기반암의 경계 부위에 해당하는 심도에서도 겉보기 비저항 장치가 변화하는 현상이 관측되었다. 이러한 수치 결과와 부합되는 결과가 실제 현장에서 획득된 겉보기 전기 비저항 단면에서도 나타났다. 수치 계산결과 및 현장 자료는 전기 비저한 모니터링이 지하수위 변동을 유무 감지하는데 유용하게 사용될 수 있음을 보여주었다. 그러나 겉보기 전기비저항 단면이 수위 변동량을 정량적으로 규명할 만큼의 뚜렷한 변화를 보여주지는 못하기 때문에 전기비저항 방법만으로 정략적인 수위변동을 감지하는데 한계가 있는 것으로 판단되었다. 이러한 지하 수위 변동량 등을 명확히 규명하기 위해서는 고해상도 탄성파 또는 지하레이다 탐사처럼 지하의 모습을 영상화 할 수 있는 지구물리 탐사법이 병행되는 것이 바람직하다.

• 비파괴검사학회지
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• 제32권6호
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• pp.648-660
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• 2012

Reliable response measurements are extremely important for proper bridge health monitoring but incomplete and unreliable data may be acquired due to sensor problems and environmental effects. In the case of a sensor malfunction, parts of the measured data can be missing so that the structural health condition cannot be monitored reliably. This means that the dynamic characteristics of natural frequencies can change as if the structure is damaged due to environmental effects, such as temperature variations. To overcome these problems, this paper proposes a systematic procedure of data analysis to recover missing data and eliminate the environmental effects from the measured data. It also proposes a health index calculated statistically using revised data to evaluate the health condition of a bridge. The proposed method was examined using numerically simulated data with a truss structure and then applied to a set of field data measured from a cable-stayed bridge.

• 한국정보통신학회논문지
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• 제15권1호
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• pp.233-240
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• 2011

산악지역이나 어떤 한정된 지역에서 급작하게 나타나는 기상변화를 모니터링하기 위해 유비쿼터스 센서 네트워크 기술을 이용한 필드서버를 개발하였다. 국지적 기상변화에 의한 인명 및 재난 피해를 최소화하기 위해 국지역내에 배치된 필드서버간의 데이터 전달이 매우 중요한 기술이다. 일정한 국지적 지역에 배치 된 필드서버들로부터 일정한 시간 간격으로 수집되는 온도, 습도, 조도, 기압, 이슬점, 수위의 기상데이터를 전송하기 위한 플러딩 라우팅 프로토콜 전송방식을 구현하였으며, 이를 제작 된 외부센서모듈과 Telosb 계열의 센서노드에 nesC 언어를 사용한 초소형 무선센서네트워크 플랫폼인 TinyOS로 프로그램 하여서 서버 컴퓨터에서 모니터링 할 수 있도록 하였다.

• International journal of advanced smart convergence
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• 제12권3호
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• pp.104-108
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• 2023

This paper deals with research on innovative systems using Python-based artificial intelligence technology in the field of plant growth monitoring. The importance of monitoring and analyzing the health status and growth environment of plants in real time contributes to improving the efficiency and quality of crop production. This paper proposes a method of processing and analyzing plant image data using computer vision and deep learning technologies. The system was implemented using Python language and the main deep learning framework, TensorFlow, PyTorch. A camera system that monitors plants in real time acquires image data and provides it as input to a deep neural network model. This model was used to determine the growth state of plants, the presence of pests, and nutritional status. The proposed system provides users with information on plant state changes in real time by providing monitoring results in the form of visual or notification. In addition, it is also used to predict future growth conditions or anomalies by building data analysis and prediction models based on the collected data. This paper is about the design and implementation of Python-based plant growth monitoring systems, data processing and analysis methods, and is expected to contribute to important research areas for improving plant production efficiency and reducing resource consumption.

• Structural Monitoring and Maintenance
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• 제1권1호
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• pp.47-67
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• 2014

This study has been motivated to examine the performance of a wireless sensor system under the typhoons as well as to analyze the effect of the typhoons on the bridge's vibration responses and the variation of cable forces. During the long-term field experiment on a real cable-stayed bridge in years 2011-2012, the bridge had experienced two consecutive typhoons, Bolaven and Tembin, and the wireless sensor system had recorded data of wind speeds and vibration responses from a few survived sensor nodes. In this paper, the wireless structural health monitoring of stay cables under the two consecutive typhoons is presented. Firstly, the wireless monitoring system for cable-stayed bridge is described. Multi-scale vibration sensor nodes are utilized to measure both acceleration and PZT dynamic strain from stay cables. Also, cable forces are estimated by a tension force monitoring software based on vibration properties. Secondly, the cable-stayed bridge with the wireless monitoring system is described and its wireless monitoring capacities for deck and cables are evaluated. Finally, the structural health monitoring of stay cables under the attack of the two typhoons is described. Wind-induced deck vibration, cable vibration and cable force variation are examined based on the field measurements in the cable-stayed bridge under the two consecutive typhoons.

• 대한원격탐사학회지
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• 제16권2호
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• pp.109-116
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• 2000

This study was carried out to assess the use of RADARSAT data which is C-band with HH polarization for the rice growth monitoring in Korea. Nine time-series data were taken by shallow incidence angle (standard beam mode 5 or 6) during rice growing season. And then, backscattering coefficients ($\sigma$$^{\circ}$) were extracted by calibration process for comparing with rice growth parameters such as plant height, leaf area index(LAI), and fresh and dry biomass. Field experimental data concerned with rice growth were collected 8 times for the ground truth at the study area, Tangjin, Chungnam, Korea. At the beginning of rice growth, backscattering coefficients were ranged from -l6~-l3dB when rice fields were not covered with rice canopy and flooded. At the maximum vegetative stage of rice, backscattering coefficients of the rice field were the highest ranging from -4.4dB~-3.1dB. The temporal variation of backscattering coefficient($\sigma$$^{\circ}$) in rice field was significant in this study. Backscattering coefficient ($\sigma$$^{\circ}$) of rice field was a little bit lower again after heading stage than before. This results show RADARSAT data is promising for rice monitoring.