• 한국통신학회논문지
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• 제38C권3호
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• pp.263-270
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• 2013

최근 세계적으로 바다가 자원의 보고로 주목 받으면서 해양 환경 분석 및 예측 기술에 대한 연구가 활발히 진행 되고 있다. 자동화된 해양 환경 자료의 수집과 수집된 자료를 분석하여서 해양재해를 예측하면 기름 유출에 의한 해양오염의 피해, 적조에 의한 수산업의 피해, 해양환경 이변에 의한 수산업 및 재해 피해를 최소화하는데 기여할 수 있다. 그러나 국내 해양 환경에 대한 조사 및 분석 연구는 제한적이다. 본 논문은 국내의 원해 및 근 해역에서 수집된 해양 환경 자료를 분석하여 해양재해를 예측할 수 있는 시스템 모델을 연구한다. 이를 위해서 본 논문에서는 해양재해 예측 시스템을 위해서 통신시스템 모델, 해양환경 자료 수집 시스템 모델, 예측분석 시스템 모델, 상황전파시스템에 대한 모델을 제시하였다. 또한 예측분석 시스템을 위한 적조 예측 모델과 요약분석 모델을 제시하였다.

• 한국멀티미디어학회논문지
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• 제25권3호
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• pp.510-518
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• 2022

This paper confirmed the technical reliability of mobile-based sarcopenia prediction and monitoring system. In implementing the developed system, we designed using only sensors built into a smartphone without a separate external device. The prediction system predicts the possibility of sarcopenia without visiting a hospital by performing the SARC-F survey, the 5-time chair stand test, and the rapid tapping test. The Monitoring system tracks and analyzes the average walking speed in daily life to quickly detect the risk of sarcopenia. Through this, it is possible to rapid detection of undiagnosed risk of undiagnosed sarcopenia and initiate appropriate medical treatment. Through prediction and monitoring system, the user may predict and manage sarcopenia, and the developed system can have a positive effect on reducing medical demand and reducing medical costs. In addition, collected data is useful for the patient-doctor communication. Furthermore, the collected data can be used for learning data of artificial intelligence, contributing to medical artificial intelligence and e-health industry.

• 대기
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• 제30권2호
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• pp.103-113
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• 2020

In this study, we analyzed and developed the monitoring system in order to confirm the effect of observations on forecast sensitivity on ensemble-based data assimilation. For this purpose, we developed the Ensemble Forecast Sensitivity to observation (EFSO) monitoring system based on Local Ensemble Transform Kalman Filter (LETKF) system coupled with Korean Integrated Model (KIM). We calculated 24 h error variance of each of observations and then classified as beneficial or detrimental effects. In details, the relative rankings were according to their magnitude and analyzed the forecast sensitivity by region for north, south hemisphere and tropics. We performed cycle experiment in order to confirm the EFSO result whether reliable or not. According to the evaluation of the EFSO monitoring, GPSRO was classified as detrimental observation during the specified period and reanalyzed by data-denial experiment. Data-denial experiment means that we detect detrimental observation using the EFSO and then repeat the analysis and forecast without using the detrimental observations. The accuracy of forecast in the denial of detrimental GPSRO observation is better than that in the default experiment using all of the GPSRO observation. It means that forecast skill score can be improved by not assimilating observation classified as detrimental one by the EFSO monitoring system.

• 대기
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• 제22권2호
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• pp.267-277
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• 2012

The objectives of this study are to develop a real-time drought monitoring and prediction system on the East Asia domain and to evaluate the performance of the system by using past historical drought records. The system is mainly composed of two parts: drought monitoring for providing current drought indices with meteorological and hydrological conditions; drought outlooks for suggesting future drought indices and future hydrometeorological conditions. Both parts represent the drought conditions on the East Asia domain (latitude $21.15{\sim}50.15^{\circ}$, longitude $104.40{\sim}149.65^{\circ}$), Korea domain (latitude $30.40{\sim}43.15^{\circ}$, longitude $118.65{\sim}135.65^{\circ}$) and South Korea domain (latitude $30.40{\sim}43.15^{\circ}$, longitude $118.65{\sim}135.65^{\circ}$), respectively. The observed meteorological data from ASOS (Automated Surface Observing System) and AWS (Automatic Weather System) of KMA (Korean Meteorological Administration) and model-driven hydrological data from LSM (Land Surface model) are used for the real-time drought monitoring, while the monthly and seasonal weather forecast information from UM (Unified Model) of KMA are utilized for drought outlooks. For the evaluation of the system, past historical drought records occurred in Korea are surveyed and are compared with the application results of the system. The results demonstrated that the selected drought indices such as KMA drought index, SPI (3), SPI (6), PDSI, SRI and SSI are reasonable, especially, the performance of SRI and SSI provides higher accuracy that the others.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2020년도 가을 학술논문 발표대회
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• pp.186-187
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• 2020

Damage to temporary facilities and structural members caused by excessive loads in the field continue to occur. If the load can be monitored in advance, the risk can be prevented. In this study, a load cell sensor is installed under the system support, and load data is wirelessly transmitted through a Bluetooth AP(wireless). Risk prediction system is proposed through an construction alarm when an abnormal load occurs through real-time multi-point monitoring by sensor location.

• Computers and Concrete
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• 제20권5호
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• pp.555-562
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• 2017

The accuracy and integrity of stress data acquired by bridge heath monitoring system is of significant importance for bridge safety assessment. However, the missing and abnormal data are inevitably existed in a realistic monitoring system. This paper presents a data reconstruction approach for bridge heath monitoring based on the wavelet multi-resolution analysis and support vector machine (SVM). The proposed method has been applied for data imputation based on the recorded data by the structural health monitoring (SHM) system instrumented on a prestressed concrete cable-stayed bridge. The effectiveness and accuracy of the proposed wavelet-based SVM prediction method is examined by comparing with the traditional autoregression moving average (ARMA) method and SVM prediction method without wavelet multi-resolution analysis in accordance with the prediction errors. The data reconstruction analysis based on 5-day and 1-day continuous stress history data with obvious preternatural signals is performed to examine the effect of sample size on the accuracy of data reconstruction. The results indicate that the proposed data reconstruction approach based on wavelet multi-resolution analysis and SVM is an effective tool for missing data imputation or preternatural signal replacement, which can serve as a solid foundation for the purpose of accurately evaluating the safety of bridge structures.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.185-189
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• 2006

Time series analysis is a frequently effective method of constructing model and prediction in data processing of deformation monitoring. The monitoring data sample must to be as more as possible and time intervals are equal roughly so as to construct time series model accurately and achieve reliable prediction. But in the project practice of GPS deformation monitoring, the monitoring data sample can't be obtained too much and time intervals are not equal because of being restricted by all kinds of factors, and it contains many variates in the deformation model moreover. It is very important to study the data processing method for small samples and multi-variates time series in GPS deformation monitoring. A new method of establishing small samples and multi-variates deformation model and prediction model are put forward so as to resolve contradiction of small samples and multi-variates encountered in constructing deformation model and improve formerly data processing method of deformation monitoring. Based on the system theory, a deformation body is regarded as a whole organism; a time-dependence linear system model and a time-dependence bilinear system model are established. The dynamic parameters estimation is derived by means of prediction fit and least information distribution criteria. The final example demonstrates the validity and practice of this method.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제22권9호
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• pp.455-460
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• 2016

최근 강도, 성폭력과 같은 중범죄들의 수위가 높아짐에 따라 범죄 예측 및 예방에 대한 중요성이 강조되고 있다. 정확한 범죄예측을 위해서는 과거 범죄기록 데이터를 기반으로 정확도 높은 범죄분류모델을 만드는 작업이 필요하며, 신속한 범죄 대응을 위한 시스템 인터페이스가 요구된다. 그러나 기존의 범죄 요소 분석 연구는 데이터 전처리에 대한 난해함으로 인해 정확도 측면에서 한계를 보이며, 범죄 모니터링 시스템은 방대한 양의 범죄 사건기록 분석 결과를 단순 제공함으로써 사용자에게 효과적인 모니터링 기능을 제공하지 못하고 있다. 따라서 본 연구는 실시간 범죄 예측을 위한 랜덤 포레스트 알고리즘 기반의 범죄 유형 분류모델 및 시스템 인터페이스 디자인 요소를 제안한다. 실험을 통해 본 연구는 제안하는 모델이 단순히 범죄기록 데이터만으로 범죄유형을 분류하는 모델 보다 우수함을 입증하였고, 기존의 범죄 모니터링 시스템 분석을 통해 실시간 범죄 모니터링을 위한 시스템 인터페이스를 설계 및 구현하였다.

• 한국정보통신학회논문지
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• 제16권10호
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• pp.2113-2120
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• 2012

국내 해양 환경에 대한 자동 감시 및 분석 연구는 미흡한 편에 있다. 최근 세계적으로 바다가 자원의 보고로 주목받으면서 해양 모니터링 기술에 대한 연구가 활발히 진행 되고 있다. 특히 해양 환경을 분석하고 이해하기 위해서는 지속적으로 해양 환경 자료를 수집해야 하나 아직 많은 부분에서 제약 사항으로 남아 있다. 자동화된 해양 환경자료의 수집과 수집된 자료를 분석하여서 해양재해를 예측하면 기름 유출에 의한 해양오염의 피해, 적조에 의한 수산업의 피해, 해양환경 이변에 의한 수산업 및 재해 피해를 최소화하는데 기여할 수 있다. 본 논문은 해양환경 감시 및 분석 시스템의 모델을 제안한다. 제안 시스템은 해양환경 정보를 자동 수집하여 해양환경을 지능적으로 감시한다. 또한 수집된 해양 자료를 분석하여서 해양 재해를 예측한다.

• Transactions on Electrical and Electronic Materials
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• 제13권5호
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• pp.256-261
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• 2012

Recently, many photovoltaic systems (PV systems) including solar parks and PV farms have been built to prepare for the post fossil fuel era. To investigate the degradation process of the PV systems and thus, efficiently operate PV systems, there is a need to visually monitor PV systems in the range of infrared ray through the Internet. For efficient visual monitoring, this paper explores a multithreaded implementation of a recently developed HEVC standard whose compression efficiency is almost two times higher than H.264. For an efficient parallel implementation under a meshbased 64 multicore system, this work takes into account various design choices which can solve potential problems of a two-dimensional interconnects-based 64 multicore system. These problems may have not occurred in a small-scale multicore system based on a simple bus network. Through extensive evaluation, this paper shows that, for an efficient multithreaded implementation of HEVC intra prediction in a mesh-based multicore system, much effort needs to be made to optimize communications among processing cores. Thus, this work provides three design choices regarding communications, i.e., main thread core location, cache home policy, and maximum coding unit size. These design choices are shown to improve the overall parallel performance of the HEVC intra prediction algorithm by up to 42%, achieving a 7 times higher speed-up.