• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.575-576
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• 2014

The Hull Mounted Sonar Dome housing the sonar sensor array is a ship's structure protruded from ship bottom, which is under turbulent flow. The flow of sonar surface is highly disturbed and turbulent. In this case the wall pressure fluctuations within the turbulent boundary layer are one of the most important flow induced self noise sources of the SONAR system. We investigate the characteristics of the wall pressure fluctuations of the hull mounted sonar dome through the model test in the cavitation tunnel. This paper contains the wall pressure fluctuation spectra at various free stream velocities.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.06a
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• pp.67-74
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• 2008

현재의 센서 네트워크 시스템은 공간적 정보를 배제한 센서 데이터스트림에 대한 저장 및 검색 방안에 대한 연구에 치중되어 있다. 하지만, 이러한 센서 네트워크가 공간적 정보와 결합하게 되면 훨씬 더 많은 응용과 의미 있는 데이터로 가공될 수 있다. 본 논문은 GeoSensor Network에서 공간적 정보와 데이터스트림이 결합된 공간 데이터스트림 정의 및 공간 데이터스트림간 조인 전략들과 그에 따른 조인 전략들 간의 비용을 추정하는 비용 모델을 제시하였다. 공간 데이터스트림간 조인 전략을 위해 Nested Loop 조인, Grid File, R-tree 알고리즘을 사용하였고, 단방향 Nested Loop 조인, 단방향 Grid 조인, 단방향 R-tree 조인 기법들을 조합하여 조인 전략들 간의 비용을 추정하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.148-150
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• 2012

최근 대용량 스트림 데이터에 대한 요구사항이 발생하고 있다. 이때 모든 대용량 스트림을 실시간으로 좋은 서비스를 제공하는 것은 실제적으로 불가능하다. 즉 대용량 스트림 데이터에 대한 QoS(Quality of Service: 서비스 품질)이 중요한 이슈가 되고 있다. 이러한 QoS를 정의하기 위해서는 센서 스트림 데이터에 대한 우선순위 부여방법이 가장 원천적으로 중요한 사항이 된다. 현재 센서 네트워크상에서의 서비스 품질은 연구되고 있지만 미들웨어 레이어에서의 우선순위 부여 방법에 대한 연구가 미비하다. 센서 스트림은 자체적으로는 우선순위를 가질 수 없으므로 사용자 질의 우선순위와 센서 스트림의 발생 시간등을 고려하여 대용량 센서 스트림에 대한 우선순위를 부여하는 방법을 제안한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.289-292
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• 2022

본 논문에서는 실제 철도 건널목(교차로)에서 발생하는 소음 및 진동, 차량 및 보행자 사고와 같은 위험 요소로부터 발생하는 위험 상황들을 분류하고, 철도 건널목(교차로) 운행 상황을 구현한 모형 철도 주변에 센서를 부착하여 철도 건널목에서 발생하는 위험 요소들을 아두이노 센서로 감지해 데이터를 수집한다. 또한 수집된 데이터들을 활용하여 사용자의 상황에 맞는 철도데이터 운영시스템을 제안한다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.116-124
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• 2011

In this paper, We implemented vessel USN middleware by server-side method considering characteristics of ocean environment. We designed multiple query process module in order to efficient process multidimensional sensor stream data and proposed optimized query plan using Mjoin query and hash table. This paper proposed method that context aware of vessel and manage considering characteristics of ocean. We decided to risk context using SVM algorithm in context awareness management module. As a result, we obtained about 87.5% average accuracy for fire case and about 85.1% average accuracy for vessel risk case by input 5,000 data sets and implemented vessel USN monitoring system.

• The Journal of Engineering Geology
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• v.21 no.1
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• pp.45-55
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• 2011

We examined the interactions between surface and groundwater through (1) flowmeter logging, (2) measurements of seasonal and vertical changes in temperature within a well, and (3) geochemical analyses of water samples from nine groundwater-monitoring wells. At two wells adjacent to a stream, subsurface water was found to flow from the stream to a surrounding alluvial fan, and the seasonal change in groundwater temperature is similar to those of surface water and air. Geochemical analyses at two wells indicated hydro-geochemical features affected by streamwater inflow, showing seasonal variations. Accordingly, these two wells are located in an area with active interaction between surface water and groundwater. The Thermochron I-button used in the present study is useful for this type of study of groundwater?surface water interaction because of its low cost and small size.

• Journal of Sensor Science and Technology
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• v.18 no.6
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• pp.423-431
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• 2009

Standard uroflowmetry measures the urine weight using single load cell to evaluate the urinary flow rate. Impact noise should be introduced due to gravity when the urine stream falls down into the container upon the load cell. The present study placed three load cells on the three vertices of a regular triangle and the three signals were ensemble averaged to enhance the signal-to-noise ratio(SNR) regardless of how the urination was made. Simulated urination experiment was performed with three different urine collection methods. In all three methods, SNR of the averaged signal was much higher than each load cell signals. With no urine collection device, the present signal averaging technique resulted in SNR values higher by 10~15 dB than when dual funnels or upper funnel were used to guide the urine stream. Therefore, it was demonstrated that the three point measurement followed by with ensemble averaging could enable accurate uroflowmetric test without any specially made urine collection devices.

• Journal of Korea Water Resources Association
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• v.48 no.5
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• pp.409-423
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• 2015

In this study the very short-term rainfall forecasting and storm water forecasting using the weather radar data were implemented in an urban stream basin. As forecasting time increasing, the very short-term rainfall forecasting results show that the correlation coefficient was decreased and the root mean square error was increased and then the forecasting model accuracy was decreased. However, as a result of the correlation coefficient up to 60-minute forecasting time is maintained 0.5 or higher was obtained. As a result of storm water forecasting in an urban area, the reduction in peak flow and outflow volume with increasing forecasting time occurs, the peak time was analyzed that relatively matched. In the application of storm water forecasting by radar rainfall forecast, the errors has occurred that we determined some of the external factors. In the future, we believed to be necessary to perform that the continuous algorithm improvement such as simulation of rapid generation and disappearance phenomenon by precipitation echo, the improvement of extreme rainfall forecasting in urban areas, and the rainfall-runoff model parameter optimizations. The results of this study, not only urban stream basin, but also we obtained the observed data, and expand the real-time flood alarm system over the ungaged basins. In addition, it is possible to take advantage of development of as multi-sensor based very short-term rainfall forecasting technology.

• Journal of KIISE:Databases
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• v.34 no.4
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• pp.343-356
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• 2007

Due to advances in position monitoring technologies such as global positioning systems and sensor networks, recent position information of moving objects has the form of streaming data which are updated continuously and rapidly. In this paper we propose an efficient trajectory maintenance method that stores the streaming position data of moving objects in the limited size of storage space and estimates past positions based on the stored data. For this, we first propose a new concept of incremental extraction of position information. The incremental extraction means that, whenever a new position is added into the system, we incrementally re-compute the new version of past position data maintained in the system using the current version of past position data and the newly added position. Next, based on the incremental extraction, we present an overall framework that stores position information and estimates past positions in the stream environment. We then propose two polynomial-based methods, line-based and curve-based methods, as the method of estimating the past positions on the framework. We also propose three incremental extraction methods: equi-width, slope-based, and recent-emphasis extraction methods. Experimental results show that the proposed incremental extraction provides the relatively high accuracy (error rate is less than 3%) even though we maintain only a little portion (only 0.1%) of past position information. In particular, the curve-based incremental extraction provides very low error rate of 1.5% even storing 0.1% of total position data. These results indicate that our incremental extraction methods provide an efficient framework for storing the position information of moving objects and estimating the past positions in the stream environment.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.3
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• pp.113-120
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• 2018

In this study, we proposed a monitoring system for identifying and handling faulty sensing stream data on manufacturing equipments where low-cost sensors can be safely used. Low cost sensors will lessen the cost of implementing distributed monitoring system, but suffer from sensor noises and inaccurate sensed data. Therefore, a distributed monitoring system with low cost sensors should identify faulty signal data as either of sensor fault or machine fault, and filter out faulty signals from sensing fault. To this end, we adopted a fourier transform based diagnostic approach mixed with a weighed moving averaging method, in order to identify faulty signals. We measured how effective our approach is and found out our approach can filter out one-third faulty signals from our experimental environment. In addition, we attached wireless communication modules to reduce sensor and network installation cost. To handle massive sensor data efficiently, we employed unstructured data format with NoSQL based database.