• 한국전자통신학회논문지
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• 제6권4호
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• pp.523-531
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• 2011

지하수 자원을 사용하기 위해 설치된 많은 관정들이 사용 후 폐공처리 소홀로 인하여 지하수 오염원이 된다. 또한 폐공된 관정에서는 중금속 및 유기화합물 등의 유해물질이 지하수로 유입 되는 문제점이 발생하여 지하수 수질 악화를 초래한다. 따라서 본 논문에서는 이러한 문제점을 개선하기 위해 유비쿼터스 센서 노드와 GIS 기술을 접목한 u-GIS 환경 하에서 관정의 위치정보와 지하수 센싱 정보를 실시간으로 모니터링하고 분석할 수 있는 지하수 관리 시스템을 설계 및 구현한다. 아울러 UML 2.0을 활용하여 시스템을 이용하는 사용자의 다양한 요구사항, 시스템 내부 모듈들 간의 상호작용 및 데이터 흐름을 분석하여 시스템을 모델링한다. GIS 맵과 웹 환경, 스마트폰 기반의 모바일 단말기 등의 다양한 플랫폼을 통해 원격지에 있는 각 관정의 지하수 상태 및 관정 관련 속성 정보를 모니터링을 하기 위한 사용자 인터페이스를 제공한다.

• Journal of Microbiology and Biotechnology
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• 제21권12호
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• pp.1330-1335
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• 2011

N-Acyl homoserine lactones (AHLs) serve as the vital quorum-sensing signals that regulate the virulence of the pathogenic bacterium Erwinia carotovora. In the present study, an approach to efficiently restrain the pathogenicity of E. carotovora-induced soft rot disease is described. Bacillus thuringiensis-derived N-acyl homoserine lactonase (AiiA) was projected onto the surface of Pseudomonas putida cells, and inoculation with both strains was challenged. The previously identified N-terminal moiety of the ice nucleation protein, InaQ-N, was applied as the anchoring motif. A surface display cassette with inaQ-N/aiiA was constructed and expressed under the control of a constitutive promoter in P. putida AB92019. Surface localization of the fusion protein was confirmed by Western blot analysis, flow cytometry, and immunofluorescence microscopy. The antagonistic activity of P. putida MB116 expressing InaQ-N/AiiA toward E. carotovora ATCC25270 was evaluated by challenge inoculation in potato slices at different ratios. The results revealed a remarkable suppressing effect on E. carotovora infection. The active component was further analyzed using different cell fractions, and the cell surface-projected fusion protein was found to correspond to the suppressing effect.

• 한국멀티미디어학회논문지
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• 제12권10호
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• pp.1436-1449
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• 2009

센서 노드의 위치에 따라서 수집되는 정보의 가치가 결정되기 때문에 센서 네트워크에서 센서 노드의 위치는 매우 중요하다. 본 논문에서는 센서 네트워크에서 인접 노드에 대한 정보와 수신되는 신호의 세기를 이용해서 노드의 위치를 추정하는 기법을 제안한다. 제안하는 기법을 이용하면 노드가 알고 있는 정보를 이용해서 쉽게 노드의 위치를 찾을 수 있다. 더욱이 위치를 알고 있는 앵커 노드를 기준으로 위치를 모르는 미지 노드에 대한 상대적인 위치를 찾을 수 있어서 전체적인 센서 노드의 분포를 쉽게 알 수 있다. 그리고 동적인 시스템인 센서 네트워크에서 제안한 기법을 구현하기 위해서 UML의 여러 다이어그램 중에서 유즈케이스 다이어그램 액티비티 다이어그램, 상태 머신 다이어그램을 이용해서 분석 및 설계를 하였다. UML을 이용하기 때문에 노드 위치 추정 시스템에서 제안 기법의 각 기능에 대한 흐름을 정확하게 파악할 수 있었다. 그리고 센서 노드들의 위치가 작은 오차를 가지고 추정됨을 확인하였다.

• JSTS:Journal of Semiconductor Technology and Science
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• 제16권5호
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• pp.542-549
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• 2016

This paper presents a SoC (System-on-a-Chip) dedicated for a single-chip smart capsule which can be used to continuously monitor human alimentary canal pH and temperature values. The SoC is composed of the pH and temperature sensor interface circuit, a wireless transceiver, the power management circuit and the flow control logic. Fabricated in $0.18{\mu}m$ standard CMOS technology, the SoC occupies a die area of ${\sim}9 mm^2$. The SoC consumes 6.15 mW from a 3 V power supply, guaranteeing the smart capsule battery life is no less than 24 hours when using 50 mAh coin batteries. The experimental results show that measurement accuracy of the smart capsule is ${\pm}0.1$ pH and ${\pm}0.2^{\circ}C$ for pH and temperature sensing, respectively, which meets the requirement of in-body pH and temperature monitoring in clinical practice.

• 한국ITS학회 논문지
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• 제10권2호
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• pp.1-8
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• 2011

교통체증은 도시지역에서 심각한 경제적, 사회적 비용을 초래하는 원인으로 간주되고 있다. ITS기법은 첨단 센싱, 컴퓨팅, 그리고 통신기술을 이용해 교통체증을 경감시킬 수 있는 훌륭한 수단이다. 본 연구는 차량과 주변 인프라 그리고 차량 간의 무선통신을 통한 중앙제어식 그리고 분산식 첨단통행자정보시스템의 프레임워크를 제안하고 전형적인 $6{\times}6$ 도시형 도로망에서 그 효과를 시뮬레이션 기법을 이용하여 분석하고자 한다. 본 논문의 연구결과로서는 교통류, 무선통신 라디오 레인지 그리고 통신차량의 보급률 등에 따라 제안된 첨단통행자정보시스템은 교통사고로 야기된 정체지역을 우회할 수 있는 최적의 노선을 제공함으로써 운전자의 통행시간을 줄여주는 효과를 보였다. 다양한 연구 환경에서도 중앙제어식 그리고 분산식 첨단통행자정보시스템은 거의 동일한 효과를 보였는바, 분산식 첨단통행자정보시스템은 고가의 건설비와 설치 운영비를 요구하는 중앙제어식 첨단통행자정보시스템을 대신할 수 있는 시스템으로 기대된다.

• 한국콘텐츠학회논문지
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• 제10권2호
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• pp.99-110
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• 2010

이벤트는 환자의 증상과 같은 시간 속성을 갖는 흐름을 의미하며 센서를 통하여 수집된 스트림 데이터는 시작과 종료 시점을 갖는 인터벌 이벤트로 요약 가능하다. 그러나 대부분의 시간 마이닝 기법은 빈발 이벤트만을 고려하며, 빈발하지 않는 이벤트는 중요하더라도 제외되는 문제가 있다. 이 논문에서는 다차원 스트림 데이터 환경에서 인터벌 이벤트에 기초하여 의미있는 시간 관계에 대한 연관 규칙 마이닝 기법을 제안한다. 제안 방법은 이벤트 가중치와 이상 이벤트가 감지된 시점의 스트림 데이터만 고려하여 이벤트의 발생 횟수에 상관없이 의미있는 시간 관계에 대한 연관 규칙을 탐사한다. 그리고 성능 평가를 통하여 제안 방법이 기존의 방법에 비하여 보다 유용한 지식을 탐사함을 보인다.

• International journal of advanced smart convergence
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• 제9권1호
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• pp.63-69
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• 2020

The rapid development in modern industrialization pollutant the water and atmospheric air across the globe that have a major impact on the human and livings health. In worldwide, every country government increasing the importance to improve the outdoor air pollution monitoring and control to provide quality of life and prevent the citizens and livings life from hazard disease. We proposed the environmental dust level detection method for outdoor facilities using sensor fusion technology to measure precise micro-dust level and monitor in realtime. In this proposed approach use the camera sensor and commercial dust level sensor data to predict the micro-dust level with data fusion method. The camera sensor based dust level detection uses the optical flow based machine learning method to detect the dust level and then fused with commercial dust level sensor data to predict the precise micro-dust level of the outdoor facilities and send the dust level informations to the outdoor air pollution monitoring system. The proposed method implemented on raspberry pi based open-source hardware with Internet-of-Things (IoT) framework and evaluated the performance of the system in realtime. The experimental results confirm that the proposed micro-dust level detection is precise and reliable in sensing the air dust and pollution, which helps to indicate the change in the air pollution more precisely than the commercial sensor based method in some extent.

• 대한의용생체공학회:의공학회지
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• 제30권6호
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• pp.503-509
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• 2009

The development of technology has led to ubiquitous health care service, which enables many patients to receive medical services anytime and anywhere. For the ubiquitous health care environment, real-time measurement of biomedical signals is very important, and the medical instruments must be small and portable or wearable. So, such devices have been developed to measure biomedical signals. In this study, we develop the biomedical monitoring device which is sensing the PPG signal, one of the useful signal in the field of ubiquitous healthcare. We design a watch-like biomedical signal monitoring system without a finger probe to prevent the user's inconvenience. This system obtains the PPG from the radial artery using a sensor in the wrist band. But, new device developed in this paper is easy to get the motion artifacts. So, we proposed new algorithm removing the motion artifacts from the PPG signal. The method detects motion artifacts by changing the degree of brightness of the light source. If the brightness of the light source is reduced, the PPG pulses will disappear. When the PPG pulses have disappeared completely, the remaining signal is not the signal that results from the changing blood flow. We believe that this signal is the motion artifact and call it the noise reference signal. The motion artifacts are removed by subtracting the noise reference signal from the input signal. We apply this algorithm to the system, so we can stabilize the biomedical monitoring system we designed.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.438-441
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• 2007

Recently, due to molecular biology and engineering technology, DNA microarray makes people watch thousands of genes and the state of variation from the tissue samples of living body. With DNA Microarray, it is possible to construct a genetic group that has similar expression patterns and grasp the progress and variation of gene. This paper practices Cluster Analysis which purposes the discovery of biological subgroup or class by using gene expression information. Hence, the purpose of this paper is to predict a new class which is unknown, open leukaemia data are used for the experiment, and MCL (Markov CLustering) algorithm is applied as an analysis method. The MCL algorithm is based on probability and graph flow theory. MCL simulates random walks on a graph using Markov matrices to determine the transition probabilities among nodes of the graph. If you look at closely to the method, first, MCL algorithm should be applied after getting the distance by using Euclidean distance, then inflation and diagonal factors which are tuning modulus should be tuned, and finally the threshold using the average of each column should be gotten to distinguish one class from another class. Our method has improved the accuracy through using the threshold, namely the average of each column. Our experimental result shows about 70% of accuracy in average compared to the class that is known before. Also, for the comparison evaluation to other algorithm, the proposed method compared to and analyzed SOM (Self-Organizing Map) clustering algorithm which is divided into neural network and hierarchical clustering. The method shows the better result when compared to hierarchical clustering. In further study, it should be studied whether there will be a similar result when the parameter of inflation gotten from our experiment is applied to other gene expression data. We are also trying to make a systematic method to improve the accuracy by regulating the factors mentioned above.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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• pp.76-82
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• 1998

Increase of greenhouse gas due to $CO_2$ and CH$_4$ gases would cause the global warming in the atmosphere. According to the global circulation model, it is pointed out in the Okhotsk Sea that the large increase of atmospheric temperature might be occurredin this region by global warming due to the doubling of greenhouse effectgases. Therefore, it is very important to monitor the sea ice extents in the Okhotsk Sea. To improve the sea ice extents and concentration with more highly accuracy, the field experiments have begun to comparewith Airborne Microwave Radiometer (AMR) and video images installed on the aircraft (Beach-200). The sea ice concentration is generally proportional to the brightness temperature and accurate retrieval of sea ice concentration from the brightness temperature is important because of the sensitivity of multi-channel data with the amount of open water in the sea ice pack. During the field experiments of airborned AMR the multi-frequency data suggest that the sea ice concentration is slightly dependending on the sea ice types since the brightness temperature is different between the thin and small piece of sea ice floes, and a large ice flow with different surface signatures. On the basis of classification of two sea ice types, it is cleary distinguished between the thin ice and the large ice floe in the scatter plot of 36.5 and 89.0GHz, but it does not become to make clear of the scatter plot of 18.7 and 36.5GHz Two algorithms that have been used for deriving sea ice concentrations from airbomed multi-channel data are compared. One is the NASA Team Algorithm and the other is the Bootstrap Algorithm. Intrercomparison on both algorithms with the airborned data and sea ice concentration derived from video images bas shown that the Bootstrap Algorithm is more consistent with the binary maps of video images.