• Journal of KIISE:Databases
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• v.36 no.3
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• pp.189-197
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• 2009

Top-k queries are important to many wireless sensor applications. Conventional Top-k query processing algorithms install a filter at each sensor node and suppress unnecessary sensor updates. However, they have some drawbacks that the sensor nodes consume energy extremely to probe sensor reading or update filters. Especially, it becomes worse, when the variation ratio of top-k result is higher. In this paper, we propose a novel Top-k query processing algorithm for energy-efficiency. First, each sensor determines its priority as the order of data gathering. Next, sensor nodes that have higher priority transmit their sensor readings to the base station until gathering k sensor readings. In order to show the superiority of our query processing algorithm, we simulate the performance with the existing query processing algorithms. As a result, our experimental results show that the network lifetime of our method is prolonged largely over the existing method.

• Journal of KIISE:Databases
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• v.33 no.2
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• pp.163-174
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• 2006

In distributed wireless sensor network, it is difficult to transmit and analyze the entire stream data depending on limited networks, power and processor. Therefore it is suitable to use alternative stream data processing after classifying the continuous stream data. We propose a classification framework for continuous multivariate stream data. The proposed approach works in two steps. In the preprocessing step, it takes input as a sliding window of multivariate stream data and discretizes the data in the window into a string of symbols that characterize the signal changes. In the classification step, it uses a standard text classification algorithm to classify the discretized data in the window. We evaluated both supervised and unsupervised classification algorithms. For supervised, we tested Bayesian classifier and SVM, and for unsupervised, we tested Jaccard, TFIDF Jaro and Jaro Winkler. In our experiments, SVM and TFIDF outperformed other classification methods. In particular, we observed that classification accuracy is improved when the correlation of attributes is also considered along with the n-gram tokens of symbols.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.5
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• pp.12-24
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• 1994

최근 수년간에 걸쳐 이루어진 센서기술의 발달과 컴퓨터를 이용한 데이타 처리능력의 혁신적인 발전은 대형의 복잡한 시스템을 실시간으로 운용하는데 있어서 막대한 양의 정보를 적절히 처리할 수 있는 기술을 요구한다. 예를 들어, 제철 또는 화학공장 공정제어에 있어서 여러 단계의 복잡한 공정의 상태에 관련된 정보는 다양한 센서들에 의하여 감지되어 제어컴퓨터에 전달된다. 또한 제어컴퓨터에서 생성되는 데이타는 자동화장비들의 각 구동장치로 분배된다. 이와 더불어 전체공정의 운용 및 관리와 제품의 품질 검사 및 시험에 관련된 데이타들도 적절히 전송되어야 한다. 또한 공장의 생산자동화 시스템에서도 수많은 로봇, PLC, CNC,AGV,켠베이어, 자동창고 등 자동화장비관련장비들의 시간적,공간적인 작업상태와 작업환경에 대한 무수한 정보들은 다양한 센서들에 의하여 감지되어 제어컴퓨터로 전달되어야 한다. 이러한 막대한 양의 데이타들을 적시에 수집하여 가공한 후 적시, 적소에 분배해 줄 수 있는 데이타 전송기술의 확보는 미래의 첨단생산시스템으로 인식되는 CIM(Computer Integrated Manufacturing)및 분산제어시스템(Distributed Control System)의 구축을 위한 선결과제라 할 수 있다. 이러한 문제들은 발전소, 최신예 항공기와 인공위성 등과 같이 고도의 제어기능과 매우 높은 신뢰도를 요구하는 시스템들에서도 마찬가지로 제기된다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.139-144
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• 2017

As technologies related to sensor network are currently emerging and the use of GeoSensor is increasing along with the development of IoT technology, spatial query processing systems to efficiently process spatial sensor data are being actively studied. However, existing spatial query processing systems do not support a spatial-temporal data type and a spatial-temporal operator for processing spatial-temporal sensor data. Therefore, they are inadequate for processing spatial-temporal sensor data like GeoSensor. Accordingly, this paper developed a spatial-temporal query processing system, for efficient spatial-temporal query processing of spatial-temporal sensor data in a sensor network. Lastly, this paper verified the utility of System through a scenario, and proved that this system's performance is better than existing systems through performance assessment of performance time and memory usage.

• Journal of Korea Spatial Information System Society
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• v.9 no.1
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• pp.45-57
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• 2007

Recently, the development of sensor devices has accelerated researches on advanced technologies like Wireless Sensor Networks. Moreover, spatial sensors using GPS lead to the era of the Ubiquitous Computing Environment which generally uses spatial information and non-spatial information together. In this new era, a real-time processing system for spatial sensor data is essential. In this reason, new data processing systems called DSMS(Data Stream Management System) are being developed by many researchers. However, since most of them do not support geometry types and spatial functions to process spatial sensor data, they are not suitable for the Ubiquitous Computing Environment. For these reasons, in this paper, we designed and implemented a spatial DSMS by extending STREAM which stands for STanford stREam datA Manager, to solve these problems. We added geometry types and spatial functions to STREAM in order to process spatial sensor data efficiently. In addition, we implemented a Spatial Object Manager to manage shared spatial objects within the system. Especially, we implemented the Simple Features Specification for SQL of OGC for interoperability and applied algorithms in GEOS to our system.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.11a
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• pp.141-146
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• 2005

최근 들어 텔레매틱스 분야에서 자동차의 위치 및 상태를 감시하고 관리하기 위해 무선 센서 네트워크의 활용이 크게 확장되고 있다. 기존에는 위치, 속도, 온도와 같은 이 기종 플랫폼간의 센서 데이타 수집 및 운용을 위해 독립적인 어플리케이션을 사용하고 있으며, 그러한 데이타 교환과 통합을 위하여 많은 비용이 소요되었다. OGC(OpenGIS Consortium)에서는 이러한 문제를 해결하고자 Sensor Collection Service 구현 명세를 제안하였다. Sensor Collection Service 구현 명세는 센서 데이타에 대한 질의를 처리하기 위한 표준 인터페이스를 정의하고 있으며, 질의 결과로는 센서에 대한 정보 및 센서데이타를 반환하도록 정의하고 있다. 본 논문에서는 Sensor Collection Service 표준 인터페이스를 이용하여 센서로부터 획득된 위치 및 속도, 온도 등의 다양한 데이타에 웹을 통하여 접근할 수 있도록 센서 데이타 서비스 시스템을 설계 잊 구현하였다. 따라서 사용자들은 센서 데이타 서비스 시스템을 통하여 센서의 종류와 위치에 관계없이 웹 상에서 위치 및 속도, 온도 등과 같은 다양한 센서 데이타를 획득할 수 있으며 시스템간 데이타의 교환 및 통합이 가능하다. 또한, 사용자가 쉴게 검색 및 분석할 수 있도록 Sensor Collection Service 표준 인터페이스 질의를 통하여 획득된 데이타를 센서의 위치와 측정 시간에 기반하여 보여주고 있다. 본 시스템은 다양한 센서 데이타의 획득과 타 시스템과의 데이타 교환이 용이하므로 텔레매틱스, 위치 추적 시스템, 상태 감시 시스템 등 다양한 분야에 효과적인 도구로 활용될 수 있다.이루어졌다 가능한 창조 모델로 이용될 수 있을 것으로 생각된다.}94,\;29.4{\pm}30.3,\;45.1{\pm}44$로 Mel 10군과 Mel 30군이 유의적인 감소를 보였으나(p<0.05) 이들 두 군 간의 차이는 나타나지 않았다. 이상의 결과로, 랫트에서 복강수술 후 melatonin 10mg/kg투여가 복강 내 유착 방지에 효과적이라고 생각된다.-1}{\cdot}yr^{-1}$로서 두 생태계에 축적되었다.여한 3,5,7군에서 PUFA 함량이 증가한 반면, SFA 함량은 감소하여 P/S 비율, n-3P/n-6P 비율은 증가하는 경향이었으며 이는 간장의 인지질, 콜레스테롤 에스테르, 총 지질의 지방산조성에서도 같은 경향을 볼 수 있었다.X>$(C_{18:2})$와 n-3계 linolenic acid$(C_{18:3})$가 대부분을 차지하였다. 야생 돌복숭아 과육 중의 지방산 조성은 포화지방산이 16.74%, 단불포화지방산 17.51% 및 다불포화지방산이 65.73%의 함유 비율을 보였는데, 이 중 다불포화지방산인 n-6계 linoleic acid$(C_{18:2})$와 n-3계 linolenic acid$(C_{18:3})$가 지질 구성 총 지방산의 대부분을 차지하는 함유 비율을 나타내었다.했다. 하강하는 약 4일간의 기상변화가 자발성 기흉 발생에 영향을 미친다고 추론할 수 있었다. 향후 본 연구에서 추론된 기상변화와 기흉 발생과의 인과관계를 확인하고 좀 더 구체화하기 위한 연구가 필요할 것이다.게 이루어질 수 있을 것으로 기대된다.는 초과수익률이 상승하지만, 이후로는 감소하므로,

• Journal of KIISE:Information Networking
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• v.35 no.2
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• pp.139-148
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• 2008

Many types of sensor data exhibit strong correlation in both space and time. Suppression, both temporal and spatial, provides opportunities for reducing the energy cost of sensor data collection. Unfortunately, existing clustering algorithms are difficult to utilize the spatial or temporal opportunities, because they just organize clusters based on the distribution of sensor nodes or the network topology but not correlation of sensor data. In this paper, we propose a novel clustering algorithm with suppression techniques. To guarantee independent communication among clusters, we allocate multiple channels based on sensor data. Also, we propose a spatio-temporal suppression technique to reduce the network traffic. In order to show the superiority of our clustering algorithm, we compare it with the existing suppression algorithms in terms of the lifetime of the sensor network and the site of data which have been collected in the base-station. As a result, our experimental results show that the size of data was reduced by $4{\sim}40%$, and whole network lifetime was prolonged by $20{\sim}30%$.

• Journal of KIISE:Information Networking
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• v.35 no.1
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• pp.21-33
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• 2008

The wireless sensor nodes near to the fixed sink node suffer from the quickly exhausted battery energy. To address this problem, the mobile sink node has been applied to distribute the energy consumption into all wireless sensor nodes. However, since the mobile sink node moves, the data collection scheduling scheme is necessary for the sink node to receive the data from all sensor nodes as fair as possible. The application fields of wireless sensor network need the real-time processing. If the uneven data collection occurs in the wireless sensor network, the real-time processing for the urgent events can not be satisfied. In this paper, a new method is proposed to support the lair data collection between all sensor nodes. The proposed method performs the scheduling algorithm based on the resident time of the sink node staying in a radius of communication range and the amount of data transferred already. In this paper, the proposed method and existing data collection scheduling schemes are evaluated in wireless sensor network with the mobile sink node. The result shows that the proposed method provides the best fairness among all data collection schemes.

• Journal of KIISE:Databases
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• v.33 no.3
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• pp.327-341
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• 2006

As we are getting to deal with more applications that generate streaming data such as sensor network, monitoring, and SDI (selective dissemination of information), active research is being conducted to support efficient processing of queries over streaming data. The applications on the Web environment like SDI, among others, require query processing over streaming XML data, and its investigation is very important because XML has been established as the standard for data exchange on the Web. One of the major problems with the previous systems that support query processing over streaming XML data is that they cannot deal adaptively with dynamically changing stream because they rely on static query plans. On the other hand, the stream query processing systems based on relational data model have achieved adaptiveness in query processing due to query operator routing. In this paper, we propose a system of adaptive query processing over streaming XML data in which the model of adaptive query processing over streaming relational data is applied. We compare our system with YFiiter, one of the representative systems that provide XML stream query processing capability, to show efficiency of our system.

• Journal of KIISE:Databases
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• v.33 no.2
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• pp.188-200
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• 2006

Once a continuous query, which is commonly used in sensor networks, is issued, the query is executed many times with a certain interval and the results of those query executions are collected to the base station. Since this comes many communication messages continuously, it is important to reduce communication cost for collecting data to the base station. In sensor networks, in-network processing reduces the number of message transmissions by partially aggregating results of an aggregate query in intermediate nodes, or merging the results in one message, resulting in reduction of communication cost. In this paper, we propose a routing tree for sensor nodes that qualify the given query predicate, called the query specific routing tree(QSRT). The idea of the QSRT is to maximize in-network processing opportunity. A QSRT is created seperately for each query during dissemination of the query. It is constructed in such a way that during the collection of query results partial aggregation and packet merging of intermediate results can be fully utilized. Our experimental results show that our proposed method can reduce message transmissions more than 18% compared to the existing one.