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    Chapter and Conference Paper

    Efficient Data Monitoring in Sensor Networks Using Spatial Correlation

    In order to reduce r the energy consumption of sensors, we present an approximate data gathering technique, called CMOS, based on the Kalman filter. The goal of CMOS is to efficiently obtain the sensor reading...

    Jun-Ki Min in Mobile, Ubiquitous, and Intelligent Computing (2014)

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    Chapter and Conference Paper

    An Efficient Outlier Detection Technique in Wireless Sensor Networks

    An outlier in wireless sensor networks is a sensor reading generated by malfunctioned sensor nodes or external environmental effect. Since an outlier is an important indicator of environment change or malfunct...

    Hongyeon Kim, Jun-Ki Min in Ubiquitous Information Technologies and Applications (2014)

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    Chapter and Conference Paper

    An Efficient Data Access Method Exploiting Quadtrees on MapReduce Frameworks

    Due to the advance of diverse techniques such as social networks and sensor networks, the volume of data to be processed has rapidly increased. After Google proposed the MapReduce framework which processes big...

    Hyunho Noh, Jun-Ki Min in Database Systems for Advanced Applications (2013)

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    Chapter and Conference Paper

    A Hybrid Context-Aware Wearable System with Evolutionary Optimization and Selective Inference of Dynamic Bayesian Networks

    Multiple sensor-based context inference systems can perceive users’ tasks in detail while it requires complicated recognition models with larger resources. Such limitations make the systems difficult to be use...

    Jun-Ki Min, Sung-Bae Cho in Hybrid Artificial Intelligent Systems (2011)

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    Chapter and Conference Paper

    Online Gesture Recognition for User Interface on Accelerometer Built-in Mobile Phones

    Recently, several smart phones are equipped with a 3D-accelerometer that can be used for gesture-based user interface (UI). In order to utilize the gesture UI for the real-time systems with various users, the ...

    BongWhan Choe, Jun-Ki Min, Sung-Bae Cho in Neural Information Processing. Models and … (2010)

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    Chapter and Conference Paper

    Mining and Visualizing Mobile Social Network Based on Bayesian Probabilistic Model

    Social networking has provided powerful new ways to find people, organize groups, and share information. Recently, the potential functionalities of the ubiquitous infrastructure let users form a mobile social ...

    Jun-Ki Min, Su-Hyung Jang, Sung-Bae Cho in Ubiquitous Intelligence and Computing (2009)

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    Chapter and Conference Paper

    WT-Heuristics: A Heuristic Method for Efficient Operator Ordering

    In this paper, we focus on the processing of stream data whose characteristics vary unpredictably by over time. Particularly, we suggest a method which generates an efficient operator execution order called WT...

    Jun-Ki Min in Advances in Databases: Concepts, Systems and Applications (2007)

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    Chapter and Conference Paper

    An Efficient Encoding and Labeling for Dynamic XML Data

    In order to efficiently determine structural relationships among XML elements and to avoid re-labeling for updates, much research about labeling schemes has been conducted, recently. However, a harmonic suppor...

    Jun-Ki Min, Jihyun Lee, Chin-Wan Chung in Advances in Databases: Concepts, Systems a… (2007)

  9. Chapter and Conference Paper

    Ensemble Approaches of Support Vector Machines for Multiclass Classification

    Support vector machine (SVM) which was originally designed for binary classification has achieved superior performance in various classification problems. In order to extend it to multiclass classification, on...

    Jun-Ki Min, **-Hyuk Hong, Sung-Bae Cho in Pattern Recognition and Machine Intelligence (2007)

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    Chapter and Conference Paper

    Multiple Classifier Fusion Using k-Nearest Localized Templates

    This paper presents a method for combining classifiers that uses k-nearest localized templates. The localized templates are estimated from a training set using C-means clustering algorithm, and matched to the dec...

    Jun-Ki Min in Intelligent Data Engineering and Automated Learning - IDEAL 2007 (2007)

  11. Chapter and Conference Paper

    A Query Index for Stream Data Using Interval Skip Lists Exploiting Locality

    To accelerate the query performance, diverse continuous que- ry index schemes have been proposed for stream data processing systems. In general, a stream query contains the range condition. Thus, by using rang...

    Jun-Ki Min in Computational Science – ICCS 2007 (2007)

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    Chapter and Conference Paper

    BEAST: A Buffer Replacement Algorithm Using Spatial and Temporal Locality

    Efficient buffer management is closely related to system performance. Thus, much research has been performed on various buffer management techniques. However, many of the proposed techniques utilize the tempor...

    Jun-Ki Min in Computational Science and Its Applications - ICCSA 2006 (2006)

  13. Chapter and Conference Paper

    BRUST: An Efficient Buffer Replacement for Spatial Databases

    This paper presents a novel buffer management technique for spatial database management systems. Much research has been performed on various buffer management techniques in order to reduce disk I/O. However, m...

    Jun-Ki Min in Computational Science – ICCS 2006 (2006)

  14. Chapter and Conference Paper

    Effective Fingerprint Classification by Localized Models of Support Vector Machines

    Fingerprint classification is useful as a preliminary step of the matching process and is performed in order to reduce searching time. Various classifiers like support vector machines (SVMs) have been used to ...

    Jun-Ki Min, **-Hyuk Hong, Sung-Bae Cho in Advances in Biometrics (2005)

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    Chapter and Conference Paper

    Agent-Based Evolutionary Labor Market Model with Strategic Coalition

    A real-world labor market has complex worksite interactions between a worker and an employer. This paper investigates the behavior patterns of workers and employers with a job capacity and a job concentration ...

    Seung-Ryong Yang, Jun-Ki Min, Sung-Bae Cho in AI 2004: Advances in Artificial Intelligence (2005)