• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1099-1101
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• 2003

Change detection technology, which discovers the change information on the surface of the earth by comparing and analyzing multi-temporal satellite images, can be usefully applied to the various fields, such as environmental inspection, urban planning, forest policy, updating of geographical information and the military usage. In this paper, we introduce a change detection system that can extract and analyze change elements from high-resolution satellite imagery as well as low- or middle-resolution satellite imagery. The developed system provides not only 7 pixelbased methods that can be used to detect change from low- or middle-resolution satellite images but also a float window concept that can be used in manual change detection from highresolution satellite images. This system enables fast access to the very large image, because it is constituted by OGC grid coverage components. Also new change detection algorithms can be easily added into this system if once they are made into grid coverage components.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.5
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• pp.904-912
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• 2011

In this paper, we have proposed a M&S tool for analyzing detection coverage and target localization in bistatic radar system. The detection coverage determined by radar parameters is meaningful when it satisfies the clear line-of-sight condition. We improved the method to find the minimum altitudes of transmitter and receiver for meeting the condition by considering three-dimensional coverage. Its computational burden is not problematic because the calculation is for maximizing the performance of the radar and does not demand a real-time operation. In addition, target localization on three-dimensional earth model based on the information of the height, longitude, and latitude is proposed instead of the previous unpractical calculation on two-dimensional bistatic plane. Its precalculated result can reduce its computation burden and it is suitable for real-time estimation of target location.

• Proceedings of the KSR Conference
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• 2000.05a
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• pp.330-335
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• 2000

Faults detection and containment requirements are typically allocated from a top-level specification as a percentage of total faults detection and containment, weighted by failure rate. This faults detection and containments are called as a fault coverage. The fault coverage requirements are typically allocated identically to all units in the system, without regard to complexity, cost of implementation or failure rate for each units. In this paper a simple methodology and mathematical model to support the allocation of system fault coverage rates to lower-level units by considering the inherent differences in reliability is presented. The models are formed as a form of constrained optimization. The objectives and constraints are modeled as a linear form and this problems are solved by linear programming. It is identified by simulation that the proposed solving methods for these problems are effective to such requirement allocating.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.379-384
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• 2003

In this paper, we introduce a change detection system that can extract and analyze change elements from high-resolution satellite imagery as well as low- or middle-resolution satellite imagery. The developed system provides not only 7 pixel-based methods that can be used to detect change from low- or middle-resolution satellite images but also a float window concept that can be used in manual change detection from high-resolution satellite images. This system enables fast process of the very large image, because it is constituted by OGC grid coverage components. Also new change detection algorithms can be easily added into this system if once they are made into grid coverage components.

• Journal of Communications and Networks
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• v.16 no.5
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• pp.493-501
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• 2014

Coverage completeness is an important indicator for quality of service in wireless sensor networks (WSN). Due to limited energy and diverse working conditions, the sensor nodes have different lifetimes which often cause network holes. Most of the existing methods expose large limitation and one-sidedness because they generally consider only one aspect, either coverage rate or energy issue. This paper presents a novel method for coverage hole detection with residual energy in randomly deployed wireless sensor networks. By calculating the life expectancy of working nodes through residual energy, we make a trade-off between network repair cost and energy waste. The working nodes with short lifetime are screened out according to a proper ratio. After that, the locations of coverage holes can be determined by calculating the joint coverage probability and the evaluation criteria. Simulation result shows that compared to those traditional algorithms without consideration of energy problem, our method can effectively maintain the coverage quality of repaired WSN while enhancing the life span of WSN at the same time.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.771-780
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• 2012

In the current analysis, we examine news coverage data widely used in media studies. News coverage data is usually time series data to capture the volume or the tone of the news media's coverage of a topic. We first describe the distributional properties of autoregressive conditionally heteroscadestic(ARCH) effects and compare two major American newspaper's coverage of U.S.-North Korea relations. Subsequently, we propose a change point detection model and apply it to the detection of major change points in the tone of American newspaper coverage of U.S.-North Korea relations.

• International Journal of Reliability and Applications
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• v.8 no.1
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• pp.53-66
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• 2007

This paper proposes a new non-homogeneous Poisson process software reliability growth model based on the coverage information. The new model incorporates the coverage information in the fault detection process by assuming that only the faults in the covered constructs are detectable. Since the coverage growth behavior depends on the testing strategy, the fault detection process is first modeled for the general testing strategy and then realized for the uniform testing. Finally the model for the uniform testing is empirically evaluated by applying it to real data sets.

• Journal of the Korea Society of Computer and Information
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• v.24 no.4
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• pp.169-176
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• 2019

Wireless sensor networks are used to monitor and control areas in a variety of military and civilian areas such as battlefield surveillance, intrusion detection, disaster recovery, biological detection, and environmental monitoring. Since the sensor nodes are randomly placed in the area of interest, separation of the sensor network area may occur due to environmental obstacles or a sensor may not exist in some areas. Also, in the situation where the sensor node is placed in a non-relocatable place, some node may exhaust energy or physical hole of the sensor node may cause coverage hole. Coverage holes can affect the performance of the entire sensor network, such as reducing data reliability, changing network topologies, disconnecting data links, and degrading transmission load. It is possible to solve the problem that occurs in the coverage hole by finding a coverage hole in the sensor network and further arranging a new sensor node in the detected coverage hole. The existing coverage hole detection technique is based on the location of the sensor node, but it is inefficient to mount the GPS on the sensor node having limited resources, and performing other location information processing causes a lot of message transmission overhead. In this paper, we propose an Adjacent Matrix-based Hole Coverage Discovery(AMHCD) scheme based on connectivity of neighboring nodes. The method searches for whether the connectivity of the neighboring nodes constitutes a closed shape based on the adjacent matrix, and determines whether the node is an internal node or a boundary node. Therefore, the message overhead for the location information strokes does not occur and can be applied irrespective of the position information error.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.77-87
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• 2023

Applying various association rule mining algorithms to the network intrusion detection task involves two critical issues: too large size of generated rule set which is hard to be utilized for IoT systems and hardness of control of false negative/positive rates. In this research, we propose an association rule mining algorithm based on the newly defined measures called coverage and exclusion. Coverage shows how frequently a pattern is discovered among the transactions of a class and exclusion does how frequently a pattern is not discovered in the transactions of the other classes. We compare our algorithm experimentally with the Apriori algorithm which is the most famous algorithm using the public dataset called KDDcup99. Compared to Apriori, the proposed algorithm reduces the resulting rule set size by up to 93.2 percent while keeping accuracy completely. The proposed algorithm also controls perfectly the false negative/positive rates of the generated rules by parameters. Therefore, network analysts can effectively apply the proposed association rule mining to the network intrusion detection task by solving two issues.

• Journal of Communications and Networks
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• v.11 no.1
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• pp.57-71
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• 2009

Networking together hundreds or thousands of cheap sensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. As sensor nodes are typically battery operated, it is important to efficiently use the limited energy of the nodes to extend the lifetime of the wireless sensor network (WSN). One of the fundamental issues in WSNs is the coverage problem. In this paper, the border coverage problem in WSNs is rigorously analyzed. Most existing results related to the coverage problem in wireless sensor networks focused on planar networks; however, three dimensional (3D) modeling of the sensor network would reflect more accurately real-life situations. Unlike previous works in this area, we provide distributed algorithms that allow the selection and activation of an optimal border cover for both 2D and 3D regions of interest. We also provide self-healing algorithms as an optimization to our border coverage algorithms which allow the sensor network to adaptively reconfigure and repair itself in order to improve its own performance. Border coverage is crucial for optimizing sensor placement for intrusion detection and a number of other practical applications.