• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.65-67
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• 2018

We introduce a system that detects smoking in a specific area. The proposed system is implemented on a wireless ad hoc network consisting of Raspberry Pi boards. It is more economical owing to low-cost device than commercial smoking monitoring system and is scalable than the existing system with single Raspberry Pi. In this paper, the probability density function of carbon monoxide concentration during smoking and non-smoking is approximated as Gauusian distribution, respectively, using data measured from sensors for a long time. Based on this, a maximum likelihood detection technique is adopted to estimate the smoking status by observing the concentration of carbon monoxide. We aim at improving the reliability by estimating the smoking status using the collected values from multiple sensors connected to the ad hoc network.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.10
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• pp.97-107
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• 2015

The initial X-ray images obtained from a digital X-ray machine have a wide data range and uneven brightness level than normal images. In particular, in Chest X-ray images, it is necessary to improve naturally all of the parts such as ribs, spine, tissue, etc. These X-ray images can not be improved enough from conventional image quality enhancement algorithms because their characteristics are different from ordinary images'. This paper proposes to eliminate unnecessary background from an input image and expand the histogram range of the image. Then, we adjust the weight per frequency band of the image for improvement of contrast and sharpness. Finally, jointly taking the advantages of global contrast enhancement and local contrast enhancement methods we obtain an improved X-ray image suitable for effective diagnosis in comparison with the existing methods. Experimental results show quantitatively that the proposed algorithm provides better X-ray images in terms of the discrete entropy and saturation than the previous works.

• Journal of Broadcast Engineering
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• v.17 no.5
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• pp.876-890
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• 2012

In this paper, we investigated the performances of the distributed video codec with adaptive Gray code to apply for frame-difference signal. That is, the best cases and the worst cases were analyzed and compared by considering the statistical characteristics of the frame difference signal in view of the Gray code allocation. Through computer simulations, if 9-bit data for frame difference signal is generated for luminance signal with 8-bit definition and so n-bit is allocated to the quantized coefficient, we were able to find the best method to reduce the virtual channel noise by adding $256+2^{9-n-1}$ to the frame difference signal. Through computer simulation with test video sequences, it was shown that the performance difference between the best cases and the worst cases is larger than about 1.5dB at same rate. It is expected that the results in this paper are applicable for the transform-domain scheme as well as the pixel-domain scheme.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.7
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• pp.679-688
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• 2010

The major objective of the present study is to extend the applications of inverse analysis to more realistic engineering fields with a complex combustion process rather than the traditional simple heat-transfer problems. In order to do this, the unknown initial mass fractions of $CH_4/O_2$ are estimated from the temperature measurement data by inverse analysis in the practical diffusion-controlled turbulent combustion problem. In order to ensure efficient inverse analysis, the repulsive particle swarm optimization (RPSO) method, which belongs to the class of stochastic evolutionary global optimization methods, is implemented as an inverse solver. Based on this study, it is expected that useful information can be obtained when inverse analysis is used in the diagnosis, design, or optimization of real combustion systems involving unknown parameters.

• Journal of Internet Computing and Services
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• v.13 no.5
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• pp.1-8
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• 2012

In this paper, we propose a new clustering combination based on numerical data driven for rule generation mechanism. In large and complicated space, a clustering method can obtain limited performance results. To overcome the single clustering method problem, hybrid combined methods can solve problem to divided simple cluster estimation. Fundamental structure of the proposed method is combined by mountain clustering and modified Chen clustering to extract detail cluster information in complicated data distribution of non-parametric space. It has automatic rule generation ability with advanced density based operation when intelligent systems including neural networks and fuzzy inference systems can be generated by clustering results. Also, results of the mechanism will be served to information of decision support system to infer the useful knowledge. It can extend to healthcare and medical decision support system to help experts or specialists. We show and explain the usefulness of the proposed method using simulation and results.

• Proceedings of the Korea Contents Association Conference
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• 2005.05a
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• pp.315-319
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• 2005

In this paper, we present a Petri Net (PN) model for reliability analysis of fault-tolerant database system models that consists of components one shared memory, bus, processors and database (disk). Each component can be failed and repaired individually. The system is operational as long as database and one of component is operational. We develop Stochastic Reward Net (SRN) Model for reliability analysis of database system. SRN is potential to define various reward functions. and can be easily used to obtain performance measures. The modeling techniques using variable cardinality, enabling function, timed transition priority in SRN are shown.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.567-574
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• 2013

Recently, many researches on P2P overlay network-based multimedia streaming services have been actively performed because of their high scalability and cost-efficiency advantages. However, P2P overlay networks also have the shortcoming of generating higher traffic owing to their unicast-based one-to-many multimedia deliveries. In order to reduce the traffic generated by the P2P streaming overlay network, we propose an ISP and locality-based parent node discovery method and check its feasibility through an implementation of a prototype streaming system. The measurement of RTTs and hop counts for random nodes having different ISPs and localities shows the proposed method to be able to shorten about 32% RTTs and about 17% Hop counts.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.4
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• pp.359-365
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• 2008

This paper focused on generation of more accurate DEM and analysis of accuracy. For this, we applied suitable sensor modeling technique for each satellite image and automatic pyramid matching using image pyramid was applied. Matching algorithm based on epipolarity and scene geometry also was applied for stereo matching. IKONOS, Quickbird, SPOT-5, Kompsat-2 were used for experiments. In particular, we applied orbit-attitude sensor modeling technique for Kompsat-2 and performed DEM generation successfully. All DEM generated show good quality. Assessment was carried out using USGS DTED and we also compared between DEM generated in this research and DEM generated from common software. All DEM had $9m{\sim}12m$ Mean Absolute Error and $13m{\sim}16m$ RMS Error. Experimental results show that the DEMs of good performance which is similar to or better than result of DEMs generated from common software.

• Journal of Korean Society of Transportation
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• v.35 no.5
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• pp.409-422
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• 2017

TOD (Transit-Oriented Development) is one of the urban structure concentrated on the multifunctional space/district with public transportation system, which is introduced for maintaining sustainable future cities. With such trends, the project of building complex transferring centers located at a urban railway station has widely been spreaded and a comprehensive and systematic analytical framework is required to clarify and readily understand the complicated procedure of estimation with the large scale of the project. By doing so, this study is to develop a comprehensive analytical framework for estimating a pedestrian OD matrix using a spatial information and an integrated smart card data, which is so called a data depository and it has been applied to the Samseong station for the model validation. The proposed analytical framework contributes on providing a chance to possibly extend with digitalized and automated data collection technologies and a BigData mining methods.

• Journal of KIISE:Information Networking
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• v.30 no.2
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• pp.143-154
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• 2003

There is a growing trend in developing system for distributed mobile system that supports services - job flow management, video conference, replicated data management and resource allocation. Supporting these services, applications have to use causally ordered message delivery. Previous proposals that provide causally ordered message delivery have problems such as communication overhead, message delaying, scalability, computing overload of mobile host. In this paper, we proposed efficient protocol for causally ordered message delivery using the methods that MSS maintains dependency information matrix between MSS and MH, Piggybacking dependency information about each immediate predecessor message. Proposed algorithm, when compared with previous proposals, provides a low message overhead, and low probability of unnecessary inhibition in delivering messages. Also, it consider resource restriction of MH and low bandwidth of wireless communication by computing most of algorithm at MSS, and reduce processing delay by executing causally ordered message delivery a unit of MH.