• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.16-21
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• 2008

Aero-engine, as one kind of rotating machinery with complex structure and high rotating speed, has complicated vibration faults. Therefore, condition monitoring and fault diagnosis system is very important for airplane security. In this paper, a vibration data acquisition and intelligent fault diagnosis system is introduced. First, the vibration data acquisition part is described in detail. This part consists of hardware acquisition modules and software analysis modules which can realize real-time data acquisition and analysis, off-line data analysis, trend analysis, fault simulation and graphical result display. The acquisition vibration data are prepared for the following intelligent fault diagnosis. Secondly, two advanced artificial intelligent(AI) methods, mapping-based and rule-based, are discussed. One is artificial neural network(ANN) which is an ideal tool for aero-engine fault diagnosis and has strong ability to learn complex nonlinear functions. The other is data mining, another AI method, has advantages of discovering knowledge from massive data and automatically extracting diagnostic rules. Thirdly, lots of historical data are used for training the ANN and extracting rules by data mining. Then, real-time data are input into the trained ANN for mapping-based fault diagnosis. At the same time, extracted rules are revised by expert experience and used for rule-based fault diagnosis. From the results of the experiments, the conclusion is obvious that both the two AI methods are effective on aero-engine vibration fault diagnosis, while each of them has its individual quality. The whole system can be developed in local vibration monitoring and real-time fault diagnosis for aero-engine.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1489-1497
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• 2018

Web application services have diversified. At the same time, research on intrusion detection is continuing due to the surge of cyber threats. Also, As a single-defense system evolves into multi-level security, we are responding to specific intrusions by correlating security events that have become vast. However, it is difficult to check the OS, service, web application type and version of the target system in real time, and intrusion detection events occurring in network-based security devices can not confirm vulnerability of the target system and success of the attack A blind spot can occur for threats that are not analyzed for problems and associativity. In this paper, we propose the validation of effectiveness for intrusion detection events using TF-IDF. The proposed scheme extracts the response traffics by mapping the response of the target system corresponding to the attack. Then, Response traffics are divided into lines and weights each line with an TF-IDF weight. we checked the valid intrusion detection events by sequentially examining the lines with high weights.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.1
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• pp.89-102
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• 2008

Internet becomes more and more popular, and most companies and institutes use web services for e-business and many other purposes. With the explosion of Internet, the attack of internet worm has grown. Simulation is one of the most widely used method to study internet worms. But, it is quite challenging to simulate very large-scale worm attacks because of various reasons. By this reason, we often use the modeling network simulation technique. But, it also has problem that it difficult to apply each worm attacks to simulation. In this paper, we propose worm attack representation and mapping methods for apply worm attack to simulation. The proposed method assist to achieve the simulation efficiency. And we can express each worm attacks more detail. Consequently, the simulation of worm attacks has the time-efficiency and the minuteness.

• Journal of the Korean Institute of Rural Architecture
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• v.25 no.1
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• pp.35-44
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• 2023

This study aimed to understand the driver change of recent research in relation to rural and migrant and draw overarching issues as well as to provide implications to contribute to migrants' social integration in Korean rural areas. As for the scope and method of the study, data through quantitative bibliographic analysis (quantitative data) and research keywords by period were derived. To address the aim this study employed bibliometric analysis utilising netwok mapping interface analysis by VOSviewer and topic modeling analysis by Netminer. The findings were revealed that firstly mental health issues in abroad research and employment and discrimination in domestic research both derived from migrant mobility constituted staple key issues, secondly internal and external research differed two issues in health and violence where Korea has overlooked the issues seriously. Therefore this study presented implications which are about first, health and violence-related sections for migrants should be specified into domestic law, second domestic-focused MIPEX index should be developed in which the two issues are over-weighted and last such newly emerging approach 'inclusive formation of social psychological mechanisms should be widely spread. Concluding remark is that delivering the implications can be foster to migrants' integration in rural area underlining that this will ultimately contribute to migrants' quality of life.

• Korean Journal of Radiology
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• v.24 no.11
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• pp.1131-1141
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• 2023

Objective: Cortical iron deposition has recently been shown to occur in Alzheimer's disease (AD). In this study, we aimed to evaluate how cortical gray matter iron, measured using quantitative susceptibility mapping (QSM), differs in the clinical cognitive impairment spectrum. Materials and Methods: This retrospective study evaluated 73 participants (mean age ± standard deviation, 66.7 ± 7.6 years; 52 females and 21 males) with normal cognition (NC), 158 patients with mild cognitive impairment (MCI), and 48 patients with AD dementia. The participants underwent brain magnetic resonance imaging using a three-dimensional multi-dynamic multi-echo sequence on a 3-T scanner. We employed a deep neural network (QSMnet+) and used automatic segmentation software based on FreeSurfer v6.0 to extract anatomical labels and volumes of interest in the cortex. We used analysis of covariance to investigate the differences in susceptibility among the clinical diagnostic groups in each brain region. Multivariable linear regression analysis was performed to study the association between susceptibility values and cognitive scores including the Mini-Mental State Examination (MMSE). Results: Among the three groups, the frontal (P < 0.001), temporal (P = 0.004), parietal (P = 0.001), occipital (P < 0.001), and cingulate cortices (P < 0.001) showed a higher mean susceptibility in patients with MCI and AD than in NC subjects. In the combined MCI and AD group, the mean susceptibility in the cingulate cortex (β = -216.21, P = 0.019) and insular cortex (β = -276.65, P = 0.001) were significant independent predictors of MMSE scores after correcting for age, sex, education, regional volume, and APOE4 carrier status. Conclusion: Iron deposition in the cortex, as measured by QSMnet+, was higher in patients with AD and MCI than in NC participants. Iron deposition in the cingulate and insular cortices may be an early imaging marker of cognitive impairment related neurodegeneration.

• International Journal of Concrete Structures and Materials
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• v.7 no.3
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• pp.225-238
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• 2013

In this study, a two-layer feed-forward neural network was constructed and applied to determine a mapping associating mix design and testing factors of cement-nano silica (NS)-rice husk ash ternary blended concrete samples with their performance in conductance to the water absorption properties. To generate data for the neural network model (NNM), a total of 174 field cores from 58 different mixes at three ages were tested in the laboratory for each of percentage, velocity and coefficient of water absorption and mix volumetric properties. The significant factors (six items) that affect the permeability properties of ternary blended concrete were identified by experimental studies which were: (1) percentage of cement; (2) content of rice husk ash; (3) percentage of 15 nm of $SiO_2$ particles; (4) content of NS particles with average size of 80 nm; (5) effect of curing medium and (6) curing time. The mentioned significant factors were then used to define the domain of a neural network which was trained based on the Levenberg-Marquardt back propagation algorithm using Matlab software. Excellent agreement was observed between simulation and laboratory data. It is believed that the novel developed NNM with three outputs will be a useful tool in the study of the permeability properties of ternary blended concrete and its maintenance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12B
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• pp.1359-1370
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• 2009

In wireless sensor networks, data dissemination is based on data-centric routing that well matches the publish/subscribe communication paradigm. The publish/subscribe paradigm requires decoupling properties: space, time, and synchronization decoupling. For large-scale applications, the three decoupling properties provide scalability and robust communication. However, existing data dissemination schemes for wireless sensor networks do not achieve full decoupling. Therefore, we propose a novel data dissemination scheme that fully accomplishes the three decoupling, called ARBIETER. ARBITER constructs an independent network structure as a logical software bus. Information interworking between publishers and subscribers is indirectly and asynchronously performed via the network structure. ARBITER also manages storage and mapping of queries and data on the structure because of supporting different time connection of publishers and subscribers. Our simulation proves ARBITER show better performance in terms of scalability, network robustness, data responsibility, mobility support, and energy efficiency.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.5
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• pp.941-950
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• 2001

In this paper, we present the integrated network architecture for supporting mobile IP in third generation mobile communication networks, and propose the end-to-end QoS control mechanisms of DiffServ and QoS control functions of each network element in the proposed network. First, the QoS supporting schemes of IMT-2000 are described. Second, the necessities of integrating the networks are discussed and the integrated architecture are proposed. Third, the mapping between wireless channels and DiffServ classes are presented. Finally, the end-to-end QoS control mechanisms are proposed. We also analyze the link level protocols with QoS provisioning for mobile multimedia assuming that the system support voice and data traffic simultaneously. In case of data traffic, the delay and throughput of SREJ ARQ and Type-1 Hybrid ARQ scheme are compared, and In case of voice traffic, the packet loss rate of BCH coding is analyzed according to the varying data traffic loads. The results indicate that the adaptive link level protocols are efficient to meet the QoS requirements while the complexities are increased.

• Journal of Broadcast Engineering
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• v.13 no.4
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• pp.440-451
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• 2008

With the advent of IP-based multimedia service based on IP network, there is a rapidly increasing demand for IPTV. Unlike the previous coaxial cable based TV, IPTV provides a variety of convergence services based on IP newark. However, since the IPTV service quality is a lot affected by the network degradation such as packet loss and jitter, it may not be guaranteed. In this paper, we propose an objective measure for various degradations of IPTV-based videos considering subjective assessment. To this end, we first determine QoE(Quality of Experience) indicators, which can affect human visual perception. Then we develop the video quality metric for each QoE indicator. Subjective assessment based on MOS is conducted and used to construct mapping relationship between each measure and perceived visual quality. Experiments are performed on various videos to confirm the efficiency and robustness of the proposed method and show high correlation with subjective assessment.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.3
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• pp.1-13
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• 2010

The aim of this study is to analyze gold-silver mineral potential in the Taebaeksan mineralized district, Korea using a Geographic Information System(GIS) and an artificial neural network(ANN) model. A spatial database considering Au and Ag deposit, geology, fault structure and geochemical data of As, Cu, Mo, Ni, Pb and Zn was constructed for the study area using the GIS. The 46 Au and Ag mineral deposits were randomly divided into a training set to analyze mineral potential using ANN and a test set to verify mineral potential map. In the ANN model, training sets for areas with mineral deposits and without them were selected randomly from the lower 10% areas of the mineral potential index derived from existing mineral deposits using likelihood ratio. To support the reliability of the Au-Ag mineral potential map, some of rock samples were selected in the upper 5% areas of the mineral potential index without known deposits and analyzed for Au, Ag, As, Cu, Pb and Zn. As the result, No. 4 of sample exhibited more enrichments of all elements than the others.