• Journal of Information Technology Services
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• v.10 no.1
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• pp.105-116
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• 2011

With recent spotlight on the, uniquitous computing technology, the need for object of indentification and location infrastructure has increased. Such GPS technolgy must utilize IEEE 802.15.4 Zigbee used for existing wireless sensor network infra as a basice element for user's context-awareness in a uniquitous environement, for effectiveness.Such real-time GPS service is provided in the internal environment where the user would actually are and most high-rise buildlings apply. Underthe assumption, the real-time GPS technology is seperated by each floor, and signals do not get transmitted to other floors, the application on one floor within the high-rise buildling was conducted. This study intends to suggest a floor detection algorithm using IEE 802.15.3/Zigbee's RSSI which supports the accuracy within a couple of meters for the user's the movement between the floors in high-rise buildings in a complex environment. It proposes an floor detection algorithm using IEEE 802.15.4/Zigbee's RSSI which provides accuracy within a radius of few meters for the users movement between the floors for real-time location tracking within high-rise building in a cmoplex environment. Furthermore, for more accurate real-time location tracking, it suggests an algorithm for real-time location tracking using IEEE 802.15.4a/Zigbee's CSS technology based on triangulation. Based on the suggested algorithm, it designs a hybrid real-time location tracking service system in a high-rise buildling and test its functions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1531-1539
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• 2017

The existing SSD storage tester processed logs in a 1-N structure between server and client using TCP and network file system. This method causes some problems for example, an increase in CPU usage and difficulty in exception handling, etc. In this paper, we implement a log processing message layer that can deal with asynchronous distributed processing using open source messaging system such as kafka, RabbitMQ and compare this layer with existing log transmission method. A log simulator was implemented to compare the transmission bandwidth and CPU usage. Test results show that the transmission using the message layer has higher performance than the transmission using the message layer, and the CPU usage does not show any significant difference The message layer can be implemented more easily than the conventional method and the efficiency is higher than that of the conventional method.

• The Transactions of the Korea Information Processing Society
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• v.4 no.11
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• pp.2662-2670
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• 1997

High speed network makes possible to transfer not only the test data but also multimedia data such as audio, image, and moving pictures and etc. In a multimedia applications, as a multimedia storage system, it is necessary to use a disk array to store and retrieve data by real time. It is important feature to various disk array parameters as a storage system on a real VOD system, such as configuration method of each disks and allocation method of multimedia data. In this paper, various parameters for the disk array are decided to be used for the video-on-demand system application by simulations in two ways. The real and simulation measurement are compared and analyzed on the performance. Simulation results shows that RAID level 5 and 256KB as striping unit and 185KB as data requests size per seconds are suitable parameter for the disk array architecture which provides MPEG-1 files with a rate of 1.5Mbps in two measurements of real and simulation.

• KEPCO Journal on Electric Power and Energy
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• v.5 no.3
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• pp.157-163
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• 2019

K-BEMS System was introduced to reduce peak load and to save total energy of the 120 buildings that KEPCO headquarter and branch offices use. K-BEMS system is composed of PV, battery, and hybrid PCS. In this system, ESS, PV, lighting is used to save building energy based on demand prediction. Currently, neural network technique for short past data is applied to demand prediction, and fixed scheduling method by operator for ESS charging/discharging is used. To enhance this system, KEPCO research institute has carried out this K-BEMS research project for 3 years since January 2016. As the result of this project, we developed new real-time highly reliable building demand prediction technique with error free and optimized automatic ESS charging/discharging technique. Through several field test, we can certify the developed algorithm performance successfully. So we will describe the details in this paper.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.363-367
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• 2009

From the recent, an big issue of the internet attack is DDoS(Distributed Denial of Service). Some government agencies and companies will buy Anti-DDoS SW for protect their their network system form DDoS attack. But We don't have any objective valuation standard of Anti-DDoS SW. So When you try to buy an Anti-DDoS SW, you can get only subjective Anti-DDoS SW information which from Anti-DDoS SW vender. Anti-DDoS SW market is getting bigger, so market needs objective valuation standard of Anti-DDoS SW for a fair evaluation. In this paper, we describe a part of Anti-DDoS SW performance tests in valuation standard of Anti-DDoS SW.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.86-89
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• 2009

In this paper, a broadband power line communication modem and network technology to develop tests with actual characteristics of the underground power line communication channel to be interpreted. Length and structure of the underground distribution line due to underground distribution line to the broadband powerline communication channels to measure the amount of attenuation on the signal generator, spectrum analyzer, such as contactless coupler was used to configure the channel measurement system. Demonstration tests in the test line as a single line by selecting the longest high-voltage lines where the two-channel measurement and signal attenuation on the noise level was measured. Measuring results degrade communication performance can be quite sure that was the presence of impulse noise, long lines, the line length was confirmed by the high-frequency attenuation appears.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.11
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• pp.251-262
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• 2019

In this paper, we propose a simulator that provides various algorithms of RBF networks on neuromorphic chips. To develop algorithms based on neuromorphic chips, the disadvantages of using simulators are that it is difficult to test various types of algorithms, although time is fast. This proposed simulator can simulate four times more types of network architecture than existing simulators, and it provides an additional a two-layer structure algorithm in particular, unlike RBF networks provided by existing simulators. This two-layer architecture algorithm is configured to be utilized for multiple input data and compared to the existing RBF for performance analysis and validation of utilization. The analysis showed that the two-layer structure algorithm was more accurate than the existing RBF networks.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.65-74
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• 2021

Recently, studies on Korean spelling correction have been actively conducted based on machine translation and automatic noise generation. These methods generate noise and use as train and data set. This has limitation in that it is difficult to accurately measure performance because it is unlikely that noise other than the noise used for learning is included in the test set In addition, there is no practical error type standard, so the type of error used in each study is different, making qualitative analysis difficult. This paper proposes new 'error type classification' for deep learning-based Korean spelling correction research, and error analysis perform on existing commercialized Korean spelling correctors (System A, B, C). As a result of analysis, it was found the three correction systems did not perform well in correcting other error types presented in this paper other than spacing, and hardly recognized errors in word order or tense.

• Journal of Advanced Navigation Technology
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• v.25 no.5
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• pp.390-396
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• 2021

In this research, design and fabrication of marine repeater capable to extend communication coverage in monitoring system of fishing gear automatic identification, which is one of implementation method of the real-name electric fishing gear system declared by Ministry of Oceans and Fisheries in 2016, is reported. The proposed marine repeater is fabricated in a form of RF repeater with interference cancellation system (ICS), which can cancel the oscillation due to feedback signal between service antenna and link antenna. In design process, we secure the isolation of 30 dB between service antenna and link antenna. It is confirmed that when the level of feedback signal into repeater input be lower of 15 dB than repeater gain, error vector magnitude due to oscillation can be lower than the performance criterion of 6%, from the test verification. It is expected that the service coverage will be extended by applying the developed marine ICS RF repeater into marine IoT network including monitoring system of fishing gear automatic identification.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.71-78
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• 2019

This study aims to identify good borrowers within the context of P2P lending. P2P lending is a growing platform that allows individuals to lend and borrow money from each other. Inherent in any loans is credit risk of borrowers and needs to be considered before any lending. Specifically in the context of P2P lending, traditional models fall short and thus this study aimed to rectify this as well as explore the problem of class imbalances seen within credit risk data sets. This study implemented an over-sampling technique known as Synthetic Minority Over-sampling Technique (SMOTE). To test our approach, we implemented five benchmarking classifiers such as support vector machines, logistic regression, k-nearest neighbor, random forest, and deep neural network. The data sample used was retrieved from the publicly available LendingClub dataset. The proposed SMOTE revealed significantly improved results in comparison with the benchmarking classifiers. These results should help actors engaged within P2P lending to make better informed decisions when selecting potential borrowers eliminating the higher risks present in P2P lending.