• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1443-1445
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• 2016

In this paper, we propose a exclusive-OR TCP coding technic imply with TCP Hybla on split PEP for enhancing the file transfer speed of the satellite communication. To evaluate performance of the proposed method, we set up a test-bed of satellite communication network. As a result of the performance evaluation, the file transmission speed enhanced more than 12% within high packet loss range. Therefore, we can expect that the proposed methodology could contribute to enhancing of data transmission speed in the satellite communication.

• Health Policy and Management
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• v.23 no.1
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• pp.44-51
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• 2013

Background: This study designed to evaluate the homogeneity of Korean diagnosis related group (KDRG) version 3.4 classification system. Methods: The total 5,921,873 claims data submitted to the Health Insurance Review and Assessment Service during 2010 were used. Both coefficient of variation (CV) and reduction in variance of cost were measured for evaluation. This analysis was divided into before and after trimming outliers at the level of adjacent DRG (ADRG), aged ADRG (AADRG) split by age, and DRG split by complication and comorbidity. Results: At the each three level of ADRG, AADRG, and DRG, there were 38.9%, 38.7%, and 30.0% of which had a CV > 100% in the untrimmed data and there were 1.4%, 1.4%, and 1.9% in the trimmed one. Before trimming outliers, ADRGs explained 52.5% of the variability in resource use, AADRGs did 53.1% and DRGs did 57.1%. The additional explanatory power by age and comorbidity and complication (CC) split were 0.6%p and 4.6%p for each, which were statistically significant. After trimming outliers, ADRGs explained 75.2% of the variability in resource use, AADRGs did 75.6%, and DRGs did 77.1%. The additional explanatory power were 0.4%p and 2.0%p for each, which were statistically significant too. Conclusion: The results demonstrated that KDRG showed high homogeneity within groups and performance after trimming outliers. But there were DRGs CV > 100% after age or CC split and the most contributing factor to high performance of KDRG was the ADRG rather than age or CC split. Therefore, it is recommended that the efforts for improving clinical homogeneity of KDRG such as review of the hierarchical structure of classification systems and classification variables.

• Fashion & Textile Research Journal
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• v.12 no.4
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• pp.467-476
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• 2010

The purpose of this study was to develop a plausible methodology based on experimental data how to set up darts and split lines on 3D parametric body dressed with tight-fit garment. The results were as following: Through the process of making convex hull, the concave parts were straightened to make a convex hull, especially in the center part of bust, under breast part and scapular part. To figure out the optimum positions of darts and split lines, the inflection points of curve ratio were searched along the horizontal polylines of waist and bust. This procedures produced reliable results with low deviation. Using Rapidform, CATIA and Unigraphics, six patches of bodice patterns were drawn and aligned. Paired t-test results showed the outline and area between 3D surface and 2D were not significantly different, meaning this method could be adaptable when flattening 3D surfaces. The amount of waist dart measured on the pattern showed that the highest portion was allocated on 2nd dart(back), followed by 1st dart(back), 1st dart(front), 2nd dart(front)/side dart, and center back dart. A series of findings suggested that curve ration inflection point could be used as a guide to set up darts and split line on 3D parametric model with low deviation.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1259-1265
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• 2004

In many applications, producing labeled data is costly and time consuming while an enormous amount of unlabeled data is available with little cost. Therefore, it is natural to ask whether we can take advantage of these unlabeled data in classification teaming. In machine learning literature, the co-training method has been widely used for this purpose. However, the current co-training method requires the entire features to be split into two independent sets. Therefore, in this paper, we improved the current co-training method in a number of ways, and proposed a new co-training method which do not need the feature split. Experimental results show that our proposed method can significantly improve the performance of the current co-training algorithm.

• Convergence Security Journal
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• v.21 no.3
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• pp.49-56
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• 2021

Recently, artificial intelligence is regarded as an essential technology in our society. In particular, the invasion of privacy in artificial intelligence has become a serious problem in modern society. Split learning, proposed at MIT in 2019 for privacy protection, is a type of federated learning technique that does not share any raw data. In this study, we studied a safe and accurate segmentation learning model using known differential privacy to safely manage data. In addition, we trained SVHN and GTSRB on a split learning model to which 15 different types of differential privacy are applied, and checked whether the learning is stable. By conducting a learning data extraction attack, a differential privacy budget that prevents attacks is quantitatively derived through MSE.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.5
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• pp.23-36
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• 2004

This paper presents a password based authentication and key exchange protocol which can be used for both authenticating users and exchanging session keys for a subsequent secure communication over an untrusted network. Our idea is to increase a randomness of the password verification data, i.e., we split the password, and then amplify the split passwords in the high entropy-structured password verification data. And in order to prevent the verifier-compromised attack, we construct our system such that the password verification data is encrypted with the verifier's key and the private key of verifier used to encrypt it is stored in a secure place like a smart cards. Also we propose the distributed password authentication scheme utilizing many authentication servers in order to prevent the server-compromised attack occurred when only one server is used. Furthermore, the security analysis on the proposed protocol has been presented as a conclusion.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.517-525
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• 2022

In the era of big data, various data mining techniques have been proposed as major analysis methodologies. As complex and diverse data is mass-produced, data mining techniques have attracted attention as a method that forms the foundation of data science. In this paper, we focused on the decision tree, which is frequently used in practice and easy to understand as one of representative data mining methods. Specifically, we analyzed the effect of the splitting method of decision trees on the model performance. We compared the prediction power and structures of decision tree models with different split methods based on various simulated data. The results show that the linear combination split method can improve the prediction accuracy of decision trees in the case of data simulated from nonlinear models with complex structure.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.2 s.314
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• pp.39-45
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• 2007

This paper presents a novel scheme that quickly searches for the sweet spot of multiple array antennas, and locks on to it for high-speed millimeter wavelength transmissions, when communications to another antenna array are disconnected. The proposed method utilizes a modified genetic algorithm, which selects a superior initial group through preprocessing in order to solve the local solution in agenetic algorithm. TDD (Time Division Duplex) is utilized as the transfer method and data controller for the antenna. Once the initial communication is completed for the specific number of individuals, no longer antenna's data will be transmitted until each station processes GA in order to produce the next generation. After reproduction, individuals of the next generation become the data, and communication between each station is made again. Simulation results of 1:1, 1:2, 1:5 array antennas confirmed the efficiency of the proposed method. The 16bit split is 8bit, but it has similar performance as 16bit gene.

• Korean Journal of Remote Sensing
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• v.14 no.1
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• pp.53-68
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• 1998

Observation of hydrometeors' behavior in the atmosphere is important to understand weather and climate. By conventional observations, we can get the distribution of water vapor at limited number of points on the earth. In this study, the precipitable water has been estimated from the split window channel data on GMS-5 based upon the technique developed by Chesters et al.(1983). To retrieve the precipitable water, water vapor absorption parameter depending on filter function of sensor has been derived using the regression analysis between the split window channel data and the radiosonde data observed at Osan, Pohang, Kwangiu and Cheju staions for 4 months. The air temperature of 700 hPa from the Global Spectral Model of Korea Meteorological Administration (GSM/KMA) has been used as mean air temperature for single layer radiation model. The retrieved precipitable water for the period from August 1996 through December 1996 are compared to radiosonde data. It is shown that the root mean square differences between radiosonde observations and the GMS-5 retrievals range from 0.65 g/$cm^2$ to 1.09 g/$cm^2$ with correlation coefficient of 0.46 on hourly basis. The monthly distribution of precipitable water from GMS-5 shows almost good representation in large scale. Precipitable water is produced 4 times a day at Korea Meteorological Administration in the form of grid point data with 0.5 degree lat./lon. resolution. The data can be used in the objective analysis for numerical weather prediction and to increase the accuracy of humidity analysis especially under clear sky condition. And also, the data is a useful complement to existing data set for climatological research. But it is necessary to get higher correlation between radiosonde observations and the GMS-5 retrievals for operational applications.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.518-521
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• 2007

To retrieve Sea Surface Temperature(SST) from NOAA-AVHRR imagery the spilt window atmospheric correction algorithm is generally used. Recently, there have been various new algorithms developed to process these data, namely the variable-coefficient split-window, the R54 transmittance-ratio method, fixed-coefficient nonlinear algorithm, dynamic water vapour (DWV) correction method, Dynamic Water Vapour and Temperature algorithm (DWVT). We used MCSST (Multi-Channel Sea surface temperature) and NLSST(Non linear sea surface temperature) algorithms in this study. The study area is around the Korea sea area (Yellow Sea). We compared and analyzed with various methods by applying each Ocean in-situ data and satellite data. The primary aim of study is to verify and optimize algorithms. Finally, this study proposes an optimized algorithm for SST retrieval.