• Journal of Positioning, Navigation, and Timing
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• v.4 no.2
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• pp.79-85
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• 2015

Existing Differential GPS (DGPS) pseudorange correction (PRC) generation techniques based on a virtual reference station cannot effectively assign a weighting factor if the baseline distance between a user and a reference station is not long enough. In this study, a virtual reference station DGPS PRC generation technique was developed based on an enhanced inverse distance weighting method using an exponential function that can maximize a small baseline distance difference due to the dense arrangement of DGPS reference stations in South Korea, and its positioning performance was validated. For the performance verification, the performance of the model developed in this study (EIDW) was compared with those of typical inverse distance weighting (IDW), first- and second-order multiple linear regression analyses (Planar 1 and 2), the model of Abousalem (1996) (Ab_EXP), and the model of Kim (2013) (Kim_EXP). The model developed in the present study had a horizontal accuracy of 53 cm, and the positioning based on the second-order multiple linear regression analysis that showed the highest positioning accuracy among the existing models had a horizontal accuracy of 51 cm, indicating that they have similar levels of performance. Also, when positioning was performed using five reference stations, the horizontal accuracy of the developed model improved by 8 ~ 42% compared to those of the existing models. In particular, the bias was improved by up to 27 cm.

• Journal of the Korea Society for Simulation
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• v.28 no.4
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• pp.33-43
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• 2019

Link-16 is a data link that provides joint interoperability to the US Navy, Air Force and NATO. Currently, the military relies entirely on foreign SW and tools for test environment, tactical simulation training and interoperability verification test for Link-16 operation. Therefore, it is necessary to develop Link-16 based operation environment test tool. In this paper, Link-16 network operational performance analysis simulator was developed by analyzing the function of Link-16 foreign tools. It also implements the SIMPLE standard interface for interworking with foreign SW and tools. The functional model for Link-16 network operation performance analysis consists of pre-analysis, real-time operational analysis, and post-analysis functional model. Each functional model test was performed through SIMPLE interworking with foreign SW and tools. Link-16 network operation performance analysis If we replace foreign SW through simulator, we can perform tactical training, network design verification and operation (scenario) verification for our military.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1796-1807
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• 2017

The domestic warship propulsion system is at the stage of a hybrid propulsion system changing from a mechanical propulsion system and the propulsion system becomes complicated so it is expected that the function of ECS(Engineering Control System) that controls and monitors the warship propulsion system becomes important. Recently the development of ECS has progressed domestically, so that verification of reliability and stability is required in the process of ECS development. The simulator to be proposed is composed of HILS, it can be divided into a shaft-line dynamics model of the simulating power transmission, a controller model of the simulating the control of the equipment, and a communication model communicating with the ECS. In this paper, we developed simulator for ECS verification for CODLOG hybrid propulsion system, set scenario, and conducted simulation.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.3
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• pp.57-67
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• 2018

The ensemble is a unified approach used for getting better performance by using multiple algorithms in machine learning. In this paper, we introduce boosting and bagging, which have been widely used in ensemble techniques, and design a method using support vector regression, radial basis function network, Gaussian process, and multilayer perceptron. In addition, our experiment was performed by adding a recurrent neural network and MOHID numerical model. The drifter data used for our experimental verification consist of 683 observations in seven regions. The performance of our ensemble technique is verified by comparison with four algorithms each. As verification, mean absolute error was adapted. The presented methods are based on ensemble models using bagging, boosting, and machine learning. The error rate was calculated by assigning the equal weight value and different weight value to each unit model in ensemble. The ensemble model using machine learning showed 61.7% improvement compared to the average of four machine learning technique.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.7 s.349
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• pp.20-28
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• 2006

A new TWA(Traveling-wave-based Waveform Approximation)-based signal integrity verification method for practical interconnect layout structures which are composed of non-uniform RLC lines with various discontinuities is presented. Transforming the non-uniform lines into virtual uniform lines, signal integrity of the practical layout structures can be very efficiently estimated by using the TWA-technique. It is shown that the proposed technique can estimate the signal integrity much more efficiently than generic SPICE circuit model with 5% timing error and 10% crosstalk error.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.147-153
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• 2018

In this paper, we propose an efficient WBC 14-Diff classification which performs using the WBC-ResNet-152, a type of CNN model. The main point of view is to use Super-pixel for the segmentation of the image of WBC, and to use ResNet for the classification of WBC. A total of 136,164 blood image samples (224x224) were grouped for image segmentation, training, training verification, and final test performance analysis. Image segmentation using super-pixels have different number of images for each classes, so weighted average was applied and therefore image segmentation error was low at 7.23%. Using the training data-set for training 50 times, and using soft-max classifier, TPR average of 80.3% for the training set of 8,827 images was achieved. Based on this, using verification data-set of 21,437 images, 14-Diff classification TPR average of normal WBCs were at 93.4% and TPR average of abnormal WBCs were at 83.3%. The result and methodology of this research demonstrates the usefulness of artificial intelligence technology in the blood cell image classification field. WBC-ResNet-152 based morphology approach is shown to be meaningful and worthwhile method. And based on stored medical data, in-depth diagnosis and early detection of curable diseases is expected to improve the quality of treatment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.3
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• pp.563-577
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• 2018

In order to support secure communication in VANET(Vehicular Ad hoc Network), messages exchanged between vehicles or between vehicle and infrastructure must be authenticated. In this paper, we propose a hierarchical anonymous authentication system for VANET. The proposed system model reduces the overhead of PKG, which is a problem of previous system, by generating private keys hierarchically, thereby enhancing practicality. We also propose a two-level hierarchical identity-based signature(TLHIBS) scheme without pairings so that improve efficiency. The proposed scheme protects the privacy of the vehicle by satisfying conditional privacy and supports batch verification so that efficiently verifies multiple signatures. Finally, The security of the proposed scheme is proved in the random oracle model by reducing the discrete logarithm problem(DLP) whereas the security proof of the previous ID-based signatures for VANET was incomplete.

• Journal of Distribution Science
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• v.14 no.9
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• pp.133-147
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• 2016

Purpose - The Purpose of this study is to observe the value of LOHAS as an exhibition that is perceived to be a specialized local exhibition with good fame and differentiated advantage as well as the spectators' will to visit the exhibition coming from the future behavior intention of visitors. Research design, data, and methodology - In order to achieve the purpose of this study, This study organized questionnaire after setting a hypothesis based on the theoretical background from the parameters. verification of the hypothesis by statistically analyzing the answers for questionnaire follows. Finally, the implication of this study is drawn through comprehensive discussion while This study indicated from the limits of the study and future direction for research. This study set up a model to research the influence on the structuring factors in LOHAS exhibition in forming perceived value, customer satisfaction and future behavior intention. Frequency analysis was used for getting demographic characteristics, verification of plausibility, reliability of measured parameters and factors analysis. This study have performed verification of difference at selection property level based on multiple regression analysis and demographic nature. Results - To summarize the study result, through the verification of hypothesis about meaningful influence among structuring factors in LOHAS exhibition, perceived value and customer satisfaction shows some noticeable points to focus on. That is, it is established things that partial adoption and meaning relationship of partial influence. The perceived value affected both customer satisfaction and future behavior intention meaningfully. Conclusions - This study could note that in the structuring factors of LOHAS exhibition, perceived value for visitors and customer satisfaction play their roles positively on the future behavior intention. In conclusion, this study implies that strategic measures are necessary to fulfill the structuring factors of LOHAS exhibition as they would make positive impact on acknowledged value, customer satisfaction and future behavior intention to contribute to the growth and development of LOHAS exhibition. Also it suggests that the method to join each other with activities is necessary to strengthen the properties of the exhibition and position well to be a solid local exhibition.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.8
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• pp.271-276
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• 2014

This study analyzed that N/A check items affect the results of the security level degree, when performing vulnerability analysis evaluation. For this, we were used vulnerability analysis evaluation range, check items and quantitative calculation method. Furthermore, were applied grade and weight for the importance of the items. In addition, because technology develop rapidly, the institution is always exposed risk. therefore, this study was carried out empirical analysis by applying RAL(Risk Acceptabel Level). According to the analyzed result N/A check items factors affecting the level of security has been proven. In other words, this study found that we shall exclude inspection items irrelevant to the institution characteristics, when perform vulnerability analysis evaluation. In this study suggested that security level evaluation shall performed, after that exclude items irrelevant to the institution characteristics based on empirical verification. And also, it proposed that model research is required for establish check items for which analysis-evaluate vulnerability based on empirical verification.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.117-136
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• 2019

In this study, a hybrid-type of day fog detection algorithm (DFDA) was developed based on the optical and textural characteristics of fog top, using the Himawari-8 /Advanced Himawari Imager data. Supplementary data, such as temperatures of numerical weather prediction model and sea surface temperatures of operational sea surface temperature and sea ice analysis, were used for fog detection. And 10 minutes data from visibility meter from the Korea Meteorological Administration were used for a quantitative verification of the fog detection results. Normalized albedo of fog top was utilized to distinguish between fog and other objects such as clouds, land, and oceans. The normalized local standard deviation of the fog surface and temperature difference between fog top and air temperature were also assessed to separate the fog from low cloud. Initial threshold values (ITVs) for the fog detection elements were selected using hat-shaped threshold values through frequency distribution analysis of fog cases.And the ITVs were optimized through the iteration method in terms of maximization of POD and minimization of FAR. The visual inspection and a quantitative verification using a visibility meter showed that the DFDA successfully detected a wide range of fog. The quantitative verification in both training and verification cases, the average POD (FAR) was 0.75 (0.41) and 0.74 (0.46), respectively. However, sophistication of the threshold values of the detection elements, as well as utilization of other channel data are necessary as the fog detection levels vary for different fog cases(POD: 0.65-0.87, FAR: 0.30-0.53).