• Journal of IKEEE
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• v.25 no.4
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• pp.766-769
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• 2021

In order to perform tasks such as design, control, optimization, and prediction of flight vehicle trajectories based on machine learning techniques including deep learning, a certain amount of flight vehicle trajectory data is required. However, there are cases in which it is difficult to secure more than a certain amount of flight vehicle trajectory data for various reasons. In such cases, synthetic data generation could be one way to make machine learning possible. In this paper, to explore this possibility, we generated and evaluated synthetic flight vehicle trajectory data using time-series generative adversarial neural network. In addition, various ablation studies (comparative experiments) were performed to explore the possibility of using synthetic data in the aircraft trajectory prediction task. The experimental results presented in this paper are expected to be of practical help to researchers who want to conduct research on the possibility of using synthetic data in the generation of synthetic flight vehicle trajectory data and the work related to flight vehicle trajectories.

• Journal of the military operations research society of Korea
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• v.28 no.2
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• pp.85-94
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• 2002

Calculation of proper expenses on acquisition and purchasing defense product is matter of survival and weighing the morality for both defense industry and the national facilities. With this reason, both parties have been a big job to estimate the resonable cost. The cost are composed of many subordinated parts such as material cost, labor cost, and so on. In the compositions of that cost, the most important part in between companies and the government throughout the whole calculating process is to define the proper labor cost. When both parties calculate imported articles or overhead expenses, they can easily calculate and confirm by documented evidences or related materials. In other hand, the labor cost, which can be seen as two absolutely different numbers and opinions can be created, depends on analyzer's point of view. These interpretation and judgment of data cannot avoid analyzer's intention. In accordance with the above matters, defining the reasonable labor cost will be the top priority in order to analyze the proper expenses. This study will provide a method of proper labor cost estimation before starting the actual manufacturing to calculate the rational labor cost.

• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.216-226
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• 2019

The purpose of this study was to provide basic data for developing strategic programs based on broadcasting of civil defense exercise in nation focused on fire-fighting officers. 33 Q-population (concourse) was selected based on the media related literature review described above, and interviews targeting the general public. As the next step representative statements were chosen randomly and reduced in number to a final 25 statement samples for the purposes of this study. The methodology of a Q-study does not infer the characteristics of the population sample from the sample, selecting of the P-sample is likewise not governed probabilistic sampling methods. Finally, in this research, 41 people were selected as the P-sample.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.4
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• pp.60-67
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• 2012

Most of a driving cycle is used to measure fuel consumption (FC) and emissions for a specified vehicle. A driving cycle was reflected geography and traffic characteristics for each country, also, driving pattern is affected these parameters such as vehicle dynamics, FC and emissions. Therefore, this study is an attempt to develop a driving cycle for military operational area. The proposed methodology the driving cycle using micro-trips extracted from real-world data. The methodology is that the driving cycle is constructed considering important parameters to be affected FC. Therefore, this approach is expected to be a better representation of heterogeneous traffic behavior. The driving cycle for the military operational area is constructed using the proposed methodology and is compared with real-world driving data. The running time and total distance of the final cycle is 1461 s, 13.10 km. The average velocity is 32.25 km/h and average grade is 0.43%. The Fuel economy in the final cycle is 5.93 km/l, as opposed to 6.10 km/l for real-world driving. There were about 3% differences in driving pattern between the final driving cycle and real-world driving.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.4 s.346
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• pp.58-66
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• 2006

This paper proposes an FSS(Frequency Selective Surface) design system that automatically derives design parameters minimally specified by engineers. The proposed system derives optimal design parameters through theory of electromagnetic scattering on FSS, database implemented from real data obtained from practically manufactured FSS, and GA(Genetic Algorithm) for optimizing design parameters. The system, at the first step, searches the best matching FSS within preconstructed DB with given characteristics specified by operators, and then sets initial genes from the searched FSS parameters. GA iterates the optimization process until the system finds the FSS design parameters that matches the characteristics specified by operators. The theory for the electromagnetic scattering on FSS is verified by comparing the simulation results with real data obtained by measuring system composed of horn antenna and receiver. The process for manufacturing the FSS is also included in the paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1499-1513
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• 2014

This paper proposes a novel blind image watermarking scheme exploiting Block Truncation Coding (BTC). Most of existing BTC-based watermarking or data hiding methods embed information in BTC compressed images by modifying the BTC encoding stage or BTC-compressed data, resulting in watermarked images with bad quality. Other than existing BTC-based watermarking schemes, our scheme does not really perform the BTC compression on images during the embedding process but uses the parity of BTC quantization data to guide the watermark embedding and extraction processes. In our scheme, we use a binary image as the original watermark. During the embedding process, the original cover image is first partitioned into non-overlapping $4{\times}4$ blocks. Then, BTC is performed on each block to obtain its BTC quantized high mean and low mean. According to the parity of high mean and the parity of low mean, two watermark bits are embedded in each block by modifying the pixel values in the block to make sure that the parity of high mean and the parity of low mean in the modified block are equal to the two watermark bits. During the extraction process, BTC is first performed on each block to obtain its high mean and low mean. By checking the parity of high mean and the parity of low mean, we can extract the two watermark bits in each block. The experimental results show that the proposed watermarking method is fragile to most image processing operations and various kinds of attacks while preserving the invisibility very well, thus the proposed scheme can be used for image authentication.

• Journal of Industrial Convergence
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• v.16 no.4
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• pp.27-32
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• 2018

In this research, in order to prevent the fire of multiple users who are concerned about many human life damage, based on the statistical data of the National Fire Protection Agency's National Fire Information Center and the Fire Defense Administration Fire Defense Administration, Attempts were made on the exploratory approach to measures that can reduce the topic of. In this research, using the preventive firefighting administrative statistics of the Fire and Disaster Management Agency, we analyzed by focusing on the effectiveness of multiple users' firefighting safety education. Through analysis results we could infer that fire safety education does not have effectiveness in actual fire prevention. Through previous research, we found out that the cause is insufficient for the management of fire safety education, thereby deriving an improvement plan to develop a systematic fire safety education system.

• Journal of Internet Computing and Services
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• v.17 no.1
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• pp.15-21
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• 2016

Under the flag of creative economy, Korea government is now releasing public data in order to develop or provide a range of services. In this paper, we develop a customized trip navigation system to recommend a trip itinerary based on integration of open government data and personal tourist data. The system uses case-based reasoning (CBR) to provide a personalized trip navigation service. The main difference between existing trip information systems and ours is that our system can offers a user-oriented information service. In addition, our system supports Turn-key style contents provision to maximize convenience. Our system can be a good example of the way in which open government data can be used to design a new service.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.9
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• pp.65-72
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• 2011

A binary integration is one of sub-optimal pulse integration which decides detection based on discriminating m successful detections out of n trials in radar systems using multiple pulse repetition frequencies. This paper introduces target measurement error reduction technique to reduce azimuth errors in suboptimal binary integration radar which applies the near value by m rather than the optimal m and verifies the performance by analyzing the experimental data measured from real radar.

• Journal of Communications and Networks
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• v.14 no.4
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• pp.451-460
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• 2012

Natural disasters often lead to regional failures that can cause network nodes and links co-located in a large geographical area to fail. Novel approaches are required to assess the network vulnerability under such regional failures. In this paper, we investigate the vulnerability of networks by considering the geometric properties of regional failures and network nodes. To evaluate the criticality of node locations and determine the critical areas in a network, we propose the concept of ${\alpha}$-critical-distance with a given failure impact ratio ${\alpha}$, and we formulate two optimization problems based on the concept. By analyzing the geometric properties of the problems, we show that although finding critical nodes or links in a pure graph is a NP-complete problem, the problem of finding critical areas has polynomial time complexity. We propose two algorithms to deal with these problems and analyze their time complexities. Using real city-level Internet topology data, we conducted experiments to compute the ${\alpha}$-critical-distances for different networks. The computational results demonstrate the differences in vulnerability of different networks. The results also indicate that the critical area of a network can be estimated by limiting failure centers on the locations of network nodes. Additionally, we find that with the same impact ratio ${\alpha}$, the topologies examined have larger ${\alpha}$-critical-distances when the network performance is measured using the giant component size instead of the other two metrics. Similar results are obtained when the network performance is measured using the average two terminal reliability and the network efficiency, although computation of the former entails less time complexity than that of the latter.