• Convergence Security Journal
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• v.11 no.3
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• pp.11-17
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• 2011

The acquisition of weapons systems test and evaluation in the early stages of the acquisition process as a source of data used for modeling and simulation are being actively encouraged. Thus, in the reliability of weapon systems acquisition can be called the most important part, and M&S to apply for this test reliability and accuracy of the assessment can provide, test time and cost savings, the pre-and post-test predictions and available data can provide. In this study, theoretical study of M&S to acquire weapon systems used for the importance of M&S, acquired the characteristics of the model, utilization for weapon systems acquisition, and weapon systems acquisition review for an effective utilization of M&S tries to find out.

• Convergence Security Journal
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• v.19 no.3
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• pp.101-107
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• 2019

Our military's cyberspace is under constant threat from the enemy. These cyber threats are targeted at the information service assets held by the military, and securing the security of the organization's information service assets is critical. However, since Information assets can not be 100% selt-sufficient in any organization as well as the military, acquisition of information assets by the supply chain is an inevitable. Therefor, after reviewing supply chain protection measures to secure the safety of the military supply chain, we proposed a method for securing supply chain companies through the citation of partnership based on the validated trust model.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.5
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• pp.889-899
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• 2021

This paper proposes a reliable data sharing scheme on the internet of vehicles (IoV) by utilizing blockchain technology for constructing a decentralized system approach. In our model, to maintain the credibility of the information messages sent by the vehicles to the system, we propose a reputation rating mechanism, in which neighboring vehicles validate every received information message. Furthermore, we incorporate an incentive mechanism based on smart contracts, so that vehicles will get certain rewards from the system when they share correct traffic information messages. We simulated the IoV network using a discrete event simulator to analyze network performance, whereas the incentive model is designed by leveraging the smart contract available in the Ethereum platform.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.603-605
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• 2023

최근 SNS 의 발달로 인해 자신의 감정을 빠르고 효과적으로 전달할 수 있는 이모지의 중요성이 커지고 있다. 하지만 이모지를 수동으로 생성하기 위해서 시간과 비용이 많이 들고 자신의 감정에 맞는 이모지를 찾아야 하며 해당 이모지가 없을 수 있다. 기존 DCGAN 을 활용한 이모지 자동 생성연구에서는 부족한 데이터셋으로 인해 G(Generator)와 D(Discriminator)가 동등하게 학습하지 못해서 두 모델 간 성능 차이가 발생한다. D 가 G 보다 최적해에 빠르게 수렴하여 G 가 학습이 되지 않아 낮은 품질의 이모지를 생성하는 불안정 문제가 발생한다. 이 문제를 해결하기 위해 본 논문에서는 Latent vector 분포를 데이터셋에 맞게 조정하여 적은 데이터로 G 에서 안정적으로 학습할 수 있게 하는 G 구조와 다양한 이모지 생성을 위한 Latent vector 평균 조정 기법을 제안한다. 비교 실험 결과 불안정 문제를 개선하였고 FID 와 IS 수치를 통해 성능 개선 효과를 검증했다.

• Smart Media Journal
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• v.10 no.4
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• pp.21-27
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• 2021

Recently, the importance of counseling is increasing due to the Corona Blue caused by COVID-19. Also, with the increase of non-face-to-face services, researches on chatbots that have changed the counseling media are being actively conducted. In non-face-to-face counseling through chatbot, it is most important to accurately understand the client's emotions. However, since there is a limit to recognizing emotions only in sentences written by the client, it is necessary to recognize the dimensional emotions embedded in the sentences for more accurate emotion recognition. Therefore, in this paper, the vector and sentence VAD (Valence, Arousal, Dominance) generated by learning the Word2Vec model after correcting the original data according to the characteristics of the data are learned using a deep learning algorithm to learn the multi-dimensional We propose an emotion recognition model. As a result of comparing three deep learning models as a method to verify the usefulness of the proposed model, R-squared showed the best performance with 0.8484 when the attention model is used.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.489-493
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• 2024

Happiness index is a measurement system for understanding collective happiness. As values change, studies have been proposed to add the value of behavior to the happiness index. However, there is a lack of studies analyze the relationship using individual emotions. Using a deep learning model, we predicted happiness index using social variables and individual emotional index. First, we collected social and emotional variables from January 2005 to December 2020. Second, we preprocessed the data and identified significant variables. Finally, we trained deep learning-based regression model. Our proposed model was evaluated using 5-fold cross validation. The proposed model showed 90.86% accuracy on test sets. Our model will be expected to analyze the significant factors of country-specific happiness index.

• Journal of the Korea Convergence Society
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• v.11 no.6
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• pp.137-144
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• 2020

As foreign tourists visiting Korea increase and Koreans traveling overseas become more frequent, a study on the level of domestic consumers' acceptance of different cultures and the perception towards products from different cultures is needed. In this study, a perceptual curiosity, which is an individual personality, was divided into Diverse perceptual curiosity and Specific perceptual curiosity, and effects of perceptual curiosity on an attitude towards different cultures and an intention to recommend products from different cultures were examined. To prove validity of measurement items and reliability of data, SPSS and LISREL were used and to prove a hypothesis, a structural equation model was used. The study results showed that the Diverse perceptual curiosity, which is Hypothesis 1, had a positive effect on the attitude towards different cultures while the Specific perceptual curiosity, which is Hypothesis 2, did not have a significant effect on the attitude towards different cultures. In addition, it was shown that the attitude towards different cultures, which is Hypothesis 3, had a significant positive effect on the intention to recommend the products from different cultures.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.150-160
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• 2020

The purpose of this study was to test the effect of socially-perfectionism on depression by mediating ambivalence over emotional expressiveness and experiential avoidance. For this purpose, 201 participants across the country conducted the survey, a measure of MPS, AEQ-K, AAQ-II, CES-D. The descriptive statistics, Pearson correlation, path coefficient were conducted using SPSS 23.0. The indirect effect was examined using bootstrap in PROCESS Macro. The results of the study are as follows. First, all the variables had meaningful positive correlations. Secondly, When socially-perfectionism affects depression, ambivalence over emotional expressiveness, and experiential avoidance were mediated. As a result, the implications and limitations of the study were discussed.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.1
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• pp.89-97
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• 2008

Chaotic behavior in motor systems is undesired dynamics in real-time implementation since the speed is oscillated in a wide range and the torque is changed by a random manner. We present an adaptive control approach for time-varying permanent-magnet synchronous motors (PMSM) with chaotic phenomenon. We consider that its parameters are changed randomly within certain bounds. First, a nonlinear system model of a PMSM is transformed to derive a nominal linear control strategy. Then, an auxiliary control for compensating real-time control error occurred by system perturbation due to parameter change is designed by using Lyapunov stability theory. Numerical simulation is accomplished for evaluating its efficiency and reliability comparing with the traditional control method. Additionally, we test our control method in real-time motor experiment including a PSoC based drive system to demonstrate its practical applicability.

• Journal of the Institute of Convergence Signal Processing
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• v.17 no.2
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• pp.77-82
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• 2016

The purpose of this paper is to develop the algorithm of human arousal inducing interface using steady-state visual evoked potential(SSVEP) and its verification through experiments. In order to develop the model, computer-based SSVEP program simulation is preliminary performed. From the results of the simulation, stimulus pattern is decided to checkerboard and SSVEP frequency range is set into beta wave (13~30Hz). After the experiment on proving the effect of SSVEP flashing stimulation while driving by installing it at the location of people mostly falling asleep in the highway, the result confirms that both during the night and the day, after SSVEP flashing stimulation, a wave Beta immediately increases and the subjects keep high stimulation for the 5 minute maintaining stage.