• Journal of the Korea Society for Simulation
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• v.32 no.1
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• pp.13-21
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• 2023

This paper proposes a method of automatically generating a model through a machine learning technique by setting a hypothetical model in the form of a gray box or black box with unknown parameters, when the big data of the actual system is given. We implements the proposed framework and conducts experiments to find an appropriate model among various hypothesis models and compares the cost and fitness of them. As a result we find that the proposed framework works well with continuous systems that could be modeled with ordinary differential equation. This technique is expected to be used well for the purpose of automatically updating the consistency of the digital twin model or predicting the output for new inputs using recently generated big data.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.2
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• pp.131-136
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• 2023

Nanocomposites have been considered innovative composite materials that have multi-functionality and high performance. Because the incorporation of nanoscale fillers may significantly improve the electrical, mechanical, and thermal properties of composites, numerous extensive studies on the characterization of nanocomposites with nanoscale fillers have been performed. In particular, the development of nanocomposites using carbon-based nanoscale fillers (e.g., carbon nanotubes, carbon black, graphene nanoplates) have attracted much interest in the composite field. This paper provides a review of recent advances in the electrical/mechanical characteristics of nanocomposites, which are essential for their practical applications. Furthermore, this paper revisits the recent research on multi-scale modeling, which is a promising approach for predicting the characteristics of nanocomposites. The current challenges and future development potentials for multi-scale modeling are also discussed.

• Composites Research
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• v.22 no.6
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• pp.1-6
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• 2009

This paper presents an experimental study on the piezoresistive behavior of nanocomposite strain sensors subjected to various loading modes and their capability to detect structural deformations and damages. The electrically conductive nanocomposites were fabricated in the form of a film using various types of thermoplastic polymers and multi-walled carbon nanotubes (MWNTs) at various loadings. In this study, the nanocomposite strain sensors were bonded to a substrate and subjected to tension, flexure, or compression. In tension and flexure, the resistivity change showed dependence on measurement direction, indicating that the sensors can be used for multi-directional strain sensing. In addition, the sensors exhibited a decreasing behavior in resistivity as the compressive load was applied, suggesting that they can be used for pressure sensing. This study demonstrates that the nanocomposite strain sensors can provide a pathway to affordable, effective, and versatile structural health monitoring.

• Journal of Industrial Convergence
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• v.20 no.2
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• pp.79-85
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• 2022

In order to promote active sales growth in the rapidly changing modern society's makeup market, it is now time to analyze makeup colors closely in line with current trends. Therefore, in this study, professional women from Gwangju Metropolitan City and Jeollanam-do were treated and analyzed with the statistical SPSS 21.0 package program for colors such as makeup base, eyebrow, lip, and cheek, and the reasons for their preference. As a result of the study, yellow makeup base, black eyebrow, red lip, and red cheek color were preferred. This study will be provided as basic data for the development of various makeup patterns and novel makeup color items, and it is believed that it will contribute directly or indirectly to increased sales while gaining an edge in the modern makeup market.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.113-118
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• 2023

Recently, as more and more cyclists ride bicycles for their health and more people commute by bicycle, the number of cyclists has increased. However, as the number of users increases, many accidents occur, and the handling of bicycle accidents is unstable. It is inadequate to prepare for accidents in other ways except for safety equipment. Therefore, there is a need for a safe and convenient way for modern adults to ride. Unlike other apps, in this study, by adding a safety function, you can shoot a black box while riding, and a function to inform you that it is an accident-prone area is implemented. In addition, a function that can detect an accident using the Android built-in sensor and automatically make emergency contact is added. Cyclists can secure safety and convenience in one app without the need to use additional apps. Furthermore it develops an app system that allows you to talk about riding and share your route through the Riding Community bulletin board.

• Elastomers and Composites
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• v.37 no.4
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• pp.217-223
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• 2002

Silica-filled rubber compounds show poor filler dispersion and slow cure characteristics compared to carbon black-filled ones. In general, a silica-filled rubber compound contains silane coupling agent (bis-(3-(triethoxysilyl)-propyl)-tetrasulfide, TESPT) and diphenylguanidine (DPG) to improve the filler dispersion and to make fast cure characteristics. Acrylonitrile-butadiene rubber (NBR) improves the filler dispersion in silica-filled styrene-butadiene rubber (SBR) compounds. In this study, effect of NBR on the properties of silica-filled SBR compounds was investigated. Properties of the compounds which contain NBR without DPG or with small amount of TESPT (Compound A) were compared with those of the compounds which contain TESPT and DPG without NBR (Compound B). Scorch time of Compound A is faster than those of Compound B. Modulus and tensile strength of Comound A are slightly lower than those of Compound B. Traction property of the Comound A is better than that of the Compound B. Addition of NBR leads to reduction of the used amount of TESPT and DPG.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.271-271
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• 2019

Estimating ship motion is difficult because it take place in complex environments.. Estimating ship motion is an important factor in ensuring the safety of ship, so accurate estimates are needed. Existing motion-related studies compare the apparent motion of the model acquired and the reference model by experimenting with the ship motion on a particular alignment, making it difficult to intuitively estimate the hull motion. This study introduces the concept of estimating the characteristics of ship motion as a transfer function through pole-zero interpretation and frequency response analysis by applying the method of transfer function of Linear-Time Invariant system. Ship motion analysis model using Linear-Time Invariant system is consist with 1) wave as input signal 2) ship motion as output signal 3) hull defined as black box. This model can be defined by numericalizing the ship motion as a transfer function and is expected to facilitate the characterization of the ship motion through pole-zero analysis and frequency response analysis.

• Convergence Security Journal
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• v.22 no.3
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• pp.101-110
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• 2022

As the cases of using artificial intelligence in various fields increase, attempts to solve various issues through artificial intelligence in the intrusion detection field are also increasing. However, the black box basis, which cannot explain or trace the reasons for the predicted results through machine learning, presents difficulties for security professionals who must use it. To solve this problem, research on explainable AI(XAI), which helps interpret and understand decisions in machine learning, is increasing in various fields. Therefore, in this paper, we propose an explanatory AI to enhance the reliability of machine learning-based intrusion detection prediction results. First, the intrusion detection model is implemented through XGBoost, and the description of the model is implemented using SHAP. And it provides reliability for security experts to make decisions by comparing and analyzing the existing feature importance and the results using SHAP. For this experiment, PKDD2007 dataset was used, and the association between existing feature importance and SHAP Value was analyzed, and it was verified that SHAP-based explainable AI was valid to give security experts the reliability of the prediction results of intrusion detection models.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3D
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• pp.303-311
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• 2010

There have been various forms of systems such as a digital speedometer or a black box etc. to meet the social requirement for reducing traffic accidents and safe driving. However that systems are based on after-accident vehicle data, there is limit to prevent the accident before. So in our previous research, by storing, analyzing the Vehicle-dynamic information coming from driver's behavior, we are developing the decision-device which could provide driver with Alerting-Information in real-time to enhance the driver's safety drive. but the performance valuation is not yet executed. Finally, this study developed positional recognition system by using the DGPS for pre-developed risky driving decision device. The result of test analyzed with the same that the aggregated vehicle dynamics data in DGPS and dangerous risky driving decision device. If the performance of risky driving decision device is verified by precisely positional recognition system, the risky driving management of vehicle would be effected.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.5
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• pp.813-826
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• 2023

Organization members often use the Internet for non-work purposes during work hours, which is called cyberloafing. Certain types of cyberloafing (e.g., webhard, adult, and gambling sites access) can be a major cause of malware infection, which can ultimately generate significant damages to organizations. It therefore is important to examine the relationship between cyberloafing and cybersecurity risks of organizations. We analyzed log data from an internet filtering system of a financial institute and found that the more employees access to blacklist sites, the higher the possibility of malicious code infection. In other words, cyberloafing increases cybersecurity risks of organizations. We suggest that organizations need to monitor and control their members' internet use in an appropriate way.