• Journal of the Korean Society of Industry Convergence
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• v.23 no.4_2
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• pp.683-691
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• 2020

In the era of super-aged societies, research and development (R&D) projects related to aging are very important agenda for establishing the direction of future R&D planning and technological competitiveness in the country. In order to respond promptly to this agenda, it is essential to establish a national-level convergence R&D policy. In this study, we utilized the global R&D funding project data from major nations (US, Europe, Japan), and then standardized them with the same fields. To analyze the current status of global R&D related to aging, we performed cluster analysis based on the co-occurrence matrix to explore convergence R&D areas in the US, Europe, and Japan related to aging. In addition, comparative analysis by country suggested that different points on the interdisciplinary area and the convergence of aging-related R&D by each country. These results provide fundamental understandings for the status of convergence in aging-related global R&D, the current technology trends, and establish the direction and strategy of R&D policy.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.19-24
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• 2024

The future military combat environment is rapidly expanding the role and importance of artificial intelligence (AI) in defense, aligning with the current trends of declining military populations and evolving dynamics. Particularly, in the civilian sector, AI development has surged into new domains based on foundation models, such as OpenAI's Chat-GPT, categorized as Super-Giant AI or Hyperscale AI. The U.S. Department of Defense has organized Task Force Lima under the Chief Digital and AI Office (CDAO) to conduct research on the application of Large Language Models (LLM) and generative AI. Advanced military nations like China and Israel are also actively researching the integration of Super-Giant AI into their military capabilities. Consequently, there is a growing need for research within our military regarding the potential applications and fields of application for Super-Giant AI in weapon systems. In this paper, we compare the characteristics and pros and cons of specialized AI and Super-Giant AI (Foundation Models) and explore new application areas for Super-Giant AI in weapon systems. Anticipating future application areas and potential challenges, this research aims to provide insights into effectively integrating Super-Giant Artificial Intelligence into defense operations. It is expected to contribute to the development of military capabilities, policy formulation, and international security strategies in the era of advanced artificial intelligence.

• Structural Engineering and Mechanics
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• v.65 no.6
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• pp.657-678
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• 2018

Sandwich structures are well known for their use in aircraft, naval and automobile industries due to their high strength resistance with light weight and high energy absorption capability. Sandwich beams with soft core are very common and simple structures that are employed in day to day general use appliances. Modeling and analysis of sandwich structures is not straight forward due to the interactions between core and face sheets. In this paper, formulation of Super Convergent finite elements for analysis of the sandwich beams with soft core based on Euler Bernoulli beam theory are presented. Two elements, Eul4d with 4 degrees of freedom assuming rigid core in transverse direction and Eul10d with 10 degrees of freedom assuming the flexible core were developed are presented. The formulation considers the top, bottom face sheets and core as separate entities and are coupled by beam kinematics. The performance of these elements are validated by results available in the published literature. Number of studies are performed using the formulated elements in static, free vibration and wave propagation analysis involving various boundary and loading conditions. The paper highlights the advantages of the elements developed over the traditional elements for modeling of sandwich beams and, in particular wave propagation analysis.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.38-45
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• 2015

Peer-to-Peer(P2P) systems are generally classified into two categories; hybrid and pure P2P. Hybrid systems have a single central index server keeping the details of shared information, so that undesirable effects such as heavy load on that server and lack of fault-tolerance can be caused. Pure P2P causes the other problems such as message flooding and scalability although it shows high degree of fault-tolerance. Recently, mobile agent-based distributed computing has been receiving wide attention for its potential to support disconnected operations, high asynchrony, and thus saving network bandwidth. In this paper, a new scheme of peer coordination is proposed for a decentralized P2P network with self-organizing structure. We deployed mobile agents for incorporating the advantages of usage of mobile agents into our P2P network. Proposed P2P network has both advantages of hybrid and pure P2P. The problems of heavy load on the server and lack of fault-tolerance are improved by using multiple special peers called super-peers. And the problems of pure P2P can be reduced by using mobile agents.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.141-144
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• 2023

현재 대한민국은 고령 사회이다. 매년 노인인구의 비율을 증가하고 있으며 2025년에는 노인인구 비율이 20%가 넘으면서 초고령사회로 접어들 전망이다. 이러한 사회적 특성으로 우리는 많은 노인 문제를 겪고 있다. 그 중 대표적인 문제는 독거노인의 비율이 증가함에 따라 매년 고독사하는 독거노인이 많아지고, 지방의 농가인구 또한 점점 감소하고 있다는 점이다. 본 논문에서는 이러한 사회문제를 해결하기 위해 Flutter를 활용한 애플리케이션 개발을 통해 식물과 IOT 기술을 접목하여 이들에게 도움을 주고자 한다. 독거노인에게는 반려 식물 시스템을 제공하여 이들의 우울증을 완화하고, 지방의 농가인구에 효과적인 스마트팜 시스템을 서비스 함으로써 이러한 사회문제를 해결하는 데 도움을 주고자 한다.

• International Journal of Aeronautical and Space Sciences
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• v.15 no.3
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• pp.281-292
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• 2014

We propose a novel cooperative guidance law design method based on the finite time disturbance observer (FTDO) for multiple near space interceptors (NSIs) with impact time control. Initially, we construct a cooperative guidance model with head pursuit, and employ the FTDO to estimate the system disturbance caused by target maneuvering. We subsequently separate the cooperative guidance process into two stages, and develop the normal acceleration command based on the super-twisting algorithm (STA) and disturbance estimated value, to ensure the convergence of the relative distance. Then, we also design the acceleration command along the line-of-sight (LOS), based on the nonsingular fast terminal sliding mode (NFTSM) control, to ensure that all the NSIs simultaneously hit the target. Furthermore, we prove the stability of the closed-loop guidance system, based on the Lyapunov theory. Finally, our simulation results of a three-to-one interception scenario show that the proposed cooperative guidance scheme makes all the NSIs hit the target at the same time.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.224-224
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• 2012

For decades, carbon fiber has expanded their application fields from reinforced composites to energy storage and transfer technologies such as electrodes for super-capacitors and lithium ion batteries and gas diffusion layers for proton exchange membrane fuel cell. Especially in fuel cell, water repellency of gas diffusion layer has become very important property for preventing flooding which is induced by condensed water could damage the fuel cell performance. In this work, we fabricated superhydrophobic network of carbon fiber with high aspect ratio hair-like nanostructure by preferential oxygen plasma etching. Superhydrophobic carbon fiber surfaces were achieved by hydrophobic material coating with a siloxane-based hydrocarbon film, which increased the water contact angle from $147^{\circ}$ to $163^{\circ}$ and decreased the contact angle hysteresis from $71^{\circ}$ to below $5^{\circ}$, sufficient to cause droplet roll-off from the surface in millimeter scale water droplet deposition test. Also, we have explored that the condensation behavior (nucleation and growth) of water droplet on the superhydrophobic carbon fiber were significantly retarded due to the high-aspect-ratio nanostructures under super-saturated vapor conditions. It is implied that superhydrophobic carbon fiber can provide a passage for vapor or gas flow in wet environments such as a gas diffusion layer requiring the effective water removal in the operation of proton exchange membrane fuel cell. Moreover, such nanostructuring of carbon-based materials can be extended to carbon fiber, carbon black or carbon films for applications as a cathode in lithium batteries or carbon fiber composites.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1486-1494
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• 2021

Character recognition is a technology required in various platforms, such as smart parking and text to speech, and many studies are being conducted to improve its performance through new attempts. However, with low-quality image used for character recognition, a difference in resolution of the training image and test image for character recognition occurs, resulting in poor accuracy. To solve this problem, this paper designed an end-to-end learning neural network that combines image super-resolution and character recognition so that the character recognition model performance is robust against various quality data, and implemented an alternative whole learning algorithm to learn the whole neural network. An alternative end-to-end learning and recognition performance test was conducted using the license plate image among various text images, and the effectiveness of the proposed algorithm was verified with the performance test.

• Carbon letters
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• v.15 no.2
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• pp.146-150
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• 2014

In this work, activated carbon nanofiber (ACNF) electrodes with high double-layer capacitance and good rate capability were prepared from polyacrylonitrile nanofibers by optimizing the carbonization temperature prior to $H_2O$ activation. The morphology of the ACNFs was observed by scanning electron microscopy. The elemental composition was determined by analysis of X-ray photoelectron spectroscopy. $N_2$-adsorption-isotherm characteristics at 77 K were confirmed by Brunauer-Emmett-Teller and Dubinin-Radushkevich equations. ACNFs processed at different carbonization temperatures were applied as electrodes for electrical double-layer capacitors. The experimental results showed that the surface morphology of the CNFs was not significantly changed after the carbonization process, although their diameters gradually decreased with increasing carbonization temperature. It was found that the carbon content in the CNFs could easily be tailored by controlling the carbonization temperature. The specific capacitance of the prepared ACNFs was enhanced by increasing the carbonization temperature.

• Journal of applied mathematics & informatics
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• v.22 no.1_2
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• pp.193-208
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• 2006

A modified BFGS algorithm for solving the unconstrained optimization, whose Hessian matrix at the minimum point of the convex function is of rank defects, is presented in this paper. The main idea of the algorithm is first to add a modified term to the convex function for obtain an equivalent model, then simply the model to get the modified BFGS algorithm. The superlinear convergence property of the algorithm is proved in this paper. To compared with the Tensor algorithms presented by R. B. Schnabel (seing [4],[5]), this method is more efficient for solving singular unconstrained optimization in computing amount and complication.