• Applied Science and Convergence Technology
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• v.26 no.4
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• pp.91-94
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• 2017

AThe effect of localized surface plasmon on silicon substrates was studied using silver nanoparticles. The nanoparticles were formed by self-arrangement through the surface energy using rapid thermal annealing (RTA) technique after the thin nanolayer of silver was deposited by thermal evaporation. By the theoretical calculation based on Mie scattering and dielectric function of air, indium tin oxide (ITO), and silver, the strong peak of scattering cross section of silver nanoparticles was found at 358 nm for air, and 460 nm for ITO, respectively. Accordingly, the strong suppression of reflectance under the condition of induced light of $30^{\circ}$ occurred at the specific wavelength which is almost in accordance with peak of scattering cross section. When the external quantum efficiency was measured using silicon solar cells with silver nanoparticles, there was small enhancement peak near the 460 nm wavelength in which the light was resonated between silver nanoparticles and ITO.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.3011-3024
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• 2021

Pose estimation of the sensor is important issue in many applications such as robotics, navigation, tracking, and Augmented Reality. This paper proposes visual-inertial integration system appropriate for dynamically moving condition of the sensor. The orientation estimated from Inertial Measurement Unit (IMU) sensor is used to calculate the essential matrix based on the intrinsic parameters of the camera. Using the epipolar geometry, the outliers of the feature point matching are eliminated in the image sequences. The pose of the sensor can be obtained from the feature point matching. The use of IMU sensor can help initially eliminate erroneous point matches in the image of dynamic scene. After the outliers are removed from the feature points, these selected feature points matching relations are used to calculate the precise fundamental matrix. Finally, with the feature point matching relation, the pose of the sensor is estimated. The proposed procedure was implemented and tested, comparing with the existing methods. Experimental results have shown the effectiveness of the technique proposed in this paper.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.149-156
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• 2021

Today, 3D softwares have become an essential tool in all areas of Video, including Movies, Animations, CFs, Motion Graphics and Games. One of the most commonly used fields is the 3D character video part. However, these 3D character animations and motion graphics softwares are difficult to learn and too much to learn, making it difficult to learn them all in a university education with a limited time of four years. In this paper, many Inverse kinematics tools, which are essential in the 3D character animations and motion graphics field, compare and analyze the strengths and weaknesses of each tool, focusing on Bone, Character Studio, and Character Animation Toolkit, which are most commonly used in work fields. And use Delphi techniques for 3D experts to secure objectivity. Therefore, for universities that require large amounts of teaching in a limited time, I propose an analysis of which of the above three Inverse Kinetics tools is advantageous for students to select and focus on for efficient education.

• Nonlinear Functional Analysis and Applications
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• v.27 no.1
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• pp.59-82
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• 2022

In this paper, we present a modified (improved) generalized M-iteration with the inertial technique for three quasi-nonexpansive multivalued mappings in a real Hilbert space. In addition, we obtain a weak convergence result under suitable conditions and the strong convergence result is achieved using the hybrid projection method with our modified generalized M-iteration. Finally, we apply our convergence results to certain optimization problem, and present some numerical experiments to show the efficiency and applicability of the proposed method in comparison with other improved iterative methods (modified SP-iterative scheme) in the literature. The results obtained in this paper extend, generalize and improve several results in this direction.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.52-57
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• 2022

In this study, keywords from representative online portal sites such as Naver, Google, and Youtube were collected based on text mining analysis technique using Textom to check the changes in metqaverse after COVID-19. before Corona, it was confirmed that social media platforms such as Kakao Talk, Facebook, and Twitter were mentioned, and among the four metaverse, consumer awareness was still concentrated in the field of life logging. However, after Corona, keywords from Roblox, Fortnite, and Geppetto appeared, and keywords such as Universe, Space, Meta, and the world appeared, so Metaverse was recognized as a virtual world. As a result, it was confirmed that consumer perception changed from the life logging of Metaverse to the mirror world. Third, keywords such as cryptocurrency, cryptocurrency, coin, and exchange appeared before Corona, and the word frequency ranking for blockchain, which is an underlying technology, was high, but after Corona, the word frequency ranking fell significantly as mentioned above.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.126-139
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• 2022

The need for synthetic automation is increasing in preparation for a gradual decrease in laboratory research manpower due to low birth rate and aging. In this study, the existing laboratory synthesis method is analyzed based on the systems engineering technique. Then, it led to the derivation of the system requirements for a fixed-based robot manipulator capable of recognition, decision and control. The robot is equipped with replaceable modular end-effectors and designed depending on the purpose and process of the synthesis. The robot with an end-effector was implemented as PoC(Proof-of-Concept), and the functions for pipetting automation was verified.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.4
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• pp.578-585
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• 1986

This paper describes a new two-dimensional adaptive lattice algorithm which determines reflection coefficients recursively by applying the gradient search technique to a two-dimensional lattice filter proposed by Parker and Kayran. The convergence characteristics of the proposed algorithm are also described. A new tow-dimensional adaptive lattice \ulcorneralgorithm has been obtained through the application of the \ulcorneralgorithm to the two-dimention adaptive lattice algorithm. Computer simulation proves that the convergence speed of the two-dimension adaptive lattice \ulcorneralgorithm is reladtively higher than that of the conventional adaptive lattice algorithm when \ulcornerhas a small value.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.256-259
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• 2023

최근 스마트 시티 등과 같은 이유로 IoT에 대한 관심이 증가하며 이에 대한 보안 솔루션 또한 주목받게 되었다. 이때 블록체인이 보안 솔루션으로써 많은 관심을 받고있지만 확장성에 한계에 의하여 IoT와의 융합에 제한을 받고있는 상황이다. 따라서 이러한 확장성 문제를 해결하기 위한 다양한 기법들이 존재한다. 본 논문에서는 확장성의 한계를 해결하기 위해 블록체인 경량화 기법의 연구 사례에 대하여 알아본다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.151-153
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• 2023

Federated learning (FL)-based network intrusion detection techniques have enormous potential for securing the Industrial Internet of Things (IIoT) cybersecurity. The openness and connection of systems in smart industrial facilities can be targeted and manipulated by malicious actors, which emphasizes the significance of cybersecurity. The conventional centralized technique's drawbacks, including excessive latency, a congested network, and privacy leaks, are all addressed by the FL method. In addition, the rich data enables the training of models while combining private data from numerous participants. This research aims to create an FL-based architecture to improve cybersecurity and intrusion detection in IoT networks. In order to assess the effectiveness of the suggested approach, we have utilized well-known cybersecurity datasets along with centralized and federated machine learning models.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.254-257
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• 2024

5G 통신과 인공지능 기술이 발전하고, 사물인터넷 기기의 수가 증가함에 따라 종래의 정보보호체계를 우회하는 지능적인 사이버 공격이 증가하고 있다. 그러나, 종래의 기계학습 기반 멀웨어 탐지 방식은 이미 알려진 멀웨어만 탐지할 수 있으며, 새로운 멀웨어는 탐지가 어렵거나, 기존의 알려진 멀웨어로 잘못 분류되는 문제가 있다. 본 연구에서는 비지도학습을 사용하여 알려지지 않은 멀웨어를 탐지하고, 새롭게 탐지된 멀웨어를 새로운 라벨로 분류하여 재학습하는 준지도 학습 기반의 멀웨어 탐지 기법을 제안한다. 다양한 데이터 환경에서 알려지지 않은 멀웨어 데이터가 탐지 모델로 입력될 때 제안한 방식의 성능을 평가했다. 실험 결과에 따르면 제안한 준지도 학습 기반의 멀웨어 탐지 방법은 종래의 방식 대비 정확도를 약 16% 개선했다.