• 융합신호처리학회논문지
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• 제15권3호
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• pp.97-103
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• 2014

근래에 와서 출입문의 물리적 보안장치로써 디지털 도어록의 사용이 보편화되었다. 기존의 자물쇠 방식 보다는 훨씬 편리한 기능이지만 도어록에 전기 충격을 가할 경우 열리는 문제점이 노출되었다. 본 연구에서는 도어록 기기를 안으로 숨기고 증강현실을 이용해 도어록을 사용자의 스마트폰 화면에 띄우게 하여 보안성을 높이는 방법을 제안한다. 아울러 메모노트를 띄우는 기능을 추가하여 가족 간의 의사소통을 원활하게 해주는 기능을 부가하였다. 본 연구 결과는 가상으로 만든 출입문과 아두이노와 와이파이 쉴드 그리고 자물쇠를 제어하기 위한 모터를 사용하여 구현하였으며, 만족할 만한 실험결과를 보였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.195-197
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• 2005

This paper is proposed adaptive fuzzy neural network(AFNN) and artificial neural network(ANN) based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed control and estimation of speed of induction motor using fuzzy and neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed. so that the actual state variable will coincide with the desired one. This paper is proposed the experimental results to verify the effectiveness of the new method.

• Restorative Dentistry and Endodontics
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• 제23권1호
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• pp.213-222
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• 1998

Advisor: Prof. The quality of apical seal obtained with 3 different gutta-percha obturation techniques was compared in 49 recently extracted single rooted teeth. The root canals were instrumented using step-back technique and obturated with laterally condensed gutta-percha, Continuous Wave gutta-percha, and hybrid technique. Teeth were suspended in black India ink for 7 days, cleared, and then examined under a stereomicroscope at ${\times}10$ magnification. The results were as follows; 1. All experimental groups produced favorable apical seal. 2. The mean leakage was $0.23{\pm}0.25mm$ for group 1, $0.17{\pm}0.21mm$ for group 2, and $0.19{\pm}0.23mm$ for froup 3, but there was no statistical difference amoung them. Within the limits of the results of this experiment, the Continuous Wave gutta-percha obturation technique demonstrated relatively favorable apical sealing effect and shorter obturation time. Thus, it is thought that this obturation technique is a acceptable method for clinical use but further studies on this metter should be conducted.

• 정보처리학회논문지D
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• 제10D권2호
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• pp.277-282
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• 2003

웹으로부터 유용한 정보를 얻기 위한 연구는 현재 많이 진행되고 있다. 본 논문에서는 특히 웹 로그 데이터의 희소성에 대한 문제 해결과 이를 통한 웹 사용자의 군집화 방안에 대하여 연구하였다. MCMC 방법의 베이지안 추론에 의한 결측치 대체 기법을 이용하여 웹 데이터의 희소성을 제거하였고, 주성분에 의한 산점도를 통하여 형상지도의 차원을 결정한 자기 조직화지도를 이용하여 웹 사용자의 군집화를 수행하였다. 제안 기법은 기존의 방법들에 비해 모형의 정확도와 빠른 학습 시간을 제공하여 주었다. KDD Cup 데이터를 이용한 실험을 통하여 제안 방법에 대한 문제 해결 절차 및 성능 평가를 객관적으로 확인하였다.

• Structural Engineering and Mechanics
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• 제57권1호
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• pp.45-63
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• 2016

Fiber metal laminates (FMLs) represent a high-performance family of hybrid materials which consist of thin metal sheets bonded together with alternating unidirectional fiber layers. In this study, the buckling behavior of a FML circular cylindrical shell under axial compression is investigated via both analytical and finite element approaches. The governing equations are derived based on the first-order shear deformation theory and solved by the Navier solution method. Also, the buckling load of a FML cylindrical shell is calculated using linear eigenvalue analysis in commercial finite element software, ABAQUS. Due to lack of experimental and analytical data for buckling behavior of FML cylindrical shells in the literature, the proposed model is simplified to the full-composite and full-metal cylindrical shells and buckling loads are compared with the available results. Afterwards, the effects of FML parameters such as metal volume fraction (MVF), composite fiber orientation, stacking sequence of layers and geometric parameters are studied on the buckling loads. Results show that the FML layup has the significant effect on the buckling loads of FML cylindrical shells in comparison to the full-composite and full-metal shells. Results of this paper hopefully provide a useful guideline for engineers to design an efficient and economical structure.

• Nuclear Engineering and Technology
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• 제53권12호
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• pp.4072-4079
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• 2021

This article presents a study on the state-of-the-art methods for automated radioactive material detection and identification, using gamma-ray spectra and modern machine learning methods. The recent developments inspired this in deep learning algorithms, and the proposed method provided better performance than the current state-of-the-art models. Machine learning models such as: fully connected, recurrent, convolutional, and gradient boosted decision trees, are applied under a wide variety of testing conditions, and their advantage and disadvantage are discussed. Furthermore, a hybrid model is developed by combining the fully-connected and convolutional neural network, which shows the best performance among the different machine learning models. These improvements are represented by the model's test performance metric (i.e., F1 score) of 93.33% with an improvement of 2%-12% than the state-of-the-art model at various conditions. The experimental results show that fusion of classical neural networks and modern deep learning architecture is a suitable choice for interpreting gamma spectra data where real-time and remote detection is necessary.

• Smart Structures and Systems
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• 제23권6호
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• pp.669-682
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• 2019

Vibration mitigation of cables or hangers is one of the crucial problems for cable supported bridges. Previous research focused on the behaviors of cable with dampers or crossties, which could help engineering community apply these mitigation devices more efficiently. However, less studies are available for hybrid applied cross-ties and dampers, especially lack of both analytical and experimental verifications. This paper studied damping and frequency of two parallel identical cables with a connection cross-tie and an attached damper. The characteristic equation of system was derived based on transfer matrix method. The complex characteristic equation was numerically solved to find the solutions. Effects of non-dimensional spring stiffness and location on the maximum cable damping, the corresponding optimum damper constant and the corresponding frequency of lower vibration mode were further addressed. System with twin small-scale cables with a cross-link and a viscous damper were tested. The damping and frequency from the test were very close to the analytical ones. The two branches of solutions: in-phase modes and the out-of-phase modes, were identified; and the two branches of solutions were different for damping and frequency behaviors.

• ETRI Journal
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• 제43권1호
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• pp.40-52
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• 2021

DNS (Domain Name System) tunnels almost obscure the true network activities of users, which makes it challenging for the gateway or censorship equipment to identify malicious or unpermitted network behaviors. An efficient way to address this problem is to conduct a temporal-spatial analysis on the tunnel traffic. Nevertheless, current studies on this topic limit the DNS tunnel to those with a single protocol, whereas more than one protocol may be used simultaneously. In this paper, we concentrate on the refined identification of two protocols mixed in a DNS tunnel. A feature set is first derived from DNS query and response flows, which is incorporated with deep neural networks to construct a regression model. We benchmark the proposed method with captured DNS tunnel traffic, the experimental results show that the proposed scheme can achieve identification accuracy of more than 90%. To the best of our knowledge, the proposed scheme is the first to estimate the ratios of two mixed protocols in DNS tunnels.

• Journal of Information Technology Applications and Management
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• 제29권3호
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• pp.43-55
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• 2022

In this study, with the goal of developing a deep learning-based product recommendation model for effective matching of influencers and products, a deep learning model with a collaborative filtering model combined with generalized matrix decomposition(GMF), a collaborative filtering model based on multi-layer perceptron (MLP), and neural collaborative filtering and generalized matrix Factorization (NeuMF), a hybrid model combining GMP and MLP was developed and tested. In particular, we utilize one-class problem free boosting (OCF-B) method to solve the one-class problem that occurs when training is performed only on positive cases using implicit feedback in the deep learning-based collaborative filtering recommendation model. In relation to model selection based on overall experimental results, the MLP model showed highest performance with weighted average precision, weighted average recall, and f1 score were 0.85 in the model (n=3,000, term=15). This study is meaningful in practice as it attempted to commercialize a deep learning-based recommendation system where influencer's promotion data is being accumulated, pactical personalized recommendation service is not yet commercially applied yet.

• 국제초고층학회논문집
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• 제11권4호
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• pp.287-300
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• 2022

Unconventional structures are getting more popular in recent days. Large-span roofs are used for many structures, such as airports, stadiums, and conventional halls. Identifying the pressure distribution and wind load acting on those structures is essential. This paper offers a collaborative study of computational fluid dynamics (CFD) simulations and wind tunnel tests for assessing wind pressure distribution for a building with a combined slender curved roof. The hybrid turbulence model, Improved Delayed Detached Eddy Simulation (IDDES), simulates the open terrain turbulent flow field. The wind-induced local pressure coefficients on complex roof structures and the turbulent flow field around the structure were thus calculated based upon open terrain wind flow simulated with the FLUENT software. Local pressure measurements were investigated in a boundary layer wind tunnel simultaneous to the simulation to determine the pressure coefficient distributions. The results predicted by CFD were found to be consistent with the wind tunnel test results. The comparative study validated that the recommended IDDES model and the vortex method associated with CFD simulation are suitable tools for structural engineers to evaluate wind effects on long-span complex roofs and plan irregular buildings during the design stage.