• 한국미생물학회:학술대회논문집
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• 한국미생물학회 2009년도 International Meeting of the Microbiological Society of Korea
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• pp.38-39
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• 2009

• Journal of Communications and Networks
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• 제9권1호
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• pp.28-33
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• 2007

Estimated channel information, especially multipath length and multipath channel of the desired user, is necessary for most previously reported linear blind multiuser detectors in code division multiple access (CDMA) systems. This paper presents a new blind intersymbol decorrelating detector in asynchronous CDMA systems, which uses the cross correlation matrix of the consecutive symbols. The proposed detector is attractive for its simplicity because no channel estimation is required except the synchronization of the desired user. Compared with other reported multiuser detectors, simulation results show that the proposed detector provides a good performance when the active users have significant intersymbol interference and the multipath length is short.

• 천문학회보
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• 제44권1호
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• pp.44.2-44.2
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• 2019

Turbulent motions perturb magnetic field lines and produce magnetic fluctuations. The perturbations leave imprints of turbulence statistics on magnetic field. Observation of synchrotron radiation is one of the easiest ways to study turbulent magnetic field. First, we obtained the spatial spectrum of synchrotron polarization so that shows how the spectrum is affected by Faraday rotation and how to recover the statistics of underlying turbulence magnetic field. Since polarized synchrotron intensity arising from magnetized turbulence are anisotropic along the direction of mean magnetic field. Secondly, we studied quadrupole ratio to quantitatively describe the degree of anisotropy introduced by magnetic field at multi-wavelengths. This work demonstrated that the spectrum and quadrupole ratio of synchrotron polarization can be very informative tools to get detailed information about the statistical properties of MHD turbulence from radio observations of diffuse synchrotron polarization.

• 반도체디스플레이기술학회지
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• 제20권1호
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• pp.64-69
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• 2021

In this paper, a method for improving the defect classification performance in low contrast, ununiformity and featureless steel plate surfaces has been studied based on deep convolution neural network and transfer-learning neural network. The steel plate surface images have low contrast, ununiformity, and featureless, so that the contrast between defect and defect-free regions are not discriminated. These characteristics make it difficult to extract the feature of the surface defect image. A classifier based on a deep convolution neural network is constructed to extract features automatically for effective classification of images with these characteristics. As results of the experiment, AlexNet-based transfer-learning classifier showed excellent classification performance of 99.43% with less than 160 seconds of training time. The proposed classification system showed excellent classification performance for low contrast, ununiformity, and featureless surface images.

• Journal of Chest Surgery
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• 제57권1호
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• pp.96-98
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• 2024

The COR-KNOT suture fastening device has dramatically improved the efficiency of valve suture fixation. Despite its relative ease of use, there are important considerations in deployment to limit the risk of prosthetic valve injury. Herein, we report a case of iatrogenic aortic bioprosthetic insufficiency caused by poorly positioned COR-KNOTs and outline technical strategies to ensure success.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제10권4호
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• pp.125-132
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• 2021

인공신경망의 계층의 깊이가 깊어지고 입력으로 사용되는 데이터 차원이 증가됨에 신경망의 학습 및 인식에 있어서 많은 연산을 고속으로 요구하는 고연산의 문제가 발생한다. 따라서 본 논문에서는 신경망 입력 데이터의 차원을 감소시키기 위한 데이터 차원 감소 방법을 제안한다. 제안하는 선분 특징 분석(Line-segment Feature Analysis; LFA) 알고리즘은 한 영상 내에 존재하는 객체의 선분(Line-segment) 특징을 분석하기 위하여 메디안 필터(median filter)를 사용한 기울기 기반의 윤곽선 검출 알고리즘을 적용한다. 추출된 윤곽 영상은 [0, 1, 2, 4, 8, 16, 32, 64, 128]의 계수 값으로 구성된 3×3 또는 5×5 크기의 검출 필터를 이용하여 8가지 선분의 종류에 상응하는 고유값을 계산한다. 각각의 검출필터로 계산된 고유값으로부터 동일한 반응값을 누적하여 두 개의 1차원의 256 크기의 데이터를 생성하고 두 가지 데이터 요소를 합산하여 LFA256 데이터를, 두 데이터를 합병하여 512 크기의 LAF512 데이터를 생성한다. 제안한 LFA 알고리즘의 성능평가는 필기체 숫자 인식을 위한 데이터 차원 감소를 목적으로 PCA 기법과 AlexNet 모델을 이용하여 비교 실험한 결과 LFA256과 LFA512가 각각 98.7%와 99%의 인식 성능을 보였다.

• International Journal of Naval Architecture and Ocean Engineering
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• 제1권1호
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• pp.1-12
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• 2009

Wing-in-Ground vehicles and aerodynamically assisted boats take advantage of increased lift and reduced drag of wing sections in the ground proximity. At relatively low speeds or heavy payloads of these craft, a flap at the wing trailing-edge can be applied to boost the aerodynamic lift. The influence of a flap on the two-dimensional NACA 4412 airfoil in viscous ground-effect flow is numerically investigated in this study. The computational method consists of a steady-state, incompressible, finite volume method utilizing the Spalart-Allmaras turbulence model. Grid generation and solution of the Navier-Stokes equations are completed using computer program Fluent. The code is validated against published experimental and numerical results of unbounded flow with a flap, as well as ground-effect motion without a flap. Aerodynamic forces are calculated, and the effects of angle of attack, Reynolds number, ground height, and flap deflection are presented for a split and plain flap. Changes in the flow introduced with the flap addition are also discussed. Overall, the use of a flap on wings with small attack angles is found to be beneficial for small flap deflections up to 5% of the chord, where the contribution of lift augmentation exceeds the drag increase, yielding an augmented lift-to-drag ratio.

• 디지털산업정보학회논문지
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• 제18권2호
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• pp.17-26
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• 2022

In this paper, we propose a novel method of performing convolutional operations on a 2-D Processing Element(PE) array. The conventional method [1] of mapping the convolutional operation using the 2-D PE array lacks flexibility and provides low utilization of PEs. However, by mapping a convolutional operation from a 2-D PE array to a 1-D PE array, the proposed method can increase the number and utilization of active PEs. Consequently, the throughput of the proposed Deep Convolutional Neural Network(DCNN) accelerator can be increased significantly. Furthermore, the power consumption for the transmission of weights between PEs can be saved. Based on the simulation results, the performance of the proposed method provides approximately 4.55%, 13.7%, and 2.27% throughput gains for each of the convolutional layers of AlexNet, VGG16, and ResNet50 using the DCNN accelerator with a (weights size) x (output data size) 2-D PE array compared to the conventional method. Additionally the proposed method provides approximately 63.21%, 52.46%, and 39.23% power savings.

• Asian Journal of Innovation and Policy
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• 제3권1호
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• pp.1-24
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• 2014

Policy planners in Asia readily covet high technology districts and regional systems of innovation such as Silicon Valley. We examine the law's role, by way of covenants not to compete (競業禁止條項) in the development of Silicon Valley by reviewing the literature from 1999 through 2013. The research suggests that in certain high-tech districts such as Silicon Valley, there are greater gains in the innovation of a region by prohibiting CNCs. While we emphasize CNC law as the main legal determinant to Silicon Valley's success, the application of trade secret law and the inevitable disclosure doctrine are also factors that can aid or restrict the mobility and knowledge spillover of a region. Even with much explored, perspectives are lacking from a regional innovation systems analysis, and more so in the context of Asian nations. To tackle these gaps, three analytical frameworks are presented that entails labor law, law and economics, and law and innovation. And from within the law and innovation framework, research is introduced in the hope that future discussions on Asian regional innovation systems consider the legal foundation of Silicon Valley.

• Journal of Computing Science and Engineering
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• 제2권1호
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• pp.44-73
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• 2008

There is general agreement that the problem of data semantics has to be addressed for XML data to become machine-processable. This problem can be tackled by defining a semantic mapping between an XML schema and an ontology. Unfortunately, creating such mappings is a tedious, time-consuming, and error-prone task. To alleviate this problem, we present a solution that heuristically discovers semantic mappings between XML schemas and ontologies. The solution takes as input an initial set of simple correspondences between element attributes in an XML schema and class attributes in an ontology, and then generates a set of mapping formulas. Once such a mapping is created, it is important and necessary to maintain the consistency of the mapping when the associated XML schema and ontology evolve. In this paper, we first offer a mapping formalism to represent semantic mappings. Second, we present our heuristic mapping discovery algorithm. Third, we show through an empirical study that considerable effort can be saved when discovering complex mappings by using our prototype tool. Finally, we propose a mapping maintenance plan dealing with schema evolution. Our study provides a set of effective solutions for building sustainable semantic integration systems for XML data.