• Proceedings of the Microbiological Society of Korea Conference
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• 2009.05a
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• pp.38-39
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• 2009

• Journal of Communications and Networks
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• v.9 no.1
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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.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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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.

• Journal of the Semiconductor & Display Technology
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• v.20 no.1
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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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• v.57 no.1
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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.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.4
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• pp.125-132
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• 2021

As the layers of artificial neural network deepens, and the dimension of data used as an input increases, there is a problem of high arithmetic operation requiring a lot of arithmetic operation at a high speed in the learning and recognition of the neural network (NN). Thus, this study proposes a data dimensionality reduction method to reduce the dimension of the input data in the NN. The proposed Line-segment Feature Analysis (LFA) algorithm applies a gradient-based edge detection algorithm using median filters to analyze the line-segment features of the objects existing in an image. Concerning the extracted edge image, the eigenvalues corresponding to eight kinds of line-segment are calculated, using 3×3 or 5×5-sized detection filters consisting of the coefficient values, including [0, 1, 2, 4, 8, 16, 32, 64, and 128]. Two one-dimensional 256-sized data are produced, accumulating the same response values from the eigenvalue calculated with each detection filter, and the two data elements are added up. Two LFA256 data are merged to produce 512-sized LAF512 data. For the performance evaluation of the proposed LFA algorithm to reduce the data dimension for the recognition of handwritten numbers, as a result of a comparative experiment, using the PCA technique and AlexNet model, LFA256 and LFA512 showed a recognition performance respectively of 98.7% and 99%.

• International Journal of Naval Architecture and Ocean Engineering
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• v.1 no.1
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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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.2
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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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• v.3 no.1
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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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• v.2 no.1
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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.