• 전자공학회논문지 IE
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• v.43 no.4
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• pp.105-114
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• 2006

In this paper, 3D input and output systems for a web-based real-time 3D video communication system using IEEE 1394 digital cameras, Intel Xeon Server system and Microsoft Directshow library is proposed. And some conditions for optimizing the operations of the stereo camera, 3D display and signal processing system are analyzed. Input & output systems are carefully selected, which can satisfy the required optimization conditions and the final 3D video communication system is implemented by using three optimized devices. The overall control system is developed with Microsoft Visual C++.Net and Microsoft DirectX 9.1 SDK. Some experimental results show that the observer can feel the natural presence from multi-view(4-view) 3D video of server system in real-time and also can feel the natural presence from 3D video of client system and finally suggest an application possibility of the proposed web-based real-time 3D video communication in real fields.

• Korean Management Science Review
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• v.25 no.1
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• pp.1-9
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• 2008

This paper investigates the R&D project portfolio selection problem. Despite its importance and impact on real world projects, there exist few practical techniques that help construct an non-dominated portfolio for a decision makers satisfaction. One of the difficulties constructing the portfolio is that such project portfolio problem is, in nature, a multi-attribute decision-making problem, which is an NP-hard class problem. This paper investigates the R&D project portfolio selection problem. Despite its importance and impact on real world projects, there exist few practical techniques that help construct an non-dominated portfolio for a decision makers satisfaction. One of the difficulties constructing the portfolio is that such project portfolio problem is, in nature, a multi-attribute decision-making problem, which is an NP-hard class problem. In order to obtain the non-dominated portfolio that a decision maker or a user is satisfied with, we devise a user-interface algorithm, in that the user provides the maximum/minimum input values for each project attribute. Then the system searches the non-dominated portfolio that satisfies all the given constraints if such a portfolio exists. The process that the user adjusts the maximum/minimum values on the basis of the portfolio found continues repeatedly until the user is optimally satisfied with. We illustrate the algorithm proposed, and the computational results show the efficacy of our procedure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4930-4951
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• 2018

The deep learning based speech enhancement has shown considerable success. However, it still suffers performance degradation under mismatch conditions. In this paper, an adaptation method is proposed to improve the performance under noise mismatch conditions. Firstly, we advise a noise aware training by supplying identity vectors (i-vectors) as parallel input features to adapt deep neural network (DNN) acoustic models with the target noise. Secondly, given a small amount of adaptation data, the noise-dependent DNN is obtained by using $L_2$ regularization from a noise-independent DNN, and forcing the estimated masks to be close to the unadapted condition. Finally, experiments were carried out on different noise and SNR conditions, and the proposed method has achieved significantly 0.1%-9.6% benefits of STOI, and provided consistent improvement in PESQ and segSNR against the baseline systems.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.268-270
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• 1995

In crane drives, DC motor has been most widely used due to simple control characteristic and favorable transient behavior. Nowadays, however, the squirrel cage induction motor is known as an attractive candidate due to elimination of all sliding electrical contacts, resulting in an exceedingly simple and rugged construction. Especially, in hoist application, the smooth torque control and four quadrant operation are essential. In this paper, an operation of dual inverters with common DC bus fed by vector controlled induction motor is described. Single DSP is employed as a main processor to control dual inverters and communicates each input/output signal with PLC. As well as giving a detailed expression, full simulation and experimental results are presented.

• Ocean and Polar Research
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• v.31 no.4
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• pp.305-318
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• 2009

A marine ranching project in Tongyoung was established in 1998, lasting 9 years to 2006. Project activities included the deployment of artificial reefs, the release of young fishes like jacopever and rockfish, and input/output control for specific marine ranching areas in Tongyoung. This report focuses on the economic feasibility of the project in hindsight. Analysis concentrates on three aspects; (a) direct economic benefits, such as increasing effects of fisheries income and savings in harvesting costs, (b) indirect benefits, including increasing effects of recreational fishing and saving R&D costs, and (c) costs, including releasing and purchasing costs of artificial reef and juvenile fish, R&D costs, maintenance costs and harvesting costs. Results show that NPV=4.7 billion won, IRR=8.55% and B/C ratio=1.286 under Scenario 1, which considers the saving effects of R&D costs, and NPV=0.9 billion won, IRR=6.03% and B/C ratio=1.11 under Scenario 2, which does not consider the saving effects of R&D costs, based on 5.5% of the social rate of discount. According to sensitivity analysis, the economic feasibility is very sensitive to the recapture rate.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.05b
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• pp.19-22
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• 2004

The resonant planar transformer, which had power capacity of 300 W, input voltage of 220 V, output voltage of 15 V, and switching frequency of 500 kHz, was designed and manufactured by using the planar core with large effective area and the flat copper lead frames for miniaturization and high efficiency of the switching mode power supply (SMPS). As well as, a resonant converter equipped with the above mentioned planar transformer was manufactured and electromagnetic characteristics were investigated. The numerical value of turns for 1st and 2nd winding were 12 and 2 respectively. The self inductance of 1st winding was 33.2 ${\mu}H$, very low leakage inductance of 1.27 ${\mu}H$, and the coupling factor of 0.98 were obtained at switching frequency of 300 kHz. The high efficiency of 88.21 % for the SMPS equipped with planar transformer was obtained at power capacity of 300 W.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.227-230
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• 1993

Recently, the development of novel control methodology enables us to improve the performance of AC-machine drives by using pulse width modulation (PWM) technique. Usually, the dynamic characteristic of induction motor (IM) has been represented by the 5-th order nonlinear differential equation. This dynamics, however, can be reduced to 3-rd order dynamics by applying direct control of IM input current. This methodology concludes that it is much easier to control IM by means of the field-oriented methods employing the current controller. Therefore a precise current control is crucial to achieve a high control performance both in dynamic and steady state operations. This paper presents an adaptive fuzzy current controller with artificial neural network (ANN) for field-oriented controlled IM. This new control structure is able to adaptively minimize a current ripple while maintaining constant switching frequency. Especially the proposed controller employs neuro-computing philosophy as well as adaptive learning pattern recognizing principles with respect to variations of the system parameters. The proposed approach is applied to the IM drive system, and its performance is tested through various simulations. Simulation results show that the proposed system, compared among several known classical methods, has a superb performance.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.16 no.1
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• pp.47-63
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• 1990

Image analyser was used to understand the condition of skin surface and to evaluate the efficacy of cosmetic treatment. It was unsatisfactory to analyse skin surface structure although several methods using image analyser had been presented. We developed the new system composed of image analyser and Tandem Scanning Reflected Light Microscope (TSRLM) having the remarkable optical sectioning property as image input device. By using this new system, we quantitatively measured the change of skin surface, the depth and width of furrow in micron unit, resulted by cosmetic treatments. And also three dimensional image of skin was reconstructed with serial sectioned images, which were captured through TSRLM, for better understanding of the effect of cosmetic treatment. It was found that skin relief was more easily understood and the change of skin surface caused by cosmetic treatment was more accurately measured by using this system. In addition, we was also aware of the possibility of in vivo direct measurement of skin furrow without replica. It was conceivable that our system could be applicable for study of cosmetic effects further.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.31-39
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• 2021

This study collected 1,870 English news articles related to research and development of autonomous vehicles in order to identify various issues emerging in the research and development process of autonomous vehicles at home and abroad, and conducted topic modeling after data pre-processing. As a result of topic modeling, we extracted 20 topics, and we performed naming operations for topics and interpreted their meanings. A logical model for autonomous vehicle research and development projects was presented in response to the R&D process of input, activity, output, and outcome of derived topics. The analysis results of this study will be used as basic data to accurately determine the progress of domestic and foreign self-driving car research and development projects and prepare for the rapidly changing technology development.

• Journal of Korea Multimedia Society
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• v.22 no.9
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• pp.1000-1010
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• 2019

Image semantic segmentation and dehazing are key tasks in the computer vision. In recent years, researches in both tasks have achieved substantial improvements in performance with the development of Convolutional Neural Network (CNN). However, most of the previous works for semantic segmentation assume the images are captured in clear weather and show degraded performance under hazy images with low contrast and faded color. Meanwhile, dehazing aims to recover clear image given observed hazy image, which is an ill-posed problem and can be alleviated with additional information about the image. In this work, we propose a deep multi-task network for simultaneous semantic segmentation and dehazing. The proposed network takes single haze image as input and predicts dense semantic segmentation map and clear image. The visual information getting refined during the dehazing process can help the recognition task of semantic segmentation. On the other hand, semantic features obtained during the semantic segmentation process can provide cues for color priors for objects, which can help dehazing process. Experimental results demonstrate the effectiveness of the proposed multi-task approach, showing improved performance compared to the separate networks.