• Journal of Institute of Control, Robotics and Systems
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• v.11 no.6
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• pp.558-563
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• 2005

In this paper, we implemented a web-based virtual laboratory system(VLab system) with creative and interactive multimedia contents, which can be used to enhance the quality of education in the area of digital logic circuits. Since the proposed VLab system is implemented to describe the on-campus laboratory, the learners can obtain similar experimental data through it. Also, the VLab system is designed to increase the learning and teaching efficiencies of both the learners and the educators, respectively. The learners will be able to achieve high teaming standard and the educators save their time and labor. The virtual experiments on our VLab system are performed according to the following procedure: (1) Circuit composition on the virtual bread board (2). Applying input voltage (3) Output measurements (4) Checkout of experiment results. Furthermore, the circuit composition on the virtual bread board and its corresponding online schematic diagram are displayed together on the VLab system for the learner's convenience. Finally, we have obtained several affirmative effects such as reducing the total experimental hours and the damage rate for experimental equipments and increasing learning efficiencies as well as faculty productivity.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.635-638
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• 2008

Online games' environments have recently changed with developments of computer technique. Various factors such as respective for realistic expression, solidity, the quality of the material, shadow, should be considered. In these factors, shadow expression plays a important role for realistic one. A lot of repeated operation should be executed to provide shadow. In other words, realm division against a lot of dots to estimate objections and the degree of brightness should be divided. This paper provides effective methods to perform realistic shadow through mapping LOD of objections as shadow without drawing data to judge the realm of shadow for shadow creation.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.661-668
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• 2022

Various lean design and construction methods such as target value design, pull planning, value stream mapping have successfully transformed the commercial building construction industry into achieving improved productivity, higher design and construction quality, and meeting the target values of construction projects. Considering the significant advantages of lean, the accelerated dissemination and adoption of lean methods and tools for construction is highly desirable. Currently, the lean design and construction body of knowledge is imparted primarily through publications and conferences. However, one of the most effective ways to impart this soft knowledge is through getting students and trainees involved in hands-on participatory games, which can quickly help them truly understand the concept and apply it to real-world problems. The COVID-19 Pandemic has raised an urgent need of developing virtual games that can be played simultaneously from various locations over the Internet, but these virtual games should be as effective as in-person games. This research develops an online 3D simulation game for Target Value Design that is as effective as in-person games or possibly better in terms of knowledge capture and retention and enjoyable environment and experience. The virtual game is tested on volunteers using feedback from pre-and post- simulation surveys to evaluate its efficacy.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.5 no.4
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• pp.789-796
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• 2015

The first phase of architecture design is the field survey of the site and its surroundings. To gather the information there are two methods :the traditional method of an onsite survey, and recently using 3D geometry data and high quality image mapping from online services such as Google Earth. However, the urban condition is fast changing, and information from online services may lack sufficient information. This paper presents the to fast and effective site survey method for urban site using an affordable and fully automated UAV for the architectural design field.

• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.851-858
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• 2009

Mobbing is not restricted to problem of young people but the bigger recent problem occurs in workspaces. According to reports of ILO and domestic case mobbing in the workplace is increasing more and more numerically from 9.1%('03) to 30.7%('08). These mobbing brings personal and social losses. The proposed algorithm makes it possible to grasp not only current mobbing victims but also potential mobbing victims through user profile and contribute to efficient personnel management. This paper extracts user profile related to mobbing, in a way of selecting seven factors and fifty attributes that are related to this matter. Next, expressing extracting factors as '1' if they are related me or not '0'. And apply similarity function to attributes summation included in factors to calculate similarity between the users. Third, calculate optimizing weight choosing factors included attributes by applying neural network algorithm of SPSS Clementine and through this summation Mobbing-Value(MV) can be calculated . Finally by mapping MV of online social network users to G2 mobbing propensity classification model(4 Groups; Ideal Group of the online social network, Bullies, Aggressive victims, Victims) which is designed in this paper, can grasp mobbing propensity of users, which will contribute to efficient personnel management.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.1020-1033
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• 2021

Nowadays, online or mobile social network services (SNS) are very popular and widely spread in our society and daily lives to instantly share, disseminate, and search information. In particular, SNS such as YouTube, Flickr, Facebook, and Amazon allow users to upload billions of images or videos and also provide a number of multimedia information to users. Information retrieval in multimedia-rich SNS is very useful but challenging task. Content-based media retrieval (CBMR) is the process of obtaining the relevant image or video objects for a given query from a collection of information sources. However, CBMR suffers from the dimensionality curse due to inherent high dimensionality features of media data. This paper investigates the effectiveness of the kernel trick in CBMR, specifically, the kernel principal component analysis (KPCA) for dimensionality reduction. KPCA is a nonlinear extension of linear principal component analysis (LPCA) to discovering nonlinear embeddings using the kernel trick. The fundamental idea of KPCA is mapping the input data into a highdimensional feature space through a nonlinear kernel function and then computing the principal components on that mapped space. This paper investigates the potential of KPCA in CBMR for feature extraction or dimensionality reduction. Using the Gaussian kernel in our experiments, we compute the principal components of an image dataset in the transformed space and then we use them as new feature dimensions for the image dataset. Moreover, KPCA can be applied to other many domains including CBMR, where LPCA has been used to extract features and where the nonlinear extension would be effective. Our results from extensive experiments demonstrate that the potential of KPCA is very encouraging compared with LPCA in CBMR.

• Proceedings of the KIEE Conference
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• 2006.04b
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• pp.344-346
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• 2006

In this paper, a novel algorithm for increasing the steady state efficiency during light load operation of the induction generator that integrated with a wind power generation system is presented. The proposed algorithm based on the flux level reduction, where the flux level is estimated using Support-Vector -Machines for regression (SVR) for the optimum d-axis current of the generator. SVR is trained off-line to estimate the unknown mapping between the system's inputs and outputs, and then is used online to calculate the optimum d-axis current for minimizing generator loss. The experimental results show that SVR can define the flux-power loss accurately and determine the optimum d-axis current value precisely. The loss minimization process is more effective at low wind speed and the percent of power saving can approach to 40%.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.253-256
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• 1996

Rainfall is one of the major and complicated elements of hydrologic system. Accurate prediction of rainfall is very important to mitigate storm damage. The neural network is a good model to be applied for the classification problem, large combinatorial optimization and nonlinear mapping. In this dissertation, rainfall predictions by the neural network theory were presented. A multi-layer neural network was constructed. The network learned continuous-valued input and output data. The network was used to predict rainfall. The online, multivariate, short term rainfall prediction is possible by means of the developed model. A multidimensional rainfall generation model is applied to Seoul metropolitan area in order to generate the 10-minute rainfall. Application of neural network to the generated rainfall shows good prediction. Also application of neural network to 1-hour real data in Seoul metropolitan area shows slightly good predictions.

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.211-212
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• 2019

The objectives of this research are to test the utility of semiparametric geographically weighted regression (SGWR, a spatial analysis method) in the small-scale urban sample, and to understand the geographic patterns of provision and pricing of sharing economy based accommodations in the tourist city. This paper focused on how network distance to heritage site, to casino, residential unit prices and other five attribute categories determine Airbnb price in Macau SAR, China. Findings show that SGWR models outperformed OLS models. Moreover, comparing with heritage sites, casinos are the stronger factors to drive up Airbnb (including hostels) rooms' provision and their prices; and residential unit prices are not related with the Airbnb price in the attraction clusters in Macau. This research showed a little example for the applications of SGWR in the small city, and for the analysis of online marketplace data as new urban study material. Practically, this study provides some scientific evidence for hosts, guests, urban planners, and policymakers' decision making in Macau.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.25-33
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• 2010

In this paper, we propose a simple and efficient algorithm for head pose estimation using a single camera. First, four subimages are obtained from the camera image for face feature extraction. These subimages are used as feature templates. The templates are then tracked by Kalman filtering, and camera projective matrix is computed by the projective mapping between the templates and their coordinate in the 3D coordinate system. And the user's face pose is estimated from the projective mapping between the user's face and image plane. The accuracy and the robustness of our technique is verified on the experimental results of several real video sequences.