• Journal of KIISE
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• v.42 no.10
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• pp.1185-1194
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• 2015

A spherical panoramic image does not conform to the pin-hole camera model, and, hence, it is not possible to utilize previous techniques consisting of plane-to-plane transformation. In this paper, we propose a new method to estimate the planar geometric transformation between the planar image and a spherical panoramic image. Our proposed method estimates the transformation parameters for latitude, longitude, rotation and scaling factors when the matching pairs between a spherical panoramic image and a planar image are given. A planar image is projected into a spherical panoramic image through two steps of nonlinear coordinate transformations, which makes it difficult to compute the geometric transformation. The advantage of using our method is that we can uncover each of the implicit factors as well as the overall transformation. The experiment results show that our proposed method can achieve estimation errors of around 1% and is not affected by deformation factors, such as the latitude and rotation.

• Journal of KIISE
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• v.43 no.3
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• pp.353-361
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• 2016

During image-guided radiation treatment of lung cancer patients, it is necessary to track the tumor motion because it can change during treatment as a consequence of respiratory motion and cardiac motion. In this paper, we propose a method for tracking the motion of the lung tumors based on the three-dimensional image information from planning 4D MDCT and treatment 4D CBCT images. First, to effectively track the tumor motion during treatment, the global motion of the tumor is estimated based on a tumor-specific motion model obtained from planning 4D MDCT images. Second, to increase the accuracy of the tumor motion tracking, the local motion of the tumor is estimated based on the structural information of the tumor from 4D CBCT images. To evaluate the performance of the proposed method, we estimated the tracking results of proposed method using digital phantom. The results show that the tumor localization error of local motion estimation is reduced by 45% as compared with that of global motion estimation.

• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.601-610
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• 2013

As a standard water clarity variable, the vertical underwater visibility, called Secchi depth, is estimated with ocean color satellite data. In the present study, Moderate Resolvtion Imaging Spectradiometer (MODIS) data are used to measure the Secchi depth which is a useful indicator of ocean transparency for estimating the water quality and productivity. To estimate the Secchi depth $Z_v$, the empirical regression model is developed based on the satellite optical data and in-situ data. In the previous study, a semi-analytical algorithm for estimating $Z_v$ was developed and validated for Case 1 and 2 waters in both coastal and oceanic waters using extensive sets of satellite and in-situ data. The algorithm uses the vertical diffuse attenuation coefficient, $K_d$($m^{-1}$) and the beam attenuation coefficient, c($m^{-1}$) obtained from satellite ocean color data to estimate $Z_v$. In this study, the semi-analytical algorithm is validated using temporal MODIS data and in-situ data over the Yellow, Southern and East Seas including Case 1 and 2 waters. Using total 156 matching data, MODIS $Z_v$ data showed about 3.6m RMSE value and 1.7m bias value. The $Z_v$ values of the East Sea and Southern Sea showed higher RMSE than the Yellow Sea. Although the semi-analytical algorithm used the fixed coupling constant (= 6.0) transformed from Inherent Optical Properties (IOP) and Apparent Optical Properties (AOP) to Secchi depth, various coupling constants are needed for different sea types and water depth for the optimum estimation of $Z_v$.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.10
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• pp.1054-1064
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• 2009

In this work, we predict a true fracture strain using load-displacement curves from tensile test and finite element analysis (FEA), and suggest a method for acquiring true stress-strain (SS) curves by predicted fracture strain. We first derived the true SS curve up to necking point from load-displacement curve. As the beginning, the posterior necking part of true SS curve is linearly extrapolated with the slope at necking point. The whole SS curve is then adopted for FE simulation of tensile test. The Bridgman factor or suitable plate correction factors are applied to pre and post FEA. In the load-true strain curve from FEA, the true fracture strain is determined as the matching point to test fracture load. The determined true strain is validated by comparing with test fracture strain. Finally, we complete the true SS curve by combining the prior necking part and linear part, the latter of which connects necking and predicted fracture points.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.950-957
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• 2011

With the convergence of disciplines in progress and Web 2.0 online collaborative environment, online knowledge exchange activities of researchers are increasing. Quickness of acquiring knowledge highly impacts on research productivity in the global era. Online knowledge exchange is critical service for researchers. In this study, knowledge exchange service model was presented from the perspective of activate participation, knowledge quality improvement, quickness of exchanges. A variety of domestic and international knowledge exchange services were analyzed, particularly Korean domestic service KOSEN What is? as for operational practice. It is confirmed that in order to stimulate researcher knowledge exchange the quality of the knowledges exchanged is essential and variety of operating activities are needed such as expert matching systems, enhancement of speed in knowledge exchange, ease of usability, and elements of fun.

• Journal of Korea Multimedia Society
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• v.23 no.11
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• pp.1396-1405
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• 2020

Cyber threats such as forced personal information collection and distribution of malicious codes using malicious URLs continue to occur. In order to cope with such cyber threats, a security technologies that quickly detects malicious URLs and prevents damage are required. In a web environment, malicious URLs have various forms and are created and deleted from time to time, so there is a limit to the response as a method of detecting or filtering by signature matching. Recently, researches on detecting and predicting malicious URLs using machine learning techniques have been actively conducted. Existing studies have proposed various features and machine learning algorithms for predicting malicious URLs, but most of them are only suggesting specialized algorithms by supplementing features and preprocessing, so it is difficult to sufficiently reflect the strengths of various machine learning algorithms. In this paper, a system for predicting malicious URLs using multiple machine learning algorithms was proposed, and an experiment was performed to combine the prediction results of multiple machine learning models to increase the accuracy of predicting malicious URLs. Through experiments, it was proved that the combination of multiple models is useful in improving the prediction performance compared to a single model.

• Journal of Advanced Navigation Technology
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• v.24 no.5
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• pp.393-407
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• 2020

In order to reduce the threat by illegal unmanned aerial vehicles, a tracking system based on sound was implemented. There are three main points to the drone acoustic tracking method. First, it scans the space through variable beam formation to find a sound source and records the sound using a microphone array. Second, it classifies it into a hidden Markov model (HMM) to find out whether the sound source exists or not, and finally, the sound source is In the case of a drone, a sound source recorded and stored as a tracking reference signal based on an adaptive beam pattern is used. The simulation was performed in both the ideal condition without background noise and interference sound and the non-ideal condition with background noise and interference sound, and evaluated the tracking performance of illegal drones. The drone tracking system designed the criteria for determining the presence or absence of a drone according to the improvement of the search distance performance according to the microphone array performance and the degree of sound pattern matching, and reflected in the design of the speech reading circuit.

• Korean Journal of Adult Nursing
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• v.15 no.3
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• pp.483-492
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• 2003

Purpose: The study was performed to identify the process of change, decisional balance and self-efficacy corresponding to the stage of smoking cessation behavior based on Transtheoretical Model in industrial workers. Method: A convenience sample of 146 industrial workers except for the never smokers, were recruited at a H industry in Ulsan. Data were collected from February 1 to 28, 2002. The research instruments were Stages of Change of Smoking Cessation Measure(DiClemente et al, 1991), Process of change(Prochaska, 1988), Smoking Abstinence Self Efficacy (SASE: DiClemente et al, 1985) and Decisional balance(SDB; Kim, 1999). Result: The results of this study were as follows; 1. The subjects were distributed in each stage of smoking cessation change: There were 64 subjects (43.0%) in the precontemplation stage, 35 subjects(23.5%) in the contemplation stage, 28 subjects(18.8%) in the preparation stage, 14 subjects(10.1%) in the action stage and 7 subjects(4.7%) in the maintenance stage. 2. Analysis of variance showed that experiental process(F=2.808, p=.042), behavioral process (F=4.567, p=.004) self-efficacy(F=9.809, p=.000), pros(F=11.107, p=.000), cons(F=6.686, p=.000), pros- cons(F=3.446, p=.018) were significantly associated with the stages of smoking cessation change. 3. Through discriminant analysis, it was found that 'PROS' was the most influential variable in discriminating the four stages of change. Conclusion: This study can provide the basis of staged matching smoking cessation program using TTM for more effective and useful intervention.

• The Journal of the Korea Contents Association
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• v.7 no.2
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• pp.1-10
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• 2007

In this paper, we propose a face recognition system using AAM and Gabor feature vectors. EBGM, which is prominent among face recognition algorithms employing Gabor feature vectors, requires localization of facial feature points where Gabor feature vectors are extracted. However, localization of facial feature points employed in EBGM is based on Gator jet similarity and is sensitive to initial points. Wrong localization of facial feature points affects face recognition rate. AAM is known to be successfully applied to localization of facial feature points. In this paper, we propose a facial feature point localization method which first roughly estimate facial feature points using AAM and refine facial feature points using Gabor jet similarity-based localization method with initial points set by the facial feature points estimated from AAM, and propose a face recognition system based on the proposed localization method. It is verified through experiments that the proposed face recognition system using the combined localization performs better than the conventional face recognition system using the Gabor similarity-based localization only like EBGM.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.80-89
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• 2009

The importance of personalized services has been attracted in smart home environments according to the development of ubiquitous computering. In this paper, we proposed the smart home personalized service system based on context information using the speech recognition. The proposed service consists of an OSGi framework based service mobile manager, service manager, voice recognition manager, and location manager. Also, this study defines the smart home space and configures the commands of units, sensor information, and user information that are largely used in the defined space as context information. In particular, this service identifies users who exist in the same space that shows a difficulty in the identification using RFID through the training model and pattern matching in voice recognition and supports the personalized service of smart home applications. In the results of the experiment, it was verified that the OSGi based automated and personalized service can be achieved through verifying users in the same space.