• Asian Journal of Innovation and Policy
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• v.8 no.1
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• pp.162-179
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• 2019

Purpose: Companies in haste for higher consumers' preference tend to appear as 'green' and mislead about environmental concerns, which are termed as "Greenwashing." The purpose of the study is to investigate the consumer perception on greenwashing activities and analyze its impact on green brand image, green brand loyalty and green brand trust among Indian consumers. Design/methodology: The study makes use of a written questionnaire method to collect survey data from approximately 500 consumers all over India. The study uses Structural Equation Modeling (SEM) to study the hypothesized relationship between constructs affected by greenwashing based on consumer perspective in the Indian context. Findings: The study shows that Indian consumers are becoming aware of greenwashing activities, which have a negative impact on green brand trust and undermines green brand image and green brand loyalty. Implications: The study results are beneficial to policy-makers, researchers, practitioners, and managers to create awareness among Indian consumers on greenwashing activities.

• Current Optics and Photonics
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• v.2 no.1
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• pp.69-78
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• 2018

This paper presents a precise edge detection algorithm for the critical dimension (CD) measurement of a Thin-Film Transistor Liquid-Crystal Display (TFT-LCD) pattern. The sigmoid surface function is proposed to model the blurred step edge. This model can simultaneously find the position and geometry of the edge precisely. The nonlinear least squares fitting method (Levenberg-Marquardt method) is used to model the image intensity distribution into the proposed sigmoid blurred edge model. The suggested algorithm is verified by comparing the CD measurement repeatability from high-magnified blurry and noisy TFT-LCD images with those from the previous Laplacian of Gaussian (LoG) based sub-pixel edge detection algorithm and error function fitting method. The proposed fitting-based edge detection algorithm produces more precise results than the previous method. The suggested algorithm can be applied to in-line precision CD measurement for high-resolution display devices.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1930-1935
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• 2003

The aim of this study is to apply engineering modeling tools to examine hemodynamics such as blood flow patterns or shear stress distributions, in order to determine the link between hemodynamics and cerebral aneurysms. Image-Based Simulation is used to analyze the realistic middle cerebral artery constructed from computed tomography raw data. As a result of simulation, high wall shear stress is appeared at the bifurcated region. And existence of the recirculation flow at the inlet of bifurcation($D_2$) is predict to affect at the development of the cerebral aneurysm.

• Ocean Systems Engineering
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• v.10 no.4
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• pp.435-449
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• 2020

This paper proposes a method to estimate the underwater target object's yaw angle using a sonar image. A simulator modeling imaging mechanism of a sonar sensor and a generative adversarial network for style transfer generates realistic template images of the target object by predicting shapes according to the viewing angles. Then, the target object's yaw angle can be estimated by comparing the template images and a shape taken in real sonar images. We verified the proposed method by conducting water tank experiments. The proposed method was also applied to AUV in field experiments. The proposed method, which provides bearing information between underwater objects and the sonar sensor, can be applied to algorithms such as underwater localization or multi-view-based underwater object recognition.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.425-428
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• 2020

본 논문에서는 경계 합성곱 신경망(Convolutional neural network, CNN)기반의 슈퍼 해상도 기법을 이용하여 저해상도 옷감 메쉬를 슈퍼 해상도로 노이즈 없이 안정적으로 표현할 수 있는 기법을 제안한다. 저해상도와 고해상도 메쉬들 간의 쌍은 옷감 시뮬레이션을 통해 얻을 수 있으며, 이렇게 얻어진 데이터를 이용하여 고해상도-저해상도 데이터 쌍을 설정한다. 학습할 때 사용되는 데이터는 옷감 메쉬를 지오메트리 이미지로 변환하여 사용한다. 우리가 제안하는 경계 합성곱 신경망은 저해상도 이미지를 고해상도 이미지로 업스케일링 시키는 이미지 합성기를 학습시키기 위해 사용된다. 테스트 결과로 얻어진 고해상도 이미지가 고해상도 메쉬로 다시 변환되면, 저해상도 메쉬에 비해 주름이 잘 표현되며, 경계 부근에서 나타나는 노이즈 문제가 완화된다. 합성 결과에 대한 성능으로는 전통적인 물리 기반 시뮬레이션보다 약 10배 정도 빠른 성능을 보여준다.

• Land and Housing Review
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• v.11 no.3
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• pp.93-101
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• 2020

Recently, as a BIM-based construction simulation system, 4D CAD tools using virtual reality (VR) objects are being applied in construction project. In such a system, since the expression of the object is based on VR image, it has a sense of separation from the real environment, thus limiting the use of field engineers. For this reason, there are increasing cases of applying augmented reality (AR) technology to reduce the sense of separation from the field and express realistic VR objects. This study attempts to develop a methodology and BIM module for the pre-construction verification system using AR technology to increase the practical utility of VR-based BIM objects. To this end, authors develop an AR-based drawing verification function and drawing object-based 4D model augmentation function that can increase the practical utility of 2D drawings, and verify the applicability of the system by performing case analysis. Since VR object-based image has a problem of low realism to field engineers, the linking technology between AR object and 4D model is expected to contribute to the expansion of the use of 4D CADsystem in the construction project.

• Journal of the Korea Convergence Society
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• v.11 no.8
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• pp.99-106
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• 2020

The purpose of this study is to find out whether image similarity between celebrities and brands on social network service be a determinant to predict advertising effectiveness. To this end, an advertising effect prediction model for celebrity endorsed advertising was created and its validity was verified through a machine learning method which is a big data analysis technique. Firstly, the celebrity-brand image similarity, which was used as an independent variable, was quantified by the association network theory with social big data, and secondly a multiple regression model which used data representing advertising effects as a dependent variable was repeatedly conducted to generate an advertising effect prediction model. The accuracy of the prediction model was decided by comparing the prediction results with the survey outcomes. As for a result, it was proved that the validity of the predictive modeling of advertising effects was secured since the classification accuracy of 75%, which is a criterion for judging validity, was shown. This study suggested a new methodological alternative and direction for big data-based modeling research through celebrity-brand image similarity structure based on social network theory, and effect prediction modeling by machine learning.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1828-1836
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• 2015

Object tracking algorithms can reduce computational cost by avoiding computation over the whole image through the selection of region of interests based on object detection. So, accurate object detection is an important task for object tracking. The background subtraction algorithm has been widely used in moving object detection using a stationary camera. However, it has the problem of object detection error due to incorrect background modeling, whereas the method of background modeling has been improved by many researches. This paper proposes a new moving object detection algorithm to overcome the drawback of the conventional background subtraction algorithm by combining the background subtraction algorithm with the motion history image algorithm that is usually used in gesture detection. Although the proposed algorithm demands more processing time because of time taken for combining two algorithms, it meet the real-time processing requirement. Moreover, experimental results show that it has higher accuracy compared with the previous two algorithms.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.101-108
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• 2011

Construction of the Jangbogo antarctic station was planned, and it requires detailed information on topography of the area around the station. The purpose of this research is to generate the topographic map to construct the Jangbogo antarctic station using the satellite image. To do this, surveying and pre-test of equipment were conducted. In addition, for sensor modeling of the GeoEye-1 satellite image, RPC-bias correction was done, and it showed that at least two control points are required. In generating the map, a 1/2,500 scale was deemed suitable in consideration of resolution of the image and the fact that supplementary topographic surveying would be impossible. In order to provide detailed information on the topography around the Jangbogo station, the digital elevation model based on image matching was created, and compared with GPS-RTK data, accuracy of vertical location about 0.6m was exhibited.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.1
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• pp.108-114
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• 2007

This paper presented an image reconstruction method based on the original capsule endoscopy photos yielding a 2-D image for faster diagnosis proposes. The proposed method constructed a 3-D intestine model using the massive images obtained from the capsule endoscope. It merged all images and completed a 3-D model of an intestine. This 3-D model was reformed as a 2-D plane image showing the inner side of the entire intestine. The proposed image composition was evaluated by the 3-D simulator, OpenGL. This approach was demonstrated successfully. A physician can find the location of a disease at a glance because the composite image provided an easy-to-understand view to show the patient's intestine and thereby shorten diagnosis time.