• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.667-677
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• 2013

The introduction of a new transit facility affects mode share of travel alternatives. The multinomial logit model, which has been the most commonly used for estimating mode share, has difficulty in reflecting heterogeneity of travelers' choices, and it has a limitation on grasping their characteristics of mode choice. The limitation may lead to over- or under-estimation of the new transit facility and bring about significant social costs. This paper aims to find a methodology to overcome the problem of preference homogeneity. It also applies market segmentation structure of separating the whole population into direct and indirect beneficiary to consider their preference heterogeneity. A mode choice model is estimated on data from Jeju Province and statistically tested. The results show that mode transfer rate of direct beneficiaries that inhabit in downtown areas increases as the new transit facility provides more advanced services with higher costs. The results and the model suggested in this study can contribute to improving the accuracy of demand forecasting of new transit facilities by reflecting heterogeneity of mode-transfer patterns.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.572-578
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• 2009

This paper introduce a structure of haptic collaboration system over high resolution tiled-display, and proposes a object based efficient display method for high resolution display in integrated system. in addition, a modeling of visualization system is defined to evaluate performance of the proposed method. Both haptic system and tiled-display system have requirements of computational power. A haptic device is unstable if haptic rendering rate is less than 1kHz. A requirement of tiled-display systems is frame rate of display. It requires update of 30 frame fer sec. If we use these systems independently, we can satisfy each requirements. However, if we integrate two systems, performance of entire system significantly decreases because of lack of resources. In this paper, therefore, we propose a segmentation-based display method for ultra high resolution display in integrated system. The proposed method reduces redundancy of display data by reducing a display rate of static objects. Finally, a modeling of visualization system is defined to evaluate performance of the proposed method.

• Journal of KIISE
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• v.44 no.4
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• pp.392-398
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• 2017

The point-cloud representation of an object is performed by scanning a space through a laser scanner that is extracting a set of points, and the points are then integrated into the same coordinate system through a registration. The set of the completed registration-integrated point clouds is classified into meaningful regions, shapes, and noises through a mathematical analysis. In this paper, the aim is the matching of a curved area like a cylinder shape in 3D point-cloud data. The matching procedure is the attainment of the center and radius data through the extraction of the cylinder-shape candidates from the sphere that is fitted through the RANdom Sample Consensus (RANSAC) in the point cloud, and completion requires the matching of the curved region with the Catmull-Rom spline from the extracted center-point data using the Principal Component Analysis (PCA). Not only is the proposed method expected to derive a fast estimation result via linear and curved cylinder estimations after a center-axis estimation without constraint and segmentation, but it should also increase the work efficiency of reverse engineering.

• The KIPS Transactions:PartA
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• v.9A no.2
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• pp.259-266
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• 2002

In this paper we implemented various image processing filtering using the format converter. This design method is based on realized the large processor-per-pixel array by integrated circuit technology. These two types of integrated structure are can be classify associative parallel processor and parallel process DRAM (or SRAM) cell. Layout pitch of one-bit-wide logic is Identical memory cell pitch to array high density PEs in integrate structure. This format converter design has control path implementation efficiently, and can be utilize the high technology without complicated controller hardware. Sequence of array instruction are generated by host computer before process start, and instructions are saved on unit controller. Host computer is executed the pixel-parallel operation starting at saved instructions after processing start. As a result, we obtained three result that 1) simple smoothing suppresses higher spatial frequencies, reducing noise but also blurring edges, 2) a smoothing and segmentation process reduces noise while preserving sharp edges, and 3) median filtering may be applied to reduce image noise. Median filtering eliminates spikes while maintaining sharp edges and preserving monotonic variations in pixel values.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.8-19
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• 2020

We see an energy fucused smart city evolution of the UK along with the project of "Smart London Plan (SLP)." A theoretical logic of business model innovation has been discussed and a research framework of evolving energy focused smart city is formulated. The starting point is the silo system. In the second stage, the private investment in smart meters establishes a basement for next stages. As results, the UK's smart energy sector has evolved from smart meter installation through smart grid to new business models such as water-energy nexus and microgrid. Before smart meter installation of the government, the electricity system was centralized. However, after consumer engagement plan has been set to make them understand benefits that they can secure through smart meters, the customer behavior has been changed. The data analytics firm enables greater understanding of consumer behavior and it helps energy industry to be smart via controlling, securing and using that data to improve the energy system. In the third stage, distribution network operators (DNOs)' access to smart meter data has been allowed and the segmentation starts. In the fourth stage, with collaboration of Ofwat and Ofgem, it is possible to eliminate unnecessary duplication of works and reduce interest conflict between water and electricity. In the fifth stage, smart meter and grid has been integrated as an "adaptive" system and a transition from DNO to DSO is accomplished for the integrated operation. Microgrid is a prototype for an "adaptive" smart grid. Previous steps enable London to accomplish a platform leadership to support the increasing electrification of the heating and transport sector and smart home.

• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.18-25
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• 2021

In many developed countries, such as South Korea, efficiently maintaining the aging infrastructures is an important issue. Currently, inspectors visually inspect the infrastructure for maintenance needs, but this method is inefficient due to its high costs, long logistic times, and hazards to the inspectors. Thus, in this paper, a novel crack inspection approach for concrete bridges is proposed using integrated image processing techniques. The proposed approach consists of four steps: (1) training a deep learning model to automatically detect cracks on concrete bridges, (2) acquiring in-situ images using a drone, (3) generating orthomosaic images based on 3D modeling, and (4) detecting cracks on the orthmosaic image using the trained deep learning model. Cascade Mask R-CNN, a state-of-the-art instance segmentation deep learning model, was trained with 3235 crack images that included 2415 hard negative images. We selected the Tancheon overpass, located in Seoul, South Korea, as a testbed for the proposed approach, and we captured images of pier 34-37 and slab 34-36 using a commercial drone. Agisoft Metashape was utilized as a 3D model generation program to generate an orthomosaic of the captured images. We applied the proposed approach to four orthomosaic images that displayed the front, back, left, and right sides of pier 37. Using pixel-level precision referencing visual inspection of the captured images, we evaluated the trained Cascade Mask R-CNN's crack detection performance. At the coping of the front side of pier 37, the model obtained its best precision: 94.34%. It achieved an average precision of 72.93% for the orthomosaics of the four sides of the pier. The test results show that this proposed approach for crack detection can be a suitable alternative to the conventional visual inspection method.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.6
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• pp.267-275
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• 2023

This paper presents the development of specialized software for annotating volume-of-interest on ¹⁸F-FDG PET/CT images with the goal of facilitating the studies and diagnosis of head and neck cancer (HNC). To achieve an efficient annotation process, we employed the SE-Norm-Residual Layer-based U-Net model. This model exhibited outstanding proficiency to segment cancerous regions within ¹⁸F-FDG PET/CT scans of HNC cases. Manual annotation function was also integrated, allowing researchers and clinicians to validate and refine annotations based on dataset characteristics. Workspace has a display with fusion of both PET and CT images, providing enhance user convenience through simultaneous visualization. The performance of deeplearning model was validated using a Hecktor 2021 dataset, and subsequently developed semi-automatic annotation functionalities. We began by performing image preprocessing including resampling, normalization, and co-registration, followed by an evaluation of the deep learning model performance. This model was integrated into the software, serving as an initial automatic segmentation step. Users can manually refine pre-segmented regions to correct false positives and false negatives. Annotation images are subsequently saved along with their corresponding ¹⁸F-FDG PET/CT fusion images, enabling their application across various domains. In this study, we developed a semi-automatic annotation software designed for efficiently generating annotated lesion images, with applications in HNC research and diagnosis. The findings indicated that this software surpasses conventional tools, particularly in the context of HNC-specific annotation with ¹⁸F-FDG PET/CT data. Consequently, developed software offers a robust solution for producing annotated datasets, driving advances in the studies and diagnosis of HNC.

• Journal of the Korean Society of Systems Engineering
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• v.15 no.2
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• pp.72-78
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• 2019

Pathology is the motor that drives healthcare to understand diseases. The way pathologists diagnose diseases, which involves manual observation of images under a microscope has been used for the last 150 years, it's time to change. This paper is specifically based on tumor detection using deep learning techniques. Pathologist examine the specimen slides from the specific portion of body (e-g liver, breast, prostate region) and then examine it under the microscope to identify the effected cells among all the normal cells. This process is time consuming and not sufficiently accurate. So, there is a need of a system that can detect tumor automatically in less time. Solution to this problem is computational pathology: an approach to examine tissue data obtained through whole slide imaging using modern image analysis algorithms and to analyze clinically relevant information from these data. Artificial Intelligence models like machine learning and deep learning are used at the molecular levels to generate diagnostic inferences and predictions; and presents this clinically actionable knowledge to pathologist through dynamic and integrated reports. Which enables physicians, laboratory personnel, and other health care system to make the best possible medical decisions. I will discuss the techniques for the automated tumor detection system within the new discipline of computational pathology, which will be useful for the future practice of pathology and, more broadly, medical practice in general.

• Korean Business Review
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• v.12
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• pp.1-27
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• 1999

The author focus on the role of IMC(integrated marketing communication)that is important for increase of relationship equity value, stress on the integration of IMC and PR in relationship marketing. This paper present as follow. The first, marketing thought have evolved through market competition situation at a market segmentation level perspective, and the concept of relationship equity is necessary to individual marketing or relationship marketing. The second, firm should identify profitable customer, build strong relationship for relationship equity, based on customer equity and life time value in customer market. The third, IMC needs integration with PR for relationship building of stakeholder including customer market at a point of view of corporate equity. Finally, this article offer discussion about implications of integration IMC and PR for future study.

• JSTS:Journal of Semiconductor Technology and Science
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• v.12 no.3
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• pp.320-330
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• 2012

In this paper, we investigate the power integrity of grid structures for power and ground distribution on printed circuit board (PCB). We propose the 2D transmission line method (TLM)-based model for efficient frequency-dependent impedance characterization and PCB-package-integrated circuit (IC) co-simulation. The model includes an equivalent circuit model of fringing capacitance and probing ports. The accuracy of the proposed grid model is verified with test structure measurements and 3D electromagnetic (EM) simulations. If the grid structures replace the plane structures in PCBs, they should provide effective shielding of the electromagnetic interference in mobile systems. An analytical model to predict the shielding effectiveness (SE) of the grid structures is proposed and verified with EM simulations.