• Spatial Information Research
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• v.6 no.1
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• pp.1-10
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• 1998

The need of aerial photographs is increasing for small area development such as facility management, site planning, residence planning, and so on. It is not an easy task, however, to take aerial photographs using an aircraft for metric photogrammetry because of the strict regulatins of flying and also photographing in Korea, as well as the cost. As one of efficient methods to take large-scale aerial photographs, we investigated the ways of photographing by a remote controlled model plane(RC plane) with a light weight non-metric camera on board. We had examined the principles of RC planes and assembled a RC plane, And test photographing was performed. Even though we obtained reasonably good stereo-pairs for the grounds and facilities using the RC plane, we found there were yet many problems to be solved, such as difficulties of RC plane control, camera focusing, and accumulation of dust on the camera lens.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.609-612
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• 2008

The solid immersion lens (SIL) based near-field recording (NFR) system is considered as one of the high density optical data storage system. For the NFR servo system, tracking servo control is a difficult technology to maintain extremely small gap between SIL and media within one twentieth. This is because the track pitch is decreased for increasing the recording density. In this paper, we propose disturbance observer (DOB) and internal model principle (IMP) for disturbance rejection due to eccentricity of disk. The performance of tracking controller using DOB is increased by about 85%, 94%, 97% using Q filters that have bandwidths of 50Hz, 125Hz, 250Hz, respectively. Moreover, IMP based controller is effectively reduced the residual error.

• Proceedings of the KSEEG Conference
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• 2005.04a
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• pp.148-151
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• 2005

Field-scale DNAPL dissolution is controlled by the topology of DNAPL distributions with respect to the velocity field. A high resolution percolation model was developed and employed to simulate the distribution of DNAPL within source zones. Statistically anisotropic permeability values and capillary parameters were generated for 10${\times}$10${\times}$10 m domains at a resolution of 0.05 to 0.1 m for various statistical properties. TCE leakage was simulated at various rates and the distribution of residual DNAPL in 'fingers' and 'lenses' was computed. Variations in finger and lens geometries, frequencies, average DNAPL saturations, and overall source topology were predicted to be strongly influenced by statistical properties of the medium as well as by injection rate and fluid properties. Model results were found to be consistent with observations from controlled DNAPL release experiments reported in the literature. The computed distributions of aquifer properties and DNAPL were utilized to perform high-resolution numerical simulations of groundwater flow and dissolved transport. Simulations were performed to assess the effect of grout or foam injection in bore holes within the source zone and of shallow point-releases of fluids with various properties on dissolution in DNAPL dissolution rate, even for widely spaced injection points. The results indicate that measures that induced partial flow reductions through DNAPL source zones can significantly decrease dissolution rates from residual DNAPL. The benefit from induced partial flow reductions is two-fold: 1) local flow reduction in DNAPL contaminated zones reduces mass transfer rates, and 2) contaminant flux reductions occur due to the decrease in groundwater velocity

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.2
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• pp.117-137
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• 2010

Iris recognition is a biometric technique which uses unique iris patterns between the pupil and sclera. The advantage of iris recognition lies in high recognition accuracy; however, for good performance, it requires the diameter of the iris to be greater than 200 pixels in an input image. So, a conventional iris system uses a camera with a costly and bulky zoom lens. To overcome this problem, we propose a new method to restore a low resolution iris image into a high resolution image using a single image. This study has three novelties compared to previous works: (i) To obtain a high resolution iris image, we only use a single iris image. This can solve the problems of conventional restoration methods with multiple images, which need considerable processing time for image capturing and registration. (ii) By using bilinear interpolation and a constrained least squares (CLS) filter based on the degradation model, we obtain a high resolution iris image with high recognition performance at fast speed. (iii) We select the optimized parameters of the CLS filter and degradation model according to the zoom factor of the image in terms of recognition accuracy. Experimental results showed that the accuracy of iris recognition was enhanced using the proposed method.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.3
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• pp.171-179
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• 2004

Micro-stereolithography technology has made it possible to fabricate a freeform 3D microslructure. This technology is based on conventional stereolithography, in which a UV laser beam irradiates the open surface of a UV-curable liquid photopolymer, causing it to solidify. In micro-stereolithography, a laser beam of a few $\mu m$ diameter is used to solidify a very small area of the photopolymer. This is one of the key technological elements, and can be achieved by using a focusing lens. Thus, the solidification phenomena of the liquid photopolymer must be carefully investigated. In this study, the photopolymer solidification phenomena in response to variations in the scanning pitch of a focused laser beam was investigated experimentally. The effect of layer thickness on the solidification width and depth was also examined. These studies were conducted under the conditions of relatively lower laser power and relatively higher scanning speed. Moreover, the photopolymer solidification phenomena for the relatively higher laser power and lower scanning speed was investigated, too. In this case, comparing to the case of lower laser power and higher scanning speed, the photopolymer absorbed large amount of irradiation energy of the laser beam. These results were compared with those obtained from a photopolymer solidification model. From these results, a new laser-scanning scheme was proposed according to the shape of the 3D model. Samples by each method were fabricated successfully.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1853-1859
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• 2008

In this paper, we propose a novel method to improve the visual quality of reconstructed images for 3D pattern recognition based on the computational integral imaging reconstruction (CIIR). The proposed CIIR method provides improved 3D reconstructed images by superimposing magnified elemental images by a combination of a round mapping model and image interpolation algorithms. To objectively evaluate the proposed method, we introduce an experimental framework for a computational pickup process and a CIIR process using a Gaussian function and evaluate the proposed method. We also carry out experiments on 3D objects and present their results.

• Korean Medical Education Review
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• v.23 no.3
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• pp.147-153
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• 2021

The coronavirus disease 2019 (COVID-19) pandemic made it necessary for medical schools to restructure their curriculum by switching from face-to-face instruction to various forms of flexible learning. Flexible learning is a student-centered approach to learning that has received interest in many educational sectors. It is a critical strategy for expanding access to higher education during the pandemic. As flexible learning includes online, blended, hybrid, and hyflex learning options, learners have the opportunity to select an instruction modality based on their needs and interests. The shift to flexible learning in medical education took place rapidly in response to the COVID-19 pandemic, and learners, instructors, and schools were not prepared for this instructional change. Through the lens of the technology acceptance model, human agency, and a social constructivist perspective, I examine students, instructors, and educational institutions' roles in successfully navigating the digital transformation era. The pandemic has also accelerated the use of advanced information and communication technologies, such as artificial intelligence and virtual reality, in learning. Through a review of the literature, this paper aimed to reflect on current flexible learning practices from the instructional design and educational technology perspective and explore emerging technologies that may be implemented in future medical education.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.3068-3085
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• 2021

The economics of big data knowledge, especially cloud computing and statistical data of consumer preferences, has attracted increasing academic and industry practitioners' attention. Firms nowadays require purchasing not only external private patent knowledge from other firms, but also proprietary big data knowledge to support their new product development. Extant research investigates pricing strategies of external private patent knowledge and proprietary big data knowledge separately. Yet, a comprehensive investigation of pricing strategies of these two types of knowledge is in pressing need. This research constructs an overarching pricing model of external private patent knowledge and proprietary big data knowledge through the lens of firm profitability as a knowledge transaction recipient. The proposed model can help those firms who purchase external knowledge choose the optimal knowledge structure and pricing strategies of two types of knowledge, and provide theoretical and methodological guidance for knowledge transaction recipient firms to negotiate with knowledge providers.

• Journal of Navigation and Port Research
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• v.46 no.5
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• pp.458-470
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• 2022

As the 4th industrial revolution progresses, the application of several cutting-edge technologies such as the Internet of Things, big data, and mixed reality (MR) in relation to autonomous ships is being considered in the maritime logistics field. The aim of this study was to apply the concept of a digital twin model based on Human Machine Interaction (HMI) including a digital twin model and the role of an operator to a ship. The role of the digital twin is divided into information provision, support, decision, and implementation. The role of the operator is divided into operation, decision-making, supervision, and standby. The system constituting the ship was investigated. The digital twin system that could be applied to the ship was also investigated. The cloud-based digital twin system architecture that could apply investigated applications was divided into ship data collection (part 1), cloud system (part 2), analysis system/ application (part 3), and MR/mobile system (part 4). A Mixed Reality device HoloLens was used as an HMI equipment to perform a simulation test of a digital twin system of an 8 m battery-based electric propulsion ship.

• Computers and Concrete
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• v.31 no.4
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• pp.277-292
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• 2023

Much of our experiments are designed to uncover the cause(s) and effect(s) behind a phenomenon (i.e., data generating mechanism) we happen to be interested in. Uncovering such relationships allows us to identify the true workings of a phenomenon and, most importantly, to realize and articulate a model to explore the phenomenon on hand and/or allow us to predict it accurately. Fundamentally, such models are likely to be derived via a causal approach (as opposed to an observational or empirical mean). In this approach, causal discovery is required to create a causal model, which can then be applied to infer the influence of interventions, and answer any hypothetical questions (i.e., in the form of What ifs? Etc.) that commonly used prediction- and statistical-based models may not be able to address. From this lens, this paper builds a case for causal discovery and causal inference and contrasts that against common machine learning approaches - all from a civil and structural engineering perspective. More specifically, this paper outlines the key principles of causality and the most commonly used algorithms and packages for causal discovery and causal inference. Finally, this paper also presents a series of examples and case studies of how causal concepts can be adopted for our domain.