• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.115-122
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• 2019

We In this study, We tested for artificial intelligence-based virtual space story books were planned. The proposed virtual space concept, a story book with the characteristics of Augmented Virtuality, was implemented Several steps are needed to proceed with the virtual space storybook's story. First, a user brings a real object in to virtual space and recognizes the real object with an artificial intelligence-based object-recognition software. Second, when object recognition progresses, the virtual 3D model is augmented in the virtual space, which is then inserted into the virtual space and rendered. Finally, software projected a virtual space storybook on the desk in which users can touch and select real-objects. This virtual space storybook was implemented using the new story-making technology by applying the virtual space concept. the Augmented Virtuality concept is to augment real objects based on virtual space. To confirm this we tested a user test using the virtual space storybook. the user seemed as if can the distinction between real objects and virtual images. Also very well and that understood the process of putting the real objects in virtual space.

• Journal of Astronomy and Space Sciences
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• v.30 no.3
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• pp.187-192
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• 2013

Honsangui (celestial globe) which is a water-hammering method astronomical clock is recorded in "Juhaesuyong" which is Volume VI of supplement from "Damheonseo", written by Hong Dae-Yong (1731~1783). We made out the conceptual design of Hong Dae-Yong's Honsangui through the study on its structure and working mechanism. Honsangui consist of three rings and two layers, the structure of rings which correspond to outer layer is similar to his own Tongcheonui (armillary sphere) which is a kind of armillary sphere. Honsang sphere which correspond to inner layer depicts constellations and milky way and two beads hang on it as Sun and Moon respectively for realize the celestial motion. Tongcheonui is operated by the pendulum power but Honsangui is operated by water-hammering method mechanism. This Honsangui's working mechanism is the traditional way of Joseon and it was simplified the working mechanism of Shui y$\ddot{u}$n i hsiang t'ai which is a representative astronomical clock of China. This record of Honsangui is the only historical record about the water-hammering method working mechanism of Joseon Era and it provide the study of water-hammering method mechanism with a vital clue.

• Korean Journal of Cognitive Science
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• v.23 no.2
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• pp.133-164
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• 2012

Paul Churchland(1989) suggests the theory of representation from the results of cognitive biology and connectionist AI studies. According to the theory, our representations of the diverse phenomena in the world can be represented as the positions of phase state spaces with the actions of the neurons or of the assembly of neurons. He insists connectionist AI neural networks can have the semantical category systems to recognize the world. But Fodor and Lepore(1996) don't look the perspective bright. From their points of view, the Churchland's theory of representation stands on the base of Quine's holism, and the network semantics cannot explain how the criteria of semantical content similarity could be possible, and so cannot the theory. This thesis aims to excavate which one is the better between the perspective of the theory and the one of Fodor and Lepore's. From my understandings of state space theory of representation, artificial nets can coordinates the criteria of contents similarity by the learning algorithm. On the basis of these, I can see that Fodor and Lepore's points cannot penetrate the Churchlands' theory. From the view point of the theory, we can see how the future's artificial systems can have the conceptual systems recognizing the world. Therefore we can have the perspectives what cognitive scientists have to focus on.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.63-80
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• 2022

As a technology to analyze and predict an issue has been developed by constructing real space into virtual space, it is becoming more important to acquire precise spatial information in complex cities. In this study, images were acquired using an unmanned aerial vehicle for urban area with complex landscapes, and land cover classification was performed object-based image analysis and semantic segmentation techniques, which were image classification technique suitable for high-resolution imagery. In addition, based on the imagery collected at the same time, the replicability of land cover classification of each artificial intelligence (AI) model was examined for areas that AI model did not learn. When the AI models are trained on the training site, the land cover classification accuracy is analyzed to be 89.3% for OBIA-RF, 85.0% for OBIA-DNN, and 95.3% for U-Net. When the AI models are applied to the replicability assessment site to evaluate replicability, the accuracy of OBIA-RF decreased by 7%, OBIA-DNN by 2.1% and U-Net by 2.3%. It is found that U-Net, which considers both morphological and spectroscopic characteristics, performs well in land cover classification accuracy and replicability evaluation. As precise spatial information becomes important, the results of this study are expected to contribute to urban environment research as a basic data generation method.

• Clean Technology
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• v.28 no.4
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• pp.331-338
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• 2022

The objective of this study is to prepare bead-type and pellet-type Pt (1 wt%)/Kieselguhr catalysts as hydrogenation catalysts for the polycyclic aromatic hydrocarbons (PAHs) included in pyrolysis fuel oil (PFO). The optimal reaction temperature to maximize the yield of saturated cyclic hydrocarbons during the PFO-cut hydrogenation reaction in a trickle bed reactor was determined to be 250 ℃. A hydrogen/PFO-cut flow rate ratio of 1800 was found to maximize 1-ring saturated cyclic compounds. The yield of saturated cyclic compound increased as the space velocity (LHSV) of PFO-cut decreased. The difference in hydrogenation reaction performance between the pellet catalyst and the bead catalyst was negligible. However, the catalyst impregnated by Pt after molding the Kieselguhr support (AI catalyst) showed higher hydrogenation activity than the catalyst molded after Pt impregnation on the Kieselguhr powder (BI catalyst), which was a common phenomenon in both the pellet catalysts and bead catalysts. This may be due to a higher number of active sites over the AI catalyst compared to the BI catalyst. It was confirmed that the pellet catalyst prepared by the AI method had the best reaction activity of the prepared catalysts in this study. The majority of the PFO-cut hydrogenation products were cyclic hydrocarbons ranging from C₈ to C₁₅, and C₁₁ cyclic hydrocarbons had the highest distribution. It was confirmed that both a cracking reaction and hydrogenation occurred, which shifted the carbon number distribution towards light hydrocarbons.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.1
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• pp.1-7
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• 2023

An artificial intelligence (AI) method based on image deep learning is proposed to predict the entire displacement shape of a structure using the feature of partial displacements. The performance of the method was investigated through a structural test of a steel frame. An image-to-image regression (I2IR) training method was developed based on the U-Net layer for image recognition. In the I2IR method, the U-Net is modified to generate images of entire displacement shapes when images of partial displacement shapes of structures are input to the AI network. Furthermore, the training of displacements combined with the location feature was developed so that nodal displacement values with corresponding nodal coordinates could be used in AI training. The proposed training methods can consider correlations between nodal displacements in 3D space, and the accuracy of displacement predictions is improved compared with artificial neural network training methods. Displacements of the steel frame were predicted during the structural tests using the proposed methods and compared with 3D scanning data of displacement shapes. The results show that the proposed AI prediction properly follows the measured displacements using 3D scanning.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.23 no.4
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• pp.301-327
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• 2019

The proper orthogonal decomposition (POD) method for time-dependent problems significantly reduces the computational time as it reduces the original problem to the lower dimensional space. Even a higher degree of reduction can be reached if the solution is smooth in space and time. However, if the solution is discontinuous and the discontinuity is parameterized e.g. with time, the POD approximations are not accurate in the reduced space due to the lack of ability to represent the discontinuous solution as a finite linear combination of smooth bases. In this paper, we propose to post-process the sample solutions and re-initialize the POD approximations to deal with discontinuous solutions and provide accurate approximations while the computational time is reduced. For the post-processing, we use the Gegenbauer reconstruction method. Then we regularize the Gegenbauer reconstruction for the construction of POD bases. With the constructed POD bases, we solve the given PDE in the reduced space. For the POD approximation, we re-initialize the POD solution so that the post-processed sample solution is used as the initial condition at each sampling time. As a proof-of-concept, we solve both one-dimensional linear and nonlinear hyperbolic problems. The numerical results show that the proposed method is efficient and accurate.

• The Journal of Korea Robotics Society
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• v.16 no.2
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• pp.112-121
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• 2021

Unlike a typical small-sized robot navigating in a free space, an autonomous vehicle has to travel in a designated road which has lanes to follow and traffic rules to obey. High-Definition (HD) maps, which include road markings, traffic signs, and traffic lights with high location accuracy, can help an autonomous vehicle avoid the need to detect such challenging road surroundings. With space constraints and a pre-built HD map, a new type of path planning algorithm can be conceived as a substitute for conventional grid-based path planning algorithms, which require substantial planning time to cover large-scale free space. In this paper, we propose an obstacle-avoiding, cost-based planning algorithm in a continuous space that aims to pursue a globally-planned path with the help of HD map information. Experimentally, the proposed algorithm is shown to outperform other state-of-the-art path planning algorithms in terms of computation complexity in a typical urban road setting, thereby achieving real-time performance and safe avoidance of obstacles.

• Smart Media Journal
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• v.13 no.1
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• pp.24-35
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• 2024

The combination of Artificial Intelligence and the Internet of Things (AIoT) has gained significant popularity. Deep neural networks (DNNs) have demonstrated remarkable success in various applications. However, deploying complex AI models on embedded boards can pose challenges due to computational limitations and model complexity. This paper presents an AIoT-based system for smart parking lots using edge devices. Our approach involves developing a detection model and a decision tree for occupancy status classification. Specifically, we utilize YOLOv5 for car license plate (LP) detection by verifying the position of the license plate within the parking space.

• Archives of design research
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• v.14 no.2
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• pp.175-185
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• 2001

This study is concerned about the meaning of space-direction in environmental design and its form for examples of Javacheff Christo's works. As environmental design that space-direction is very important thing, but it is difficult to find some concreted style. Even more there are greatly indistinct in the boundary between environmental art and environmental design. Studying on Cristo's work which is valuable way of using space-direction. We will applicate for needful methods in environmental design. Christo's works are divided three boundary. ai. environmental wrapping, environmental installation, environmental partition. His way of space-direction that is dramatic, participating in process, concentrating in place-specific, and various way of utilizing object. It is meaningful study that survey to Christo's works. They present as environmentally directing object, showing situation, and building experience of space. So it is possible to judge the evaluation of his works. Finally, space-direction that finding in Christo's work is very useful way in environmental design process.