• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.41.2-41.2
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• 2021

In this study, we generate He I 1083 nm images from Solar Dynamic Observatory (SDO)/Atmospheric Imaging Assembly (AIA) images using a novel deep learning method (pix2pixHD) based on conditional Generative Adversarial Networks (cGAN). He I 1083 nm images from National Solar Observatory (NSO)/Synoptic Optical Long-term Investigations of the Sun (SOLIS) are used as target data. We make three models: single input SDO/AIA 19.3 nm image for Model I, single input 30.4 nm image for Model II, and double input (19.3 and 30.4 nm) images for Model III. We use data from 2010 October to 2015 July except for June and December for training and the remaining one for test. Major results of our study are as follows. First, the models successfully generate He I 1083 nm images with high correlations. Second, the model with two input images shows better results than those with one input image in terms of metrics such as correlation coefficient (CC) and root mean squared error (RMSE). CC and RMSE between real and AI-generated ones for the model III with 4 by 4 binnings are 0.84 and 11.80, respectively. Third, AI-generated images show well observational features such as active regions, filaments, and coronal holes. This work is meaningful in that our model can produce He I 1083 nm images with higher cadence without data gaps, which would be useful for studying the time evolution of chromosphere and coronal holes.

• Journal of Astronomy and Space Sciences
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• v.29 no.2
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• pp.131-140
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• 2012

We presented fundamental stellar parameters and evolutionary statuses of six solar type detached eclipsing binaries whose masses are in the range of 0.97-1.43 $M_{\odot}$. EK Cep and FL Lyr belong to the zero age main sequence. HS Hya, IT Cas and CD Tau are on the main sequence. Their ages are 1.3, 1.9 and 2.2 Gyr, respectively. Both component stars of AI Phe evolved to sub giants and its age is 4.0 Gyr. Those ages of the detached binary systems show good agreement with the time scale for synchronization and circularization of the binary systems.

• Journal of KIBIM
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• v.13 no.3
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• pp.12-20
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• 2023

Deep learning-based anomaly detection technology is used in various fields such as computer vision, speech recognition, and natural language processing. In particular, this technology is applied in various fields such as monitoring manufacturing equipment abnormalities, detecting financial fraud, detecting network hacking, and detecting anomalies in medical images. However, in the field of construction and architecture, research on deep learning-based data anomaly detection technology is difficult due to the lack of digitization of domain knowledge due to late digital conversion, lack of learning data, and difficulties in collecting and processing field data in real time. This study acquires necessary data through IoT (Internet of Things) from the viewpoint of monitoring for environmental management of architectural spaces, converts them into a database, learns deep learning, and then supports anomaly patterns using AI (Artificial Infelligence) deep learning-based anomaly detection. We propose an implementation process. The results of this study suggest an effective environmental anomaly pattern detection solution architecture for environmental management of architectural spaces, proving its feasibility. The proposed method enables quick response through real-time data processing and analysis collected from IoT. In order to confirm the effectiveness of the proposed method, performance analysis is performed through prototype implementation to derive the results.

• Advances in Computational Design
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• v.3 no.4
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• pp.339-366
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• 2018

Parametric design systems serve as powerful assistive tools in the design process by providing a flexible approach for the generation of a vast number of design alternatives. However, contemporary parametric design systems focus primarily on low-level engineering and structural forms, without an explicit means to also take into account high-level, cognitively motivated people-centred design goals. We present a precedent-based parametric design method that integrates people-centred design "precedents" rooted in empirical evidence directly within state of the art parametric design systems. As a use-case, we illustrate the general method in the context of an empirical study focusing on the multi-modal analysis of wayfinding behaviour in two large-scale healthcare environments. With this use-case, we demonstrate the manner in which: (1). a range of empirically established design precedents -e.g., pertaining to visibility and navigation- may be articulated as design constraints to be embedded directly within state of the art parametric design tools (e.g., Grasshopper); and (2). embedded design precedents lead to the (parametric) generation of a number of morphologies that satisfy people-centred design criteria (in this case, pertaining to wayfinding). Our research presents an exemplar for the integration of cognitively motivated design goals with parametric design-space exploration methods. We posit that this opens-up a range of technological challenges for the engineering and development of next-generation computer aided architecture design systems.

• Journal of Digital Contents Society
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• v.12 no.2
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• pp.217-223
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• 2011

AI(Artificial Intelligence) refers to the area of computer engineering and IT technology that focuses on the methodology and creation of intelligent agents. The Othello game is often produced with AI, since it is played with relatively simple rules on a board and on a limited space of 8 rows and 8 columns. Previous algorithms take longer time than desirable and often fail to face new circumstances, as they search for all the possible cases and rules. In order to solve this crucial weakness, we propose that a CBR algorithm be applied to Orthello. Case-Based Reasoning(CBR), is the process of solving new problems based on the solutions of the past similar problems. We can apply this process to Othello and expedite the process of computer reasoning for a solution to new cases based on the data from accumulated past cases. Then, these new solutions are dynamically added to the set of past cases so that it becomes harder for players(users) to be able to read the pattern. The proposed system in which a CBR algorithm is applied to the Othello game makes the computation process faster and the game harder to play.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12A
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• pp.1181-1187
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• 2010

This paper proposes a mobile AI (Artificial Intelligence) conducting decision-making in the game through education for intelligent character on the basis of Neural Network. Neural Network is learned through the input/output value of the algorithm which defines the game rule and the problem solving method. The learned character is able to perceive the circumstances and make proper action. In this paper, the mobile AI using Neural Network has been step-by-step designed, and a simple game has been materialized for its functional experiment. In this game, the goal, the character, and obstacles exist on regular 2D space, and the character, evading obstacles, has to move where the goal is. The mobile AI can achieve its goals in changing environment by learning the solution to several problems through the algorithm defined in each experiment. The defined algorithm and Neural Network are designed to make the input/output system the same. As the experimental results, the suggested mobile AI showed that it could perceive the circumstances to conduct action and to complete its mission. If mobile AI learns the defined algorithm even in the game of complex structure, its Neural Network will be able to show proper results even in the changing environment.

• Journal of Astronomy and Space Sciences
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• v.29 no.2
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• pp.221-232
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• 2012

We analyzed the manufacturing procedure, specifications, repair history, and details of celestial movements of the water-hammering type $Honsang$ (celestial globe). Results from our study on the remaining $Honsangs$ in China and Japan and on the reconstruction models in Korea were applied to our conceptual design of the water-hammering type $Honsang$. A $Honui$ (armillary sphere) and $Honsang$ using the water-hammering method were manufactured in $Joseon$ in 1435 (the 17th year of King $Sejong$). $Jang$ $Yeong-Sil$ developed the $Honsang$ system based on the water-operation method of $Shui$ $y{\ddot{u}}n$ $i$ $hsiang$ $t'ai$ in China. Water-operation means driving water wheels using a water flow. The most important factor in this type of operation is the precision of the water clock and the control of the water wheel movement. The water-hammering type $Honsang$ in $Joseon$ probably adopted the $Cheonhyeong$ (天衡; oriental escapement device) system of $Shui$ $y{\ddot{u}}n$ $i$ $hsiang$ $t'ai$ in China and the overflow mechanism of $Jagyeongnu$ (striking clepsydra) in $Joseon$, etc. In addition to the $Cheonryun$ system, more gear instruments were needed to stage the rotation of the $Honsang$ globe and the sun's movement. In this study, the water-hammering mechanism is analyzed in the structure of a water clock, a water wheel, the $Cheonhyeong$ system, and the $Giryun$ system, as an organically working operation mechanism. We expect that this study will serve as an essential basis for studies on $Heumgyeonggaknu$, the water-operating astronomical clock, and other astronomical clocks in the middle and latter parts of the $Joseon$ dynasty.

• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.178-185
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• 2021

Three-dimensional high-resolution magnetic resonance imaging (MRI) provides fine-level anatomical information for disease diagnosis. However, there is a limitation in obtaining high resolution due to the long scan time for wide spatial coverage. Therefore, in order to obtain a clear high-resolution(HR) image in a wide spatial coverage, a super-resolution technology that converts a low-resolution(LR) MRI image into a high-resolution is required. In this paper, we propose a super-resolution technique through filter learning based on information on the surrounding gradient information in 3D space from 3D MRI images. In the learning step, the gradient features of each voxel are computed through eigen-decomposition from 3D patch. Based on these features, we get the learned filters that minimize the difference of intensity between pairs of LR and HR images for similar features. In test step, the gradient feature of the patch is obtained for each voxel, and the filter is applied by selecting a filter corresponding to the feature closest to it. As a result of learning 100 T1 brain MRI images of HCP which is publicly opened, we showed that the performance improved by up to about 11% compared to the traditional interpolation method.

• Journal of the Korean Society of Industry Convergence
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• v.9 no.1
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• pp.61-66
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• 2006

In perspective of saving natural resource and energy, today's automobiles are in process of regenerating by smaller and lighter. In order to achieve the sufficiency on the consumption of the fuel, new mechanism and new assembly are required. Therefore the expectations on the new materials are very high. Especially, AI materials are widely used to reduce the weight. AI that is used in automobiles is mostly casting material, and according to the innovation of technique is in rapid development. AI Die casting is an important field as today's trend of lightweight on automobiles. One of the parts in steering system, Valve Housing plays a role of reduce the operating effort of drivers. Unfortunately, the Valve Housing which is widely reliable to the most automobiles are not developed at this moment in our automobile industry. Therefore, they are produced by casting method which cost three times or even more expensive in production. If Valve Housing, which is a part of steering system is produced by Gravity Casting, the space that manufacturing equipment will be increased, and more time and workers would be brought into service. For such reason, Die Casting would replace Gravity Casting in order to minimize cost of time, manpower, and working space.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.8
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• pp.674-682
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• 2014

Radio Frequency Test Set (RFTS) is essential to verify Telemetry, Command & Ranging (TC&R) RF subsystem of both Low Earth Orbit (LEO) and Geostationary Earth Orbit (GEO) satellite during Assembly Integration & Test (AI&T). The existing RFTS was specialized for each project and needed to be modified for each new satellite. The new design enables RFTS to be used in various projects. The hardware and software was designed considering this and therefore it could be directly used in other projects within a similar test period without modification or inconvenience. It will be also easily controlled, modified, and managed through the extension in modularization according to each function and the use of COTS (commercial on-the-self) and this will improve system reliability. A more reliable RF test measurement is also provided in this new RFTS by using an accurate reference clock signal.