• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.203-212
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• 2019

Along with the recent fourth industrial revolution, the world's manufacturing powerhouses are pushing for national strategies to revive the sluggish manufacturing industry. Moon Jae-in, the government is in accordance with the trend, called 'advancement of science and technology is leading the fourth round of the Industrial Revolution' strategy. Intelligent information technology such as IoT, Cloud, Big Data, Mobile, and AI, which are key technologies that lead the fourth industrial revolution, is promoting the emergence of new industries such as robots and 3D printing and the smarting of existing major manufacturing industries. Advances in technologies such as smart factories have enabled IoT-based sensing technology to measure various data that could not be collected before, and data generated by each process has also exploded. Thus, this paper uses data generators to generate virtual data that can occur in smart factories, and uses them to analyze the cause of the defect in real time and to predict the replacement cycle of the facility.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.533-540
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• 2021

To evaluate the performance of a system, one-dimensional 3-neighborhood cellular automata(CA) based pseudo-random generators are widely used in many fields. Although two-dimensional CA and one-dimensional 5-neighborhood CA have been applied for more effective key sequence generation, designing symmetric one-dimensional 5-neighborhood CA corresponding to a given primitive polynomial is a very challenging problem. To solve this problem, studies on one-dimensional 5-neighborhood CA synthesis, such as synthesis method using recurrence relation of characteristic polynomials and synthesis method using Krylov matrix, were conducted. However, there was still a problem with solving nonlinear equations. To solve this problem, a symmetric one-dimensional 5-neighborhood CA synthesis method using a transition matrix of 90/150 CA and a block matrix has recently been proposed. In this paper, we detail the theoretical process of the proposed algorithm and use it to obtain symmetric one-dimensional 5-neighborhood CA corresponding to high-order primitive polynomials.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.861-866
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• 2023

Unlike conventional smart farms that require chemical fertilizers and large spaces, aquaponics farming, which utilizes the symbiotic relationship between aquatic organisms and crops to grow crops even in abnormal environments such as environmental pollution and climate change, is being actively researched. Different crops require different environments and nutrients for growth, so it is necessary to configure the ratio of aquatic organisms optimized for crop growth. This study proposes a method to measure the degree of growth based on area and volume using image processing techniques in an aquaponics environment. Tilapia, carp, catfish, and lettuce crops, which are aquatic organisms that produce organic matter through excrement, were tested in an aquaponics environment. Through 2D and 3D image analysis of lettuce and real-time data analysis, the growth degree was evaluated using the area and volume information of lettuce. The results of the experiment proved that it is possible to manage cultivation by utilizing the area and volume information of lettuce. It is expected that it will be possible to provide production prediction services to farmers by utilizing aquatic life and growth information. It will also be a starting point for solving problems in the changing agricultural environment.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.173-186
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• 2024

This paper analyzes a case of successful faculty entrepreneurship through a coupled process of open innovation in a university context, using the core competency theory perspective. Initially, the current state of faculty entrepreneurship is examined, and the effects of interdisciplinary coupled processes of open innovation are explored, focusing on the case of 'Omotion Inc.,' a startup utilizing generative AI technology for hyper-realistic 3D virtual human experiences. The research methodology involves in-depth interviews with Omotion Inc.'s co-founders, technology commercialization professionals, and experts in the field, followed by analysis based on foundational theories. Applying the core competency theory, this paper scrutinizes the process of integrating diverse expertise and technologies from various academic disciplines. The analysis goes beyond the limitations of faculty entrepreneurship confined to a single technology-centric research domain. Instead, it explores the possibilities of enhancement and value creation through coupled processes, providing practical implications for the university entrepreneurial ecosystem. The aim is to extend the traditional roles of education and research within the university, presenting a role in economic value creation beyond the boundaries of conventional faculty entrepreneurship. Through the collaboration of two faculty members, this study showcases the creation of novel technology and business models. It establishes that successful coupled processes of open innovation in faculty entrepreneurship, from a core competency theory perspective, require the entrepreneurial firm to possess (1) entrepreneurial capabilities, (2) technological capabilities, and (3) networking capabilities. The implications of this research highlight the positive impact of coupled processes of open innovation in faculty entrepreneurship, as evidenced by the Omotion Inc. case, offering guidance on entrepreneurial directions for university members preparing for entrepreneurship.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.333-342
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• 2022

Cellular Automata (CA) is a discrete and abstract computational model that is being applied in various fields. Applicable as an excellent pseudo-random sequence generator, CA has recently developed into a basic element of cryptographic systems. Several studies on CA-based stream ciphers have been conducted and it has been observed that the encryption strength increases when the radius of a CA's neighbor is increased when appropriate CA rules are used. In this paper, among CAs that can be applied as a one-dimensional pseudo-random number sequence generator (PRNG), one-dimensional 5-neighbor CAs are classified according to the connection state of their neighbors, and the ignition relationship of the characteristic polynomial is obtained. Also this paper propose a synthesis algorithm for an asymmetric 1-D linear 5-neighbor MLCA in which the radius of the neighbor is increased by 2 using the one-dimensional 3-neighbor 90/150 CA state transition matrix.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.91-108
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• 2022

In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.

• Journal of the Korea Computer Graphics Society
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• v.28 no.3
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• pp.125-134
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• 2022

This paper implements an AR manual for a vehicle that can be used even in the vehicle interior space where it is difficult to apply the augmentation method of AR content, which is mainly used, and applies a deep learning model to improve the augmentation matching between real space and virtual objects. Through deep learning, the logo of the steering wheel is recognized regardless of the position, angle, and inclination, and 3D interior space coordinates are generated based on this, and the virtual button is precisely augmented on the actual vehicle parts. Based on the same learning model, the function to recognize the main warning light symbols of the vehicle is also implemented to increase the functionality and usability as an AR manual for vehicles.

• Clinical and Experimental Pediatrics
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• v.49 no.2
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• pp.150-156
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• 2006

Purpose : The aims of this study included assessment of molecular-epidemiologic features during an outbreak of colonization of extended spectrum ${\beta}$-lactamase producing Klebsiella pneumoniae(ESBL-KPN) and re-evaluation of their colonized status one year later. Methods : Rectal swab cultures for ESBL-KPN from all hospitalized infants and newly admitted infants were obtained during the outbreak of colonization from July to December, 2000. The pattern of XbaI-digested chromosomal DNA of isolates were analyzed by pulsed-field gel electrophoresis. Weekly rectal swab cultures were obtained during the outbreak until patients were either discharged or decolonized. Patients discharged after being colonized had follow up stool cultures a year later. Results : A total of 80 patients(28.5 percent) were colonized. Of those, 53 whose pulsed-field gel electrophoresis(PFGE) was possible only once, were ESBL-KPN grouped into six cluster clones and 10 single clones : 28 patients(52.8 percent) were colonized with type A, the most common clone, followed by type B in 11 patients(20.8 percent). Of those 12 patients in whom serial PFGE was done more than twice, type A was predominant. Narrowed-down in strains occurred from types A, B, C, D and three single clones at initiation of the study into types A and type B after three months of strict infection control. Among 75 patients(93.7 percent) who were sent home after being colonized, 30 patients were re-called for stool cultures a year later : All of them were decolonized. Conclusion : This study demonstrates the importance of infection control as the diversity of ESBL-KPN strains could be narrowed into fewer strains. Colonization of ESBL-KPN could be reversed upon return to the community.

• Applied Chemistry for Engineering
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• v.5 no.3
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• pp.385-394
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• 1994

Numerical solutions were obtained to the model equations for various of the parameters characterizing the pore structure, effective internal diffusion, and the chemical reaction constant. The conversion was decreased with the cause of pore closure at the surface of reacting particles, reduction of porosity, surface area of reaction and effective diffusion coefficient in the solid with the progress of reaction. Total conversion was strongly dependent on the local conversion at surface. According to the decreasing of impregnated concentration of the copper oxide and the increase of the flue gases concentration, total conversion was increased. The conversion was affected by gas flow rate and pore size distribution in the reacting solid.

• Solar Energy
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• v.17 no.4
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• pp.3-11
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• 1997

Because grain boundaries in polycrystalline silicon act as potential barriers and recombination centers for the photo-generated charge carriers, these defects degrade conversion effiency of solar cell. To reduce these effects of grain boundaries, we investigated various influencing factors such as thermal treatment, various grid pattern, selective wet etching for grain boundaries, buried contact metallization along grain boundaries, grid on metallic thin film. Pretreatment above $900^{\circ}C$ in $N_2$ atmosphere, gettering by $POCl_3$ and Al treatment for back surface field contributed to obtain a high quality poly-Si. To prevent carrier losses at the grain boundaries, we carried out surface treatment using Schimmel etchant. This etchant delineated grain boundaries of $10{\mu}m$ depth as well as surface texturing effect. A metal AI diffusion into grain boundaries on rear side reduced back surface recombination effects at grain boundaries. A combination of fine grid with finger spacing of 0.4mm and buried electrode along grain boundaries improved short circuit current density of solar cell. A ultra-thin Chromium layer of 20nm with transmittance of 80% reduced series resistance. This paper focused on the grain boundary effect for terrestrial applications of solar cells with low cost, large area, and high efficiency.