• Journal of the Korea Furniture Society
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• v.20 no.5
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• pp.467-479
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• 2009

The high-tech computer technology developments have greatly affected the area of design education. Starting from the mid 80s, innovations in visual presentation methods have heightened with 2D computer graphic programs, CAD & 3D modeling, and Rapid Prototype that allows dimensional generation. The specialty and quality in design studio education have advanced due to the development in presentation methods such as Power Point and Keynote. But there are many problems with the current method of presenting the visual outcome in a data format using beam projectors, which is a vertical presenting method compared to the old studio study method of conducting discussions and reviews based on the substantial outcome. The essence of studio study that allows for comparisons and analysis by horizontally opening up the various work outcomes is being offset. Also the requirement for manual idea sketching work that plays an important role in the initial design phase continuing to decrease due to the digital working process dependence and cumbersome procedures in the presentation. In order to resolve this problem, the CALM system (Class Applied LCD Modular System) has been developed that replaces the method of attaching the sketches or renderings on the wall with a digital multi-display system. In a nutshell, individuals will upload the outcomes online and display them on the CALM system studio that is composed of 32 LCD (Columns: 4 $\times$ Rows: 8) monitors that are 19 inches in size so that various personnel can openly study the design outcomes. Also the central 42 inch PDP monitor that offers touch pad capability allows each design outcome to be described and examined by expanding. The concept phase of this development process has elevated to the production of an operating prototype that is being reviewed of its practicality. It is considered that the development of this system will decrease the extreme tendency of depending on digital operation but achieve revitalization of a more realistic and opened studio study environment compared to the individual consulting method of the old study approach.

• Journal of the Korean Magnetics Society
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• v.19 no.1
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• pp.35-42
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• 2009

Among the next generation memory, MRAM (Magnetic Random Access Memory) is worthy of notice for substituting the preexisting memory thanks to its non-volatile property and other advantages. Recently perpendicular MRAM and spin transfer torque MRAM techniques are under active investigation to realize a high density and low power consumption. As a result, there are increasing of patents applications for high density, low current density for magnetization switching and high thermal stability. In this paper, we analyze the trend of patent applications and registrations about MRAM and propose a direction of future investigation.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.105-116
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• 2021

Habruta is a question-based learning that talks, discusses, and argues in pairs. In particular, the famous painting Habruta is being implemented for the purpose of enhancing the appreciation ability of paintings and enriching the expressive power through questions and answers about the famous paintings. In this study, in order to support the famous painting Habruta for oriental paintings, we propose a method of automatically generating questions from the gender perspective of oriental painting characters using the current deep learning technology. Specifically, in this study, based on the pre-trained model, VGG16, we propose a model that can effectively analyze the features of Asian paintings by performing fine-tuning. In addition, we classify the types of questions into three types: fact, imagination, and applied questions used in the famous Habruta, and subdivide each question according to the character to derive a total of 9 question patterns. In order to verify the feasibilityof the proposed methodology, we conducted an experiment that analyzed 300 characters of actual oriental paintings. As a result of the experiment, we confirmed that the gender classification model according to our methodology shows higher accuracy than the existing model.

• Journal of Hydrogen and New Energy
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• v.30 no.4
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• pp.303-311
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• 2019

Reversible solid oxide fuel cell (RSOFC) has become a prospective device for energy storage and hydrogen production. Many studies have been conducted around the world focusing on system efficiency improvement and realization. The system should have not only high efficiency but also a certain level of simplicity for stable operation. External waste steam utilization was proved to remarkably increase the efficiency at solid oxide electrolysis system. In this study, RSOFC system coupled with waste steam was proposed and optimized in term of simplicity and efficiency. Ejector for fuel recirculation is selected due to its simple design and high stability. Three system configurations using ejector for fuel recirculation were investigated for performance of design condition. In parametric study, the system efficiencies at different current density were analyzed. The system configurations were simulated using validated lumped model in EBSILON(R) program. The system components, balance of plants, were designed to work in both electrolysis and fuel cell modes, and their off-design characteristics were taken into account. The base case calculation shows that, the system with suction pump results in slightly lower efficiency but stack can be operated more stable with same inlet pressure of fuel and air electrode.

• Journal of Hydrogen and New Energy
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• v.32 no.1
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• pp.11-40
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• 2021

Solid oxide fuel cell (SOFC) has received significant attention recently because of its potential for the clean and efficient power generation. The current manufacturing processes for the SOFC components are somehow complex and expensive, therefore, new and innovative techniques are necessary to provide a great deal of cell performance and fabricability. Three-dimensional (3D) printing processes have the potential to provide a solution to all these problems. This study reviews the literature for manufacturing the SOFC components using 3D printing processes. The technical aspects for fabrication of SOFC components, 3D printing processes optimization and material characterizations are discussed. Comparison of the SOFC components fabricated by 3D printing to those manufactured by conventional ceramic processes is highlighted. Further advancements in the 3D printing of the SOFC components can be a step closer to the cost reduction and commercialization of this technology.

• Current Applied Physics
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• v.18 no.12
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• pp.1564-1570
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• 2018

Charge transport dynamics in ZnO based inverted organic solar cell (IOSC) has been characterized with transient photocurrent spectroscopy and localised photocurrent mapping-atomic force microscopy. The value of maximum exciton generation rate was found to vary from $2.6{\times}10^{27}m^{-3}s^{-1}$ ($J_{sat}=79.7A\;m^{-2}$) to $2.9{\times}10^{27}m^{-3}s^{-1}$ ($J_{sat}=90.8A\;m^{-2}$) for devices with power conversion efficiency ranging from 2.03 to 2.51%. These results suggest that nanorods served as an excellent electron transporting layer that provides efficient charge transport and enhances IOSC device performance. The photovoltaic performance of OSCs with various growth times of ZnO nanorods have been analysed for a comparison between AM1.5G spectrum and local solar spectrum. The simulated PCE of all devices operating under local spectrum exhibited extensive improvement with the gain of 13.3-3.7% in which the ZnO nanorods grown at 15 min possess the highest PCE under local solar with the value of 2.82%.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.85-92
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• 2021

Ambient Air Vaporizer (AAV) is an essential facility in the process of generating natural gas that uses air in the atmosphere as a medium for heat exchange to vaporize liquid natural gas into gas-state gas. AAV is more economical and eco-friendly in that it uses less energy compared to the previously used Submerged vaporizer (SMV) and Open-rack vaporizer (ORV). However, AAV is not often applied to actual processes because it is heavily affected by external environments such as atmospheric temperature and humidity. With insufficient operational experience and facility operations that rely on the intuition of the operator, the actual operation of AAV is very inefficient. To address these challenges, this paper proposes an artificial intelligence-based model that can intelligent AAV operations based on operational big data. The proposed artificial intelligence model is used deep neural networks, and the superiority of the artificial intelligence model is verified through multiple regression analysis and comparison. In this paper, the proposed model simulates based on data collected from real-world processes and compared to existing data, showing a 48.8% decrease in power usage compared to previous data. The techniques proposed in this paper can be used to improve the energy efficiency of the current natural gas generation process, and can be applied to other processes in the future.

• Current Photovoltaic Research
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• v.8 no.4
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• pp.107-113
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• 2020

Here we report the long-term stability of polymer:nonfullerene solar cells which were stored under dark and indoor light condition. The polymer:nonfullerene solar cells were fabricated using bulk heterojunction (BHJ) layers of poly[(2,6-(4,8-bis(5-(2-ethylhexyl) thiophen-2-yl)-benzo[1,2-b:4,5-b']dithiophene))-alt-(5,5-(1',3'-di-2-thienyl-5',7-bis(2-ethylhexyl)benzo[1',2'-c:4',5'-c']dithiophene-4,8-dione))] (PBDB-T) and 3,9-bis(6-methyl-2-methylene-(3-(1,1-dicyanomethylene)-indanone))-5,5,11,11-tetrakis(4-hexylphenyl)-dithieno[2,3-d:2',3-d']-s-indaceno[1,2-b:5,6-b']dithiophene (IT-M). To investigate their long-term stability, the PBDB-T:IT-M solar cells were stored in an argon-filled glove box. One set of the fabricated solar cells was completely covered with an aluminum foil to prevent any effect of light, whereas another set was exposed to indoor light. The solar cells were subjected to a regular performance measurement for 40 weeks. Results revealed that the PBDB-T:IT-M solar cells underwent a gradual decay in performance irrespective of the storage condition. However, the PBDB-T:IT-M solar cells stored under indoor light condition exhibited relatively lower power conversion efficiency (PCE) than those stored under the dark. The inferior stability of the solar cells under indoor light was explained by the noticeably changed optical absorption spectra and dark spot generation, indicative of degradations in the BHJ layers.

• Current Photovoltaic Research
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• v.10 no.3
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• pp.77-83
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• 2022

Renewable energy is receiving attention again as a way to realize carbon neutrality to overcome the climate change crisis. Among renewable energy sources, the installation of Photovoltaic is continuously increasing, and as of 2020, the global cumulative installation amount is about 590 GW and the domestic cumulative installation amount is about 17 GW. Accordingly, O&M technology that can analyze the power generation and fault diagnose about PV plants the is required. In this paper, a study was conducted to diagnose fault using I-V curves of PV strings and deep learning. In order to collect the fault I-V curves for learning in the deep learning, faults were simulated. It is partial shade and voltage mismatch, and I-V curves were measured on a sunny day. A two-step data pre-processing technique was applied to minimize variations depending on PV string capacity, irradiance, and PV module temperature, and this was used for learning and validation of deep learning. From the results of the study, it was confirmed that the PV fault diagnosis using I-V curves and deep learning is possible.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.641-648
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• 2023

Recently, the rapid growth of artificial intelligence among the 4th industrial revolution has progressed based on the performance improvement of semiconductor, and circuit integration. According to transistors, which help operation of internal electronic devices and equipment that have been progressed to be more complicated and miniaturized, the control of heat generation and improvement of heat dissipation efficiency have emerged as new performance indicators. The DUT(Device Under Test) Shell is equipment which detects malfunction transistor by evaluating the durability of transistor through heat dissipation in a state where the power is cut off at an arbitrary heating point applying the rating current to inspect the transistor. Since the DUT shell can test more transistor at the same time according to the heat dissipation structure inside the equipment, the heat dissipation efficiency has a direct relationship with the malfunction transistor detection efficiency. Thus, in this paper, we propose various method for PCB configuration structure to optimize heat dissipation of DUT shell and we also propose various transformation and thermal analysis of optimal DUT shell using computational fluid dynamics.