• Korean Journal of Metals and Materials
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• v.48 no.4
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• pp.369-375
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• 2010

Ti-6Al-4V ELI alloy, which is commonly used as a biomaterial, is associated with a high elastic modulus and poor biocompatibility. This alloy presents a variety of problems on several areas. Therefore, the development of good non-toxic biocompatible biomaterials with a low elastic modulus is necessary. Particularly, hydroxyapatite (HA) is an attractive material for human tissue implantation. This material is widely used as artificial bone due to its good biocompatibility and similar composition to human bone. Many scientists have studied the fabrication of HA as a biomaterial. However, applications of bulk HA compact are hindered by the low strength of HA when it is sintered. Therefore, HA has been coated on Ti or Ti alloy to facilitate good bonding between tissue and the HA surface. However, there are many problems when doing this, such as the low bonding strength between HA and Ti due to the different thermal expansion coefficients and mechanical properties. In this study, a Ti-HA composite with a porous surface was successfully fabricated by pulse current activated sintering (PCAS) and a subsequent leaching process.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.103-110
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• 2022

Since satellite images generally include clouds in the atmosphere, it is essential to detect or mask clouds before satellite image processing. Clouds were detected using physical characteristics of clouds in previous research. Cloud detection methods using deep learning techniques such as CNN or the modified U-Net in image segmentation field have been studied recently. Since image segmentation is the process of assigning a label to every pixel in an image, precise pixel-based dataset is required for cloud detection. Obtaining accurate training datasets is more important than a network configuration in image segmentation for cloud detection. Existing deep learning techniques used different training datasets. And test datasets were extracted from intra-dataset which were acquired by same sensor and procedure as training dataset. Different datasets make it difficult to determine which network shows a better overall performance. To verify the effectiveness of the cloud detection network such as Cloud-Net, two types of networks were trained using the cloud dataset from KOMPSAT-3 images provided by the AIHUB site and the L8-Cloud dataset from Landsat8 images which was publicly opened by a Cloud-Net author. Test data from intra-dataset of KOMPSAT-3 cloud dataset were used for validating the network. The simulation results show that the network trained with KOMPSAT-3 cloud dataset shows good performance on the network trained with L8-Cloud dataset. Because Landsat8 and KOMPSAT-3 satellite images have different GSDs, making it difficult to achieve good results from cross-sensor validation. The network could be superior for intra-dataset, but it could be inferior for cross-sensor data. It is necessary to study techniques that show good results in cross-senor validation dataset in the future.

• Journal of Energy Engineering
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• v.12 no.4
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• pp.302-308
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• 2003

The peformence tests of zinc-based desulfurization sorbents using the yellow earth as support for the hot gas clean up were carried out. The zinc-based sorbent with 25 wt％ yellow earth was prepared, and their properties such as the reaction rate, the sulfur capacity and the attrition resistance, were investigated. The reactivity tests for hot gas desulfurization was performed at middle temperatures (sulfidation/regeneration：480$^{\circ}C$/580$^{\circ}C$). During multi-cyclic desulfurization, the deactivation of zinc-based sorbent was decreased by the addition of yellow earth, and their efficiency was enhanced. The ZnO/yellow earth sorbent had high reactivity, good regenerability, long-term durability (about 19 gS/100 g sorbent for 10-cycles) and high attrition resistance (AI=19.1％). It was concluded that the peroperties of zinc-based sorbent were improved by metal oxides (Fe$_2$O$_3$, Na$_2$O, MnO$_2$, etc) in the yellow earth. From these results, it was confirmed that the desulfurization properties of zinc-based sorbents at middle temperatures could be improved by the yellow earth using as support.

• 한국금형공학회:학술대회논문집
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• 2008.06a
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• pp.23-26
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• 2008

In order to examine the deformation characteristics of Al circular pipe underthe biaxial compression, the horizontal biaxial compression die for the experiment was manufactured. From this, in the various compressive strain rate (1 mm/min. ${\sim}$ 400 mm/min.)conditions, the circular pipes, which were made by Al materials, were investigated based on the properties change of cross section area, punch load and deformation behavior. The tensile and compressive strains were evaluated from micro Vickers hardness tester. From these results, the punch load and deformation characteristic of Al circular pipes were highly changed in the compressive strain rate about 200 mm/min. The Al circular pipes had the tendency that the punch load decreased with increasing the compressive strain rate. In addition, following as the change of the shape and position of neutral axis due to the deformation proceeding of the circular pipe, the special point of the internal circular pipe at maximum load showed the maximum deformation strain and the maximum measured hardness value. The CAE (computer aided engineering) simulation using Deform-2D program was performed on the circular pipe in order to know and verify the exact compressive deformation behavior. From these results, the experimentally measured results were reasonably in good agreement with the simulation results.

• Korean Journal of Animal Reproduction
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• v.10 no.1
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• pp.91-99
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• 1986

This experiment was undertaken to examine the effects of HIS treatment on the motility and acrosome reaction of frozen bovine spermatozoa and to test their abilities to interact with zona-free hamster eggs in vitro. Also, in vitro results were compared with those of bull's fertility in AI. The frozen semen from four Holstein bulls were exposed to HIS-DM for 5 minutes after thawing and then preincubated for 60 minutes in DM prior to insemination. The hamster eggs were mounted, fixed and stained 6 hours after exposure to boving spermatozoa and examined under a phase-contrast microscope. 1. The sperm motility expressed as a mobility index dro, pp.d significantly from 60-75 to 12-24 after exposure to HIS-DM, but increased in 32 to 41 at insemination. Bull C showed a low motility index than those of the orher bulls. The percentage of acrosome reaction by staining procedure were increased by HIS-DM treatment but did not change during 7 hours incubation period in DM. 2. The overall percentage of hamster eggs interacting with bull spermatozoa was 56.3%, 58.3%, 66.6% and 70.0%, respectively. Although there was no significant difference among bulls in the penetration rate of spermatozoa into hamster eggs, high proportions of eggs interacted with spermatozoa from Bull C and D than those from Bull A and B. 3. The conception rates (60-90 day RP) resulting from AI were 62.5%, 67.5% and 70.9% for Bull A, B and C, respectively. These results were in good agreement with the invitro results that the proportions of bull sperm-egg interction were greater for Bull C than for Bull A and B.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.16 no.3
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• pp.247-252
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• 2003

In this paper, we made four types of metal particle $Al_2$O$_3$ barrier reactors with and without dielectric of BaTiO$_3$ between metal particle and $Al_2$O$_3$ barrier to investigate NOx removal characteristic and the effect of dielectric on Nox removal. And Nox removal rate is measured when sludge pellets are put at down stream of plasma reactor. Nox removal rate in the reactor with $Al_2$O$_3$ barrier is much better than that in the reactor without $Al_2$O$_3$ barrier, Nox removal rate is not so good in metal particle-Al$_2$O$_3$ barrier reactor with BaTiO$_3$ between metal particle and $Al_2$O$_3$ barrier, however, Nox removal rate is about 40% in metal particle-Al$_2$O$_3$ barrier reactor with TiO$_2$. The most of NO is conversed to NO$_2$ in these kind of reactor. When sludge pellets are put at down stream of plasma reactor, Nox removal rate is greatly improved up to 90%. It indicates that sludge pellets have great effect on the NO$_2$ removal and the improvement of Nox removal rate, however, dielectric materials between metal particle and $Al_2$O$_3$ barrier have not effect. Organic materials included in sludge may react with NO$_2$ and ozone so that Nox removal rate is greatly improved.

• KSBB Journal
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• v.30 no.4
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• pp.155-160
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• 2015

The present study was to investigate the antioxidant activity in ethanol and water extracts of root and stem of Sargassum coreanum. Antioxidant activities were evaluated by total polyphenol contents, DPPH radical scavenging activity, chelating effect, reducing power, and rancimat method. Total polyphenol contents of ethanol and water extracts were 32.79 mg/g and 15.55 mg/g, respectively. Ethanol extract showed higher DPPH radical scavenging activity than water extract and similar activity to BHT. Reducing power of extracts was increased in a concentration-dependent manner and ethanol extract had more reducing power than water extract. Ethanol and water extracts have little chelating effect at all concentrations. Antioxidant index (AI) of ethanol extract measured by Rancimat was higher than that of water extract, but their AI was lower than that of BHT. These results indicate that ethanol extract of S. coreanum root and stem has more potent antioxidant activity than water extract through DPPH radical scavenging and reducing power, and could potentially be used as a good source of natural antioxidants.

• Journal of Digital Convergence
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• v.14 no.7
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• pp.167-174
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• 2016

The university and college turn into the field of job readiness to get a good job and students build a lot of job specification than others and are constantly studying for employment. Then since employment, some people are fortunate to keep the job for lifetime, but for many people work in the workplace did not meet his aptitude with patience and some people move for work several times without perseverance. One of the reasons for job dissatisfaction is that the job does not fit his aptitude. Meantime many organizations conducted the aptitude(Psychology) test. There are limits, however, to find a suitable job. This study was presented as a model of a platform that is a rational and scientific alternative to search course and job. This model is to better understand the individual characteristics using Big data and artificial intelligence, offers several jobs to meet the characteristics among the various professions selectively and supports to select and design an appropriate job based on the field experience, consulting and mentoring.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.74-85
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• 2019

This Study explores the reason why the social media like Cyworld, Iloveschool in Korea in the viewpoint if the layered model by interview. As a result the success factor in the viewpoint of layered model, user used social media for fulfilling the need for linking with other users and the social media offers the customized contents to user. Finally the social media dominated the market in advance. Facebook and Kakao talk are good examples of successful media. The failure factors are to care less about what other users want, to limit the expand of platform and not to copy with the change of the media environment. Iloveschool, Cyworld and Twitter are the examples of failure social media in Korean society. This study highlights the importance of the sensitivity of the change of environment. The expert mentioned the importance of 4th industrial revolution technology like AI, Big data and expected that new technology will emerge and the service will be developed by the change of user's taste.

• Journal of Advanced Navigation Technology
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• v.25 no.5
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• pp.409-414
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• 2021

The growing concerns on the emission of particulate matter has prompted a demand for highly reliable particulate matter forecasting. Currently, several studies on particulate matter prediction use various deep learning algorithms. In this study, we compared the predictive performances of typical neural networks used for particulate matter prediction. We used deep neural network(DNN), recurrent neural network, and long short-term memory algorithms to design an optimal predictive model on the basis of a hyperparameter search. The results of a comparative analysis of the predictive performances of the models indicate that the variation trend of the actual and predicted values generally showed a good performance. In the analysis based on the root mean square error and accuracy, the DNN-based prediction model showed a higher reliability for prediction errors compared with the other prediction models.