• The Journal of Korean Academy of Prosthodontics
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• v.47 no.4
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• pp.406-415
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• 2009

Purpose: The purpose of this study was to compare the marginal fitness and fracture load of the zirconia copings according to the design with different thickness and coloration. Material and methods: The evaluation was based on 80 zirconia copings. Zirconia copings were fabricated in design with different thicknesses using CAD/CAM system (Everset, KAVO dental GmbH, Biberach, Germany). The designs of copings were divided into four groups. The first group consisted of copings with uniform thickness of 0.3 mm. The thickness in the second group was 0.3 mm on the buccal surface and 0.6 mm on the lingual surface. The third group consisted of coping with uniform thickness of 0.6 mm. The thickness in the fourth group was 0.6 mm on the buccal surface and 1mm on the lingual surface. Each group consisted of 10 colored and 10 uncolored copings. Half of the copings (40) processed with a milling system according to the specific design were sent to be given a color (A3) through saturation in special dye by a manufacturing company. Just after sintering, the marginal discrepancies of copings were measured on the buccal, lingual, mesial and distal surfaces of metal die, under a Video Microscope System (sv-35, Sometech, Seoul, Korea) at a magnification of $\times$ 100. It was remeasured after the adjusting of the inner surface. Next, all copings were luted to the metal dies using reinforced cement {GC FujiCEM (GC Corp. Tokyo, Japan)} and mounted on the testing jig in a Universal Testing Machine (Instron 4467, Norwood, MA, USA). The results were analyzed statistically using the one-way ANOVA test. Results: The obtained results were as follow: 1. The measured value of marginal discrepancy right after sintering was the greatest in the contraction of the buccal area in all groups, except for group I2. 2. There was no significant difference of marginal fitness among the groups in the colored zirconia group (P<.05). 3. When the marginal fitness among the groups in the uncolored zirconia group was considered, group II2 had the smallest marginal discrepancy. 4. When the colored and uncolored groups with the same design were compared, there was a significant difference between I1 and II1 groups. In group 2, 3, and 4, the uncolored zirconia had the greatest marginal fitness (P<.05). 5. After adjustment of inner surface, there was no significant difference in the marginal fitness in all groups when color and design of the zirconia coping were compared. 6. The fracture load of CAD/CAM zirconia copings showed significant difference in group 1, 2, 3, and 4. I4 and II4 had the strongest fracture load. 7. When groups with different color and same design were compared, all colored groups showed greater fracture load (P>.05), with no significance. Conclusion: There was difference in the marginal fitness according to the design and coloration of zirconia copings right after sintering, but it was decided that the copings may well be used clinically if the inner surface are adjusted. The copings should be thick enough for the reinforcement of fracture strength. But considering the esthetics of the visible surfaces (labial and buccal surface), the thickness of copings may be a little thin, without giving any significant effect on the fracture strength. This type of design may be considered when giving priority to preservation of tooth or esthetics.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.24 no.2
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• pp.65-71
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• 2018

Paper packs, glass bottles, metal cans, and plastic materials are classified according to packaging material recycling groups that are Extended Producer Responsibility (EPR). In the case of waste paper pack, the compressed cartons are dissociated to separate polyethylene films and other foreign substance, and then these are washed, pulverized and dried to produce toilet paper. Glass bottle for recycling is provided to the bottle manufacturers after the process of collecting the waste glass bottle, removing the foreign substance, sorting by color, crushing, raw materializing process. Waste glass recycling technology of Korea is largely manual, except for removal of metal components and low specific gravity materials. Metal can is classified into iron and aluminum cans through an automatic sorting machine, compressed, and reproduced as iron and aluminum through a blast furnace. In the case of composite plastic material, the selected compressed product is crushed and then recycled through melt molding and refined products are produced through solid fuel manufacturing steps through emulsification and compression molding through pyrolysis. In the recycling process of paper packs, glass bottles, metal cans, and plastic materials, the influx of recycled materials and other substances interferes with the recycling process and increases the recycling cost and time. Therefore, the government needs to improve the legal system which is necessary to use materials and structure that are easy to recycle from the design stage of products or packaging materials.

• Korean Journal of Social Welfare
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• v.53
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• pp.285-310
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• 2003

As National Pension Scheme for all nation complete in 1999 through expanding application in cities, the public pension including Public Occupational Pension became main axis of old-age income maintenance. After 4years since then, now, it is only half of total National Pension insured persons who have been qualified to receive pension through participate and contribution. The other half of National Pension insured is left the excluded from public pension. This paper is intended to identify scale and characteristics of the excluded from public pension and to analysis its cause, and to explore policy measures for solving the excluded's problem. for current recipients over 60 years old generation, the its excluded's scale is no less than 86% of the old over 60 years. The probability of getting in the excluded is high in case of old elderly and female for current elderly generation. For future recipients 18-59 years working generation, the its excluded's scale is no less than 61% of the 18-59 years total population. The probability of getting in the excluded is high in case of 18-29 years and female for current working generation. As logistic regression analysis determinant factor of paying or not pension contribution for future recipients, it appear that probability of getting in the excluded for current working generation is high in case of younger old, lower education attainment, irregular employee, working at agriculture forestry fishery sector, construction sector, wholesale retail trade restaurants hotels sector, financial institution and insurance real estate renting and leasing sector in comparison with manufacturing sector, occpaying at elementary occupation, professionals technicians and associate professionals, sale and service workers, plant machine operators and assemblers, legislators senior officials and managers in comparison with clerks. The Policy measures for the current recipient old generation have need to reinforce supplemental role of Senior's pension(non-contribution pension) until maturing of public pension, because of no having chance of public pension participants for them. And the Policy measures for the future recipient working generation have need to restructure social security fundamentally corresponding with social-economic change as labour market and family structure etc. The pension system has need to change from one earner one pension to one citizen one pension with citizenship rights. At this point, public pension have need to manage with combining insurance's contribution principle and citizenship principle financing by taxes. Then public pension will become substantially universal social network for old-age income maintenance and we can find real solution for the excluded from.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2000.06a
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• pp.16-23
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• 2000

The increasing functional needs of top-quality printing papers and packaging paperboards, and especially the rapid developments in electronic printing processes and various computer printers during past few years, set new targets and requirements for modern paper quality. Most of these paper grades of today have relatively high filler content, are moderately or heavily calendered , and have many coating layers for the best appearance and performance. In practice, this means that many of the traditional quality assurance methods, mostly designed to measure papers made of pure. native pulp only, can not reliably (or at all) be used to analyze or rank the quality of modern papers. Hence, introduction of new measurement techniques is necessary to assure and further develop the paper quality today and in the future. Paper formation , i.e. small scale (millimeter scale) variation of basis weight, is the most important quality parameter of paper-making due to its influence on practically all the other quality properties of paper. The ideal paper would be completely uniform so that the basis weight of each small point (area) measured would be the same. In practice, of course, this is not possible because there always exists relatively large local variations in paper. However, these small scale basis weight variations are the major reason for many other quality problems, including calender blacking uneven coating result, uneven printing result, etc. The traditionally used visual inspection or optical measurement of the paper does not give us a reliable understanding of the material variations in the paper because in modern paper making process the optical behavior of paper is strongly affected by using e.g. fillers, dye or coating colors. Futhermore, the opacity (optical density) of the paper is changed at different process stages like wet pressing and calendering. The greatest advantage of using beta transmission method to measure paper formation is that it can be very reliably calibrated to measure true basis weight variation of all kinds of paper and board, independently on sample basis weight or paper grade. This gives us the possibility to measure, compare and judge papers made of different raw materials, different color, or even to measure heavily calendered, coated or printed papers. Scientific research of paper physics has shown that the orientation of the top layer (paper surface) fibers of the sheet paly the key role in paper curling and cockling , causing the typical practical problems (paper jam) with modern fax and copy machines, electronic printing , etc. On the other hand, the fiber orientation at the surface and middle layer of the sheet controls the bending stiffness of paperboard . Therefore, a reliable measurement of paper surface fiber orientation gives us a magnificent tool to investigate and predict paper curling and coclking tendency, and provides the necessary information to finetune, the manufacturing process for optimum quality. many papers, especially heavily calendered and coated grades, do resist liquid and gas penetration very much, bing beyond the measurement range of the traditional instruments or resulting invonveniently long measuring time per sample . The increased surface hardness and use of filler minerals and mechanical pulp make a reliable, nonleaking sample contact to the measurement head a challenge of its own. Paper surface coating causes, as expected, a layer which has completely different permeability characteristics compared to the other layer of the sheet. The latest developments in sensor technologies have made it possible to reliably measure gas flow in well controlled conditions, allowing us to investigate the gas penetration of open structures, such as cigarette paper, tissue or sack paper, and in the low permeability range analyze even fully greaseproof papers, silicon papers, heavily coated papers and boards or even detect defects in barrier coatings ! Even nitrogen or helium may be used as the gas, giving us completely new possibilities to rank the products or to find correlation to critical process or converting parameters. All the modern paper machines include many on-line measuring instruments which are used to give the necessary information for automatic process control systems. hence, the reliability of this information obtained from different sensors is vital for good optimizing and process stability. If any of these on-line sensors do not operate perfectly ass planned (having even small measurement error or malfunction ), the process control will set the machine to operate away from the optimum , resulting loss of profit or eventual problems in quality or runnability. To assure optimum operation of the paper machines, a novel quality assurance policy for the on-line measurements has been developed, including control procedures utilizing traceable, accredited standards for the best reliability and performance.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.53-62
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• 2023

This paper has suggested the necessity of introducing training contents using XR(Extended reality) technology as a way to lower the high rate of nursing accidents among unskilled technical personnel in domestic shipbuilding industry, focusing on cable pulling using winch. The occurrence rate of nursing accidents in the domestic shipbuilding industry was almost double(197.4%) (2017~2020) when compared with other manufacturing industries. In particular, it is worth noting that more than 31.8% of nursing accidents in the shipbuilding industry occurred among workers whose job experience is no more than 6 months. Most of new workers are seen to have hard time due to several factors such as lack of work information, inexperience, and unfamiliarity with the working environments. This indicates that it is essential to incorporate more effective training method that could help new workers become familiar with technical skills as well as working environments in a short period of time. Currently, education/training at the domestic shipyard is biased toward technical skills such as welding, painting, machine installation, and electrical installation. Contrary, even more important training required to get new workers used to the working environment has remained at a superficial level such as explaining ship building processes using 2D drawings. This may be the reason why it is inevitable to repeat similar training at OJT (On-the-Job Training) even at the leading domestic companies. Domestic shipbuilding industries have been attracting a lot of new workers thanks to recent economic recovery, which is very likely to increase the occurrence of disasters. In this paper, the introduction of training using XR technology was proposed, and as a specific example, the process of pulling cables using winches on ships was implemented as XR-based training content by using Unity. Using the developed content, it demonstrated that new workers can experience the actual work process in advance through simulation in a virtual space, thereby becoming more effective training content that can help new workers become familiar with the work environment.

• Korean Journal of Heritage: History & Science
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• v.57 no.3
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• pp.24-35
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• 2024

Recently, research using deep learning technologies such as artificial intelligence, convolutional neural networks, etc. has been actively conducted in various fields including healthcare, manufacturing, autonomous driving, and security, and is having a significant influence on society. In line with this trend, the present study attempted to apply deep learning to the classification of archaeological artifacts, specifically ancient Korean roof-end tiles. Using 100 images of roof-end tiles from each of the Goguryeo, Baekje, and Silla dynasties, for a total of 300 base images, a dataset was formed and expanded to 1,200 images using data augmentation techniques. After building a model using transfer learning from the pre-trained EfficientNetB0 model and conducting five-fold cross-validation, an average training accuracy of 98.06% and validation accuracy of 97.08% were achieved. Furthermore, when model performance was evaluated with a test dataset of 240 images, it could classify the roof-end tile images from the three dynasties with a minimum accuracy of 91%. In particular, with a learning rate of 0.0001, the model exhibited the highest performance, with accuracy of 92.92%, precision of 92.96%, recall of 92.92%, and F1 score of 92.93%. This optimal result was obtained by preventing overfitting and underfitting issues using various learning rate settings and finding the optimal hyperparameters. The study's findings confirm the potential for applying deep learning technologies to the classification of Korean archaeological materials, which is significant. Additionally, it was confirmed that the existing ImageNet dataset and parameters could be positively applied to the analysis of archaeological data. This approach could lead to the creation of various models for future archaeological database accumulation, the use of artifacts in museums, and classification and organization of artifacts.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.