• Nuclear Engineering and Technology
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• v.39 no.5
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• pp.603-616
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• 2007

Roy Huddle, having invented the coated particle in Harwell 1957, stated in the early 1970s that we know now everything about particles and coatings and should be going over to deal with other problems. This was on the occasion of the Dragon fuel performance information meeting London 1973: How wrong a genius be! It took until 1978 that really good particles were made in Germany, then during the Japanese HTTR production in the 1990s and finally the Chinese 2000-2001 campaign for HTR-10. Here, we present a review of history and present status. Today, good fuel is measured by different standards from the seventies: where $9*10^{-4}$ initial free heavy metal fraction was typical for early AVR carbide fuel and $3*10^{-4}$ initial free heavy metal fraction was acceptable for oxide fuel in THTR, we insist on values more than an order of magnitude below this value today. Half a percent of particle failure at the end-of-irradiation, another ancient standard, is not even acceptable today, even for the most severe accidents. While legislation and licensing has not changed, one of the reasons we insist on these improvements is the preference for passive systems rather than active controls of earlier times. After renewed HTGR interest, we are reporting about the start of new or reactivated coated particle work in several parts of the world, considering the aspects of designs/ traditional and new materials, manufacturing technologies/ quality control quality assurance, irradiation and accident performance, modeling and performance predictions, and fuel cycle aspects and spent fuel treatment. In very general terms, the coated particle should be strong, reliable, retentive, and affordable. These properties have to be quantified and will be eventually optimized for a specific application system. Results obtained so far indicate that the same particle can be used for steam cycle applications with $700-750^{\circ}C$ helium coolant gas exit, for gas turbine applications at $850-900^{\circ}C$ and for process heat/hydrogen generation applications with $950^{\circ}C$ outlet temperatures. There is a clear set of standards for modem high quality fuel in terms of low levels of heavy metal contamination, manufacture-induced particle defects during fuel body and fuel element making, irradiation/accident induced particle failures and limits on fission product release from intact particles. While gas-cooled reactor design is still open-ended with blocks for the prismatic and spherical fuel elements for the pebble-bed design, there is near worldwide agreement on high quality fuel: a $500{\mu}m$ diameter $UO_2$ kernel of 10% enrichment is surrounded by a $100{\mu}m$ thick sacrificial buffer layer to be followed by a dense inner pyrocarbon layer, a high quality silicon carbide layer of $35{\mu}m$ thickness and theoretical density and another outer pyrocarbon layer. Good performance has been demonstrated both under operational and under accident conditions, i.e. to 10% FIMA and maximum $1600^{\circ}C$ afterwards. And it is the wide-ranging demonstration experience that makes this particle superior. Recommendations are made for further work: 1. Generation of data for presently manufactured materials, e.g. SiC strength and strength distribution, PyC creep and shrinkage and many more material data sets. 2. Renewed start of irradiation and accident testing of modem coated particle fuel. 3. Analysis of existing and newly created data with a view to demonstrate satisfactory performance at burnups beyond 10% FIMA and complete fission product retention even in accidents that go beyond $1600^{\circ}C$ for a short period of time. This work should proceed at both national and international level.

• Journal of IKEEE
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• v.25 no.3
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• pp.493-500
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• 2021

In this paper, we propose the development of deep learning structure to improve quality of polygonal containers. The deep learning structure consists of a convolution layer, a bottleneck layer, a fully connect layer, and a softmax layer. The convolution layer is a layer that obtains a feature image by performing a convolution 3x3 operation on the input image or the feature image of the previous layer with several feature filters. The bottleneck layer selects only the optimal features among the features on the feature image extracted through the convolution layer, reduces the channel to a convolution 1x1 ReLU, and performs a convolution 3x3 ReLU. The global average pooling operation performed after going through the bottleneck layer reduces the size of the feature image by selecting only the optimal features among the features of the feature image extracted through the convolution layer. The fully connect layer outputs the output data through 6 fully connect layers. The softmax layer multiplies and multiplies the value between the value of the input layer node and the target node to be calculated, and converts it into a value between 0 and 1 through an activation function. After the learning is completed, the recognition process classifies non-circular glass bottles by performing image acquisition using a camera, measuring position detection, and non-circular glass bottle classification using deep learning as in the learning process. In order to evaluate the performance of the deep learning structure to improve quality of polygonal containers, as a result of an experiment at an authorized testing institute, it was calculated to be at the same level as the world's highest level with 99% good/defective discrimination accuracy. Inspection time averaged 1.7 seconds, which was calculated within the operating time standards of production processes using non-circular machine vision systems. Therefore, the effectiveness of the performance of the deep learning structure to improve quality of polygonal containers proposed in this paper was proven.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.1-17
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• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.375-384
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• 2022

The shipping industry is cyclically impacted by complex variables such as various economic indicators, social events, and supply and demand. The purpose of this study was to analyze the operating profit of 13 Korean liner companies over 30 years, including the financial crisis of the late 1990s, the global financial crisis of the late 2000s, and the COVID-19 global pandemic. This study was conducted to also identify factors that impacted the profit ratio of Korea's liner shipping companies according to economic conditions. It was divided into ocean-going and short-sea shipping, reflecting the characteristics of liner shipping companies, and was analyzed by hierarchical multiple regression analysis. The time series data are based on the Korean International Financial Reporting Standards (K-IFRS) and comprise seaborne trade volume, fleet evolution, and macroeconomic indicators. The outliers representing the economic downturn due to social events were separately analyzed. As a result of the analysis, the China Container Freight Index (CCFI) positively impacted ocean-going as well as short-sea liner shipping companies. However, the Korean container shipping volume only impacted ocean-going liners positively. Additionally, world and Korea's GDP, world seaborne trade volume, and fuel price are factored in the operating profit of short sea liner shipping. Also, the GDP growth rate of China, exchange rate, and interest rate did not significantly impact both groups. Notably, the operating profitability of Korea's liner shipping shows an exceptionally high rate during the recessions of 1998 and 2020. It is paradoxical, and not correlated with the classical economic indicators. Unlike other studies, this paper focused on the operating profit before financial expenses, considering the complexity as well as difficulty in forecasting the shipping cycle, and rendered conclusions using relatively long-term empirical analysis, including three economic shocks.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.1
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• pp.88-100
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• 2018

Methane emissions from rice paddies are the largest source of greenhouse gases in the agricultural sector, but there are significant regional differences depending on the surrounding conditions and cultivation practices. To visualize these differences and to analyze their causes and characteristics, the methane emissions from each administrative district in South Korea were calculated according to the IPCC guidelines using the data from the 2010 Agriculture, Forestry and Fisheries Census, and then the results were mapped by using the ArcGIS. The nationwide average of methane emissions per unit area was $380{\pm}74kg\;CH_4\;ha^{-1}\;yr^{-1}$. The western region showed a trend toward higher values than the eastern region. One of the major causes resulting in such regional differences was the $SF_o$ (scaling factor associated with the application of organic matter), where the number of cultivation days played an important role to either offset or deepen the differences. Comparison of our results against the actual methane emissions data observed by eddy covariance flux measurement in the three KoFlux rice paddy sites in Gimje, Haenam and Cheorwon showed some differences but encouraging results with a difference of 10 % or less depending on the sites and years. Using the updated GWP (global warming potential) value of 28, the national total methane emission in 2010 was estimated to be $8,742,000tons\;CO_2eq$ - 13% lower than that of the National Greenhouse Gas Inventory Report (i.e., $10,048,000tons\;CO_2eq$). The administrative districts-based map of methane emissions developed in this study can help identify the regional differences, and the analysis of their key controlling factors will provide important scientific basis for the practical policy makings for methane mitigation.

• The Korean Journal of Air & Space Law and Policy
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• v.19 no.2
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• pp.97-136
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• 2004

The Northeast Asian air cargo market has expanded tremendously as a result of the opening up of the Chinese market. The importance of the Asia-Pacific region in the global air transport has also increased. The exchange of human and material resources, services, and information in Northeast Asia, which is expected to increase in the near future, requires that the airlines operating within this region adopt a more liberalized approach. This paper introduced alternatives which can be applied to the Northeast Asian airlines industry so as to bring about the integration of regional air transport: First, this paper found a need for individual Northeast Asian nations to alter their policies towards the airlines industry. Second, each country should further liberalize their respective domestic air transport. Third, there is a need for freer air service agreements to be signed between the nations of Northeast Asia. Fourth, the strategic alliances between the airlines operating in Northeast Asia should be further strengthened. Fifth, this liberalization process should be carried out in an incremental manner, beginning with more competitive airports and routes, or with less-in-demand routes. Sixth, there is a need for a shuttle system to be put into place between the main airports in China, Korea, and Japan. Seventh, these three nations jointly develop aviation safety and security systems that are in accordance with international standards. Eighth, the liberalization process of the aviation industry should be undertaken in conjunction with other related fields. Ninth, organizations linking together civil aviation organization in the Asia-Pacific area should be formed, as should each government linking together. By doing so, these countries will be able to establish regular venues through which to exchange opinions on the integration and liberalization of the air cargo market so as to induce the gradual liberalization of the actual market. The liberalization of the air transport in Northeast Asia will prove to be a daunting task in the short term. However, if the Chinese airlines continue to exhibit continuous growth and Japanese airlines are able to complete their move towards a low-cost structure, this process could be completed earlier than expected. Over the last twenty five years the air transport has undergone tremendous changes. The most important factor behind these changes has been the increased liberalization of the market. As a result, rates have decreased while demand has increased. This has resulted in turning the air transport industry, which was long perceived as an industry in decline, into a high-growth industry. The only method of increasing regional exchanges in the air transport is to pursue further liberalization. The country which implements this liberalization process at the earliest date may very well emerge as a leading force within the air transport industry.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.1
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• pp.189-206
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• 2012

It is urgently requested to innovate the management process of business-service areas in all industry such as financial business, services and manufacturing because of recent business trend - de-manufacturing trend and the weight increment of service in all industries. Many enterprises introduce various management - innovation methodologies in order to meet the rapidly changing business environment. Especially in Korea, it is a vogue to introduce the innovation methodology of the advanced company's. According to this style, the six sigma has been introduced over 10 years since late 1990's and it has become a synonym of innovation indeed. But the result of six sigma introduction has not reached to the level of expectation in its beginning. And the "Lean" have been introduced in Korea in the situation of global financial crisis, economic slump and the pursuit of developing country such as China. Many Korea companies pay attention to the "Lean" innovation activity because the TPS(Toyota Production System) is the matrix of Lean and is the motive power of Toyota growth. In this study, it was analyzed for the evolution course, distinctive features and effects of Lean management and was examined for the difference of Lean management between manufacturing industry and business-service areas. From this results, the characteristics of Lean management in business-service was analyzed. After survey of innovation agent in Korea company, the Lean model of business-service Industry was developed and applied. This study will be worthy to show the right direction to the enterprises which are to apply lean methodologies, or the enterprises which examine lean management for competitive advantages or the peoples who research the same topics.

• Economic and Environmental Geology
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• v.51 no.2
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• pp.185-201
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• 2018

Nuclear power plants(NPP) are constructed and operated to ensure safety against natural disasters and man-made disasters in all processes including site selection, site survey, design, construction, and operation. This paper will introduce a series of efforts conducted in Korea Hydro and Nuclear Power Co. Ltd., to assure the safety of nuclear power plant against earthquakes and other natural hazards. In particular, the present status of the earthquake, fault, and slope safety monitoring system for nuclear power plants is introduced. A earthquake observatory network for the NPP sites has been built up for nuclear safety and providing adequate seismic design standards for NPP sites by monitoring seismicity in and around NPPs since 1999. The Eupcheon Fault Monitoring System, composed of a strainmeter, seismometer, creepmeter, Global Positioning System, and groundwater meter, was installed to assess the safety of the Wolsung Nuclear Power Plant against earthquakes by monitoring the short- and long-term behavioral characteristics of the Eupcheon fault. Through the analysis of measured data, it was verified that the Eupcheon fault is a relatively stable fault that is not affected by earthquakes occurring around the southeastern part of the Korean peninsula. In addition, it was confirmed that the fault monitoring system could be very useful for seismic safety analysis and earthquake prediction study on the fault. K-SLOPE System for systematic slope monitoring was successfully developed for monitoring of the slope at nuclear power plants. Several kinds of monitoring devices including an inclinometer, tiltmeter, tension-wire, and precipitation gauge were installed on the NPP slope. A macro deformation analysis using terrestrial LiDAR (Light Detection And Ranging) was performed for overall slope deformation evaluation.

• The Journal of Industrial Distribution & Business
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• v.2 no.2
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• pp.15-24
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• 2011

Modern enterprises should concentrate their efforts on continuous improvements in focusing their development in the core areas of business and to reduce their expenses and to enhance the quality of service for customers. The enterprises should focus on their core business while outsourcing the non-core areas of business to external specialists for the purpose of reducing cost. In South Korea, the enterprises are becoming increasingly interested in outsourcing their logistics function, especially in using IT technologies to the 3PL. The underlying reason for this trend is because the logistics costs of Korean businesses are much higher than that of other advanced countries. This higher logistic costs weakens the price competitiveness of Korean companies in the overseas export markets and even dampening the balance of international trade. Domestically, the higher logistics costs have the effect of raising prices in the local markets and thus affecting the local economy. Therefore a solution is urgently needed to save the logistics costs for the Korean companies in the interest of increasing national competitiveness. Outsourcing to the 3PL is becoming an attraction solution to this problem. Thanks to the increasing supply of professional logistics companies, many of the enterprises are switching to the Third Party Logistics. Nevertheless the enterprises do not yet utilize the integrated third-party logistics services on a full scale. This study analyzes present conditions and problems of the domestic third-party logistics market and suggests directions for future development. To solve the problems in the domestic third-party logistics market, four actions are recommended. First there should be new supporting policies in the laws and regulations and a system for small and medium sized companies to grow. Solutions to structural problems such as abnormal multilevel merchandising, illegal operation of private cars, and freight dumping should be implemented concurrently. Furthermore, standards for new companies entry into the market should be enhanced to allow only the competitive distribution companies to enter the market. Second, development of variety of educational programs is needed through establishing human-resource development system and specialized formal educational institution focused on this market. Third, the third party distribution companies, which seek long-term relationships with the owners of goods, should endeavor to strengthen their communications capability. Fourth, adoption of high-tech distribution system and the advent of U-Logistics, making use of RFID is urgent. This study has the limitation of objectivity because it does not include various comparative case studies about companies relating to the Third Party Logistics and domestic franchise companies. However, this study is significant to the extent that it analyzes the general present conditions and the problems of domestic Third Party Logistics and suggests recommendations for revitalization of Third Party Logistics. For future studies, analyzing the successful cases of international third party logistics companies' empirical data and studying the application into domestic franchise companies would improve the objectivity of the results. This would assist the domestic third party logistics companies not only to perform excellent domestic logistics function but also to enter into the global market for international logistics.

• Journal of Distribution Science
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• v.12 no.6
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• pp.15-20
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• 2014

Purpose - In general, researchers try to abide by the code of research ethics, but many of them are not fully aware of plagiarism, unintentionally committing the research misconduct when they write a research paper. This research aims to introduce researchers a clear and easy guideline at a conference, which helps researchers avoid accidental plagiarism by addressing the issue. This research is expected to contribute building a climate and encouraging creative research among scholars. Research design, data, methodology & Results - Plagiarism is considered a sort of research misconduct along with fabrication and falsification. It is defined as an improper usage of another author's ideas, language, process, or results without giving appropriate credit. Plagiarism has nothing to do with examining the truth or accessing value of research data, process, or results. Plagiarism is determined based on whether a research corresponds to widely-used research ethics, containing proper citations. Within academia, plagiarism goes beyond the legal boundary, encompassing any kind of intentional wrongful appropriation of a research, which was created by another researchers. In summary, the definition of plagiarism is to steal other people's creative idea, research model, hypotheses, methods, definition, variables, images, tables and graphs, and use them without reasonable attribution to their true sources. There are various types of plagiarism. Some people assort plagiarism into idea plagiarism, text plagiarism, mosaic plagiarism, and idea distortion. Others view that plagiarism includes uncredited usage of another person's work without appropriate citations, self-plagiarism (using a part of a researcher's own previous research without proper citations), duplicate publication (publishing a researcher's own previous work with a different title), unethical citation (using quoted parts of another person's research without proper citations as if the parts are being cited by the current author). When an author wants to cite a part that was previously drawn from another source the author is supposed to reveal that the part is re-cited. If it is hard to state all the sources the author is allowed to mention the original source only. Today, various disciplines are developing their own measures to address these plagiarism issues, especially duplicate publications, by requiring researchers to clearly reveal true sources when they refer to any other research. Conclusions - Research misconducts including plagiarism have broad and unclear boundaries which allow ambiguous definitions and diverse interpretations. It seems difficult for researchers to have clear understandings of ways to avoid plagiarism and how to cite other's works properly. However, if guidelines are developed to detect and avoid plagiarism considering characteristics of each discipline (For example, social science and natural sciences might be able to have different standards on plagiarism.) and shared among researchers they will likely have a consensus and understanding regarding the issue. Particularly, since duplicate publications has frequently appeared more than plagiarism, academic institutions will need to provide pre-warning and screening in evaluation processes in order to reduce mistakes of researchers and to prevent duplicate publications. What is critical for researchers is to clearly reveal the true sources based on the common citation rules and to only borrow necessary amounts of others' research.