• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.3
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• pp.664-673
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• 2008

Recently, the ubiquitous is handled by maximum topic. New knowledge information and ubiquitous computing evolution have promoted new paradigm transfer and grand change. Also, need technology as powerful engineering approached fairly system and educational guidance side examination necessarily to overcome u-Learning base situation and studying obstacle situations. This treatise embodied handiness examination about attention shortage and excess obstacle (Attention Deficit Hyperactivity Disorder, low ADHD) who must solve so as to be square and level being increase trend in primary school using USB (Universal Serial Bus) terminal system that allow fetters to OSGi (Open Service Gateway Initiative). That OSGi base USB terminal system is easy preservation of information, safety of network, cost-cutting and maintenance by various ubiquitous system that server that load many USB terminals and OSGi uses an USB bus of high speed and construct network, there is advantage of concentration elevation and so on of week and ADHD handled in this treatise because early diagnosis and treatment are serious. The confirmed system application that can supplement paper and pens examination's shortcoming and could solve examination's problem which use computer, and help in student guidance through ADHD simpleexamination who utilize OSGi base USB terminal system. Is available by game system that system for human nature examination or intelligence test and general exam explaining and level studying, order style question investigation program, studying system for disabled person, majority that enforce in public in school this study finding does together.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.5
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• pp.209-220
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• 2013

Handover is the technology to minimize data lose of mobile devices and make continuous communication possible even if the device could be moved from one digital cell site to another one. That is, it is a function that enables the mobile user to avoid the disconnection of phone conversations when moving from a specific mobile communication area to another. Today, there are a lot of ongoing researches for fast and efficient hand-over, in order to address phone call's delay and disconnection which are believed to be the mobile network's biggest problems, and these should essentially be resolved in all mobile networks. Thanks to recent technology development in mobile network, the LTE network has been commercialized today and it has finally opened a new era that makes it possible for mobile phones to process data at high speed. In LTE network environment, however, a new authentication key must be generated for the hand-over. In this case, there can be a problem that the authentication process conducted by the hand-over incurs its authentication cost and delay time. This essay suggests an efficient key caching hand-over method which simplifies the authentication process: when UE makes hand-over from oMME to nMME, the oMME keeps the authentication key for a period of time, and if it returns to the previous MME within the key's lifetime, the saved key can be re-used.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.7
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• pp.413-420
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• 2006

The speed of present-day network technology exceeds a gigabit and is developing rapidly. When using TCP/IP in these high-speed networks, a high load is incurred in processing TCP/IP protocol in a host CPU. To solve this problem, research has been carried out into TCP/IP Offload Engine (TOE). The TOE processes TCP/IP on a network adapter instead of using a host CPU; this reduces the processing burden on the host CPU. In this paper, we developed two software-based TOEs. One is the TOE implementation using an embedded Linux. The other is the TOE implementation using Lightweight TCP/IP (lwIP). The TOE using an embedded Linux did not have the bandwidth more than 62Mbps. To overcome the poor performance of the TOE using an embedded Linux, we ported the lwIP to the embedded system and enhanced the lwIP for the high performance. We eliminated the memory copy overhead of the lwIP. We added a delayed ACK and a TCP Segmentation Offload (TSO) features to the lwIP and modified the default parameters of the lwIP for large data transfer. With the aid of these modifications, the TOE using the modified lwIP shows a bandwidth of 194 Mbps.

• Journal of Applied Biological Chemistry
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• v.65 no.4
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• pp.439-446
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• 2022

Soybean is a crop with high-quality of protein and oil, and it is one of the most widely used genetically modified (GM) crops in the world today. In South Korea, Kwangan is the most utilized variety as a parental line for GM soybean development. In this study, untargeted LC-MS metabolomic approaches were used to compare metabolite profiles of Kwangan and three other commercial varieties cultivated in Gunwi and Jeonju in 2020 year. Metabolomic studies revealed that the 4 soybean varieties were distinct based on the partial least squares-discriminant analysis (PLS-DA) score plots; 18 metabolites contributed to variety distinction, including phenylalanine, isoflavones, and fatty acids. All varieties were clearly differentiated by location on the PLS-DA score plot, indicating that the growing environment is also attributable to metabolite variability. In particular, isoflavones and linolenic acid levels in Kwangan were significantly lower and higher, respectively compared to those of the three varieties. It was discussed that it might need to include more diverse conventional varieties as comparators in regard to metabolic characteristics of Kwangan for the assessment of substantial equivalence biogenetically engineered soybeans in a Kwangan-variety background.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.3
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• pp.127-143
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• 2022

Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.33-54
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• 2021

With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.