• Nuclear Engineering and Technology
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• v.51 no.5
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• pp.1297-1306
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• 2019

Probabilistic safety assessments (PSA) have been used for several decades to visualize the risk level of commercial nuclear power plants (NPPs). Since the role of a human reliability analysis (HRA) is to provide human error probabilities for safety critical tasks to support PSA, PSA quality is strongly affected by HRA quality. Therefore, it is important to understand the underlying limitations or problems of HRA techniques. For this reason, this study conducted a survey among 14 subject matter experts who represent the HRA community of domestic Korean NPPs. As a result, five significant HRA issues were identified: (1) providing a technical basis for the K-HRA (Korean HRA) method, and developing dedicated HRA methods applicable to (2) diverse external events to support Level 1 PSA, (3) digital environments, (4) mobile equipment, and (5) severe accident management guideline tasks to support Level 2 PSA. In addition, an HRA method to support multi-unit PSA was emphasized because it plays an important role in the evaluation of site risk, which is one of the hottest current issues. It is believed that creating such a catalog of prioritized issues will be a good indication of research direction to improve HRA and therefore PSA quality.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.603-605
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• 2014

Has been switched to the online shopping market in stores of the consumer is from increased utilization and smart devices, the internet popularization. That is why has been converting the user's consumption patterns and consumer culture. Open markets is provides of making a wide variety of events and lowest price policies, safe transactions etc, for attract the consumers of expand distribution channels of the web and via mobile. In this paper, a designs of provides a search system for minimum price product information to the user of Information collect and analyze on sale from open market.

• The Journal of Korea Robotics Society
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• v.17 no.4
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• pp.407-416
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• 2022

Multiple AMRs have been proved to be effective in improving warehouse productivity by eliminating workers' wasteful walking time. Although Multi-agent Path Finding (MAPF)-based solution is an optimal approach for this task, its deployment in practice is challenging mainly due to its imperfect plan-execution capabilities and insufficient computing resources for high-density environments. In this paper, we present a MAPF-based fleet management system architecture that robustly manages multiple robots by re-computing their paths whenever it is necessary. To achieve this, we defined four events that trigger our MAPF solver framework to generate new paths. These paths are then delivered to each AMR through ROS2 message topic. We also optimized a graph structure that effectively captures spatial information of the warehouse. By using this graph structure we can reduce computational burden while keeping its rescheduling functionality. With proposed MAPF-based fleet management system, we can control AMRs without collision or deadlock. We applied our fleet management system to the real logistics warehouse with 10 AMRs and observed that it works without a problem. We also present the usage statistic of adopting AMRs with proposed fleet management system to the warehouse. We show that it is useful over 25% of daily working time.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.309-318
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• 2009

The researches on the system that automatically records and retrieves one's everyday life is relatively actively worked recently. These systems, called personal memex or life log, usually entail dedicated devices such as SenseCam in MyLifeBits project. This research paid attention to the digital devices such as mobile phones, credit cards, and digital camera that people use everyday. The system enables a person to store everyday life systematically that are saved in the devices or the deviced-related web pages (e.g., phone records in the cellular phone company) and to refer this quickly later. The data collection agent in the proposed system, called MyMemex, collects the personal life log "web data" using the web services that the web sites provide and stores the web data into the server. The "file data" stored in the off-line digital devices are also loaded into the server. Each of the file data or web data is viewed as a memex event that can be described by 4W1H form. The different types of data in different services are transformed into the memex event data in 4W1H form. The memex event ontology is used in this transform. Users can sign in to the web server of this service to view their life logs in the chronological manner. Users can also search the life logs using keywords. Moreover, the life logs can be viewed as a diary or story style by converting the memex events to sentences. The related memex events are grouped to be displayed as an "episode" by a heuristic identification method. A result with high accuracy has been obtained by the experiment for the episode identification using the real life log data of one of the authors.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.469-479
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• 2014

N-RTK(Network based RTK) methods are able to improve the accuracy of GNSS positioning results through modelling of the distance-dependent error sources(i.e. primarily the ionospheric and tropospheric delays and orbit errors). In this study, the comparison of the TTFF(Time-To-Fix-First ambiguity), accuracy and discrepancies in horizontal/vertical components of N-RTK methods(VRS and FKP) with the static GNSS at 20 Unified Control Stations covering Incheon metropolitan city area during solar storms(Solar cycle 24 period) were performed. The results showed that the best method, compared with the statics GNSS survey, is the VRS, followed by the FKP, but vertical components of both VRS and FKP were approximately two times bigger than horizontal components. The reason for this is considered as the ionospheric scintillation because of irregularities in electron density, and the tropospheric scintillation because of fluctuations on the refractive index take the place. When the TTFF at each station for each technique used, VRS gave shorter initialization time than FKP. The possible reasons for this result might be the inherent differences in principles, errors in characteristics of different correction networks, interpolating errors of FKP parameters according to the non-linear variation of the dispersive and non-dispersive errors at rover when considering both domestic mobile communication infra and the standardized high-compact data format for N-RTK. Also, those test results revealed degradation of positing accuracy, long initialization time, and sudden re-initialization, but more failures to resolve ambiguity during space weather events caused by Sunspot activity and solar flares.

• Knowledge Management Research
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• v.18 no.1
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• pp.83-116
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• 2017

The purpose of this study is to analyze empirically analyze how the characteristics of participants in educational and social learning forums and the quality of events influence expectations and satisfaction of forums. The study also aims to provide strategic implications for forum organizers and give them suggestions on how to set up target audience, manage forum contents, speakers, and services, improve attendee satisfaction, and ultimately maximize overall outcomes. As exchanges among individuals, enterprises, and organizations, as well as countries are growing rapidly, the convention industry has become a key player in the market. Conventions have also become a venue for people to discuss a specific agenda or topic, exchange information and learn knowledge and insights. Especially, the forum - as part of the convention industry - plays a vital role providing educational and social learning opportunities as scholars and expertise come together to share their knowledge and experience through a variety of discussions. With its role, many of forums are taking place in recent years; however, there have been few empirical studies upon the forum itself. Also, there have been few attempts to research how the quality of forums affect participants' satisfaction along with their characteristics and how much of practical knowledge is provided throughout the events. This study is meaningful in that it is the first practical study that takes a deep understanding of the forum and sees how the quality of the forums influences participants' satisfaction and whether the characteristics of participants have a moderating effect in increasing the level of satisfaction. Forum organizers could also take a strategic approach as their major concerns are to increase the number of participants and raise degree of satisfaction by providing significant information. There are four key elements that determine success or failure of a social learning forum. The four elements are contents, speakers, services, and participants. Content plays an important role in providing rich information and knowledge for participants. Speakers are the main knowledge providers who contribute to the forum's social learning role. Also, the services provided by forum organizers such as simultaneous interpretation services, program brochures, lunch and refreshments, and the overall design of event hall can also influence the level of participants' satisfaction. Lastly, the participants and their characteristics are important since they are the ones who receive knowledge from the providers. The results of this study show that the quality of forum (content, speaker, and services) has a decisive effect on the participants' satisfaction and there are some differences in expectation among the participants in the forum. Also, some groups of participants were more likely to be stimulated by the quality of forum when determining their satisfaction. The study is modeled after MBN Y Forum 2016 and its participants' characteristics. The forum is one of the most representative social learning forums of South Korea and its audiences are mostly young people. It has analyzed how the participants' characteristics influence their satisfaction by grouping them into ${\Delta}participants$ who have invited for free and those who paid for the entrance fee, ${\Delta}first-time$ participants and returning participants, ${\Delta}voluntary$ and involuntary participants, ${\Delta}participants$ who registered through web and those who did through mobile, and ${\Delta}participants$ who registered during pre-sale opens and those who registered during general opens.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.10
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• pp.447-454
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• 2015

This paper proposes geographical name denoising by machine learning of event detection based on twitter. Recently, the increasing number of smart phone users are leading the growing user of SNS. Especially, the functions of short message (less than 140 words) and follow service make twitter has the power of conveying and diffusing the information more quickly. These characteristics and mobile optimised feature make twitter has fast information conveying speed, which can play a role of conveying disasters or events. Related research used the individuals of twitter user as the sensor of event detection to detect events that occur in reality. This research employed geographical name as the keyword by using the characteristic that an event occurs in a specific place. However, it ignored the denoising of relationship between geographical name and homograph, it became an important factor to lower the accuracy of event detection. In this paper, we used removing and forecasting, these two method to applied denoising technique. First after processing the filtering step by using noise related database building, we have determined the existence of geographical name by using the Naive Bayesian classification. Finally by using the experimental data, we earned the probability value of machine learning. On the basis of forecast technique which is proposed in this paper, the reliability of the need for denoising technique has turned out to be 89.6%.

• Journal of Life Science
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• v.29 no.9
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• pp.1047-1054
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• 2019

Transposable elements (TEs) occupy approximately 45% of the human genome and can enter functional genes randomly. During evolutionary radiation, multiple copies of TEs are produced by duplication events. Those elements contribute to biodiversity and phylogenomics. Most of them are controlled by epigenetic regulation, such as methylation or acetylation. Every species contains their own specific mobile elements, and they are divided into DNA transposons and retrotransposons. Retrotransposons can be divided by the presence of a long terminal repeat (LTR). They show various biological functions, such as promoter, enhancer, exonization, rearrangement, and alternative splicing. Also, they are strongly implicated to genomic instability, causing various diseases. Therefore, they could be used as biomarkers for the diagnosis and prognosis of diseases such as cancers. Recently, it was found that TEs could produce miRNAs, which play roles in gene inhibition through mRNA cleavage or translational repression, binding seed regions of target genes. Studies of TE-derived miRNAs offer a potential for the expression of functional genes. Comparative analyses of different types of miRNAs in various species and tissues could be of interest in the fields of evolution and phylogeny. Those events allow us to understand the importance of TEs in relation to biological roles and various diseases.

• Journal of the Korean Society of Costume
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• v.64 no.1
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• pp.136-151
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• 2014

This study systematically analyzed types of fashion brand application focusing on accounts created in Korea. While referring to 'Chanel' which has developed a fashion brand app for the first time in August of 2008, not only for App store by Apple Inc. of the greatest market share but also for Android market, the one and only competitor of App store, the study examined cases of fashion brand app in Korea and foreign countries which have been in service till August of 2013 since the year of 2008. To achieve the research goal, the study conducted a literature research and a case review, categorizing the app by their distinctive functions which were Basic Information, SNS, AR, LBS, Entertainment, Mobile Shopping and Live Streaming. As for the first function, Basic Information, it was considered to provide information on a brand such as prices, sizes and colors of products which should be the most fundamental function of a fashion brand. The function would include look book, catalogues, photographs and others of products, helping users of the app with their understanding on images and concepts of the brand. Second, SNS function was considered useful for its mobility and communication and with the help of theirs, the users share fashion information with each other. Third, AR function as in a filed of virtual reality would edit virtual objects to look real in an actual environment. This would eventually offer the users a chance to try for clothes virtually. The fourth function, LBS, would work with GPS to find a store closest from a present location. This would be a help when the users try to find stores holding promotion events or trails while hiking in mountains. The fifth Entertainment function would include all sorts of games and chances for the users to listen to music and keep fashion diaries. The sixth function, Mobile Shopping, would help the users purchase items online via the app as they would not visit a store in person. The seventh function, Live Streaming, would give the users chances to actually see fashion collections in real time, held all over the world in every season. Because of this function, not only fashion experts but also regular people have become able to enjoy the fashion shows. The distinctive characteristics of the fashion brand application discussed in the study will be a useful reference when any relevant fields try to design other new fashion brand application.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.12-19
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• 2020

The clustered heterogeneous wireless sensor network is comprised of sensor nodes and cluster heads, which are hierarchically organized for different objectives. In the network, we should especially take care of managing node resources to enhance network performance based on memory and battery capacity constraints. For instances, if some interesting events occur frequently in the vicinity of particular sensor nodes, those nodes might receive massive amounts of data. Data congestion can happen due to a memory bottleneck or link disconnection at cluster heads because the remaining memory space is filled with those data. In this paper, we utilize drones as mobile sinks to resolve data congestion and model the network, sensor nodes, and cluster heads. We also design a cost function and a congestion indicator to calculate the degree of congestion. Then we propose a data congestion map index and a data congestion mapping scheme to deploy drones at optimal points. Using control variable, we explore the relationship between the degree of congestion and the number of drones to be deployed, as well as the number of drones that must be below a certain degree of congestion and within communication range. Furthermore, we show that our algorithm outperforms previous work by a minimum of 20% in terms of memory overflow.