• Applied Microscopy
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• v.50
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• pp.2.1-2.7
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• 2020

Electron energy loss spectroscopy (EELS) is an analytical technique that can provide the structural, physical and chemical information of materials. The EELS spectra can be obtained by combining with TEM at sub-nanometer spatial resolution. However, EELS spectral information can't be obtained easily because in order to interpret EELS spectra, we need to refer to and/or compare many reference data with each other. And in addition to that, we should consider the different experimental variables used to produce each data. Therefore, reliable and easily interpretable EELS standard reference data are needed. Our Electron Energy Loss Data Center (EELDC) has been designated as National Standard Electron Energy Loss Data Center No. 34 to develop EELS standard reference (SR) data and to play a role in dissemination and diffusion of the SR data to users. EELDC has developed and collected EEL SR data for the materials required by major industries and has a total of 82 EEL SR data. Also, we have created an online platform that provides a one-stop-place to help users interpret quickly EELS spectra and get various spectral information. In this paper, we introduce EEL SR data, the homepage of EELDC and how to use them.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• The Journal of the Korea Contents Association
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• v.17 no.6
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• pp.540-550
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• 2017

To investigate a variety of nonpharmacologic interventions have confirmed what the symptoms and effects, mainly interventions by acting on behavioral and psychological symptoms of dementia was conducted a meta-analysis. Data were collected from online search engines using search words from domestic and foreign article database. The researcher independently and among the pre-post experimental studies published from January 2000 to June 2016, recalled applying for the elderly with dementia presents the effect of treatment group and the control group RCT in this study were included in the study. The results of this meta-analysis showed that, effect size of the nonpharmacologic interventions of total -0.33, occupational therapy - 0.26, multi-sensory stimulation intervention -0.65 was significant beneficial effects to elderly with dementia(p<.05). According to interventions as a major affected the symptoms associated with behavioral problems, mainly aggression, memory-related problem behavior in the home-based program. Also, reminiscence therapy and occupational therapy is generally apathy, multi-sensory stimulation and music therapy was confirmed that there was a major change in behavior anxiety or agitation. The results of this study confirmed that various nonpharmacologic interventions were effective on behavioral psychological symptoms of dementia patients and confirmed the main symptoms of intervention.

• Information Systems Review
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• v.10 no.2
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• pp.137-158
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• 2008

Rapid development of various information technologies creates new opportunities in online and offline markets. In this changing market environment, customers have various demands on new products and services. Therefore, their power and influence on the markets grow stronger each year. Companies have paid great attention to customer relationship management. Especially, personalized product recommendation systems, which recommend products and services based on customer's private information or purchasing behaviors in stores, is an important asset to most companies. CRM is one of the important business processes where reliable information is mined from customer database. Data mining techniques such as artificial intelligence are popular tools used to extract useful information and knowledge from these customer databases. In this research, we propose a recommendation system that predicts customer's purchase intention. Then, customer's purchasing intention of specific product is predicted by using data mining techniques using receipt data set. The performance of this suggested method is compared with that of other data mining technologies.

• Journal of KIISE:Software and Applications
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• v.36 no.10
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• pp.777-785
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• 2009

Collaborative filtering is a technique used to predict whether a particular user will like a particular item. User-based or item-based collaborative techniques have been used extensively in many commercial recommender systems. In this paper, a hybrid collaborative filtering method that combines user-based and item-based methods using a low-dimensional linear model is proposed. The proposed method solves the problems of sparsity and a large database by using NMF among the low-dimensional linear models. In collaborative filtering systems the methods using the NMF are useful in expressing users as semantic relations. However, they are model-based methods and the process of computation is complex, so they can not recommend items dynamically. In order to complement the shortcomings, the proposed method clusters users into groups by using NMF and selects features of groups by using TF-IDF. Mutual information is then used to compute similarities between items. The proposed method clusters users into groups and extracts features of groups on offline and determines the most suitable group for an active user using the features of groups on online. Finally, the proposed method reduces the time required to classify an active user into a group and outperforms previous methods by combining user-based and item-based collaborative filtering methods.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.2
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• pp.495-500
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• 2015

Background: Published studies have reported relationships between X-ray repair cross-complementing group 1 (XRCC1) Arg399Gln polymorphism and lung cancer risk in Chinese population. However, the epidemiological results remained controversial. The objective of this study was to clarify the association of XRCC1 Arg399Gln polymorphism with lung cancer risk in the Chinese population. Materials and Methods: Systematic searches were performed through the database of Medline/Pubmed, Web of Science, Embase, CNKI and WanFang Medical Online. Odds ratios (ORs) with 95% confidence interval (95%CI) were calculated to estimate the strength of the association. Results: Overall, we observed an increased lung cancer risk among subjects carrying XRCC1 codon 399 Gln/Gln genotype (OR=1.36, 95%CI: 1.09-1.71) in the Chinese population on the basis of 19 studies with 5,416 cases and 5,782 controls. We did not observe any association between XRCC1 codon 399 Arg/Gln and Arg/Gln+Gln/Gln polymorphisms and lung cancer risk (OR=1.00, 95%CI: 0.92-1.08 and OR=1.05, 95%CI: 0.97-1.13, respectively). Limiting the analysis to studies with controls in agreement with Hardy-Weinberg equilibrium (HWE), we observed an increased lung cancer risk among subjects carrying XRCC1 codon 399 Gln/Gln genotype (OR=1.18, 95%CI: 1.01-1.38). When stratified by source of control, we observed an increased lung cancer risk among subjects carrying XRCC1 codon 399 Arg/Gln+Gln/Gln genotype on the basis of hospitalized patient-based controls (OR=1.21, 95%CI: 1.04-1.42) and among subjects carrying XRCC1 codon 399 Gln/Gln genotype on the basis of healthy subject-based controls (OR=1.22, 95%CI: 1.04-1.43). Conclusions: Our findings indicated that certain XRCC1 Arg399Gln variants might affect the susceptibility of lung cancer in Chinese population. Larger sample size studies are required to confirm our findings.

• Journal of Agricultural Extension & Community Development
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• v.21 no.4
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• pp.1149-1189
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• 2014

Nowadays, many farmers use online management diagnosis tool developed by Rural development agency(RDA) for the purpose of self-diagnosis of their farm management. Database(DB) was created using the diagnosis results and has been used for agri-firm management consulting. However, the amount of diagnosis data in the DB has been decreasing year by year. This means that the diagnosis tool of RDA did not reach farmers' expectation. Therefore it is necessary to develop a practical consulting tool which is applicable for various types of agri-firm management. This study introduces a management diagnosis tool and consulting method based on multi-contingency organization theory and value chain model for the purpose of improving existing tools and methods. The consulting method based on multi-contingency organization theory shows the core strategy of agri-firms by two different ways such as "efficiency-oriented" direction and "effectiveness-orientated" direction. Also, this method emphasizes that the performance of firm can be achieved when subelements of firm activities follow the same direction with the orientation of core strategy. The important thing is the right firm management activity fitted to its strategic direction. Through this action, limited firm resources can be optimized. In order to make itself understand, this study shows a practical example applied by this method from actual agri-firms.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.721-732
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• 2012

Patent information, which is generated under a specific, objective rule for a prolonged period of time, has the properties of technology, right, and management. Because of these characteristics of patents, patent analysis is used to identify R&D capacities and performances, and management strategies of a given nation or enterprise. In this paper, we analyze LTE essential patents which are key IPRs for implementing standardized LTE technology and major weapons in a global patent war. Total of 2,307 LTE essential patents, published and registered applications from European Telecommunications Standards Institute(ETSI)'s online IPR database as of January 2011, are analyzed in quantitative methods. The analysis results present status and statistics of LTE essential patents by major countries, applicant companies and technical fields. And a comparative study is done using 4 patent indices limited to the LTE essential patents issued in the United States. It is expected that results herein are useful for not only figuring out the technological competitiveness of countries and companies in LTE market, but also suggesting a guide to strategic IPR management for related industries.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.71-81
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• 2011

The EMR management services can monitoring the patients' record with any doctors in any hospital by using the internet and smartphones online. To handle the real time, multidimensional, continuous data, database management systems (DBMS) must cope with high insert rates for updates, however the traditional DBMS suffers from processing these kinds of data due to its serious design bottlenecks. So the researchers put forward to Data Stream Management System (DSMS). In this paper we describe the real-time Data Stream Server for Continuity of Care Record (CCR) that including continuos query processor. This system is compiled with DSMS and DBMS in EMR system for processing and monitoring the coming CCR data stream, and also storing the processed result with high-efficiency. The system enables users not only to query stored CCR information from DBMS, but also to execute continue query on real-time CCR Data Stream, and health information can be transferred between different healthcare providers that would reduce medical error. At last, we develop a IPhone mobile application to test the proposed real-time data stream server.

• Journal of Acupuncture Research
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• v.26 no.3
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• pp.133-147
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• 2009

Objectives : To review RCTs on acupuncture treatment for low back pain in order to establish a standard acupuncture treatment model in treating low back pain. Methods : RCT articles on traditional acupuncture treatment for low back pain were searched through online database. Study Quality was assessed using the FEAS. Results : Ten out of the one hundred six articles searched were reviewed. Among the ten articles reviewed, six articles compared acupuncture treatment with no treatment or non-penetrating sham acupuncture. All six articles concluded significantly positive effect of acupuncture compared to the control. Conclusions : The ideal acupuncture treatment model for low back pain was obtained as follows. A sterile disposable stainless steel(0.30mm${\times}$40mm) should be inserted to more than six acupuncture points on the BL, GV and GB meridians such as $BL_23$, $BL_25$, $BL_40$, $BL_60$, $GV_4$ and $GB_30$. Sparrow pecking method to obtain 'de-qi' is recommended and repeated stimulation during the 20 minute retention time is necessary. Ideal treatment frequency would be more than one a week for about 7 weeks.