• Nuclear Engineering and Technology
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• v.27 no.1
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• pp.33-44
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• 1995

Public acceptance has become an important factor in nuclear power program particularly after Chernobyl accident and recent rapid democratization in Korea. Methods reflecting public opinions in order to improve public acceptance are firstly to understand what the public think about nuclear power plant and secondly to find out the public preference values for its policies. For this purpose, simplified multi-attribute utility (MAU) model was applied to analyze the public perception pattern for fire power production systems. And the conjoint analysis was applied to find out the quantitative values of public preferences for twelve policy alternatives to improve the safety and to support communities surrounding nuclear power plants in Korea. To implement these perception and preference analyses, mail survey was conducted to the Qualified sample who had the experience of visiting nuclear power plant. Diagnosis of their perception pattern for five power production systems was made by the simplified MAU model. Estimation of the quantitative preference values for potential policy alternatives was made by the conjoint measurement technique, which made it possible to forecast the effectiveness of each option. The results from the qualified sample and the methods used in this study would be helpful to set up new policy of nuclear power plant.

• Journal of Information Management
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• v.40 no.1
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• pp.113-132
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• 2009

Unlike existing other industries, the knowledge-based industry has the potential to grow increasingly with factor input unlimited. Importance of investigating knowledge and information evaluation cannot be overemphasized to promote economic development in that knowledge and information is accepted as an engine of new economy. We attempt to define the scope and value of knowledge and information and develop the knowledge and information value model. The results help policy-makers to manage and evaluate the knowledge and information with useful and responsible information.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.12
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• pp.1721-1732
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• 2007

This study identified types of information source, and explored a path model for consumer information search by shopping attributes in the context of online decision making. Participants completed self-administered questionnaires during regularly scheduled classes. A total of 219 usable questionnaires were obtained from respondents who enroll at universities in the southwestern region of the United States. For data analysis, factor analysis and path model estimation were used. Consumer information source was classified into three types for online clothing purchases: Online source, Offline retail source, and Mass media. Consumers were more likely to rely on offline retail source for online clothing purchases, than other sources. In consumer information search by shopping attributes, online sources were more likely to be related to transaction-related attributes(e.g., incentive service), whereas offline retail source(e.g., displays in stores, manufacturer's catalogs and pamphlets) were more likely to be related to product and market related attributes(e.g., aesthetics, price) when purchasing clothing online. Also, the path model emphasizes the effect of shopping attributes on traditional retailer search behavior, leading to online purchase intention for clothing. This study supports consumer information search by attributes, and discusses a managerial implication of multi-channel retailing for apparel.

• Journal of Digital Convergence
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• v.13 no.4
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• pp.227-233
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• 2015

The recent health care is growing rapidly want to receive offers users a variety of medical services, can be exploited easily exposed to a third party information on the role of the patient's hospital staff (doctors, nurses, pharmacists, etc.) depending on the patient clearly may have to be classified. In this paper, in order to ensure safe use by third parties in the health care environment, classify the attributes of patient information and patient privacy protection technique using hierarchical multi-property rights proposed to classify information according to the role of patient hospital officials The. Hospital patients and to prevent the proposed method is represented by a mathematical model, the information (the data consumer, time, sensor, an object, duty, and the delegation circumstances, and so on) the privacy attribute of a patient from being exploited illegally patient information from a third party the prevention of the leakage of the privacy information of the patient in synchronization with the attribute information between the parties.

• Journal of the Korean earth science society
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• v.21 no.6
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• pp.719-733
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• 2000

Normally, a digital geologic map can be defined as mappable one whose spatial information with geographic information details and geologic database attribute, recorded in a digital format that is readable by computer. It shows fundamentally two different conceptual perspectives: cartography for digital mapping and analysis for geo-data processing. While, as both aspects basically relate to natural entities and their interpretation of complex features fused with multi-sources, digital geo-data mapping or geologic mapping, it should be distinguished from digital mapping in engineering such as UIS(Urban Infomation System) and AM/FM(Automated Mapping/Facilities Management). Furthermore, according to short-cycled development of GIS(Geographic Information System) software architecture based on IT(Information Technology) and wide expansion of GIS applications' fields, the importance of domain analysis and application model is emphasized at digital geologic informatizaion. In this paper, first terms and concepts of geo-data model with general data modeling aspects are addressed, and then case histories for geo-data modeling and several approaches for data modeling in GIS application fields are discussed. Lastly, tentative conceptual geo-data modeling by using UML(Unified Modeling Language) of OO(Object-oriented) concepts with respect to USGS/AASG geo-data mode is attempted. Through this approach, the main benefits for standardization and implementation lineage with conceptual model in consideration to reusability are expected. Conclusively, it is expected that geo-information system and its architecture by UML is the new coming key approach for the GIS application in geo-sciences.

• The Journal of Society for e-Business Studies
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• v.9 no.4
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• pp.19-36
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• 2004

This paper suggests a business process between the collaborative companies that want to extend globally sales and delivery service with restricted physical branches in their own areas. The companies integrate their business processes for sales and delivery services using a shared product taxonomy table. In order to perform the collaborative processes, they need the algorithm to exchange their own products. We suggest a similar product finding algorithm to compose the product taxonomy table that defines product relationships to exchange them between the companies. The main idea of the proposed algorithm is using a multi-attribute decision making (MADM) to find the utility values of products in a same product class of the companies. Based on the values we determine what products are similar. It helps the product manager to register the similar products into a same product sub-category. The companies then allow consumer to shop and purchase the products at their own residence site and deliver them or similar products to another sites.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4531-4544
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• 2021

Because the traditional network information security vulnerability risk assessment method does not set the weight, it is easy for security personnel to fail to evaluate the value of information security vulnerability risk according to the calculation value of network centrality, resulting in poor evaluation effect. Therefore, based on the network security data element feature system, this study designed a quantitative assessment method of network information security vulnerability detection risk under single transmission state. In the case of single transmission state, the multi-dimensional analysis of network information security vulnerability is carried out by using the analysis model. On this basis, the weight is set, and the intrinsic attribute value of information security vulnerability is quantified by using the qualitative method. In order to comprehensively evaluate information security vulnerability, the efficacy coefficient method is used to transform information security vulnerability associated risk, and the information security vulnerability risk value is obtained, so as to realize the quantitative evaluation of network information security vulnerability detection under single transmission state. The calculated values of network centrality of the traditional method and the proposed method are tested respectively, and the evaluation of the two methods is evaluated according to the calculated results. The experimental results show that the proposed method can be used to calculate the network centrality value in the complex information security vulnerability space network, and the output evaluation result has a high signal-to-noise ratio, and the evaluation effect is obviously better than the traditional method.

• Journal of Korea Game Society
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• v.9 no.5
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• pp.25-41
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• 2009

The objective of this study is to develop an analytic framework to code systematically the gamer's behaviour in MMO(Massively Multi-player Online) gameplay experience, to explore their gameplay as a problem solving procedure empirically. Previous studies about model human processor, content based protocol, and procedure based protocol are reviewed in order to build the outline of the analytic framework related to MMO gameplay. The specific gameplay actions and contents were derived by using concurrent protocol analysis method through the empirical experiment executed in MMORPG gameplay. Consequently, gameplay are divided into six actions : kinematics, perception, function, representation, simulation, and rule (heuristics, following, and transcedence). The analytic framework suitable for MMO gameplay was built. As a result of this study, we found three rule spaces in the problem solving domain of gameplay that are an heuristics, a following of the rule, and a transcendence of the rule. 'Heuristics' denotes the rule action that discovers the rule of game through trial-and-error. 'Following' indicates the rule action that follows the rule of game embedded in game by game designers. 'Transcendence' presents the rule action that transcends that. The new discovered rule spaces where 'Following' and 'Transcendence' actions occur and the gameplay pattern in them is provided with the key basis to determine the level design elements of MMO game, such as terrain feature, monster attribute, item, and skill et cetera. Therefore, this study is concludes with key implications to support game design to improve the quality of MMO game product.

• Journal of Korean Library and Information Science Society
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• v.53 no.2
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• pp.355-375
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• 2022

This study is to grasp LRM's feature and applications plan to reflect LRM to cataloging related standards and individual system through comparing and analyzing LRM with the FR model in terms of entities, attributes, and relationships. The application plan is suggested as follows. First, the entity can be extended by defining sub-entities of each entity in the standards and the individual system in order to reflect LRM, even though entities such as families, groups, identifiers, authorized access points, concepts, objects, events, agency and rules have been deleted in LRM. Second, the attribute should be subdivided in the standards and the individual system in order to apply LRM, though many attributes have been changed to relationships for linked data and decreased in LRM. In particular, more specific and detailed property names in the standards and the individual system should be clearly presented, and the vocabulary encoding scheme corresponding to each property should be also developed, since properties with similar functions or repetition in various entities, and material specific properties are generalized and integrated into comprehensive property names. Third, the relationship should be extended through newly declaring the refinement or subtype of the relationship and considering a multi-level relationship, since the relationship itself is general and abstract under increasing the number of relationships in comparing to the property. This study will be practically utilized in cataloging related standards and individual system for applying LRM.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.