• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.6
• /
• pp.2021-2029
• /
• 2010

This paper suggested the method to design and analyze FMC robot's dispatching rule using the Simulation and Sequential Patterns. To do this, first of all, we built FMC using simulation and then, extracted signals that facilities call a robot, saved it as the log type. Secondly, we built robot's optimal path using the Sequential Pattern Mining with the results of analyzing the log and relationship between machine and robot actions. Lastly, we adapted it to the A corp.'s manufacturing line for verifying its performance. As a result of applying the new dispatching rule in FMC, total throughput and total flow time decrease because of decreasing material loss time and increasing robot utility. Furthermore, because this method can be applied for every manufacturing plant using simulation, it can contribute to advance total FMC efficiency as well.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.4
• /
• pp.1739-1750
• /
• 2012

This study was to develop the assessment of medical service outcome using administration data through compared with hospital standardized mortality ratios(HSMR) in various hospitals. This study analyzed 63,664 cases of Hospital Discharge Injury Data of 2007 and 2008, provided by Korea Centers for Disease Control and Prevention. We used data mining technique and compared decision tree and logistic regression for developing risk-adjustment model of in-hospital mortality. Our Analysis shows that gender, length of stay, Elixhauser comorbidity index, hospitalization path, and primary diagnosis are main variables which influence mortality ratio. By comparing hospital standardized mortality ratios(HSMR) with standardized variables, we found concrete differences (55.6-201.6) of hospital standardized mortality ratios(HSMR) among hospitals. This proves that there are quality-gaps of medical service among hospitals. This study outcome should be utilized more to achieve the improvement of the quality of medical service.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.11
• /
• pp.670-681
• /
• 2016

Recently, based on Internet and mobile environments, the Fintech industry that fuses finance and IT together has been rapidly growing and Fintech services armed with simplicity and convenience have been leading the conversion of all financial services into online and mobile services. However, despite the rapid growth of the Fintech industry, few studies have classified Fintech technologies into detailed technologies, analyzed the technology development trends of major market countries, and supported technology planning. In this respect, using Fintech technological data in the form of unstructured data, the present study extracts and defines detailed Fintech technologies through the topic modeling technique. Thereafter, hot and cold topics of the derived detailed Fintech technologies are identified to determine the trend of Fintech technologies. In addition, the trends of technology development in the USA, South Korea, and China, which are major market countries for major Fintech industrial technologies, are analyzed. Finally, through the analyses of networks between detailed Fintech technologies, linkages between the technologies are examined. The trends of Fintech industrial technologies identified in the present study are expected to be effectively utilized for the establishment of policies in the area of the Fintech industry and Fintech related enterprises' establishment of technology strategies.

• Journal of KIISE:Computing Practices and Letters
• /
• v.15 no.3
• /
• pp.178-188
• /
• 2009

A blog is a personal website where its owner publishes his/her articles for others. A blog can have relationships with other blogs. In this paper, we define a network that is composed of blogs connected together with such relationships as a blog network. Blog networks can have two different propensities characterized by the articles published in the blogs: information-valued propensity and friendship-valued propensity. The degree of each propensity of a blog network plays an important role in deciding business policies for blog networks. In this paper, we address the problem of determining the degrees of two propensities of a given blog network. First, we determine the degree of the propensity of every relationship, a basic unit of a blog network, by using classification that is one of data mining functionalities. Then, by utilizing the result thus obtained, we compute the degrees of two propensities of the whole blog network. Also, we propose a method to solve the problem that the degree of propensities depends on the size of blog networks. To verify the superiority of the proposed approach, we perform extensive experiments using a huge volume of real-world blog data. The results show that our approach provides high accuracy of around 93% in determining the degrees of both propensities of relationships between arbitrary two blogs. We also verify the applicability of the proposed approach by showing that if determines the degrees of the information-valued and friendship-valued propensities correctly in real-world blog networks.

• Resources Recycling
• /
• v.22 no.2
• /
• pp.29-36
• /
• 2013

Although Korean domestic production of flat panel displays totalled more than 48 trillion KRW in 2007, most of the flat panel display wastes have been land-filled or incinerated, which greatly overshadows Korean national prestige as a world leading producer and developer of flat panel display devices. Countries such as Japan or EU possess quite limited land-fill capability and have sought ways to dispose of WEEEs from environment-friendly perspective rather than recovery of valuable materials from the wastes. Considering relatively short cycle of about 5 years for flat panel display devices, it is estimated that more than 5 million units will be accumulated as wastes by 2015. Urban mining is a most suitable countermeasures against China's monopoly of rare and rare earth metals, which are contained in flat panel display wastes. Therefore, materials recycling of waste LCD units has to be developed and commercialized soon enough for economic and environment-friendly recovery of valuable resources hidden in LCD wastes.

• Resources Recycling
• /
• v.23 no.2
• /
• pp.3-16
• /
• 2014

Car exhaust $CO_2$ gas reduction and fuel efficiency of the car lighter for the current era is a big challenge. The developments of high-performance Nd magnets, Li-ion secondary battery and exhaust gas purification performance of PGM catalysts used in the lightweight EV and HEV are activated. Country in order to improve the car lighter and function that use the resources of rare metals are ubiquitous imported from China because of export supply control, as soaring prices have unstable supply and demand. Compared to the emissions from the next-generation automotive recycling, waste scarce resources need to be. This study investigated the recycling technology analysis and development of the information technology, or delivered to the researchers by giving national car industry aims to contribute to the development. Findings, pulmonary high-performance motor vehicle emissions in the exhaust gas purification PGM Catalysts, Li-ion battery and Nd magnets recycling technology, such as pre- and post-processing techniques to classify technology, pre-urban mining technology mechanical separation by screening techniques under development, the study and post-processing technology has, pyro and hydro metallurgical smelting technology is established. Waste Recycling in terms of economic efficiency of mechanical components for the intensive study of screening techniques is needed.

• Journal of the Korea Society for Simulation
• /
• v.15 no.3
• /
• pp.23-30
• /
• 2006

A recommender system for E-commerce site receives information from customers about which products they are interested in, and recommends products that are likely to fit their needs. In this paper, we investigate several methods for large-scale product purchase data for the purpose of producing useful recommendations to customers. We apply the traditional data mining techniques of cluster analysis and collaborative filtering(CF), and CF with reduction of product-dimensionality by use of latent semantic indexing(LSI). If reduced product-dimensionality obtained from LSI shows a similar latent trend of customers for buying products to that based on original customer-product purchase data, we expect less computational effort for obtaining the nearest-neighbor for target customer may improve the efficiency of recommendation performance. From simulation experiments on synthetic customer-product purchase data, CF-based method with reduction of product-dimensionality presents a better performance than the traditional CF methods with respect to the recall, precision and F1 measure. In general, the recommendation quality increases as the size of the neighborhood increases. However, our simulation results shows that, after a certain point, the improvement gain diminish. Also we find, as a number of products of recommendation increases, the precision becomes worse, but the improvement gain of recall is relatively small after a certain point. We consider these informations may be useful in applying recommender system.

• Journal of Service Research and Studies
• /
• v.3 no.2
• /
• pp.53-60
• /
• 2013

Datamining from the large data in the form of various techniques for obtaining information have been developed. In recent years one of the most sought areas of pattern recognition and machine learning method is created with most of existing learning algorithms based on categorical attributes to a rule or decision model. However, the real-world data, it may consist of numeric attributes in many cases. In addition it contains attributes with numerical values to the normal categorical attribute. In this case, therefore, it is required processes in order to use the data to learn an appropriate value for the type attribute. In this paper, the domain of the numeric attributes are divided into several segments using learning algorithm techniques of discritization. It is described Clustering with other data mining techniques. Large amount of first cluster with characteristics is similar records from the database into smaller groups that split multiple given finite patterns in the pattern space. It is close to each other of a set of patterns that together make up a bunch. Among the set without specifying a particular category in a given data by extracting a pattern. It will be described similar grouping of data clustering technique to classify the data.

• International Commerce and Information Review
• /
• v.16 no.5
• /
• pp.151-178
• /
• 2014

The objective of the present case study is to analysis how effectively Hilti, which is a former family firm owned and managed by a family in Liechtenstein as a tiny european country, a land sandwiched between Switzerland and Austria, has made a global market success. Liechtenstein has $160km^2$ land and about 36,000 residents. Despite its small size of country, however, Hilti Corporation doesn't view its location as a liability in its business strategy. Hilti is a global leading provider of professional power tools in building, mining, civil engineering etc. Also, Hilti is a firm with a clear vision to become the leading industry partner for construction professionals and building installations through customer focus, high quality equipment, and tools and systems specially designed for specific jobs. This study considered Hilti as a good case, which verifies that born-conditions, endogenous factors according to Michael Porters diamond model does not decisive role more for international competitiveness of firms. Lessons from Hilti are that in order to obtain and sustain the global competitiveness of small and medium-sized firms in Korean manufacturing sector under high production cost, they have to do actively innovative. Also they can give to customers newer and higher customer-values than competitors in abroad give. The case summarizes that the strategy of Hilti for the global market success is comprised of several factors: Technological and organizational innovation, and a clear customer-value oriented business strategy and its implementation. Innovation and its integration into marketing for the customers value creation is central to Hilti's Success. The present case study is expected to provide insights and implication for many firms in Korea that are seeking to secure global presence and market success.

• Journal of the Korean Geosynthetics Society
• /
• v.15 no.1
• /
• pp.59-70
• /
• 2016

The purpose of this study is to review that the VE techniques can be used as a selection tool of borrow pit locations. The analysis of the soil investigation report is performed for the selection of proposed borrow pit site on a large-scale residential development area. Possible earthwork volume of mining is estimated and the weighting matrix evaluation is applied to the VE techniques. After determining the evaluation items for VE assessment, important degree was calculated. The Rating and evaluation of performance is carried out on a proposed borrow pit site. And, development priority has to be decided for a proposed borrow pit sites. As a result, the relative construction cost is closely related to the haulage distance. As the haulage distance increases, the relative construction cost will be increased. Therefore, it was confirmed quantitatively that haulage distance has a significant impact on the select of borrow pits. Also, it was found that the condition of borrow pits itself is important, but it cannot be ignored the impact of the life cycle cost for the selection of optimal borrow pit sites.