• Proceedings of the KSR Conference
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• 2005.05a
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• pp.193-198
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• 2005

According to the ISO 14040(1997), Life Cycle Assessment is not the tool only focusing on the emissions from the manufacturing processes of a product, but the tool also expressing environmental adverse impact quantitatively through products entire life cycle (i.e. raw material acquisition, manufacturing, transportation, use, and end-of-life stage). Because the LCA for EMUs(Electrical Multiple Units), however, requires astronomical time and cost for collecting big amount of data. it is inevitable to bring in the simplified LCA methodology, In this study, we introduced standardized methodology of LCA in the world, and found appropriate S-LCA methodology for EMUs. Furthermore, we recommended how to evaluate the environmental impact of EMUs in detail and precisely, using the S-LCA.

• Journal of the Korea Computer Graphics Society
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• v.22 no.5
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• pp.27-36
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• 2016

As big data become more complex than ever, there has been a need for various techniques and approaches to better analyze and explore such big data. A research discipline of visual analytics has been proposed to help users' visual data analysis and decision-making. Since 2006 when the first symposium of visual analytics was held, the visual analytics research has become popular as the advanced technology in computer graphics, data mining, and human-computer interaction has been incorporated in visual analytics. In this work we introduce the visual analytics research by reviewing and surveying the papers published in IEEE VAST 2015 in terms of data and visualization techniques to help domestics researchers' understanding on visual analytics.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.87-96
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• 2019

In this paper, we propose a MapReduce-supported clustering technique for collecting and classifying distributed workflow enactment event logs as a preprocessing tool. Especially, we would call the distributed workflow enactment event logs as Workflow BIG-Logs, because they are satisfied with as well as well-fitted to the 5V properties of BIG-Data like Volume, Velocity, Variety, Veracity and Value. The clustering technique we develop in this paper is intentionally devised for the preprocessing phase of a specific workflow process mining and analysis algorithm based upon the workflow BIG-Logs. In other words, It uses the Map-Reduce framework as a Workflow BIG-Logs processing platform, it supports the IEEE XES standard data format, and it is eventually dedicated for the preprocessing phase of the ${\rho}$-Algorithm that is a typical workflow process mining algorithm based on the structured information control nets. More precisely, The Workflow BIG-Logs can be classified into two types: of activity-based clustering patterns and performer-based clustering patterns, and we try to implement an activity-based clustering pattern algorithm based upon the Map-Reduce framework. Finally, we try to verify the proposed clustering technique by carrying out an experimental study on the workflow enactment event log dataset released by the BPI Challenges.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.1-30
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• 2024

The purpose of this study is to develop a diagnostic tool to strengthen the reading competencies of children and adolescents with disabilities, analyze its validity and reliability, and present basic data for the development of a diagnostic program. For this study, it was conducted on literature and case studies, the Delphi Method, and a preliminary survey of actual disabled children/adolescents. As a result of the study, there were limitations in validity and reliability analysis due to the small number of samples, but basic data was secured along with the development of a prototype diagnostic tool for the reading ability of children and adolescents with disabilities. It was proposed to develop the future reading competency diagnostic program by expanding it to the web and mobile platforms, considering various variables such as the characteristics of each disability type, a plan for data collection and utilization through big data, diagnostic procedures, and precautions during the diagnosis.

• The Journal of the Korea Contents Association
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• v.16 no.6
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• pp.260-269
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• 2016

With the development of genomics, wearable device and IT/NT, a vast amount of bio-medical data are generated recently. Also, healthcare industries based on big-data are booming and big-data technology based on bio-medical data is rising rapidly as a core technology for improving the national health and aged society. Also, oriental medicine research is focused with modern research technology and validate it's various biochemical effect by combining with molecular biology technology. However there are few searching system for finding biochemical mechanism which is related to major compounds in oriental medicine. Therefore, in this paper, we collected papers related with medical herbs from PubMed and constructed a medical herbs database to store and manage chemical, gene/protein and biological interaction information extracted by a literature analysis on the papers. Also, to supporting a multidimensional analysis on the database, we developed a network analysis system based on a hierarchy structure of chemical, gene/protein and biological interaction information. Finally, we expect this system will be used the major tool to discover various biochemical effect by combining with molecular biology technology.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.4
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• pp.177-182
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• 2024

The issue of teenage drinking and smoking has been raised repeatedly over the years. However, for various reasons, adolescents have continued to drink and smoke up to the present. Consequently, various preventive education programs are being implemented in all elementary, middle, and high schools, but these efforts have not been significantly effective in reducing the rates of adolescent drinking and smoking. Furthermore, while youth centers exist in various locations, they are often underutilized due to inadequate promotion or facilities. Given that drinking can lead to serious juvenile crimes, and there are indeed cases to this effect, preventive measures are absolutely necessary. Therefore, this paper analyzes the behavior of adolescents regarding drinking and smoking using public data. Based on the analysis conducted using R, a tool for big data analysis, this paper proposes measures to reduce the rates of adolescent drinking and smoking. The proposed measures focus more on prevention than on post-event solutions.

• Journal of Science of Art and Design
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• v.1
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• pp.95-123
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• 1999

The goal of this research is a visual and auditory tool development enabling designers to have the same emotional value with users in the process of user centered design. Through the research, we intend to show the aid measure for making cognitive gaps narrow between users and designer in the process of transforming and understanding the emotional needs as a verbal image. because In the business practice of design, most of tools and techniques for assessment and analysis of emotional needs are those used usually in the marketing fields. So the information generated and transformed from users to designers have a form of physical words. When the designer's understanding of the emotional needs is considered as a product mediated communication process, the morphologic and cognitive information gaps become obvious. This difference could be a false basis in designing with emotional user needs. So the alternative needs assessment sub-tools of visual and auditory information form was embodied mainly for designer's cognitive gaps and inter-cultural emotional needs assessment. As the method of embodiment, Firstly, adjectives related to emotion were classified in their cognitive dimension. Secondly, visual and auditory data were extracted, and then the relativity verified. Finally, the practicality and effectiveness were tested through the database generation. In view of the results so far achieved, 1. We could find being of the big information cognitive gaps in the verbal assessment of emotional needs between designers and users. 2. With the visual and auditory assessment tool, we could make the big cognitive gaps narrower than we expected. 3. Also, we could find the chance that the fidelity, recognition, and friendliness of design for emotional user needs would become better.

• Journal of KIISE
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• v.45 no.3
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• pp.280-287
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• 2018

Recently, the use of a recommendation system and tensor data analysis, which has high-dimensional data, is increasing, as they allow us to analyze the tensor and extract potential elements and patterns. However, due to the large size and complexity of the tensor, it needs to be decomposed in order to analyze the tensor data. While several tools are used for tensor decomposition such as rTensor, pyTensor, and MATLAB, since such tools run on a single machine, they are unable to handle large data. Also, while distributed tensor decomposition tools based on Hadoop can handle a scalable tensor, its computing speed is too slow. In this paper, we propose S-PARAFAC, which is a tensor decomposition tool based on Apache Spark, in distributed in-memory environments. We converted the PARAFAC algorithm into an Apache Spark version that enables rapid processing of tensor data. We also compared the performance of the Hadoop based tensor tool and S-PARAFAC. The result showed that S-PARAFAC is approximately 4~25 times faster than the Hadoop based tensor tool.

• Smart Media Journal
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• v.8 no.1
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• pp.59-66
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• 2019

The importance of data is increasing at a high rate as data is massively generated and taken into account in various policy supports and contents. However, because of their speed of growth, it is difficult to find the data that is needed. Both the methodological elements that summarize the data and the technical elements of the visualization that help to see at a glance are important. This paper summarizes data visualization methods to improve the currently used design - oriented infographics and propose data - centric infographics. In addition, we will present examples of data analysis and infographics production using Tableau Public. The Gwangju metropolitan city bus user data was used for infographics production, and the results show that the total number of passengers using the stopping point is similar to that of the general passengers, while it is different from the numbers of transit passengers and teen riding-and-transit passengers. Data-centric infographics visualization, unlike existing infographics that is pronounced only as a visual role, is expected to be used as a tool for scientific research as well as efficiently delivering data.

• Journal of Digital Contents Society
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• v.19 no.4
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• pp.771-777
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• 2018

This study proposes a big data based risk analysis framework to analyze more comprehensive disaster risk and vulnerability. We introduce a distributed and parallel framework that allows large volumes of data to be processed in a short time by using open-source disaster risk assessment tool. A performance analysis of the proposed system presents that it achieves a more faster processing time than that of the existing system and it will be possible to respond promptly to precise prediction and contribute to providing guideline to disaster countermeasures. Proposed system is able to support accurate risk prediction and mitigate severe damage, therefore will be crucial to giving decision makers or experts to prepare for emergency or disaster situation, and minimizing large scale damage to a region.