• Journal of Korean Society for Quality Management
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• v.21 no.1
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• pp.78-95
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• 1993

The art of designing and analyzing fault-tolerant computers is surveyed with special emphasis on problems of analyzing the behavior of computers that have autonomous repair capability. The survey covers the following topics : (1) general issues in computer reliability, (2) fault-tolerance state relations and requirements, (3) computational hierarchy, (4) fault characteristics, (5) fault diagnosis, (6) fault-tolerance schemes for logic network and machines, (7) fault-coverage effects, and (8) fault-tree analysis of coverage. This paper does not include techniques for verifying nonredundant hardware or system software designs or for verifying the correctness of application programs.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.11a
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• pp.75-76
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• 2019

The purpose of this study is to achieving a sufficient fluidity without segregation for normal strength grade concrete mixture. therefore in this research, by analyzing the various superplasticizer dosages on the concrete mixture, the segregation range was analyzed to provide a proper concrete mix design with sufficient fluidity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.3
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• pp.263-270
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• 2013

Recently, the prediction and analysis technology of marine environment are actively being studied since the ocean resources in the world is taken notice. The prediction of marine disaster by automatic collecting marine environment data and analyzing the collected data can contribute to minimized the damages with respect to marine pollution of oil spill and fisheries damage by red tide blooms and marine environment upsets. However the studies of the marine environment monitoring and analysis system are limited in South Korea. In this paper, we study the marine disasters prediction system model to analyze collection marine information of out sea and near sea. This paper proposes the models for the marine disasters prediction system as communication system model, a marine environment data monitoring system model, prediction and analyzing system model, and situations propagation system model. The red tide prediction model and summarizing and analyzing model is proposed for prediction and analyzing system model.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.5 no.6
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• pp.49-63
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• 2002

While the existing feng-shui is largely approached architecturally and geographically as positive place and negative place, the study is characterized by approaching and analyzing poong-soo environmentally. The theory of Eco-city as one of modern-city theories is worthy of studying by analyzing the merits and demerits of it and combining it with poong-soo and making a new alternative theory. Theory of Natural Energy and principle of Natural Balance. Thus, poong-soo ideas can be an important view of nature in analyzing the theory of Eco-city which is coming to the front these days. In particular, we try to make use of poong-soo as a basic theory for a city planning and design by studying and analyzing and combining the merits and demerits of Eco-city with poong-soo and presenting a new alternative method of a stable and balanced "refined city development". On the other hand, we connect 'theory with practice(or experience)' by covering all spaces variably from minimum unit space to city-space from the standpoint of poong-soo. But, problem of the Theory of Eco-city from the view of poong-soo are too artificial and theoretical, even if ideal. Conversely, from the view of Eco-city, the possibility of the practicability of Korean poong-soo is judged to be high. we can tell that among capital cities applied by poong-soo, historical cities like Beijing in China, Seoul in Korea and Tokyo in Japan are poong-soo cities in accordance with the requirements of Eco-city.

• Journal of Fashion Business
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• v.24 no.5
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• pp.52-71
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• 2020

This study examines the color characteristics of the usage of the color pink in menswear by analyzing its usage status and method. It involves an empirical research method establishing the frame of the study through a document study centered on trend, gender neutral considerations, and the utilization of the color pink in men's fashion, by analyzing the characteristics of color and tone by extracting the pink color shown in menswear collections as well as analyzing and categorizing the fashion image and genderless characteristics. Analyzing the color and tone of the pink color shown indicate that bright, light and pale tones had higher proportions. Pink color can also be said to be utilized as a design element that gives off a younger and more vital color image in menswear. Further, the use of brighter and softer pink colors can be interpreted as reflecting modern society's demands of masculinity to change into a more sophisticated and soft image. To analyze the characteristics of the color pink utilized in gender neutral fashion, fashion images were presented as the analysis standard. An image grouping technique was used to classify pink while utilizing genderless types-fashion style. The result showed that even with the same pink color, the fashion image can vary with different methods of expression in terms of clothes and styling. The results of this study can serve as basic data for planning fashion design concepts as it analyzed pink-using fashion images and the genderless concept type.

• Journal of Digital Convergence
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• v.16 no.8
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• pp.321-329
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• 2018

The aim of this study is to examine the effects on emotional empathy given by type and degree of adolescent participation in recreational activities, and investigate the associated causal relationships. The following conclusions were obtained: First, analyzing the differences in emotional empathy based on demographic characteristics, the results statistically indicated emotional contagion is a subfactor of emotional empathy. Second, analyzing the differences based on participation type, the results statistically indicated emotional contagion is more influential than positive sharing and emotional intervention, which are sub-factors of emotional empathy. Third, analyzing the differences based on participation degree, the variables influencing participation frequency, participation time, and participation period were positive sharing and emotional contagion, rather than emotional intervention. Fourth, analyzing the causal relationship between participation degree and emotional empathy, the results revealed that participation degree affects positive sharing and emotional contagion, which are sub-factors of emotional empathy.

• Journal of Korean Elementary Science Education
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• v.36 no.2
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• pp.113-128
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• 2017

This study aims to investigate the research trend of elementary environmental education. Thus, author keywords were extracted from a total of 197 academic these related to elementary environmental education during two different periods when detailed goals were applied to the 2007 and 2009 revised curriculums respectively, and then this study analyzed the network of author keywords. The results of this study can be summarized as below. Firstly, as a result of analyzing the frequency of author keywords from academic theses related to elementary environmental education, this study discovered 369 author keywords from the period when detailed goals were applied to 2009 revised curriculum. Out of them, it was found that the keyword, 'climate change education', showed the highest frequency, followed by 'environmental literacy' and 'environmental perception', except such central keywords as 'environmental education' and 'elementary school student'. From the period when detailed goals were applied to the 2007 revised curriculum, a total of 394 author keywords were discovered, and the keyword, 'environmental literacy', showed the highest frequency, followed by 'environmental perception' and 'ESD (education for sustainable development)'. Secondly, as a result of analyzing the network of author keywords, this study found out that in the total number of network connections, average connection degree, density and clique, the period when detailed goals were applied to the 2007 revised curriculum was somewhat higher than the period when detailed goals were applied to the 2009 revised curriculum. As a result of analyzing the centrality of author keywords, this study found out that during both the periods, 'environmental perception' and 'environmental literacy' were high in degree centrality and betweenness centrality, except such central keywords as 'environmental education' and 'elementary school student'. As a result of analyzing the components of author keywords as sub-networks, this study discovered 9 components from the period when detailed goals were applied to the 2009 revised curriculum and 6 components from the period when detailed goals were applied to the 2007 revised curriculum. During both the periods, the largest component was composed of keywords high in degree centrality and betweenness centrality.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2871-2877
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• 2015

Shopping patterns are changing with the emergence of SNS. Recently, it is also interested in providing the information based on the users' needs. Generally, the provided information is obtained from the history of users' simple browsing. Best selling hot item list is also provided in order to reflect the preferences of public users. However, the provided information is irrelevant to an individual preference. In this paper, we propose a method to utilize inner and outer SNS for analyzing public preferences about goods which are interested by individual users. The inner analyzing module collects and analyzes the preferences of community members about two goods designated by individual users. The outer analyzing module supports to analyze public preferences by using the tweeter SNS. The results of implementation show that it is possible to recommend goods based on the individual users' preferences unlike the existing shopping mall.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.661-664
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• 2017

Recently, during disasters occurrence, dealing with emergencies has been handled well by the early transmission of disaster relating notifications on social media networks (e.g., Twitter or Facebook). Intuitively, with their characteristics (e.g., real-time, mobility) and big communities whose users could be regarded as volunteers, social networks are proved to be a crucial role for disasters response. However, the amount of data transmitted during disasters is an obstacle for filtering informative messages; because the messages are diversity, large and very noise. This large volume of data could be seen as Social Big Data (SBD). In this paper, we proposed a big data platform for collecting and analyzing disasters' data from SBD. Firstly, we designed a collecting module; which could rapidly extract disasters' information from the Twitter; by big data frameworks supporting streaming data on distributed system; such as Kafka and Spark. Secondly, we developed an analyzing module which learned from SBD to distinguish the useful information from the irrelevant one. Finally, we also designed a real-time visualization on the web interface for displaying the results of analysis phase. To show the viability of our platform, we conducted experiments of the collecting and analyzing phases in 10 days for both real-time and historical tweets, which were about disasters happened in South Korea. The results prove that our big data platform could be applied to disaster information based systems, by providing a huge relevant data; which can be used for inferring affected regions and victims in disaster situations, from 21.000 collected tweets.

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.149-158
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• 2017

Big data have been presenting us with exciting opportunities and challenges in economic development. For instance, in the agriculture sector, mixing up of various agricultural data (e.g., weather data, soil data, etc.), and subsequently analyzing these data deliver valuable and helpful information to farmers and agribusinesses. However, massive data in agriculture are generated in every minute through multiple kinds of devices and services such as sensors and agricultural web markets. It leads to the challenges of big data problem including data collection, data storage, and data analysis. Although some systems have been proposed to address this problem, they are still restricted either in the type of data, the type of storage, or the size of data they can handle. In this paper, we propose a novel design of a platform for collecting and analyzing agricultural big data. The proposed platform supports (1) multiple methods of collecting data from various data sources using Flume and MapReduce; (2) multiple choices of data storage including HDFS, HBase, and Hive; and (3) big data analysis modules with Spark and Hadoop.