• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.179-196
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• 2019

Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.

• Korean Journal of Mineralogy and Petrology
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• v.33 no.3
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• pp.195-214
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• 2020

The Samgwang Au-Ag deposit has been one of the largest deposits in Korea. The deposit consists of eight lens-shaped quartz veins which filled fractures along fault zones in Precambrian metasedimentary rock, which feature suggest that it is an orogenic-type deposit. The Ti-bearing minerals occur in wallrock (titanite, ilmenite and rutile) and laminated quartz vein (rutile). They occur minerals including biotite, muscovite, chlorite, white mica, monazite, zircon, apatite in wallrock and white mica, chlorite, arsenopyrite in laminated quartz vein. Chemical composition of titanite has maximum vaules of 3.94 wt.% (Al₂O₃), 0.49 wt.% (FeO), 0.52 wt.% (Nb₂O₅), 0.46 wt.% (Y₂O₃) and 0.43 wt.% (V₂O₅). Titanite with 0.06~0.14 (Fe/Al ratio) and 0.06~0.15 (X_Al (=Al/Al+Fe³⁺+Ti)) corresponds with metamorphic origin and low-Al variety. Chemical composition of ilmenite has maximum values of 0.07 wt.% (ZrO₂), 0.12 wt.% (HfO₂), 0.26 wt.% (Nb₂O₅), 0.04 wt.% (Sb₂O₅), 0.13 wt.% (Ta₂O₅), 2.62 wt.% (As₂O₅), 0.29 wt.% (V₂O₅), 0.12 wt.% (Al₂O₃) and 1.59 wt.% (ZnO). Chemical composition of rutile in wallrock and laminated quartz vein has maximum values of 0.35 wt.%, 0.65 wt.% (HfO₂), 2.52 wt.%, 0.19 wt.% (WO₃), 1.28 wt.%, 1.71 wt.% (Nb₂O₃), 0.03 wt.%, 0.07 wt.% (Sb₂O₃), 0.28 wt.%, 0.21 wt.% (As₂O₅), 0.68 wt.%, 0.70 wt.% (V₂O₃), 0.48 wt.%, 0.59 wt.% (Cr₂O₃), 0.70 wt.%, 1.90 wt.% (Al₂O₃) and 4.76 wt.%, 3.17 wt.% (FeO), respectively. Rutile in laminated quartz vein is higher contents (HfO₂, Nb₂O₃, As₂O₅, Cr₂O₃, Al₂O₃ and FeO) and lower content (WO₃) than rutile in wallrock. The substitutions of rutile in wallrock and laminated quatz vein are as followed : rutile in wallrock [(Fe³⁺, Al³⁺, Cr³⁺) + Hf⁴⁺ + (W⁵⁺, As⁵⁺, Nb⁵⁺) ⟵⟶ 2Ti⁴⁺ + V⁴⁺, 2Fe²⁺ + (Al³⁺, Cr³⁺) + Hf⁴⁺ + (W⁵⁺, As⁵⁺, Nb⁵⁺) ⟵⟶ 2Ti⁴⁺ + 2V⁴⁺], rutile in laminated quartz vein [(Fe³⁺, Al³⁺) + As⁵⁺ ⟵⟶ Ti⁴⁺ + V⁴⁺, (Fe³⁺, Al³⁺) + As⁵⁺ ⟵⟶ Ti⁴⁺ + Hf⁴⁺, 4(Fe³⁺, Al³⁺) ⟵⟶ Ti⁴⁺ + (W⁵⁺, Nb⁵⁺) + Cr³⁺], respectively. Based on these data, titanite, ilmenite and rutile in wallrock were formed by resolution and reconcentration of cations (W⁵⁺, Nb⁵⁺, As⁵⁺, Hf⁴⁺, V⁴⁺, Cr³⁺, Al³⁺, Fe³⁺, Fe²⁺) in minerals of wallrock during regional metamorphism. And then rutile in laminated quartz vein was formed by reconcentration of cations (Nb⁵⁺, As⁵⁺, Hf⁴⁺, Cr³⁺, Al³⁺, Fe³⁺, Fe²⁺) in alteration minerals (white mica, chlorite) and Ti-bearing minerals reaction between hydrothermal fluid originated during ductile shear and Ti-bearing minerals (titanite, ilmenite and rutile) in wallrock.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.33-54
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• 2021

With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.