• Economic and Environmental Geology
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• v.53 no.4
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• pp.347-362
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• 2020

Iron (hydro)oxides in aqueous environments are primarily formed due to mining activities, and they are known to be typical colloidal particles disturbing surrounding environments. Among them, hematites are widespread in surface environments, and their behavior is controlled by diverse factors in aqueous environments. This study was conducted to elucidate the effect of environmental factors, such as ionic composition and strength, pH, and natural organic matter (NOM) on the behavior of colloidal hematite particles. In particular, two analytical methods, such as dynamic light scattering (DLS) and single-particle ICP-MS (spICP-MS), were compared to quantify and characterize the behavior of colloidal hematites. According to the variation of ionic composition and strength, the aggregation/dispersion characteristics of the hematite particles were affected as a result of the change in the thickness of the diffuse double layer as well as the total force of electrostatic repulsion and van der Walls attraction. Besides, the more dispersed the particles were, the farther away the aqueous pH was from their point of zero charge (PZC). The results indicate that the electrostatic and steric (structural) stabilization of the particles was enhanced by the functional groups of the natural organic matter, such as carboxyl and phenolic, as the NOM coated the surface of colloidal hematite particles in aqueous environments. Furthermore, such coating effects seemed to increase with decreasing molar mass of NOM. On the contrary, these stabilization (dispersion) effects of NOM were much more diminished by divalent cations such as Ca²⁺ than monovalent ones (Na⁺), and it could be attributed to the fact that the former acted as bridges much more strongly between the NOM-coated hematite particles than the latter because of the relatively larger ionic potential of the former. Consequently, it was quantitatively confirmed that the behavior of colloidal hematites in aqueous environments was significantly affected by diverse factors, such as ionic composition and strength, pH, and NOM. Among them, the NOM seemed to be the primary and dominant one controlling the behavior of hematite colloids. Meanwhile, the results of the comparative study on DLS and spICPMS suggest that the analyses combining both methods are likely to improve the effectiveness on the quantitative characterization of colloidal behavior in aqueous environments because they showed different strengths: the main advantage of the DLS method is the speed and ease of the operation, while the outstanding merit of the spICP-MS are to consider the shape of particles and the type of aggregation.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.45-67
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• 2016

Given the recent development of smart devices, users are producing, sharing, and acquiring a variety of information via the Internet and social network services (SNSs). Because users tend to use multiple media simultaneously according to their goals and preferences, domestic SNS users use around 2.09 media concurrently on average. Since the information provided by such media is usually textually represented, recent studies have been actively conducting textual analysis in order to understand users more deeply. Earlier studies using textual analysis focused on analyzing a document's contents without substantive consideration of the diverse characteristics of the source medium. However, current studies argue that analytical and interpretive approaches should be applied differently according to the characteristics of a document's source. Documents can be classified into the following types: informative documents for delivering information, expressive documents for expressing emotions and aesthetics, operational documents for inducing the recipient's behavior, and audiovisual media documents for supplementing the above three functions through images and music. Further, documents can be classified according to their contents, which comprise facts, concepts, procedures, principles, rules, stories, opinions, and descriptions. Documents have unique characteristics according to the source media by which they are distributed. In terms of newspapers, only highly trained people tend to write articles for public dissemination. In contrast, with SNSs, various types of users can freely write any message and such messages are distributed in an unpredictable way. Again, in the case of newspapers, each article exists independently and does not tend to have any relation to other articles. However, messages (original tweets) on Twitter, for example, are highly organized and regularly duplicated and repeated through replies and retweets. There have been many studies focusing on the different characteristics between newspapers and SNSs. However, it is difficult to find a study that focuses on the difference between the two media from the perspective of supply and demand. We can regard the articles of newspapers as a kind of information supply, whereas messages on various SNSs represent a demand for information. By investigating traditional newspapers and SNSs from the perspective of supply and demand of information, we can explore and explain the information dilemma more clearly. For example, there may be superfluous issues that are heavily reported in newspaper articles despite the fact that users seldom have much interest in these issues. Such overproduced information is not only a waste of media resources but also makes it difficult to find valuable, in-demand information. Further, some issues that are covered by only a few newspapers may be of high interest to SNS users. To alleviate the deleterious effects of information asymmetries, it is necessary to analyze the supply and demand of each information source and, accordingly, provide information flexibly. Such an approach would allow the value of information to be explored and approximated on the basis of the supply-demand balance. Conceptually, this is very similar to the price of goods or services being determined by the supply-demand relationship. Adopting this concept, media companies could focus on the production of highly in-demand issues that are in short supply. In this study, we selected Internet news sites and Twitter as representative media for investigating information supply and demand, respectively. We present the notion of News Value Index (NVI), which evaluates the value of news information in terms of the magnitude of Twitter messages associated with it. In addition, we visualize the change of information value over time using the NVI. We conducted an analysis using 387,014 news articles and 31,674,795 Twitter messages. The analysis results revealed interesting patterns: most issues show lower NVI than average of the whole issue, whereas a few issues show steadily higher NVI than the average.

• Management & Information Systems Review
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• v.35 no.1
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• pp.85-116
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• 2016

The present study aims to explore the causes of employment difficulty on the basis of job applicant's interest from P-E (person-environment) fit perspective. Our approach relied on a textual analytic method to reveal insights from their situational interests in a job search during the change of labor market. Thus, to investigate the type of major interests and psychological responses, user-generated texts in a social community were collected for analysis between January 1, 2013 through December 31, 2015 by crawling the online-community in regard to job seeking and sharing information and opinions. The results of topic analysis indicated user's primary interests were divided into four types: perception of vocation expectation, employment pre-preparation behaviors, perception of labor market, and job-seeking stress. Specially, job applicants put mainly concerns of monetary reward and a form of employment, rather than their work values or career exploration, thus youth job applicants expressed their psychological responses using contextualized language (e.g., slang, vulgarisms) for projecting their unstable state under uncertainty in response to environmental changes. Additionally, they have perceived activities in the restricted preparation (e.g., certification, English exam) as determinant factors for success in employment and suffered form job-seeking stress. On the basis of these findings, current unemployment matters are totally attributed to the absence of pursing the value of vocation and job in individuals, organizations, and society. Concretely, job seekers are preoccupied with occupational prestige in social aspect and have undecided vocational value. On the other hand, most companies have no perception of the importance of human resources and have overlooked the needs for proper work environment development in respect of stimulating individual motivation. The attempt in this study to reinterpret the effect of environment as for classifying job applicant's interests in reference to linguistic and psychological theories not only helps conduct a more comprehensive meaning for understanding social matters, but guides new directions for future research on job applicant's psychological factors (e.g., attitudes, motivation) using topic analysis.

• Economic and Environmental Geology
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• v.47 no.6
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• pp.563-569
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• 2014

Ruby is one of the most favor colored gem, for beautiful red tone, be high in scarcity value. However, rubies with high quality are produced in restricted regions, such as in Thailand, Sri Lanka, Myanmar, and Tanzania etc., and they have been gradually exhausted by mining for a long period. Therefore, improving qualities of low level rubies with various treatments is arising an alternative way to obtain better rubies. Gemological and mineralogical properties of the natural ruby from Tanzanian were studied with heat treatments. Those characteristics were compared between only heat and adding flux materials under heating. Tanzanian raw rubies were applied a heat treatment ($1,600^{\circ}C$ for 6 hours). However, chromameter and UV-Vis analyses found that a simple heat treatment is inappropriated for the Tanzanian ruby. Although $Cr^{3+}$ containing for red color in the ruby increased with heat treatment, the ruby displays dark medium red because of Fe in the ruby as a form of $Fe_2O_3$. The low transparency after heat treatment is attributed to the recrystallization of $SiO_2$ which has a low melting point. Chromameter confirmed adding Pb-containing flux under heating greatly improves the clarity and color of Tanzanian rubies with micro-fractures and cavities on the surface. EMPA results show that Pb as an additive fills the cavities and cracks on raw Tanzanian rubies during the heat treatment. As a rewult of it, the quality of the Tanzanian ruby raw dramatically improved. These results indicate that the heat treatment with an additive (Pb in this study) is an effective way to obtain better quality of the Tanzanian ruby. Consequently, this study suggests a suitable method to improve the properties of the Tanzanina ruby. The result of this study would provide useful information to upgrade the qualities of similar gem stones such as corundum and sapphire.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.1
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• pp.14-27
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• 2024

Unlike the shelf sand ridges moribund in motion, nearshore sand ridges are highly mobile, sensitive to changes in ocean environments, thereby becoming of particular interest with respect to morphological changes. About 5 km off the Daesan port, the Jangan Sand Ridge has been undergoing severe subsea morphological change over the past two decades. Understanding the nature of sand ridges is critical to elucidate the causes of morphological changes. In this context, this study aims at understanding the characteristics and distribution patterns of surface sediments of the ridge and its vicinity. For this purpose, 227 sediment samples were acquired using a grab-sampler, the grain sizes being analysed by the sieve-pipette method. In addition, comparison of grain sizes in sediments between 1997 and 2021 was made in order to investigate the 25-years change in sediment composition. Surface sediments along the ridge axis are fine to medium sands with 2-3 phi in mean grain size, whereas, in the trough of ridge, the sediments are composed of gravels and muddy sandy gravels with mean sizes of -2 to -6 phi. Sediments in the crest of the ridge are well-sorted with normal distribution, on the other hand, the basal sediments are poorly-sorted and positively skewed. Along the ridge crest, the sediments are negatively skewed. From 1997 to 2021, the ridge sediments became largely coarser about 0.5 phi. Such coarsening trend in mean grain size can be explained either by elimination of fine sediments during high waves in winter or elimination of fines suspended during sand mining activities in the past. Spatial distribution pattern of surface sediments shows that ca. 30 m thick of the sand ridge itself overlies the thin relict gravels. The strong asymmetry of sand ridge, the exposure of ridge base, and reworked gravel lags suggest that Jangan sand ridge is probably sediment-deficit and hence erosive in nature at present.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.1-23
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• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.