• Elastomers and Composites
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• v.40 no.2
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• pp.93-103
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• 2005

In this study, surface treatment of the elastomeric matrix was investigated to develop a substituting material for steel dynamic damper of automobile. The key technology is to get ultra high density elastomeric compound in order to substitute steel dynamic damper. The optimum matrix material(chloroprene rubber) and filler(metal powder) were selected for this. The several properties of elastomeric compound were examined. According to the results, the $t_{s2}$ of filled elastomeric compound was decreased with increasing the filler loading whereas the $t_{90}$ was increased. Also, tensile strength and rebound resilience were decreased with filler loading. To solve the problem of high filler loading, the photo grafting technique was employed on elastomeric matrix. The degree of grafting was determined by FTIR-ATR. Also, the filler surface was modified by chemical etching and the surface morphology was examine by SEM. After chemical treatment of filler, the particle size analyzer was used to examined the particle size, size distribution, and morphology of the modified filler.

• Geophysics and Geophysical Exploration
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• v.22 no.3
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• pp.149-159
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• 2019

Borehole elemental concentration logging, measuring neutron-induced gamma rays by inelastic scattering and neutron capture interactions between neutron and formation, delivers concentrations of the most common elements found in the minerals and fluids of subsurface formation. X-ray diffraction and X-ray fluorescence analysis from core samples are traditionally used to understand formation composition and mineralogy, but it represents only part of formations. Additionally, it is difficult to obtain elemental analysis over the whole intervals because of poor core recovery zones such as fractures or sand layers mainly responsible for groundwater flow. The development of borehole technique for in situ elemental analysis plays a key role in assessing subsurface environment. Although this technology has advanced consistently starting from conventional and unconventional resources evaluation, it has been considered as exclusive techniques of some major service company. As regards domestic research and development, it has still remained an unexplored field because of some barriers such as the deficiency of detailed information on tools and calibration facility for chemistry and mineralogy database. This article reviews the basic theory of spectroscopy measurements, system configuration, calibration facility, and current status. In addition, this article introduces the domestic researches and self-development status on borehole elemental concentration tools.

• Journal of the Korean GEO-environmental Society
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• v.12 no.9
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• pp.71-78
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• 2011

Cement treating technique, such as deep mixing method, has been used widely to stabilize the dredged clayey soil for many years. Despite of its effectiveness in treating soil by cement, several efforts have also been made to try to reduce the side effect of the cement that used to stabilize the dredged clay. However, authors considered that more detailed study on the physical and mechanical properties of lean-mixed soil-cement has been required to establish the design procedure to apply the practical problems. Therefore, in this study, the curing time and mixing ratio was used as key parameters to estimate the physical and mechanical properties including long-term behavior. The unconfined strength of lean-mixed soil-cement increase continuously during curing period, 270 days, while increasing rate becomes low in ordinary cement-treated dredged clay. We also concluded that cement-treated dredging clay shows apparent quasi overconsolidation behavior even in low cement proportion. By this study, fundamental approach was carried out for effective reuse of very soft dredged clayey soil both in mechanical and environmental aspect. It can be also expected that this study can propose a basic design data to use the lean-mixed soil cement.

• Korean Journal of Radiology
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• v.22 no.2
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• pp.263-280
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• 2021

Percutaneous transthoracic needle biopsy (PTNB) is one of the essential diagnostic procedures for pulmonary lesions. Its role is increasing in the era of CT screening for lung cancer and precision medicine. The Korean Society of Thoracic Radiology developed the first evidence-based clinical guideline for PTNB in Korea by adapting pre-existing guidelines. The guideline provides 39 recommendations for the following four main domains of 12 key questions: the indications for PTNB, pre-procedural evaluation, procedural technique of PTNB and its accuracy, and management of post-biopsy complications. We hope that these recommendations can improve the diagnostic accuracy and safety of PTNB in clinical practice and promote standardization of the procedure nationwide.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.69-94
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• 2017

Recently, increase of demand for big data analysis has been driving the vigorous development of related technologies and tools. In addition, development of IT and increased penetration rate of smart devices are producing a large amount of data. According to this phenomenon, data analysis technology is rapidly becoming popular. Also, attempts to acquire insights through data analysis have been continuously increasing. It means that the big data analysis will be more important in various industries for the foreseeable future. Big data analysis is generally performed by a small number of experts and delivered to each demander of analysis. However, increase of interest about big data analysis arouses activation of computer programming education and development of many programs for data analysis. Accordingly, the entry barriers of big data analysis are gradually lowering and data analysis technology being spread out. As the result, big data analysis is expected to be performed by demanders of analysis themselves. Along with this, interest about various unstructured data is continually increasing. Especially, a lot of attention is focused on using text data. Emergence of new platforms and techniques using the web bring about mass production of text data and active attempt to analyze text data. Furthermore, result of text analysis has been utilized in various fields. Text mining is a concept that embraces various theories and techniques for text analysis. Many text mining techniques are utilized in this field for various research purposes, topic modeling is one of the most widely used and studied. Topic modeling is a technique that extracts the major issues from a lot of documents, identifies the documents that correspond to each issue and provides identified documents as a cluster. It is evaluated as a very useful technique in that reflect the semantic elements of the document. Traditional topic modeling is based on the distribution of key terms across the entire document. Thus, it is essential to analyze the entire document at once to identify topic of each document. This condition causes a long time in analysis process when topic modeling is applied to a lot of documents. In addition, it has a scalability problem that is an exponential increase in the processing time with the increase of analysis objects. This problem is particularly noticeable when the documents are distributed across multiple systems or regions. To overcome these problems, divide and conquer approach can be applied to topic modeling. It means dividing a large number of documents into sub-units and deriving topics through repetition of topic modeling to each unit. This method can be used for topic modeling on a large number of documents with limited system resources, and can improve processing speed of topic modeling. It also can significantly reduce analysis time and cost through ability to analyze documents in each location or place without combining analysis object documents. However, despite many advantages, this method has two major problems. First, the relationship between local topics derived from each unit and global topics derived from entire document is unclear. It means that in each document, local topics can be identified, but global topics cannot be identified. Second, a method for measuring the accuracy of the proposed methodology should be established. That is to say, assuming that global topic is ideal answer, the difference in a local topic on a global topic needs to be measured. By those difficulties, the study in this method is not performed sufficiently, compare with other studies dealing with topic modeling. In this paper, we propose a topic modeling approach to solve the above two problems. First of all, we divide the entire document cluster(Global set) into sub-clusters(Local set), and generate the reduced entire document cluster(RGS, Reduced global set) that consist of delegated documents extracted from each local set. We try to solve the first problem by mapping RGS topics and local topics. Along with this, we verify the accuracy of the proposed methodology by detecting documents, whether to be discerned as the same topic at result of global and local set. Using 24,000 news articles, we conduct experiments to evaluate practical applicability of the proposed methodology. In addition, through additional experiment, we confirmed that the proposed methodology can provide similar results to the entire topic modeling. We also proposed a reasonable method for comparing the result of both methods.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.183-203
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• 2018

News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.

• Journal of Distribution Science
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• v.9 no.4
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• pp.93-102
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• 2011

With the increasing interest in boosting conventional markets, many authors have paid considerable attention to the roles of shop owners, store image improvement, and how to attract or maintain customers. Nevertheless, it is not easy to find papers related to the relationship between shop owners and their contribution to trading areas, directly or indirectly, in the academic world. Accordingly, research for answering the following question has been initiated: what kind of roles do shopkeepers should play in revitalizing poor conventional markets? Based on the previous studies focusing on enhancing traditional markets, this research was approached from the new insights that have been obtained concerning how to boost conventional markets, that is, from the perspectives of a shop owner and a trader. Therefore, this research aims at identifying some resolutions associated with the roles of shop owners to enhance a shopping district in a specific area, classifying their business roles into a few categories, depending on the degree of their participation in improving the shopping environment. Compared with previous studies focusing on emphasizing the importance of improving customer services from a shopkeeper's perspective, this research provides a new insight as far as how to boost conventional markets. It is, furthermore, necessary to note how market participants, particularly shop owners as they are the key players, can contribute to rebuilding their business area together with their customers. As a research technique for effectively achieving the research goal, the authors adopted a documentation methodology based on a large amount of the existing literature for studying how to rebuild traditional markets. Concerned about the ways to revitalize conventional markets, many authors have proposed a variety of strategies, and have suggested more detailed action plans from a practitioner's perspective. By analyzing these research results, the authors will have accomplished the research aim. Rather than simply identifying the roles of shop owners, the author found that they had to understand their social contribution for enhancing their trading areas, as well as their functional roles, in forming a regional society. The conventional market should be, thus, regarded as the place to share regional culture. Consequently, the authors draw some conclusions from the research results. In order to answer the above question, it was found that the roles of shop owners have been considered as one of the most important ways for revitalizing traditional markets. With respect to their roles, it is evident that their business activities are closely related to the improvement of the trading area in terms of sociality, regional development, and market revitalization, by selling products or services to the customers visiting that area. In a word, this implies that shop owners have to actively take part in boosting conventional markets as a core player. Although the authors have properly achieved the research aim, this study has a limitation, like most other research, in adopting a documentation method. Because the research is based on existing data results provided by the prior research conducted a long time ago, whether the research findings are applicable in a contemporary market should be re-examined in future research from a practitioner's perspective, rather than from an academic's perspective.

• Korean Journal of Heritage: History & Science
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• v.53 no.3
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• pp.62-79
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• 2020

The rock-carved seated Avalokiteśvara statue at Ganghwa Bomunsa Temple is a giant rock-carved Buddhist statue that was built in 1928 during the Japanese colonial era. Although it is a year-recorded Buddhist statue that occupies a prominent place in modern Korean Buddhist sculpture history, it has not been the subject of in-depth discussion due to weak research on modern Buddhist sculptures. In this study, to examine the various significant aspects of the rock-carved Seated Avalokiteśvara statue at Bomunsa Temple as a modern Buddhist sculpture, I have managed to determine its construction year, artificers, and patrons by deciphering the inscription around the rock-carved statue; in addition I have researched the effects of the rock shapes and landforms on the formation of the Buddhist statue by comparing and analyzing the points of view of both artificers and worshipers. I have also identified the specific circumstances of the time of construction from interviews with the descendants of artificers. A monk from Geumgangsan Mountain, Lee Hwaeung, took the role of sponsor and chief painter to construct the rock-carved seated Avalokiteśvara statue at Bomunsa temple. In the beginning of its construction in 1928, more than 100 donators jointly sponsored the construction of the statue. Gansong Jeon Hyoungphil sponsored alone at the time of the place of worship's expansion in 1938. Bomunsa Temple has been regarded as one of the top-three sacred places of Avalokiteśvara Bodhisattva together with Naksansa Temple in Yang Yang and Boriam in Nam Hae, due to the construction of the rock-carved statue. It took about three months to construct the statue. Lee Hwaeung drew a rough sketch and then Un Songhag and five masons from Ganghwa Island took part in the carving process. We can observe the line drawing technique around the rock-carved statue because the statue was carved based on the rough sketch of the monk painter. The aspect of Lee Hwaeung as a painter is revealed; therefore, we can identify the clue of painting pattern leading to Seogongchulyou- Hwaunghyoungjin- Ilonghyegag. The rock-carved seated Avalokiteśvara statue at Bomunsa Temple is a typical Avalokiteśvara that wears a jeweled crown and holds Kundica. It makes a strong impression as it has a big square-shaped face and a short neck and is unsophisticated in general. The artificers solved the issue of visual distortion of the rock-carved statue caused by carving on a 10-meter high and 40-degree sloping rock by controlling motion to its maximum, omitting detailed expression by emphasizing symmetry, and adjusting the head-to-body proportion to be almost one-to-one. In this study, especially, I presume the unified form of sacred sculptures and Buddhist altars, without making a Buddhist altar like the rock-carved seated Avalokiteśvara statue at Bomunsa Temple, to be a key characteristic of modern Buddhist sculptures. Furthermore, I make newly clear that the six letters of Sanskrit carved on nimbus, which had been interpreted as a Six-Syllable Mantra, are a combination with Jeongbeopgye and Sabang Mantras. In addition, three iron rings driven on eaves rock were used as a reference point, and after construction they were used as a decoration for the Bodhisattva with hanging wind chimes.

• Asia pacific journal of information systems
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• v.23 no.4
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• pp.103-128
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• 2013

When a consumer needs a product or service and multiple sellers are available online, the process of selecting a seller to buy online from is complex since the process involves many behavioral dimensions that have to be taken into account. As a part of this selection process, consumers may set minimum trust expectation that can be used to screen out less trustworthy sellers. In the previous research, the level of consumers' trust expectation has been anchored on two important factors: product involvement and perceived risk. Product involvement refers to the extent to which a consumer perceives a specific product important. Thus, the higher product involvement may result in the higher trust expectation in sellers. On the other hand, other related studies found that when consumers perceived a higher level of risk (e.g., credit card fraud risk), they set higher trust expectation as well. While abundant research exists addressing the relationship between product involvement and perceived risk, little attention has been paid to the integrative view of the link between the two constructs and their impacts on the trust expectation. The present paper is a step toward filling this research gap. The purpose of this paper is to understand the process by which a consumer chooses an online merchant by examining the relationships among product involvement, perceived risk, trust expectation, and intention to buy from an e-tailer. We specifically focus on the mediating role of perceived risk in the relationships between enduring product involvement and the trust expectation. That is, we question whether product involvement affects the trust expectation directly without mediation or indirectly mediated by perceived risk. The research model with four hypotheses was initially tested using data gathered from 635 respondents through an online survey method. The structural equation modeling technique with partial least square was used to validate the instrument and the proposed model. The results showed that three out of the four hypotheses formulated were supported. First, we found that the intention to buy from a digital storefront is positively and significantly influenced by the trust expectation, providing support for H4 (trust expectation ${\rightarrow}$ purchase intention). Second, perceived risk was found to be a strong predictor of trust expectation, supporting H2 as well (perceived risk ${\rightarrow}$ trust expectation). Third, we did not find any evidence of direct influence of product involvement, which caused H3 to be rejected (product involvement ${\rightarrow}$ trust expectation). Finally, we found significant positive relationship between product involvement and perceived risk (H1: product involvement ${\rightarrow}$ perceived risk), which suggests that the possibility of complete mediation of perceived risk in the relationship between enduring product involvement and the trust expectation. As a result, we conducted an additional test for the mediation effect by comparing the original model with the revised model without the mediator variable of perceived risk. Indeed, we found that there exists a strong influence of product involvement on the trust expectation (by intentionally eliminating the variable of perceived risk) that was suppressed (i.e., mediated) by the perceived risk in the original model. The Sobel test statistically confirmed the complete mediation effect. Results of this study offer the following key findings. First, enduring product involvement is positively related to perceived risk, implying that the higher a consumer is enduringly involved with a given product, the greater risk he or she is likely to perceive with regards to the online purchase of the product. Second, perceived risk is positively related to trust expectation. A consumer with great risk perceptions concerning the online purchase is likely to buy from a highly trustworthy online merchant, thereby mitigating potential risks. Finally, product involvement was found to have no direct influence on trust expectation, but the relationship between the two constructs was indirect and mediated by the perceived risk. This is perhaps an important theoretical integration of two separate streams of literature on product involvement and perceived risk. The present research also provides useful implications for practitioners as well as academicians. First, one implication for practicing managers in online retail stores is that they should invest in reducing the perceived risk of consumers in order to lower down the trust expectation and thus increasing the consumer's intention to purchase products or services. Second, an academic implication is that perceived risk mediates the relationship between enduring product involvement and trust expectation. Further research is needed to elaborate the theoretical relationships among the constructs under consideration.

• Proceedings of the Korea Environmental Mutagen Society Conference
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• 2003.10a
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• pp.34-63
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• 2003

Occupational and environmental exposure to manganese continue to represent a realistic public health problem in both developed and developing countries. Increased utility of MMT as a replacement for lead in gasoline creates a new source of environmental exposure to manganese. It is, therefore, imperative that further attention be directed at molecular neurotoxicology of manganese. A Need for a more complete understanding of manganese functions both in health and disease, and for a better defined role of manganese in iron metabolism is well substantiated. The in-depth studies in this area should provide novel information on the potential public health risk associated with manganese exposure. It will also explore novel mechanism(s) of manganese-induced neurotoxicity from the angle of Mn-Fe interaction at both systemic and cellular levels. More importantly, the result of these studies will offer clues to the etiology of IPD and its associated abnormal iron and energy metabolism. To achieve these goals, however, a number of outstanding questions remain to be resolved. First, one must understand what species of manganese in the biological matrices plays critical role in the induction of neurotoxicity, Mn(II) or Mn(III)? In our own studies with aconitase, Cpx-I, and Cpx-II, manganese was added to the buffers as the divalent salt, i.e., $MnCl_2$. While it is quite reasonable to suggest that the effect on aconitase and/or Cpx-I activites was associated with the divalent species of manganese, the experimental design does not preclude the possibility that a manganese species of higher oxidation state, such as Mn(III), is required for the induction of these effects. The ionic radius of Mn(III) is 65 ppm, which is similar to the ionic size to Fe(III) (65 ppm at the high spin state) in aconitase (Nieboer and Fletcher, 1996; Sneed et al., 1953). Thus it is plausible that the higher oxidation state of manganese optimally fits into the geometric space of aconitase, serving as the active species in this enzymatic reaction. In the current literature, most of the studies on manganese toxicity have used Mn(II) as $MnCl_2$ rather than Mn(III). The obvious advantage of Mn(II) is its good water solubility, which allows effortless preparation in either in vivo or in vitro investigation, whereas almost all of the Mn(III) salt products on the comparison between two valent manganese species nearly infeasible. Thus a more intimate collaboration with physiochemists to develop a better way to study Mn(III) species in biological matrices is pressingly needed. Second, In spite of the special affinity of manganese for mitochondria and its similar chemical properties to iron, there is a sound reason to postulate that manganese may act as an iron surrogate in certain iron-requiring enzymes. It is, therefore, imperative to design the physiochemical studies to determine whether manganese can indeed exchange with iron in proteins, and to understand how manganese interacts with tertiary structure of proteins. The studies on binding properties (such as affinity constant, dissociation parameter, etc.) of manganese and iron to key enzymes associated with iron and energy regulation would add additional information to our knowledge of Mn-Fe neurotoxicity. Third, manganese exposure, either in vivo or in vitro, promotes cellular overload of iron. It is still unclear, however, how exactly manganese interacts with cellular iron regulatory processes and what is the mechanism underlying this cellular iron overload. As discussed above, the binding of IRP-I to TfR mRNA leads to the expression of TfR, thereby increasing cellular iron uptake. The sequence encoding TfR mRNA, in particular IRE fragments, has been well-documented in literature. It is therefore possible to use molecular technique to elaborate whether manganese cytotoxicity influences the mRNA expression of iron regulatory proteins and how manganese exposure alters the binding activity of IPRs to TfR mRNA. Finally, the current manganese investigation has largely focused on the issues ranging from disposition/toxicity study to the characterization of clinical symptoms. Much less has been done regarding the risk assessment of environmenta/occupational exposure. One of the unsolved, pressing puzzles is the lack of reliable biomarker(s) for manganese-induced neurologic lesions in long-term, low-level exposure situation. Lack of such a diagnostic means renders it impossible to assess the human health risk and long-term social impact associated with potentially elevated manganese in environment. The biochemical interaction between manganese and iron, particularly the ensuing subtle changes of certain relevant proteins, provides the opportunity to identify and develop such a specific biomarker for manganese-induced neuronal damage. By learning the molecular mechanism of cytotoxicity, one will be able to find a better way for prediction and treatment of manganese-initiated neurodegenerative diseases.