• Korean Journal of Environmental Agriculture
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• v.25 no.3
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• pp.217-227
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• 2006

Micronutrient status in soils and crops of plastic film house and their relationship were investigated. Total 203 plastic film houses were selected (red pepper, 66; cucumber, 63; tomato, 74) in Yeongnam region and soil and leaf samples were collected. Hot-water extractable B and 0.1 N HCl extractable Cu, Zn, Fe, and Mn in soil samples and total micronutrients in leaf samples were analyzed. Contents Zn, Fe, and Mn in most of the investigated soils were higher than the upper limits of optimum level for general crop cultivation. Contents of Cu in most soils of cucumber and tomato cultivation were higher than the upper limit of optimum level, but Cu contents in about 30% of red pepper cultivation soils were below the sufficient level. Contents of B in most soils of cucumber and tomato were above the sufficient level but in 48% of red pepper cultivation soils B were found to be deficient. Micronutrient contents in leaf of investigated crops were much variable. Contents of B, Fe, and Mn were mostly within the sufficient levels, while in 71% of red pepper samples Cu was under deficient level and in 44% of cucumber samples Cu contents were higher than the upper limit of sufficient level. Contents of Zn in red pepper and cucumber samples were mostly within the sufficient level but in 62% of tomato samples Zn contents were under deficient condition. However, any visible deficiency or toxicity symptoms of micronutrients were not found in the crops. No consistent relationships were found between micronutrient contents in soil and leaf, and this indicates that growth and absorption activity of root and interactions among the nutrients in soil might be important factors in overall micronutrient uptake of crops. For best management of micronutrients in plastic film house, much attention should be focused on the management of soil and plant characteristics which control the micronutrient uptake of crops.

• Journal of the Mineralogical Society of Korea
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• v.20 no.1 s.51
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• pp.47-60
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• 2007

While sedimentological researches on Western coastal tidal flats of Korea have been much pelformed previously, mineralogical and biogeochemical studies are beginning to be studied. The objectives of this study were to investigate mineralogical characteritics of the inter-tidal flat sediments and to explore phase transformation of iron(oxyhydr)oxides and biomineralization by metal-reducing bacteria enriched from the inter-tidal flat sediments from Muan, Jeollanam-do, Korea. Inter-tidal flat sediment samples were collected in Chungkye-myun and Haeje-myun, Muan-gun, Jeollanam-do. Particle size analyses were performed using the pipette method and sedimentation method. The separates including sand, silt and clay fractions were examined by scanning electron microscopy (SEM) with energy dispersive X-ray (EDX) analysis, transmission electron microscopy (TEM), and X-ray diffiaction (XRD). After enriching the metal-.educing bacteria from the into,-tidal flat sediments, the bacteria were used to study phase transformation of the synthesized iron (oxyhydr)oxides and iron biomineralization using lactate or glucose as the electron donors and Fe(III)-containing iron oxides as the electron accepters. Mineralogical studies showed that the sediments of tidal flats in Chung]rye-myun and Haeje-myun consist of quartz, plagioclase, microcline, biotite, kaolinite and illite. Biogeochemical researches showed that the metal-reducing bacteria enriched from the inter-tidal flat sediments reduced reddish brown akaganeite and mineralized nanometer-sized black magnetite. The bacteria also reduced the reddish brown ferrihydrite into black amorphous phases and reduced the yellowish goethite into greenish with formation of nm-sized phases. These results indicate that microbial Fe(III) reduction may play one of important roles in iron and carbon biogeochemistry as well as iron biomineralization in subsurface environments.

• Tuberculosis and Respiratory Diseases
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• v.44 no.6
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• pp.1343-1352
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• 1997

Background : Heat-treated cells are known to be protected from lysis by TNF, which is considered to play a central role in the pathogenesis of sepsis-induced acute lung injury. The objective of the study was to investigate the effect of heat shock response by heat-pretreatment on the acute lung injury of the rats induced by intratracheally administered TNF-$\alpha$, Methods : We intratracheally instilled either saline or TNF (R&D, 500ng) with and without heat pretreatment in Sprague-Dawley rats weighing 250~350 g. The heated rats were raised their rectal temperature to $41^{\circ}C$ and was maintained thereafter for 13 minutes at 18 h before intratracheal administration of saline or TNF. After 5 h of intratracheal treatment, lung leak, lung myeloperoxidase activity (MPO) and heat shock proteins were measured in rats. Lung leak index was defined as counts per minute of $I^{25}$ in the right lung divided by counts per minutes of $I^{25}$ in 1.0 ml of blood. All data are expressed as means ${\pm}$SE. Results : There is no difference in acute lung leak index ($0.099{\pm}0.024$ vs $0.123{\pm}0.005$) among the rats given saline intratracheally with and without heat pretreatment, but MPO activity showed a decreased tendency in heat-pretreated rats ($4.58{\pm}0.79\;U/g$) compared with heat-unpretreated rats ($7.32{\pm}0.97\;U/g$) (P=0.064). Rats administered TNF intratracheally with heat-pretreatment had decreased lung leak index ($0.137{\pm}0.012$) and lung MPO activity ($5.51{\pm}1.04\;U/g$) compared with those of heat-unpretreated and TNF-administered rats ($0.186{\pm}0.016$, $14.34{\pm}1.22\;U/g$) (P<0.05 in each). There were no significant difference of lung leak index and MPO activity between TNF-treated rats with heat-pretreatment and saline-treated rats with and without heat-pretreatment. Conclusion : The heat shock response attenuated neutrophil recruitment and acute lung leak induced by intratracheal instillation of TNF-in rats.

• Trans-
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• v.3
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• pp.109-135
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• 2017

The purpose of this thesis is to analyze characteristics of everyday movement showed in performances of Steve Paxton. A work of art has been realized as a special object enjoyed by high class people as high culture for a long time. Therefore, a gap between everyday life and art has been greatly existed, and the emergence of everyday elements in a work of art means that public awareness involving social change is changed. The postmodernism as the period when a boundary between art and everyday life is uncertain was a postwar society after the Second World War and a social situation that rapidly changes into a capitalistic society. Changes in this time made scholars gain access academically concepts related to everyday life, and affected artists as the spirit of the times of pluralistic postmodernism refusing totality. At the same period of the time, modern dance also faced a turning point as post-modern dance. After the Second World War, modern dance started to be evaluated as it reaches the limit, and at this juncture, headed by dancers including the Judson Dance Theatre. Acting as a dancer in a dance company of Merce Cunningham, Steve Paxton, one of founders of the Judson Dance Theatre, had a critical mind of the conditions of dance company with the social structure and the process that movement is made. This thinking is showed in early performances as an at tempt to realize everyday motion it self in performances. His early activity represented by a walking motion attracted attention as a simple motion that excludes all artful elements of existing dance performances and is possible to conduct by a person who is not a dancer. Although starting the use of everyday movement is regarded as an open characteristic of post-modern dance, advanced researches on this were rare, so this study started. In addition, studies related to Steve Paxton are skewed towards Contact Improvisation that he rose as an active practician. As the use of ordinary movement before he focused on Contact Improvisation, this study examines other attempts including Contact Improvisation as attempts after the beginning of his performances. Therefore, the study analyzes Satisfyin' Lover, Contact at 10th & 2nd and Bound that are performances of Steve Paxton, and based on this, draws everyday characteristics. In addition, related books, academic essays, dance articles and reviews are consulted to consider a concept related to everyday life and understand dance historical movement of post-modern dance. Paxton attracted attention because of his activity starting at critical approach of movement of existing modern dance. As walking of performers who are not dancers, a walking motion showed in Satisfyin' Lover gave esthetic meaning to everyday movement. After that, he was affected by Eastern ideas, so developed Contact Improvisation making a motion through energy of the natural laws. In addition, he had everyday things on his performances, and used a method to deliver various images by using mundane movement and impromptu gestures originating from relaxed body. Everyday movement of his performances represents change in awareness of performances of the art of dancing that are traditionally maintained including change of dance genre of an area. His activity with unprecedented attempt and experimentation should be highly evaluated as efforts to overcome the limit of modern dance.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.109-131
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• 2014

As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.

• Journal of the Korean Vacuum Society
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• v.15 no.6
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• pp.563-575
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• 2006

Ti(C,N) films are synthesized by pulsed DC plasma enhanced chemical vapor deposition (PEMOCVD) using metal-organic compounds of tetrakis diethylamide titanium at $200-300^{\circ}C$. To compare plasma parameter, in this study, $H_2$ and $He/H_2$ gases are used as carrier gas. The effect of $N_2\;and\;NH_3$ gases as reactive gas is also evaluated in reduction of C content of the films. Radical formation and ionization behaviors in plasma are analyzed in-situ by optical emission spectroscopy (OES) at various pulsed bias voltages and gas species. He and $H_2$ mixture is very effective in enhancing ionization of radicals, especially for the $N_2$. Ammonia $(NH_3)$ gas also highly reduces the formation of CN radical, thereby decreasing C content of Ti(C, N) films in a great deal. The microhardness of film is obtained to be $1,250\;Hk_{0.01}\;to\;1,760\;Hk_{0.01}$ depending on gas species and bias voltage. Higher hardness can be obtained under the conditions of $H_2\;and\;N_2$ gases as well as bias voltage of 600 V. Hf(C, N) films were also obtained by pulsed DC PEMOCYB from tetrakis diethyl-amide hafnium and $N_2/He-H_2$ mixture. The depositions were carried out at temperature of below $300^{\circ}C$, total chamber pressure of 1 Torr and varying the deposition parameters. Influences of the nitrogen contents in the plasma decreased the growth rate and attributed to amorphous components, to the high carbon content of the film. In XRD analysis the domain lattice plain was (111) direction and the maximum microhardness was observed to be $2,460\;Hk_{0.025}$ for a Hf(C,N) film grown under -600 V and 0.1 flow rate of nitrogen. The optical emission spectra measured during PEMOCVD processes of Hf(C, N) film growth were also discussed. $N_2,\;N_2^+$, H, He, CH, CN radicals and metal species(Hf) were detected and CH, CN radicals that make an important role of total PEMOCVD process increased carbon content.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.95-110
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• 2013

Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.

• The Journal of Korean Society for Radiation Therapy
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• v.32
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• pp.17-29
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• 2020

Purpose: The purpose of this work was to investigate the dosimetric impact of mixed energy partial arc technique on prostate cancer VMAT. Materials and Methods: This study involved prostate only patients planned with 70Gy in 30 fractions to the planning target volume (PTV). Femoral heads, Bladder and Rectum were considered as oragan at risk (OARs). For this study, mixed energy partial arcs (MEPA) were generated with gantry angle set to 180°~230°, 310°~50° for 6MV arc and 130°~50°, 310°~230° for 15MV arc. Each arc set the avoidance sector which is gantry angle 230°~310°, 50°~130° at first arc and 50°~310° at second arc. After that, two plans were summed and were analyzed the dosimetry parameter of each structure such as Maximum dose, Mean dose, D2%, Homogeneity index (HI) and Conformity Index (CI) for PTV and Maximum dose, Mean dose, V70Gy, V50Gy, V30Gy, and V20Gy for OARs and Monitor Unit (MU) with 6MV 1 ARC, 6MV, 10MV, 15MV 2 ARC plan. Results: In MEPA, the maximum dose, mean dose and D2% were lower than 6MV 1 ARC plan(p<0.0005). However, the average difference of maximum dose was 0.24%, 0.39%, 0.60% (p<0.450, 0.321, 0.139) higher than 6MV, 10MV, 15MV 2 ARC plan, respectively and D2% was 0.42%, 0.49%, 0.59% (p<0.073, 0.087, 0.033) higher than compared plans. The average difference of mean dose was 0.09% lower than 10MV 2 ARC plan, but it is 0.27%, 0.12% (p<0.184, 0.521) higher than 6MV 2 ARC, 15MV 2 ARC plan, respectively. HI was 0.064±0.006 which is the lowest value (p<0.005, 0.357, 0.273, 0.801) among the all plans. For CI, there was no significant differences which were 1.12±0.038 in MEPA, 1.12±0.036, 1.11±0.024, 1.11±0.030, 1.12±0.027 in 6MV 1 ARC, 6MV, 10MV, 15MV 2 ARC, respectively. MEPA produced significantly lower rectum dose. Especially, V70Gy, V50Gy, V30Gy, V20Gy were 3.40, 16.79, 37.86, 48.09 that were lower than other plans. For bladder dose, V30Gy, V20Gy were lower than other plans. However, the mean dose of both femoral head were 9.69±2.93, 9.88±2.5 which were 2.8Gy~3.28Gy higher than other plans. The mean MU of MEPA were 19.53% lower than 6MV 1 ARC, 5.7% lower than 10MV 2 ARC respectively. Conclusion: This study for prostate radiotherapy demonstrated that a choice of MEPA VMAT has the potential to minimize doses to OARs and improve homogeneity to PTV at the expense of a moderate increase in maximum and mean dose to the femoral heads.

• Economic and Environmental Geology
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• v.56 no.2
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• pp.125-138
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• 2023

Most of previous cesium (Cs) sorbents have limitations on the treatment in the large-scale water system having low Cs concentration and high ion strength. In this study, the new Cs sorbent that is eco-friendly and has a high Cs removal efficiency was developed by improving the coal mine drainage treated sludge (hereafter 'CMDS') with the addition of Na and S. The sludge produced through the treatment process for the mine drainage originating from the abandoned coal mine was used as the primary material for developing the new Cs sorbent because of its high Ca and Fe contents. The CMDS was improved by adding Na and S during the heat treatment process (hereafter 'Na-S-CMDS' for the developed sorbent in this study). Laboratory experiments and the sorption model studies were performed to evaluate the Cs sorption capacity and to understand the Cs sorption mechanisms of the Na-S-CMDS. The physicochemical and mineralogical properties of the Na-S-CMDS were also investigated through various analyses, such as XRF, XRD, SEM/EDS, XPS, etc. From results of batch sorption experiments, the Na-S-CMDS showed the fast sorption rate (in equilibrium within few hours) and the very high Cs removal efficiency (> 90.0%) even at the low Cs concentration in solution (< 0.5 mg/L). The experimental results were well fitted to the Langmuir isotherm model, suggesting the mostly monolayer coverage sorption of the Cs on the Na-S-CMDS. The Cs sorption kinetic model studies supported that the Cs sorption tendency of the Na-S-CMDS was similar to the pseudo-second-order model curve and more complicated chemical sorption process could occur rather than the simple physical adsorption. Results of XRF and XRD analyses for the Na-S-CMDS after the Cs sorption showed that the Na content clearly decreased in the Na-S-CMDS and the erdite (NaFeS₂·2(H₂O)) was disappeared, suggesting that the active ion exchange between Na⁺ and Cs⁺ occurred on the Na-S-CMDS during the Cs sorption process. From results of the XPS analysis, the strong interaction between Cs and S in Na-S-CMDS was investigated and the high Cs sorption capacity was resulted from the binding between Cs and S (or S-complex). Results from this study supported that the Na-S-CMDS has an outstanding potential to remove the Cs from radioactive contaminated water systems such as seawater and groundwater, which have high ion strength but low Cs concentration.