• Research in Plant Disease
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• v.17 no.1
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• pp.19-24
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• 2011

It was identified as a sharp eyespot (Rhizoctonia cerealis) that the isolates from abnormal symptoms in wheat that showed yellowing leaves, necrotic spot on stem base and dead tillers. These isolates have slower growth property and fewer mycelia than Rhizoctonia solani AG-1(1A) (KACC 40106). They showed binuclear cell, same media cultural and DNA characteristics to R. cerealis. They caused same symptoms on leaves and stem base appeared in artificial inoculation test, comparing to diseased wheat fields and also affect to maturing of kernels. They have optimal growth temperature and acidity on the artificial media as $20{\sim}25^{\circ}C$ and pH 5~7, respectively. In the investigation of varietal resistance of Korean winter cereal crops to sharp eyespot, there was no resistant in wheat cultivars that all materials infected over 20% diseased ratio. 12 cultivars including 'Anbaekmil', however, considered to moderate resistance with 20 to 30% infection ratio. The others crops using in feeding, whole crop barley, oat, rye and triticale were resistant below 15% diseased degree except the rye that showed over 50% infection rate. It was the first evaluation to sharp eyespot resistance for the Korean feeding crop cultivars. Most tested Korean barley cultivars for malting and food were moderate and susceptible to the sharp eyespot. Only 3 hulled barley, 'Tapgolbori', 'Albori' and 'Seodunchalbori', showed resistance with less than 10% diseased ratio. All tested naked barley cultivars showed susceptible response to the disease.

• Journal of Bio-Environment Control
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• v.28 no.2
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• pp.134-142
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• 2019

This study was conducted to evaluate the growth characteristics of lettuce (Lactuca sativa L.) as affected by artificial light sources and different growing media in a closed-type plant production system (CPPS). The lettuce seeds were sown in the 128-cell plug tray filled with 5 different growing media such as urethane sponge (US), rock-wool (RW), Q-plug (QP), TP-S2 (TP) and PU-7B (PU). The germination rate of lettuce seeds was examined during 12 days after sowing. On the 13 days after sowing, the lettuce seedlings were transplanted in a CPPS with temperature $25{\pm}1^{\circ}C$ and nutrient solution (EC $2.0dS{\cdot}m^{-1}$, pH 6.5) using recirculating deep floating technique system. The light sources were set with FL (fluorescent lamps) and combined RB LEDs (red : blue = 7 : 3) with $150{\pm}10{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$ PPFD and a photoperiod of 14/10 hours (light/dark). The initial germination rate of lettuce was the highest in TP. The final germination and mean daily germination were the significantly highest in RW, QP and TP. The plant height, leaf length, leaf width, leaf area, and fresh and dry weights of shoot were the greatest in QP irradiated with RB LED. The number of leaves, fresh and dry weights of root and SPAD were the greatest in QP and TP irradiated with RB LED. The root length was the longest in TP irradiated with RB LED. Therefore, these results indicate that RB LED was effective for the growth of lettuce and it was also found that the QP and TP were effective for the germination and growth of lettuce in a CPPS. In addition, we confirmed the applicability of the newly developed growing medium TP for the lettuce production in a CPPS.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.33-56
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• 2016

Many researchers have focused on developing bankruptcy prediction models using modeling techniques, such as statistical methods including multiple discriminant analysis (MDA) and logit analysis or artificial intelligence techniques containing artificial neural networks (ANN), decision trees, and support vector machines (SVM), to secure enhanced performance. Most of the bankruptcy prediction models in academic studies have used financial ratios as main input variables. The bankruptcy of firms is associated with firm's financial states and the external economic situation. However, the inclusion of qualitative information, such as the economic atmosphere, has not been actively discussed despite the fact that exploiting only financial ratios has some drawbacks. Accounting information, such as financial ratios, is based on past data, and it is usually determined one year before bankruptcy. Thus, a time lag exists between the point of closing financial statements and the point of credit evaluation. In addition, financial ratios do not contain environmental factors, such as external economic situations. Therefore, using only financial ratios may be insufficient in constructing a bankruptcy prediction model, because they essentially reflect past corporate internal accounting information while neglecting recent information. Thus, qualitative information must be added to the conventional bankruptcy prediction model to supplement accounting information. Due to the lack of an analytic mechanism for obtaining and processing qualitative information from various information sources, previous studies have only used qualitative information. However, recently, big data analytics, such as text mining techniques, have been drawing much attention in academia and industry, with an increasing amount of unstructured text data available on the web. A few previous studies have sought to adopt big data analytics in business prediction modeling. Nevertheless, the use of qualitative information on the web for business prediction modeling is still deemed to be in the primary stage, restricted to limited applications, such as stock prediction and movie revenue prediction applications. Thus, it is necessary to apply big data analytics techniques, such as text mining, to various business prediction problems, including credit risk evaluation. Analytic methods are required for processing qualitative information represented in unstructured text form due to the complexity of managing and processing unstructured text data. This study proposes a bankruptcy prediction model for Korean small- and medium-sized construction firms using both quantitative information, such as financial ratios, and qualitative information acquired from economic news articles. The performance of the proposed method depends on how well information types are transformed from qualitative into quantitative information that is suitable for incorporating into the bankruptcy prediction model. We employ big data analytics techniques, especially text mining, as a mechanism for processing qualitative information. The sentiment index is provided at the industry level by extracting from a large amount of text data to quantify the external economic atmosphere represented in the media. The proposed method involves keyword-based sentiment analysis using a domain-specific sentiment lexicon to extract sentiment from economic news articles. The generated sentiment lexicon is designed to represent sentiment for the construction business by considering the relationship between the occurring term and the actual situation with respect to the economic condition of the industry rather than the inherent semantics of the term. The experimental results proved that incorporating qualitative information based on big data analytics into the traditional bankruptcy prediction model based on accounting information is effective for enhancing the predictive performance. The sentiment variable extracted from economic news articles had an impact on corporate bankruptcy. In particular, a negative sentiment variable improved the accuracy of corporate bankruptcy prediction because the corporate bankruptcy of construction firms is sensitive to poor economic conditions. The bankruptcy prediction model using qualitative information based on big data analytics contributes to the field, in that it reflects not only relatively recent information but also environmental factors, such as external economic conditions.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.259-278
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• 2022

With the spread of Artificial Intelligence (AI), various AI-based services are expanding in the financial sector such as service recommendation, automated customer response, fraud detection system(FDS), credit scoring services, etc. At the same time, problems related to reliability and unexpected social controversy are also occurring due to the nature of data-based machine learning. The need Based on this background, this study aimed to contribute to improving trust in AI-based financial services by proposing a checklist to secure fairness in AI-based credit scoring services which directly affects consumers' financial life. Among the key elements of trustworthy AI like transparency, safety, accountability, and fairness, fairness was selected as the subject of the study so that everyone could enjoy the benefits of automated algorithms from the perspective of inclusive finance without social discrimination. We divided the entire fairness related operation process into three areas like data, algorithms, and user areas through literature research. For each area, we constructed four detailed considerations for evaluation resulting in 12 checklists. The relative importance and priority of the categories were evaluated through the analytic hierarchy process (AHP). We use three different groups: financial field workers, artificial intelligence field workers, and general users which represent entire financial stakeholders. According to the importance of each stakeholder, three groups were classified and analyzed, and from a practical perspective, specific checks such as feasibility verification for using learning data and non-financial information and monitoring new inflow data were identified. Moreover, financial consumers in general were found to be highly considerate of the accuracy of result analysis and bias checks. We expect this result could contribute to the design and operation of fair AI-based financial services.

• Journal of Food Hygiene and Safety
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• v.31 no.2
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• pp.74-84
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• 2016

Literacy on food additives of elementary school teachers (ET) and nutrition teachers (NT) could be influential factor on safe dietary education for school children. Therefore, the perceptions and information needs on food additives were surveyed from 351 elementary school teachers and nutrition teachers in metropolitan area of Korea, and the basic data for the promotion of risk communication on food additives among them were obtained. Compared to ET who consider 'taste' (39.1%) as the most important factor while purchasing food, NT considered 'safety' (68.1%) first (p < 0.001). Among the food labelling items, the level of understanding on food additives was the lowest both in ET (3.53) and NT (4.17), and NT showed better levels of understanding overall on food labels. Both ET and NT regarded hazardous factors of food as environmental pollutants, foodborne pathogens, and food additives in order, and tended to select 'no additives' or 'no artificial color' products while purchasing processed food. Although NT answered that they know all food additives had been passed the evaluation of safety and effectiveness tests (100%) and have standards of use (81.9%), majority of them (87.5%) believed the consumption of food additives are harmful on human health. ET (75.2%) also regarded food additives as dangerous materials. Above results suggested the necessity of proper and enough risk communication for both ET and NT. Both ET and NT wanted to have information on the safety or hazard of food additives. Most preferred media to get the information on food additives was TV (3.80) among ET and lecture (3.65) among NT. ET and NT trusted hospital, research institution/universities or the personnels working in these institutions as the provider of information on food additives. The result that the trust levels of ET and NT on government were relative low suggested the weakness of risk communication in Korean government. Although ET and NT answered that they do not trust mass media, their behaviors were affected by them such as reading food labels in ET (39.4%) and reducing the consumption of food additives in NT (50%). They also indicated mass media's problem of sensitive approach on food additives and asked the urgent reaction of government by providing sound information through experts on food additives. Above results revealed that ET and NT have different perceptions and information needs on food additives, therefore, proper risk communication should be provided for them to serve as dietary educators for elementary school children.

• Journal of Mushroom
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• v.2 no.3
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• pp.149-156
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• 2004

This study was carried out to obtain basic data on physiological characteristics for an artificial cultivation of fruiting body of Cordyceps. Specimens such as Cordyceps longissima, C. militaris and C. pruinosa were collected at Mt. Halla of Cheju island in July, 2003. Among four different culture media which have been used for culture of mushrooms, MCM medium was selected for the favorable culture medium of the Cordyceps tested. The initial pH of solid medium for mycelial growth of Cordyceps was good in the range of pH 5.0~7.0 lower than 8.0. The mycelial growth of C. longissima was most favorable on culture media supplemented with glucose, one of monosaccharides. In C. militaris, nine carbon sources were favorable to the mycelial growth as compared with control among 11 carbon sources. Six nitrogen sources were favorable to the mycelial growth of C. longissima as compared with control among 9 carbon sources; namely, the mycelial growth of C. longissima was most favorable on culture media contained potassium nitrate, and followed in order by ammonium citrate and sodium nitrate in 4 weeks incubation.

• The Korean Journal of Archival Studies
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• no.79
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• pp.5-32
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• 2024

The Korean government ranked 3rd among 193 UN member countries in the UN's 2022 e-Government Development Index. Korea, which has consistently been evaluated as a top country, can clearly be said to be a leading country in the world of e-government. The lubricant of e-government is data. Data itself is neither information nor a record, but it is a source of information and records and a resource of knowledge. Since administrative actions through electronic systems have become widespread, the production and technology of data-based records have naturally expanded and evolved. Technology may seem value-neutral, but in fact, technology itself reflects a specific worldview. The digital order of new technologies, armed with hyper-connectivity and super-intelligence, not only has a profound influence on traditional power structures, but also has an a similar influence on existing information and knowledge transmission media. Moreover, new technologies and media, including data-based generative artificial intelligence, are by far the hot topic. It can be seen that the all-round growth and spread of digital technology has led to the augmentation of human capabilities and the outsourcing of thinking. This also involves a variety of problems, ranging from deep fakes and other fake images, auto profiling, AI lies hallucination that creates them as if they were real, and copyright infringement of machine learning data. Moreover, radical connectivity capabilities enable the instantaneous sharing of vast amounts of data and rely on the technological unconscious to generate actions without awareness. Another irony of the digital world and online network, which is based on immaterial distribution and logical existence, is that access and contact can only be made through physical tools. Digital information is a logical object, but digital resources cannot be read or utilized without some type of device to relay it. In that respect, machines in today's technological society have gone beyond the level of simple assistance, and there are points at which it is difficult to say that the entry of machines into human society is a natural change pattern due to advanced technological development. This is because perspectives on machines will change over time. Important is the social and cultural implications of changes in the way records are produced as a result of communication and actions through machines. Even in the archive field, what problems will a data-based archive society face due to technological changes toward a hyper-intelligence and hyper-connected society, and who will prove the continuous activity of records and data and what will be the main drivers of media change? It is time to research whether this will happen. This study began with the need to recognize that archives are not only records that are the result of actions, but also data as strategic assets. Through this, author considered how to expand traditional boundaries and achieves reterritorialization in a data-driven society.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.10 no.4
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• pp.70-82
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• 2007

Aiming at nature's early restoring needs to select plant species harmonizing with surrounding environment that fits to restoring goal of ultimately aiming at woody plants dominant vegetation that protect and stabilize surface parts of bared slopes. And it is important to make it assimilated with surrounding natural vegetation by differentiating planning of seed mixtures. Natural Ecological Restoring Construction Methods (JSB Method) was developed to increase the effect of landscape change according to seasons not to simple hydro-seeding by reducing rate of foreign grasses while raising rate of wild flower using. It was considered that using wild flowers that bloom on each season solved the problems of slope landscapes that looks artificial and uninteresting. After researching environmental condition of the slopes, JSB Method has shown that, as of wet-type method, soil is relatively soft and the difference of thickness of plant base soil media affects on the difference of soil hardness. In case of soil hardness of 8.8~17mm, there's dangerousness of slope's collapsing, but it has shown that growth of plant was favorable. For the acidity of soil, most of them are in the type of neutralized soil of more than pH 6. And after analyzing the degree of woody plants dominance, it had shown that lower part was occupied with wild flowers and other herbaceous species like China pin, golden phesant mum, pitcher plant, and middle and upper part was occupied with woody plants like silk-tree, sumac forming multi-layer structure. It can be concluded that the restoration objects of the woody plant vegetation on the roadside slopes can be accomplished successfully by Natural Ecological Restoring Construction Method (JSB method).

• Development and Reproduction
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• v.20 no.3
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• pp.219-225
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• 2016

Most of the commercial devices for vitrification are directly immersed into the warming solution (WS) for increasing of warming rate. However, the previous modified cut standard straw (MCS) which has reported is difficult to immerse into the WS. The aim of this study was to investigate whether the long cut straw (LCS) could be useful as a stable tool for vitrified-warmed human blastocysts. A total of 138 vitrified-warmed cycles were performed between November 2013 and November 2014 (exclusion criteria: women ${\geq}38$ years old, poor responder, surgical retrieval sperm, and severe male factor). The artificial shrinkage was conducted using 29-gauge needles. Ethylene glycol and dimethyl sulfoxide (7.5% and 15% (v/v)) were used as cryoprotectants. Freezing and warming were conducted using the LCS tool. The cap of LCS was removed using the forceps in the liquid nitrogen ($LN_2$) and then directly immersed into the first WS for 1 min at $37^{\circ}C$ (1 M sucrose). Only re-expanded blastocysts were transferred after it was cultured in sequential media for 18-20 h. A total of 294 blastocysts were warmed, and all were recovered (100%). Two hundred eighty-five embryos were survived (96.9%). The vitrified-warmed blastocysts of all patients were transferred without any cancellation. We were able to achieve a reasonable implantation (24.2%), following by clinical pregnancy (36.2%), which then continued to ongoing pregnancy (36.2%), and live birth (31.2%). Using LCS is achieved the acceptable rates of survival, pregnancy and live birth. Therefore, the LCS could be considered as a stable and simple tool for human embryo vitrificaton.

• Journal of Life Science
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• v.12 no.6
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• pp.708-714
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• 2002

A new leaf blight was found on the perilla leaves at the major perilla-cultivating areas such as Kangdong in Busan and Miryang in Kyungnam province. Symptoms of the disease initially appeared on the edge of perilla leaves showing black necrosis and drying, and the infected leaves were finally fell down. The SD1 isolate showing strong pathogenicity and forming abundant conidial spores on the diseased lesions was isolated. Among the tested media, mycelial growth was abundant on PDA (Potato Dextrose Agar) medium at $25^{\circ}C$ under dark condition, but conidial formation was greater on V8A (V-8 juice A8ar) medium than that on PDA medium. Optimal temperatures for mycelial growth and conidial formation on PDA medium were respectively $25^{\circ}C$ and 3$0^{\circ}C$. The rate of conidial germination and the elongation of germ tube were more effective in 10% tomato juice than those in PDB (Potato Dextrose Broth) and sterile water. In 10% tomato juice, the rate of conidial germination and the length of germ tube were 100% after incubation for 24k and 535.2${\mu}{\textrm}{m}$ after incubation for 36hr, respectively. According to the result of pathogenicity, it revealed that conidial suspention with 10% tomato juice was the most effective for pathogenicity test showing as 100% of disease incidence, and the symptoms caused by artificial inoculum were same as those of naturally infected perilla. In this study, the SD1 isolate according to the results of morphological characteristics, the incubation characteristics and pathogenicity was firstly identified A. alternata, and named as leaf blight of perilla.