• Food Science and Industry
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• v.55 no.2
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• pp.188-202
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• 2022

In the insect industry, as the scope of application of insects is expanded from pet insects and natural enemies to feed, edible and medicinal insects, the demand for quality control of insect raw materials is increasing, and interest in securing the safety of insect products is increasing. In the process of expanding the industrial scale, controlling the temperature and humidity and air quality in the insect breeding room and preventing the spread of pathogens and other pollutants are important success factors. It requires a controlled environment under the operating system. European commercial insect breeding facilities have attracted considerable investor interest, and insect companies are building large-scale production facilities, which became possible after the EU approved the use of insect protein as feedstock for fish farming in July 2017. Other fields, such as food and medicine, have also accelerated the application of cutting-edge technology. In the future, the global insect industry will purchase eggs or small larvae from suppliers and a system that focuses on the larval fattening, i.e., production raw material, until the insects mature, and a system that handles the entire production process from egg laying, harvesting, and initial pre-treatment of larvae., increasingly subdivided into large-scale production systems that cover all stages of insect larvae production and further processing steps such as milling, fat removal and protein or fat fractionation. In Korea, research and development of insect smart factory farms using artificial intelligence and ICT is accelerating, so insects can be used as carbon-free materials in secondary industries such as natural plastics or natural molding materials as well as existing feed and food. A Korean-style customized breeding system for shortening the breeding period or enhancing functionality is expected to be developed soon.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.

• Journal of Embryo Transfer
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• v.26 no.1
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• pp.65-70
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• 2011

This study was conducted to investigate the survival rate of AndroMed and Tris-egg yolk extender for cryopreservation of Korean Native Bull Semen (Chick Cow). Semen was collected from a Korean Native Bull Semen over 3 year's old. The semen was diluted 1:1 by AndroMed and Tris-egg yolk extender. The pellet was diluted to final sperm concentration of $5{\times}10^7$ cell/ml by doubling in every 10 minutes at $4^{\circ}C$ cold chamber. The semen was equilibrated for 1 hrs at cold chamber and packed to 0.5 ml straw. The semen straws were located above 5 cm of liquid nitrogen for 5 minutes. And then the frozen straw was plunged to LN2. The presented straws were examined the viability and motility after thawed at $37^{\circ}C$ water bath. The survival rates was significantly higher (p<0.05) in Tris-egg yolk extender than AndroMed extender ($89.7{\pm}19.8$ vs. $73.4{\pm}11.2$). However, motility was no significant differences ($78.4{\pm}18.7$ vs. $67.9{\pm}14.6$). Survival rate in time of equilibration between visual and CASA program had higher in 2 h ($86.33{\pm}9.4$ vs. $92.32{\pm}12.4$) than in 5 h ($78.20{\pm}7.8$ vs. $88.28{\pm}13.1$) 15 h ($65.24{\pm}6.6$ vs. $76.48{\pm}17.3$) 20 h ($56.26{\pm}4.6$ vs. $67.73{\pm}18.4$). The development rates to cleavage was higher in Tris-egg yolk extender than AndroMed extender (82.2% vs. 81.7%). Similarly, the development rates to blastocyst was significantly higher (p<0.05) in Tris-egg yolk extender than AndroMed extender (42.3% vs. 29.6%). In conclusion, the obvious impact of this study will be its practical application to improve viability and fertilizing ability of cryopreserved spermatozoa used for in vitro fertilization (IVF) and AI, Which in turn will be beneficial to animal genetic resources conservation.

• Korean Journal of Soil Science and Fertilizer
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• v.34 no.4
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• pp.255-264
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• 2001

This study was conducted to investigate changes in inorganic phosphorus fractions in phosphorus accumulated plastic film house soils under cropping condition. Pot experiment was conducted with surface soils taken from plastic film house fields cultivated for 3, 8 and 16 years. Phosphorus fertilizer was applied at the rates of 0 (P0), $100kg\;ha^{-1}$ (recommended application rate. P1) and $200kg\;ha^{-1}$ (P2) as fused phosphate. Crops were grown sequentially in the order of corn-Chinese cabbage-Chinese cabbage-corn for 3 years. The content of easily soluble-P fraction was decreased with cropping. There were significantly positive relationship not only between the contents of easily soluble-P and the amounts of soil available P ($r=0.839^{**}{\sim}0.952^{**}$ for Bray-1 P, $r=0.895^{**}{\sim}0.967^{**}$ for Lancaster P, and $r=0.491^{**}{\sim}0.821^{**}$ for Olsen P), but also between the amounts of P absorbed by plants and the amounts of easily soluble P decreased ($r=0.644^{**}{\sim}0.822^{**}$). The decrease of easily soluble-P during cropping period could be described by a first-order reaction. The number of cropping times needed to decrease the content of easily soluble-P to an index level of $0.2mg\;kg^{-1}$, which is commonly reported as the desired concentration for soil P, was predicted in the range of 26~33 cropping times by using the equations. Regardless of P fertilization, the proportion of Al-P to total P was little varied during cropping period, but the proportion of Fe-P to total P increased with cropping. Although the content of Ca-P was high before cropping, the proportion of Ca-P to total P was increased with cropping. The proportion of reductant soluble-P to total P was little varied for P fertilizer treatment but was increased for no P fertilizer treatment. The residual-P was decreased during cropping period due to the absorption by crops and the conversion to other inorganic P fractions.

• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.321-335
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• 2020

Given that with the development of the 4th industry, interest and desire for smart cities are gradually increasing and related technologies are developed as a way to strengthen urban competitiveness by utilizing big data, information and communication technology, IoT, M2M, and AI, the purpose of this study is to find out how to achieve this goal on the premise of the idea of smart well fair city. In other words, the purpose is to devise a smart well-fair city in the care area, such as health care, medical care, and welfare, and see if it is feasible. With this recognition, the paper aimed to review the concept and scope of smart city, the discussions that have been made so far and the issues or limitations on its connection to social security and social welfare, and based on it, come up with the concept of welfare city. As a method of realizing the smart welfare city, the paper reviewed characteristics and features of a social security platform as well as the applicability of smart city, especially care services. Furthermore, the paper developed discussions on the standardization of the city in terms of political and institutional improvements, utilization of personal information and public data as well as ways of institutional improvement centering on social security information system. This paper highlights the importance of implementing the digitally based community care and smart welfare city that our society is seeking to achieve. With regard to the social security platform based on behavioral design and the 7 principles(6W1H method), the present paper has the limitation of dealing only with smart cities in the fields of healthcare, medicine, and welfare. Therefore, further studies are needed to investigate the effects of smart cities in other fields and to consider the application and utilization of technologies in various aspects and the corresponding impact on our society. It is expected that this paper will suggest the future course and vision not only for smart cities but also for the social security and welfare system and thereby make some contribution to improving the quality of people's lives through the requisite adjustments made in each relevant field.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.6
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• pp.1-11
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• 2019

This study aims to understand the tendencies and characteristics when constructing landscape architectural archives in the United States, and to find implications for creating Korean landscape architectural archives. Focusing on seven American landscape architectural archives operated by public institutes, universities, and research institutes, this study examines the background, mission, scope, subject, acquisition, arrangement, and application of the programs in the archives. The results show that the characteristics of the American landscape architectural archives are as follows: first, the recognition of the value and importance of the landscape plays a major role in the establishment of archives; second, the purpose of the archives is to educate and encourage people to find diversity or significance of landscapes; third, the subject and scope of the archives vary according to the purpose of each operating institution; fourth, the main acquisitional method is to receive a donation and to purchase materials or documents; fifth, the classification systems of each archive differs depending on the subject and scope; and sixth, the archives were built on the basis of participation and collaboration with various experts and organizations with stable and sustainable financial resources. These characteristics offer three implications for constructing landscape architectural archives in Korea. First, a long-term vision for landscape architectural archives and the establishment of differentiated themes are required. Second, appropriate methods of material collection and systems of classification, recording, and digitization are necessary and therefore research and pilot archives are required. Third, it is necessary to secure the sustainability of archives by developing ways to utilize the archives in connection with academic and educational programs, thereby securing financial resources and allowing for the establishment of appropriate policies. As basic research, this study is significant as it provides a basis for further research concerning the development of landscape architectural archives in Korea.

• Journal of Life Science
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• v.19 no.9
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• pp.1328-1332
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• 2009

Anisakidosis is caused by anisakid nematodes (family Anisakidae) larvae which can cause not only direct tissue damage but also a severe allergic response related to excretory-secretion products. Lots of different species of anisakid larvae, including Anisakis simplex, Contracaecum, Goezia, Pseudoterranova, and Hysterothylacium, cause the anisakidosis. But it is difficult to diagnosis the species of larvae since the morphologies of larval anisakid nematodes are almost indistinguishable. In order to diagnosis the differential infections of larval anisakid nematodes, polymerase chain reaction - restriction fragment length polymorphism (PCR-RFLP) of 18S rDNA - was conducted. Three major species of anisakid larvae including A. simplex, C.ontracaecum spp, and Goezia spp. were collected from mackerel (Scomber japonicus), mullet (Mugil cephalus), founder (Paralichthys olivaceus), eel (Astroconger myriaster) and red sea bream (Pagrus major). PCR amplified 18S rDNA from each species of anisakid larvae was digested with eight restriction enzymes including Taq I, Hinf I, Hha I, Alu I, Dde I, Hae III, Sau96 I, and Sau3A I. The original sizes of PCR amplified 18S rDNA were 2.0Kb in both anisakid larvaes and Goezia. Restrction enzymes including Hinf 1, Alu 1, Hha I, Dde 1 and Hae III cut differently and distinguished the A. simplex and Contracaecum type C'. However, Contracaecum type A showed two different restriction enzyme cutting patterns by Taq 1, Hinf I, Alu 1, and Dde 1. One of the patterns was the same as those of A. simplex, Contracaecum type C' and Goezia and the other was unique. These results suggest that PCR-RFLP pattern by Hinf 1, Alu 1, Hae I, Dde 1 and Hae III can be applied to differential diagnosis of human infection with A. simplex and Contracaecum type C'. Contracaecum type A needs further study of classification by morphological characteristics and genetic analysis.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Korean Journal of Weed Science
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• v.3 no.2
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• pp.174-189
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• 1983

Experiments were conducted to evaluate the herbicidal characteristics of pyrazolate [4-(2,4-dichloro benzoyl)-1,3-dimethylpyrazol-5-yl-p-toluene-sulphonate] in greenhouse and lowland rice field. Pyrazolate controlled effectively most of annual weeds and such perennial weeds as Sagittaria pygmaea MIQ., Potamogeton distinctus A. BENN, Sagittaria trifolia L., Cyperus serotinus ROTTB, and Scirpus hotarui OHWI., whereas Eleocharis kuroguwai OHWI. was tolerent to pyrazolate. Although pyrazolate was applied at 2 to 10 days after transplanting, there was no difference in weed control The weeding effect was not influenced by percolation, depth of water and soil type. No difference in crop injury of rice was found with various levels of seedling age, transplanting depth, percolation, depth of water, soil type and time of application. When combined with butachlor, the mixture gave the same effect on rice phytotoxicity and weed control as pyrazolate alone did. Pyrazolate moved 1 to 2cm downward in lowland soil regardless of soil type and percolation. The herbicidal activity of pyrazolate persisted in soil for 60 to 90 days, depending on soil type, percolation and presence of soil microorganism.

• Korean Journal of Medicinal Crop Science
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• v.9 no.2
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• pp.156-165
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• 2001

Exogeneous application of pokeweed antiviral protein (PAP), a ribosomal-inacivating protein in the cell wall of Phytolacca americana (pokeweed) protects heterologous plants from viral and fungal infection. A cDNA clone of PAP introduced into Scrophularia buergeriana Miquel by thransformation with Agrobacterium tumefaciences. For plant transformation, explants were precultured on shoot induction medium without kanamycin for 2-5 day, and then they were cocultured with Agrobacterium for 10 minutes. The explants were placed on co culture medium in dark condition, $28^{\circ}C$ for 2days. After explants were washed in MS liquid medium, they were transferred into selection medium including kanamycin 50mg/L (MS salts+1mg/ l BAP+2mg/ l TDZ+0,2mg/ l NAA+MS vitamin+3% sucrose+0.8% agar, pH5.8). From PCR analysis, NPT II band was confirmed in transgenic plant genome and showed resistance against fungi in antifungal activity test. Micro assay to which protein extracted from transgenic line were added, revealed hyphae growth inhibition and no spore germination at high concentration. The characteristics of inhibited hyphae was represented transparent and thin. Expression of PAP in transgenic plants offers the possibility of developing resistance to viral and fungal infection.