• Korean Journal of Environmental Agriculture
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• v.38 no.4
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• pp.225-236
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• 2019

BACKGROUND: Hydroponics is one of the methods for evaluating plant production using the inorganic nutrient solutions, which is applied under the artificial light conditions of plant factory system. However, the application of the conventional inorganic nutrients for hydroponics caused several environmental problems: waste from culture mediums and high nitrate concentration in plants. Organic nutrients are generally irrigated as a supplementary fertilizer for plant growth promotion under field or greenhouse conditions. Hydroponic culture using organic nutrients derived from the agricultural by-products such as dumped stems, leaves or immature fruits is rarely considered in plant factory system. Effect of organic or conventional inorganic nutrient solutions on the growth and nutrient absorption pattern of green and red leaf lettuces was investigated in this experiment under fluorescent lamps (FL) and mixture Light-Emitting Diodes (LEDs). METHODS AND RESULTS: Single solution of tomatoes (TJ) and kales (K) deriving from agricultural by-products including leaves or stems and its mixed solution (mixture ration 1:1) with conventional inorganic Yamazaki (Y) were supplied for hydroponics under the plant factory system. The Yamazaki solution was considered as a control. 'Jeockchima' and 'Cheongchima' lettuce seedlings (Lactuca sativa L.) were used as plant materials. The seedlings which developed 2~3 true leaves were grown under the light qualities of FL and mixed LED lights of blue plus red plus white of 1:2:1 mixture in energy ratio for 35 days. Light intensity of the light sources was controlled at 180 μmol/㎡/s on the culture bed. The single and mixture nutrient solutions of organic and/or inorganic components which controlled at 1.5 dS/m EC and 5.8 pH were regularly irrigated by the deep flow technique (DFT) system on the culture gutters. Number of unfolded leaves of the seedlings grown under the single or mixed nutrient solutions were significantly increased compared to the conventional Y treatment. Leaf extension of 'Jeockchima' under the mixture LED radiation condition was not affected by Y and YK or YTJ mixture treatments. SPAD value in 'Jeockchima' leaves exposed by FL under the YK mixture medium was approximately 45 % higher than under conventional Y treatment. Otherwise, the maximum SPAD value in the leaves of 'Cheongchima' seedlings was shown in YK treatment under the mixture LED lights. NO₃-N contents in Y treatment treated with inorganic nutrient at the end of the experiment were up to 75% declined rather than increased over 60 % in the K and TJ organic treatment. CONCLUSION: Growth of the seedlings was affected by the mixture treatments of the organic and inorganic solutions, although similar or lower dry weight was recorded than in the inorganic treatment Y under the plant factory system. Treatment Y containing the highest NO₃-N content among the considered nutrients influenced growth increment of the seedlings comparing to the other nutrients. However effect of the higher NO₃-N content in the seedling growth was different according to the light qualities considered in the experiment as shown in leaf expansion, pigmentation or dry weight promotion under the single or mixed nutrients.

• Journal of Global Scholars of Marketing Science
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• v.19 no.4
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• pp.24-31
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• 2009

Firms produce various products that differ by function, design, color, etc. Product proliferation occurs for three different reasons. When there exist economies of scope, the unit cost for a product is lower when it is produced in conjunction with another product than when it is produced separately. Second, consumers are heterogeneous in the sense that they have different tastes, preferences, or price elasticities. A firm can earn more profit by segmenting consumers into different groups with similar characteristics. For example, product proliferation helps a firm increase profits by satisfying various consumer needs more precisely. The third reason for product proliferation is based on strategy. Producing a number of products can not only deter entry by providing few niches, but can also cause a firm to react efficiently to a low-price entry. By producing various products, a firm can reduce niches so that potential entrants have less incentive to enter. Moreover, a firm can produce new products in response to entry, which is called fighting brands. That is, when an entrant tries to attract consumers with a low price, an incumbent introduces a new lower-quality product while maintaining the price of the existing product. The drawback of product proliferation, however, is cannibalization. Some consumers who would have bought a high-price product switch to a low-price product. Moreover, it is possible that proliferation can decrease profits when a new product is less differentiated from a rival’s than is the existing product because of more severe competition. Many studies have analyzed the effect of product line rivalry in the areas of economics and marketing. They show how a monopolist can solve the problem of cannibalization by adjusting quality in a market where consumers differ in their preferences for quality. They find that a consumer who prefers high-quality products will obtain his or her most preferred quality, but a consumer who has not such preference will obtain less than his or her preferred quality to reduce cannibalization. This study analyzed the effects of product line rivalry in a duopoly market with two types of consumers differentiated by quality preference. I assume that the two firms are asymmetric in the sense that an incumbent can produce both high- and low-quality products, while an entrant can produce only a low-quality product. The effects of product proliferation can be explained by comparing the market outcomes when an incumbent produces both products to those when it produces only one product. Compared to the case in which an incumbent produces only a high-quality product, the price of a low-quality product tends to decrease in a consumer segment that prefers low-quality products because of more severe competition. Prices, however, tend to increase in a segment with high preferences because of less severe competition. It is known that when firms compete over prices, it is optimal for a firm to increase its price when its rival increases its price, which is called a strategic complement. Since prices are strategic complements, we have two opposing effects. It turns out that the price of a high-quality product increases because the positive effect of reduced competition outweighs the negative effect of strategic complements. This implies that an incumbent needs to increase the price of a high-quality product when it is also introducing a low-quality product. However, the change in price of the entrant’s low-quality product is ambiguous. Second, compared to the case in which an incumbent produces only a low-quality product, prices tend to increase in a consumer segment with low preferences but decrease in a segment with high preferences. The prices of low-quality products decrease because the negative effect outweighs the positive effect. Moreover, when an incumbent produces both kinds of product, the price of an incumbent‘s low-quality product is higher, even though the quality of both firms’ low-quality products is the same. The reason for this is that the incumbent has less incentive to reduce the price of a low-quality product because of the negative impact on the price of its high-quality product. In fact, the effects of product line rivalry on profits depend not only on changes in price, but also on sales and cannibalization. If the difference in marginal cost is moderate compared to the difference in product quality, the positive effect of product proliferation outweighs the negative effect, thereby increasing the profit. Furthermore, if the cost difference is very large (small), an incumbent is better off producing only a low (high) quality product. Moreover, this study also analyzed the effect of product line rivalry when a firm can determine product characteristics by focusing on the issue of fighting brands. Recently, Korean air and Asiana airlines have established budget airlines called Jin air and Air Busan, respectively, to confront the launching of budget airlines such as Hansung airline and Jeju air, among others. In addition, as more online bookstores have entered the market, a leading off-line bookstore Kyobo began its own online bookstore. Through fighting brands, an incumbent with a high-quality product can increase profits by producing an additional low-quality product when its low-quality product is more differentiated from that of the entrant than is its high-quality product.

• Journal of Korean Academy of Nursing
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• v.20 no.2
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• pp.153-173
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• 1990

One of the important tasks for new parents. especially mothers, is to establish warm, mutually affirming interpersonal relationships with the new baby in the family, with the purpose of promoting the healthy development of the child and the wellbeing of the whole family. Nurses assess the quality of the behavioral characteristics of the maternal-infant interaction. This study examined the relationships between primiparas pereptions of their delivery experience and their maternal infant interaction. It compared to delivery experience of mothers having a normal vaginal delivery with those having a casearean section. The purpose was to explore the relationships between the mother's perceptions of her delivery experience with her maternal infant interaction. The aim was to contribute to the development of theoretical understanding on which to base care toward promoting the quality of maternal-infant interaction. Data were collected directly by the investigator and a trained associate from Dec. 1, 1987 to March 8, 1988. Subjects were 3 random sample of 62 mothers, 32 who had a normal vaginal delivery and 30 who had a non-elective cesarean section (but without other perinatal complications) at three general hospitals in Seoul. Instruments used were the Stainton Parent -infant Interaction Scale(1981) and the Marut and Mercer Perception of Birth Scale(1979). The first observations were made in the delivery room (for vaginally delivered mothers only), followed by day 1, day 2, day 3, and 2 weeks, 4 weeks, 6 weeks and 8 weeks after birth, for a total of 7-8 contacts(Cesarean section mothers were observed on days 4 and 5 but the data not used for analysis). Observations in the hospital were made during the hour prior to scheduled feedings. The infant was placed beside the mother. Later contacts were made at home. Data analysis was done by computer using as SPSS program and indulded X² test, paired t-test, t-test, and Pearson Correlation coefficient ; the results were as follows. 1. Mothers who had a normal vaginal delivery tended to perceive the delivery experience more positively than cesarean section mothers(p＝0.002). The finding supported the hypothesis I that perception of delivery would vary according to the method of delivery. Mothers' perceptions of birth were classified into three dimensions, labor, delivery and the bady. There was a significantly different and positive perception by the vaginally delivered mothers to the delivery experience(p＝0.000) but no differences for labor or the bady according to the delivery method(p＝0.096, p＝0.389), 2. Mothers who had a normal vaginal delivery had higher average maternal-infant interaction scores(p＝0.029) than mothers who had a cesarean section. There were similar higher scores for the 1st day(p＝0.042), 2nd day (p＝0.009), and the 3rd day(p＝0.006) after delivery but not for later times. The findings supported the hypothesis Ⅱ that there would be differences in maternal-infant interaction for mothers having vaginal and cesarean section deliveries. However these differences deccreased section deliveries. However these differences decreased over time . by eight weeks the scores for vaginal delivery mothers averaged 8.1 and for cesarean section mothers, 7.9. 3. The more highly positive the pereption of the delivery experience, the higher the maternal-infant interaction score for all subjects(F＝.3206, p＝.006). The findings supported the hypothesis Ⅲ that there would be correlations between perceptions of delivery and maternal-infant interaction. The maternal infant interaction was highest when the perception of the bady and deliery was positive(r＝.4363, p＝.000, r＝.2881, p＝.012). No correlations between perceptions of labor and maternal-infant interaction were found(p＝0.062). 4. The daily maternal-infant interaction score for the initial contact after birth to 8 weeks postpartum had the lowest average score 5.20 and the highest 7.98(in a range of 0-10). This subjects group of mothers needed nursing intervention to promote their maternal- infant interaction. The daily scores for the maternal-infant over the period of eight weeks. However, there were significantly different increases in maternal-infant interaction only from the first to second day(p＝0.000) and from the fourth to sixth weeks after birth(P＝0.000). 5. When the eight items of maternal-infant interaction were evaluated separately, “Expresses feelings about her role as mother” had the highest average score, 1.64(ina range of 0-3)and “Speaks to baby” the lowest, 0.9. All items, with the possible exception of “Expresses feelings about her role as mother”, suggested the subjects' need of nursing intervention to promote maternal-infant interaction. 6. There were positive correlations between certain general charateristis, namely, both a higher economic status(p＝0.002) and breast feeding(p＝0.202) and maternal - infant interaction. There were positive correlations between a mother's confidence in her role as a mother and the perception of the birth experience(p＝0.004). For mothers who had a cesarean section, a positive perception of the birth experience was related to the duration of her marriage(p＝0.010), a wanted pregnancy (P＝0.030) and her confidence in her role as a mother(p＝0.000). Pereptions of birth for mothers who had a normal vaginal delivery were positive than those for mothers who had a cesarean section. The level of maternalinfant interaction for mothers delivered vaginally was higher than for cesarean section mothers. The relationship between perception of birth and materanalinfant interaction was confirmed. Cesarean section has an impact on the mother's perceived experience of birth which, in turn, is positively related to maternal-infant in turn, is positively related to maternal-infant interaction. Nursing intervention to enhance maternal-infant interaction should begin in prenatal classes with an exploration of the potential impact of cesarean section on the perceptions of the birth experience and continue throughout the perinatal and post-natal periods to promote the mother's ability to control with this crisis experience and to mobilize social support. Nursing should help transform a relatively negatively perceived experience into an accepted, positively perceived and self affirming experience which enhances the maternal-infant relationship.

• Journal of the East Asian Society of Dietary Life
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• v.14 no.1
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• pp.11-19
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• 2004

To investigate the effect of eating habits and lifestyle on the food intake of university students in Daejeon, 104 male students(26.75％) and 282 female students(73.75％) were surveyed about their food intake, eating habits, and lifestyle using the questionnaire. The major food served as breakfast was steamed rice(76.05％) and there was a little significant difference between male and female. The major food served as lunch was also steamed rice(73.77％) and male students ate it more than female ones. According to the survey, 41.95％ of the subjects had breakfast regularly, and 24.35％ seldom, which showed no significant difference between male and female. In case of lunch, the percentile of subjects(54.55％) who had regularly eaten lunch was more than that of breakfast, and there was a little significant difference between male and female. The survey said most subjects(49.22％) had eaten dinner irregularly, which rate was higher in male students. The meal skipped usually was the breakfast(24.35％), which rate was higher in female students. The reason why the subjects skipped the meal was mainly due to the lack of sufficient time for breakfast and lunch, and for dinner to the weight loss. Among the subjects, 80％ said they were non-smokers; 96.44％ in female students and 35.58％ in male ones. In case of drinking, most subjects said they sometimes drank(67.19％) and the frequency of drinking was once or twice a month(51.99％), which showed the significant difference between male and female. In the aspects of effects of drinking and smoking on the food intake, the drinking practice after eating was shown to be the highest(55.98％); smoking generally affected the food intake, which showed the difference between male and female. Food intake during the examination period didn't show any differences to the usual one or increased a little bit, which showed a difference between male and female. Losing appetite during the examination period was shown mainly in the female students. When they felt blue or tired, the food intake decreased, which showed a significant difference between male and female was shown. When feeling good, the food intake significantly increased, which showed a significant difference between male and female. Therefore, there was a significant difference between male and female in the actual eating habits and in the aspects of food intake.

• Korean Journal of Environment and Ecology
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• v.31 no.6
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• pp.537-548
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• 2017

The purpose of this study was to investigate the species composition and the aquatic environment of Jojong Stream and Sudong Stream, which were the original habitats of Zacco koreanus population and restored population re-introduced in Bongseonsa Stream. It also compared and analyzed the states of the growth and reproductive ability of Z. koreanus habiting in each of the three streams. The investigation was conducted in June 2016 which was known as the spawning season of Z. koreanus. The results of the physical aquatic environments showed the slight differences in altitude, width and depth of water among three streams, but the bottom structure was found to be quite different in the composition of the boulder, cobble, and pebble among the streams. The result of the physicochemical aquatic environment analysis showed that there were no significant differences in water temperature, pH, DO, BOD, and EC among the three stream. In the fish fauna investigation, 530 individuals of 11 species of 3 families were collected in Bongseonsa Stream, 293 individuals of 12 species of 4 families were collected in Jojong Stream, and 361 individuals of 11 species of 4 families were collected in Sudong Stream. All three streams were dominated by Z. koreanus and Z. platypus. Six Korean endemic species appeared in each of the three streams, showing the high occurrence rate of indigenous species of 50.0% or more. The aggregation index analysis revealed that the mean dominance index ranged from 0.63 (${\pm}0.05$, BS) to 0.72(${\pm}0.01$, JJ), mean diversity index from 1.55 (${\pm}0.06$, JJ) to 1.78 (${\pm}0.11$, BS), mean evenness index from 0.71 (${\pm}0.03$, JJ) to 0.76 (${\pm}0.02$, BS), and mean richness index from 1.61 (${\pm}0.33$, JJ) to 1.73 (${\pm}0.24$, SD). The result indicated that the observed differences between the stream community indices were statistically nonsignificant. The similarity analysis showed that 75.4% similarity was divided into two groups of A and B and that the fish fauna on each analyzed point was similar. The quantitative habitat evaluation index (QHEI) analysis showed that the average value of QHEI was 151.0 (${\pm}46.0$), which means that it was a suboptimal habitat environment. The result of length-weight analysis of Z. koreanus populations showed that the regression coefficient b of the restoration population and the original habitat population were at 3.0 or higher while the condition factor had a positive slope. Moreover, it was found that the slopes of the regression coefficient b and condition factor of the original habitat population were larger than the restored population. The analysis of the length frequency distribution of the Z. koreanus population revealed that all three streams maintained the stable life cycle although it was found that the growth rate of the original habitat population was faster than the restored population in the one-year-old class. The result of the gonadosomatic index (GSI) analysis showed that the GSI median value of the Z. koreanus population in the restored habitat Bongseonsa Stream was higher than the population in the original habitat Jojong Stream and Sudong Stream for both of males and females.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.45-69
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• 2016

Recently, sentiment analysis using open Internet data is actively performed for various purposes. As online Internet communication channels become popular, companies try to capture public sentiment of them from online open information sources. This research is conducted for the purpose of analyzing pulbic sentiment of Korean Top-10 companies using a multi-categorical sentiment lexicon. Whereas existing researches related to public sentiment measurement based on big data approach classify sentiment into dimensions, this research classifies public sentiment into multiple categories. Dimensional sentiment structure has been commonly applied in sentiment analysis of various applications, because it is academically proven, and has a clear advantage of capturing degree of sentiment and interrelation of each dimension. However, the dimensional structure is not effective when measuring public sentiment because human sentiment is too complex to be divided into few dimensions. In addition, special training is needed for ordinary people to express their feeling into dimensional structure. People do not divide their sentiment into dimensions, nor do they need psychological training when they feel. People would not express their feeling in the way of dimensional structure like positive/negative or active/passive; rather they express theirs in the way of categorical sentiment like sadness, rage, happiness and so on. That is, categorial approach of sentiment analysis is more natural than dimensional approach. Accordingly, this research suggests multi-categorical sentiment structure as an alternative way to measure social sentiment from the point of the public. Multi-categorical sentiment structure classifies sentiments following the way that ordinary people do although there are possibility to contain some subjectiveness. In this research, nine categories: 'Sadness', 'Anger', 'Happiness', 'Disgust', 'Surprise', 'Fear', 'Interest', 'Boredom' and 'Pain' are used as multi-categorical sentiment structure. To capture public sentiment of Korean Top-10 companies, Internet news data of the companies are collected over the past 25 months from a representative Korean portal site. Based on the sentiment words extracted from previous researches, we have created a sentiment lexicon, and analyzed the frequency of the words coming up within the news data. The frequency of each sentiment category was calculated as a ratio out of the total sentiment words to make ranks of distributions. Sentiment comparison among top-4 companies, which are 'Samsung', 'Hyundai', 'SK', and 'LG', were separately visualized. As a next step, the research tested hypothesis to prove the usefulness of the multi-categorical sentiment lexicon. It tested how effective categorial sentiment can be used as relative comparison index in cross sectional and time series analysis. To test the effectiveness of the sentiment lexicon as cross sectional comparison index, pair-wise t-test and Duncan test were conducted. Two pairs of companies, 'Samsung' and 'Hanjin', 'SK' and 'Hanjin' were chosen to compare whether each categorical sentiment is significantly different in pair-wise t-test. Since category 'Sadness' has the largest vocabularies, it is chosen to figure out whether the subgroups of the companies are significantly different in Duncan test. It is proved that five sentiment categories of Samsung and Hanjin and four sentiment categories of SK and Hanjin are different significantly. In category 'Sadness', it has been figured out that there were six subgroups that are significantly different. To test the effectiveness of the sentiment lexicon as time series comparison index, 'nut rage' incident of Hanjin is selected as an example case. Term frequency of sentiment words of the month when the incident happened and term frequency of the one month before the event are compared. Sentiment categories was redivided into positive/negative sentiment, and it is tried to figure out whether the event actually has some negative impact on public sentiment of the company. The difference in each category was visualized, moreover the variation of word list of sentiment 'Rage' was shown to be more concrete. As a result, there was huge before-and-after difference of sentiment that ordinary people feel to the company. Both hypotheses have turned out to be statistically significant, and therefore sentiment analysis in business area using multi-categorical sentiment lexicons has persuasive power. This research implies that categorical sentiment analysis can be used as an alternative method to supplement dimensional sentiment analysis when figuring out public sentiment in business environment.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.123-138
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• 2017

Since the stock market is driven by the expectation of traders, studies have been conducted to predict stock price movements through analysis of various sources of text data. In order to predict stock price movements, research has been conducted not only on the relationship between text data and fluctuations in stock prices, but also on the trading stocks based on news articles and social media responses. Studies that predict the movements of stock prices have also applied classification algorithms with constructing term-document matrix in the same way as other text mining approaches. Because the document contains a lot of words, it is better to select words that contribute more for building a term-document matrix. Based on the frequency of words, words that show too little frequency or importance are removed. It also selects words according to their contribution by measuring the degree to which a word contributes to correctly classifying a document. The basic idea of constructing a term-document matrix was to collect all the documents to be analyzed and to select and use the words that have an influence on the classification. In this study, we analyze the documents for each individual item and select the words that are irrelevant for all categories as neutral words. We extract the words around the selected neutral word and use it to generate the term-document matrix. The neutral word itself starts with the idea that the stock movement is less related to the existence of the neutral words, and that the surrounding words of the neutral word are more likely to affect the stock price movements. And apply it to the algorithm that classifies the stock price fluctuations with the generated term-document matrix. In this study, we firstly removed stop words and selected neutral words for each stock. And we used a method to exclude words that are included in news articles for other stocks among the selected words. Through the online news portal, we collected four months of news articles on the top 10 market cap stocks. We split the news articles into 3 month news data as training data and apply the remaining one month news articles to the model to predict the stock price movements of the next day. We used SVM, Boosting and Random Forest for building models and predicting the movements of stock prices. The stock market opened for four months (2016/02/01 ~ 2016/05/31) for a total of 80 days, using the initial 60 days as a training set and the remaining 20 days as a test set. The proposed word - based algorithm in this study showed better classification performance than the word selection method based on sparsity. This study predicted stock price volatility by collecting and analyzing news articles of the top 10 stocks in market cap. We used the term - document matrix based classification model to estimate the stock price fluctuations and compared the performance of the existing sparse - based word extraction method and the suggested method of removing words from the term - document matrix. The suggested method differs from the word extraction method in that it uses not only the news articles for the corresponding stock but also other news items to determine the words to extract. In other words, it removed not only the words that appeared in all the increase and decrease but also the words that appeared common in the news for other stocks. When the prediction accuracy was compared, the suggested method showed higher accuracy. The limitation of this study is that the stock price prediction was set up to classify the rise and fall, and the experiment was conducted only for the top ten stocks. The 10 stocks used in the experiment do not represent the entire stock market. In addition, it is difficult to show the investment performance because stock price fluctuation and profit rate may be different. Therefore, it is necessary to study the research using more stocks and the yield prediction through trading simulation.

• Journal of The Korean Society of Grassland and Forage Science
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• v.36 no.4
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• pp.344-349
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• 2016

This study was conducted to evaluate the possibility of expanding the usage of whole crop silage from beef cattle and dairy cow to hogs and chickens. For this purpose, a crushing device was developed to crush whole crop silage. The crushed silage was sealed, and analyzed for its feed value. The silage varieties used for the experiment included Saessal barley and Geumgang wheat. Whole crop barley and wheat were crushed in the crushing system as a whole without separating stems, leaves, grains, etc.. When the crushed whole crop silages (CWCS) were analyzed, full grain, grains above 10 mm in size, grains 5~10 mm in size, and grains below 5 mm in size accounted for, 20%, 4%, 27%, and 49 %, respectively. In order to facilitate the fermentation of CWCS, inoculated some fermenter into each CWCS sample (barley or wheat). As control, another set of sample was not inoculated. Crude protein (CP), ether extract (EE), crude fiber (CF), neutral detergent fiber (NDF), acid detergent fiber (ADF), lignin, cellulose content, total digestible nutrient (TDN), and relative feed value (RFV) of fermenter-inoculated Saessal barley were 2.45 %, 1.61%, 8.95%, 16.94%, 9.52%, 1.01%, 8.51%, 81.38%, and 447.5%, respectively. The CP, EE, CF, NDF, ADF, lignin, cellulose content, TDN, and RFV in the other sample of Saessal barley without inoculation of fermenter were 2.57%, 1.62%, 9.61%, 18.25%, 10.13%, 1.10%, 9.04%, 80.90%, and 412.9%, respectively. The CP, EE, CF, NDF, ADF, lignin, cellulose content, TDN, and RFV of fermenter-inoculated Geumgang wheat sample were 2.43%, 1.27%, 10.99%, 19.49%, 11.23%, 1.46%, 9.77%, 80.03%, and 382.6%, respectively. The CP, EE, CF, NDF, ADF, lignin, cellulose content, TDN, RFV of the other set sample of Geumgang wheat sample without the inoculation of fermenter were 2.28%, 1.44%, 10.08%, 18.02%, 10.44%, 1.26%, 9.18%, 80.65%, and 416.9%, respectively. The TDN and RFV content in the fermenter-inoculated Saessal barley were 81.38% and 447.5%, respectively, while the one in the fermenter-inoculated Geumgang wheat were 80.03% and 382.6% respectively. When the feed value of whole crop barley and wheat silage without crushing process was compared to the feed value of whole crop barley and wheat silage made from crushing system, the latter appeared to be higher than the former. This could be due to the process of sealing the crushed silage which might have minimized air content between samples and shortened the golden period of fermentation. In conclusion, these results indicate that a crushing process might be needed to facilitate fermentation and improve the quality of silage when making whole crop silage.

• Korean Journal of Soil Science and Fertilizer
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• v.10 no.1
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• pp.61-67
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• 1977

A study was conducted in order to compare the topdressing method of the conventional fertilizers as control and the deep application method of the ball complex fertilizer newly developed. The ball complex fertilizer consisted of 5% of nitrogen, 5% of phosphorus, and 7% of potassium. Basal application of nitrogen for the rice plant was the same for both control plots and ball complex plots. One ball complex fertilizer per four hills was applied at depth of 12~13cm 35days before heading stage while control plot received three times topdressing at different growth stages as usual practice. The results obtained were as follows. 1. The ball complex fertilizer applied in the soil was continuously utilized by the rice plants until harvest time while nitrogen and potassium uptake of control plots was reduced rapidly after heading stage. Daily uptake of nitrogen and potassium per hill at maturing stage were 0.45mg and 0.68mg in control plots, but 4.80mg and 7.0mg respectively in ball complex plots. 2. Dry matter productivity of the rice plant in control plots, well coinciding with nutrients uptake pattern, was maximum just after heading stage decreased at maturing stage. But dry matter productivity in ball complex plots was much higher at maturing stage than at heading stage. 3. Ball complex application increased effective tillering rate, causing higher panicle number per hill. 4. Ball complex application brought about 528kg/10a of hulled grain yield while the conventional practice 423kg/10a. 5. Deep application of ball complex was superior to usual practice in terms of yield components such as panicle number per hill, filled grain number per panicle, maturing rate, and 1,000 grain weight. 6. From the morphological characteristics point of view, the deep application of ball complex made the flag leaf and the 2nd leaf heavier, larger and broader as compared to control treatment. 7. It is considered that by applying the ball complex fertilizer at depth of 12~13cm sufficient amount of nitrogen and potassium could be utilized by rice plants during the maturing stage and assimilated in the leaf blade, consequently making the flag leaf and the 2nd leaf bigger and healthier. The fact can easily explain that the ball complex plots had higher capacity of photosynthesis, less discoloration of lower leaves, bigger leaf area index, and better grain yield as compared to the conventional practice. In conclusion the deep application method of the ball complex fertilizer was superior to the routine topdressing method of the usual fertilizers.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.95-108
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• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.