• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.27 no.3
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• pp.239-249
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• 2001

The purpose of this study is to evaluate the relationship of the factors which could be influenced by orthognathic surgery especillay SSRO. We measured the amounts of the maximum opening, lateral movements, maximum velocity and pattern of mandibular path during the opening and closing of mandible at the following times ; preoperative, 1 month after operation, 6 months after operation respectively using MKG. And the results were compared according to the categorized subgroups. Following results were obtained : 1. The change of the amounts of mandibular lateral movement and maximum opening velocity were statistically different between male and female (p<0.05), but the others were not. 2. According to the method of operation, there was no difference in the change of the mandibular movements between the group of SSRO and SSRO plus LeFort I osteotomy (p>0.05). 3. According to the amounts of mandibular movement, the recovery of left lateral movement of the group of $6{\sim}10mm$ was better than the other groups (p<0.05). 4. In the frontal pattern of the opening and closing of the mandible, the complex deflected type (F5), simple deflected type (F4), complex deviated type (F3), simple deviated type (F2), straight type (F1) were obtained in order at the time of preoperative, simple deflected type, simple deviated type, complex deviated type, straight type, complex deflected type in order at the time of 1 month after surgery, and the result at the time of 6 months after surgery was the same with that of the time of preoperative. In the sagittal pattern, non-coincident type (S2) was predominant at the time of preoperative, and coincident type (S1) was predominant at the time of 1 month after surgery. After 6 months, the result was also the same with that of the preoperative in sagittal pattern. 5. There was not a statistical difference in the change of the mandibular movement between group of presence of the preoperative TMJ symptoms and non-presence group (p>0.05). 6. There was not a statistical difference in the change of the mandibular movement between repositioning device applied group and non-applied group (p>0.05). 7. Sixty three percents of the patients who had preoperative TMJ symptoms were improved after surgery and preoperative TMJ symptoms were more improved after operation in the repositioning device non-applied group statistically (p<0.05).

• Korean Journal of Organic Agriculture
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• v.16 no.4
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• pp.421-434
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• 2008

This study was carried out to estimate the selection of appropriate forage crops, proper application levels of livestock manure, and carrying capacity per unit area for organic livestock, as influenced by livestock manure application levels compared with chemical fertilizer to corn and sorghum $\times$ sorghum hybrid, in order to produce organic forages by utilizing livestock manure. For both corns and sorghum $\times$ sorghum hybrids, no fertilizer plots had significantly (p<0.05) lower annual dry matter (DM), crude protein (CP) and total digestible nutrients (TDN) yields than those of other plots, whereas the N+P+K plots ranked the highest yields, followed by 150% cattle manure plots and 100% cattle manure plots. Dry matter, CP and TDN yields of cattle manure plots were significantly (p<0.05) higher than those of no fertilizer and P+K plots. In applying cattle manure, the yields of cattle slurry plots tended to be a little higher than those of composted cattle manure plots. Assuming that corns and sorghum $\times$ sorghum hybrids produced from this trial were fed at 70% level to 450kg of Hanwoo heifer with 400g of average daily gain, livestock carrying capacity (head/year/ha) ranked the highest in N+P+K plots of the case of corns (mean 6.7 heads), followed by 150% cattle slurry plots (mean 5.6 heads), 150% composted cattle manure plots (mean 4.8 heads), 100% cattle slurry plots (mean 4.4 heads), 100% composted cattle manure plots (mean 4.3 heads), P+K plots (mean 4.1 heads), and no fertilizer plots (mean 3.1 heads). Meanwhile, in case of sorghum $\times$ sorghum hybrids, N+P+K plots (mean 5.7 heads) ranked the highest carrying capacity, followed by $100{\sim}150%$ cattle slurry plots (mean $4.8{\sim}5.2$ heads), 150% composted cattle manure plots (mean 4.7 heads), 100 % composted cattle manure plots (mean 4.3 heads), P+K plots (mean 3.8 heads), and no fertilizer plots (mean 3.4 heads). The results indicated that replacing chemical fertilizer by livestock manure application to cultivation soil for forage crops could enhance not only DM and TDN yields, but also organic stock carrying capacity. In conclusion, it was conceived that organic forage production by reutilizing livestock manure might contribute to reduced environmental pollution and the production of environment friendly agricultural products through resources recycling.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.1-10
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• 2013

RFID(Radio Frequency Identification) system is non-contact identification technology. A basic RFID system consists of a reader, and a set of tags. RFID tags can be divided into active and passive tags. Active tags with power source allows their own operation execution and passive tags are small and low-cost. So passive tags are more suitable for distribution industry than active tags. A reader processes the information receiving from tags. RFID system achieves a fast identification of multiple tags using radio frequency. RFID systems has been applied into a variety of fields such as distribution, logistics, transportation, inventory management, access control, finance and etc. To encourage the introduction of RFID systems, several problems (price, size, power consumption, security) should be resolved. In this paper, we proposed an algorithm to significantly alleviate the collision problem caused by simultaneous responses of multiple tags. In the RFID systems, in anti-collision schemes, there are three methods: probabilistic, deterministic, and hybrid. In this paper, we introduce ALOHA-based protocol as a probabilistic method, and Tree-based protocol as a deterministic one. In Aloha-based protocols, time is divided into multiple slots. Tags randomly select their own IDs and transmit it. But Aloha-based protocol cannot guarantee that all tags are identified because they are probabilistic methods. In contrast, Tree-based protocols guarantee that a reader identifies all tags within the transmission range of the reader. In Tree-based protocols, a reader sends a query, and tags respond it with their own IDs. When a reader sends a query and two or more tags respond, a collision occurs. Then the reader makes and sends a new query. Frequent collisions make the identification performance degrade. Therefore, to identify tags quickly, it is necessary to reduce collisions efficiently. Each RFID tag has an ID of 96bit EPC(Electronic Product Code). The tags in a company or manufacturer have similar tag IDs with the same prefix. Unnecessary collisions occur while identifying multiple tags using Query Tree protocol. It results in growth of query-responses and idle time, which the identification time significantly increases. To solve this problem, Collision Tree protocol and M-ary Query Tree protocol have been proposed. However, in Collision Tree protocol and Query Tree protocol, only one bit is identified during one query-response. And, when similar tag IDs exist, M-ary Query Tree Protocol generates unnecessary query-responses. In this paper, we propose Adaptive M-ary Query Tree protocol that improves the identification performance using m-bit recognition, collision information of tag IDs, and prediction technique. We compare our proposed scheme with other Tree-based protocols under the same conditions. We show that our proposed scheme outperforms others in terms of identification time and identification efficiency.

• Journal of The Korean Society of Grassland and Forage Science
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• v.33 no.2
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• pp.123-130
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• 2013

This study was conducted to investigate the effects of climate change on the growth characteristics and dry matter yields of silage corn hybrids in fields of forage crops of Hanwoo Experiment Station, National Institute of Animal Science, RDA, from Apr. 2009 to Sep. 2011. Corn hybrids were cultivated in Daegwallyeong of Gangwon Province, at an altitude of 760 m. Corn varieties used in this study consisted of 5 domestic varieties and 5 foreign varieties. Differences of silk days according to years occurred at an average of 5.5 days. The silk periods of domestic varieties occurred from Aug. 8 to 12, while that of overseas varieties was from Aug. 5 to 11. Silk days of domestic varieties occurred approximately 3 to 4 days earlier than those of oversea varieties. Silk days of Kwangpyeongok and P3156 belonging to the early varieties were Aug. 8 and 5, respectively. Kwangpyeongok and P3156 were Aug. 8 and 5, respectively. Pyeonganok and DK729 belonged to late varieties. The mean plant height of corn was approximately 231 cm, while those of Kwangpyeongok and Pyeonganok were 236 cm and 237 cm, respectively. The mean stem diameter and ear height of corn were approximately 23.2 mm and 94 cm, respectively. In the case of stem diameters, those of Cheonganok and 33J56 were 86 cm and 80 cm, respectively, while Gangdaok grew to a greater height (enter height) than other varieties. Dry matter yields of Kwangpyeongok and Pyeonganok were higher than those of other varieties. The mean leaf ratio of corn was 39.3%, while that of domestic varieties increased as compared to foreign varieties. The average DM yield of corn was 16,653 kg/ha, while those of 32P75, P3156, Pyeonganok, P3394 and Kwangpyeongok were 18,901, 17,997, 17,675, 17,194, 17,188 kg/ha, respectively. Total digestible nutrient (TDN) yields of 32P75, P3156, P3394, Pyeonganok and Kwangpyeongok were 13,381, 12,590, 12,532, 12,140 and 12,036 kg/ha, respectively. Corn crude protein (CP), in vitro dry matter digestibility (IVDMD), neutral detergent fiber (NDF), acid detergent fiber (ADF) and TDN were 7.8%, 74.2%, 42.4%, 23.5% and 70.3%, respectively. In the case of nutritive values of corn, there was no significant difference between of corn varieties of domestic and foreign origin.

• Proceedings of the Safety Management and Science Conference
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• 2004.11a
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• pp.355-380
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• 2004

I test the hypothesis that the gradual diffusion of information across asset markets leads to cross-asset return predictability in Korea. Using thirty-six industry portfolios and the broad market index as our test assets, I establish several key results. First, a number of industries such as semiconductor, electronics, metal, and petroleum lead the stock market by up to one month. In contrast, the market, which is widely followed, only leads a few industries. Importantly, an industry's ability to lead the market is correlated with its propensity to forecast various indicators of economic activity such as industrial production growth. Consistent with our hypothesis, these findings indicate that the market reacts with a delay to information in industry returns about its fundamentals because information diffuses only gradually across asset markets. Traditional theories of asset pricing assume that investors have unlimited information-processing capacity. However, this assumption does not hold for many traders, even the most sophisticated ones. Many economists recognize that investors are better characterized as being only boundedly rational(see Shiller(2000), Sims(2201)). Even from casual observation, few traders can pay attention to all sources of information much less understand their impact on the prices of assets that they trade. Indeed, a large literature in psychology documents the extent to which even attention is a precious cognitive resource(see, eg., Kahneman(1973), Nisbett and Ross(1980), Fiske and Taylor(1991)). A number of papers have explored the implications of limited information- processing capacity for asset prices. I will review this literature in Section II. For instance, Merton(1987) develops a static model of multiple stocks in which investors only have information about a limited number of stocks and only trade those that they have information about. Related models of limited market participation include brennan(1975) and Allen and Gale(1994). As a result, stocks that are less recognized by investors have a smaller investor base(neglected stocks) and trade at a greater discount because of limited risk sharing. More recently, Hong and Stein(1999) develop a dynamic model of a single asset in which information gradually diffuses across the investment public and investors are unable to perform the rational expectations trick of extracting information from prices. Hong and Stein(1999). My hypothesis is that the gradual diffusion of information across asset markets leads to cross-asset return predictability. This hypothesis relies on two key assumptions. The first is that valuable information that originates in one asset reaches investors in other markets only with a lag, i.e. news travels slowly across markets. The second assumption is that because of limited information-processing capacity, many (though not necessarily all) investors may not pay attention or be able to extract the information from the asset prices of markets that they do not participate in. These two assumptions taken together leads to cross-asset return predictability. My hypothesis would appear to be a very plausible one for a few reasons. To begin with, as pointed out by Merton(1987) and the subsequent literature on segmented markets and limited market participation, few investors trade all assets. Put another way, limited participation is a pervasive feature of financial markets. Indeed, even among equity money managers, there is specialization along industries such as sector or market timing funds. Some reasons for this limited market participation include tax, regulatory or liquidity constraints. More plausibly, investors have to specialize because they have their hands full trying to understand the markets that they do participate in

• The Journal of Natural Sciences
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• v.4
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• pp.103-142
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• 1991

These studies were carried out to select somatic hybrid using selectable marker genes of Nicotiana glauca transformed by NPTII gene and Solanum tuberosum transformed by T- DNA, and to study characteristics of transformant. The results are summarized as follows. 1. Crown gall tumors and hairy roots were formed on potato tuber disc infected by A. tumefaciens Ach5 and A. rhizogenes ATCC15834. These tumors and roots could be grown on the phytohormone free media. 2. Callus formation from hairy root was prompted on the medium containing 2, 4 D 2mg/I with casein hydrolysate lg/l. 3. The survival ratio of crown gall tumor callus derived from potato increased on the medium containing the activated charcoal 0. 5-2. 0mg/I because of the preventions on the other hand, hairy roots were necrosis on the same medium. 4. Callus derived from hairy root were excellently grown for a short time by suspension culture on liquid medium containing 2, 4-D 2mg/I and casein hydrolysate lg/l. 5. The binary vector pGA643 was mobilized from E. coli MC1000 into wild type Agrobacteriurn tumefaciens Ach5, A. tumefaciens $A_4T$ and disarmed A. tuniefaciens LBA4404 using a triparental mating method with E. ccli HB1O1/pRK2013. Transconjugants were obtained on the minimal media containing tetracycline and kanamycin. pGA643 vectors were confirmed by electrophoresis on 0.7% agarose gel. 6. Kanamycin resistant calli were selected on the media supplemented with 2, 4-D 0.5mg/1 and kanamycin $100\mug$/ml after co- cultivating with tobacco stem explants and A. tumefaciens LBA4404/pGA643, and selected calli propagated on the same medium. 7. The multiple shoots were regenerated from kanamycin resistant calli on the MS medium containing BA 2mg/l. 8. Leaf segments of transformed shoot were able to grow vigorusly on the medium supplemented with high concentration of kanamycin $1000\mug$/ml. 9. Kanamycin resistant shoots were rooting and elongated on medium containing kanamycin $100\mug$/ml, but normal shoot were not. 10. For the production of protoplast from potato calli transformed by T-DNA and mesophyll tissue transformed by NPTII gene, the former was isolated in the enzyme mixture of 2.0% celluase Onozuka R-10, 1.0% dricelase, 1.0% macerozyme. and 0.5M mannitol, the latter was isolated in the enzyme mixture 1.0% Celluase Onozuka R-10, 0.3% macerozyme, and 0.7M mannitol. 11. The optimal concentrationn of mannitol in the enzyme mixture for high protoplast yield was 0.8M at both transformed tobacco mesophyll and potato callus. The viabilities of protoplast were shown above 90%, respectively. 12. Both tobacco mesophyll and potato callus protoplasts were fused by using PEG solution. Cell walls were regenerated on hormone free media supplemented with kanamycin after 5 days, and colonies were observed after 4 weeks culture.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.2
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• pp.110-118
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• 2021

This study was conducted to investigate the effects of species and varieties of summer forage crops on growth characteristics and productivity in Sihwa reclaimed land. The summer forage crops used in the trial were silage corn, sorghum×sudangrass hybrid(SSH), and proso millet. For each forage species, Gwangpyeongok(GPO), P15453, P1952 and P2088 were used for silage corn, and 877F, Green star, Honey chew, and Turbo gold cultivars were used for SSH. For proso millet, Ibaekchal, Geumsilchal and Manhongchal developed by the National Institute of Crop Science were used. Silage corn and SSH were sown on May 21, 2019 and proso millet on June 4, and harvested on September 2. There was no significant difference in plant and ear height of silage corn among varieties. P1543 was the highest and P2088 was the lowest in yield of silage corn, but there was no significant difference among treatments. Among the SSH, the plant height of 877F was the highest and Turbo gold variety had the smallest (p<0.05). As for the dry matter(DM) yields, 877F had the highest at 3,862 kg/ha and Green star had the lowest at 2,669 kg/ha (p<0.05). The fresh matter yield of proso millet was 15,778 kg/ha, which was higher than that of corn or SSH, The average dry matter yield was 4,780 kg/ha, and Ibaekchal variety had the highest DM yield compared to other varieties (p<0.05). P2088 had the highest TDN content and GPO was the lowest (p<0.05). As for the SSH, the TDN content of Green star and Honey chew varieties was significantly higher, and the RFV value was the lowest in Turbo gold. The average crude protein content of proso millet was 7.03%, and the highest TDN and RFV values were 64.36% and 106 in Geumsilchal. In the experiment of the germination rate of summer forage crops according to salt concentration, silage corn showed a germination rate of 83.1% even at 0.4% salinity. In particular, P2088 and P1921 varieties had more than 80% germination rate even at 0.6% salt concentration. As for the SSH, the germination rate of 877F was 93.3% even at 0.8% salinity, and 88.3% with Honey chew, indicating higher resistance to salt concentration compared to other varieties. Proso millet showed a high germination rate of 84.0 to 88.7% even at a salt concentration of 0.6%. Considering the above results, proso millet was recommended as the most suitable forage crop species in the Sihwa reclaimed land with high salt concentration, and the Ibaekchal variety is recommended as a suitable forage crop due to its high yield.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.23-46
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• 2021

Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.26 no.1
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• pp.56-68
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• 1981

A maize line was selected in 1979 among 1000 Korean local maize lines collected in 1977. The selected maize line was characterized by having three to four tillers and eight to 10 ears on each individual plant. The line was assumed to have a great potential as a silage crop. The investigation was conducted as one of the serial studies on the Korean maize collected lines to provide basic information on the genetic variabilities of the multi-eared and tillered (MET) line and on other agronomic characters, prior to use the line as material for future breeding works for silage crop. The MET line and Suwon #19, single cross hybrid, as check variety were planted on May 1, 15 and 30, in three different levels of plant populations. The results obtained were summarized as follows: 1. The genetic variabilities of multi-ear and tillering habits were greater than environmental variabilities. 2. Total dry leaf weight of individual plant of MET line was also significantly higher than that of Suwon #19. 3. The mean number of tillers and ears bearing on the individual plant of MET line varied greatly with plant densities. The number of tillers and ears was on the average 2.9 and 7.0, respectively, when planted in 60cm. by 60cm. 4. The total dry matter and dried stem weight of the individual plant on MET line were comparable to those of Suwon #19. 5. The kernel weight from the individual plant of MET line was 5 to 40% less than that of Suwon #19, depending upon the plant densities. 6. The Kernel to stover ratio was higher for Suwon #19 than for the MET line. (41% to 35%). 7. The MET line had shown first tiller two weeks after planted on May 1. The second and third tillers appeared three to five days after the appearance of the first tiller. 8. The MET line was very specific in tillering habits. All the tillers were borne on the first few nodes of main stem below the soil surface. 9. The tillering habits of MET line were vigorous in the early part of the growing season, but less vigorous in the later part of the growing season. The number of efficient tillers bearing useable ears, was around two to three, when planted in 60cm. by 60cm. 10. The difference of plant height between main stem and first few tillers was around 10cm. 11. The ear size of MET line was around one-third of the major corn belt hybrids. The shape of ear of MET line was conical, with different diameter. 12. The kernel of the MET line was flinty with small soft starch patches on the endosperm part. 13. The 100 kernel weight was around 15gr., which is about one half of the major high yielding hybrids. 14. The ear height of MET line was comparatively higher than that of Suwon #19. 15. Significantly high and positive phenotypic correlation coefficients were obtained among major plant characters. 16. The growth rate of MET line was slower than that of Suwon #19. 17. MET line and Suwon #19 were both heavily infected with black streaked mosaic virus.