• Tuberculosis and Respiratory Diseases
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• v.54 no.5
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• pp.551-562
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• 2003

Background : NF-${\kappa}B$ is a characteristic transcriptional factor which has been shown to regulate production of acute inflammatory mediators and to be involved in the pathogenesis of many inflammatory lung diseases. There has been some evidence that PI3K/Akt pathway could activate NF-${\kappa}B$ in human cell lines. However, the effect of PI3K/Akt pathway on the activation of NF-${\kappa}B$ varied depending on the cell lines used in the experiments. In this study we evaluated the effect of PI3K/Akt pathway on the activation of NF-${\kappa}B$ in human respiratory epithelial cell lines. Methods : BEAS-2B, A549 and NCI-H157 cell lines were used in this experiment. To evaluate the activation of Akt activation and I${\kappa}B$ degradation, cells were analysed by western blot assay using phospho-specific Akt Ab and $I{\kappa}B$ Ab. To block PI3K/Akt pathway, cells were pretreated with wortmannin or LY294002 and transfected with dominant negative Akt (DN-Akt). For IKK activity, immune complex kinase assay was performed. To evaluate the DNA binding affinity and transcriptional activity of NF-${\kappa}B$, electrophoretic mobility shift assay (EMSA) and luciferase assay were performed, respectively. Results : In BEAS-2B, A549 and NCI-H157 cell lines, Akt was activated by TNF-$\alpha$ and insulin. Activation of Akt by insulin did not induce $I{\kappa}B{\alpha}$ degradation. Blocking of PI3K/Akt pathway via wortmannin/LY294002 or DN-Akt did not inhibit TNF-$\alpha$-induced $I{\kappa}B{\alpha}$ degradation or IKK activation. Inhibition of PI3K/Akt did not affect TNF-$\alpha$-induced NF-${\kappa}B$ activation. Overexpression of DN-Akt did not block TNF-$\alpha$-induced transcriptional activation of NF-${\kappa}B$, but wortmannin enhanced TNF-$\alpha$-induced in NF-${\kappa}B$ transcriptional activity. Conclusion : PI3K/Akt was not involved in TNF-$\alpha$-induced $I{\kappa}B{\alpha}$ degradation or transcriptional activity of NF-${\kappa}B$ in human respiratory epithelial cell lines.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.45-67
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• 2017

According to the Internet Usage Research performed in 2016, the number of internet users and the internet usage have been increasing. Smartphone, compared to the computer, is taking a more dominant role as an internet access device. As the number of smart devices have been increasing, some views that the demand on high-speed internet will decrease; however, Despite the increase in smart devices, the high-speed Internet market is expected to slightly increase for a while due to the speedup of Giga Internet and the growth of the IoT market. As the broadband Internet market saturates, telecom operators are over-competing to win new customers, but if they know the cause of customer exit, it is expected to reduce marketing costs by more effective marketing. In this study, we analyzed the relationship between the cancellation rates of telecommunication products and the factors affecting them by combining the data of 3 cities, Anyang, Gunpo, and Uiwang owned by a telecommunication company with the regional data from KOSIS(Korean Statistical Information Service). Especially, we focused on the assumption that the neighboring areas affect the distribution of the cancellation rates by coupling type, so we conducted spatial cluster analysis on the 3 types of cancellation rates of each region using the spatial analysis tool, SatScan, and analyzed the various relationships between the cancellation rates and the regional data. In the analysis phase, we first summarized the characteristics of the clusters derived by combining spatial information and the cancellation data. Next, based on the results of the cluster analysis, Variance analysis, Correlation analysis, and regression analysis were used to analyze the relationship between the cancellation rates data and regional data. Based on the results of analysis, we proposed appropriate marketing methods according to the region. Unlike previous studies on regional characteristics analysis, In this study has academic differentiation in that it performs clustering based on spatial information so that the regions with similar cancellation types on adjacent regions. In addition, there have been few studies considering the regional characteristics in the previous study on the determinants of subscription to high-speed Internet services, In this study, we tried to analyze the relationship between the clusters and the regional characteristics data, assuming that there are different factors depending on the region. In this study, we tried to get more efficient marketing method considering the characteristics of each region in the new subscription and customer management in high-speed internet. As a result of analysis of variance, it was confirmed that there were significant differences in regional characteristics among the clusters, Correlation analysis shows that there is a stronger correlation the clusters than all region. and Regression analysis was used to analyze the relationship between the cancellation rate and the regional characteristics. As a result, we found that there is a difference in the cancellation rate depending on the regional characteristics, and it is possible to target differentiated marketing each region. As the biggest limitation of this study and it was difficult to obtain enough data to carry out the analyze. In particular, it is difficult to find the variables that represent the regional characteristics in the Dong unit. In other words, most of the data was disclosed to the city rather than the Dong unit, so it was limited to analyze it in detail. The data such as income, card usage information and telecommunications company policies or characteristics that could affect its cause are not available at that time. The most urgent part for a more sophisticated analysis is to obtain the Dong unit data for the regional characteristics. Direction of the next studies be target marketing based on the results. It is also meaningful to analyze the effect of marketing by comparing and analyzing the difference of results before and after target marketing. It is also effective to use clusters based on new subscription data as well as cancellation data.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.51-69
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• 2020

Now, it is a stylized fact that a small number of technology firms such as Apple, Alphabet, Microsoft, Amazon, Facebook and a few others have become larger and dominant players in an industry. Coupled with the rise of these leading firms, we have also observed that a large number of young firms have become an acquisition target in their early IPO stages. This indeed results in a sharp decline in the number of new entries in public exchanges although a series of policy reforms have been promulgated to foster competition through an increase in new entries. Given the observed industry trend in recent decades, a number of studies have reported increased concentration in most developed countries. However, it is less understood as to what caused an increase in industry concentration. In this paper, we uncover the mechanisms by which industries have become concentrated over the last decades by tracing the changes in industry concentration associated with a firm's status change in its early IPO stages. To this end, we put emphasis on the case in which firms are acquired shortly after they went public. Especially, with the transition to digital-based economies, it is imperative for incumbent firms to adapt and keep pace with new ICT and related intelligent systems. For instance, after the acquisition of a young firm equipped with AI-based solutions, an incumbent firm may better respond to a change in customer taste and preference by integrating acquired AI solutions and analytics skills into multiple business processes. Accordingly, it is not unusual for young ICT firms become an attractive acquisition target. To examine the role of M&As involved with young firms in reshaping the level of industry concentration, we identify a firm's status in early post-IPO stages over the sample periods spanning from 1990 to 2016 as follows: i) being delisted, ii) being standalone firms and iii) being acquired. According to our analysis, firms that have conducted IPO since 2000s have been acquired by incumbent firms at a relatively quicker time than those that did IPO in previous generations. We also show a greater acquisition rate for IPO firms in the ICT sector compared with their counterparts in other sectors. Our results based on multinomial logit models suggest that a large number of IPO firms have been acquired in their early post-IPO lives despite their financial soundness. Specifically, we show that IPO firms are likely to be acquired rather than be delisted due to financial distress in early IPO stages when they are more profitable, more mature or less leveraged. For those IPO firms with venture capital backup have also become an acquisition target more frequently. As a larger number of firms are acquired shortly after their IPO, our results show increased concentration. While providing limited evidence on the impact of large incumbent firms in explaining the change in industry concentration, our results show that the large firms' effect on industry concentration are pronounced in the ICT sector. This result possibly captures the current trend that a few tech giants such as Alphabet, Apple and Facebook continue to increase their market share. In addition, compared with the acquisitions of non-ICT firms, the concentration impact of IPO firms in early stages becomes larger when ICT firms are acquired as a target. Our study makes new contributions. To our best knowledge, this is one of a few studies that link a firm's post-IPO status to associated changes in industry concentration. Although some studies have addressed concentration issues, their primary focus was on market power or proprietary software. Contrast to earlier studies, we are able to uncover the mechanism by which industries have become concentrated by placing emphasis on M&As involving young IPO firms. Interestingly, the concentration impact of IPO firm acquisitions are magnified when a large incumbent firms are involved as an acquirer. This leads us to infer the underlying reasons as to why industries have become more concentrated with a favor of large firms in recent decades. Overall, our study sheds new light on the literature by providing a plausible explanation as to why industries have become concentrated.

• Korean Journal of Soil Science and Fertilizer
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• v.39 no.5
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• pp.321-327
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• 2006

In Korea, there is a growing competitive for water resources between industrial, domestic and agricultural consumer, and the environment as many other OECD countries. The demand on water use is also affecting aquatic ecosystems particularly where withdrawals are in excess of minimum environmental needs for rivers, lakes and wetland habits. OECD developed three indicators related to water use by the agriculture in above contexts : the first is a water use intensity indicator, which is expressed as the quantity or share of agricultural water use in total national water utilization; the second is a water stress indicator, which is expressed as the proportion of rivers (in length) subject to diversion or regulation for irrigation without reserving a minimum of limiting reference flow; and the third is a water use efficiency indicator designated as the technical and the economic efficiency. These indicators have different meanings in the aspect of water resource conservation and sustainable water use. So, it will be more significant that the indicators should reflect the intrinsic meanings of them. The problem is that the aspect of an overall water flow in the agro-ecosystem and recycling of water use not considered in the assessment of agricultural water use needed for calculation of these water use indicators. Namely, regional or meteorological characteristics and site-specific farming practices were not considered in the calculation of these indicators. In this paper, we tried to calculate water use indicators suggested in OECD and to modify some other indicators considering our situation because water use pattern and water cycling in Korea where paddy rice farming is dominant in the monsoon region are quite different from those of semi-arid regions. In the calculation of water use intensity, we excluded the amount of water restored through the ground from the total agricultural water use because a large amount of water supplied to the farm was discharged into the stream or the ground water. The resultant water use intensity was 22.9% in 2001. As for water stress indicator, Korea has not defined nor monitored reference levels of minimum flow rate for rivers subject to diversion of water for irrigation. So, we calculated the water stress indicator in a different way from OECD method. The water stress indicator was calculated using data on the degree of water storage in agricultural water reservoirs because 87% of water for irrigation was taken from the agricultural water reservoirs. Water use technical efficiency was calculated as the reverse of the ratio of irrigation water to a standard water requirement of the paddy rice. The efficiency in 2001 was better than in 1990 and 1998. As for the economic efficiency for water use, we think that there are a lot of things to be taken into considerations to make a useful indicator to reflect socio-economic values of agricultural products resulted from the water use. Conclusively, site-specific, regional or meteorogical characteristics as in Korea were not considered in the calculation of water use indicators by methods suggested in OECD(Volume 3, 2001). So, it is needed to develop a new indicators for the indicators to be more widely applicable in the world.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.10 no.3
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• pp.154-163
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• 2005

Irregular discharges of freshwater through the water gates of the Keum River Estuarine Weir, Korea, whose construction had been completed in 1998 with its water gates being operated as late as August 1994, drastically modified the estuarine environment. Sharp decrease of salinity along with the altered concentrations of inorganic nutrients are accompanied with the irregular discharges of freshwater into the estuary under the influence of regular semi-diurnal tidal effect. Field sampling was carried out on the time of high tide at 2 fixed stations(St.1 near the Estuarine Weir and St.2 off Kunsan Ferry Station) every other day for 4 months from mid-February 2004 to investigate into the semi-weekly variation of spring phytoplankton community in relation to the freshwater discharges from Keum River Estuarine Weir. CV(coefficient of variation) of salinity measurements was roughly 2 times greater in St.1 than that in St.2, reflecting extreme salinity variation in St.1 Among inorganic nutrients, concentrations of N-nutrients($NO_3^-,\;NO_2^-$ and $NH_4^+$) were clearly higher in St.1, to imply the more drastic changes of the nutrient concentrations in St.1. than St.2 following the freshwater discharges. As a component of phytoplankton community, diatoms were among the top dominants in terms of species richness as well as biomass. Solitary centric diatom, Cyclotella meneghiniana, and chain-forming centric diatom, Skeletonema costatum, dominated over the phytoplankton community in order for S-6 weeks each (Succession Interval I and II), and the latter succeeded to the former from the time of <$10^{\circ}C$ of water temperature. Cyanobacterial species, Aphanizomenon Posaquae and Phormidium sp., which might be transported into the estuary along with the discharged freshwater, occupied high portion of total biomass during Succession Interval III(mid-April to late-May). During this period, freshwater species exclusively dominated over the phytoplankton community except the low concentrations of the co-occurring 2 estuarine diatoms, Cyclotella meneghiniana and Skeletonema costatum. During the 4th Succession Interval when the water temperature was over $18^{\circ}C$, the diatom, Guinardia delicatula, was predominant for a week with the highest dominance of $75\%$ in discrete samples. To summarize, during all the Succession Intervals other than Succession Interval III characterized by the extreme variation of salinity under cooler water temperature than $18^{\circ}C$, the diatoms were the most important dominants for species succession in spring. If the scale and frequency of the freshwater discharge could have been adjusted properly even during the Succession Interval III, the dominant species would quite possibly be replaced by other estuarine diatom species rather than the two freshwater cyanobacteria, Aphanizomenon flosaquae and Phormidium sp.. The scheme of field sampling every other day for the present study was concluded to be the minimal requirement in order to adequately explore the phytoplankton succession in such estuarine environment as in Keum River Estuary: which is stressed by the unpredictable and unavoidable discharges of freshwater under the regular semi-diurnal tide.

• Journal of the Korean Applied Science and Technology
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• v.13 no.1
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• pp.21-29
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• 1996

Levels of total, neutral and polar lipids from the seeds of eight species of the Cucurbitaceae f Cucurbita moschata, Lufa cylindrica, Citrullus vulgari, Cucumis melo var. makuwa, Cucumis satvus, Lag leucantha. Trichosanthes kirilowii and Momordica charantia, were determinded, and their fatty compositions were also analyzed by gas-liquid chromatography. The results were summarized as foll. Lipid contents of the seeds range from 21.9 to 50.7%, which contained 98% up of neutral lipi the fatty acid compositon of ottal lipids from the seeds of Cucurbita moschata, Lufa cylindrica, Ci vulgari, Cucumis melo var. makuwa, Cucumis sativus and Lagenaria leucantha, linoleic acid is the mos dominant component(56.8${\sim}$84.0%) followed by oleic acid(5.7${\sim}$22.2%) and palmitic acid(6.1${\sim}$1) with a trace amount of ${\alpha}-linolenic$ acid(below 0.6%). On the contrary, the seed oils of Tricho kirilowii and Momordica charantia are characterized by presence of considerable amounts of con trienoic acid such as punicic acid($_{9c.11t.13c-}C_{18:3}$) and ${\alpha}-eleostearic$ acid($_{9c.11t.13c-}C_{18:3}$). For example total lipids of T. kirilowii seeds were mainly composed of linoleic acid(40.5%) and punicic acid(3) in the fatty acid composition, while those of M. charantia seeds predominantly comprised ${\alpha}-eleos$ acid as a main component(66.9%), accompanied by oleic acid(11.7%) and linoleic acid(10.4%). oil ${\beta}-eleostearic$ acid($_{9t.11t.13c-}C_{18:3}$) was checked as a trace. Fatty acid profiles of neutral lipids close resemblance to those of total lipids in all the seed oils, but are different from those of polar In particular, conjugate trienoic acids including punicic acid and ${\alpha}-eleostearic$ acid which are oc as the most abundant component in both neutral lipids of T. kirilowii and M. charantia seed oils, ar ent in a extremely small amount in both polar lipids. The fatty acid distribution in the polar lipid the samples except for T. kirilowii and M. charantia seed oils, showed a tendency of consid increased level of saturated fatty acids(25.0${\sim}$29.4%) compared with that in the neutral lipids(9.9%). The results obtained in this experiment suggest us that the seed oils of the Cucurbitaceae

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.167-194
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• 2019

This research starts from the four basic concepts of incentive incompatibility, limited information, myopia and decision variable which are confronted when making decisions in keyword bidding. In order to make these concept concrete, four framework approaches are designed as follows; Strategic approach for the incentive incompatibility, Statistical approach for the limited information, Alternative optimization for myopia, and New model approach for decision variable. The purpose of this research is to propose the statistical optimization model in constructing the portfolio of Sponsored Search Advertising (SSA) in the Sponsor's perspective through empirical tests which can be used in portfolio decision making. Previous research up to date formulates the CTR estimation model using CPC, Rank, Impression, CVR, etc., individually or collectively as the independent variables. However, many of the variables are not controllable in keyword bidding. Only CPC and Rank can be used as decision variables in the bidding system. Classical SSA model is designed on the basic assumption that the CPC is the decision variable and CTR is the response variable. However, this classical model has so many huddles in the estimation of CTR. The main problem is the uncertainty between CPC and Rank. In keyword bid, CPC is continuously fluctuating even at the same Rank. This uncertainty usually raises questions about the credibility of CTR, along with the practical management problems. Sponsors make decisions in keyword bids under the limited information, and the strategic portfolio approach based on statistical models is necessary. In order to solve the problem in Classical SSA model, the New SSA model frame is designed on the basic assumption that Rank is the decision variable. Rank is proposed as the best decision variable in predicting the CTR in many papers. Further, most of the search engine platforms provide the options and algorithms to make it possible to bid with Rank. Sponsors can participate in the keyword bidding with Rank. Therefore, this paper tries to test the validity of this new SSA model and the applicability to construct the optimal portfolio in keyword bidding. Research process is as follows; In order to perform the optimization analysis in constructing the keyword portfolio under the New SSA model, this study proposes the criteria for categorizing the keywords, selects the representing keywords for each category, shows the non-linearity relationship, screens the scenarios for CTR and CPC estimation, selects the best fit model through Goodness-of-Fit (GOF) test, formulates the optimization models, confirms the Spillover effects, and suggests the modified optimization model reflecting Spillover and some strategic recommendations. Tests of Optimization models using these CTR/CPC estimation models are empirically performed with the objective functions of (1) maximizing CTR (CTR optimization model) and of (2) maximizing expected profit reflecting CVR (namely, CVR optimization model). Both of the CTR and CVR optimization test result show that the suggested SSA model confirms the significant improvements and this model is valid in constructing the keyword portfolio using the CTR/CPC estimation models suggested in this study. However, one critical problem is found in the CVR optimization model. Important keywords are excluded from the keyword portfolio due to the myopia of the immediate low profit at present. In order to solve this problem, Markov Chain analysis is carried out and the concept of Core Transit Keyword (CTK) and Expected Opportunity Profit (EOP) are introduced. The Revised CVR Optimization model is proposed and is tested and shows validity in constructing the portfolio. Strategic guidelines and insights are as follows; Brand keywords are usually dominant in almost every aspects of CTR, CVR, the expected profit, etc. Now, it is found that the Generic keywords are the CTK and have the spillover potentials which might increase consumers awareness and lead them to Brand keyword. That's why the Generic keyword should be focused in the keyword bidding. The contribution of the thesis is to propose the novel SSA model based on Rank as decision variable, to propose to manage the keyword portfolio by categories according to the characteristics of keywords, to propose the statistical modelling and managing based on the Rank in constructing the keyword portfolio, and to perform empirical tests and propose a new strategic guidelines to focus on the CTK and to propose the modified CVR optimization objective function reflecting the spillover effect in stead of the previous expected profit models.

• Trans-
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• v.12
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• pp.51-79
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• 2022

This study investigates the methods for deriving colors which can serve as a reference to users such as designers and or contents creators who search for online images from the web portal sites using specific words for color planning and more. Two experiments were conducted in order to accomplish this. Digital scenery photos within the geographic scope of Korea were downloaded from web portal sites, and those photos were studied to find out what colors were used to describe daytime and nighttime. Machine learning was used as the study methodology to classify colors in daytime and nighttime, and KSCA was used to derive the color frequency of daytime and nighttime photos and to compare and analyze the two results. The results of classifying the colors of daytime and nighttime photos using machine learning show that, when classifying the colors by 51~100%, the area of daytime colors was approximately 2.45 times greater than that of nighttime colors. The colors of the daytime class were distributed by brightness with white as its center, while that of the nighttime class was distributed with black as its center. Colors that accounted for over 70% of the daytime class were 647, those over 70% of the nighttime class were 252, and the rest (31-69%) were 101. The number of colors in the middle area was low, while other colors were classified relatively clearly into day and night. The resulting color distributions in the daytime and nighttime classes were able to provide the borderline color values of the two classes that are classified by brightness. As a result of analyzing the frequency of digital photos using KSCA, colors around yellow were expressed in generally bright daytime photos, while colors around blue value were expressed in dark night photos. For frequency of daytime photos, colors on the upper 40% had low chroma, almost being achromatic. Also, colors that are close to white and black showed the highest frequency, indicating a large difference in brightness. Meanwhile, for colors with frequency from top 5 to 10, yellow green was expressed darkly, and navy blue was expressed brightly, partially composing a complex harmony. When examining the color band, various colors, brightness, and chroma including light blue, achromatic colors, and warm colors were shown, failing to compose a generally harmonious arrangement of colors. For the frequency of nighttime photos, colors in approximately the upper 50% are dark colors with a brightness value of 2 (Munsell signal). In comparison, the brightness of middle frequency (50-80%) is relatively higher (brightness values of 3-4), and the brightness difference of various colors was large in the lower 20%. Colors that are not cool colors could be found intermittently in the lower 8% of frequency. When examining the color band, there was a general harmonious arrangement of colors centered on navy blue. As the results of conducting the experiment using two methods in this study, machine learning could classify colors into two or more classes, and could evaluate how close an image was with certain colors to a certain class. This method cannot be used if an image cannot be classified into a certain class. The result of such color distribution would serve as a reference when determining how close a certain color is to one of the two classes when the color is used as a dominant color in the base or background color of a certain design. Also, when dividing the analyzed images into several classes, even colors that have not been used in the analyzed image can be determined to find out how close they are to a certain class according to the color distribution properties of each class. Nevertheless, the results cannot be used to find out whether a specific color was used in the class and by how much it was used. To investigate such an issue, frequency analysis was conducted using KSCA. The color frequency could be measured within the range of images used in the experiment. The resulting values of color distribution and frequency from this study would serve as references for color planning of digital design regarding natural scenery in the geographic scope of Korea. Also, the two experiments are meaningful attempts for searching the methods for deriving colors that can be a useful reference among numerous images for content creator users of the relevant field.

• Journal of Practical Agriculture & Fisheries Research
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• v.24 no.3
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• pp.15-24
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• 2022

In 2000, a total of 23,794ha of forest was lost due to the East Coast forest fire, and about 70% of the damaged area was concentrated in Samcheok. In 2001, artificial restoration and natural restoration were implemented in the damaged area. This study was conducted to understand the current vegetation structure 21 years after the restoration of forest fire damage in the Samcheok, Gumbong Mountain area. As a result of classifying the vegetation community, it was divided into three communities: Quercus variabilis-Pinus densiflora community, Pinus densiflora-Quercus mongolica community, and Pinus thunbergii community. Quercus variabilis, Pinus densiflora, and Pinus thunbergii planted in the artificial restoration site were found to continue to grow as dominant species in the local vegetation after restoration. As for the species diversity index of the community, the Quercus variabilis-Pinus densiflora community dominated by deciduous broad-leaf trees showed the highest, and the coniferous forest Pinus thunbergii community showed the lowest. Vegetation in areas affected by forest fires is greatly affected by reforestation tree species, and 21 years later, it has shown a tendency to recover to the forest type before forest fire. In order to establish DataBase for effective restoration and to prepare monitoring data, it is necessary to construct data through continuous vegetation survey on the areas affected by forest fires.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.28 no.2
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• pp.216-226
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• 1983

Genetic studies on the $F_2$ generation of a set of half diallel crosses involving six cowpea varieties were conducted. by the randomized block design with three replications to determine combining ability, gene action and the relationships between parents and their $F_2$ hybrids. The 12 agronomic characters namely, days to flowering, days from flowering to maturity, days to maturity, diameter of stem, length of internode, number of branches per plant, length of pod, number of pods per plant, number of grains per pod, number of grains per plant, 100 grain weight and grain weight per plot were observed, and the $F_2$ generation of this diallel set of crosses was analysed for each character according to the method by Jinks and Hayman. The results obtained are summarized as follows: 1. Vr-Wr graphical analyses; The following seven characters, days to flowering, number of branches per plant, length of pod, number of pods per plant, number of grains per plant, 100 grain weight and grain weight per plot appeared to be partially dominant, and over dominance was found for days from flowering to maturity, days to maturity, length of internode and number of grains per pod. But diameter of stem indicated partial dominance near complete dominance. 2. Estimates of genetic variance components; In the degree of dominance,. eight characters, that is, days to flowering, days from flowering to maturity, days to maturity, length of internode, number of pods per plant, number of grains per pod, number of grains per plant and grain weight per plot were expressed larger than 1. And the characters, days from flowering to maturity, number of branches per plant and number of grains per plant as the degree of mean dominance ($H_1$/D) were found to be negative value over other characters. On the other hand, apprent asymmetry of dominance-recessive allele ($H_2$ /$4H_1$) produced comparatively estimates with lower value on days from flowering to maturity, length of internode, number of branches per plant and number of grains per pod. 3. Analyses of combining ability; Mean square value of GCA(general combining ability) appeared to be more important than those of SCA (specific combining ability) for most characters, and among them, grain weight per plot showed the highest mean square value in GCA and SCA. 4. Effect of combining ability; Variety 178 was expressed as the highest GCA effects in five characters (days to flowering days to maturity, number of pods per plant, number of grains per plant and grain weight per plot). SCA effects were differed from parents, characters and crosses, but crosses between TVu 1857 $\times$ TVu 2885 and TVu 2702 $\times$ J78 were shown to be highly with SCA effects on yield.