• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.139-153
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• 2024

The importance of sustainable growth and cost reduction has increased globally, leading to the expansion of outsourcing by companies. Additionally, the spread of the platform economy has brought changes in the way we work, and the online outsourcing market, where tasks are mediated through platforms, is growing. Academically, while research on general outsourcing is actively conducted, studies on online outsourcing are relatively insufficient compared to its actual utilization. This study aims to analyze the factors and performance factors of online outsourcing utilization by startups, to identify the effects and concerns of using online outsourcing from multiple perspectives, and to suggest the roles of various stakeholders for effective utilization and industry development. For the research, a survey was conducted with 281 employees of startups who have experience in using online outsourcing, and the main findings are as follows. First, the enhancement of efficiency, profitability, and innovation through the use of online outsourcing positively affects organizational commitment and job satisfaction of startup members. Especially, the improvement of efficiency due to the use of online outsourcing has a significant effect on enhancing job satisfaction. Second, concerns about the burden of online outsourcing fees or uncertain outcomes negatively affect organizational commitment and job satisfaction. Third, there are perceptual differences in the motivations and performance regarding the utilization of online outsourcing depending on the job position. Practitioners perceive that the use of online outsourcing increases organizational commitment, whereas managers have relatively higher concerns about the uncertainty of outsourced task outcomes and information security. Through this study, the possibility that human resource shortages and employee management issues in startups can be improved through online outsourcing was confirmed. By verifying the influence of various factors of online outsourcing utilization, this study also provides meaningful implications for establishing business strategies for online outsourcing intermediary platform companies and for formulating startup support policies by government and other startup support organizations.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.

• Korean Journal of Agricultural Science
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• v.4 no.2
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• pp.254-282
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• 1977

To obtain information on the inheritance of the quantitative characters related with the vegetative and reproductive growth of rice, the $F_1$ seeds were obtained in 1974 from the all possible combinations of the diallel crosses among five leading rice varieties : Nongbaek, Tongil, Palgueng, Mangyeong and Gimmaze. The $F_1$'s including reciprocals and parents were grown under the standard cultivation method at Chungnam Provincial Office of Rural Development in 1975. The arrangement of experimental plots was randomized block design with 3 replications and 12 characters were used for the analysis. Analytical procedure for genetic components was followed the Griffing's and Hayman's methods and the results obtained are summarized as follows. 1. In all $F_1$'s of Tongil crosses, the longer duration to heading was due to dominant effect of Tongil and each $F_1$ showed high heterosis in delaying the heading time. It was assumed that non-allelic gene action besides dominant gene effect might be involed in days to heading character. However, in all $F_1$'s from the crosses among parents excluding Tongil the shorter duration was due to dominant gene action and the degree of dominance was partial, since dominance effects were not greater than the additive effect. The non-allelic gene interaction was not significant. Considering the results mentioned above, it was regarded that there were two kinds of Significantly different genetic systems in the days to heading. 2. The rate of heterosis was significantly different depending upon the parents used in the crosses. For instance, the $F_1$'s from Togil cross showed high rate of heterosis in longer culm. Compared to short culm, longer culm was due to recesive gene action and short culm was due to recesive gene action. The dominant gene effect was greater than the additive gene effect in culm length. The narrow sense of heretability was very low and the maternal effects as well as reciprocal effects were significantly recognized. 3. The lenght of the of the uppermost internode of each $F_1$ plant was a little lorger than these of respective parental means or same as those of parents having long internodes, indicating partial dominance in the direction of lengthening the uppermost internodes. The additive gene effects on the uppermost internode was greater than the dominance gene effect. The narrow as well as broad sense of heritabilities for the character of the uppermost internode were very high. There were significant maternal and reciprocal effect in the uppermost internode. 4. The gene action for the flag leaf angle was rather dominance in a way of getting narrower angle. However, in the Palgueng combinations, heterosis of $F_1$ was observed in both narrow and wide angles of the flag leaf. The dominant effects were greater than the additive effects on the flag leaf angle. There were observed also a great deal of non-allelic gene interacticn on the inheritance of the flag leaf angle. 5. Even though the dominant gene action on the length and width of flag leaf was effective in increasing the length or width of the flag leaf, there were found various degrees of hetercsis depending upon the cross combination. Over-dominant gene effect were observed in the inheritance of length of the flag leaf, while additive gene effects was found in the inheritance of the width of the flag leaf. High degree of heretabilities, either narrow or broad sense, were found in both length and width of the flag leaf. No maternal and reciprocal effect were found in both characters. 6. When Tongil was used as one parent in the cross, the length of panicle of $F_1$'s was remarkedly longer than that of parents. In other cross comination, the length of panicle of $F_1$'s was close to the parental mean values. Rather greater dominent gene effect than additive gene effect was observed in the inheritance of panicle length and the dominant gene was effective in increasing the panicle length. 7. The effect of dominant genes was effective in increasing the number of panicles. The degree of heterosis was largely dependent on the cross combination. The effect of dominant gene in the inheritance of panicle number was a little greater than that of additive genes, and the inheritance of panicle number was assumed to be due to complete dominant gene effects. Significantly high maternal and reciprocal effects were found in the character studied. 8. There were minus and plus values of heterosis in the kernel number per panicle depending upon the cross combination. The mean dominant effect was effective in increasing the kernel number per panicle, the degree of dominant effect varied with cross combination. The dominant gene effect and non-allelic gene interaction were found in the inheritance of the kernel number per panicle. 9. Genetic studies were impossible for the maturing ratio, because of environmental effects such as hazards delaying heads. The dominant gene effect was responsible for improving the maturing ratio in all the cross combinations excluding Tongil 10. The heavier 1000 grain weight was due to dominant gene effects. The additive gene effects were greater than the dominant gene effect in the 1000 grain weight, indicating that partial dominance was responsible for increasing the 1000 grain weight. The heritabilites, either narrow or broad sense of, were high for the grain weight and maternal or reciprocal effects were not recognized. 11. When Tongil was used as parent, the straw weight was showing high heterosis in the direction of increasing the weight. But in other crosses, the straw weight of $F_1$'s was lower than those of parental mean values. The direction of dominant gene effect was plus or minus depending upon the cross combinations. The degree of dominance was also depending on the cross combination, and apparently high nonallelic gene interaction was observed.

• Clinical and Experimental Reproductive Medicine
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• v.2 no.2
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• pp.27-36
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• 1975

The success of the family planning program in Korea is reflected in the decrease in the growth rate from 3.0% in 1962 to 2.0% in 1971, and in the decrease in the fertility rate from 43/1,000 in 1960 to 29/1,000 in 1970. However, it would be erroneous to attribute these reductions entirely to the family planning program. Other socio-economic factors, such as the increasing age at marriage and the increasing use of induced abortions, definitely had an impact on the lowered growth and fertility rate. Despite the relative success of the program to data in meeting its goals, there is no room for complacency. Meeting the goal of a further reduction in the population growth rate to 1.3% by 1981 is a much more difficult task than any one faced in the past. Not only must fertility be lowered further, but the size of the target population itself will expand tremendously in the late seventies; due to the post-war baby boom of the 1950's reaching reproductive ages. Furthermore, it is doubtful that the age at marriage will continue to rise as in the past or that the incidence of induced abortion will continue to increase. Consequently, future reductions in fertility will be more dependent on the performance of the national family planning program, with less assistance from these non-program factors. This paper will describe various approaches to help to the solution of these current problems. 1. PRACTICE RATE IN FAMILY PLANNING In 1973, the attitude (approval) and knowledge rates were quite high; 94% and 98% respectively. But a large gap exists between that and the actual practice rate, which is only 3695. Two factors must be considered in attempting to close the KAP-gap. The first is to change social norms, which still favor a larger family, increasing the practice rate cannot be done very quickly. The second point to consider is that the family planning program has not yet reached all the eligible women. A 1973 study determineded that a large portion, 3096 in fact, of all eligible women do not want more children, but are not practicing family planning. Thus, future efforts to help close the KAP-gap must focus attention and services on this important large group of potential acceptors. 2. CONTINUATION RATES Dissatisfaction with the loop and pill has resulted in high discontinuation rates. For example, a 1973 survey revealed that within the first six months initial loop acceptance. nearly 50% were dropouts, and that within the first four months of inital pill acceptance. nearly 50% were dropouts. These discontinuation rates have risen over the past few years. The high rate of discontinuance obviously decreases the contraceptive effectiveness. and has resulted in many unwanted births which is directly related to the increase of induced abortions. In the future, the family planning program must emphasize the improved quality of initial and follow-up services. rather than more quantity, in order to insure higher continuation rates and thus more effective contraceptive protection. 3. INDUCED ABORTION As noted earlier. the use of induced abortions has been increase yearly. For example, in 1960, the average number of abortions was 0.6 abortions per women in the 15-44 age range. By 1970. that had increased to 2 abortions per women. In 1966. 13% of all women between 15-44 had experienced at least one abortion. By 1971, that figure jumped to 28%. In 1973 alone, the total number of abortions was 400,000. Besides the ever incre.sing number of induced abortions, another change has that those who use abortions have shifted since 1965 to include- not. only the middle class, but also rural and low-income women. In the future. in response to the demand for abortion services among rural and low-income w~men, the government must provide and support abortion services for these women as a part of the national family planning program. 4. TARGET SYSTIi:M Since 1962, the nationwide target system has been used to set a target for each method, and the target number of acceptors is then apportioned out to various sub-areas according to the number of eligible couples in each area. Because these targets are set without consideration for demographic factors, particular tastes, prejudices, and previous patterns of acceptance in the area, a high discontinuation rate for all methods and a high wastage rate for the oral pill and condom results. In the future. to alleviate these problems of the methodbased target system. an alternative. such as the weighted-credit system, should be adopted on a nation wide basis. In this system. each contraceptive method is. assigned a specific number of points based upon the couple-years of protection (CYP) provided by the method. and no specific targets for each method are given. 5. INCREASE OF STERILIZA.TION TARGET Two special projects. the hospital-based family planning program and the armed forces program, has greatly contributed to the increasing acceptance in female and male sterilization respectively. From January-September 1974, 28,773 sterilizations were performed. During the same time in 1975, 46,894 were performed; a 63% increase. If this trend continues, by the end of 1975. approximately 70,000 sterilizations will have been performed. Sterilization is a much better method than both the loop and pill, in terms of more effective contraceptive protection and the almost zero dropout rate. In the future, the. family planning program should continue to stress the special programs which make more sterilizations possible. In particular, it should seek to add the laparoscope techniques to facilitate female sterilization acceptance rates. 6. INCREASE NUMBER OF PRIVATE ACCEPTORS Among the current family planning users, approximately 1/3 are in the private sector and thus do not- require government subsidy. The number of private acceptors increases with increasing urbanization and economic growth. To speed this process, the government initiated the special hospital based family planning program which is utilized mostly by the private sector. However, in the future, to further hasten the increase of private acceptors, the government should encourage doctors in private practice to provide family planning services, and provide the contraceptive supplies. This way, those do utilize the private medical system will also be able to receive family planning services and pay for it. Another means of increasing the number of private acceptors, IS to greatly expand the commercial outlets for pills and condoms beyond the existing service points of drugstores, hospitals, and health centers. 7. IE&C PROGRAM The current preferred family size is nearly twice as high as needed to achieve a stable poplation. Also, a strong boy preference hinders a small family size as nearly all couples fuel they must have at least one or more sons. The IE&C program must, in the future, strive to emphasize the values of the small family and equality of the sexes. A second problem for the IE&C program to work. with in the: future is the large group of people who approves family planning, want no more children, but do not practice. The IE&C program must work to motivate these people to accept family planning And finally, for those who already practice, an IE&C program in the future must stress continuation of use. The IE&C campaign, to insure highest effectiveness, should be based on a detailed factor analysis of contraceptive discontinuance. In conclusion, Korea faces a serious unfavorable sociodemographic situation- in the future unless the population growth rate can be curtailed. And in the future, the decrease in fertility will depend solely on the family planning program, as the effect of other socio-economic factors has already been maximumally felt. A second serious factor to consider is the increasing number of eligible women due to the 1950's baby boom. Thus, to meet these challenges, the program target must be increased and the program must improve the effectiveness of its current activities and develop new programs.

• KDI Journal of Economic Policy
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• v.12 no.3
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• pp.27-45
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• 1990

Two opposing views prevail regarding the economic impact of rural out-migration on the rural areas of origin. The optimistic neoclassical view argues that rapid rural out-migration is not detrimental to the income and welfare of the rural areas of origin, whereas Lipton (1980) argues the opposite. We developed our own alternative model for rural to urban migration, appropriate for rapidly developing economies such as Korea's. This model, which adopts international trade theories of nontraded goods and Dutch Disease to rural to urban migration issues, argues that rural to urban migration is caused mainly by two factors: first, the unprofitability of farming, and second, the decrease in demand for rural nontraded goods and the increase in demand for urban nontraded goods. The unprofitability of farming is caused by the increase in rural wages, which is induced by increasing urban wages in booming urban manufacturing sectors, and by the fact that the cost increases in farming cannot be shifted to consumers, because farm prices are fixed worldwide and because the income demand elasticity for farm products is very low. The demand for nontraded goods decreases in rural and increases in urban areas because population density and income in urban areas increase sharply, while those in rural areas decrease sharply, due to rapid rural to urban migration. Given that the market structure for nontraded goods-namely, service sectors including educational and health facilities-is mostly in monopolistically competitive, and that the demand for nontraded goods comes only from local sources, the urban service sector enjoys economies of scale, and can thus offer services at cheaper prices and in greater variety, whereas the rural service sector cannot enjoy the advantages offered by scale economies. Our view concerning the economic impact of rural to urban migration on rural areas of origin agrees with Lipton's pessimistic view that rural out-migration is detrimental to the income and welfare of rural areas. However, our reasons for the reduction of rural income are different from those in Lipton's model. Lipton argued that rural income and welfare deteriorate mainly because of a shortage of human capital, younger workers and talent resulting from selective rural out-migration. Instead, we believe that rural income declines, first, because a rapid rural-urban migration creates a further shortage of farm labor supplies and increases rural wages, and thus reduces further the profitability of farming and, second, because a rapid rural-urban migration causes a further decline of the rural service sectors. Empirical tests of our major hypotheses using Korean census data from 1966, 1970, 1975, 1980 and 1985 support our own model much more than the neoclassical or Lipton's models. A kun (county) with a large out-migration had a smaller proportion of younger working aged people in the population, and a smaller proportion of highly educated workers. But the productivity of farm workers, measured in terms of fall crops (rice) purchased by the government per farmer or per hectare of irrigated land, did not decline despite the loss of these youths and of human capital. The kun having had a large out-migration had a larger proportion of the population in the farm sector and a smaller proportion in the service sector. The kun having had a large out-migration also had a lower income measured in terms of the proportion of households receiving welfare payments or the amount of provincial taxes paid per household. The lower incomes of these kuns might explain why the kuns that experienced a large out-migration had difficulty in mechanizing farming. Our policy suggestions based on the tests of the currently prevailing hypotheses are as follows: 1) The main cause of farming difficulties is not a lack of human capital, but the in­crease in production costs due to rural wage increases combined with depressed farm output prices. Therefore, a more effective way of helping farm economies is by increasing farm output prices. However, we are not sure whether an increase in farm output prices is desirable in terms of efficiency. 2) It might be worthwhile to attempt to increase the size of farmland holdings per farm household so that the mechanization of farming can be achieved more easily. 3) A kun with large out-migration suffers a deterioration in income and welfare. Therefore, the government should provide a form of subsidization similar to the adjustment assistance provided for international trade. This assistance should not be related to the level of farm output. Otherwise, there is a possibility that we might encourage farm production which would not be profitable in the absence of subsidies. 4) Government intervention in agricultural research and its dissemination, and large-scale social overhead projects in rural areas, carried out by the Korean government, might be desirable from both efficiency and equity points of view. Government interventions in research are justified because of the problems associated with the appropriation of knowledge, and government actions on large-scale projects are justified because they required collective action.

• Journal of Korean Society of Forest Science
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• v.77 no.4
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• pp.429-444
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• 1988

Considering the recent trent toward the development of multiple-use of forest trees, investigations for comprehensive information on these young stands of Hinoki cypress are necessary for rational forest management. From this point of view, 83 sample trees were selected and cut down from 23-ear old stands of Hinoki cypress at Changsung-gun, Chonnam-do. Various stem growth factors of felled trees were measured and canonical correlaton analysis, principal component analysis and factor analysis were applied to investigate the stem growth characteristics, relationships among stem growth factors, and to get potential information and comprehensive information. The results are as follows ; Canonical correlation coefficient between stem volume and quality growth factor was 0.9877. Coefficient of canonical variates showed that DBH among diameter growth factors and height among height growth factors had important effects on stem volume. From the analysis of relationship between stem-volume and canonical variates, which were linearly combined DBH with height as one set, DBH had greater influence on volume growth than height. The 1st-2nd principal components here adopted to fit the effective value of 85% from the pincipal component analysis for 12 stem growth factors. The result showed that the 1st-2nd principal component had cumulative contribution rate of 88.10%. The 1st and the 2nd principal components were interpreted as "size factor" and "shape factor", respectively. From summed proportion of the efficient principal component fur each variate, information of variates except crown diameter, clear length and form height explained more than 87%. Two common factors were set by the eigen value obtained from SMC (squared multiple correlation) of diagonal elements of canonical matrix. There were 2 latent factors, $f_1$ and $f_2$. The former way interpreted as nature of diameter growth system. In inherent phenomenon of 12 growth factor, communalities except clear length and crown diameter had great explanatory poorer of 78.62-98.30%. Eighty three sample trees could he classified into 5 stem types as follows ; medium type within a radius of ${\pm}1$ standard deviation of factor scores, uniformity type in diameter and height growth in the 1st quadrant, slim type in the 2nd quadrant, dwarfish type in the 3rd quadrant, and fall-holed type in the 4 th quadrant.

• Korean Journal of Weed Science
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• v.31 no.2
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• pp.119-133
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• 2011

Sulfonylurea (SU)-resistant weeds include seven annual weeds such as Monochoria vaginalis, Scirpus juncoides and Cyperus difformis, etc., and three perennial weeds of Scirpus planiculmis, Sagittaria pigmaea and Eleocharis acicularis as of 2010 since identification Monochoria korsakowii in the reclaimed rice field in 1998. The Echinochloa oryzoides resistant to acetyl CoA carboxylase (ACCase) and acetolactate synthase (ALS) inhibitors has been confirmed in wet-direct seeding rice field of the southern province, Korea in 2009. In the beginning of occurrence of SU-resistant weeds the M. vaginalis, S. juncoides and C. difformis were rapidly and individually spreaded in different fields, however, theses resistant weeds have been occurring simultaneously in the same filed as time goes by. The resistant biotype by weed species demonstrated about 10- to 1,000-fold resistance, base on $GR_{50}$ (50% growth reduction) values of the SU herbicides tested. And the resistant biotype of E. oryzoides to cyhalofop-butyl, pyriminobac-methyl, and penoxsulam was about 14, 8, and 11 times more resistant than the susceptible biotype base on $GR_{50}$ values. In history of paddy herbicides in Korea, the introduction of SU herbicides including besulfuron-metyl and pyrazosulfuron-ethyl that control many troublesome weeds at low use rates and provide excellent crop safety gave farmers and many workers for herbicide business refreshing jolt. The products and applied area of SU-included herbicides have been rapidly increased, and have accounted for about 69% and 96%, respectively, in Korea. The top ten herbicides by applied area were composed of all SU-included herbicides by 2003. The concentrated and successive treatment of ACCase and ALS inhibitors for control of barnyardgrass in direct-seeded rice led up to the resistance of E. oryzoides. Also, SU-herbicides like pyrazosulfuron-ethyl and imazosulfuron which are effective to barnyardgrass can be bound up with the resistance of E. oryzoides. The ALS activity isolated from the resistant biotype of M. korsakowii to SU-herbicides tested was less sensitive than that of susceptible biotype. The concentration of herbicide required for 50% inhibition of ALS activity ($I_{50}$) of the SU-resistant M. korsakowii was 14- to 76-fold higher as compared to the susceptible biotype. No differences were observed in the rates of [$^{14}C$]bensulfuron uptake and translocation. ALS genes from M. vaginalis resistant and susceptible biotypes against SU-herbicides revealed a single amino acid substitution of proline (CCT), at 197th position based on the M. korsakowii ALS sequence numbering, to serin (TCT) in conserved domain A of the gene. Carfentrazone-ethyl and pyrazolate were used mainly to control SU-resistant M. vaginalis by 2006, the early period, in Korea. However, the alternative herbicides such as benzobicyclone, to be possible to control simultaneously the several resistant weeds, have been developing and using broadly because the several resistant weeds have been occurring simultaneously in the same filed. The top ten herbicides by applied area in Korea have been occupied by products of 3-way mixture type including herbicides with alternative mode of action for the herbicide resistant weeds. Mefenacet, fentrazamide and cafenstrole had excellent controlling effects on the ACCase and ALS inhibitors resistant when they were applied within 2 leaf stage.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.93-112
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• 2015

Depending on the change in consumer's consumption pattern, existing retail shop has evolved in hypermarket or convenience store offering grocery and daily products mostly. Therefore, it is important to maintain the inventory levels and proper product configuration for effectively utilize the limited space in the retail store and increasing sales. Accordingly, this study proposed proper product configuration and inventory level strategy based on RFM(Recency, Frequency, Monetary) model and SOM(self-organizing map) for manage the retail shop effectively. RFM model is analytic model to analyze customer behaviors based on the past customer's buying activities. And it can differentiates important customers from large data by three variables. R represents recency, which refers to the last purchase of commodities. The latest consuming customer has bigger R. F represents frequency, which refers to the number of transactions in a particular period and M represents monetary, which refers to consumption money amount in a particular period. Thus, RFM method has been known to be a very effective model for customer segmentation. In this study, using a normalized value of the RFM variables, SOM cluster analysis was performed. SOM is regarded as one of the most distinguished artificial neural network models in the unsupervised learning tool space. It is a popular tool for clustering and visualization of high dimensional data in such a way that similar items are grouped spatially close to one another. In particular, it has been successfully applied in various technical fields for finding patterns. In our research, the procedure tries to find sales patterns by analyzing product sales records with Recency, Frequency and Monetary values. And to suggest a business strategy, we conduct the decision tree based on SOM results. To validate the proposed procedure in this study, we adopted the M-mart data collected between 2014.01.01~2014.12.31. Each product get the value of R, F, M, and they are clustered by 9 using SOM. And we also performed three tests using the weekday data, weekend data, whole data in order to analyze the sales pattern change. In order to propose the strategy of each cluster, we examine the criteria of product clustering. The clusters through the SOM can be explained by the characteristics of these clusters of decision trees. As a result, we can suggest the inventory management strategy of each 9 clusters through the suggested procedures of the study. The highest of all three value(R, F, M) cluster's products need to have high level of the inventory as well as to be disposed in a place where it can be increasing customer's path. In contrast, the lowest of all three value(R, F, M) cluster's products need to have low level of inventory as well as to be disposed in a place where visibility is low. The highest R value cluster's products is usually new releases products, and need to be placed on the front of the store. And, manager should decrease inventory levels gradually in the highest F value cluster's products purchased in the past. Because, we assume that cluster has lower R value and the M value than the average value of good. And it can be deduced that product are sold poorly in recent days and total sales also will be lower than the frequency. The procedure presented in this study is expected to contribute to raising the profitability of the retail store. The paper is organized as follows. The second chapter briefly reviews the literature related to this study. The third chapter suggests procedures for research proposals, and the fourth chapter applied suggested procedure using the actual product sales data. Finally, the fifth chapter described the conclusion of the study and further research.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.1-19
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• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.