• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.101-123
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• 2013

Recently due to the advancements of science and information technology, the socio-economic business areas are changing from the industrial economy to a knowledge economy. Furthermore, companies need to do creation of new value through continuous innovation, development of core competencies and technologies, and technological convergence. Therefore, the identification of major trends in technology research and the interdisciplinary knowledge-based prediction of integrated technologies and promising techniques are required for firms to gain and sustain competitive advantage and future growth engines. The aim of this paper is to understand the recent research trend in management of technology (MOT) and to foresee promising technologies with deep knowledge for both technology and business. Furthermore, this study intends to give a clear way to find new technical value for constant innovation and to capture core technology and technology convergence. Bibliometrics is a metrical analysis to understand literature's characteristics. Traditional bibliometrics has its limitation not to understand relationship between trend in technology management and technology itself, since it focuses on quantitative indices such as quotation frequency. To overcome this issue, the network focused bibliometrics has been used instead of traditional one. The network focused bibliometrics mainly uses "Co-citation" and "Co-word" analysis. In this study, a keywords network analysis, one of social network analysis, is performed to analyze recent research trend in MOT. For the analysis, we collected keywords from research papers published in international journals related MOT between 2002 and 2011, constructed a keyword network, and then conducted the keywords network analysis. Over the past 40 years, the studies in social network have attempted to understand the social interactions through the network structure represented by connection patterns. In other words, social network analysis has been used to explain the structures and behaviors of various social formations such as teams, organizations, and industries. In general, the social network analysis uses data as a form of matrix. In our context, the matrix depicts the relations between rows as papers and columns as keywords, where the relations are represented as binary. Even though there are no direct relations between papers who have been published, the relations between papers can be derived artificially as in the paper-keyword matrix, in which each cell has 1 for including or 0 for not including. For example, a keywords network can be configured in a way to connect the papers which have included one or more same keywords. After constructing a keywords network, we analyzed frequency of keywords, structural characteristics of keywords network, preferential attachment and growth of new keywords, component, and centrality. The results of this study are as follows. First, a paper has 4.574 keywords on the average. 90% of keywords were used three or less times for past 10 years and about 75% of keywords appeared only one time. Second, the keyword network in MOT is a small world network and a scale free network in which a small number of keywords have a tendency to become a monopoly. Third, the gap between the rich (with more edges) and the poor (with fewer edges) in the network is getting bigger as time goes on. Fourth, most of newly entering keywords become poor nodes within about 2~3 years. Finally, keywords with high degree centrality, betweenness centrality, and closeness centrality are "Innovation," "R&D," "Patent," "Forecast," "Technology transfer," "Technology," and "SME". The results of analysis will help researchers identify major trends in MOT research and then seek a new research topic. We hope that the result of the analysis will help researchers of MOT identify major trends in technology research, and utilize as useful reference information when they seek consilience with other fields of study and select a new research topic.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.

• Magazine of the Korean Society of Agricultural Engineers
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• v.15 no.3
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• pp.3059-3088
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• 1973

The Object of research was laid on the dry paddy field which had a low level of underground water, rather than on a paddy field with a high level of underground water. In the treatment of the clay paddy field before transplanting we employed 3 kinds of methods; deep plowing, development of cracks by drying the surface of the field under which pipe drain was built. This study was to find which one, among these three methods, is the most effective to let roots extend to deep zone and increase the yield of rice and at the same time, for trafficability of large scale machinery which will be introduced to the harvest, in the light of the earth bearing capacity in relation with underground drainage. In the treatments of plots, 1) the kyong plot was plowed 39 days before transplanting and dried, 2) the kyun plot was plowed again 2days before transplanting after plowing 39 days before transplanting, leveling field surface in the saturation with water and developing the cracks by drying, 3) the kyunam plot was plowed again 2 days before transplanting after setting the drainage pipe and at the same time plowing 39 days before transplanting, leveling field surface in the saturation with water and developing the cracks by drying. Also each plot above had three different levels of soil depth, respectively; that is 15cm, 25cm, 35cm. The kyong plot with 15cm-depth was he control. The results obtained were as follows; 1. The kyunam plot showed a remarkably lager amount of water consumption by better underground drainage than the kyong and the kyun plot, and the kyong plot indicated a greater amount of water consumption than the kyun plot. Therefore the amount of available rainfall was decreased in the order of kyunam>kyong>kyun. The net duty of water decreased in the order of kyunam>kyong>kyun and its showed about 105cm in depth at the kyunam plot, about 70cm in depth at the kyong plot and about 45cm in depth at kyun plot, regardless of soil depth. 2. According to the tendency that the weight of the total root was effected by the maximum depth of the crack, it seemed that the root development was more affected by the depth of the crack than by only the crack itself. The weight of the total roots tended to increase as the depth of the crack got deeper and deeper, and the weight of the total roots was increased in the order of kyun<kyunam<kyong. 3. In the growing of the plant height, the difference did not appear at the beginning of growing(peak period of tillering) of any plot, But for the mid period of growing(ending period of tillering) to the period of young panicle formation, the deeper the depth of plot is, the more the growing goes down. On the contrary at the late period of growing, growth was more vigorous in the plot with deep depth than in the plot with shallow depth. Since the midperiod of growing, in the light of experimental treatment, the kyun plot was not better in growing than the other two plots and no remarkable defference was shown between the kyunam and the kyong plot, but the kyunam plot had the tendency of superiority in growing plant height. 4. As the depth of plot went deeper, the decreasing tendency was shown in the number of tillers through a whole period of growingi. When the above results were observed concering each plot of experimental treatment, the kyun plot was always smaller in the number of tiilers than the kyunam and the kvong plot, and the kyong plot was slightly larger than the kyunam plot in the number of tillers. 5. When each plot of the different experimental treatments was compared with the control plot(15-kyong), yield(weight of grains) was increased by 17% for the 35-kyong plot, by 10% for the 35-kyunam and yields for the other plots were less or nomore than the control plot. On the whole, as the depth of plot went deeper, yields for plots was increased in the order of kyong>kyunam>kyun. 1% of significance between the levels of depths and 5% of significance between the treatments were shown. 6. The depth of consumptive water which was more effective on the weight of grains is that of the last half period. When the depth of consumptive water was increased at the range of less than 2.7cm/day in the 15cm plot, 3.0cm/day in the 25cm plot and 3.3cm/day in the 35cm plot, the weight of grains was increased, and at the same time the weight of grains was increased as the depth of plot went deeper. The deeper plots was of advantage to the productivity at the same depth of consumptive water. 7. The increase in the weight of grains in propertion to the weighte of root showed a tendency to increase depending on the depth of plot at each plot of the same weight of roots. The weight of roots and grains together increasezd in the order of kyun>kyunam>kyong, considering each treatment of experimental plot. The weight of grains was in relation to the minimum water content ratio during the midperiod of surface drainage and the average earth temperature was mainly affected by the minimum water content ratio because it was relatively increased in proportion to the water content ratio(at less than 40%) 8. The weight ratio of straw to grain showed an increasing tendency at the plot of shallow depth and had a relation of an inversely exponental function to the weight of roots. At the same depth of plot except the 15cm plot, the weight ratio of straw to grain was increased in proportion to the depth of consumptive water. The weight of grains was increased as the depth of consumptive water was increased to some extent, but at the same time the weight of ratio of straw to grain was increased. 9. At a certain texture of soils the increase in the amount of the cracks depends on meteorological conditions, especially increase in amounts of pan evaporation. So if it rains during the progressing of field drying the cracks largely decrease. The amount of cracks of clay soil had relation of inversely exponental function to the water content ratio(at more than 25%). The maximum depth of crack kept generally a constant value at less than 30% of water content ratio. 10. The cone index showed the tendency that it was propertional to the amount of cracks within a certain limit but more or less inversely proportional over a certain limit. The water content ratio at the limit may be about 25%. 11. The increase in the cone index with the progressing of time after final surface drainage showed the tendency that it was proportional to the depth of consumptive water at the last half of growing period. Based on the same depth of if the cone index in the kyunam plot was much larger than in the other two plots and that in the kyong plot was much smaller than in the kyun plott, as long as the depth of plot was deeper, especially in the 35-kyong plot. 12. In the light of a situation where water content ratio of soil decreased and the cone index increased after final surface drainage the porogress of the field dryness was much more rapid in the kyunam plot than in the kyong plot and the kyun plot, especially slowest in the kyong plot. In the plot with deeper zone the progress was much slower. The progress requiring the value of the cone index, $2.5kg/cm^2$, that working machinary can move easily on the field changed with the time of final surface drainage and the amount of rainfall, but without nay rain it required, in the kyunam plot, about 44mm in total amount of pan evaporation and more than 50mm in the other two plots. Therefore the drying in the kyunam plot was generally more rapid in the kyunam plot was generally more rapid over 2days than in the kyun plot, and especially may be more rapid over 5days than in the 35-kyong plot.