• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• The Korean Journal of Malacology
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• v.22 no.2
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• pp.125-134
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• 2006

We investigated the reproductive cycle of the hard clam, Meretrix petechialis with its gonadal development by histological observations. The seasonal changes in biochemical component of the adductor muscle, visceral mass, foot muscle and mantle of the clam were studied by biochemical analysis, from January to December, 2002. The reproductive cycle of this species can be divided into five successive stages: early stage (January to March), late active stage (February to May), ripe stage (April to August), partially spawned stage (July to August) and spent/inactive stage (September to January). Total protein content in the visceral mass was over two times higher than that in the adductor muscle. Monthly changes of total protein content in the adductor muscle were not statistically significant (ANOVA, p = 0.071), while the changes in the visceral mass were significant (p < 0.001). Total protein content in visceral mass was higher during the early active, late active, and ripe stages (from January to May), while the lowest in July. Glycogen content in the adductor muscle was higher than that in the visceral mass. Monthly changes in glycogen contents were statistically significant in both adductor muscle (F = 237.2, p < 0.001) and the visceral mass (F = 64.04, p < 0.001). Glycogen content in the adductor muscle was the highest in the ripe stage (April). Its content was lower in the partially spawned and the spent/inactive stages (June-September). Glycogen contents in the visceral mass were relatively lower until the early active stage, while the highest in the late active stage. RNA content was higher in visceral mass than that in the adductor muscle. Monthly changes in RNA contents were significant in both adductor muscle (F = 195.2, p < 0.001) and visceral mass (F = 78.85, p < 0.001). RNA content in the adductor muscle was high in the early active stage (January-February), and then it decreased rapidly in the late active stage (March-April), thereafter, slightly increased during the partially spawned stage (June-July). RNA content in the visceral mass reached a maximum during the ripe stage (May), and then it decreased rapidly during the partially-spawned stage (June-July). There was significant positive correlation in total protein contents between adductor muscle and visceral mass (r = 0.715, p = 0.020). However, there was no correlation between adductor muscle and visceral mass in glycogen (p = 0.550), while a negative correlation was found between the adductor muscle and visceral mass in RNA (p = 0.518) contents. Especially, changes in RNA content showed a negative correlation between the adductor muscle tissue and visceral mass. Therefore, these results suggest that the nutrient content of the adductor muscle, visceral muscle and foot muscle changed in response to gonadal energy needs.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.27-42
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• 2020

Traditional companies with offline stores were unable to secure large display space due to the problems of cost. This limitation inevitably allowed limited kinds of products to be displayed on the shelves, which resulted in consumers being deprived of the opportunity to experience various items. Taking advantage of the virtual space called the Internet, online shopping goes beyond the limits of limitations in physical space of offline shopping and is now able to display numerous products on web pages that can satisfy consumers with a variety of needs. Paradoxically, however, this can also cause consumers to experience the difficulty of comparing and evaluating too many alternatives in their purchase decision-making process. As an effort to address this side effect, various kinds of consumer's purchase decision support systems have been studied, such as keyword-based item search service and recommender systems. These systems can reduce search time for items, prevent consumer from leaving while browsing, and contribute to the seller's increased sales. Among those systems, recommender systems based on association rule mining techniques can effectively detect interrelated products from transaction data such as orders. The association between products obtained by statistical analysis provides clues to predicting how interested consumers will be in another product. However, since its algorithm is based on the number of transactions, products not sold enough so far in the early days of launch may not be included in the list of recommendations even though they are highly likely to be sold. Such missing items may not have sufficient opportunities to be exposed to consumers to record sufficient sales, and then fall into a vicious cycle of a vicious cycle of declining sales and omission in the recommendation list. This situation is an inevitable outcome in situations in which recommendations are made based on past transaction histories, rather than on determining potential future sales possibilities. This study started with the idea that reflecting the means by which this potential possibility can be identified indirectly would help to select highly recommended products. In the light of the fact that the attributes of a product affect the consumer's purchasing decisions, this study was conducted to reflect them in the recommender systems. In other words, consumers who visit a product page have shown interest in the attributes of the product and would be also interested in other products with the same attributes. On such assumption, based on these attributes, the recommender system can select recommended products that can show a higher acceptance rate. Given that a category is one of the main attributes of a product, it can be a good indicator of not only direct associations between two items but also potential associations that have yet to be revealed. Based on this idea, the study devised a recommender system that reflects not only associations between products but also categories. Through regression analysis, two kinds of associations were combined to form a model that could predict the hit rate of recommendation. To evaluate the performance of the proposed model, another regression model was also developed based only on associations between products. Comparative experiments were designed to be similar to the environment in which products are actually recommended in online shopping malls. First, the association rules for all possible combinations of antecedent and consequent items were generated from the order data. Then, hit rates for each of the associated rules were predicted from the support and confidence that are calculated by each of the models. The comparative experiments using order data collected from an online shopping mall show that the recommendation accuracy can be improved by further reflecting not only the association between products but also categories in the recommendation of related products. The proposed model showed a 2 to 3 percent improvement in hit rates compared to the existing model. From a practical point of view, it is expected to have a positive effect on improving consumers' purchasing satisfaction and increasing sellers' sales.

• Korean Journal of Poultry Science
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• v.16 no.2
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• pp.105-127
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• 1989

Although poultry industry in Japan has been much developed in recent years, it still needs to be developed , compared with developed countries. Since the poultry market in Korea is expected to be opened in the near future it is necessary to maximize the Productivity to reduce the production costs and to develop the scientific, technologies and management organization systems for the improvement of the quality in poultry production. Followings ale the summary of poultry industry in Japan. 1. Poultry industry in Japan is almost specized and commercialized and its management system is ： integrated, cooperative and developed to industrialized intensive style. Therefore, they have competitive power in the international poultry markets. 2. Average egg weight is 48-50g per day (Max. 54g) and feed requirement is 2. 1-2. 3. 3. The management organization system is specialized and farmers in small scale form complex and farmers in large scale are integrated.

• 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.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.27-65
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• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.

• The Korean Journal of Nuclear Medicine Technology
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• v.26 no.2
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• pp.20-31
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• 2022

Purpose Broad Quantification Calibration(B.Q.C) is the procedure for Quantitative Analysis to measure Standard Uptake Value(SUV) in SPECT/CT scanner. B.Q.C was performed with Tc-99m, I-123, I-131, Lu-177 respectively and then we acquired the phantom images whether the SUVs were measured accurately. Because there is no standard for SUV test in SPECT, we used ACR Esser PET phantom alternatively. The purpose of this study was to lay the groundwork for Quantitative Analysis with various isotopes in SPECT/CT scanner. Materials and Methods Siemens SPECT/CT Symbia Intevo 16 and Intevo Bold were used for this study. The procedure of B.Q.C has two steps; first is point source Sensitivity Cal. and second is Volume Sensitivity Cal. to calculate Volume Sensitivity Factor(VSF) using cylinder phantom. To verify SUV, we acquired the images with ACR Esser PET phantom and then we measured SUV_mean on background and SUV_max on hot vials(25, 16, 12, 8 mm). SPSS was used to analyze the difference in the SUV between Intevo 16 and Intevo Bold by Mann-Whitney test. Results The results of Sensitivity(CPS/MBq) and VSF were in Detector 1, 2 of four isotopes (Intevo 16 D1 sensitivity/D2 sensitivity/VSF and Intevo Bold) 87.7/88.6/1.08, 91.9/91.2/1.07 on Tc-99m, 79.9/81.9/0.98, 89.4/89.4/0.98 on I-123, 124.8/128.9/0.69, 130.9, 126.8/0.71, on I-131, 8.7/8.9/1.02, 9.1/8.9/1.00 on Lu-177 respectively. The results of SUV test with ACR Esser PET phantom were (Intevo 16 BKG SUV_mean/25mm SUV_max/16mm/12mm/8mm and Intevo Bold) 1.03/2.95/2.41/1.96/1.84, 1.03/2.91/2.38/1.87/1.82 on Tc-99m, 0.97/2.91/2.33/1.68/1.45, 1.00/2.80/2.23/1.57/1.32 on I-123, 0.96/1.61/1.13/1.02/0.69, 0.94/1.54/1.08/0.98/ 0.66 on I-131, 1.00/6.34/4.67/2.96/2.28, 1.01/6.21/4.49/2.86/2.21 on Lu-177. And there was no statistically significant difference of SUV between Intevo 16 and Intevo Bold(p>0.05). Conclusion Only Qualitative Analysis was possible with gamma camera in the past. On the other hand, it's possible to acquire not only anatomic localization, 3D tomography but also Quantitative Analysis with SUV measurements in SPECT/CT scanner. We could lay the groundwork for Quantitative Analysis with various isotopes; Tc-99m, I-123, I-131, Lu-177 by carrying out B.Q.C and could verify the SUV measurement with ACR phantom. It needs periodic calibration to maintain for precision of Quantitative evaluation. As a result, we can provide Quantitative Analysis on follow up scan with the SPECT/CT exams and evaluate the therapeutic response in theranosis.

• Korean Journal of Soil Science and Fertilizer
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• v.12 no.4
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• pp.189-213
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• 1980

1. Aiming at supply of basic informations on tree species siting and forest fertilization by understanding of soil properties that are demanded by each tree species through studies of forest soil's morphological, physical and chemical properties in relation to tree growth in our country, the necessary data have been collected in the last 10 years, are quantified according to quantification theory and are analyzed in accordance with multi-variate analysis. 2. Test species, larch and the Korean white pine, are plantable in extensive areas from mid to north in the temperate zone and are the two most recommended reforestation tree species in Korea. However, their respective site demands are not known and they have been in confusion or considered demanding the same site during reforestation. When the Korean white pine is planted in larch sites, it has shown relatively good growth. But, when larch is planted in the Korean white pine site it can be hardly said that the larch growth is good. To understand on such a difference soil factors have been studied so as to see how the soil's morphological, physical and chemical factors affect tree growth helped with the electronic computer. 3. All the stands examined are man-made mature forests. From 294 larch plots and 259 white pine plots dominant trees are cut as samples and through stem analysis site index is determined. For each site index soil profiles are made in the related forest-land for analysis. Soil samples are taken from each profile horizon and forest-land productivity classification tables are worked out through physical and chemical analysis of the soil samples for each tree species for the study of relationships between physical, chemical and the combined physical/chemical properties of soil and tree growth. 4. In the study of relationships between physical properties of soil and tree growth it is found out that larch growth is influenced by the following factors in the order of deposit form, soil depth, soil moisture, altitude, relief, soil type, depth of A-horizon, soil consistency content of organic matter soil texture bed rock gravel content aspect and slope. For the Korean white pine the influencing factors' order is soil type, soil consistency bed rock aspect depth of A-horizon soil moisture altitude relief deposit form soil depth soil texture gravel content and slope. 5. In the study of relationships between chemical properties of soil and tree growth it is found out that larch growth is influenced by the following factors in the order of base saturation organic matter CaO C/N ratio, effective $P_2O_5$ PH.exchangeable $K_2O$ T-N MgO C E C Total Base and Na. For the Korean white pine the influencing factors' order is effective $P_2O_5$ Total Base T-N Na C/N ratio PH CaO base saturation organic matter exchangeable $K_2O$ C E C and MgO. 6. In the study of relationships between the combined physical and chemical properties of soil and tree growth it is found out that larch growth is influenced by the following factors in the order of soil depth deposit form soil moisture PH relief soil type altitude T-N soil consistency effective $P_2O_5$ soil texture depth of A-horizon Total Base exchangeable $K_2O$ and base saturation. For the Korean white pine the influencing factors' order is soil type soil consistency aspect effective $P_2O_5$ depth of A-horizon exchangeable $K_2O$ soil moisture Total Base altitude soil depth base saturation relief T-N C/N ratio and deposit from. 7. In the multiple regression of forest soil's physical properties larch's correlation coefficient is 0.9272 and for the Korean white pine it is 0.8996. With chemical properties larch has 0.7474 and the Korean white pine has 0.7365. So, the soil's physical properties are found out more closely related with tree growth than chemical properties. However, this seems due to inadequate expression of soil's chemical factors and it is proved that the chemical properties are not less important than the physical properties. In the multiple regression of the combined physical and chemical properties consisting of important morphological and physical factors as well as chemical factors of forest soils larch's multiple correlation coefficient is found out to be 0.9434 and for the Korean white pine it is 0.9103 leading to the highest correlation. 8. As shown in the partial correlation coefficients larch needs deeper soil depth than the Korean white pine and in the deposit form colluvial and creeping soils are demanded by the larch. Adequately moist to too moist should be soil moisture and PH should be from 5.5 to 6.1 for the larch. Demands of T-N soil texture and soil nutrients are higher for the larch than the Korean white pine. Thus, soil depth, deposit form, relief soil moisture PH N altitude and soil texture are good indicators for species sitings with larch and the Korean white pine while soil type and soil consistency are indicative only limitedly of species sitings due to their wide variation as plantation environments. For larch siting soil depth deposit form relief soil moisture PH soil type N and soil texture are indicators of good growth and for Korean white pine they are soil type soil consistency effective $P_2O_5$ and exchangeable $K_2O$, which is demanded more by the Korean white pine than larch generally. 9. Physical properties of soil has been known as affecting tree growth to greatest extent so far. However, as a result of this study it is proved through computer analysis that chemical properties of soil are not less important factors for tree growth than chemical properties and site demands for larch and the Korean white pine that have been uncertain So far could be clarified.

• Korean small business review
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• v.31 no.2
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• pp.85-102
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• 2009

With the continued globalization of world markets, transfer pricing has become one of the dominant sources of controversy in international taxation. Transfer pricing is the process by which a multinational corporation calculates a price for goods and services that are transferred to affiliated entities. Consider a Korean electronic enterprise that buys supplies from its own subsidiary located in China. How much the Korean parent company pays its subsidiary will determine how much profit the Chinese unit reports in local taxes. If the parent company pays above normal market prices, it may appear to have a poor profit, even if the group as a whole shows a respectable profit margin. In this way, transfer prices impact the taxable income reported in each country in which the multinational enterprise operates. It's importance lies in that around 60% of international trade involves transactions between two related parts of multinationals, according to the OECD. Multinational enterprises (hereafter MEs) exert much effort into utilizing organizational advantages to make global investments. MEs wish to minimize their tax burden. So MEs spend a fortune on economists and accountants to justify transfer prices that suit their tax needs. On the contrary, local governments are not prepared to cope with MEs' powerful financial instruments. Tax authorities in each country wish to ensure that the tax base of any ME is divided fairly. Thus, both tax authorities and MEs have a vested interest in the way in which a transfer price is determined, and this is why MEs' international transfer prices are at the center of disputes concerned with taxation. Transfer pricing issues and practices are sometimes difficult to control for regulators because the tax administration does not have enough staffs with the knowledge and resources necessary to understand them. The authors examine transfer pricing practices to provide relevant resources useful in designing tax incentives and regulation schemes for policy makers. This study focuses on identifying the relevant business and environmental factors that could influence the international transfer pricing of MEs. In this perspective, we empirically investigate how the management perception of related variables influences their choice of international transfer pricing methods. We believe that this research is particularly useful in the design of tax policy. Because it can concentrate on a few selected factors in consideration of the limited budget of the tax administration with assistance of this research. Data is composed of questionnaire responses from foreign firms in Korea with investment balances exceeding one million dollars in the end of 2004. We mailed questionnaires to 861 managers in charge of the accounting departments of each company, resulting in 121 valid responses. Seventy six percent of the sample firms are classified as small and medium sized enterprises with assets below 100 billion Korean won. Reviewing transfer pricing methods, cost-based transfer pricing is most popular showing that 60 firms have adopted it. The market-based method is used by 31 firms, and 13 firms have reported the resale-pricing method. Regarding the nationalities of foreign investors, the Japanese and the Americans constitute most of the sample. Logistic regressions have been performed for statistical analysis. The dependent variable is binary in that whether the method of international transfer pricing is a market-based method or a cost-based method. This type of binary classification is founded on the belief that the market-based method is evaluated as the relatively objective way of pricing compared with the cost-based methods. Cost-based pricing is assumed to give mangers flexibility in transfer pricing decisions. Therefore, local regulatory agencies are thought to prefer market-based pricing over cost-based pricing. Independent variables are composed of eight factors such as corporate tax rate, tariffs, relations with local tax authorities, tax audit, equity ratios of local investors, volume of internal trade, sales volume, and product life cycle. The first four variables are included in the model because taxation lies in the center of transfer pricing disputes. So identifying the impact of these variables in Korean business environments is much needed. Equity ratio is included to represent the interest of local partners. Volume of internal trade was sometimes employed in previous research to check the pricing behavior of managers, so we have followed these footsteps in this paper. Product life cycle is used as a surrogate of competition in local markets. Control variables are firm size and nationality of foreign investors. Firm size is controlled using dummy variables in that whether or not the specific firm is small and medium sized. This is because some researchers report that big firms show different behaviors compared with small and medium sized firms in transfer pricing. The other control variable is also expressed in dummy variable showing if the entrepreneur is the American or not. That's because some prior studies conclude that the American management style is different in that they limit branch manger's freedom of decision. Reviewing the statistical results, we have found that managers prefer the cost-based method over the market-based method as the importance of corporate taxes and tariffs increase. This result means that managers need flexibility to lessen the tax burden when they feel taxes are important. They also prefer the cost-based method as the product life cycle matures, which means that they support subsidiaries in local market competition using cost-based transfer pricing. On the contrary, as the relationship with local tax authorities becomes more important, managers prefer the market-based method. That is because market-based pricing is a better way to maintain good relations with the tax officials. Other variables like tax audit, volume of internal transactions, sales volume, and local equity ratio have shown only insignificant influence. Additionally, we have replaced two tax variables(corporate taxes and tariffs) with the data showing top marginal tax rate and mean tariff rates of each country, and have performed another regression to find if we could get different results compared with the former one. As a consequence, we have found something different on the part of mean tariffs, that shows only an insignificant influence on the dependent variable. We guess that each company in the sample pays tariffs with a specific rate applied only for one's own company, which could be located far from mean tariff rates. Therefore we have concluded we need a more detailed data that shows the tariffs of each company if we want to check the role of this variable. Considering that the present paper has heavily relied on questionnaires, an effort to build a reliable data base is needed for enhancing the research reliability.

• Journal of Korean Society of Forest Science
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• v.53 no.1
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• pp.1-26
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• 1981

1. Aiming at supply of basic informations on tree species siting and forest fertilization by understanding of soil properties that are demanded by each tree species through studies of forest soil's morphological, physical and chemical properties in relation to tree growth in our country, the necessary data have been collected in the last 10 years, are quantified according to quantification theory and are analyzed in sccordance with multi-variate analysis. 2. Test species, japanese larch (Larix leptolepis Gord) and the Korean white pine, (pinus koraiensis S et Z.) are plantable in extensive areas from mid to north in the temperate forest zone and are the two most recommended reforestation tree species in Korea. However, their respective site demands are little known and they have been in confusion or considered demanding the same site during reforestation. When the Korean white pine is planted in larch sites, it has shown relatively good growth, but, when Japanese larch is planted in Korean white pine site it can be hardly said that the Japanese Larch growth is good. To understand on such a difference soil factors have been studied so as to see how th soil's morphological, physical and chemical factors affect tree growth helped with the electronic computer. 3. All the stands examined are man-made mature forests. From 294 Japanese larch plots and 259 Korean white pine plots dominant trees are cut as samples and through stem analysis site index is determined. For each site index soil profiles are made in the related forest-land for analysis. Soil samples are taken from each profile horizon and forest-land productivity classification tables are worked out through physical and chemical analyses of the soil samples for each tree species for the study of relationships between physical, chemical and the combined physical/properties of soil and tree growth. 4. In the study of relationships between physical properties of soil and tree growth it is found out that Japanese larch growth is influenced by the following factors in the decreasing order of weight deposit form, soil depth, soil moisture, altitude, relief, soil type, depth a A-horizon, soil consistency, content of organic matter, soil texture, bed rock, gravel content, aspect and slope. For the Korean white pine the influencing factors' order is soil type, soil consistency, bed rock, aspect, depth of A-horizon, soil moisture, altitude, relief, deposit form, soil depth, soil texture, gravel content and slope. 5. In the study of relationships between chemical properties of soil and tree growth it is found out that Japanese larch growth is influenced by the following factors in the order of base saturation, organic matter, CaO, C/N ratio, effective $P_2O_5$, PH, exchangeable, $K_2O$, T-N, MgO, CEC, Total Base and Na. For the Korean white pine the influencing factors' order is effective $P_2O_5$, Total Base, T-N, Na, C/N ratio, PH, CaO, base saturation, organic matter, exchangeable $K_2O$, CEC and MgO. 6. In the study of relationships between the combined physical and chemical properties of soil and tree growth it is found out that Japanese larch growth is influenced by the following factors in the order of soil depth, deposit form, soil moisture, PH, relief, soil type altitude, T-N, soil consistency, effective $P_2O_5$, soil texture, depth of A-horizon, Total Base, exchangeable $K_2O$ and base saturation. For the Korean white pine the influencing factors' order is soil type, soil consistency, aspect, effective $P_2O_5$, depth of A-horizon, exchangeable $K_2O$, soil moisture, Total Base, altitude, soil depth, base saturation, relief, T-N, C/N ratio and deposit form. 7. In the multiple correlation of forest soil's physical properties larch's correlation coefficient for Japanese Larch is 0.9272 and for Korean white pine, 0.8996. With chemical properties larch has 0.7474 and Korean white pine has 0.7365. So, the soil's physical properties are found out more closely related with tree growth than chemical properties. However, this seems due to inadequate expression of soil's chemical factors and it is proved that the chemical properities are not less important than the physical properties. In the multiple correlation of the combined physical and chemical properties consisting of important morphological and physical factors as well as chemical factors of forest soils larch's multiple correlation coefficient is found out to be 0.9434 and for Korean white pine it is 0.9103 leading to the highest correlation. 8. As shown in the partial correlation coefficients Japanese larch needs deeper soil depth than Korean white pine and in the deposit form of colluvial and creeping soils are demanded by the larch. Moderately moist to not moist should be soil moisture and PH should be from 5.5 to 6.1 for the larch. Demands of T-N, soil texture and soil nutrients are higher for the larch than the Korean white pine. Thus, soil depth, deposit form, relief, soil moisture, PH, N, altitude and soil texture are good indicators for species sitings with larch and the Korean white pine while soil type and soil consistency are indicative only limitedly of species sitings due to their wide variations as plantation environments. For the larch siting soil depth, deposit form, relief, soil moisture, pH, soil type, N and soil texture are indicators of good growth and for the Korean white pine they are soil type, soil consistency, effective $P_2O_5$ and exchangeable $K_2O$. In soil nutrients larch has been found out demanding more than the Korean white pine except $K_2O$, which is demanded more by the Korean white pine than Japanese larch generally. 9. Physical properties of soil has been known as affecting tree growth to the greatest extent so far. However, as a result of this study it is proved through computer analysis that chemical properties of soil are not less important factors for tree growth than chemical properties and site demands for the Japanese larch and the Korean white pine that have been uncertain so far could be clarified.