• Title/Summary/Keyword: performance index

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Development of Predictive Models for Rights Issues Using Financial Analysis Indices and Decision Tree Technique (경영분석지표와 의사결정나무기법을 이용한 유상증자 예측모형 개발)

  • Kim, Myeong-Kyun;Cho, Yoonho
    • Journal of Intelligence and Information Systems
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    • v.18 no.4
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    • pp.59-77
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    • 2012
  • This study focuses on predicting which firms will increase capital by issuing new stocks in the near future. Many stakeholders, including banks, credit rating agencies and investors, performs a variety of analyses for firms' growth, profitability, stability, activity, productivity, etc., and regularly report the firms' financial analysis indices. In the paper, we develop predictive models for rights issues using these financial analysis indices and data mining techniques. This study approaches to building the predictive models from the perspective of two different analyses. The first is the analysis period. We divide the analysis period into before and after the IMF financial crisis, and examine whether there is the difference between the two periods. The second is the prediction time. In order to predict when firms increase capital by issuing new stocks, the prediction time is categorized as one year, two years and three years later. Therefore Total six prediction models are developed and analyzed. In this paper, we employ the decision tree technique to build the prediction models for rights issues. The decision tree is the most widely used prediction method which builds decision trees to label or categorize cases into a set of known classes. In contrast to neural networks, logistic regression and SVM, decision tree techniques are well suited for high-dimensional applications and have strong explanation capabilities. There are well-known decision tree induction algorithms such as CHAID, CART, QUEST, C5.0, etc. Among them, we use C5.0 algorithm which is the most recently developed algorithm and yields performance better than other algorithms. We obtained data for the rights issue and financial analysis from TS2000 of Korea Listed Companies Association. A record of financial analysis data is consisted of 89 variables which include 9 growth indices, 30 profitability indices, 23 stability indices, 6 activity indices and 8 productivity indices. For the model building and test, we used 10,925 financial analysis data of total 658 listed firms. PASW Modeler 13 was used to build C5.0 decision trees for the six prediction models. Total 84 variables among financial analysis data are selected as the input variables of each model, and the rights issue status (issued or not issued) is defined as the output variable. To develop prediction models using C5.0 node (Node Options: Output type = Rule set, Use boosting = false, Cross-validate = false, Mode = Simple, Favor = Generality), we used 60% of data for model building and 40% of data for model test. The results of experimental analysis show that the prediction accuracies of data after the IMF financial crisis (59.04% to 60.43%) are about 10 percent higher than ones before IMF financial crisis (68.78% to 71.41%). These results indicate that since the IMF financial crisis, the reliability of financial analysis indices has increased and the firm intention of rights issue has been more obvious. The experiment results also show that the stability-related indices have a major impact on conducting rights issue in the case of short-term prediction. On the other hand, the long-term prediction of conducting rights issue is affected by financial analysis indices on profitability, stability, activity and productivity. All the prediction models include the industry code as one of significant variables. This means that companies in different types of industries show their different types of patterns for rights issue. We conclude that it is desirable for stakeholders to take into account stability-related indices and more various financial analysis indices for short-term prediction and long-term prediction, respectively. The current study has several limitations. First, we need to compare the differences in accuracy by using different data mining techniques such as neural networks, logistic regression and SVM. Second, we are required to develop and to evaluate new prediction models including variables which research in the theory of capital structure has mentioned about the relevance to rights issue.

Radiotherapy in Supraglottic Carcinoma - With Respect to Locoregional Control and Survival - (성문상부암의 방사선치료 -국소종양 제어율과 생존율을 중심으로-)

  • Nam Taek-Keun;Chung Woong-Ki;Cho Jae-Shik;Ahn Sung-Ja;Nah Byung-Sik;Oh Yoon-Kyeong
    • Radiation Oncology Journal
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    • v.20 no.2
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    • pp.108-115
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    • 2002
  • Purpose : A retrospective study was undertaken to determine the role of conventional radiotherapy with or without surgery for treating a supraglottic carcinoma in terms of the local control and survival. Materials and Methods : From Jan. 1986 to Oct. 1996, a total of 134 patients were treated for a supraglottic carcinoma by radiotherapy with or without surgery. Of them, 117 patients who had completed the radiotherapy formed the base of this study. The patients were redistributed according to the revised AJCC staging system (1997). The number of patients of stage I, II, III, IVA, IVB were $6\;(5\%),\;16\;(14\%),\;53\;(45\%),\;32\;(27\%),\;10\;(9\%)$, respectively. Eighty patients were treated by radical radiotherapy in the range of $61.2\~79.2\;Gy$ (mean : 69.2 Gy) to the primary tumor and $45.0\~93.6\;Gy$ (mean : 54.0 Gy) to regional lymphatics. All patients with stage I and IVB were treated by radiotherapy alone. Thirty-seven patients underwent surgery plus postoperative radiotherapy in the range of $45.0\~68.4\;Gy$ (mean : 56.1 Gy) to the primary tumor bed and $45.0\~59.4\;Gy$ (mean : 47.2 Gy) to the regional lymphatics. Of them, 33 patients received a total laryngectomy (${\pm}lymph$ node dissection), three had a supraglottic horizontal laryngectomy (${\pm}lymph$ node dissection), and one had a primary excision alone. Results : The 5-year survival rate (5YSR) of all patients was $43\%$. The 5YSRs of the patients with stage I+II, III+IV were $49.9\%,\;41.2\%$, respectively (p=0.27). However, the disease-specific survival rate of the patients with stage I (n=6) was $100\%$. The 5YSRs of patients who underwent surgery plus radiotherapy (S+RT) vs radiotherapy alone (RT) in stage II, III, IVA were $100\%\;vs\;43\%$ (p=0.17), $62\%\;vs\;52\%$ (p=0.32), $58\%\;vs\;6\%$ (p<0.001), respectively. The 5-year actuarial locoregional control rate (5YLCR) of all the patients was $57\%$. The 5YLCR of the patients with stage I, II, III, IVA, IVB was $100\%,\;74\%,\;60\%,\;44\%,\;30\%$, respectively (p=0.008). The 5YLCR of the patients with S+RT vs RT in stage II, III, IVA was $100\%\;vs\;68\%$ (p=0.29), $67\%\;vs\;55\%$ (p=0.23), $81\%\;vs\;20\%$ (p<0.001), respectively. In the radiotherapy alone group, the 5YLCR of the patients with a complete, partial, and minimal response were $76\%,\;20\%,\;0\%$, respectively (p<0.001). In all patients, multivariate analysis showed that the N-stage, surgery or not, and age were significant factors affecting the survival rate and that the N-stage, surgery or not, and the ECOG performance index were significant factors affecting the locoregional control. In the radiotherapy alone group, multivariate analysis showed that the radiation response and N-stage were significant factors affecting the overall survival rate as well as locoregional control. Conclusion : In early stage supraglottic carcinoma, conventional radiotherapy alone is an equally effective modality compared to surgery plus radiotherapy and could preserve the laryngeal function. However, in the advanced stages, radiotherapy combined with concurrent chemotherapy for laryngeal preservation or surgery should be considered. In bulky neck disease, all the possible planned neck dissections after induction chemotherapy or before radiotherapy should be attempted.

The Effects of Supplemental Bacterial Phytase to the Calcium and Nonphosphorus Levels in Feed of Laying Hens (산란계 사료 내 칼슘 및 무기태 인 수준에 따른 Bacterial Phytase 급여 효과)

  • Kang, H.K.;Park, S.Y.;Yu, D.J.;Kim, J.H.;Kang, G.H.;Na, J.C.;Kim, D.W.;Suh, O.S.;Lee, S.J.;Lee, W.J.;Kim, S.H.
    • Korean Journal of Poultry Science
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    • v.35 no.2
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    • pp.143-151
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    • 2008
  • This study was conducted to identify the correlation of bacterial phytase ($Transphos^{(R)}$) to the calcium level in feed. Of all 21-week-old 720 HyLine brown laying hens, 2 birds of similar weight were placed on each individual cage. The experiment was conducted by $3{\times}2{\times}3$ factorial design with including 3 different levels of phytase (0, 300, and 1,000 DPU/kg), 2 different levels of calcium (3.5% and 4.0%), and 3 different levels of no NPP addition 0% (0.095 NPP), 0.5% (0.185% NPP), and 1.0% (0.275% NPP). The feeding trial maintained the ME level of 2,800 kcal/kg and 16% for crude protein. The diet was fed ad libitum and 17 hours of lighting was provided throughout the experimental period. Egg production seemed to increase, in the 300 DPU of bacterial phytase added group and the cracked egg tended to reduce in Transphos added group. The egg productivity between treatment groups did not show significant difference by dietary calcium level, whereas non NPP added group (0.095% NPP) was found to be low compared to NPP added groups (P<0.05). The highest mean egg weight and the highest daily egg mass were detected in 300 DPU phytase added group. Although the mean egg weight was significantly higher in treatment groups fed with 3.5% calcium containing feeds (P<0.05), daily egg mass was no among treatment groups. The mean egg weight and daily egg mass were the lowest in non NPP added group (0.095% NPP) compared to other treatment groups (P<0.05). The feed intake showed similar pattern regardless of the bacterial phytase and calcium levels in the diet. However, the treatment groups fed diets containing NPP level of 0.275% and 0.165% showed significantly higher feed intake than the group fed with 0.095% NPP (P<0.05). Although the feed conversion was not affected by calcium and NPP levels in the diet, the most improved result was obtained from 300 DPU phytase added group (P<0.05). The eggshell breaking strength and thickness increased as dietary calcium level increase the level of calcium increases in diet. The treatment groups fed diet containing 0.275% and 0.165% NPP revealed to show improvement in eggshell breaking strength and yolk color index compared to the NPP non added (0.095% NPP) treatment group. The result of the present study suggests that the appropriate level of microbial phytase is 300 DPU and at this level, tricalciumphosphate supplementation in feed can be reduced to 40% of NRC recommendation. Higher calcium level in feed fail to show synergistic effect by adding microbial phytase.

A Study on the Determinants of Patent Citation Relationships among Companies : MR-QAP Analysis (기업 간 특허인용 관계 결정요인에 관한 연구 : MR-QAP분석)

  • Park, Jun Hyung;Kwahk, Kee-Young;Han, Heejun;Kim, Yunjeong
    • Journal of Intelligence and Information Systems
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    • v.19 no.4
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    • pp.21-37
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    • 2013
  • Recently, as the advent of the knowledge-based society, there are more people getting interested in the intellectual property. Especially, the ICT companies leading the high-tech industry are working hard to strive for systematic management of intellectual property. As we know, the patent information represents the intellectual capital of the company. Also now the quantitative analysis on the continuously accumulated patent information becomes possible. The analysis at various levels becomes also possible by utilizing the patent information, ranging from the patent level to the enterprise level, industrial level and country level. Through the patent information, we can identify the technology status and analyze the impact of the performance. We are also able to find out the flow of the knowledge through the network analysis. By that, we can not only identify the changes in technology, but also predict the direction of the future research. In the field using the network analysis there are two important analyses which utilize the patent citation information; citation indicator analysis utilizing the frequency of the citation and network analysis based on the citation relationships. Furthermore, this study analyzes whether there are any impacts between the size of the company and patent citation relationships. 74 S&P 500 registered companies that provide IT and communication services are selected for this study. In order to determine the relationship of patent citation between the companies, the patent citation in 2009 and 2010 is collected and sociomatrices which show the patent citation relationship between the companies are created. In addition, the companies' total assets are collected as an index of company size. The distance between companies is defined as the absolute value of the difference between the total assets. And simple differences are considered to be described as the hierarchy of the company. The QAP Correlation analysis and MR-QAP analysis is carried out by using the distance and hierarchy between companies, and also the sociomatrices that shows the patent citation in 2009 and 2010. Through the result of QAP Correlation analysis, the patent citation relationship between companies in the 2009's company's patent citation network and the 2010's company's patent citation network shows the highest correlation. In addition, positive correlation is shown in the patent citation relationships between companies and the distance between companies. This is because the patent citation relationship is increased when there is a difference of size between companies. Not only that, negative correlation is found through the analysis using the patent citation relationship between companies and the hierarchy between companies. Relatively it is indicated that there is a high evaluation about the patent of the higher tier companies influenced toward the lower tier companies. MR-QAP analysis is carried out as follow. The sociomatrix that is generated by using the year 2010 patent citation relationship is used as the dependent variable. Additionally the 2009's company's patent citation network and the distance and hierarchy networks between the companies are used as the independent variables. This study performed MR-QAP analysis to find the main factors influencing the patent citation relationship between the companies in 2010. The analysis results show that all independent variables have positively influenced the 2010's patent citation relationship between the companies. In particular, the 2009's patent citation relationship between the companies has the most significant impact on the 2010's, which means that there is consecutiveness regarding the patent citation relationships. Through the result of QAP correlation analysis and MR-QAP analysis, the patent citation relationship between companies is affected by the size of the companies. But the most significant impact is the patent citation relationships that had been done in the past. The reason why we need to maintain the patent citation relationship between companies is it might be important in the use of strategic aspect of the companies to look into relationships to share intellectual property between each other, also seen as an important auxiliary of the partner companies to cooperate with.

A Methodology to Develop a Curriculum based on National Competency Standards - Focused on Methodology for Gap Analysis - (국가직무능력표준(NCS)에 근거한 조경분야 교육과정 개발 방법론 - 갭분석을 중심으로 -)

  • Byeon, Jae-Sang;Ahn, Seong-Ro;Shin, Sang-Hyun
    • Journal of the Korean Institute of Landscape Architecture
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    • v.43 no.1
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    • pp.40-53
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    • 2015
  • To train the manpower to meet the requirements of the industrial field, the introduction of the National Qualification Frameworks(hereinafter referred to as NQF) was determined in 2001 by National Competency Standards(hereinafter referred to as NCS) centrally of the Office for Government Policy Coordination. Also, for landscape architecture in the construction field, the "NCS -Landscape Architecture" pilot was developed in 2008 to be test operated for 3 years starting in 2009. Especially, as the 'realization of a competence-based society, not by educational background' was adopted as one of the major government projects in the Park Geun-Hye government(inaugurated in 2013) the NCS system was constructed on a nationwide scale as a detailed method for practicing this. However, in the case of the NCS developed by the nation, the ideal job performing abilities are specified, therefore there are weaknesses of not being able to reflect the actual operational problem differences in the student level between universities, problems of securing equipment and professors, and problems in the number of current curricula. For soft landing to practical curriculum, the process of clearly analyzing the gap between the current curriculum and the NCS must be preceded. Gap analysis is the initial stage methodology to reorganize the existing curriculum into NCS based curriculum, and based on the ability unit elements and performance standards for each NCS ability unit, the discrepancy between the existing curriculum within the department or the level of coincidence used a Likert scale of 1 to 5 to fill in and analyze. Thus, the universities wishing to operate NCS in the future measuring the level of coincidence and the gap between the current university curriculum and NCS can secure the basic tool to verify the applicability of NCS and the effectiveness of further development and operation. The advantages of reorganizing the curriculum through gap analysis are, first, that the government financial support project can be connected to provide quantitative index of the NCS adoption rate for each qualitative department, and, second, an objective standard is provided on the insufficiency or sufficiency when reorganizing to NCS based curriculum. In other words, when introducing in the subdivisions of the relevant NCS, the insufficient ability units and the ability unit elements can be extracted, and the supplementary matters for each ability unit element per existing subject can be extracted at the same time. There is an advantage providing directions for detailed class program and basic subject opening. The Ministry of Education and the Ministry of Employment and Labor must gather people from the industry to actively develop and supply the NCS standard a practical level to systematically reflect the requirements of the industrial field the educational training and qualification, and the universities wishing to apply NCS must reorganize the curriculum connecting work and qualification based on NCS. To enable this, the universities must consider the relevant industrial prospect and the relation between the faculty resources within the university and the local industry to clearly select the NCS subdivision to be applied. Afterwards, gap analysis must be used for the NCS based curriculum reorganization to establish the direction of the reorganization more objectively and rationally in order to participate in the process evaluation type qualification system efficiently.

Machine learning-based corporate default risk prediction model verification and policy recommendation: Focusing on improvement through stacking ensemble model (머신러닝 기반 기업부도위험 예측모델 검증 및 정책적 제언: 스태킹 앙상블 모델을 통한 개선을 중심으로)

  • Eom, Haneul;Kim, Jaeseong;Choi, Sangok
    • Journal of Intelligence and Information Systems
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    • v.26 no.2
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    • pp.105-129
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    • 2020
  • This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

A Study of the Reactive Movement Synchronization for Analysis of Group Flow (그룹 몰입도 판단을 위한 움직임 동기화 연구)

  • Ryu, Joon Mo;Park, Seung-Bo;Kim, Jae Kyeong
    • Journal of Intelligence and Information Systems
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    • v.19 no.1
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    • pp.79-94
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    • 2013
  • Recently, the high value added business is steadily growing in the culture and art area. To generated high value from a performance, the satisfaction of audience is necessary. The flow in a critical factor for satisfaction, and it should be induced from audience and measures. To evaluate interest and emotion of audience on contents, producers or investors need a kind of index for the measurement of the flow. But it is neither easy to define the flow quantitatively, nor to collect audience's reaction immediately. The previous studies of the group flow were evaluated by the sum of the average value of each person's reaction. The flow or "good feeling" from each audience was extracted from his face, especially, the change of his (or her) expression and body movement. But it was not easy to handle the large amount of real-time data from each sensor signals. And also it was difficult to set experimental devices, in terms of economic and environmental problems. Because, all participants should have their own personal sensor to check their physical signal. Also each camera should be located in front of their head to catch their looks. Therefore we need more simple system to analyze group flow. This study provides the method for measurement of audiences flow with group synchronization at same time and place. To measure the synchronization, we made real-time processing system using the Differential Image and Group Emotion Analysis (GEA) system. Differential Image was obtained from camera and by the previous frame was subtracted from present frame. So the movement variation on audience's reaction was obtained. And then we developed a program, GEX(Group Emotion Analysis), for flow judgment model. After the measurement of the audience's reaction, the synchronization is divided as Dynamic State Synchronization and Static State Synchronization. The Dynamic State Synchronization accompanies audience's active reaction, while the Static State Synchronization means to movement of audience. The Dynamic State Synchronization can be caused by the audience's surprise action such as scary, creepy or reversal scene. And the Static State Synchronization was triggered by impressed or sad scene. Therefore we showed them several short movies containing various scenes mentioned previously. And these kind of scenes made them sad, clap, and creepy, etc. To check the movement of audience, we defined the critical point, ${\alpha}$and ${\beta}$. Dynamic State Synchronization was meaningful when the movement value was over critical point ${\beta}$, while Static State Synchronization was effective under critical point ${\alpha}$. ${\beta}$ is made by audience' clapping movement of 10 teams in stead of using average number of movement. After checking the reactive movement of audience, the percentage(%) ratio was calculated from the division of "people having reaction" by "total people". Total 37 teams were made in "2012 Seoul DMC Culture Open" and they involved the experiments. First, they followed induction to clap by staff. Second, basic scene for neutralize emotion of audience. Third, flow scene was displayed to audience. Forth, the reversal scene was introduced. And then 24 teams of them were provided with amuse and creepy scenes. And the other 10 teams were exposed with the sad scene. There were clapping and laughing action of audience on the amuse scene with shaking their head or hid with closing eyes. And also the sad or touching scene made them silent. If the results were over about 80%, the group could be judged as the synchronization and the flow were achieved. As a result, the audience showed similar reactions about similar stimulation at same time and place. Once we get an additional normalization and experiment, we can obtain find the flow factor through the synchronization on a much bigger group and this should be useful for planning contents.

A Study on the Characteristics of Enterprise R&D Capabilities Using Data Mining (데이터마이닝을 활용한 기업 R&D역량 특성에 관한 탐색 연구)

  • Kim, Sang-Gook;Lim, Jung-Sun;Park, Wan
    • Journal of Intelligence and Information Systems
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    • v.27 no.1
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    • pp.1-21
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    • 2021
  • As the global business environment changes, uncertainties in technology development and market needs increase, and competition among companies intensifies, interests and demands for R&D activities of individual companies are increasing. In order to cope with these environmental changes, R&D companies are strengthening R&D investment as one of the means to enhance the qualitative competitiveness of R&D while paying more attention to facility investment. As a result, facilities or R&D investment elements are inevitably a burden for R&D companies to bear future uncertainties. It is true that the management strategy of increasing investment in R&D as a means of enhancing R&D capability is highly uncertain in terms of corporate performance. In this study, the structural factors that influence the R&D capabilities of companies are explored in terms of technology management capabilities, R&D capabilities, and corporate classification attributes by utilizing data mining techniques, and the characteristics these individual factors present according to the level of R&D capabilities are analyzed. This study also showed cluster analysis and experimental results based on evidence data for all domestic R&D companies, and is expected to provide important implications for corporate management strategies to enhance R&D capabilities of individual companies. For each of the three viewpoints, detailed evaluation indexes were composed of 7, 2, and 4, respectively, to quantitatively measure individual levels in the corresponding area. In the case of technology management capability and R&D capability, the sub-item evaluation indexes that are being used by current domestic technology evaluation agencies were referenced, and the final detailed evaluation index was newly constructed in consideration of whether data could be obtained quantitatively. In the case of corporate classification attributes, the most basic corporate classification profile information is considered. In particular, in order to grasp the homogeneity of the R&D competency level, a comprehensive score for each company was given using detailed evaluation indicators of technology management capability and R&D capability, and the competency level was classified into five grades and compared with the cluster analysis results. In order to give the meaning according to the comparative evaluation between the analyzed cluster and the competency level grade, the clusters with high and low trends in R&D competency level were searched for each cluster. Afterwards, characteristics according to detailed evaluation indicators were analyzed in the cluster. Through this method of conducting research, two groups with high R&D competency and one with low level of R&D competency were analyzed, and the remaining two clusters were similar with almost high incidence. As a result, in this study, individual characteristics according to detailed evaluation indexes were analyzed for two clusters with high competency level and one cluster with low competency level. The implications of the results of this study are that the faster the replacement cycle of professional managers who can effectively respond to changes in technology and market demand, the more likely they will contribute to enhancing R&D capabilities. In the case of a private company, it is necessary to increase the intensity of input of R&D capabilities by enhancing the sense of belonging of R&D personnel to the company through conversion to a corporate company, and to provide the accuracy of responsibility and authority through the organization of the team unit. Since the number of technical commercialization achievements and technology certifications are occurring both in the case of contributing to capacity improvement and in case of not, it was confirmed that there is a limit in reviewing it as an important factor for enhancing R&D capacity from the perspective of management. Lastly, the experience of utility model filing was identified as a factor that has an important influence on R&D capability, and it was confirmed the need to provide motivation to encourage utility model filings in order to enhance R&D capability. As such, the results of this study are expected to provide important implications for corporate management strategies to enhance individual companies' R&D capabilities.

Development of Yóukè Mining System with Yóukè's Travel Demand and Insight Based on Web Search Traffic Information (웹검색 트래픽 정보를 활용한 유커 인바운드 여행 수요 예측 모형 및 유커마이닝 시스템 개발)

  • Choi, Youji;Park, Do-Hyung
    • 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.

The Variation of Natural Population of Pinus densiflora S. et Z. in Korea (III) -Genetic Variation of the Progeny Originated from Mt. Chu-wang, An-Myon Island and Mt. O-Dae Populations- (소나무 천연집단(天然集團)의 변이(變異)에 관(關)한 연구(硏究)(III) -주왕산(周王山), 안면도(安眠島), 오대산(五臺山) 소나무집단(集團)의 차대(次代)의 유전변이(遺傳變異)-)

  • Yim, Kyong Bin;Kwon, Ki Won
    • Journal of Korean Society of Forest Science
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    • v.32 no.1
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    • pp.36-63
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    • 1976
  • The purpose of this study is to elucidate the genetic variation of the natural forest of Pinus densiflora. Three natural populations of the species, which are considered to be superior quality phenotypically, were selected. The locations and conditions of the populations are shown in table 1 and 2. The morphological traits of tree and needle and some other characteristics were presented already in our first report of this series in which population and family differences according to observed characteristics were statistically analyzed. Twenty trees were sampled from each populations, i.e., 60 trees in total. During the autumn of 1974, matured cones were collected from each tree and open-pollinated seeds were extracted in laboratory. Immediately after cone collection, in closed condition, the morphological characteristics were measured. Seed and seed-wing dimensions were also studied. In the spring of 1975, the seeds were sown in the experimental tree nursery located in Suweon. And in the April of 1976, the 1-0 seedlings were transplanted according to the predetermined experimental design, randomized block design with three replications. Because of cone setting condition. the number of family from which progenies were raised by populations were not equal. The numbers of family were 20 in population 1. 18 in population 2 and 15 in population 3. Then, each randomized block contained seedlings of 53 families from 3 populations. The present paper is mainly concerned with the variation of some characteristics of cone, seed, needle, growth performance of seedlings, and chlorophyll and monoterpene compositions of needles. The results obtained are summerized as follows. 1. The meteorological data obtained by averaging the records of 30 year period, observed from the nearest station to each location of populations, are shown in Fig. 3, 4, and 5. The distributional pattern of monthly precipitation are quite similar among locations. However, the precipitation density on population 2, Seosan area, during growing season is lower as compared to the other two populations. Population 1. Cheong-song area, and population 3, Pyong-chang area, are located in inland, but population 2 in the western seacoast. The differences on the average monthly air temperatures and the average monthly lowest temperatures among populations can hardly be found. 2. Available information on the each mother trees (families) studied, such as age, stem height, diameter at breast height, clear-bole-length, crown conditions and others are shown in table 6,7, and 8. 3. The measurements of fresh cone weight, length and the widest diameter of cone are given in Tab]e 9. All these traits arc concerned with the highly significant population differences and family differences within population. And the population difference was also found in the cone-index, that is, length-diameter ratio. 4. Seed-wing length and seed-wing width showed the population differences, and the family differences were also found in both characteristics. Not discussed in this paper, however, seed-wing colours and their shapes indicate the specificity which is inherent to individual trees as shown in photo 3 on page 50. The colour and shape are fully the expression of genetic make up of mother tree. The little variations on these traits are resulted from this reason. The significant differences among populations and among families were found in those characteristics, such as 1000-seed weight, seed length, seed width, and seed thickness as shown in table 11. As to all these dimensions, the values arc always larger in population 1 which is younger in age than that of the other two. The population differences evaluated by cone, seed and seed-wing sizes could partly be attributed to the growth vigorousity. 5. The values of correlation between the characteristics of cone and seed are presented in table 12. As shown, the positive correlations between cone diameter and seed-wing width were calculated in all populations studied. The correlation between seed-wing length and seed length was significantly positive in population 1 and 3 but not in population 2, that is, the r-value is so small as 0.002. in the latter. The correlation between cone length and seed-wing length was highly significant in population 1, but not in population 2. 6. Differences among progenies in growth performances, such as 1-0 and 1-1 seedling height and root collar diameter were highly singificant among populations as well as families within population(Table 13.) 7. The heritability values in narrow sense of population characteristics were estimated on the basis of variance components. The values based on seedling height at each age stage of 1-1 and 1-0 ranged from 0.146 to 0.288 and the values of root collar diameter from 0.060 to 0.130. (Table 14). These heritability values varied according to characteristics and seedling ages. Here what must be stated is that, for calculation of heritability values, the variance values of population was divided by the variance value of environment (error) and family and population. The present authors want to add the heritability values based on family level in the coming report. It might be considered that if the tree age is increased in furture, the heritability value is supposed to be altered or lowered. Examining the heritability values studied previously by many authors, in pine group at age of 7 to 15, the values of height growth ranged from 0.2 to 0.4 in general. The values we obtained are further below than these. 8. The correlation between seedling growth and seed characteristics were examined and the values resulted are shown in table 16. Contrary to our hypothetical premise of positive correlation between 1-0 seedling height and seed weight, non-significance on it was found. However, 1-0 seedling height correlated positively with seed length. And significant correlations between 1-0 and 1-1 seedling height are calculated. 9. The numbers of stomata row calculated separately by abaxial and adaxial side showed highly significant differences among populations, but not in serration density. On serration density, the differences among families within population were highly significant. (Table 17) A fact must be noted is that the correlation between stomata row on abaxial side and adaxial side was highly significant in all populations. Non-significances of correlation coefficient between progenies and parents regarding to stomata row on abaxial side were shown in all populations studied.(Table 18). 10. The contents of chhlorophyll b of the needle were a little more than that of chlorophyll a irrespective of the populations examined. The differences of chlorophyll a, b and a plus b contents were highly significant but not among families within populations as shown in table 20. The contents of chlorophyll a and b are presented by individual trees of each populations in table 21. 11. The occurrence of monoterpene components was examined by gas liquid chromatography (Shimazu, GC-1C type) to evaluate the population difference. There are some papers reporting the chemical geography of pines basing upon monoterpene composition. The number of populations studied here is not enough to state this problem. The kinds of monoterpene observed in needle were ${\alpha}$-pinene, camphene, ${\beta}$-pinene, myrcene, limonene, ${\beta}$-phellandrene and terpinolene plus two unknowns. In analysis of monoterpene composition, the number of sample trees varied with population, I.e., 18 families for population 1, 15 for population 2 and 11 for population3. (Table 22, 23 and 24). The histograms(Fig. 6) of 7 components of monoterpene by population show noticeably higher percentages of ${\alpha}$-pinene irrespective of population and ${\beta}$-phellandrene in the next order. The minor Pinus densiflora monoterpene composition of camphene, myrcene, limonene and terpinolene made up less than 10 percent of the portion in general. The average coefficients of variation of ${\alpha}$-pinene and ${\beta}$-phellandrene were 11 percent. On the contrary to this, the average coefficients of variation of camphene, limonene and terpinolene varied from 20 to 30 percent. And the significant differences between populaiton were observed only in myrcene and ${\beta}$-phellandrene. (Table 25).

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