• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.151-171
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• 2015

This study examined the concepts of the Internet of Things(IoT), the major issue and IoT trend in the domestic and international market. also reviewed the advent of IoT era which caused a 'Paradigm Shift'. This study proposed a solution for the appropriate corresponding strategy in terms of Enterprise. Global competition began in the IoT market. So, Businesses to be competitive and responsive, the government's efforts, as well as the efforts of companies themselves is needed. In particular, in order to cope with the dynamic environment appropriately, faster and more efficient strategy is required. In other words, proposed a management strategy that can respond the IoT competitive era on tipping point through the vision of paradigm shift. We forecasted and proposed the emergence of paradigm shift through a comparative analysis of past management paradigm and IoT management paradigm as follow; I) Knowledge & learning oriented management, II) Technology & innovation oriented management, III) Demand driven management, IV) Global collaboration management. The Knowledge & learning oriented management paradigm is expected to be a new management paradigm due to the development of IT technology development and information processing technology. In addition to the rapid development such as IT infrastructure and processing of data, storage, knowledge sharing and learning has become more important. Currently Hardware-oriented management paradigm will be changed to the software-oriented paradigm. In particular, the software and platform market is a key component of the IoT ecosystem, has been estimated to be led by Technology & innovation oriented management. In 2011, Gartner announced the concept of "Demand-Driven Value Networks(DDVN)", DDVN emphasizes value of the whole of the network. Therefore, Demand driven management paradigm is creating demand for advanced process, not the process corresponding to the demand simply. Global collaboration management paradigm create the value creation through the fusion between technology, between countries, between industries. In particular, cooperation between enterprises that has financial resources and brand power and venture companies with creative ideas and technical will generate positive synergies. Through this, The large enterprises and small companies that can be win-win environment would be built. Cope with the a paradigm shift and to establish a management strategy of Enterprise process, this study utilized the 'RTE cyclone model' which proposed by Gartner. RTE concept consists of three stages, Lead, Operate, Manage. The Lead stage is utilizing capital to strengthen the business competitiveness. This stages has the goal of linking to external stimuli strategy development, also Execute the business strategy of the company for capital and investment activities and environmental changes. Manege stage is to respond appropriately to threats and internalize the goals of the enterprise. Operate stage proceeds to action for increasing the efficiency of the services across the enterprise, also achieve the integration and simplification of the process, with real-time data capture. RTE(Real Time Enterprise) concept has the value for practical use with the management strategy. Appropriately applied in this study, we propose a 'IoT-RTE Cyclone model' which emphasizes the agility of the enterprise. In addition, based on the real-time monitoring, analysis, act through IT and IoT technology. 'IoT-RTE Cyclone model' that could integrate the business processes of the enterprise each sector and support the overall service. therefore the model be used as an effective response strategy for Enterprise. In particular, IoT-RTE Cyclone Model is to respond to external events, waste elements are removed according to the process is repeated. Therefore, it is possible to model the operation of the process more efficient and agile. This IoT-RTE Cyclone Model can be used as an effective response strategy of the enterprise in terms of IoT era of rapidly changing because it supports the overall service of the enterprise. When this model leverages a collaborative system among enterprises it expects breakthrough cost savings through competitiveness, global lead time, minimizing duplication.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.49-67
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• 2015

Recently, emerging the notion of big data and social media has led us to enter data's big bang. Social networking services are widely used by people around the world, and they have become a part of major communication tools for all ages. Over the last decade, as online social networking sites become increasingly popular, companies tend to focus on advanced social media analysis for their marketing strategies. In addition to social media analysis, companies are mainly concerned about propagating of negative opinions on social networking sites such as Facebook and Twitter, as well as e-commerce sites. The effect of online word of mouth (WOM) such as product rating, product review, and product recommendations is very influential, and negative opinions have significant impact on product sales. This trend has increased researchers' attention to a natural language processing, such as a sentiment analysis. A sentiment analysis, also refers to as an opinion mining, is a process of identifying the polarity of subjective information and has been applied to various research and practical fields. However, there are obstacles lies when Korean language (Hangul) is used in a natural language processing because it is an agglutinative language with rich morphology pose problems. Therefore, there is a lack of Korean natural language processing resources such as a sentiment lexicon, and this has resulted in significant limitations for researchers and practitioners who are considering sentiment analysis. Our study builds a Korean sentiment lexicon with collective intelligence, and provides API (Application Programming Interface) service to open and share a sentiment lexicon data with the public (www.openhangul.com). For the pre-processing, we have created a Korean lexicon database with over 517,178 words and classified them into sentiment and non-sentiment words. In order to classify them, we first identified stop words which often quite likely to play a negative role in sentiment analysis and excluded them from our sentiment scoring. In general, sentiment words are nouns, adjectives, verbs, adverbs as they have sentimental expressions such as positive, neutral, and negative. On the other hands, non-sentiment words are interjection, determiner, numeral, postposition, etc. as they generally have no sentimental expressions. To build a reliable sentiment lexicon, we have adopted a concept of collective intelligence as a model for crowdsourcing. In addition, a concept of folksonomy has been implemented in the process of taxonomy to help collective intelligence. In order to make up for an inherent weakness of folksonomy, we have adopted a majority rule by building a voting system. Participants, as voters were offered three voting options to choose from positivity, negativity, and neutrality, and the voting have been conducted on one of the largest social networking sites for college students in Korea. More than 35,000 votes have been made by college students in Korea, and we keep this voting system open by maintaining the project as a perpetual study. Besides, any change in the sentiment score of words can be an important observation because it enables us to keep track of temporal changes in Korean language as a natural language. Lastly, our study offers a RESTful, JSON based API service through a web platform to make easier support for users such as researchers, companies, and developers. Finally, our study makes important contributions to both research and practice. In terms of research, our Korean sentiment lexicon plays an important role as a resource for Korean natural language processing. In terms of practice, practitioners such as managers and marketers can implement sentiment analysis effectively by using Korean sentiment lexicon we built. Moreover, our study sheds new light on the value of folksonomy by combining collective intelligence, and we also expect to give a new direction and a new start to the development of Korean natural language processing.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Journal of Technology Innovation
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• v.22 no.4
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• pp.235-259
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• 2014

New product or new technology developments are directly linked to a firm's survival and thus their performance and improvement are gaining attention in the midst of rapidly changing business environment and aggravating competition. However, despite SMEs' significance in the national economy, they are limited in terms of size and resources in possession, so the government provides a variety of supports as a policy. According to a study on the organizational life cycle, a firm's limits and difficulties differ by growth stage, so the supports need to be tailored. Based on the data from 2,575 firms that responded to the "2011 SMEs Technological Statistics," how technological capability level and deviation in the R&D process affect the R&D sales performance was studied. The result of analysis revealed that the technological capability has a positive impact on the R&D sales performance. It was also learned that the relationship between deviation in the technological capability and R&D sales performance was moderated by the government support. For the hypothesis that the government support would have a different moderating effect by growth stage for the impact the technology level has on the R&D sales performance, the empirical analysis showed a different meaningful moderating effect for each growth stage. The theoretical implications of the study are that, instead of a simple relation of dynamics that does not take the growth stages into account, it suggested a more realistic causal relationship model that reflects the complex environment the SMEs are in and that the need for measuring and using the deviation in technological capability as a research variable has been justified. The practical implications are that the government policy for supports can be tailored to a growth stage and that the guidelines have been suggested to effectively use the government funding by encouraging the SMEs in a different growth stage to adapt to the customized policy.

• Journal of the Korean Society of Food Science and Nutrition
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• v.46 no.1
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• pp.46-55
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• 2017

In this study, extracts of gamma-irradiated Aralia continentalis for health and beauty food resources were examined on antioxidant activities and increasing extraction yield. In photostimulated luminescence analysis, non-irradiated (0 kGy) sample showed an intermediate result of 891.00 photon counts (PCs), whereas irradiated (5 and 10 kGy) samples showed positive results of 79,956.67 and 282,498.67 PCs, respectively. The thermoluminescence ratio of non-irradiated samples was 0.018, whereas the values of irradiated samples (5 and 10 kGy) were 0.395 and 0.464, respectively. Electron spin resonance (ESR) analysis as a physical technique for irradiation identification of Aralia continentalis showed a pair of peaks on a space of 6.0 mT in the symmetric ESR spectrums. For phenolics of gamma-irradiated Aralia continentalis, water extracts had the highest amounts of 7.61 mg/g at non-irradiated condition (0 kGy) while 50% ethanol extracts had the highest amounts of 6.86 mg/g at 10 kGy irradiation. 2,2-Diphenyl-1-picrylhydrazyl scavenging activity of water and 50% ethanol extracts from non-irradiated and irradiated Aralia continentalis were very high (94.99~100.00%). 2,2'-Azinobis-(3-ethylbenzothiazoline-6-sulfonic acid) radical cation inhibitory activity was over 95.00% at $200{\mu}g/mL$ phenolics. Antioxidant protection factor (PF) showed a very high level of activity (1.38~2.51 PF). Thiobarbituric acid reactive substance inhibitory activity was high (70% and 95%, respectively). Thus, treatment of gamma irradiation can be used as a method of storage for long-term preservation of Oriental medicine.

• Journal of Korean Society of Forest Science
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• v.89 no.5
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• pp.666-676
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• 2000

For the study of morphological variation of Q. variabilis natural population in Korea, 19 populations were selected through the country in considering latitude, longitude, and geographical characters. Thirty trees were randomly selected from each population and 60 mature leaves were sampled from each tree. Four characters (leaf blade length, maximum blade width, petiole length, and vein number) were measured, and their ratios (the ratio of blade length to maximum blade width, the ratio of blade length to petiole length, the ratio of petiole length to vein number, upper 1/3 blade width to maximum blade width, and upper 1/3 blade width to lower 1/3 blade width) were calculated. 1. Analysis of variance for all leaf characters were significantly different among populations and among individuals within population. Contributions of variance among individuals within population in all the characters were higher than those among populations. Therefore, selection of plus trees may be preferable to desirable populations for breeding program of Q. variabilis. 2. Among principal component analysis for leaf characters, primary 2 principal components appeared to be major variables for leaf form of Q. variabilis because of the loading contribution of 80.5%. The first contribution component was petiole length/vein number and petiole length ; the second one was upper 1/3 blade width/maximum blade width, upper blade width/lower 1/3 blade width and vein number, respectively. 3. Latitude was positively correlated with blade length/maximum blade width and blade length/petiole length, but negatively correlated with petiole length/vein number, upper 1/3 blade width/maximum blade width, upper 1/3 blade width/lower 1/3 blade width, petiole length, and vein number. But, for longitude and altitude the former two traits and the later five traits exhibited the negative and positive correlation, respectively. 4. Cluster analysis using complete linkage method for leaf characters showed two groups to Euclidean distance 1.6. They were group I of population 1. 4, 5, and 13 and group II of population 2, 3, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 17, 18, and 19. However, group II was divided again to Euclidean distance 1.3, that is a group including population 3, 7, 10, 14, 15, and 17(group II-1) and the other group comprising population 2, 6, 8, 9, 11, 12, 16, 18, and 19(group II-2). This cluster could be mainly observed due to difference among population in aspect (group I : NE, group II-1 : SE, and group II-2 : SW).

• Journal of Korean Society of Forest Science
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• v.84 no.2
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• pp.239-246
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• 1995

This research aimed at the contribution to obtaining the scientifical data which were required for planning she environmentally sound and sustainable management, particularly in the field of the logging road construction. Main natural environmental variables including natural vegetation, rainfall, soil runoff were measured in the logging road on-sites and analysed. This project was carried out at the (mt.)Paekunsan Research sorest of Seoul National University, located in Gwangyang, Chollanam-do in southern part of Korea, from 1993 to 1994. 1. The explanatory variables for erosion and sedimentation on logging road surface were accumulated rainfall, erosion distance, cross-sectional gradient, and soil hardness. The erosion and sedimentation on logging road was increasing positively in proportion to the accumulated rainfall, soil distance from starting point of the logging road, and cross-sectional gradient. 2. On cut-slope of logging road, cut-slope shape, part of the slope, plant coverage, soil hardness, sand content, accumulated rainfall, clay content, and silt content were effective factors. Cut-slope erosion and sedimentation on logging roam increased as with the lower plant coverage, the lower accumulated rainfall, the high sand content in the soil. 3. On fill-slope of logging road, there were three significant variables such as total rainfall and number of rainfall-storm. Fill-slope erosion and sedimentation had a positive correlation with the amount of rainfall, the number of rainfall, the soil hardness. 4. The total erosion and sedimentation on logging road were $5.04{\times}10^{-2}m^2/m^2$ in logging road construction year, $7.37{\times}10^{-2}m^2/m^2$ in next year. The erosion and sedimentation on logging road surface were 32.7% of total erosion and sedimentation on Logging road in construction year, and 57.1% in next year, respectively. The erosion and sedimentation on cut-slopes were 30.4% on logging road in construction year, fill-slopes of total erosion and sedimentation and 21.0% in next year, respectively. The erosion and sedimentation on fill-slopes were 36.9% on logging road in construction year, 21.9 in next year. To decrease the erosion and sedimentation at the logging road from the beginning stage of construction, the effective revegetation works should be implemented on the cut-slope and fill slopes, and erosion control measures such as optima. road design must be constructed on read surface.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.3
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• pp.1-16
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• 2012

Under the international business circumstance, global supply chain management is considered a vital strategic challenge to small and medium-sized enterprises(SMEs) suffering from deficient resources and capabilities to exploit overseas markets comparing with large corporations. That is because they can expand their business domains into overseas markets by establishing strategic alliances with global supply chain partners. Although a wide range of previous researches have emphasized the cooperative networks in the chain, most are ignoring the importance of developing relational characteristics such as trust and reciprocity with the partners. Besides, verifying the relational factors influencing firms' export performances, some studies proposed different and inconsistent factors. According to the social capital theory, which is the social quality and networks facilitating close cooperation of inter-individual and inter-organization, provides the integrated view to identify the relational characteristics in the aspects of network, trust and reciprocal norm. Meanwhile, a number of researchers shows that global entrepreneurship is the internal and intangible resource necessary to promote SMEs' internationalization. Upon closer examination, however, they cannot explain clearly its influencing mechanism in the inter-firm cooperative relationships. This study is to verify the effect of social capital accumulated within global supply chain on SMEs' qualitative and quantitative export performance. In addition, we shed new light on global entrepreneurship expected to be concerned with the formation of social capital and the enhancement of export performances. For this purpose, the questionnaires, developed through literature review, were collected from 192 Korean SMEs affiliated in Korean Medium Industries Association and Global Chief Executive Officer's Club focusing on their memberships' international business. As a result of multi-regression analysis, the social capital - network, trust and reciprocal norm shared with global supply chain partner - as well as global entrepreneurship - innovativeness, proactiveness and risk-taking - have positive effect on SMEs' export performances. Also global entrepreneurship affects positively social capital which has mediating effect partially in the relationship between global entrepreneurship and performances. These results means that there is a structural process - global entrepreneurship(input), social capital(output), and export performances(outcome). In other words, a firm should consistently invest in and develop the social capital with global supply chain partners in order to achieve common goals, establish strategic collaborations and obtain long-term export performances. Furthermore, it is required to foster the global entrepreneurship in an organization so as to build up the social capital. More detailed practical issues and discussion are made in the conclusion.

• Korean Journal of Soil Science and Fertilizer
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• v.25 no.3
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• pp.231-241
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• 1992

To study the relationships between major micrometeorological elements and their influences on evapotranspiration(ET) in the canopy of two rice cultivars, Daecheongbyo and Samgangbyo, synoptic meteorological factors, micrometeorological elements and ET from the canopy and biomass production were observed at various growth stages in the paddy field of Suwon Weather Forcast Office in 1989. ET from the rice community was highly correlated with the following factors in order of pan evaporation>air temperature>leaf temperature>solar radiation>sunshine duration>difference in vapor pressure depicit(VPD)>water temperature. ET observed showed higher correlation with the evaporation from small pan than that from Class A pan. Varietal difference would be noted in the relationships between ET in Samgangbyo canopy and the evaporations observed from the pans, with which closer a correlation was found in Samgangbyo than in Daecheongbyo. The ratio of canopy ET to the evaporation from Class A pan was maintained over 1.0 through the growth stages with the maximum of 1.9 at the late August. The evaporation observed from Class A pan was amounted to 71.9% of that from small pan. ET was better correlated with solar radiation than with net radiation which reached about 66% of solar radiation. Maximum temperature showed higher correlation with ET than mean air temperature, and also wind speed of 1m above ground revealed positive correlation. The relative humidity, however, had no correlation with the exception of ET in rainy days. A regression model developed to estimate ET as a function of meteorological elements being described with $R^2$ of 0.607 as : $ET=-5.3594+0.7005Pan\;A+0.1926T_{mean}+0.0878_{sol}+0.025RH$.

• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.6
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• pp.759-765
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• 2012

This study was performed to investigate improvements in diabetes mellitus by extracts of yacon in streptozotocin (STZ)-induced diabetic rats. Fifty rats were divided into a normal group and four experimental groups. STZ (45 mg/kg) was injected intraperitoneally to induce type I diabetes in the four experimental groups. Yacon extracts were administered for 5 weeks. Forty-five ICR mice were also divided into one positive control group and four experimental groups for the oral glucose tolerance test (OGTT) after fed yacon extract. The control group did not eat any yacon extracts, while Group 1 (GI) was fed 125 mg/kg of yacon extracts, Group 2 (GII) was fed 250 mg/kg of yacon extracts, and Group 3 (GIII) was fed 500 mg/kg of yacon extracts. After treatment for 5 weeks, blood glucose in GIII group showed decreased tendency at the 5 week. In OGTT by glucose, the glucose level of yacon treatment group in diabetic rats was significantly decreased compared to the glucose level of the control group, but there was no difference in OGTT by maltose. In ICR mice, the glucose level of the experimental group in OGTT by maltose was significantly decreased compared to the control group. The area of the islets of Langerhans was increased by yacon treatment in a dose-dependent manner on diabetic rats. Insulin concentration of the GIII group was also decreased compared to the control group, while the concentration of fructosamine, total cholesterol, and triglycerides in serum showed no difference. OGTT by glucose or maltose in ICR mice or diabetic rats, area of the Islets of Langerhans, and insulin concentration improved. Yacon treatment may be a useful therapeutic and preventive strategy for diabetes mellitus.