• Asia pacific journal of information systems
• /
• v.19 no.4
• /
• pp.125-148
• /
• 2009

UGC(User Generated Contents) is emerging as the center of e-business in the web 2.0 era. The trend reflects changing roles of users in production and consumption of contents on websites and helps us to understand new strategies of websites such as web portals and social network websites. Nowadays, we consume contents created by other non-professional users for both utilitarian (e.g., knowledge) and hedonic values (e.g., fun). Also, contents produced by ourselves (e.g., photo, video) are posted on websites so that our friends, family, and even the public can consume those contents. This means that non-professionals, who used to be passive audience in the past, are now creating contents and share their UGCs with others in the Web. Accessible media, tools, and applications have also reduced difficulty and complexity in the process of creating contents. Realizing that users create plenty of materials which are very interesting to other people, media companies (i.e., web portals and social networking websites) are adjusting their strategies and business models accordingly. Increased demand of UGC may lead to website visits which are the source of benefits from advertising. Therefore, they put more efforts into making their websites open platforms where UGCs can be created and shared among users without technical and methodological difficulties. Many websites have increasingly adopted new technologies such as RSS and openAPI. Some have even changed the structure of web pages so that UGC can be seen several times to more visitors. This mainstream of UGCs on websites indicates that acquiring more UGCs and supporting participating users have become important things to media companies. Although those companies need to understand why general users have shown increasing interest in creating and posting contents and what is important to them in the process of productions, few research results exist in this area to address these issues. Also, behavioral process in creating video UGCs has not been explored enough for the public to fully understand it. With a solid theoretical background (i.e., theory of implementation intentions), parts of our proposed research model mirror the process of user behaviors in creating video contents, which consist of intention to upload, intention to edit, edit, and upload. In addition, in order to explain how those behavioral intentions are developed, we investigated influences of antecedents from three motivational perspectives (i.e., intrinsic, editing software-oriented, and website's network effect-oriented). First, from the intrinsic motivation perspective, we studied the roles of self-expression, enjoyment, and social attention in forming intention to edit with preferred editing software or in forming intention to upload video contents to preferred websites. Second, we explored the roles of editing software for non-professionals to edit video contents, in terms of how it makes production process easier and how it is useful in the process. Finally, from the website characteristic-oriented perspective, we investigated the role of a website's network externality as an antecedent of users' intention to upload to preferred websites. The rationale is that posting UGCs on websites are basically social-oriented behaviors; thus, users prefer a website with the high level of network externality for contents uploading. This study adopted a longitudinal research design; we emailed recipients twice with different questionnaires. Guided by invitation email including a link to web survey page, respondents answered most of questions except edit and upload at the first survey. They were asked to provide information about UGC editing software they mainly used and preferred website to upload edited contents, and then asked to answer related questions. For example, before answering questions regarding network externality, they individually had to declare the name of the website to which they would be willing to upload. At the end of the first survey, we asked if they agreed to participate in the corresponding survey in a month. During twenty days, 333 complete responses were gathered in the first survey. One month later, we emailed those recipients to ask for participation in the second survey. 185 of the 333 recipients (about 56 percentages) answered in the second survey. Personalized questionnaires were provided for them to remind the names of editing software and website that they reported in the first survey. They answered the degree of editing with the software and the degree of uploading video contents to the website for the past one month. To all recipients of the two surveys, exchange tickets for books (about 5,000~10,000 Korean Won) were provided according to the frequency of participations. PLS analysis shows that user behaviors in creating video contents are well explained by the theory of implementation intentions. In fact, intention to upload significantly influences intention to edit in the process of accomplishing the goal behavior, upload. These relationships show the behavioral process that has been unclear in users' creating video contents for uploading and also highlight important roles of editing in the process. Regarding the intrinsic motivations, the results illustrated that users are likely to edit their own video contents in order to express their own intrinsic traits such as thoughts and feelings. Also, their intention to upload contents in preferred website is formed because they want to attract much attention from others through contents reflecting themselves. This result well corresponds to the roles of the website characteristic, namely, network externality. Based on the PLS results, the network effect of a website has significant influence on users' intention to upload to the preferred website. This indicates that users with social attention motivations are likely to upload their video UGCs to a website whose network size is big enough to realize their motivations easily. Finally, regarding editing software characteristic-oriented motivations, making exclusively-provided editing software more user-friendly (i.e., easy of use, usefulness) plays an important role in leading to users' intention to edit. Our research contributes to both academic scholars and professionals. For researchers, our results show that the theory of implementation intentions is well applied to the video UGC context and very useful to explain the relationship between implementation intentions and goal behaviors. With the theory, this study theoretically and empirically confirmed that editing is a different and important behavior from uploading behavior, and we tested the behavioral process of ordinary users in creating video UGCs, focusing on significant motivational factors in each step. In addition, parts of our research model are also rooted in the solid theoretical background such as the technology acceptance model and the theory of network externality to explain the effects of UGC-related motivations. For practitioners, our results suggest that media companies need to restructure their websites so that users' needs for social interaction through UGC (e.g., self-expression, social attention) are well met. Also, we emphasize strategic importance of the network size of websites in leading non-professionals to upload video contents to the websites. Those websites need to find a way to utilize the network effects for acquiring more UGCs. Finally, we suggest that some ways to improve editing software be considered as a way to increase edit behavior which is a very important process leading to UGC uploading.

• Korean Journal of Soil Science and Fertilizer
• /
• v.43 no.4
• /
• pp.407-414
• /
• 2010

Until now, the pore size distribution, PSD, of soil profile has been calculated from soil moisture characteristic data by water release method or mercury porosimetry using the capillary rise equation. But the current methods are often difficult to use and time consuming. Thus, in this work, theoretical framework for an easy and fast technique was suggested to estimate the PSD from unsaturated hydraulic conductivity data in an undisturbed field soil profile. In this study, unsaturated hydraulic conductivity data were collected and simulated by the variation of soil parameters in the given boundary conditions (Brooks and Corey soil parameters, ${\alpha}_{BC}=1-5L^{-1}$, b = 1 - 10; van Genuchten soil parameters, ${\alpha}_{VG}=0.001-1.0L^{-1}$, m = 0.1 - 0.9). Then, $K_s$ (1.0 cm $h^{-1})$ was used as the fixed input parameter for the simulation of each models. The PSDs were estimated from the collected K(h) data by model simulation. In the simulation of Brooks-Corey parameter, the saturated hydraulic conductivity, $K_s$, played a role of scaling factor for unsaturated hydraulic conductivity, K(h) Changes of parameter b explained the shape of PSD curve of soil intimately, and a ${\alpha}_{BC}$ affected on the sensitivity of PSD curve. In the case of van Genuchten model, $K_s$ and ${\alpha}_{VG}$ played the role of scaling factor for a vertical axis and a horizontal axis, respectively. Parameter m described the shape of PSD curve and K(h) systematically. This study suggests that the new theoretical technique can be applied to the in situ prediction of PSD in undisturbed field soil.

• Tuberculosis and Respiratory Diseases
• /
• v.64 no.4
• /
• pp.266-271
• /
• 2008

Background: Estimation of the probability of a patient having an acute pulmonary embolism (PE) for patients with a suspected PE are well established in North America and Europe. However, an assessment of the prediction rules for a PE has not been clearly defined in Korea. The aim of this study is to assess the prediction rules for patients with a suspected PE in Korea. Methods: We performed a retrospective study of 210 inpatients or patients that visited the emergency ward with a suspected PE where computed tomography pulmonary angiography was performed at a single institution between January 2005 and March 2007. Simplified Wells rules and revised Geneva rules were used to estimate the clinical probability of a PE based on information from medical records. Results: Of the 210 patients with a suspected PE, 49 (19.5%) patients had an actual diagnosis of a PE. The proportion of patients classified by Wells rules and the Geneva rules had a low probability of 1% and 21%, an intermediate probability of 62.5% and 76.2%, and a high probability of 33.8% and 2.8%, respectively. The prevalence of PE patients with a low, intermediate and high probability categorized by the Wells rules and Geneva rules was 100% and 4.5% in the low range, 18.2% and 22.5% in the intermediate range, and 19.7% and 50% in the high range, respectively. Receiver operating characteristic curve analysis showed that the revised Geneva rules had a higher accuracy than the Wells rules in terms of detecting PE. Concordance between the two prediction rules was poor ($\kappa$ coefficient=0.06). Conclusion: In the present study, the two prediction rules had a different predictive accuracy for pulmonary embolisms. Applying the revised Geneva rules to inpatients and emergency ward patients suspected of having PE may allow a more effective diagnostic process than the use of the Wells rules.

• Cartoon and Animation Studies
• /
• s.33
• /
• pp.597-616
• /
• 2013

Character industry is not only knowledge-based industry chiefly with copyrights but also motive power for creative economy to take a role functionally over the fields of industries because it has industrial characteristic as complement product to promote sale value in manufacturing industry and service industry and increase profit on sales. Since 2003, the national policy related to character has aimed to maximize effect among connected industries, extend its business abroad, enforce copyrights through the improvement of marketing system, develop industrial infrastructure through raising quality of character products. With the result of this policy, the successful cases of connected contents have been crystallized and domestic character industry has stepped up methodically since 2007. It is needed to reset the scales of character industry and industrial stats because there are more know-how of self industry promotion and more related characters through strategy of market departmentalization starting with cartoon, animation, games, novels, movies and musicals. Especially, The Korea government set our target for 'Global Top Five Character Power' since 2009 and has started to carry out to find global star characters, support to establish network among connected industries, diversify promotion channels, and develop licensing business. Particularly, since 2013, There have been prospered the indoor character theme park with time management just like character experimental marketing or Kids cafes using characters, the demand market of digital character focusing on SNS emoticon, and the performance market for character musical consistently. Moreover, The domestic and foreign illegal black markets on off-line have been enlarged, so we need another policy alternative. To prepare for the era of exploding character demand market and diversifying platform, it is needed to set up a solid strategy that is required the elements of policy changes in character industry to vitalize character industry and support new character design and connected contents. the following shows that the elements of policy changes related to the existing policy, the current position of market. Nowadays, the elements of policy changes in domestic character industry are that variety of consumers in the digital character market according to platform diversification, Convergence contents of character goods for the Korean waves, legalization of the illegal black contents market, and controling the tendency of consumers in departmentalized market. This can help find the policy issue entirely deferent with the existing character powers like US, Japan or Europe. In its final analysis, the alternatives are the promotion of models with contract copyrights of domestic and foreign connected contents, the diversification of profit models of platform economy, the additive development of target market related to enlarging the Korean waves, and the strategy of character market for the age-specific tendency according to developing character demand market.

• Journal of Intelligence and Information Systems
• /
• v.17 no.4
• /
• pp.109-130
• /
• 2011

One of the major problems in the area of data mining is the size of the data, as most data set has huge volume these days. Streams of data are normally accumulated into data storages or databases. Transactions in internet, mobile devices and ubiquitous environment produce streams of data continuously. Some data set are just buried un-used inside huge data storage due to its huge size. Some data set is quickly lost as soon as it is created as it is not saved due to many reasons. How to use this large size data and to use data on stream efficiently are challenging questions in the study of data mining. Stream data is a data set that is accumulated to the data storage from a data source continuously. The size of this data set, in many cases, becomes increasingly large over time. To mine information from this massive data, it takes too many resources such as storage, money and time. These unique characteristics of the stream data make it difficult and expensive to store all the stream data sets accumulated over time. Otherwise, if one uses only recent or partial of data to mine information or pattern, there can be losses of valuable information, which can be useful. To avoid these problems, this study suggests a method efficiently accumulates information or patterns in the form of rule set over time. A rule set is mined from a data set in stream and this rule set is accumulated into a master rule set storage, which is also a model for real-time decision making. One of the main advantages of this method is that it takes much smaller storage space compared to the traditional method, which saves the whole data set. Another advantage of using this method is that the accumulated rule set is used as a prediction model. Prompt response to the request from users is possible anytime as the rule set is ready anytime to be used to make decisions. This makes real-time decision making possible, which is the greatest advantage of this method. Based on theories of ensemble approaches, combination of many different models can produce better prediction model in performance. The consolidated rule set actually covers all the data set while the traditional sampling approach only covers part of the whole data set. This study uses a stock market data that has a heterogeneous data set as the characteristic of data varies over time. The indexes in stock market data can fluctuate in different situations whenever there is an event influencing the stock market index. Therefore the variance of the values in each variable is large compared to that of the homogeneous data set. Prediction with heterogeneous data set is naturally much more difficult, compared to that of homogeneous data set as it is more difficult to predict in unpredictable situation. This study tests two general mining approaches and compare prediction performances of these two suggested methods with the method we suggest in this study. The first approach is inducing a rule set from the recent data set to predict new data set. The seocnd one is inducing a rule set from all the data which have been accumulated from the beginning every time one has to predict new data set. We found neither of these two is as good as the method of accumulated rule set in its performance. Furthermore, the study shows experiments with different prediction models. The first approach is building a prediction model only with more important rule sets and the second approach is the method using all the rule sets by assigning weights on the rules based on their performance. The second approach shows better performance compared to the first one. The experiments also show that the suggested method in this study can be an efficient approach for mining information and pattern with stream data. This method has a limitation of bounding its application to stock market data. More dynamic real-time steam data set is desirable for the application of this method. There is also another problem in this study. When the number of rules is increasing over time, it has to manage special rules such as redundant rules or conflicting rules efficiently.

• The Korean Journal of Nuclear Medicine
• /
• v.32 no.1
• /
• pp.32-49
• /
• 1998

For estimation of regional myocardial blood flow with O-15 water PET, a few modifications considering partial volume effect based on single compartment model have been proposed. In this study, we attempted to quantify the degree of heterogeneity and to show the effect of tissue flow heterogeneity on partition coefficient(${\lambda}$) and to find the relation between perfusable tissue index(PTI) and ${\lambda}$ by computer simulation using two modified models. We simulated tissue curves for the regions with homogeneous and heterogeneous blood flow over a various flow range(0.2-4.0ml/g/min). Simulated heterogeneous tissue composed of 4 subregions of the same or different size of block which have different homogeneous flow and different degree of slope of distribution of blood flow. We measured the index representing heterogeneity of distribution of blood flow for each heterogeneous tissue by the constitution heterogeneity(CH). For model I, we assumed that tissue recovery coefficient ($F_{MME}$) was the product of partial volume effect($F_{MMF}$) and PTI. Using model I, PTI, flow, and $F_{MM}$ were estimated. For model II, we assumed that partition coefficient was another variable which could represent tissue characteristics of heterogeneity of flow distribution. Using model II, PTI, flow and ${\lambda}$ were estimated. For the simulated tissue with homogeneous flow, both models gave exactly the same estimates, of three parameters. For the simulated tissue with heterogeneous flow distribution, in model I, flow and $F_{MM}$ were correctly estimated as CH was increased moderately. In model II, flow and ${\lambda}$ were decreased curvi-linearly as CH was increased. The degree of underestimation of ${\lambda}$ obtained using model II, was correlated with CH. The degree of underestimation of flow was dependent on the degree of underestimation of ${\lambda}$. PTI was somewhat overestimated and did not change according to CH. We conclude that estimated ${\lambda}$ reflect the degree of tissue heterogeneity of flow distribution. We could use the degree of underestimation of ${\lambda}$ to find the characteristic heterogeneity of tissue flow and use ${\lambda}$ to recover the underestimated flow.

• Korean Journal of Heritage: History & Science
• /
• v.53 no.1
• /
• pp.150-167
• /
• 2020

The purpose of this paper is to share the status and introduce a scientific analysis of the GeumguJagi (gilt-silver overlay porcelain, 金釦瓷器) excavated from Seongneung (石陵). This analysis aimed to highlight the GeumguJagi excavated from the Royal Tombs of Goryeo with a clear lower year (1237) and to aid research into the GeumguJagi. In 2001, the National Institute of Cultural Heritage excavated and investigated Seongneung in Heejong (熙宗). Various artifacts such as celadon, gold, bronze, and iron products were collected from the chambers inside of the tomb. There were a total of 160 celadon items including bowls, dishes, glasses, and saucers. Of those, there were 58 celadon items (including fragments) with metal frames on the openings. These consisted of bowls, plates, lids, and saucers. Until recently, in various exhibitions and papers, only one GeumguJagi was known to have been excavated from Seongneung, which was a . However, the survey identified a number of further GeumguJagis. It had been understood from inherited and excavated products that the materials used for ornaments were restricted to high-quality celadon. However, this study confirmed that the excavation of Seongneung demonstrated the use of various other materials for different models and qualities of GeumguJagis. It can be said that it is characteristic that various models and quality are confirmed together through the excavation of Seongneung. A scientific analysis was carried out that selected 12 of 58 products excavated from Seongneung. Results showed that the main component used for Geumgu ornaments was tin (Sn), and trace amounts of copper (Cu) and lead (Pb) were also commonly identified. When analyzing the material used to affix the metal fittings, this was found to be glue (膠) made from animal skins, muscle, and bones. This pattern matches that of the GeumguJagi excavated from Paju Hyeeumwonji, and the reason for this could be assumed on the basis of the contents of the 『Cheongonggaemul (天工開物)』 written by Song Ongsung (宋應星) during the Ming Dynasty. At that time, metals such as tin and copper would have been difficult to obtain. 『Xuānhwafengshi Gaolitujing (宣和奉使高麗圖經)』 shows that the use of metal was limited to certain classes; thus, the use of the GeumguJagi seems to have been centered around the royal family.

• Journal of Animal Science and Technology
• /
• v.48 no.2
• /
• pp.151-160
• /
• 2006

This study was conducted to investigate the genetic characteristics of growth stages in Hanwoo, to provide useful information in farm management decisions. Data were taken from the nucleus herds of three farms, Namwon, Daegwalyong and Seosan, comprising 27,647 cows, 14,744 bulls, and 1,290 steers in between 1980 and 2004. According to the growth curve by year, the residuals for cows and bulls were 68.49 and 54.29, respectively, under the Gompertz model. The values were lower than in other years. Parameters, A, b and k were estimated as 423.6±5.8, 2.387±0.064 and 0.0908±0.0033 in cows and 823.3±15.3, 3.584±0.070, 0.1139±0.0032 in bulls, respectively. The fitness was higher under the Gompertz model than under the logistic model: monthly and daily estimation for cows were 379.3±7.509, 2.499±0.057, 0.114±0.0045 and 367.1±1.9003, 2.3983±0.012, 0.004±0.00003, respectively. Estimated residual mean squares were 31.85 and 998.4 in their respective models. Monthly and daily estimation of bulls were 834.6±22.00, 3.319±0.062, 0.104±0.0037 and 796.0±6.128, 3.184±0.014, 0.003±0.00003, respectively. Estimated residual mean square were 66.18 and 2106.5. Monthly and daily estimation of steers were 1049.1±144.2, 3.024±0.008, 0.067±0.0096 and 1505.1±176.6, 2.997±0.067, 0.001±0.0001, relatively. Squares, 186.0 and 1119.1. In terms of growth characteristic estimated by Gompertz model, body weight for cows and bulls were 139.53kg and 307.03kg, and the daily gains were 0.52kg and 1.04kg, respectively. Body weight for steers was 385.94kg at the inflection point. Body weight gain was 0.84kg in both models. Our results showed that cows had lower mature weight and daily weight gain, and reached the inflection point earlier than bulls or steers.

• Journal of Intelligence and Information Systems
• /
• v.29 no.1
• /
• pp.121-142
• /
• 2023

As the number and weight of imported food are steadily increasing, safety management of imported food to prevent food safety accidents is becoming more important. The Ministry of Food and Drug Safety conducts on-site inspections of foreign food facilities before customs clearance as well as import inspection at the customs clearance stage. However, a data-based safety management plan for imported food is needed due to time, cost, and limited resources. In this study, we tried to increase the efficiency of the on-site inspection by preparing a machine learning prediction model that pre-selects the companies that are expected to fail before the on-site inspection. Basic information of 303,272 foreign food facilities and processing businesses collected in the Integrated Food Safety Information Network and 1,689 cases of on-site inspection information data collected from 2019 to April 2022 were collected. After preprocessing the data of foreign food facilities, only the data subject to on-site inspection were extracted using the foreign food facility_code. As a result, it consisted of a total of 1,689 data and 103 variables. For 103 variables, variables that were '0' were removed based on the Theil-U index, and after reducing by applying Multiple Correspondence Analysis, 49 characteristic variables were finally derived. We build eight different models and perform hyperparameter tuning through 5-fold cross validation. Then, the performance of the generated models are evaluated. The research purpose of selecting companies subject to on-site inspection is to maximize the recall, which is the probability of judging nonconforming companies as nonconforming. As a result of applying various algorithms of machine learning, the Random Forest model with the highest Recall_macro, AUROC, Average PR, F1-score, and Balanced Accuracy was evaluated as the best model. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the selection reason for nonconforming facilities of individual instances, and discuss applicability to the on-site inspection facility selection system. Based on the results of this study, it is expected that it will contribute to the efficient operation of limited resources such as manpower and budget by establishing an imported food management system through a data-based scientific risk management model.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.17 no.1
• /
• pp.121-137
• /
• 2022

The purpose of this study is to present the necessary success factors and strategies for high-tech social ventures and stakeholders in the related ecosystem by empirically identifying factors that affect their sustainable performance. Based on prior research, the dimensions of three performance factors were presented: core technology competency, core business competency, and social mission orientation. Then, such sub-dimensions such as technology innovation orientation, R&D capability, business model, customer orientation, social network, and social mission pursuit were derived. For empirical analysis, a survey was conducted on domestic high-tech social ventures, and the significance of the hypothesis was tested through PLS-structural equation analysis of the collected 243 valid data. As a result, it was found that the technology innovation orientation was embedded as an abstract organizational and cultural characteristic in the high-tech social venture, which is a research sample, and thus did not significantly affect the dependent variable. In other words, aiming for the latest cutting-edge technology alone cannot affect performance, and it is a result of proving the need for substantial influencing factors that can strengthen it. On the other hand, the business model had a significant effect only on social performance, which is presumed to be the limitation of measurement tools developed for social enterprises, and the results of additional multi-group analysis to determine the cause also supported the basis for this estimation. Excluding the previous two performance factors, R&D competency, customer orientation, social network, and social mission pursuit were all found to have a significant positive (+) effect on social and economic performance. This study laid a foundation for related research by identifying high-tech social ventures emerging in the ecosystem of a social economy and expanded empirical research models related to the performance of existing social enterprises and social ventures. However, in the research method or process, there were limitations such as factor derivation or verification for balance of dual performance, subjective measurement method, and sample representativeness. It is expected that more in-depth follow-up studies will continue by supplementing future limitations and designing improved research models.