• Management & Information Systems Review
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• v.37 no.1
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• pp.139-154
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• 2018

R programming is free and open source system associated with a rich and ever-growing set of libraries of functions developed and submitted by independent end-users. It is recognized as a popular tool for handling big data sets and analyzing them. Reflecting these characteristics, R has been gaining popularity from data analysts. However, the antecedents of R technology acceptance has not been studied yet. In this study we identify and investigates cognitive factors contributing to build user acceptance toward R in education environment. We extend the existing technology acceptance model by incorporating social norms and software capability. It was found that the factors of subjective norm, perceived usefulness, ease of use affect positively on the intention of acceptance R programming. In addition, perceived usefulness is related to subjective norms, perceived ease of use, and software capability. The main difference of this research from the previous ones is that the target system is not a stand-alone. In addition, the system is not static in the sense that the system is not a final version. Instead, R system is evolving and open source system. We applied the Technology Acceptance Model (TAM) to the target system which is a platform where diverse applications such as statistical, big data analyses, and visual rendering can be performed. The model presented in this work can be useful for both colleges that plan to invest in new statistical software and for companies that need to pursue future installations of new technologies. In addition, we identified a modified version of the TAM model which is extended by the constructs such as subjective norm and software capability to the original TAM model. However one of the weak aspects that might inhibit the reliability and validity of the model is that small number of sample size.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.3
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• pp.219-226
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• 2014

Evaluation of tree responses to temperature elevation is critical for a development of forest management techniques coping with climate change. We conducted a study on the growth responses of Betula costata, Fraxinus rhynchophylla, and Quercus variabilis seedlings to open-field artificial warming. Artificial warming set-up using infra-red heater was built in 2012 and the temperature in warmed plots was regulated to be consistently $3^{\circ}C$ higher than that of control plots. The seeds of three species were sown, and the responses of growth, biomass allocation, and net photosynthetic rate of newly-germinated seedlings on the open-field artificial warming were determined. As a result, the growth responses of the seedlings differed with the species. B. costata showed decreases in the height to diameter ratio (H/D ratio), biomass, root weight to shoot weight ratio, and net photosynthetic rate. However, root collar diameter (RCD), height, biomass, and net photosynthetic rate of Q. variabilis were increased, while the response of F. rhynchophylla was rather obscure. There was no significant difference between warmed and control plots in seedling growth for 3 species in July, whereas, RCD, height, and H/D ratio of Q. variabilis were increased and H/D ratio of B. costata was decreased in November under warming. Species-specific growth responses to warming were similar to the species-specific responses of net photosynthetic rate and biomass allocation; therefore, net photosynthetic rate and biomass allocation might attribute to growth responses to warming. Besides, a relatively obvious response in autumn compared to summer might be affected by the phenological change following artificial warming. Species-specific responses of three deciduous species to warming in this study could be applied to the development of adaptive forest management policies to climate change.

• Journal of the Korean Society of Radiology
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• v.7 no.4
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• pp.285-291
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• 2013

In this study, compare and analyze the dose distribution and availability of radiation therapy when using a different devices to TNI(Total Lymphnodal Irradiation). Test subjects(patients) are 15 people(Male 7, Female 8). Acquire CT Simulation images of the 15 people using Somatom Sansation Open 16 channel and then acquired images was transferred to each treatment planning system Pinnacle Ver 8.0 and Tomotherapy Planning System and separate the tumor tissue and normal tissues(whole lung, spinal cord, Rt kidney, Lt kidney). Tumor prescription dose was set to 750 cGy. and then Compare the Dose Compatibility, Normal Tissue's Absorbed Dose, Dose Distribution and DVH. Statistical analysis was performed SPSS Ver. 18.0 by paired sample Assay. The absorbed dose in the tumor tissue was $751.0{\pm}4.7cGy$ in tomotherapy planning, $746.9{\pm}14.1cGy$ in linac. Tomotherapy's absorbed dose in the tumor was more appropriate than linac. and These values are not statistically significant(p>0.05). Tomotherapy plan's absorbed dose in the normal tissues were less than linac's plan. This value was statistically significant(p<0.05) excepted of whole lung. In DVH, appropriated on tumor and normal tissues in tomotherapy and linac but tomotherapy's TER was better than linac. Namely, a result of Absorbed dose in tumor and normal tissue, Dose distribution pattern, DVH, Both radiation therapy devices were appropriated in radiation therapy on TER. The Linac has a short treatment time(about 15-20 min) and open space on treatment time. It cause infant and pediatric patients to receiving uncomfortable treatment. So, In this case, it will be fine that Linac based therapy was restricted use. and if the patient was cooperative, it will be show a better prognosis that Tomotherapy using Radiation Therapy.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.1
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• pp.147-159
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• 2021

After the 2020 Corona 19 pandemic, consumers' online consumption is increasing rapidly, and non-store online retail channels are showing high growth. In particular, social media is gaining its status as a social media market where direct transactions take place in the means of promoting companies' brands and products. In this study, changes in consumer behavior after the Corona 19 pandemic are different in choosing online shopping media such as existing online shopping malls and SNS markets that can be classified into open social media and closed social media when purchasing agri-food online. We tried to find out what type of product is preferred in the selection of agri-food products. For this study, demographic characteristics of consumers, perceived risk of consumers, and dietary lifestyle were set as independent variables to investigate the effect on online shopping media type and product selection. The summary of the empirical analysis results is as follows. When consumers purchase agri-food online, there are significant differences in demographic characteristics, consumer perception risks, and detailed factors of dietary lifestyle in selecting shopping channels such as online shopping malls, open social media, and closed social media. Appeared to be. The consumers who choose the open SNS market are higher in men than in women, with lower household income, and higher in consumers seeking health and taste. Consumers who choose the closed SNS market were analyzed as consumers who live in rural areas and have a high degree of risk perception for delivery. Consumers who choose existing online shopping malls have high educational background, high personal income, and high consumers seeking taste and economy. Through this study, we tried to provide practical assistance by providing a basis for judgment to farmers who have difficulty in selecting an online shopping medium suitable for their product characteristics. As a shopping channel for agri-food, social media is not a simple promotional channel, but a direct transaction. It can be differentiated from existing studies in that it is approached as a market that arises.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Journal of Korean Society of Steel Construction
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• v.10 no.3 s.36
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• pp.553-564
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• 1998

Recently, more and more steel-deck structural system for two story roads has been adopted as a solution against traffic congestion in urban area, mainly because of fast construction, reduced self-weight, higher stiffness and efficient erection compared to that of concrete decks. The main objective is to study on the unit-elective optimal type and proportioning of a rational steel-deck system for two story roads using an optimum design program specifically developed for steel-deck systems. The objective function for the optimization is formulated as a minimum cost design problem. The behavior and design constraints are formulated based on the ASD(Allowable Stress Design) criteria of the Korean Bridge Design Code. The optimum design program developed in this study consists of two steps - the first step for the optimization of the steel box or plate girder viaducts, and the second step for the optimum design of the steel-decks with closed or open ribs. A grid model is used as a structural analysis model for the optimization of the main girder system, while the analysis of the deck system is based on the Pelican-Esslinger method. The SQP(Sequential Quadratic Programming) is used as the optimization technique for the constrained optimization problem. By using a set of application examples, the rational type related to the optimized steel-deck system designs is investigated by comparing the cost effectiveness of each type. Based on the results of the investigation it may be concluded that the optimal linear box girder and deck system with closed ribs may be utilized as one of the most rational and economical viaducts in the construction of two-story roads.

• Journal of Chest Surgery
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• v.13 no.4
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• pp.346-355
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• 1980

It has been proposed that wide individual variation in response to heparin be not considered in the conventional set protocol for the control of heparin and protamine during extracorporeal circulation. In this paper, two protocol of heparin and protamine therapy were compared to assess the role of the Activated Clotting Time [ACT] in relation to heparin, protamine, and postoperative blood loss and transfusion. The study groups consisted of the 31 patients [adults 15 and children 16] anticoagulated with the conventional heparin protocol and the 31 patients [adults 15 and children 16] anticoagulated with ACT protocol during extracorporeal circulation. In the conventional heparin protocol, two mg of heparin per kg was administered initially with an additional 0.75 mg of heparin per kg every 30 minutes of extracorporeal circulation, and reversal was accomplished with protamine in a dose of 1.5 times the total milligram of heparin. In the ACT protocol, two mg of heparin per kg was administered initially with an additional dose of heparin enough to reach an ACT of 480 seconds [within safe zone 300 to 600 seconds] from the patient`s dose response curve every 1 hour of extracorporeal circulation, and reversal was done with protamine in a dose of 1.3 times the milligram of the residual heparin. The results were summarized as follows. After a dose of 2 mg per kg of heparin, the patient`s ACT varied from 240 to 600 seconds in adults and from 240 t~ 660 seconds in children. In the ACT group the total amount of heparin administered was markedly reduced when compared to the conventional group, and less protamine was required to neutralize heparin. The dose of heparin administered decreased from 7.07 [SE 0.42] mg/kg of the conventional group to 4.92 [SE 0.32] mg/k8 of the ACT group in adults and from 10.17 [SE 1.15] mg/kg to 5.23 [SE 0.24] mg/kg in children, which represent 30.4% and 48.6% decrease respectively. The dose of protamine administered for reversal decreased from 10.6 [SE 0.63] mg/kg of the conventional group to 3.35 [SE 0.35] mg/kg of the ACT group in adults and from 15.7 [SE 1.70] mg/kg to 3.26 [SE 0.27] mg/kg in children, which represent 68.4% and 79.2% respectively. The ratio of protamine to heparin administered in the conventional group was 1.50:1 in adults and 1.54:1 in children, but in the ACT group 0.68:1 in adults and 0.62:1 in children. Postoperative blood loss and transfusion revealed no statistically significant difference between the two groups. Although six patients in the conventional group and one in the ACT group needed re-exploration for continuous hemorrhage, no case of generalized oozing was encountered, and in each case a definite bleeding site was identified. Author would like emphasizing the value of the ACT protocol in controlling heparin and protamine administration during extracorporeal circulation.

• Journal of KIISE:Information Networking
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• v.34 no.5
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• pp.405-422
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• 2007

Recently, according to the network environment, there are many researches for home network. Nowadays, in home network, the method that access control policy is managed for each home device by using ACL is popular, and EAM (Extranet access management) is applied as a solution. In addition, the research about secure OS is ongoing based on open operating system and the research of user authentication mechanisms for home network using home server is also in progress. However, these researches have some problems as follows; First, the transmission scope of expected access technology in home network is wide, so unauthenticated outside terminal can access the home network. Second, user is inconvenient because user need to set the necessary information for each device. Third, user privacy and convenience are not considered. OSGi provides a service platform for heterogeneous technologies in home network environment. Here, user access control is one of the core parts which should have no problems such as above items, but there are no concrete researches yet. Thus in this paper, we propose an access control policy management framework and access control operation based on RBAC for user access control in home network environment in which OSGi service platform is operated. First, we list the consideration which is not clearly mentioned in OSGi standard, and then we solve these above problems through new framework. In addition, we propose the effective and economical operation method which reduces the policy change frequency for user access control by using RBAC concept though limited resource of home gateway. Besides, in this paper, these proposed policies are defined separately as user-role assignment policy and permission-role assignment policy, and user decide their own policies. In conclusion, we provide the scheme to enhance the user convenience and to solve the privacy problem.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.3
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• pp.240-247
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• 2001

Java is a promising runtime environment for embedded systems because it has many advantages such as platform independence, high security and support for multi-threading. One of the most famous Java run-time environments, Sun's ($PersonalJave^{TM}$) is based on Truffle architecture, which enables programmers to design various GUIs easily. For this reason, it has been ported to various embedded systems such as set-top boxes and personal digital assistants(PDA's). Basically, Truffle uses heavy-weight window managers such as Microsoft vVin32 API and X-Window. However, those window managers are not adequate for embedded systems because they require a large amount of memory and disk space. To come up with the requirements of embedded systems, we adopt Microwindows as the platform graphic system for Personal] ava A WT onto Embedded Linux. Although Microwindows is a light-weight window manager, it provides as powerful API as traditional window managers. Because Microwindows does not require any support from other graphics systems, it can be easily ported to various platforms. In addition, it is an open source code software. Therefore, we can easily modify and extend it as needed. In this paper, we implement Personal]ava A WT using Microwindows on embedded Linux and prove the efficiency of our approach.

• The Journal of Society for e-Business Studies
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• v.21 no.1
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• pp.15-32
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• 2016

Online news on the Internet, as published open data, contain facts or opinions about a specific affair and hence influences considerably on the decisions of the general publics who are interested in a particular issue. Therefore, we can predict the people's choices related with the issue by analyzing a large number of related internet news. This study aims to propose a text analysis methodto predict the outcomes of events that take place in a specific place. We used topics of the news articles because the topics contains more essential text than the news articles. Moreover, when it comes to mobile environment, people tend to rely more on the news topics before clicking into the news articles. We collected the titles of news articles and divided them into the learning and evaluation data set. Morphemes are extracted and their polarity values are identified with the learning data. Then we analyzed the sensitivity of the entire articles. As a result, the prediction success rate was 70.6% and it showed a clear difference with other analytical methods to compare. Derived prediction information will be helpful in determining the expected demand of goods when preparing the event.