• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.215-235
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• 2024

As artificial intelligence (AI) technology is recognized as a key technology that will determine future national competitiveness, competition for AI technology and industry promotion policies in major countries is intensifying. This study aims to present implications for domestic policy making by analyzing the policies of major countries on the start-up of AI companies, which are the basis of the AI industry ecosystem. The top four countries and the EU for the number of new investment attraction companies in the 2023 AI Index announced by the HAI Research Institute at Stanford University in the United States were selected, The United States enacted the National AI Initiative Act (NAIIA) in 2021. Through this law, The US Government is promoting continued leadership in the United States in AI R&D, developing reliable AI systems in the public and private sectors, building an AI system ecosystem across society, and strengthening DB management and access to AI policies conducted by all federal agencies. In the 14th Five-Year (2021-2025) Plan and 2035 Long-term Goals held in 2021, China has specified AI as the first of the seven strategic high-tech technologies, and is developing policies aimed at becoming the No. 1 AI global powerhouse by 2030. The UK is investing in innovative R&D companies through the 'Future Fund Breakthrough' in 2021, and is expanding related investments by preparing national strategies to leap forward as AI leaders, such as the implementation plan of the national AI strategy in 2022. Israel is supporting technology investment in start-up companies centered on the Innovation Agency, and the Innovation Agency is leading mid- to long-term investments of 2 to 15 years and regulatory reforms for new technologies. The EU is strengthening its digital innovation hub network and creating the InvestEU (European Strategic Investment Fund) and AI investment fund to support the use of AI by SMEs. This study aims to contribute to analyzing the policies of major foreign countries in making AI company start-up policies and providing a basis for Korea's strategy search. The limitations of the study are the limitations of the countries to be analyzed and the failure to attempt comparative analysis of the policy environments of the countries under the same conditions.

• The Journal of Korean Academy of Prosthodontics
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• v.62 no.2
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• pp.95-103
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• 2024

Purpose. With the advancement of digital technology, 3D printing is being utilized in the fabrication of denture base. Nevertheless, increasing microbial adhesion to the surface of denture base has been reported as the disadvantage of 3D-printed denture base. The purpose of this study is to investigate the antifungal properties and flexural strength of 3D-printed denture base resin according to the different contents of titanium dioxide nanoparticles. Materials and methods. Titanium dioxide nanoparticles were mixed with the 3D printing resin at the ratios of 0.5, 1, 1.5, and 2 wt%. Twenty specimens per each group were printed in the form of cylindrical shape (diameter: 20 mm, height: 3 mm) to evaluate antifungal properties. Ten specimens from each group underwent polishing using autogrinder, while the remaining ten specimens did not. Candida albicans in hyphae form was inoculated onto each specimen, optical density and colony-forming unit were analyzed. The surface of the specimen was observed using scanning electron microscopy. To evaluate the flexural strength, twenty specimens per each group were 3D printed in the form of rectangular prism shape (length: 64 mm, height: 10 mm, width: 3 mm) and three-point bending tests were conducted using universal testing machine according to ISO 20795-1. Results. Colony-forming unit of C.albicans and optical density of culture medium showed no difference between non-polished groups, but decreased in the polished groups at concentration of 1, 1.5, 2 wt% titanium dioxide nanoparticles. Flexural strength increased with titanium dioxide nanoparticle at concentration of 0.5, 1, 1.5 wt%, but decreased at 2 wt% compared to 1.5 wt%. Conclusion. When 1.5 wt% of titanium dioxide nanoparticles were added to the 3D-printed denture base resin with polishing, antifungal properties were increased.

• Restorative Dentistry and Endodontics
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• v.27 no.2
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• pp.158-174
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• 2002

The aim of this study was to investigate the effect of light irradiation modes on polymerization shrinkage, degree of cure and microleakage of a composite resin. VIP$^{TM}$ (Bisco Dental Products, Schaumburg, IL, USA) and Optilux 501$^{TM}$ (Demetron/Kerr, Danbury, CT, USA) were used for curing Filtek$^{TM}$ Z-250 (3M Dental Products, St. Paul., MN, USA) composite resin using following irradiation modes: VIP$^{TM}$ (Bisco) 200mW/$\textrm{cm}^2$ (V2), 400mW/$\textrm{cm}^2$ (V4), 600mW/$\textrm{cm}^2$ (V6), Pulse-delay (200 mW/$\textrm{cm}^2$ 3 seconds, 5 minutes wait, 600mW/$\textrm{cm}^2$ 30seconds, VPD) and Optilux 501$^{TM}$ (Demetron/Kerr) C-mode (OC), R-mode (OR). Linear polymerization shrinkage of the composite specimens were measured using Linometer (R&B, Daejeon, Korea) for 90 seconds for V2, V4, V6, OC, OR groups and for up to 363 seconds for VPD group (n=10, each). Degree of conversion was measured using FTIR spectrometer (IFS 120 HR, Bruker Karlsruhe, Germany) at the bottom surface of 2 mm thick composite specimens V2, Y4, V6, OC groups were measured separately at five irradiation times (5, 10, 20, 40, 60 seconds) and OR, VPD groups were measured in the above mentioned irradiation modes (n=5 each). Microhardness was measured using Digital microhardness tester (FM7, Future-Tech Co., Tokyo, Japan) at the top and bottom surfaces of 2mm thick composite specimens after exposure to the same irradiation modes as the test of degree of conversion(n=3, each). For the microleakage test, class V cavities were prepared on the distal surface of the ninety extracted human third molars. The cavities were restored with one of the following irradiation modes : V2/60 seconds, V4/40 seconds, V6/30 seconds, VPD , OC and OR. Microleakage was assessed by dye penetration along enamel and dentin margins of cavities. Mean polymerization shrinkage, mean degree of conversion and mean microhardness values for all groups at each time were analyzed using one-way ANOVA and Duncan's multiple range test, and using chi-square test far microleakage values. The results were as follows : . Polymerization shrinkage was increased with higher light intensity in groups using VIP$^{TM}$ (Bisco) : the highest with 600mW/$\textrm{cm}^2$, followed by Pulse-delay, 400mW/$\textrm{cm}^2$ and 200mW/$\textrm{cm}^2$ groups, The degree of polymerization shrinkage was higher with Continuous mode than with Ramp mode in groups using Optilux 501$^{TM}$ (Demetron/Kerr). . Degree of conversion and microhardness values were higher with higher light intensity. The final degree of conversion was in the range of 44.7 to 54.98% and the final microhardness value in the range of 34.10 to 56.30. . Microleakage was greater in dentin margin than in enamel margin. Higher light intensity showed more microleakage in dentin margin in groups using VIP$^{TM}$ (Bisco). The microleakage was the lowest with Continuous mode in enamel margin and with Ramp mode in dentin margin when Optilux 501$^{TM}$ (Demetron/Kerr) was used.

• Journal of Dental Rehabilitation and Applied Science
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• v.26 no.1
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• pp.21-32
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• 2010

The convergence angle of a prepared tooth is a very important factor in the retention and resistance of a crown restoration. But various intraoral environments and clinician's techniques make it difficult to obtain the ideal inclination. Therefore, in this study, clinical convergence angle of a prepared tooth was investigated. The data was collected from the patient models of prosthodontic residents and the patient models of general practitioners. The images of mesiodistal and buccolingual surfaces were taken with a digital camera to evaluate the convergence angle on 'ImageJ' program. The images were classified according to the criteria (1. Clinician group, 2. Position in the dental arch, 3. The purpose of abutment preparation)and then analyzed. The mean convergence angle of a prepared tooth for Korean clinicians was $15.02^{\circ}$ (${\pm}10.13^{\circ}$). 1. It was significant in the convergence angle between the general practitioner group and the prosthodontic resident group(p<0.05). 2. It was significant between the mesiodistal and buccolingual surface in the the prosthodontic resident group(p<0.05). 3. For the general practitioner group, it was significant when anteriors and premolars were compared with molars(p<0.05). For the prosthodontic resident group, it was significant when anteriors and premolars were compared with molars (p<0.05). 4. When divided into upper and lower arches, for the general practitioner group, it showed significant difference in the buccolingual aspect(p<0.05). Also in the prosthodontic resident group, it showed significant difference in the buccolingual aspect(p<0.05). 5. Dividing left and right sides of the arches, there was no significant difference in the general practitioner group and the prosthodontic resident group(p>0.05). 6. In the general practitioner group, it was significant in the mesiodistal axial convergence angle of single crown abutment and 3 unit bridge abutment(p<0.05). In the prosthodontic resident group, it was significant in the mesiodistal and overall axial convergence angle of single crown abutment and 3 unit bridge abutment(p<0.05). Clinical convergence angle of prepared tooth in Korea was included in agreement with other studies investigating convergence angle that ranged from 10 to 22 degrees, achieved in clinical practice.

• Journal of Global Scholars of Marketing Science
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• v.18 no.2
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• pp.89-111
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• 2008

Due to the development of digital technology, studies regarding smart wear integrating daily life have rapidly increased. However, consumer research about perception and attitude toward smart clothing hardly could find. The purpose of this study was to identify innovative characteristics and perceived risk of smart clothing and to analyze the influences of theses factors on product attitudes and intention to adopt. Specifically, five hypotheses were established. H1: Perceived attributes of smart clothing except for complexity would have positive relations to product attitude or purchase intention, while complexity would be opposite. H2: Product attitude would have positive relation to purchase intention. H3: Product attitude would have a mediating effect between perceived attributes and purchase intention. H4: Perceived risks of smart clothing would have negative relations to perceived attributes except for complexity, and positive relations to complexity. H5: Product attitude would have a mediating effect between perceived risks and purchase intention. A self-administered questionnaire was developed based on previous studies. After pretest, the data were collected during September, 2006, from university students in Korea who were relatively sensitive to innovative products. A total of 300 final useful questionnaire were analyzed by SPSS 13.0 program. About 60.3% were male with the mean age of 21.3 years old. About 59.3% reported that they were aware of smart clothing, but only 9 respondents purchased it. The mean of attitudes toward smart clothing and purchase intention was 2.96 (SD=.56) and 2.63 (SD=.65) respectively. Factor analysis using principal components with varimax rotation was conducted to identify perceived attribute and perceived risk dimensions. Perceived attributes of smart wear were categorized into relative advantage (including compatibility), observability (including triability), and complexity. Perceived risks were identified into physical/performance risk, social psychological risk, time loss risk, and economic risk. Regression analysis was conducted to test five hypotheses. Relative advantage and observability were significant predictors of product attitude (adj $R^2$=.223) and purchase intention (adj $R^2$=.221). Complexity showed negative influence on product attitude. Product attitude presented significant relation to purchase intention (adj $R^2$=.692) and partial mediating effect between perceived attributes and purchase intention (adj $R^2$=.698). Therefore hypothesis one to three were accepted. In order to test hypothesis four, four dimensions of perceived risk and demographic variables (age, gender, monthly household income, awareness of smart clothing, and purchase experience) were entered as independent variables in the regression models. Social psychological risk, economic risk, and gender (female) were significant to predict relative advantage (adj $R^2$=.276). When perceived observability was a dependent variable, social psychological risk, time loss risk, physical/performance risk, and age (younger) were significant in order (adj $R^2$=.144). However, physical/performance risk was positively related to observability. The more Koreans seemed to be observable of smart clothing, the more increased the probability of physical harm or performance problems received. Complexity was predicted by product awareness, social psychological risk, economic risk, and purchase experience in order (adj $R^2$=.114). Product awareness was negatively related to complexity, meaning high level of product awareness would reduce complexity of smart clothing. However, purchase experience presented positive relation with complexity. It appears that consumers can perceive high level of complexity when they are actually consuming smart clothing in real life. Risk variables were positively related with complexity. That is, in order to decrease complexity, it is also necessary to consider minimizing anxiety factors about social psychological wound or loss of money. Thus, hypothesis 4 was partially accepted. Finally, in testing hypothesis 5, social psychological risk and economic risk were significant predictors for product attitude (adj $R^2$=.122) and purchase intention (adj $R^2$=.099) respectively. When attitude variable was included with risk variables as independent variables in the regression model to predict purchase intention, only attitude variable was significant (adj $R^2$=.691). Thus attitude variable presented full mediating effect between perceived risks and purchase intention, and hypothesis 5 was accepted. Findings would provide guidelines for fashion and electronic businesses who aim to create and strengthen positive attitude toward smart clothing. Marketers need to consider not only functional feature of smart clothing, but also practical and aesthetic attributes, since appropriateness for social norm or self image would reduce uncertainty of psychological or social risk, which increase relative advantage of smart clothing. Actually social psychological risk was significantly associated to relative advantage. Economic risk is negatively associated with product attitudes as well as purchase intention, suggesting that smart-wear developers have to reflect on price ranges of potential adopters. It will be effective to utilize the findings associated with complexity when marketers in US plan communication strategy.

• Journal of Preventive Medicine and Public Health
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• v.4 no.1
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• pp.41-64
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• 1971

During the period from July 1st to the end of November 1970, a survey on air pollution and noise level was made in Seoul, Pusan and Taegu, the three largest cities in Korea. Each city was divided into 4-6 areas; the industrial area, the semi-industrial area, the commercial area, the residential area, the park area and the downtown area. Thirty eight sites were selected from each area. A. Method of Measurement : Dustfall was measured by the Deposit Gauge Method, sulfur oxides by $PbO_2$ cylinder method, suspended particles by the Digital Dust Indicator, Sulfur dioxide ($SO_2$) and Carbon Monoxide (CO) by the MSA & Kitakawa Detector and the noise levels by Rion Sound Survey meter. B. Results: 1. The mean value of dustfall in 3 cities was $30.42ton/km^2/month$, ranging from 8.69 to 95.44. 2. The mean values of dustfall by city were $33.17ton/km^2/month$ in Seoul, 32.11 in Pusan and 25.97 in Taegu. 3. The mean values of dustfall showed a trend of decreasing order of semi-industrial area, downtown area, industrial area, commercial area, residential area, and park area. 4. The mean value of dustfall in Seoul by area were $52.32ton/km^2/month$ in downtown, 50.54 in semi-industrial area, 40.37 in industrial area, 24,19 in commercial area, 16.25 in park area and 15.39 in residential area in order of concentration. 5. The mean values of dustfall in Pusan by area were $48.27ton/km^2/month$ in semi-industrial area, 36.68 in industrial area 25.31 in commercial area, and 18.19 in residential area. 6. The mean values of dustfall in Taegu by area were $36.46ton/km^2/month$ in downtown area, 33.52 in industrial area, 20.37 in commercial area and 13.55 in residential area. 7. The mean values of sulfur oxides in 3 cities were $1.52mg\;SO_3/day/100cm^2\;PbO_2$, ranging from 0.32 to 4.72. 8. The mean values of sulfur oxides by city were $1.89mg\;SO_3/day/100cm^2\;PbO_2$ in Pusan, 1.64 in Seoul and 1.21 in Taegu. 9. The mean values of sulfur oxides by area in 3 cities were $2.16mg\;SO_3/day/100cm^2\;PbO_2$ in industrial area, 1.69 in semi-industrial area, 1.50 in commercial area, 1.48 in downtown area, 1.32 in residential area and 0.94 in the park area, respectively. 10. The monthly mean values of sulfur oxides contents showed a steady increase from July reaching a peak in November. 11. The mean values of suspended particles was $2.89mg/m^3$, ranging from 1.15 to 5.27. 12. The mean values of suspended particles by city were $3.14mg/m^3$ in Seoul, 2.79 in Taegu and 2.25 in Pusan. 13. The mean values of noise level in 3 cities was 71.3 phon, ranging from 49 to 99 phon. 14. The mean values of noise level by city were 73 phon in Seoul, 72 in Pusan, and 69 in Taegu in that order. 15. The mean values of noise level by area in 3 cities showed a decrease in the order of the downtown area, commercial area, industrial area and semi-industrial area, park area and residential area. 16. The comparison of the noise levels by area in 3 cities indicated that the highest level was detected in the downtown area in Seoul and Taegu and in the industrial area in Pusan. 17. The daily average concentration of sulfur dioxides ($SO_2$) in 3 cities was 0.081 ppm, ranging from 0.004 to 0.196. 18. The daily average concentrations of sulfur dioxides by city were 0.092 ppm in Seoul, 0.089 in Pusan and 0.062 in Taegu in that order. 19. The weekly average concentration of carbon monoxides(CO) was 27.59 ppm. 20. The daily average concentrations of carbon monoxides by city were 33.37 ppm. in Seoul, 25.76 in Pusan and 23.65 in Taegu in that order. 21. The concentration of $SO_2$ and CO reaches a peak from 6 p. m. to 8 p. m. 22. About 3 times probably the daily average concentration of CO could be detected in the downtown area probably due to heavy traffic emission in comparison with that in the industial area. 23. As for daily variation of the concentration of $SO_2$ and CO it was found that the concentration maintains relatively higher value during weekdays in the industrial area and on the first part of the week in the downtown area.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.149-161
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• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.75-100
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• 2018

Mobile devices have become an important channel for news content usage in our daily life. However, online news content readers' resistance to online news monetization is more serious than other digital content businesses, such as webtoons, music sources, videos, and games. Since major portal sites distribute online news content free of charge to increase their traffics, customers have been accustomed to free news content; hence this makes online news providers more difficult to switch their policies on business models (i.e., monetization policy). As a result, most online news providers are highly dependent on the advertising business model, which can lead to increasing number of false, exaggerated, or sensational advertisements inside the news website to maximize their advertising revenue. To reduce this advertising dependencies, many online news providers had attempted to switch their 'free' readers to 'paid' users, but most of them failed. However, recently, some online news media have been successfully applying the Pay-What-You-Want (PWYW) payment model, which allows readers to voluntarily pay fees for their favorite news content. These successful cases shed some lights to the managers of online news content provider regarding that the PWYW model can serve as an alternative business model. In this study, therefore, we collected 379 online news articles from Ohmynews.com that has been successfully employing the PWYW model, and analyzed the comparative importance of systematic attributes of online news content on readers' voluntary payment. More specifically, we derived the six systematic attributes (i.e., Type of Article Title, Image Stimulation, Article Readability, Article Type, Dominant Emotion, and Article-Image Similarity) and three or four levels within each attribute based on previous studies. Then, we conducted content analysis to measure five attributes except Article Readability attribute, measured by Flesch readability score. Before conducting main content analysis, the face reliabilities of chosen attributes were measured by three doctoral level researchers with 37 sample articles, and inter-coder reliabilities of the three coders were verified. Then, the main content analysis was conducted for two months from March 2017 with 379 online news articles. All 379 articles were reviewed by the same three coders, and 65 articles that showed inconsistency among coders were excluded before employing conjoint analysis. Finally, we examined the comparative importance of those six systematic attributes (Study 1), and levels within each of the six attributes (Study 2) through conjoint analysis with 314 online news articles. From the results of conjoint analysis, we found that Article Readability, Article-Image Similarity, and Type of Article Title are the most significant factors affecting online news readers' voluntary payment. First, it can be interpreted that if the level of readability of an online news article is in line with the readers' level of readership, the readers will voluntarily pay more. Second, the similarity between the content of the article and the image within it enables the readers to increase the information acceptance and to transmit the message of the article more effectively. Third, readers expect that the article title would reveal the content of the article, and the expectation influences the understanding and satisfaction of the article. Therefore, it is necessary to write an article with an appropriate readability level, and use images and title well matched with the content to make readers voluntarily pay more. We also examined the comparative importance of levels within each attribute in more details. Based on findings of two studies, two major and nine minor propositions are suggested for future empirical research. This study has academic implications in that it is one of the first studies applying both content analysis and conjoint analysis together to examine readers' voluntary payment behavior, rather than their intention to pay. In addition, online news content creators, providers, and managers could find some practical insights from this research in terms of how they should produce news content to make readers voluntarily pay more for their online news content.

• Journal of radiological science and technology
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• v.32 no.3
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• pp.335-341
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• 2009

Purpose : The medical imaging issuance is changed from conventional film method to Digital Compact Disk solution because of development on IT technology. However other medical record department's are undergoing identification check through and through whereas medical imaging department cannot afford to do that. So, we examine present applicant's recognition of private intelligence safeguard, and medical imaging issuance condition by CD & DVD medium toward various medical facility and then perform comparative analysis associated with domestic and foreign law & recommendation, lastly suggest standard for medical imaging issuance and process relate with internal environment. Materials and methods : First, we surveyed issuance process & required documents when situation of medical image issuance in the metropolitan medical facility by wire telephone between 2008.6.1$\sim$2008.7.1. in accordance with the medical law Article 21$\sim$clause 2, suggested standard through applicant's required documents occasionally - (1) in the event of oneself $\rightarrow$ verifying identification, (2) in the event of family $\rightarrow$ verifying applicant identification & family relations document (health insurance card, attested copy, and so on), (3) third person or representative $\rightarrow$ verifying applicant identification & letter of attorney & certificate of one's seal impression. Second, also checked required documents of applicant in accordance with upper standard when situation of medical image issuance in Kyung-hee university medical center during 3 month 2008.5.1$\sim$2008.7.31. Third, developed a work process by triangular position of issuance procedure for situation when verifying required documents & management of unpreparedness. Result : Look all over the our manufactured output in the hospital - satisfy the all conditions $\rightarrow$ 4 place(12%), possibly request everyone $\rightarrow$ 4 place(12%), and apply in the clinic section $\rightarrow$ 9 place(27%) that does not medical imaging issuance office, so we don't know about required documents condition. and look into whether meet or not the applicant's required documents on upper 3month survey - satisfy the all conditions $\rightarrow$ 629 case(49%), prepare a one part $\rightarrow$ 416 case(33%), insufficiency of all document $\rightarrow$ 226case(18%). On the authority of upper research result, we are establishing the service model mapping for objective reception when image export situation through triangular position of issuance procedure and reduce of friction with patient and promote the patient convenience. Conclusion : The PACS is classified under medical machinery that mean indicates about higher importance of medical information therefore medical information administrator's who already received professional education & mind, are performer about issuance process only and also have to provide under ID checking process exhaustively.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.