• The Journal of Korean Academy of Prosthodontics
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• v.60 no.2
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• pp.135-142
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• 2022

Purpose. This study aims to evaluate the combined effect of reduced thickness in different regions on the fracture resistance of monolithic zirconia crowns. Materials and methods. Seven nickel-chromium dies were generated from a 3D model of mandibular first molar using the digital scanner with the following geometries: 1.5 mm occlusal reduction, 1.0 mm deep chamfer. Based on the abutment model, Zirconia blocks (Luxen Zirconia) were selected to fabricate Sixty-three zirconia crowns with occlusal thicknesses of 0.3 mm, 0.5 mm, and 1.5 mm, and different axial thicknesses of 0.3 mm, 0.5 mm, and 1.0 mm. All crowns were cemented by resin cement. Next, the crowns were subjected to load-to-fracture test until fracture using an electronic universal testing machine. In addition, fracture patterns were observed with a scanning electron microscope (SEM). Two-way ANOVA and the Tuckey HSD test for post hoc analysis were used for statistical analysis (P < .05). Results. The mean values of fracture resistancerecorded was higher than the average biting force in the posterior region. The two-way ANOVA showed that the occlusal and axial thickness affected the fracture resistance significantly (P < .05). However, the effect of axial thickness on fracture resistance did not show a statistical difference when thicker than 0.5 mm. The observed failure modes were partial or complete fracture depending on the severity of crack propagation. Conclusion. Within the limitations of the present study, the CAD-CAM monolithic zirconia crown with extremely reduced thickness showed adequate fracture resistance to withstand occlusal load in molar regions. In addition, both occlusal and axial thickness affected the fracture resistance of the zirconia crown and showed different results as combined.

• Informatization Policy
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• v.29 no.1
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• pp.24-37
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• 2022

Amid rapid changes in the ICT environment attributed to the 4th Industrial Revolution, the development of information & communication technology, and COVID-19, the existing internet developed without considering security, mobility, manageability, QoS, etc. As a result, the structure of the internet has become complicated, and problems such as security, stability, and reliability vulnerabilities continue to occur. In addition, there is a demand for a new concept of the internet that can provide stability and reliability resulting from digital transformation-geared advanced technologies such as artificial intelligence and IoT. Therefore, in order to suggest a way of implementing the Korean future internet that can strengthen cybersecurity, this study suggests the direction and strategy for promoting the future internet that is suitable for the Korean cyber environment through analyzing important key factors in the implementation of the future internet and evaluating the trend and suitability of domestic & foreign research related to future internet. The importance of key factors in the implementation of the future internet proceeds in the order of security, integrity, availability, stability, and confidentiality. Currently, future internet projects are being studied in various ways around the world. Among numerous projects, Bright Internet most adequately satisfies the key elements of future internet implementation and was evaluated as the most suitable technology for Korea's cyber environment. Technical issues as well as strategic and legal issues must be considered in order to promote the Bright Internet as the frontrunner Korean future internet. As for technical issues, it is necessary to adopt SAVA IPv6-NID in selecting the Bright Internet as the standard of Korean future internet and integrated data management at the data center level, and then establish a cooperative system between different countries. As for strategic issues, a secure management system and establishment of institution are needed. Lastly, in the case of legal issues, the requirement of GDPR, which includes compliance with domestic laws such as Korea's revised Data 3 Act, must be fulfilled.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.1-17
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• 2023

With the recent rapid development of ICT(Information and Communication Technology) and the popularization of digital devices, the size of the online market continues to grow. As a result, we live in a flood of information. Thus, customers are facing information overload problems that require a lot of time and money to select products. Therefore, a personalized recommender system has become an essential methodology to address such issues. Collaborative Filtering(CF) is the most widely used recommender system. Traditional recommender systems mainly utilize quantitative data such as rating values, resulting in poor recommendation accuracy. Quantitative data cannot fully reflect the user's preference. To solve such a problem, studies that reflect qualitative data, such as review contents, are being actively conducted these days. To quantify user review contents, text mining was used in this study. The general CF consists of the following three steps: user-item matrix generation, Top-N neighborhood group search, and Top-K recommendation list generation. In this study, we propose a recommendation algorithm that applies an extended similarity measure, which utilize quantified review contents in addition to user rating values. After calculating review similarity by applying TF-IDF, Word2Vec, and Doc2Vec techniques to review content, extended similarity is created by combining user rating similarity and quantified review contents. To verify this, we used user ratings and review data from the e-commerce site Amazon's "Health and Personal Care". The proposed recommendation model using extended similarity measure showed superior performance to the traditional recommendation model using only user rating value-based similarity measure. In addition, among the various text mining techniques, the similarity obtained using the TF-IDF technique showed the best performance when used in the neighbor group search and recommendation list generation step.

• Informatization Policy
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• v.30 no.2
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• pp.22-45
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• 2023

In research on the use of AI-based voice assistant services, problems related to the user's trust and privacy protection arising from the experience of service use are constantly being raised. The purpose of this study was to investigate empirically the effects of individual trust in AI and online privacy concerns on the continued use of AI-based voice assistants, specifically the impact of their interaction. In this study, question items were constructed based on previous studies, with an online survey conducted among 405 respondents. The effect of the user's trust in AI and privacy concerns on the adoption and continuous use intention of AI-based voice assistant services was analyzed using the Heckman selection model. As the main findings of the study, first, AI-based voice assistant service usage behavior was positively influenced by factors that promote technology acceptance, such as perceived usefulness, perceived ease of use, and social influence. Second, trust in AI had no statistically significant effect on AI-based voice assistant service usage behavior but had a positive effect on continuous use intention. Third, the privacy concern level was confirmed to have the effect of suppressing continuous use intention through interaction with trust in AI. These research results suggest the need to strengthen user experience through user opinion collection and action to improve trust in technology and alleviate users' concerns about privacy as governance for realizing digital government. When introducing artificial intelligence-based policy services, it is necessary to disclose transparently the scope of application of artificial intelligence technology through a public deliberation process, and the development of a system that can track and evaluate privacy issues ex-post and an algorithm that considers privacy protection is required.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.63-79
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• 2024

The startup ecosystem is experiencing a paradigm shift in founding due to the acceleration of digital transformation, online platform companies have grown significantly into unicorns, but the lack of differentiated approaches and strategic support for deep tech startups has led to the inactivity of the startup ecosystem. is lacking. Therefore, in this study, we proposed ways to develop domestic startup development policies, focusing on the US system, which is an advanced example overseas. Focusing on the definition and characteristics of deep tech startups, current investment status, success stories, support policies, etc., we comprehensively analyzed domestic and international literature and derived suggestions. In particular, he proposed specific ways to improve support policies for domestic deep tech startups and presented milestones for their development. Currently, the United States is significantly strengthening the role of the government in supporting deep tech startups. The US government provides direct financial support to deep tech startups, including detergent support and infrastructure support. It has also established policies to foster deep tech startups, established related institutions, and systematized support. It is worth noting that US universities play a core role in nurturing deep tech startups. Leading universities in the United States operate deep tech startup discovery and development programs, providing research and development infrastructure and technology. It also works with companies to provide co-investment and commercialization support for deep tech startups. As a result, the growth of domestic deep tech startups requires the cooperation of diverse entities such as the government, universities, companies, and private investors. The government should strengthen policy support, and universities and businesses should work together to support R&D and commercialization capabilities. Furthermore, private investors must stimulate investment in deep tech startups. Through such efforts, deep tech startups are expected to grow and Korea's innovation ecosystem will be revitalized.

• Information Systems Review
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• v.25 no.2
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• pp.145-162
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• 2023

Asset management is a complex and difficult field that requires insight into numerous variables and even human psychology. Thus, it has traditionally been the domain of professionals, and these services have been expensive to obtain. Changes are taking place in these markets, and the driving force is the digital revolution, so-called the fourth industrial revolution. Among them, the Robo-Advisor service using artificial intelligence technology is the highlight. The reason is that it is possible to popularize investment advisory services with convenient accessibility and low cost. This study aims to clarify what factors are critically important when selecting robo-advisors for service users and providers in Korea, and what perception differences exist in the selection factors between user and provider groups. The framework of the study was based on the marketing mix 4C model, and the design and analysis of the model used Delphi survey and AHP. Through the study design, 4 main criteria and 15 sub-criteria were derived, and the findings of the study are as follows. First, the importance of the four main criteria was in the order of customer needs > customer convenience > customer cost > customer communication for both groups. Second, looking at the 15 sub-criteria, it was found that investment purpose coverage, investment propensity coverage, fee level and accessibility factors were the most important. Third, when comparing between groups, the user group found that the fee level and accessibility factors were the most important, and the provider group recognized the investment purpose coverage and investment propensity coverage factors as important. This study derived useful implications in practice. First, when designing for the spread of the robo-advisor service, the basis for constructing a user-oriented system was prepared by considering the priority of importance according to the weight difference between the four main criteria and the 15 sub-criteria. In addition, the difference in priority of each sub-criteria shown in the group comparison and the cause of the sub-criteria with large weight differences were identified. In addition, it was suggested that it is very important to form a consensus to resolve the difference in perception of factors between those in charge of strategy and marketing and system development within the provider group. Academically, it is meaningful in that it is an early study that presented various perspectives and perspectives by deriving a number of robo-advisor selection factors. Through the findings of this study, it is expected that a successful user-oriented robo-advisor system can be built and spread in Korea to help users.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.97-117
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• 2020

Product evaluation criteria is an indicator describing attributes or values of products, which enable users or manufacturers measure and understand the products. When companies analyze their products or compare them with competitors, appropriate criteria must be selected for objective evaluation. The criteria should show the features of products that consumers considered when they purchased, used and evaluated the products. However, current evaluation criteria do not reflect different consumers' opinion from product to product. Previous studies tried to used online reviews from e-commerce sites that reflect consumer opinions to extract the features and topics of products and use them as evaluation criteria. However, there is still a limit that they produce irrelevant criteria to products due to extracted or improper words are not refined. To overcome this limitation, this research suggests LDA-k-NN model which extracts possible criteria words from online reviews by using LDA and refines them with k-nearest neighbor. Proposed approach starts with preparation phase, which is constructed with 6 steps. At first, it collects review data from e-commerce websites. Most e-commerce websites classify their selling items by high-level, middle-level, and low-level categories. Review data for preparation phase are gathered from each middle-level category and collapsed later, which is to present single high-level category. Next, nouns, adjectives, adverbs, and verbs are extracted from reviews by getting part of speech information using morpheme analysis module. After preprocessing, words per each topic from review are shown with LDA and only nouns in topic words are chosen as potential words for criteria. Then, words are tagged based on possibility of criteria for each middle-level category. Next, every tagged word is vectorized by pre-trained word embedding model. Finally, k-nearest neighbor case-based approach is used to classify each word with tags. After setting up preparation phase, criteria extraction phase is conducted with low-level categories. This phase starts with crawling reviews in the corresponding low-level category. Same preprocessing as preparation phase is conducted using morpheme analysis module and LDA. Possible criteria words are extracted by getting nouns from the data and vectorized by pre-trained word embedding model. Finally, evaluation criteria are extracted by refining possible criteria words using k-nearest neighbor approach and reference proportion of each word in the words set. To evaluate the performance of the proposed model, an experiment was conducted with review on '11st', one of the biggest e-commerce companies in Korea. Review data were from 'Electronics/Digital' section, one of high-level categories in 11st. For performance evaluation of suggested model, three other models were used for comparing with the suggested model; actual criteria of 11st, a model that extracts nouns by morpheme analysis module and refines them according to word frequency, and a model that extracts nouns from LDA topics and refines them by word frequency. The performance evaluation was set to predict evaluation criteria of 10 low-level categories with the suggested model and 3 models above. Criteria words extracted from each model were combined into a single words set and it was used for survey questionnaires. In the survey, respondents chose every item they consider as appropriate criteria for each category. Each model got its score when chosen words were extracted from that model. The suggested model had higher scores than other models in 8 out of 10 low-level categories. By conducting paired t-tests on scores of each model, we confirmed that the suggested model shows better performance in 26 tests out of 30. In addition, the suggested model was the best model in terms of accuracy. This research proposes evaluation criteria extracting method that combines topic extraction using LDA and refinement with k-nearest neighbor approach. This method overcomes the limits of previous dictionary-based models and frequency-based refinement models. This study can contribute to improve review analysis for deriving business insights in e-commerce market.

• Journal of radiological science and technology
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• v.33 no.2
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• pp.109-120
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• 2010

The purpose of this study was first to analyze the utilization of dental examination through questionnaire to develop a diagnostic reference level of patient doses for dental radiography in korea. 77 dental institutions were classified into three groups: A group for the dental hospitals of the college of dentistry (11 institutions), B group for dental hospitals (30 institutions) and C group for dental clinics (36 institutions). The results were as follows : The mean numbers of unit chairs and medical staffs were 140.2, 15.3 and 5.8 sets, 112.6, 7.3 and 1.7 dentists, 3.1, 0.5 and no one radiologic technologists, and 19.7, 12.5 and 3.3 dental hygienists in A, B and C groups, respectively. The mean numbers of dental X-ray equipments were 14.64, 3.21 and 2.19 in A, B and C groups, respectively. Intraoral dental X-ray unit was used the most, the following equipments were panoramic, cephalometric, and cone-beam CT units. The most used X-ray imaging system was also digital system (above 50%) in all three groups. Insight dental film (Kodak, USA) having high sensitivity was routinely used for periapical radiography. The automatic processor was not used in many dental institutions, but the film-holding device was used in many dental institutions. The utilization rates of PACS in A, B and C groups were 90.9%, 83.3% and 16.7% respectively, and the PACS software program was used the most PiView STAR (Infinitt, Korea). The annual mean number of radiographic cases in one dental institution in 2008 for A group was 6.8 times and 21.2 times more than those for B and C groups, and periapical and panoramic radiographs were taken mostly. Tube voltage (kVp) and tube current (mA) for periapical radiography were similar in all three groups, but exposure time in C group was 12.0 times and 3.5 times longer than those in B and C groups. The amount of radiation exposure in C group, in which dental hygienists take dental radiographs, was more than those in other groups. The exposure parameters for panoramic radiography were similar in all three groups. In conclusion, the exposure parameters in dental radiography should be determined with reference level, not past experiences. Use of automatic processor and film-holding devices reduces the radiation exposure in film system. The quality assurance of dental equipments are necessary for the reduction of the patient dose and the improvement of X-ray image quality.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.109-125
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• 2019

As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.

• Fashion & Textile Research Journal
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• v.6 no.1
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• pp.41-50
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• 2004

This research proposes the on-stage costumes for the play Hamlet of Shakespeare performed by Yunheedan Guhri Pae - the Street Theater Troupe. Stage costumes have an important role in displaying the characteristics of each characters to the audience and has big visual effects. However, in order to design the costumes in the object viewpoints of the audience, the survey on the images of the characters who had actually watched the performance was taken place and proposed the costume design according to the results of the survey. Hamlet a: This result was applied to propose a sweater in black color, black leather pants and vest. Hamlet b: This result was applied to propose hooded coat in purple in middle level of brightness and color spectrum and yellow coat. For free image, loose pants in blue and vest in the same color tone were proposed. Gertrude a: This result was applied to use purple (violet) with reddish tone to propose the formation of a dress applying tailored suit. Gertrude b: This result was applied to propose purple gown and the one-piece dress with black laces. Ophelia a: This result was applied to propose feminine white dress and cape in purple color tone. Ophelia b: This result was applied to propose dyed and weaved clothes. Through the surveys as above, the images of each character was driven in adjectives, and using the results driven from the brightness, coloration, and color, color images were proposed. Only one costume cannot make up for the stage costumes and because it exists as an element of stage production, it is true that costumes are limited in some areas. However, that limit can become the motive of the costume. There is a limit, which the designer cannot produce the costumes as he or she had designed but I believe it is the center of the on-stage customers to display the characteristics of the characters according to the given concept. The limit of this research is the fact that because the costumes were designed so they fit the conditions already given, thus it was difficult to regard the process of designing and producing the costume as a project done according to the interaction. And in the future, if it is possible, I wish for the joint research with the people responsible for stage art to take place as a practical stage art. It was possible to produce practical costume since they were produced for actual performance and the production of costumes considering the dance steps, line of flow, and acting, was able to reduce the trial and error on stage. Through this research, I felt that the understanding and smooth interaction on diverse other areas not limited to the costume design should be taken place and believe that this was a research that proposes new research method since there had been only a few previous research regarding the on-stage costumes for actual performances. Therefore, this research had depended on the surveys given to the audiences to endow objectivity, however, I wish this research can contribute to defining effective process and methods for the on-stage costumes with more active researches with diverse methods and in diverse areas. I am sorry that the costume production for all the characters and all the scenes in Hamlet couldn't be done due to many limitations. As the following research assignment, I am planning on designing the costumes for all the scenes.