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

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.287-310
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• 2022

Companies' interest in developing AI-based intelligent new products is increasing. Recently, the main concern of companies is to innovate customer experience and create new values by developing new products through the effective use of Artificial intelligence technology. However, due to the nature of products based on radical technologies such as artificial intelligence, intelligent products differ from existing products and development methods, so it is clear that there is a limitation to applying the existing development methodology as it is. This study proposes a new research method based on KANO-TOPSIS for the successful development of AI-based intelligent new products by using car voice assistants as an example. Using the KANO model, select and evaluate functions that customers think are necessary for new products, and use the TOPSIS method to derives priorities by finding the importance of functions that customers need. For the analysis, major categories such as vehicle condition check and function control elements, driving-related elements, characteristics of voice assistant itself, infotainment elements, and daily life support elements were selected and customer demand attributes were subdivided. As a result of the analysis, high recognition accuracy should be considered as a top priority in the development of car voice assistants. Infotainment elements that provide customized content based on driver's biometric information and usage habits showed lower priorities than expected, while functions related to driver safety such as vehicle condition notification, driving assistance, and security, also showed as the functions that should be developed preferentially. This study is meaningful in that it presented a new product development methodology suitable for the characteristics of AI-based intelligent new products with innovative characteristics through an excellent model combining KANO and TOPSIS.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Journal of the korean academy of Pediatric Dentistry
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• v.34 no.2
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• pp.222-233
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• 2007

One of the most important and basic test of dental restorative materials is the evaluation of microleakage into the tooth-restorative interface. There are many techniques to test microleakage, but most of them have several disadvantages. Recently developed microtomography(micro-CT) can provide the three dimensional image and information about the internal component in non-destructive way, therefore using micro-CT, it is possible to evaluate microleakage exactly in quantitative manner. The purpose of this study is to find a new method for quantitative and non-destructive evaluation of microleakage in composite resin restorations using micro-CT and to compare the new method with conventional dye penetration method. Thus, microleakages of two kinds of dentin bonding systems were evaluated with above two methods. 40 extracted sound human premolars were randomly divided into two groups consisting of 20 samples and restored accordingly. Group 1 : Class V resin restorations with $Adper^{TM}$ Singe Bond Group, 2 : Class V resin restorations with $Adper^{TM}\;Promp^{TM}$ L-pop. The $Filtek^{TM}$ Supreme was applied to the Class V cavities of all teeth. After that, 10 teeth from each group were applied to evaluation of microleakage using micro-CT, and other 10 teeth from each group were using conventional dye penetration method. The conclusions of this study were as follow : 1 Using micro-CT, Group 1 showed significantly less microleakage than Group 2 and there was statistically significant difference(p<0.01) between two groups. 2. Using conventional dye penetration method, Group 1 leaked less than Group 2 and there was statistically significant difference(p<0.01) between two groups 3. The difference between two groups is more evident in the method using micro-CT. 4. In all two methods, microleakage appeared more into the cavities to dentinal margins than enamel margins.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.1-27
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• 2017

It is known that the economic sentiment index and macroeconomic indicators are closely related because economic agent's judgment and forecast of the business conditions affect economic fluctuations. For this reason, consumer sentiment or confidence provides steady fodder for business and is treated as an important piece of economic information. In Korea, private consumption accounts and consumer sentiment index highly relevant for both, which is a very important economic indicator for evaluating and forecasting the domestic economic situation. However, despite offering relevant insights into private consumption and GDP, the traditional approach to measuring the consumer confidence based on the survey has several limits. One possible weakness is that it takes considerable time to research, collect, and aggregate the data. If certain urgent issues arise, timely information will not be announced until the end of each month. In addition, the survey only contains information derived from questionnaire items, which means it can be difficult to catch up to the direct effects of newly arising issues. The survey also faces potential declines in response rates and erroneous responses. Therefore, it is necessary to find a way to complement it. For this purpose, we construct and assess an index designed to measure consumer economic sentiment index using sentiment analysis. Unlike the survey-based measures, our index relies on textual analysis to extract sentiment from economic and financial news articles. In particular, text data such as news articles and SNS are timely and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. There exist two main approaches to the automatic extraction of sentiment from a text, we apply the lexicon-based approach, using sentiment lexicon dictionaries of words annotated with the semantic orientations. In creating the sentiment lexicon dictionaries, we enter the semantic orientation of individual words manually, though we do not attempt a full linguistic analysis (one that involves analysis of word senses or argument structure); this is the limitation of our research and further work in that direction remains possible. In this study, we generate a time series index of economic sentiment in the news. The construction of the index consists of three broad steps: (1) Collecting a large corpus of economic news articles on the web, (2) Applying lexicon-based methods for sentiment analysis of each article to score the article in terms of sentiment orientation (positive, negative and neutral), and (3) Constructing an economic sentiment index of consumers by aggregating monthly time series for each sentiment word. In line with existing scholarly assessments of the relationship between the consumer confidence index and macroeconomic indicators, any new index should be assessed for its usefulness. We examine the new index's usefulness by comparing other economic indicators to the CSI. To check the usefulness of the newly index based on sentiment analysis, trend and cross - correlation analysis are carried out to analyze the relations and lagged structure. Finally, we analyze the forecasting power using the one step ahead of out of sample prediction. As a result, the news sentiment index correlates strongly with related contemporaneous key indicators in almost all experiments. We also find that news sentiment shocks predict future economic activity in most cases. In almost all experiments, the news sentiment index strongly correlates with related contemporaneous key indicators. Furthermore, in most cases, news sentiment shocks predict future economic activity; in head-to-head comparisons, the news sentiment measures outperform survey-based sentiment index as CSI. Policy makers want to understand consumer or public opinions about existing or proposed policies. Such opinions enable relevant government decision-makers to respond quickly to monitor various web media, SNS, or news articles. Textual data, such as news articles and social networks (Twitter, Facebook and blogs) are generated at high-speeds and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. Although research using unstructured data in economic analysis is in its early stages, but the utilization of data is expected to greatly increase once its usefulness is confirmed.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.55-78
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• 2021

Tosolve complex and diverse social problems and ensure the quality of life of individuals, social robots that can interact with humans are attracting attention. In the past, robots were recognized as beings that provide labor force as they put into industrial sites on behalf of humans. However, the concept of today's robot has been extended to social robots that coexist with humans and enable social interaction with the advent of Smart technology, which is considered an important driver in most industries. Specifically, there are service robots that respond to customers, the robots that have the purpose of edutainment, and the emotionalrobots that can interact with humans intimately. However, popularization of robots is not felt despite the current information environment in the modern ICT service environment and the 4th industrial revolution. Considering social interaction with users which is an important function of social robots, not only the technology of the robots but also other factors should be considered. The design elements of the robot are more important than other factors tomake consumers purchase essentially a social robot. In fact, existing studies on social robots are at the level of proposing "robot development methodology" or testing the effects provided by social robots to users in pieces. On the other hand, consumer emotions felt from the robot's appearance has an important influence in the process of forming user's perception, reasoning, evaluation and expectation. Furthermore, it can affect attitude toward robots and good feeling and performance reasoning, etc. Therefore, this study aims to verify the effect of appearance of social robot and consumer emotions on consumer's attitude toward social robot. At this time, a social robot design evaluation model is constructed by combining heterogeneous data from different sources. Specifically, the three quantitative indicator data for the appearance of social robots from the ABOT Database is included in the model. The consumer emotions of social robot design has been collected through (1) the existing design evaluation literature and (2) online buzzsuch as product reviews and blogs, (3) qualitative interviews for social robot design. Later, we collected the score of consumer emotions and attitudes toward various social robots through a large-scale consumer survey. First, we have derived the six major dimensions of consumer emotions for 23 pieces of detailed emotions through dimension reduction methodology. Then, statistical analysis was performed to verify the effect of derived consumer emotionson attitude toward social robots. Finally, the moderated regression analysis was performed to verify the effect of quantitatively collected indicators of social robot appearance on the relationship between consumer emotions and attitudes toward social robots. Interestingly, several significant moderation effects were identified, these effects are visualized with two-way interaction effect to interpret them from multidisciplinary perspectives. This study has theoretical contributions from the perspective of empirically verifying all stages from technical properties to consumer's emotion and attitudes toward social robots by linking the data from heterogeneous sources. It has practical significance that the result helps to develop the design guidelines based on consumer emotions in the design stage of social robot development.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.175-196
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• 2022

Information and communication and home appliance industries, which were one of South Korea's main industries, are gradually losing their export share as their export competitiveness is weakening. This study objectively analyzed export competitiveness and suggested export-promising countries in order to help South Korea's information communication and home appliance industries improve exports. In this study, network properties, centrality, and structural hole analysis were performed during network analysis to evaluate export competitiveness. In order to select promising export countries, we proposed a new variable that can take into account the characteristics of an already established International Trade Network (ITN), that is, the Global Value Chain (GVC), in addition to the existing economic factors. The conditional log-odds for individual links derived from the Exponential Random Graph Model (ERGM) in the analysis of the cross-border trade network were assumed as a proxy variable that can indicate the export potential. In consideration of the possibility of ERGM linkage, a parametric approach and a non-parametric approach were used to recommend export-promising countries, respectively. In the parametric method, a regression analysis model was developed to predict the export value of the information and communication and home appliance industries in South Korea by additionally considering the link-specific characteristics of the network derived from the ERGM to the existing economic factors. Also, in the non-parametric approach, an abnormality detection algorithm based on the clustering method was used, and a promising export country was proposed as a method of finding outliers that deviate from two peers. According to the research results, the structural characteristic of the export network of the industry was a network with high transferability. Also, according to the centrality analysis result, South Korea's influence on exports was weak compared to its size, and the structural hole analysis result showed that export efficiency was weak. According to the model for recommending promising exporting countries proposed by this study, in parametric analysis, Iran, Ireland, North Macedonia, Angola, and Pakistan were promising exporting countries, and in nonparametric analysis, Qatar, Luxembourg, Ireland, North Macedonia and Pakistan were analyzed as promising exporting countries. There were differences in some countries in the two models. The results of this study revealed that the export competitiveness of South Korea's information and communication and home appliance industries in GVC was not high compared to the size of exports, and thus showed that exports could be further reduced. In addition, this study is meaningful in that it proposed a method to find promising export countries by considering GVC networks with other countries as a way to increase export competitiveness. This study showed that, from a policy point of view, the international trade network of the information communication and home appliance industries has an important mutual relationship, and although transferability is high, it may not be easily expanded to a three-party relationship. In addition, it was confirmed that South Korea's export competitiveness or status was lower than the export size ranking. This paper suggested that in order to improve the low out-degree centrality, it is necessary to increase exports to Italy or Poland, which had significantly higher in-degrees. In addition, we argued that in order to improve the centrality of out-closeness, it is necessary to increase exports to countries with particularly high in-closeness. In particular, it was analyzed that Morocco, UAE, Argentina, Russia, and Canada should pay attention as export countries. This study also provided practical implications for companies expecting to expand exports. The results of this study argue that companies expecting export expansion need to pay attention to countries with a relatively high potential for export expansion compared to the existing export volume by country. In particular, for companies that export daily necessities, countries that should pay attention to the population are presented, and for companies that export high-end or durable products, countries with high GDP, or purchasing power, relatively low exports are presented. Since the process and results of this study can be easily extended and applied to other industries, it is also expected to develop services that utilize the results of this study in the public sector.

• Journal of Agricultural Extension & Community Development
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• v.2 no.2
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• pp.205-227
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• 1995

The objectives of this study were to 1) classify the cooperative farmers' organizations in Korea according to the development level and institutional aspects through the exploration of its' conceptual and institutional basis, 2) analyze the farmers' needs for organization, 3) identify the problems and situation of organizations, and 4) formulate an effective management model for each cooperative farmers' organization. The study was carried out through a review of literature and using available statistical data collected from various sources and empirical survey. Major findings of the study were: 1) the cooperative farmers' organizations could be classified into four types : crop units, farming cooperative corporation, trust farming companies and joint-stock agri-business. 2) a lot of members of the organization feel that the information is insufficient, the opportunity to suggest their own ideas is hardly given, and the members are not satisfied with the cooperation among the members, 3) the members who have higher level of schooling education showed a higher participation level in the organization, 4) most of members did not recognize the organization they participated in, 5) participation of the organization's members and concerned institutions is an important factor to promote problem solving and better communication within the organization, 6) any type of continuing education for the members is needed to facilitate the transfer of a new agricultural and organizational technology, 7) research and development(R & D) is one of the most important factors of the development of organizations, 8) most organizations are deficient in professional management skills(financial, personal, accounts, etc.), 9) the trust farming companies have difficulties in managing the firm on account of the characteristics of agriculture(especially seasonal), the dispersed trust lands, and the need for more alternative work in the winter season, and 10) in the case of agri-businesses, their organizations are more specialized in marketing and have more structured systems of management. Based on the results of the study the following recommendations were made for further improvement and development of agricultural cooperative organizations : (1) More governmental support should be given to education for improvement of the organizational structure. And more deliberate and differentiated governmental support should be provided for the organizations to be viably managed. (2) For more efficient communication between the members and the organization, more opportunities for discussion are needed. (3) The more research should be committed to this kind of work in order to get more analytic data and strategic plans of cooperative organizations.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.54.3-54.3
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• 2015

To probe the star formation in local and early Universe, the NISS with a capability of imaging spectroscopy in the near-infrared is being developed by KASI. The main scientific targets are nearby galaxies, galaxy clusters, star-forming regions and low background regions. The off-axis optical design of the NISS with 15cm aperture was optimized to obtain a wide field of view (FoV) of $2deg.{\times}2deg.$ as well as a wide spectral coverage from 0.9 to $3.8{\mu}m$. The opto-mechanical structure was designed to be safe enough to endure in both the launching condition and the space environment. The dewar will operate $1k{\times}1k$ infrared sensor at 80K stage. The NISS will be launched in 2017 and explore the large areal near-infrared sky up to $200deg.^2$ in order to get both spatial and spectral information for astronomical objects. As an extension of the NISS, KASI is planning to participate in a new small space mission together with NASA. The promising candidate, SPHEREx (Spectro-Photometer for the History of the Universe Epoch of Reionization, and Ices Explorer) is an all-sky survey satellite designed to reveal the origin of the Universe and water in the planetary systems and to explore the evolution of galaxies. Though the survey concept is similar to that of the NISS, the SPHEREx will perform the first near-infrared all-sky imaging spectroscopic survey with the wider spectral range from 0.7 to $5{\mu}m$ and the wider FoV of $3.5deg.{\times}7deg.$ Here, we report the current status of the NISS and introduce new mission for the near-infrared imaging spectroscopic survey.

• Journal of Satellite, Information and Communications
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• v.12 no.3
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• pp.41-49
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• 2017

This paper will describe lunar lava tubes' five analyzed fields, such as geology, geomorphology, internal configuration, stability, communication and habitats requirements. This research gets through qualitative and qualitative data analysis as following results. A huge size and configuration differences between lunar lava tubes and earth one on geology and landform environments. Exo-genetics activities, such as meteorites, radiation, and sudden temperature bigger affect than Endo-genetic activities, such as effusion and earthquake of the lunar lava tubes. Landform and internal configuration of the lunar lava tubes due to the huge cave perilous landform that gravity difference have a technical limitation from internal approach and data obtain of the huge skylights and sinuous rilles. Stability of the lunar lava tubes deals with geology and landform. It was obvious geo-structural stability elements results generated on low rate of collapsed halls(skylights), low gravity, and relatively thick covers. In terms of the communication capability on the external and internal lunar lava tubes cordless communication techniques will overcome limitations of the sun-power generates supporting communication systems. Through this research it realized obvious differs between potential habitats possibility by accumulative theories by scholars and techniques of the lunar lava tubes. Especially, it is a favorable expectation throughout overcoming attempt on zero gravity, cosmo radiation, lunar dust of the exo-genetic limitations to the steep escarpment of skylights to approach and achieve techniques by the civil engineering, networking and GIS techniques as the endo-genetic environment treatment.