• Science of Emotion and Sensibility
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• v.17 no.1
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• pp.39-52
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• 2014

Use of vision and audition for video reality has made much advancement. However use of olfaction, which is effective in inducing emotion, has not yet been realized due to technical limitations and lack of basic research. In particular it is difficult to fabricate many odors required for each different video. One way to resolve this is to discover clusters of odors of similar smell and to use representative odor for each cluster. This research explored clusters of odors based on pairwise similarity ratings. 300 diverse odors were first collected and sorted them into 11 categories. We selected 152 odors based on their frequency, preference, and concreteness. Participants rated similarity on 1,018 pairs of odors from selected odors and the results were analyzed using multi-dimensional scaling (MDS). Based on the idea that low odor concreteness would support valid use of representative odor, the MDS results are presented from low to high smell concreteness. First, flowers, plants, fruits, and vegetables was classified under the easy categories to use representative odor due to their low smell concreteness (Figure 1). Second, chemicals, personal cares, physiological odors, and ordinary places was classified under the careful categories of using it due to their intermediate concreteness (Figure 2). Finally, food ingredients, beverages, and foods was classified under the difficult categories to use it because of their high concreteness (Figure 3). The results of this research will contribute to reduction of cost and time in odor production and provision of realistic media service to customers at reasonable price.

• Korean Security Journal
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• no.11
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• pp.159-181
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• 2006

This study is concerned on Why The Certified Security certification is needed and How to control the security quality to get better service to the clients. Theses days are required The Certified Certificate in all the industry. And in this point of view, the certified certificate is a kind of confirmation by an authority to the person who has how much special knowledge and practice in a certain field. Moreover, in the functionalism society the certified certificate system would be very positive effect to the related industry and society as official measurement by an authority. The security is freedom from fear and anxiety. Which means the security can not be operated in isolation from citizen's safe-living expectation, and which is also dealing with valuable human being's life. For getting the better purpose the security industry employees should have more organized special training and education. As my understanding the certified certificate exam system is the confirmation by an authority, the certified certificate is only neutral evidence to get the confidence and credit from the clients. In this point of view the core point is How to control The Certified Certificate by a credied authority.

• The Journal of Society for e-Business Studies
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• v.21 no.3
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• pp.51-78
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• 2016

Online-to-offline (O2O) commerce is the new trend that merges online commerce with traditional industries in various fields. The primary purpose of this paper is to find out which factors influence customers' intention to switch from call-based driver-for-hire services to O2O app-based services. This study used variables and factors based on Theory of Switching Intention, and Extended Unified Theory of Acceptance and Use of Technology in order to design research questions. We surveyed 500 users of call-based driver-for-hire services. According to the result of this study, dissatisfaction with the current call-based driver-for-hire services is estimated to be a significant factor that strengthens customers' intention to switch from the call-based driver-for-hire services to the app-based services. Loyalty to the previous call-based driver-for-hire services was not seen as a crucial motivator that causes customers to switch to the new O2O driver service. Switching cost also did not play a key role in explaining the relationship between dissatisfaction with the current call-based service and the intention to use the new app-based service. Performance expectancy, easiness in use, the level of user's knowledge or available assistance in relation to the use of app-based services, and expectancy for reasonable price was found to have meaningful impacts on customers' intention to switch from the call-based driver-for-hire services to the app-based services. Age, gender and user experience on the new service were found incapable of moderating the relationship between aforementioned factors which influence customers' choice of the app-based driver-for-hire service, and customers' intent to switch to the app-based service.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.1-36
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• 2020

This study is to reveal the acceptance factors of the Market Sentiment Index (MSI) created by reflecting the investor sentiment extracted by processing unstructured big data. The research model was established by exploring exogenous variables based on the rational behavior theory and applying the Technology Acceptance Model (TAM). The acceptance of MSI provided to investors in the stock market was found to be influenced by the exogenous variables presented in this study. The results of causal analysis are as follows. First, self-efficacy, investment opportunities, Innovativeness, and perceived cost significantly affect perceived ease of use. Second, Diversity of services and perceived benefits have a statistically significant impact on perceived usefulness. Third, Perceived ease of use and perceived usefulness have a statistically significant effect on attitude to use. Fourth, Attitude to use statistically significantly influences the intention to use, and the investment opportunities as an independent variable affects the intention to use. Fifth, the intention to use statistically significantly affects the final dependent variable, the intention to use continuously. The mediating effect between the independent and dependent variables of the research model is as follows. First, The indirect effect on the causal route from diversity of services to continuous use intention was 0.1491, which was statistically significant at the significance level of 1%. Second, The indirect effect on the causal route from perceived benefit to continuous use intention was 0.1281, which was statistically significant at the significance level of 1%. The results of the multi-group analysis are as follows. First, for groups with and without stock investment experience, multi-group analysis was not possible because the measurement uniformity between the two groups was not secured. Second, the analysis result of the difference in the effect of independent variables of male and female groups on the intention to use continuously, where measurement uniformity was secured between the two groups, In the causal route from usage attitude to usage intention, women are higher than men. And in the causal route from use intention to continuous use intention, males were very high and showed statistically significant difference at significance level 5%.

• The KIPS Transactions:PartC
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• v.10C no.6
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• pp.683-694
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• 2003

We present X-tree Diff, a change detection algorithm for tree-structured data. Our work is motivated by need to monitor massive volume of web documents and detect suspicious changes, called defacement attack on web sites. From this context, our algorithm should be very efficient in speed and use of memory space. X-tree Diff uses a special ordered labeled tree, X-tree, to represent XML/HTML documents. X-tree nodes have a special field, tMD, which stores a 128-bit hash value representing the structure and data of subtrees, so match identical subtrees form the old and new versions. During this process, X-tree Diff uses the Rule of Delaying Ambiguous Matchings, implying that it perform exact matching where a node in the old version has one-to one corrspondence with the corresponding node in the new, by delaying all the others. It drastically reduces the possibility of wrong matchings. X-tree Diff propagates such exact matchings upwards in Step 2, and obtain more matchings downwsards from roots in Step 3. In step 4, nodes to ve inserted or deleted are decided, We aldo show thst X-tree Diff runs on O(n), woere n is the number of noses in X-trees, in worst case as well as in average case, This result is even better than that of BULD Diff algorithm, which is O(n log(n)) in worst case, We experimented X-tree Diff on reat data, which are about 11,000 home pages from about 20 wev sites, instead of synthetic documets manipulated for experimented for ex[erimentation. Currently, X-treeDiff algorithm is being used in a commeercial hacking detection system, called the WIDS(Web-Document Intrusion Detection System), which is to find changes occured in registered websites, and report suspicious changes to users.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.29-56
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• 2021

Recently, various types of products have been launched with the rapid growth of the e-commerce market. As a result, many users face information overload problems, which is time-consuming in the purchasing decision-making process. Therefore, the importance of a personalized recommendation service that can provide customized products and services to users is emerging. For example, global companies such as Netflix, Amazon, and Google have introduced personalized recommendation services to support users' purchasing decisions. Accordingly, the user's information search cost can reduce which can positively affect the company's sales increase. The existing personalized recommendation service research applied Collaborative Filtering (CF) technique predicts user preference mainly use quantified information. However, the recommendation performance may have decreased if only use quantitative information. To improve the problems of such existing studies, many studies using reviews to enhance recommendation performance. However, reviews contain factors that hinder purchasing decisions, such as advertising content, false comments, meaningless or irrelevant content. When providing recommendation service uses a review that includes these factors can lead to decrease recommendation performance. Therefore, we proposed a novel recommendation methodology through CNN-based review usefulness score prediction to improve these problems. The results show that the proposed methodology has better prediction performance than the recommendation method considering all existing preference ratings. In addition, the results suggest that can enhance the performance of traditional CF when the information on review usefulness reflects in the personalized recommendation service.

• Korean Journal of Community Nutrition
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• v.26 no.5
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• pp.327-336
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• 2021

Objectives: This study was conducted to create a 3D printable snack dish model for the elderly with low food or fluid intake along with barriers towards eating. Methods: The decision was made by the hybrid-brainstorming method for creating the 3D model. Experts were assigned based on their professional areas such as clinical nutrition, food hygiene and chemical safety for the creation process. After serial feedback processes, the grape shape was suggested as the final model. After various concept sketching and making clay models, 3D-printing technology was applied to produce a prototype. Results: 3D design modeling process was conducted by SolidWorks program. After considering Dietary reference intakes for Koreans (KDRIs) and other survey data, appropriate supplementary water serving volume was decided as 285 mL which meets 30% of Adequate intake. To consider printing output conditions, this model has six grapes in one bunch with a safety lid. The FDM printer and PLA filaments were used for food hygiene and safety. To stimulate cognitive functions and interests of eating, numbers one to six was engraved on the lid of the final 3D model. Conclusions: The newly-developed 3D model was designed to increase intakes of nutrients and water in the elderly with dementia during snack time. Since dementia patients often forget to eat, engraving numbers on the grapes was conducted to stimulate cognitive function related to the swallowing and chewing process. We suggest that investigations on the types of foods or fluids are needed in the developed 3D model snack dish for future studies.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.79-105
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• 2023

Due to unprecedented extreme weather events such as global warming and climate change, many parts of the world suffer from severe pain, and economic losses are also snowballing. In order to address these problems, 'The Paris Agreement' was signed in 2016, and an intergovernmental consultative body was formed to keep the average temperature rise of the Earth below 1.5℃. Korea also declared 'Carbon Neutrality in 2050' to prevent climate catastrophe. In particular, it was found that the increase in temperature caused by greenhouse gas emissions hurts the environment and society as a whole, as well as the export-dependent economy of Korea. In addition, as the diversification of transportation types is accelerating, the change in means of choice is also increasing. As the development paradigm in the low-growth era changes to urban regeneration, interest in idle railway sites is rising due to reduced demand for routes, improvement of alignment, and relocation of urban railways. Meanwhile, it is possible to partially achieve the solar power generation goal of 'Renewable Energy 3020' by utilizing already developed but idle railway sites and take advantage of being free from environmental damage and resident acceptance issues surrounding the location; but the actual use and plan for these solar power facilities are still lacking. Therefore, in this study, using the big data provided by the Korea National Railway and the Renewable Energy Cloud Platform, we develop an algorithm to discover and analyze suitable idle sites where solar power generation facilities can be installed and identify potentially applicable areas considering conditions desired by users. By searching and deriving these idle but relevant sites, it is intended to devise a plan to save enormous costs for facilities or expansion in the early stages of development. This study uses various cluster analyses to develop an optimal algorithm that can derive solar power plant locations on idle railway sites and, as a result, suggests 202 'actively recommended areas.' These results would help decision-makers make rational decisions from the viewpoint of simultaneously considering the economy and the environment.

• Journal of Food Hygiene and Safety
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• v.38 no.3
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• pp.123-130
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• 2023

Salmonella spp. are prevalent foodborne pathogens that are infective at relatively low concentrations, thus posing a serious health threat, especially to young children and the elderly. In several countries, the management and regulation of Salmonella spp. in food, including seafood, adhere to a negative detection standard. The risk of infection is particularly high when seafood is consumed raw, which underscores the importance of timely detection of pathogenic microorganisms, such as Salmonella. Accordingly, this study aimed to develop a combined pre-treatment and detection method that includes pre-culture and DNA extraction in order to detect five species of Salmonella at concentrations below 10 CFU/mL in seafood. The effectiveness of the proposed method was assessed in terms of the composition of the enrichment (pre-culture) medium, minimum incubation time, and minimum cell concentration for pathogen detection. Furthermore, a practical DNA extraction method capable of effectively handling high salt conditions was tested and found to be successful. Through polymerase chain reaction, Salmonella spp. Were detected and positively identified in shellfish samples at cell concentrations below 10 CFU/g. Thus, the proposed method, combining sample pre-treatment and cell culture with DNA extraction, was shown to be an effective strategy for detecting low cellular concentrations of harmful bacteria. The proposed methodology is suitable as an economical and practical in situ pre-treatment for effective detection of Salmonella spp. in seafood.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.79-92
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• 2015

Knowledge map is widely used to represent knowledge in many domains. This paper presents a method of integrating the national R&D data and assists of users to navigate the integrated data via using a knowledge map service. The knowledge map service is built by using a lightweight ontology and a topic modeling method. The national R&D data is integrated with the research project as its center, i.e., the other R&D data such as research papers, patents, and reports are connected with the research project as its outputs. The lightweight ontology is used to represent the simple relationships between the integrated data such as project-outputs relationships, document-author relationships, and document-topic relationships. Knowledge map enables us to infer further relationships such as co-author and co-topic relationships. To extract the relationships between the integrated data, a Relational Data-to-Triples transformer is implemented. Also, a topic modeling approach is introduced to extract the document-topic relationships. A triple store is used to manage and process the ontology data while preserving the network characteristics of knowledge map service. Knowledge map can be divided into two types: one is a knowledge map used in the area of knowledge management to store, manage and process the organizations' data as knowledge, the other is a knowledge map for analyzing and representing knowledge extracted from the science & technology documents. This research focuses on the latter one. In this research, a knowledge map service is introduced for integrating the national R&D data obtained from National Digital Science Library (NDSL) and National Science & Technology Information Service (NTIS), which are two major repository and service of national R&D data servicing in Korea. A lightweight ontology is used to design and build a knowledge map. Using the lightweight ontology enables us to represent and process knowledge as a simple network and it fits in with the knowledge navigation and visualization characteristics of the knowledge map. The lightweight ontology is used to represent the entities and their relationships in the knowledge maps, and an ontology repository is created to store and process the ontology. In the ontologies, researchers are implicitly connected by the national R&D data as the author relationships and the performer relationships. A knowledge map for displaying researchers' network is created, and the researchers' network is created by the co-authoring relationships of the national R&D documents and the co-participation relationships of the national R&D projects. To sum up, a knowledge map-service system based on topic modeling and ontology is introduced for processing knowledge about the national R&D data such as research projects, papers, patent, project reports, and Global Trends Briefing (GTB) data. The system has goals 1) to integrate the national R&D data obtained from NDSL and NTIS, 2) to provide a semantic & topic based information search on the integrated data, and 3) to provide a knowledge map services based on the semantic analysis and knowledge processing. The S&T information such as research papers, research reports, patents and GTB are daily updated from NDSL, and the R&D projects information including their participants and output information are updated from the NTIS. The S&T information and the national R&D information are obtained and integrated to the integrated database. Knowledge base is constructed by transforming the relational data into triples referencing R&D ontology. In addition, a topic modeling method is employed to extract the relationships between the S&T documents and topic keyword/s representing the documents. The topic modeling approach enables us to extract the relationships and topic keyword/s based on the semantics, not based on the simple keyword/s. Lastly, we show an experiment on the construction of the integrated knowledge base using the lightweight ontology and topic modeling, and the knowledge map services created based on the knowledge base are also introduced.