• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.179-186
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• 2021

We have been developed the smart tourism app and the Instagram and YouTube contents to provide personalized tourism information and travel product information to individual tourists. In this paper, we develop a rule-based smart tourism chatbot with the khaiii (Kakao Hangul Analyzer III) morphological analyzer and Neo4J graph database. In the proposed chatbot system, we use a morpheme analyzer, a proper noun dictionary including tourist destination names, and a general noun dictionary including containing frequently used words in tourist information search to understand the intention of the user's question. The tourism knowledge base built using the Neo4J graph database provides adequate answers to tourists' questions. In this paper, the nodes of Neo4J are Area based on tourist destination address, Contents with property of tourist information, and Service including service attribute data frequently used for search. A Neo4J query is created based on the result of analyzing the intention of a tourist's question with the property of nodes and relationships in Neo4J database. An answer to the question is made by searching in the tourism knowledge base. In this paper, we create the tourism knowledge base using more than 1300 Jeju tourism information used in the smart tourism app. We plan to develop a multilingual smart tour chatbot using the named entity recognition (NER), intention classification using conditional random field(CRF), and transfer learning using the pretrained language models.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.730-737
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• 2018

With the increasing number of health consumers aiming for a happy quality of life, the O2O medical marketing market is activated by choosing reliable health care facilities and receiving high quality medical services based on the medical information distributed on web's blog. Because unstructured text data used on the Internet, mobile, and social networks directly or indirectly reflects authors' interests, preferences, and expectations in addition to their expertise, it is difficult to guarantee credibility of medical information. In this study, we propose a blog reading system that provides users with a higher quality medical information service by classifying medical information blogs (medical blog, ad blog) using bigdata and MLP processing. We collect and analyze many domestic medical information blogs on the Internet based on the proposed big data and machine learning technology, and develop a personalized health information recommendation system for each disease. It is expected that the user will be able to maintain his / her health condition by continuously checking his / her health problems and taking the most appropriate measures.

• Journal of Fashion Business
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• v.23 no.1
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• pp.14-24
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• 2019

Various types of functional bedding for inducing and maintaining sleep, are developed and launched with the importance of improving health through sleep emphasized currently. The purpose of this study is to examine development status and direction of functional bedding in the $4^{th}$ Industrial Revolution era, through systematic classification of elements of IoT-based smart bedding cases actively developed as functional bedding at home and abroad. Through previous research, literature and Internet data, characteristics and functional extension of smart bedding and the background of smart bed development was analyzed. And it was analyzed that smart bedding pursues recent functionalism and convergence of physical and digital concept such as IoT or AI, and also mental value to improve sleep quality. As bedroom where smart bedding place in has the private and limited characteristics and users are in sleep-conscious, that hard to ensure power and discomfort in carrying are moderated and the aesthetic elements are not very important, and that the smart bedding performance while sleeping were affected on developmental background. Based on CES case study and analysis on how smart beds are functionally expanded from conventional bedding, smart beds have gained information through digital sensing, and common properties that can be controlled anytime, anywhere, using a smart phone. Some set up the right environment and pose, while others stimulate nerves directly as active intervention. It is expected that smart bedding will be developed to cure user's body and mind, through active intervention when sleeping.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.29 no.4
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• pp.57-68
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• 2018

In a situation when domestic construction market is expected to be stagnant, Overseas Information System for Construction Engineering (OVICE) is operated to support the construction SMEs that advance to the global market. In this study, we aimed to improve the quality of information service by providing direction of information provision, by comparing expert questionnaire with information system user statistics. For statistical analysis of information systems, to improve the efficiency of statistical analysis that is difficult to prioritize, K-means clustering is used for more efficient analysis. As a result, analyzing the difference between the survey results and the information system statistics, we were able to identify improvement point of information provision in the system and important contents that were not highlighted during the survey.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.185-199
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• 2018

The purpose of this study is to derive the core technologies of VR using patent analysis and to explore the direction of social and public interest in VR using news analysis. In Study 1, we derived keywords using the frequency of words in patent texts, and we compared by company, year, and technical classification. Netminer, a network analysis program, was used to analyze the IPC codes of patents. In Study 2, we analyzed news articles using T-LAB program. TF-IDF was used as a keyword selection method and chi-square and association index algorithms were used to extract the words most relevant to VR. Through this study, we confirmed that VR is a fusion technology including optics, head mounted display (HMD), data analysis, electric and electronic technology, and found that optical technology is the central technology among the technologies currently being developed. In addition, through news articles, we found that the society and the public are interested in the formation and growth of VR suppliers and markets, and VR should be developed on the basis of user experience.

• Journal of Environmental Health Sciences
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• v.45 no.4
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• pp.358-369
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• 2019

Objective: This study aimed to introduce cases of exposure to humidifier disinfectant (HD) in hospitals and to present their exposure characteristics. Methods: We used data from 4,393 subjects who participated in the fourth assessment survey of environmental exposure to HD conducted by the Korea Environmental Industry & Technology Institute. In this study, we selected 301 subjects who reported their place of use of HD as a hospital. Then, we classified cases as 'Hospital-provided'. 'Probably hospital-provided', 'Individual purchased', and 'Unknown' according to the supply sources of HD. Also, we introduced detailed exposure characteristics for the selected cases. Results: Of the 4,393 subjects, 301 (6.9%) reported the use of HD in 392 hospitals (including duplicate answers for the use in ${\geq}2$ hospitals). The 301 hospital-user subjects included 139 survivors and 162 non-survivors. When we classified the 392 cases by supply sources, 'Hospital-provided' was 12.2% (48 cases), 'Probably hospital-provided' was 25.5% (100 cases), 'Individual purchased' was 59.7% (234 cases), and 'Unknown' was 2.6% (10 cases). Among the 'Hospital-provided' cases, we selected six cases and provided a detailed description of the HD use in this study. Additionally, we reported details for six cases that had purchased HD upon a doctor or nurse's recommendation and for three cases that had purchased it at hospital stores. Conclusion: This study presents various cases of HD exposure in hospitals. Because there may be a considerable burden of HD exposure in public spaces, including hospitals, further studies are necessary to assess HD exposure in hospitals and public places.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.139-148
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• 2019

The paper proposes an analytical framework for the impact of technical change on business model innovation. Based upon the examination of the relationship between the mission of business and technology, it introduces classification of technology-based business models such as problem-solving model, production model and network model, respectively employing intensive technology, interlinked technology and mediating technology as a key technology. The discussion of various cases of business model innovation shows that the impact of digital technology is first translated into the value generation in terms of efficiency or effectiveness. These new values then enable a new business model which is based on a different key technology through business model shift, expansion, unbundling, or platform. Quite often those business model changes involves system-wide innovation. The framework for the analysis of the impact of technical change on business model innovation is presented with directions for future research.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.1
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• pp.29-37
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• 2020

This paper implements a method of extracting an object about a dog through real-time image analysis and classifying dog behaviors from the extracted images. The Darknet YOLO was used to detect dog objects, and the Teachable Machine provided by Google was used to classify behavior patterns from the extracted images. The trained Teachable Machine is saved in Google Drive and can be used by ml5.js implemented on a node.js server. By implementing an interactive web server using a socket.io module on the node.js server, the classified results are transmitted to the user's smart phone or PC in real time so that it can be checked anytime, anywhere.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.6
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• pp.759-767
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• 2020

This paper proposes a new Recurrent neural network (RNN) based spectrum sensing technique for cognitive radio communications. The proposed technique determines the existence of primary user's signal without any prior information of the primary users. The method performs high-speed sampling by considering the whole sensing bandwidth and then converts the signal into frequency spectrum via fast Fourier transform (FFT). This spectrum signal is cut in sensing channel bandwidth and entered into the RNN to determine the channel vacancy. The performance of the proposed technique is verified through computer simulations. According to the results, the proposed one is superior to more than 2 [dB] than the existing threshold-based technique and has similar performance to that of the existing Convolutional neural network (CNN) based method. In addition, experiments are carried out in indoor environments and the results show that the proposed technique performs more than 4 [dB] better than both the conventional threshold-based and the CNN based methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1224-1230
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• 2020

Since the spread of smart phones, interest in wearable devices has increased and diversified, and is closely related to the lives of users, and has been used as a method for providing personalized services. In this paper, we propose a method to detect the user's behavior by applying information from a 3-axis acceleration sensor and a 3-axis gyro sensor embedded in a smartphone to a convolutional neural network. Human behavior differs according to the size and range of motion, starting and ending time, including the duration of the signal data constituting the motion. Therefore, there is a performance problem for accuracy when applied to a convolutional neural network as it is. Therefore, we proposed a Time-Division Feature Fusion Convolutional Neural Network (TDFFCNN) that learns the characteristics of the sensor data segmented over time. The proposed method outperformed other classifiers such as SVM, IBk, convolutional neural network, and long-term memory circulatory neural network.