• The Journal of Korean Institute of Information Technology
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• v.17 no.2
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• pp.71-77
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• 2019

With 5G standards proceeding in earnest and increasing demand for services of indoor localization, research on indoor location recognition is being studied in various industrial fields, and research based on fingerprint recognition technology using Wireless Local Area Network (WLAN) is representative. In this paper, we propose an indoor positioning system based on fingerprinting technique that uses Cloud Radio Access Network (C-RAN) architecture and Channel State Information (CSI). In order to improve the performance in indoor positioning, we combined existing fingerprinting method and K nearest neighbor (KNN) technology which is one of the machine running technique. The performance improvements of the proposed indoor positioning system was verified by comparative experiments with the existing localization technique in a indoor localizztion testbed.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.595-607
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• 2021

In response to increasing demand of contactless services, the overall usage of "task-oriented chatbots" in the industry is on the rise. The purpose of a task-oriented chatbot is to raise the efficiency of data sharing and workflow; in order to establish a guideline, there must be a discussion on "what" and "how" to share information. We investigate the effects of personalization and different types of the interface on 'performance expectancy', 'effort expectancy', 'intention to use', and 'satisfaction' in the context of a task-oriented chatbot. Results show that 'intention to use' and 'satisfaction' were higher when the level of personalization was higher. Within the closed-discourse interface, 'intention to use' and 'satisfaction' were higher when personalization was lower. We highlight the practical insights in the use of personalization and types of chatbot interface based on 'perceived personalization', 'expectation disconfirmation theory', 'privacy concern' and 'privacy paradox'.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.29-34
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• 2021

With the advent of the 4th industrial revolution era, IT technology is creating new services that have not existed by converging with various existing industries and fields. In particular, in the field of artificial intelligence, chatbots and the latest technologies have developed dramatically with the development of natural language processing technology, and various business processes are processed through chatbots. This study is a study on a system that provides a close answer to the question the user wants to find by creating a structural form for legal inquiries through Slot Filling-based chatbot technology, and inputting a predetermined type of question. Using the proposal system, it is possible to construct question-and-answer data in a more structured form of legal information, which is unstructured data in text form. In addition, by managing the accumulated Q&A data through a big data storage system such as Apache Hive and recycling the data for learning, the reliability of the response can be expected to continuously improve.

• Journal of Industrial Convergence
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• v.18 no.6
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• pp.147-154
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• 2020

It is difficult to educate the overall operation of public and private blockchains with different characteristics. Recently, most education for blockchain is targeted at public blockchains such as Bitcoin and Ethereum. However, in an actual business environment, a private blockchain such as HyperLedger Fabric is used because access to corporate data is controlled through user authentication. In the case of HLF-based education, it is necessary to understand various components that are not in the public blockchain, such as peers, orderers, and channels. In this paper, a lab framework for HLF is designed for an efficient and systematic understanding of the functions and operations. The framework consists of HLF network, chaincode, and decentralized software control functions. Through the framework, the network configuration, distribution and activation of chaincode, and dApp execution process were checked step by step, and it was very easy to understand the overall flow for blockchain services. In addition, it is expected that a systematic understanding of the overall flow will be possible even in future network expansion.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.571-576
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• 2021

This study was carried out to overcome the problems of the existing fitness business and to build a fitness system that can meet the increased demand in the Corona situation. As a platform technology for non-face-to-face fitness edutainment service, it is a next-generation fitness exercise device that can use various body parts and synchronize network-type information. By synchronizing the exercise information of the fitness equipment, it was composed of learning contents through MR-based avatars. A quantified result was derived from examining the applicability of the customized evaluation system through momentum analysis with A.I analysis applying the LSTM-based algorithm according to the cumulative exercise effect of the user. It is a motion capture and 3D visualization fitness program for the application of systematic exercise techniques through academic experts, and it is judged that it will contribute to the improvement of the user's fitness knowledge and exercise ability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1053-1059
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• 2021

In order to realize a smart home, a new type of service that converges the two technologies is required as a method to overcome the respective limitations of augmented reality and IoT technologies. Augmented reality recognizes objects and projects augmented content with the recognized objects on the screen. This technology mainly uses image processing methods such as markers as a method for recognizing objects. In this paper, an augmented reality-based IoT control platform using markers was developed. By defining a marker unique to the object, a unique identifier displayed on the camera was distinguished. A smart home system was implemented by calling a controller to control things. The proposed system receives state information of objects through symptom reality and transmits control commands. The proposed platform was verified by manipulating household lights.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.941-948
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• 2021

This study investigated the differences between active and inactive TV watching groups, in terms of residential characteristics, of class-oriented drama viewing rate. We compared Flow and Social Comparison Theories to explain the relationship between class-oriented contents in the drama and viewing rate. We collected 110,000 TV viewers data of 4 class-oriented and the other 4 dramas, aired between Feb. 2016 and March 2019, through D-Live local cable service provider. Controlling gender ratio and income level which may affect viewing rate, we found that class-oriented content significantly and positively affects viewing rate in active watching group while the same content significantly and negatively affects viewing rate in inactive watching group. These results imply that Flow and Social Comparison Theories may apply in opposite directions in different watching groups.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.475-480
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• 2021

With the rapid development of mobile, cloud computing technology and social network services, we are in the flood of huge data and realize that these large-scale data contain very precious value and important information. Big data, however, have both latent useful value and critical risks, so, nowadays, a lot of researches and applications for big data has been executed actively in order to extract useful information from big data efficiently and make the most of the potential information effectively. At this moment, the data analysis technique that can extract precious information from big data efficiently is the most important step in big data computing process. In this study, we investigate various data analysis techniques that can extract the most useful information in big data computing process efficiently, compare pros and cons of those techniques, and propose proper data analysis method that can help us to find out the best solution of the big data analysis in the peculiar situation.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.6
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• pp.223-234
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• 2021

Recent advances in the 4th Industrial Revolution have accelerated the change of the shopping behavior from offline to online. Search queries show customers' information needs most intensively in online shopping. However, there are not many search query research in the field of search, and most of the prior research in the field of search query research has been studied on a limited topic and data-based basis based on researchers' qualitative judgment. To this end, this study defines the type of search query with data-based quantitative methodology by applying machine learning to search research query field to define the 15 topics of search query by conducting topic modeling based on search query and clicked document information. Furthermore, we present a new classification system of new search query types representing searching behavior characteristics by extracting key variables through principal component analysis and analyzing. The results of this study are expected to contribute to the establishment of effective search services and the development of search systems.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.519-528
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• 2022

The purpose of the study was to further investigate the direction for one-person experience design based on visual shift due to the isolation one has experienced after the COVID-19 and the factors regarding it. The study involves eight female participants who are in their twenties via digital platform. The participants were instructed to choose digital image similar to COVID-19 and to write down facts based upon the image and the researcher will look into the result microscopically. The researchers found that the isolation factors include decreased face-to-face communication, reliance on social media, heavy usage of OTT platform, limited outdoor occasion and activity, limitation of untact technology and education program, fear over the pandemic and so on. The study has shown that the one-person experience design should be heading in a direction where it adopts space design that can crossover online and offline world, digital complex design to embody realness as well as the communication design to regain the relationships with others.