• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.3
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• pp.80-90
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• 1994

In this paper, a high-resolution algorithm for detecting the orientation and position of the SMD and an algorithm for compensating the position and skew angle of the PCB are proposed. The proposed algorithm for the first topic consists of two parts. Its first part is a preprocessing step. in which corner points of the SMD are detected and they are grouped. Then the coarse angle of the principal axis is obtained by line fitting. The second part is a main processing step, in which the fuzzy Hough transform over the limited range of angles is applied to the corner points to detect precisely the orientation of the SMD. The position of the SMD is determined by using its four corner points. The proposed algorithm for the second topic is the one which detects a rotation angle and translation parameters of the PCB using a template matching method. The computer simulation shows that the parametes obtained by proposed algorithms are more precise than those by the several conventional methods considered. The proposed algorithms can be applied to the fast and accurate automatic inspection systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.663-677
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• 2023

As the paradigm of future vehicles changes, the interest in automotive semiconductor, which plays a key role in realizing this, is increasing. Automotive semiconductors are the technology with very high entry barriers that require a lot of effort and time because it must secure technology readiness level and also consider safety and reliability. In this technology field, it is very important to develop new businesses and create opportunities through technology trend analysis. However, systematic analysis and application of automotive semiconductor technology trends are currently lacking. In this paper, U.S. registered patent documents related to automotive semiconductor were collected and investigated based on the patent's IPC. The main technology of automotive semiconductor was analyzed through topic modeling, and the technology path such as emerging technology was investigated through cosine similarity. We identified that those emerging technologies such as driving control for vehicle and AI service appeared. We observed that as time passed, both convergence and independence of automotive semiconductor technology proceeded simultaneously.

• Journal of Information Technology Applications and Management
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• v.30 no.2
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• pp.19-30
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• 2023

This study aims to analyze service improvement and success factors of electric scooter sharing service companies by using text mining after collecting reviews of shared electric scooter service applications among various models of sharing economy. In this study, the factors of satisfaction and dissatisfaction of service users were identified using the term frequency inverse document frequency (TF-IDF) technique, and topics for each keyword were extracted using the Latent Dirichlet Allocation (LDA) Topic Modeling technique. According to the analysis results, the main topics were entertainment, safety, service area, application complaints, use complaints, convenience, and mobility. Using the analysis results of this study, employees and researchers of electric scooter sharing service companies will be able to contribute to the improvement and success of related services.

• Asia Marketing Journal
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• v.26 no.1
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• pp.45-59
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• 2024

Extended Reality (XR) technology, the umbrella term covering hyper-realistic technologies, is known to enhance consumer experience and is therefore developing rapidly and being utilized across various industries. Growing studies have examined XR technology and consumer experience; however, the literature has failed to fully explore hyper-realistic technology through a holistic perspective. To fill this gap, we analyzed 720 Korean and international articles through semantic network analysis and topic modeling and identified the literature on XR research in consumer experience. As a result, we extracted six main topics: "Tourism," "Buying Behavior," "XR Technology Acceptance," "Virtual Space," "Game," and "XR Environment." The results provide comprehensive insight on XR technology in consumer experience, whereas the literature is bounded on the production side as revealing a lack of academic discourse on consumer rights and responsibilities. Research reflecting the consumer welfare perspective is, therefore, recommended for future studies.

• Asia Marketing Journal
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• v.26 no.2
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• pp.104-128
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• 2024

More consumers are choosing pro-consumption for social change, but scholars know little about why and how consumers engage in pro-consumption behaviors. A newly emerged pro-consumption behavior called "Don-jjul," which appeared during the COVID-19 pandemic in South Korea, refers to compensating businesses that have engaged in altruistic actions by boosting their sales. This study used Latent Dirichlet Allocation (LDA) of topic modeling, sentiment analysis, and in-depth interviews to investigate the perceptions, motivations, and emotions regarding Don-jjul. As a result, the study revealed pro-consumers' perceptions of Don-jjul as "collective pro-consumption for contributing to social well-being." Don-jjul has two main motives: "supporting underdogs with difficulties" and "compensating good businesses economically." We also found two ambivalent emotions evoked by Don-jjul: "respect for good business owners" and "concerns regarding the misuse of Don-jjul." The results contribute to pro-consumption research for social well-being, providing business opportunities for retailers and CSR managers with a deep understanding of pro-consumers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6411-6418
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• 2015

To respond the climate change and environmental pollution, the studies on renewable energy policies are increasing. The renewable energy is a new growth engine technology represented by the green industry and green technology. At present, the investments for the renewable energy supply and technology development projects of three main strategy sectors such as sunlight, wind power and hydrogen fuel cell are implemented in our country, while they are still in the early stage, accordingly reducing those uncertainty for the research direction and investment fields is the most urgent issue among others. Thus, this study applied text mining method and multinominal topic model among the big data analysis methods on our country's newspaper articles concerning the renewable energy over the last 10 years, and then analyzed the core issues and global research trend, forecasting the renewable energy fields with the growth potential. It is predicted that these results of the study based on information and communication technology will be actively applied on the renewable energy fields.

• Smart Media Journal
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• v.10 no.2
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• pp.38-47
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• 2021

This study analyzed media reports on the Address of Things, which are being introduced through the amendment of related law and pilot projects. The titles and its texts in the media's reports were collected by searching for 'Address of Things' on the Naver News Platform. Then, we analyzed the corpus using by topic modeling and network analysis. As a result, there were four topics: 'Promotion of the address of things system', Proof of assigning Address of Things', 'Improvement of usage of the Roadname Address Systems', and 'Education and public relation for the address activation'. It was confirmed that the topic 'Proof of assigning Address of Things' was the main agenda. We presented some implication by comparing the results with the 「3rd Basic Plan for Address Policy (2018-2022)」 of the Ministry of Public Administration and Security.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.86-98
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• 2022

This study explored the agenda of conservative and liberal media in reporting COVID-19, and observed the effects of each media's partisan agenda-setting on the public with the same political orientation. To this end, researchers collected 5,286 articles on COVID-19 from five newspapers, and analyzed the survey data of 1,067 respondents. Next, the researchers extracted main agenda using LDA topic modeling and analyzed the correlation between newspapers' agenda and survey respondents' agenda. As results, 15 topics such as infection, vaccine, and economic crisis appeared as the media agenda, and the difference in major agenda between conservative and liberal media was found. On the other hand, the conservative media exerted an agenda-setting influence not only on the conservatives but also on the liberals, but the liberal media did not have a significant influence on the liberals. This study contributes to the methodological expansion of agenda-setting research by introducing a new way to confirm the effectiveness of agenda-setting by combining topic modeling and survey.

• Journal of Industrial Convergence
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• v.20 no.1
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• pp.43-51
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• 2022

The purpose of this study is to provide basic information necessary for the establishment of mobile service marketing strategies, educational service development, and engineering education for Generation Z by analyzing the utilitization of various applications by Gen Z. To this end, 177 essays on mobile service usage experience were collected, major topics were analyzed using topic modeling, and these were visualized through word cloud analysis. As a result of the study, the main topics were related to 'transportation' such as movement and public transportation, 'personal management' such as schedule management, financial management, food management, 'transaction' such as checkout, meeting, purchase, 'leisure' such as eating out, travel, study, culture. Additionally, words such as time, thought, people, life, bus, information, confirmation, payment, KakaoTalk, and so on were found to have a high of frequency of use. Also, there was found to be a difference between topics by college. This study is meaningful in that it collected essays, which are unstructured data, and analyzed them through topic modeling.

• Smart Media Journal
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• v.12 no.6
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• pp.27-34
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• 2023

As Netflix usage has increased due to the COVID-19 pandemic, users' experiences with the service have also increased. Therefore, this study aims to conduct topic modeling analysis based on Netflix review data to explore the changes in Netflix user experience and service before and after the COVID-19 pandemic. We collected Netflix app review data from the Google Play Store using the Google Play Scraper library, and used topic modeling to examine keyword differences between app reviews before and after the pandemic. The analysis revealed four main topics: Netflix app features, Netflix content, Netflix service usage, and Netflix overall reviews. After the pandemic, when user experience increased, users tended to use more diverse and detailed keywords in their reviews. By using Netflix review data to analyze users' opinions, this study shows the changes in user experience of Netflix services before and after the pandemic, which can be used as a guide to strengthen competitiveness in the competitive OTT market.