• Journal of Korea Technology Innovation Society
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• v.22 no.3
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• pp.340-361
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• 2019

This study analyzes the technological structure of artificial intelligence (AI) and technological capabilities of AI companies based on patent information. 2589 AI patents registered in USPTO from 2007 to 2017 were collected and analyzed by the Latent Dirichlet Allocation (LDA) to derive 20 AI technology topics. Analysis of technology development trends by AI technology reveals that visual understanding, data analysis, motion control, and machine learning are growing, while language understanding and speech technology are sluggish. In addition, we also investigated leading companies in each sub-field of AI as well as core competencies of global IT companies. The findings of this study are expected to be fruitfully used for formulation and implementation of technology strategy of AI companies.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.33-39
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• 2019

As cyber attack methods are becoming more intelligent, incidents such as security breaches and international crimes are increasing. In order to predict and respond to these cyber attacks, the characteristics, methods, and types of attack techniques should be identified. To this end, many security companies are publishing security intelligence reports to quickly identify various attack patterns and prevent further damage. However, the reports that each company distributes are not structured, yet, the number of published intelligence reports are ever-increasing. In this paper, we propose a method to extract structured data from unstructured security intelligence reports. We also propose an automatic intelligence report analysis system that divides a large volume of reports into sub-groups based on their topics, making the report analysis process more effective and efficient.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.211-225
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• 2023

In the future, infotainment systems are expected to play a pivotal role in mobility ecosystems connecting users and vehicles. This study draws user-experience factors from reviews of Android Auto, a car infotainment application, and analyzes factors that affect satisfaction. The user-experience factors of infotainment have been redefined based on previous studies. To analyze actual user-experience factors, topics are obtained, applied, and interpreted from user discourse through topic modeling. Sentiment analysis and logistic regression are used to determine positive and negative user-experience factors that affect satisfaction. Results of the empirical analysis show that Ease of Use and Understandability are factors that have the greatest impact on satisfaction, and Flexibility, Safety, and Playfulness are factors that have the most critical effect on dissatisfaction. Therefore, this paper suggests ways to improve the satisfaction level of the infotainment system, and establishes a strategy accordingly.

• Korea Trade Review
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• v.48 no.1
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• pp.29-53
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• 2023

This study analyzes the statements made by representatives of member countries at the WTO Ministerial Conference (MC), the highest decision-making body of the WTO, to examine the position and attitude that Korea has shown at the WTO during the last 27 years. After constructing text dataset by extracting about 1,800 statement documents made by member countries from the WTO document database, the text mining technique is applied to figure out the characteristics of Korea's statements compared to other member countries. Through formal characteristics such as the number of remarks and length of speech, basic attitudes such as continuity of Korea's interest in the WTO and the level of interest in the WTO are measured. In terms of substantive characteristics, the topics in the statements of Korea are categorized through the LDA topic model, and the keywords of Korea for each session are analyzed through comparative analysis with statements by other member countries.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.19 no.1
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• pp.94-131
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• 2007

A review on the papers published in the Korean Journal of Air-Conditioning and Refrigerating Engineering in 2004 and 2005 has been done. Focus has been put on current status of research in the aspect of heating, cooling, air-conditioning, ventilation, sanitation and building environment. The conclusions are as follows. (1) Most of fundamental studies on fluid flow were related with heat transportation of facilities. Drop formation and rivulet flow on solid surfaces were interesting topics related with condensation augmentation. Research on micro environment considering flow, heat, humidity was also interesting for comfortable living environment. It can be extended considering biological aspects. Development of fans and blowers of high performance and low noise were continuing topics. Well developed CFD and flow visualization(PIV, PTV and LDV methods) technologies were widely applied for developing facilities and their systems. (2) The research trends of the previous two yews are surveyed as groups of natural convection, forced convection, electronic cooling, heat transfer enhancement, frosting and defrosting, thermal properties, etc. New research topics introduced include natural convection heat transfer enhancement using nanofluid, supercritical cooling performance or oil miscibility of $CO_2$, enthalpy heat exchanger for heat recovery, heat transfer enhancement in a plate heat exchanger using fluid resonance. (3) The literature for the last two years($2004{\sim}2005$) is reviewed in the areas of heat pump, ice and water storage, cycle analysis and reused energy including geothermal, solar and unused energy). The research on cycle analysis and experiments for $CO_2$ was extensively carried out to replace the Ozone depleting and global warming refrigerants such as HFC and HCFC refrigerants. From the year of 2005, the Gas Engine Heat Pump(GHP) has been paid attention from the viewpoint of the gas cooling application. The heat pipe was focused on the performance improvement by the parametric analysis and the heat recovery applications. The storage systems were studied on the performance enhancement of the storage tank and cost analysis for heating and cooling applications. In the area of unused energy, the hybrid systems were extensively introduced and the life cycle cost analysis(LCCA) for the unused energy systems was also intensively carried out. (4) Recent studies of various refrigeration and air-conditioning systems have focused on the system performance and efficiency enhancement. Heat transfer characteristics during evaporation and condensation are investigated for several tube shapes and of alternative refrigerants including carbon dioxide. Efficiency of various compressors and expansion devices are also dealt with for better modeling and, in particular, performance improvement. Thermoelectric module and cooling systems are analyzed theoretically and experimentally. (5) According to the review of recent studies on ventilation systems, an appropriate ventilation systems including machenical and natural are required to satisfied the level of IAQ. Also, an recent studies on air-conditioning and absorption refrigeration systems, it has mainly focused on distribution and dehumidification of indoor air to improve the performance were carried out. (6) Based on a review of recent studies on indoor environment and building service systems, it is noticed that research issues have mainly focused on optimal thermal comfort, improvement of indoor air Quality and many innovative systems such as air-barrier type perimeter-less system with UFAC, radiant floor heating and cooling system and etc. New approaches are highlighted for improving indoor environmental condition as well as minimizing energy consumption, various activities of building control and operation strategy and energy performance analysis for economic evaluation.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.175-186
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• 2023

In this paper, we aim to build a gentrification analysis model and examine its characteristics, focusing on the point at which rents rose sharply alongside the recovery of commercial districts after the gradual resumption of daily life. Recently, in Korea, the influence of social distancing measures after the pandemic has led to the formation of small-scale commercial districts, known as 'hot places', rather than large-scale ones. These hot places have gained popularity by leveraging various media and social networking services to attract customers effectively. As a result, with an increase in the floating population, commercial districts have become active, leading to a rapid surge in rents. However, for small business owners, coping with the sudden rise in rent even with increased sales can lead to gentrification, where they might be forced to leave the area. Therefore, in this study, we seek to analyze the periods before and after by identifying points where rents rise sharply as commercial districts experience revitalization. Firstly, we collect text data to explore topics related to gentrification, utilizing LDA topic modeling. Based on this, we gather data at the commercial district level and build a gentrification analysis model to examine its characteristics. We hope that the analysis of gentrification through this model during a time when commercial districts are being revitalized after facing challenges due to the pandemic can contribute to policies supporting small businesses.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.1
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• pp.19-30
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• 2023

An electric scooter(e-scooter), one popularized micro-mobility vehicle has shown rapidly increasing use in many cities. In South Korea, the use of e-scooters has greatly increased, as some companies have launched e-scooter sharing services in a few large cities, starting with Seoul in 2018. However, the use of e-scooters is still controversial because of issues such as parking and safety. Since the perception toward the means of transportation affects the mode choice, it is necessary to track the trends for electric scooters to make the use of e-scooters more active. Hence, this study aimed to analyze the trends related to e-scooters. For this purpose, we analyzed news articles related to e-scooters published from 2014 to 2020 using dynamic topic modeling to extract issues and sentiment analysis to investigate how the degree of positive and negative opinions in news articles had changed. As a result of topic modeling, it was possible to extract three different topics related to micro-mobility technologies, shared e-scooter services, and regulations for micro-mobility, and the proportion of the topic for regulations for micro-mobility increased as shared e-scooter services increased in recent years. In addition, the top positive words included quick, enjoyable, and easy, whereas the top negative words included threat, complaint, and ilegal, which implies that people satisfied with the convenience of e-scooter or e-scooter sharing services, but safety and parking issues should be addressed for micro-mobility services to become more active. In conclusion, this study was able to understand how issues and social trends related to e-scooters have changed, and to determine the issues that need to be addressed. Moreover, it is expected that the research framework using dynamic topic modeling and sentiment analysis will be helpful in determining social trends on various areas.

• Journal of Technology Innovation
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• v.26 no.4
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• pp.199-232
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• 2018

There are increasing needs for understanding and fathoming of business management environment through big data analysis at industrial and corporative level. The research using the company disclosure information, which is comprehensively covering the business performance and the future plan of the company, is getting attention. However, there is limited research on developing applicable analytical models leveraging such corporate disclosure data due to its unstructured nature. This study proposes a text-mining-based analytical model for industrial and firm level analyses using publicly available company disclousre data. Specifically, we apply LDA topic model and word2vec word embedding model on the U.S. SEC data from the publicly listed firms and analyze the trends of business topics at the industrial and corporate levels. Using LDA topic modeling based on SEC EDGAR 10-K document, whole industrial management topics are figured out. For comparison of different pattern of industries' topic trend, software and hardware industries are compared in recent 20 years. Also, the changes of management subject at firm level are observed with comparison of two companies in software industry. The changes of topic trends provides lens for identifying decreasing and growing management subjects at industrial and firm level. Mapping companies and products(or services) based on dimension reduction after using word2vec word embedding model and principal component analysis of 10-K document at firm level in software industry, companies and products(services) that have similar management subjects are identified and also their changes in decades. For suggesting methodology to develop analysis model based on public management data at industrial and corporate level, there may be contributions in terms of making ground of practical methodology to identifying changes of managements subjects. However, there are required further researches to provide microscopic analytical model with regard to relation of technology management strategy between management performance in case of related to various pattern of management topics as of frequent changes of management subject or their momentum. Also more studies are needed for developing competitive context analysis model with product(service)-portfolios between firms.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.273-280
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• 2020

Automatic Static Analysis Tools help developers to quickly find potential defects in source code with less effort. However, the tools reports a large number of false positive warnings which do not have to fix. In our study, we proposed an artificial neural network-based warning classification method using topic models of source code blocks. We collect revisions for fixing bugs from software change management (SCM) system and extract code blocks modified by developers. In deep learning stage, topic distribution values of the code blocks and the binary data that present the warning removal in the blocks are used as input and target data in an simple artificial neural network, respectively. In our experimental results, our warning classification model based on neural network shows very high performance to predict label of warnings such as true or false positive.

• Journal of the Korea Convergence Society
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• v.10 no.7
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• pp.199-211
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• 2019

This study analyzed the research trends of college students' entrepreneurship in 172 scholarly articles in the registered journals of the Korea Research Foundation from 2010 to 2018. The results of this study are as follows: First, the research areas and topics on university students' entrepreneurship focuses on not only characteristics of entrepreneurship and entrepreneur but also entrepreneurship education. Also, the research method was dependent on the quantitative research method coupled with the statistic techniques such as descriptive statistics, correlation, t-test, ANOVA, regression analysis, and structural equation modeling. In future research, it is necessary to expand research areas to startup idea design, startup business environment and policies. Also, it is necessary to explore various variables related to entrepreneurship, not focusing on specific variables such as entrepreneurship, entrepreneurship education as well as to analyze meta analysis of the relationship between the variables influencing on the entrepreneurial intention. In addition, qualitative research and mixed research are needed to explore the process of developing entrepreneurship and the factors affecting the process of entrepreneurship.