• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.327-334
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• 2021

In this study, using the raw data of the 7th Food Consumption Behavior Survey(2019), compare and analyze what factors affect the food delivery service and take-out food expenditure of single-person and multi-person households. It was found that women(especially women in single-person households), have a high tendency to pursue safety preference versus price. In the future, Korea's population structure is expected to steadily increase single-person household and elderly households, and women's participation in economic activities is expected to continue to increase. In addition, the food delivery market has more than doubled compared to the previous year in 12 cities and provinces out of 17 cities and provinces nationwide with Covid-19, especially in the non-capital area, making it has become a universal service nationwide. Therefore, the growing home meal replacement market needs marketing strategies to secure and emphasize food safety.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.176-183
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• 2021

Digital medical technology is very effective and at the same time faces the challenge of protecting privacy. However, for contact tracking and exposure notification apps in COVID-19 environment, there is always a trade-off between privacy measures and the effectiveness of the app's use. Today, many countries have developed and used contact tracking and exposure notification apps in various forms to prevent the spread of COVID-19, but the suspicion of digital surveillance (digital panopticon) is unavoidable. Therefore, this study aims to identify the factors of personal information infringement and dissatisfaction through text mining analysis by extracting user reviews of "Self-Quarantine Safety Protection" in Korea. As a result of the text mining analysis, we derived four groups, 'Address recognition error', 'Exit warning error', 'Access error', and 'App. program error'. Since 'Address recognition error' and 'Exit warning error' can give the app users a strong perception that they are keeping under surveillanc by the app, transparent management of personal information protection and consent procedures related to personal information collection are required. In addition, if the other two groups are not corrected immediately due to an error in an app function or a program bug, the complaints of users can be maximized and a protest against the monitor can be raised.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.247-254
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• 2021

As COVID-19 spread, non-face-to-face activities were required, and the use of service robots is gradually increasing. This paper analyzed the relationship between the increasing trend of service robots before and after COVID-19 through keyword search containing the keyword 'service robot AND non-face-to-face' over the past three years (2018.10-20219) using BigKines, a news big data analysis system. As a result, there were 0 cases in the first period (2018.10~2019.9), 52 cases in the second period (2019.10~2020.9) and 112 cases in the third period (2020.10~2021.9), an increase of 115% compared to the second period. The keywords commonly mentioned in the analysis of related words in the second and third periods were COVID-19, AI, the Ministry of Trade, Industry, and Energy, and LG Electronics, and the weight of COVID-19 was the largest, confirming that the analysis keyword. Due to the spread of Corona 19, non-face-to-face is required, and with the development of information and communication technology, the field of application of service robots is rapidly increasing. Accordingly, for the commercialization of service robots that will lead the non-face-to-face economy, there is an urgent need to nurture human resources that require standardization and expertise in safety and performance fields.

• International Area Studies Review
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• v.14 no.1
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• pp.221-254
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• 2010

This study is for analyzing the mgmt performances of Korean tourism firms, operating as preparing strategically against FTA, one of the most importantly external environment in int'l mgmt since in the mid of 1990s. The main purpose can be mentioned to test empirically some relations between the mgmt performances of Korean tourism ones and the economic effects originated from FTA. The dependent variables of mgmt performances are classified with sales, profits and mgmt satisfaction, while the independent one regarding with economic effects from FTA are sorted based on the previous studies with the 2 following factors like direct with inbound/outbound and indirect effects. This study is conducted in two stages. Firstly, the research model is designed by the reviewing relevant theories and previous studies. Secondly, the survey of Korean tourism firms engaging in mgmt activities is implemented by collecting questionnaires. And for testing the hypothesis, the analyzing tools are used for correlation, reliability, validity and multi-regression on SPSS 12.0 and the path analysis of structural equation modeling is activated with AMOS 11.0.

• 재활복지
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• v.21 no.3
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• pp.129-146
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• 2017

In an event of an emergency, such as fire in a building, visually impaired and blind people are prone to exposed to a level of danger that is greater than that of normal people, for they cannot be aware of it quickly. Current fire detection methods such as smoke detector is very slow and unreliable because it usually uses chemical sensor based technology to detect fire particles. But by using vision sensor instead, fire can be proven to be detected much faster as we show in our experiments. Previous studies have applied various image processing and machine learning techniques to detect fire, but they usually don't work very well because these techniques require hand-crafted features that do not generalize well to various scenarios. But with the help of recent advancement in the field of deep learning, this research can be conducted to help solve this problem by using deep learning-based object detector that can detect fire using images from security camera. Deep learning based approach can learn features automatically so they can usually generalize well to various scenes. In order to ensure maximum capacity, we applied the latest technologies in the field of computer vision such as YOLO detector in order to solve this task. Considering the trade-off between recall vs. complexity, we introduced two convolutional neural networks with slightly different model's complexity to detect fire at different recall rate. Both models can detect fire at 99% average precision, but one model has 76% recall at 30 FPS while another has 61% recall at 50 FPS. We also compare our model memory consumption with each other and show our models robustness by testing on various real-world scenarios.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.151-157
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• 2019

This study is about the process capability index (PCI). In this study, we introduce several indices including the index $C_{PR}$ and present the characteristics of the $C_{PR}$ as well as its validity. The difference between the other indices and the $C_{PR}$ is the way we use to estimate the standard deviation. Calculating the index, most indices use sample standard deviation while the index $C_{PR}$ uses range R. The sample standard deviation is generally a better estimator than the range R. But in the case of the panel process, the $C_{PR}$ has more consistency than the other indices at the point of non-conforming ratio which is an important term in quality control. The reason why the $C_{PR}$ using the range has better consistency is explained by introducing the concept of 'flatness ratio'. At least one million cells are present in one panel, so we can't inspect all of them. In estimating the PCI, it is necessary to consider the inspection cost together with the consistency. Even though we want smaller sample size at the point of inspection cost, the small sample size makes the PCI unreliable. There is 'trade off' between the inspection cost and the accuracy of the PCI. Therefore, we should obtain as large a sample size as possible under the allowed inspection cost. In order for $C_{PR}$ to be used throughout the industry, it is necessary to analyze the characteristics of the $C_{PR}$. Because the $C_{PR}$ is a kind of index including subgroup concept, the analysis should be done at the point of sample size of the subgroup. We present numerical analysis results of $C_{PR}$ by the data from the random number generating method. In this study, we also show the difference between the $C_{PR}$ using the range and the $C_P$ which is a representative index using the sample standard deviation. Regression analysis was used for the numerical analysis of the sample data. In addition, residual analysis and equal variance analysis was also conducted.

• Journal of Technology Innovation
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• v.27 no.2
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• pp.37-71
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• 2019

How has the passenger car's architecture evolved? In the meantime, the discussions on the car architecture have been mixed, i.e., integral, modular, and the coexistence of two types. Therefore, in this study, we aim to develop two indices can measure the degree of modularization of passenger car and its all modules using global trade data. By applying the indices to the framework of architecture positioning that reflects the hierarchical structure of a product, we examined that the degree of modularization of the passenger car architecture has been enhanced. Meanwhile, the degree of modularization differs across the modules that make up the car. Specifically, we observed the higher degree of modularization in front-end, cockpit and seat modules. Whereas, we found that body module had a relatively low degree of modularization. In particular, we observed that the platform of passenger car has notably modularized due to carmakers' efforts to achieve model diversification and reduction of cost and period in new product development at the same time. Interestingly, we showed that three modules, i.e., engine, chassis (relatively less modularized), and transmission (relatively highly modularized), had a different level of modularization, even if they commonly make up the platform. We contribute to the suggestion for analytical approaches that examine the degree of modularization and its progress longitudinally. In addition, we propose the necessity of decomposition of a system into elements in a study of product architecture, considering the possibly distinctive progress of modularization across the elements.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.17-24
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• 2019

Since the information of $4^{th}$ Industrial Revolution is introduced in WEF (World Economic Forum) in 2016, IoT, AI, Big Data, 5G, Cloud Computing, 3D/4DPrinting, Robotics, Nano Technology, and Bio Engineering have been rapidly developed as business applications as well as technologies themselves. Among the diverse business applications for IoT, wearable devices are recognized as the leading application devices for final customers. This longitudinal study is compared to the results of the 1st study conducted to identify customer needs of activity trackers, and links the identified users' needs with the well-known marketing frame of marketing mix. For this longitudinal study, a survey was applied to university students in June, 2018, and ANOVA were applied for major variables on usable features. Further, potential customer needs were identified and visualized by Word Cloud Technique. According to the analysis results, different from other high tech IT devices, activity trackers have diverse and unique potential needs. The results of this longitudinal study contribute primarily to understand usable features and their changes according to product maturity. It would provide some valuable implications in dynamic manner to activity tracker designers as well as researchers in this arena.

• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.21-35
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• 2020

Due to the coronavirus pandemic and diplomatic disputes, governments are actively developing a policy to revitalize·reshore manufacturing and to diversify international cooperations. In order to develop such a policy, it is very important to compare and analyze domestic·international geospatial information. Over the decade, the US·EC governments have conducted a series of national researches to build data-based tools that can monitor·analyze regional geospatial information driven by government R&D investments. In the case of the EC system, it can compare geospatial information in domestic and international(including Korea) regions. Compared to US·EC cases, Korean examples of national researches with available data analplatform need future improvements. Current study is investigating an automated analysis methodologies using "National Institute of Science and Technology Information (NTIS)" DB, which was national security data until recently. Research on data-mining regional geospatial information can contribute to support policy fields that need to discover new issues in response to unexpected social problems such as recently faced corona and trade disputes.

• Journal of the Korean Regional Science Association
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• v.37 no.2
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• pp.63-82
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• 2021

This study aims to explore how manufacturing start-up activities from 2000 to 2018 have changed spatially and to predict changes in distribution patterns of future start-up activities. For the analysis, the Census on Establishments microdata from 2000 to 2018 were used, and the manufacturing industry was classified into four detailed industrial groups according to the 40 manufacturing standards presented by the Korea Institute for Industrial Economics and Trade's ISTANS. According to the results, start-up activities in industries that require high technology levels are concentrated in southern Gyeonggi region, and other start-up activities are concentrated outside of the metropolitan area. When the distribution change from 2018 to 2036, extending the trend from 2000 to 2018, it was confirmed that there was a high possibility of a rise in the hierarchy in the future in regions adjacent to regions where start-up activities occur. This study aimed to provide implications for regional policies related to fostering start-ups and creating jobs by dynamically analyzing the location pattern of manufacturing start-ups, which is a major source of job creation.