• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.209-221
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• 2023

In the external inspection and packaging stages of products used in the semiconductor manufacturing process, there is a problem in which particles are adsorbed to the product itself or a carrying tool due to electrostatic discharge. This study presents a methodology that can improve the problem of adsorption of particles to a product by using a practical TRIZ technique. By applying the proposed practical TRIZ-based methodology, the problem was defined, and contradictions caused by product waiting time were derived. Among the derived contradictions, physical contradictions were set and the concept of 'space separation' was applied to derive solutions such as 'installation of Ionizer' and 'improvement of the layout of the workroom'. As a result of the experiment by applying 'Ionizer Installation' and 'Workroom Layout Improvement' derived through the application of practical TRIZ, it was confirmed that the particle adsorption problem that occurs during the waiting time of the product can be solved.Through this study, it is expected that workers, facility engineers, and technical engineers working at manufacturing processes will be able to effectively solve the problems they face through creative thinking and change of ideas by using practical TRIZ techniques, and contribute to innovative technology development and productivity improvement.

• Smart Media Journal
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• v.12 no.10
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• pp.55-62
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• 2023

Innovation and change are occurring rapidly in the agriculture and livestock industry, and new technologies such as smart bams are being introduced, and data that can be used to control equipment is being collected by utilizing various sensors. However, there are various challenges in the operation of bams, and virtual sensor technology is needed to solve these challenges. In this paper, we define various data items and sensor data types used in livestock farms, study cases that utilize virtual sensors in other fields, and implement and design a virtual sensor system for the final smart livestock farm. MBE and EVRMSE were used to evaluate the finalized system and analyze performance indicators. As a result of collecting and managing data using virtual sensors, there was no obvious difference in data values from physical sensors, showing satisfactory results. By utilizing the virtual sensor system in smart livestock farms, innovation and efficiency improvement can be expected in various areas such as livestock operation and livestock health status monitoring. This paper proposes an innovative method of data collection and management by utilizing virtual sensor technology in the field of smart livestock, and has obtained important results in verifying its performance. As a future research task, we would like to explore the connection of digital livestock using virtual sensors.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.69-75
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• 2024

This paper proposes an innovative cognitive IoT framework specifically designed for fog computing (FC) in the context of industrial Internet of Things (IIoT). The discourse in this paper is centered on the intricate design and functional architecture of the Cognitive IoT platform. A crucial feature of this platform is the integration of machine learning (ML) and artificial intelligence (AI), which enhances its operational flexibility and compatibility with a wide range of industrial applications. An exemplary application of this platform is highlighted through the Predictive Maintenance-as-a-Service (PdM-as-a-Service) model, which focuses on real-time monitoring of machine conditions. This model transcends traditional maintenance approaches by leveraging real-time data analytics for maintenance and management operations. Empirical results substantiate the platform's effectiveness within a fog computing milieu, thereby illustrating its transformative potential in the domain of industrial IoT applications. Furthermore, the paper delineates the inherent challenges and prospective research trajectories in the spheres of Cognitive IoT and Fog Computing within the ambit of Industrial Internet of Things (IIoT).

• Journal of the Economic Geographical Society of Korea
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• v.26 no.3
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• pp.238-255
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• 2023

In this study, we derived the characteristic factors of the cluster as measurable variables, and attempted to clarify the characteristics of the apparel sewing areas in Changsin-dong, Doksan-dong, and Jangwi-dong. Based on these results, a comparative analysis was conducted to see how the demand for the government's support policy differs for each agglomeration area. Materials were collected through face-to-face questionnaires targeting tenant companies in the three regions. As a result of the analysis, Changsin-dong was identified as an "innovative growth type," Doksan-dong as a "networking type," and Jangwi-dong as a "specialized localization type." As a result of the research on policy demands, the policy demands of the three agglomerations appeared different, but Changsin-dong preferred capacity building, Doksan-dong preferred information provision, and Jangwi-dong favored policy means of benefit. It was confirmed that even among clusters of the same apparel sewing industry, the formation process and characteristics are different, and as a result, the demand for policy instruments is also different. Policy recommendations include understanding the characteristics and policy demands of each agglomeration area through periodic fact-finding surveys, and recommending the establishment and implementation of differentiated support policies that match the characteristics of each agglomeration area.

• The Korean Journal of Physiology and Pharmacology
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• v.27 no.6
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• pp.521-531
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• 2023

Transmembrane protein TMEM16A, which encodes calcium-activated chloride channel has been implicated in tumorigenesis. Overexpression of TMEM16A is associated with poor prognosis and low overall survival in multiple cancers including lung adenocarcinoma, making it a promising biomarker and therapeutic target. In this study, three structure-related sesquiterpene lactones (mecheliolide, costunolide and dehydrocostus lactone) were extracted from the traditional Chinese medicine Aucklandiae Radix and identified as novel TMEM16A inhibitors with comparable inhibitory effects. Their effects on the proliferation and migration of lung adenocarcinoma cells were examined. Whole-cell patch clamp experiments showed that these sesquiterpene lactones potently inhibited recombinant TMEM16A currents in a concentration-dependent manner. The half-maximal concentration (IC50) values for three tested sesquiterpene lactones were 29.9 ± 1.1 µM, 19.7 ± 0.4 µM, and 24.5 ± 2.1 µM, while the maximal effect (E_max) values were 100.0% ± 2.8%, 85.8% ± 0.9%, and 88.3% ± 4.6%, respectively. These sesquiterpene lactones also significantly inhibited the endogenous TMEM16A currents and proliferation, and migration of LA795 lung cancer cells. These results demonstrate that mecheliolide, costunolide and dehydrocostus lactone are novel TMEM16A inhibitors and potential candidates for lung adenocarcinoma therapy.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.67-76
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• 2023

Although deep learning models are making innovative achievements in the field of computer vision, the problem of vulnerability to adversarial examples continues to be raised. Adversarial examples are attack methods that inject fine noise into images to induce misclassification, which can pose a serious threat to the application of deep learning models in the real world. In this paper, we propose a model that detects adversarial examples using differences in predictive values between edge-learned classification models and underlying classification models. The simple process of extracting the edges of the objects and reflecting them in learning can increase the robustness of the classification model, and economical and efficient detection is possible by detecting adversarial examples through differences in predictions between models. In our experiments, the general model showed accuracy of {49.9%, 29.84%, 18.46%, 4.95%, 3.36%} for adversarial examples (eps={0.02, 0.05, 0.1, 0.2, 0.3}), whereas the Canny edge model showed accuracy of {82.58%, 65.96%, 46.71%, 24.94%, 13.41%} and other edge models showed a similar level of accuracy also, indicating that the edge model was more robust against adversarial examples. In addition, adversarial example detection using differences in predictions between models revealed detection rates of {85.47%, 84.64%, 91.44%, 95.47%, and 87.61%} for each epsilon-specific adversarial example. It is expected that this study will contribute to improving the reliability of deep learning models in related research and application industries such as medical, autonomous driving, security, and national defense.

• Ecology and Resilient Infrastructure
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• v.10 no.4
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• pp.237-249
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• 2023

This study was carried to establish a new landscape-oriented gardening model based on climate, vegetation, and forest landscape characteristics. In addition, innovative forest garden models were suggested through an integrated approach to the ecological characteristics of forest vegetation communities and existing garden planting types. For the study, the key landscape elements that make up the main forest vegetation community were identified. And the vertical layers and horizontal distribution patterns of the community structure were typified by diagnostic species and their growth forms & habits such as dominant species, character species, and differential species, and degree of dominance-sociability. Based on this, a standardized vegetation structure and formation was developed by stratifying the landscape into main features, minor features, and detailed features according to visual dominant elements. Also, the applicability of the forest garden model was examined by applying the concept of borrowing landscape to representative deciduous broadleaf forests in the temperate northern region of Korea. Additionally, an integrated forest garden models based on the conceptual definition and typology of forest gardens, and a strategic approach to forest vegetation were proposed

• Informatization Policy
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• v.30 no.4
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• pp.113-137
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• 2023

This study aims to conduct the classification of Government as a Platform (GaaP) in a situation where the concept of GaaP can be diversely recognized. This is because inclusiveness and ambiguity in the concept of GaaP can hinder policy enforcement by working-level officials in the public sector. It drew the criteria for classification for GaaP based on literature and cases for GaaP. In the technical aspect, considering data as an overarching factor, the integrated system platform integrating the information system or websites of the public sector and the data platform as a single portal for open data to external stakeholders were sorted. In the governance aspect considering stakeholder as an overarching factor, the communication platform utilized for interaction between public and private sectors and the co-creation platform that encourages public-private partnership to create innovative outcomes were sorted. It suggested an actual implementation case and the policy implication according to each type of GaaP. Additionally, according to the classification of GaaP, it conducted contents analysis as to which type of GaaP the domestic Digital Platform Government belongs to based on its detailed assignment. Based on the classification of GaaP, it drew balanced implementation for various types of GaaP, plan for promoting the participation and collaboration of stakeholders, and necessity of restructuring and reinventing of the public sector as policy implications for the domestic digital platform government.

• Journal of Korea Trade
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• v.27 no.5
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• pp.1-22
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• 2023

Purpose - Southeast Asia has been the focus of Korea's foreign investment. Korea has been helping developing countries in Southeast Asia achieve economic growth and win-win cooperation through capital exports. FDI is an important channel for technology diffusion. However, the impact of FDI on the bias of technological progress in the host country is dependent on the host country's own endowment structure and capital-labor factor substitution elasticity. Therefore, the central issue of this paper is to accurately evaluate the impact of Korea's FDI to the four Southeast Asian countries in various industries on their bias of technological progress. Design/methodology - The paper uses macroeconomic data for Korea and four East Asian countries to estimate capital-labor factor elasticities of substitution using nonlinear, seemingly uncorrelated regressions (NLSUR). Then, the biased technological change index (BTCI) is calculated for each country. Finally, panel data analysis is used to explore the impact of Korean FDI in various industries in the four Southeast Asian countries on their own directed technological progress, and a robustness test is conducted. Findings - There is a substitution relationship between capital and labor factors based on their elasticity in Korea, Singapore and the Philippines. There is a complementary relationship between capital and labor factors in Indonesia and Malaysia. According to the BTCI, there is a trend toward labor-biased technological progress in all countries. Korean investments in manufacturing, wholesale and retail trade in the host country trigger capital-biased technological change in the host country; investments in the finance, insurance and information and communication sectors trigger labor-biased technological change. In addition, this paper also confirms that directed technological progress can enable cross-country transmission. Originality/value - The innovation of this paper lies in three aspects. First, we estimate the BTCI for five countries and explore the trend and situation of directed technological progress in each country from each country's own perspective. Second, we explore the impact of Korean FDI in the host country on the bias to its technological progress at the industry level. Second, we explore the impact of Korean FDI in various industries in the four Southeast Asian countries on the four countries' own directed technological progress from a national perspective. Finally, we propose corresponding countermeasures for technological progress from the perspective of inverse factor endowment. These innovative points not only expand the understanding of technological progress and cross-country technology transfer in East Asia but also provide practical references for policy-makers and business operators.

• Information Systems Review
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• v.25 no.4
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• pp.291-314
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• 2023

The concept of Mydata emerged with the expansion of the data economy. MyData aims to empower individuals by enhancing their right to self-determination over their personal data. The use of MyData is expected to enable the provision of innovative service in various fields. Since 2022, MyData has been introduced and actively used in the financial sector. In the future, not only financial institutions but also Bigtech and Fintech companies are expected to actively join and demonstrate rapid expansion. To ensure steady growth for MyData in the financial sector, it is necessary to assess acceptance behaviors from multiple perspectives. However, the majority of existing research solely focuses on positive acceptance. This study analyzed the impact of users' personal characteristics and innovation characteristics on both innovation resistance and acceptance resistance. The analysis revealed that personal and innovation characteristics contribute to an increase in distrust and innovation resistance in the MyData service. In addition, it has been confirmed that it can lead to actions such as delayed acceptance and refusal to accept. The results of this study offer both theoretical and practical insights into user behavior within the MyData service market.