• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.85-92
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• 2023

Recently, interest in artificial intelligence has increased due to the development of artificial intelligence fields such as ChatGPT and self-driving cars. However, there are still many unknown elements in training process of artificial intelligence, so that optimizing the model requires more time and effort than it needs. Therefore, there is a need for a tool or methodology that can analyze the weight changes during the training process of artificial intelligence and help out understatnding those changes. In this research, I propose a visualization system which helps people to understand the accumulated weight changes. The system calculates the weights for each training period to accumulates weight changes and stores accumulated weight changes to plot them in 3D space. This research will allow us to explore different aspect of artificial intelligence learning process, such as understanding how the model get trained and providing us an indicator on which hyperparameters should be changed for better performance. These attempts are expected to explore better in artificial intelligence learning process that is still considered as unknown and contribute to the development and application of artificial intelligence models.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.83-91
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• 2023

In this paper, we propose a robustness sensitivity index (RSI) of highway networks to analyze the effect of congestion in a specific section on the entire highway. The newly proposed RSI is defined as the change in the total mileage of the transportation network per extended unit length when the length of a particular section is extended. When the RSI value is large, traffic congestion in the section has a worse effect on the entire network than in other sections. The existing network robustness index (NRI) simply observes changes in transportation networks with and without specific sections, but the RSI proposed in this study is a kind of performance indicator that allows quantitative analysis of the ripple effect of the entire network according to the degree of congestion in a specific section. While changing the degree of congestion in a particular section, it is possible to calculate how the traffic volume increases, decreases, and the size and location of the congestion section change. This analysis proves the superiority of RSI as it cannot be analyzed with NRI. Various properties of RSI are analyzed using data from the domestic highway network. In addition, using the RSI concept, it is shown that the ripple effect on other sections in which a change in the degree of congestion of a specific section occurs can be analyzed.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.214-222
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• 2022

It is important to realize employment equality to fulfill corporate social responsibility. The most suitable indicator for assessing its performance is the gender wage gap. Korea is considered the country with the most severe gender wage gap among OECD member countries, however, studies on the gender wage gap have been mainly attempted to explain in terms of the structure of the labor market, government policies, etc. This study focus on the characteristics of CEO and HR systems among the characteristics of organizations affecting the gender wage gap. The management philosophy sets the direction of organizational decision-making and activates the system. In addition, the HR system enables fair and objective organizational management for members through rules and procedures. However, even in organizations seeking rationalization, minority people may experience discrimination. Moreover, the rational HR system may act as a mechanism to justify discrimination, contrary to existing intentions. This study proposes that in order for the rational HR system to work positively, it must be based on the management philosophy. In other words, it is intended to derive a mechanism that can alleviate the gender wage gap from the integrated perspective of the characteristics of the CEO and the rational HR system. In particular, it aims to provide specific implications for how the organization should operate the HR system by examining the gender wage gap based on internal factors of companies that utilize manpower.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.248-256
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• 2023

ESG, which stands for Environmental, Social, and Governance, becomes a keyword in managing a company as it becomes an "indicator" that judge companies. Since the environment has suffered so much damage for economic development, it is now to reflect the enormous environmental costs of the future in the management standard rather than the immediate financial benefits at the expense of the environment. Compared to the days when corporate social responsibility (CSR) was discussed, ESG management has improved significantly as it requires practice beyond the declarative level, but the level of consideration for the environmental field is still not high. There may be many backgrounds, but the biggest problem may be the lack of understanding for other fields. Accordingly, this study aims to inform corporates of the need for investment in the environmental field by explaining ESG reviewed in the environmental field and ESG management required in the environmental field. Furthermore, another purpose is to inform them that ESG management is a win-win strategy that can have a meaningful effect not only in the environmental field where investment is received but also in terms of companies by explaining the benefits that companies can gain through this. To reach this goal, this study proposed a method of restoring a damaged ecosystem based on corporate investment, evaluating its effects based on carbon absorption capacity, and using it as a means of carbon neutrality practice as well as ESG management performance of a company.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.3
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• pp.19-31
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• 2022

Currently, the role of public accelerators in the domestic accelerator market is gradually expanding. Accordingly, in order to establish relevant policies properly, it is necessary to check the effect and validity of public accelerators' investment. However, there is no quantitative research conducted on domestic accelerators, using their financial data, as domestic accelerators have a short history and quantitative data on them are not disclosed. Therefore, this study conducted an empirical analysis with financial data of the startups that received equity investments from public accelerators to confirm the effect of public accelerators'investment in startups. A regression analysis was conducted with financial data from 112 startups that acquired investments from public accelerators in the period of 2016~2020. And the findings are as follows: First, it was found that the initial investment of public accelerators had an effect on the growth and profitability of startups. Specifically, it was confirmed that the initial investment of public accelerators had a positive (+) effect on sales growth rates and total asset growth rates, which are growth indicators. Second, it was found that the joint investment of public accelerators had a significant positive (+) effect on profit margin, an indicator of profitability, rather than on growth. Therefore, it is deemed that it will be a great force for growth if investment in the early-stage startups that showed significant investment results in this study is continuously expanded in combination with support projects, which are a strength of public accelerators. Since this study has confirmed the investment effect of public accelerators, it is deemed necessary to actively promote policies that direct public accelerators' projects toward improving the performance of startups through joint investment with the private sector and supplementing private accelerators' deficiencies.

• Journal of Korean Society of Rural Planning
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• v.30 no.1
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• pp.57-66
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• 2024

This study aimed to develop a precise vegetation cover classification model for small streams using the combination of drone remote sensing and support vector machine (SVM) techniques. The chosen study area was the Idong stream, nestled within Geosan-gun, Chunbuk, South Korea. The initial stage involved image acquisition through a fixed-wing drone named ebee. This drone carried two sensors: the S.O.D.A visible camera for capturing detailed visuals and the Sequoia+ multispectral sensor for gathering rich spectral data. The survey meticulously captured the stream's features on August 18, 2023. Leveraging the multispectral images, a range of vegetation indices were calculated. These included the widely used normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) that factors in soil background, and the normalized difference water index (NDWI) for identifying water bodies. The third stage saw the development of an SVM model based on the calculated vegetation indices. The RBF kernel was chosen as the SVM algorithm, and optimal values for the cost (C) and gamma hyperparameters were determined. The results are as follows: (a) High-Resolution Imaging: The drone-based image acquisition delivered results, providing high-resolution images (1 cm/pixel) of the Idong stream. These detailed visuals effectively captured the stream's morphology, including its width, variations in the streambed, and the intricate vegetation cover patterns adorning the stream banks and bed. (b) Vegetation Insights through Indices: The calculated vegetation indices revealed distinct spatial patterns in vegetation cover and moisture content. NDVI emerged as the strongest indicator of vegetation cover, while SAVI and NDWI provided insights into moisture variations. (c) Accurate Classification with SVM: The SVM model, fueled by the combination of NDVI, SAVI, and NDWI, achieved an outstanding accuracy of 0.903, which was calculated based on the confusion matrix. This performance translated to precise classification of vegetation, soil, and water within the stream area. The study's findings demonstrate the effectiveness of drone remote sensing and SVM techniques in developing accurate vegetation cover classification models for small streams. These models hold immense potential for various applications, including stream monitoring, informed management practices, and effective stream restoration efforts. By incorporating images and additional details about the specific drone and sensors technology, we can gain a deeper understanding of small streams and develop effective strategies for stream protection and management.

• Journal of IKEEE
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• v.28 no.2
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• pp.221-227
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• 2024

This paper presents a smartphone-attachable vascular compliance monitoring module. The proposed sensor module measures photoplethysmogram (PPG) and reconstructs an accelerated PPG waveform. The feature points are extracted from the accelerated PPG waves, and vascular compliance is estimated using these extracted features. The module is powered via the smartphone's USB terminal and transmits the acquired waveforms along with vascular compliance values through Bluetooth. The transmitted waveforms and vascular compliance value are displayed through the smartphone application. This work proposes an assessment method for consistency of PPG instrumentation, and it was implemented in a processor of sensor module. The proposed sensor module can be easily attached to smartphone that does not support PPG instrumentation, providing simple measurment and numerical analysis of vascular compliance. To verify the performance of the implemented sensor module, we acquired vascular compliance and pulse pressure data from 29 subjects. Pulse pressure, which serves as a representative indicator of vascular compliance, was obtained using a commercial blood pressure monitor. The analysis results showed that the Pearson coefficient between vascular compliance and pulse pressure was 0.778, confirming a relatively high correlation between two metrics.

• Journal of Science Education
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• v.48 no.1
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• pp.1-14
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• 2024

The Korean Science Education Standards (KSES) were developed to support the establishment of a domestic national science curriculum to respond to future social and environmental changes as an action plan to improve scientific literacy in the context of science education. In this study, we analyzed the relationship between KSES and the 2022 revised middle science curriculum focusing its learning contents and learning objectives and sought effects of the successful implementation of the curriculum. As a result, the content system of the 2022 revised middle science curriculum was highly related to the categories of knowledge in KSES. Attempts to deal with the content related to the nature of science was also confirmed through content elements in science and society domains. In the case of achievement standards, it was focused on some areas of the performance expectations in KSES, but the level of statement of the achievement standards closely matched the level of middle school students as suggested by KSES. From these results, it was possible to confirm the high relationship between the 2022 revised middle science curriculum and KSES, as well as the possibility of using KSES as an international indicator for establishing future science education plans.

• Journal of The Korean Society of Clinical Toxicology
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• v.21 no.2
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• pp.135-142
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• 2023

Purpose: In patients with glufosinate poisoning, severe neurological symptoms may be closely related to a poor prognosis, but their appearance may be delayed. Therefore, this study aimed to determine whether the Acute Physiology and Chronic Health Evaluation II (APACHE II) score could predict the neurological prognosis in patients with glufosinate poisoning who present to the emergency room with alert mental status. Methods: This study was conducted retrospectively through a chart review for patients over 18 years who presented to a single emergency medical center from January 2018 to December 2022 due to glufosinate poisoning. Patients were divided into groups with a good neurological prognosis (Cerebral Performance Category [CPC] Scale 1 or 2) and a poor prognosis (CPC Scale 3, 4, or 5) to identify whether any variables showed significant differences between the two groups. Results: There were 66 patients (67.3%) with good neurological prognoses and 32 (32.8%) with poor prognoses. In the multivariate logistic analysis, the APACHE II score, serum amylase, and co-ingestion of alcohol showed significant results, with odds ratios of 1.387 (95% confidence interval [CI], 1.027-1.844), 1.017 (95% CI, 1.002-1.032), and 0.196 (95% CI, 0.040-0.948), respectively. With an APACHE II score cutoff of 6.5, the AUC was 0.826 (95% CI, 0.746-0.912). The cutoff of serum amylase was 75.5 U/L, with an AUC was 0.761 (95% CI, 0.652-0.844), and the AUC of no co-ingestion with alcohol was 0.629 (95% CI, 0.527-0.722). Conclusion: The APACHE II score could be a useful indicator for predicting the neurological prognosis of patients with glufosinate poisoning who have alert mental status.

• Journal of Practical Engineering Education
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• v.16 no.3_spc
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• pp.309-325
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• 2024

The purpose of this study was to develop self-evaluation criteria for objective verification and performance analysis of LINC 3.0. To achieve this goal, evaluation indicators in the fields of human resources development and skill development and commercialization were developed and their validity was verified. We investigated previous evaluation-related studies and similar cases to construct an evaluation model and system and develop indicators. The validity of the developed evaluation indicators was secured through two round Delphi surveys. As a result of the research, LINC 3.0 evaluation indicators can be divided into the field of human resources development and skill development and commercialization. A total of 66 evaluation indicators were developed. CIPP in the field of human resources development was developed with 13 categories and 38 evaluation indicators, and CIPP in the field of skill development and commercialization was developed with 12 categories and 28 evaluation indicators. The significance of this study is that it suggests a way to increase the objective verification and validity of the university industry-academia cooperation model by developing self-evaluation indicators for the LINC 3.0 project. The evaluation indicators developed in the research need to be continuously upgraded based on field usability, and it is necessary to improve the quality and competitiveness of university education by sharing and spreading excellent affairs.