• The Korean Journal of Archival Studies
• /
• 제78호
• /
• pp.153-195
• /
• 2023

RDBMS is a widely used database system worldwide, and the term dataset refers to the vast amount of data produced in administrative information systems using RDBMS. Unlike business systems that mainly produce administrative documents, administrative information systems generate records centered around the unique tasks of organizations. These records differ from traditional approval documents and metadata, making it challenging to seamlessly transfer them to standard record management systems. With the 2022 revision of the 'Public Records Act Enforcement Decree,' dataset was included in the types of records for which only management authority is transferred. The core aspect of this revision is the need to manage the lifecycle of records within administrative information systems. However, there has been little exploration into how to manage dataset within administrative information systems. As a result, this research aims to design a database for a record management module that needs to be integrated into administrative information systems to manage the lifecycle of records. By modifying and supplementing ISO 16175-1:2020, we are designing an "human resource management system" and identifying and evaluating personnel management dataset. Through this, we aim to provide a concrete example of record management within administrative information systems. It's worth noting that the prototype system designed in this research has limitations in terms of data volume compared to systems currently in use within organizations, and it has not yet been validated by record researchers and IT developers in the field. However, this endeavor has allowed us to understand the nature of dataset and how they should be managed within administrative information systems. It has also affirmed the need for a record management module's database within administrative information systems. In the future, once a complete record management module is developed and standards are established by the National Archives, it is expected to become a necessary module for organizations to manage dataset effectively.

• Korean Journal of Remote Sensing
• /
• 제39권5_1호
• /
• pp.521-535
• /
• 2023

When converting rice fields into fields,sorghum (sorghum bicolor L. Moench) has excellent moisture resistance, enabling stable production along with soybeans. Therefore, it is a crop that is expected to improve the self-sufficiency rate of domestic food crops and solve the rice supply-demand imbalance problem. However, there is a lack of fundamental statistics,such as cultivation fields required for estimating yields, due to the traditional survey method, which takes a long time even with a large manpower. In this study, U-Net was applied to RGB images based on unmanned aerial vehicle to confirm the possibility of non-destructive segmentation of sorghum cultivation fields. RGB images were acquired on July 28, August 13, and August 25, 2022. On each image acquisition date, datasets were divided into 6,000 training datasets and 1,000 validation datasets with a size of 512 × 512 images. Classification models were developed based on three classes consisting of Sorghum fields(sorghum), rice and soybean fields(others), and non-agricultural fields(background), and two classes consisting of sorghum and non-sorghum (others+background). The classification accuracy of sorghum cultivation fields was higher than 0.91 in the three class-based models at all acquisition dates, but learning confusion occurred in the other classes in the August dataset. In contrast, the two-class-based model showed an accuracy of 0.95 or better in all classes, with stable learning on the August dataset. As a result, two class-based models in August will be advantageous for calculating the cultivation fields of sorghum.

• Korean Journal of Plant Resources
• /
• 제36권5호
• /
• pp.435-445
• /
• 2023

The aim of this study was to explore the effects of vinegar extract from seed of common buckwheat (Fagopyrum esculentum Moench) and seed of tartary buckwheat (F. tataricum Gaertner) on acute ethanol-induced hangover in Sprague-Dawley rats. Vinegar extract from buckwheat is rich choline, quercetin and its glycoside, rutin known as flavonoid antioxidants. The test extract containing buckwheat was proven to alleviate hangovers through a significant reduction in the concentration of alcohol and acetaldehyde in the context of an alcohol-induced hangover model. Hepatic alcohol dehydrogenase (ADH) and acetaldehyde dehydrogenase (ALDH) activities were significantly higher in buckwheat vinegar-treated rats than in ethanol-treated rats. Moreover, tartary buckwheat vinegar upregulated antioxidant enzyme such as superoxide dismutase and Catalase activities in liver tissues. These results suggest that buckwheat vinegar extract could alleviate ethanol-induced hangover symptoms by elevating activities related to hepatic ethanol-metabolizing enzymes against ethanol induced metabolites, and in particular, tartary buckwheat should be further developed to be a novel anti-hangover material.

• The Journal of the Acoustical Society of Korea
• /
• 제42권6호
• /
• pp.603-616
• /
• 2023

In this study, machine learning-based clustering and classification of residential noise in apartment buildings was conducted using frequency and temporal characteristics. First, a residential noise source dataset was constructed . The residential noise source dataset was consisted of floor impact, airborne, plumbing and equipment noise, environmental, and construction noise. The clustering of residential noise was performed by K-Means clustering method. For frequency characteristics, L_eq and L_max values were derived for 1/1 and 1/3 octave band for each sound source. For temporal characteristics, Leq values were derived at every 6 ms through sound pressure level analysis for 5 s. The number of k in K-Means clustering method was determined through the silhouette coefficient and elbow method. The clustering of residential noise source by frequency characteristic resulted in three clusters for both L_eq and L_max analysis. Temporal characteristic clustered residential noise source into 9 clusters for L_eq and 11 clusters for L_max. Clustering by frequency characteristic clustered according to the proportion of low frequency band. Then, to utilize the clustering results, the residential noise source was classified using three kinds of machine learning. The results of the residential noise classification showed the highest accuracy and f1-score for data labeled with L_eq values in 1/3 octave bands, and the highest accuracy and f1-score for classifying residential noise sources with an Artificial Neural Network (ANN) model using both frequency and temporal features, with 93 % accuracy and 92 % f1-score.

• Korean Journal of Remote Sensing
• /
• 제39권6_1호
• /
• pp.1211-1224
• /
• 2023

Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• 제22권5호
• /
• pp.53-73
• /
• 2023

Although it is mandatory to wear a seat belt that can minimize human injury when traffic accident occurs, the number of traffic accident casualties not wearing seat belts still accounts for a significant proportion.The seat belt wearing detection system for all seats is a system that identifies whether all seat passengers wear a seat belt and encourages their usage, also it can be a useful technical countermeasure. Firstly, this study established the viability of system implementation by assessing the factors influencing the severity of injuries in traffic accidents through the development of an ordered probit model. Analysis results showed that the use of seat belts has statistically significant effects on the severity of traffic accidents, reducing the probability of death or serious injury by 0.054 times in the event of a traffic accident. Secondly, a meta-analysis was conducted based on prior research related to seat belts and injuries in traffic accidents to estimate the expected reduction in accident severity upon the implementation of the system.The analysis of the effect of accident severity reduction revealed that wearing seat belts would lead to a 63.3% decrease in fatal accidents, with the front seats showing a reduction of 75.7% and the rear seats showing a reduction of 58.1% in fatal accidents. Lastly, Using the results of the meta-analysis and traffic accident statistics, the expected decrease in the number of traffic accident casualties with the implementation of the system was derived to analyze the traffic safety effects of the proposed detection system. The analysis demonstrated that with an increase in the adoption rate of the system, the number of casualties in accidents where seat belts were not worn decreased. Specifically, at a system adoption rate of 60%, it is anticipated that the number of fatalities would decrease by more than three times compared to the current scenario. Based on the analysis results, operational strategies for the system were proposed to increase seat belt usage rates and reduce accident severity.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• 제18권5호
• /
• pp.123-139
• /
• 2023

Incubating future social entrepreneurs is of increasing importance for governments and industries that aim to create positive social changes through innovative, market-based solutions. Considering the distinct and challenging nature of a social entrepreneurial career, prior research has explored various antecedents of the formation of social entrepreneurial intention. The current research aims to contribute to the literature by examining social class as a potential precursor of individuals' social entrepreneurial intention formation, with a specific focus on social entrepreneurial identity aspiration as the underlying psychological mechanism and communal narcissism as the contingent factor. Using a two-wave survey data collected among 144 potential entrepreneurs from South Korea, we tested a moderated mediation model to validate the research propositions. The findings can be summarized as follows. First, lower social class was associated with higher social entrepreneurial identity aspiration. Second, when communal narcissism was high(low), the negative relationship between social class and social entrepreneurial identity aspiration was stronger(weaker). Third, communal narcissism moderated the negative impact of social class on social entrepreneurial intention via its effect on social entrepreneurial identity aspiration. This study has significant implications on several fronts. First, we explore the motivations that drive individuals from lower-class backgrounds to participate in social entrepreneurship, going beyond the previous notion that a higher-class context promotes entrepreneurial pursuits. Second, we delve into the underlying mechanism and condition that influence the formation of social entrepreneurial intentions, highlighting the pivotal roles played by social entrepreneurial identity aspiration and communal narcissism. Our findings provide practical insights for institutions seeking to foster the involvement of prospective social entrepreneurs from lower-class backgrounds, thereby generating positive outcomes for marginalized communities.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• 제18권4호
• /
• pp.21-35
• /
• 2023

Expectations surrounding generative AI technology and its profound ramifications are sweeping across various industrial domains. Given the anticipated pivotal role of the startup ecosystem in the utilization and advancement of generative AI technology, it is imperative to cultivate a deeper comprehension of the present state and distinctive attributes characterizing venture capital (VC) investments within this domain. The current investigation delves into South Korea's landscape of VC investment deals and prognosticates the projected VC investments by juxtaposing these against the United States, the frontrunner in the generative AI industry and its associated ecosystem. For analytical purposes, a compilation of 286 investment deals originating from 117 U.S. generative AI startups spanning the period from 2008 to 2023, as well as 144 investment deals from 42 South Korean generative AI startups covering the years 2011 to 2023, was amassed to construct new datasets. The outcomes of this endeavor reveal an upward trajectory in the count of VC investment deals within both the U.S. and South Korea during recent years. Predominantly, these deals have been concentrated within the early-stage investment realm. Noteworthy disparities between the two nations have also come to light. Specifically, in the U.S., in contrast to South Korea, the quantum of recent VC deals has escalated, marking an augmentation ranging from 285% to 488% in the corresponding developmental stage. While the interval between disparate investment stages demonstrated a slight elongation in South Korea relative to the U.S., this discrepancy did not achieve statistical significance. Furthermore, the proportion of VC investments channeled into generative AI enterprises, relative to the aggregate number of deals, exhibited a higher quotient in South Korea compared to the U.S. Upon a comprehensive sectoral breakdown of generative AI, it was discerned that within the U.S., 59.2% of total deals were concentrated in the text and model sectors, whereas in South Korea, 61.9% of deals centered around the video, image, and chat sectors. Through forecasting, the anticipated VC investments in South Korea from 2023 to 2029 were derived via four distinct models, culminating in an estimated average requirement of 3.4 trillion Korean won (ranging from at least 2.408 trillion won to a maximum of 5.919 trillion won). This research bears pragmatic significance as it methodically dissects VC investments within the generative AI domain across both the U.S. and South Korea, culminating in the presentation of an estimated VC investment projection for the latter. Furthermore, its academic significance lies in laying the groundwork for prospective scholarly inquiries by dissecting the current landscape of generative AI VC investments, a sphere that has hitherto remained void of rigorous academic investigation supported by empirical data. Additionally, the study introduces two innovative methodologies for the prediction of VC investment sums. Upon broader integration, application, and refinement of these methodologies within diverse academic explorations, they stand poised to enhance the prognosticative capacity pertaining to VC investment costs.

• Journal of the Korean Institute of Landscape Architecture
• /
• 제52권1호
• /
• pp.71-86
• /
• 2024

Despite the increasing importance of urban parks' ecological functions in dealing with the climate crisis, ecological parks are not clearly defined in Korea's legal system. Numerous ecological parks created nationwide cannot be systematically designated and managed due to various legal bases and varying management authorities. It is important to clarify the legal status of ecological parks in order to lead the ecological paradigm shift of urban parks and to improve the natural park system for a comprehensive and integrated approach to protect the national ecosystem. To this end, related laws were analyzed to identify problems and to draw directions for legislative improvement. Through the literature review of relevant laws, acts, and ordinances, six major directions for improvement were suggested based on the analysis of problems. First, the legal status of ecological parks in the administrative dichotomy of the current park system is ambiguous, and ecological parks should be clarified through the revision of park-related laws. Second, an ecological park can be defined as a sustainable park created and managed in an ecological manner, promoting the protection and restoration of the ecosystem, conservation, and promotion of biodiversity, and balancing nature observation, ecological learning, and leisure activities. Third, the role of the state and local governments should be systematically revised to lead to a new park planning and management model through new governance. Fourth, since the characteristics of ecological parks are affected by individual laws, the possibility of overlapping ecological parks for other uses should be allowed. Fifth, detailed guidelines and standard ordinances need to be enacted to meet the goals, principles, and facilities of ecological parks. Lastly, along with the revision of the laws, ordinances by local governments also need to be more concrete. This study, which tracks various legal realities related to ecological parks, can contribute to policymaking that can systematize the foundation for the creation of ecological parks to preserve nationwide ecosystems and provide citizens with opportunities to experience and learn about nature.

• Journal of the Korea Organic Resources Recycling Association
• /
• 제31권4호
• /
• pp.13-28
• /
• 2023

This study assessed the biochemical methane potential (B_u-P) of three grass species-Poa pratensis (PP), Zoysia japonica (ZJ), and Agrostis stolonifera (AS). B_u-P values were determined as 0.330 Nm³/kg-VS_added for PP, 0.297 Nm³/kg-VS_added for ZJ, and 0.261 Nm³/kg-VS_added for AS. Notably, PP exhibited superior suitability for methane production. The investigation also examined the impact of silage storage duration on PP grass clippings, revealing a 19% decline in B_u-P from an initial value of 0.269 Nm³/kg-VS_added on day 0 to 0.217 Nm³/kg-VS_added on day 180. Throughout the storage period, there were significant increases in neutral detergent fiber (NDF), acid detergent fiber (ADF), and crude protein (CP) contents, rising from 67.59%, 39.68%, and 3.02% on day 0 to 77.12%, 54.65%, and 6.24% on day 180, respectively. These findings highlight the influence of storage duration on the anaerobic digestibility of PP grass clippings. To effectively utilize grass clippings as a renewable resource for methane production, further studies considering factors such as initial moisture content, pretreatment methods, and potential effects of residual pesticides are necessary to optimize anaerobic digestion efficiency for herbaceous biomass.