• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.2
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• pp.127-139
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• 2023

Compensation and pay dispersion has been rigorously scrutinized to investigate their impacts on productivity and organizational performance. However, it is difficult to find a systematic study on the systematic dynamics of compensation and pay dispersion effects specifically in the context of Korean venture companies. Venture companies should manage their organizational resources efficiently to maximize their organizational performance through pay structure by efficiently managing the inherent resources. However, we acknowledge that empirical studies on how compensation and pay dispersion affect organizational productivity and performance are rare to find in the Korean context. To overcome this supplement limitation, this study hypothesized that (1) pay and members' productivity are positively related, (2) pay dispersion and organizational productivity have U shaped relationship, and (3) organizational productivity mediates the positive relationship between compensation and organizational performance. Venture companies and professional sports teams share manifold common characteristics such as size, financial circumstances, and operational objectives. We collect 9 seasons (2013~2014 - 2021~2022) of 10 teams' data of Korean Basketball League teams to test our hypotheses. Methodologically, the assessment of our analysis is rendered with PROCESS macro model 58. The statistical results showed that all hypotheses are statistically supported. This study explains how compensation and pay dispersion affect organizational productivity and performance of venture companies in Korea.

• Information Systems Review
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• v.24 no.4
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• pp.97-118
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• 2022

As generative adversarial network (GAN) based oversampling techniques have achieved impressive results in class imbalance of unstructured dataset such as image, many studies have begun to apply it to solving the problem of imbalance in structured dataset. However, these studies have failed to reflect the characteristics of structured data due to changing the data structure into an unstructured data format. In order to overcome the limitation, this study adapted CycleGAN to reflect the characteristics of structured data, and proposed hybridization of synthetic minority oversampling technique (SMOTE) and the adapted CycleGAN. In particular, this study tried to overcome the limitations of existing studies by using a one-dimensional convolutional neural network unlike previous studies that used two-dimensional convolutional neural network. Oversampling based on the method proposed have been experimented using various datasets and compared the performance of the method with existing oversampling methods such as SMOTE and adaptive synthetic sampling (ADASYN). The results indicated the proposed hybrid oversampling method showed superior performance compared to the existing methods when data have more dimensions or higher degree of imbalance. This study implied that the classification performance of oversampling structured data can be improved using the proposed hybrid oversampling method that considers the characteristic of structured data.

• Journal of Digital Convergence
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• v.22 no.2
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• pp.21-28
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• 2024

This study analyzed the current status of care policies and senior citizen issues in Korea, which has entered a super-aging society, and attempted to suggest improvement measures for desirable convergence policies. The problems of the elderly in Korea have emerged as health problems, poverty problems, loss of roles, and care problems due to changes in the concept of family, values, and socioeconomic structure. In addition, poor seniors need jobs and employment policies, and healthy middle-class seniors need policy development to enable leisure activities and volunteer activities. In particular, it is necessary to establish policies to enable people to spend the rest of their lives in elderly care facilities and elderly care hospitals through community care policies. The super-aging society accounts for more than 20% of the total population among those aged 65 or older, and according to the National Statistical Office, it is expected to become a super-aging society by 2025. Elderly welfare policies must provide various programs and the needs and services of elderly care, and in the future, a super-aging society will need to secure a lot of financial resources and maintain a productive population to cover the financial resources. In other words, the human life cycle is from birth to death, and when the ratio of natural deaths of the elderly and infants born is appropriate, the society and the country can be seen as stable, vibrant, and healthy societies.

• Information Systems Review
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• v.22 no.3
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• pp.99-118
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• 2020

At present, our society is developing into the intelligent information society in the wave of the 4th industrial revolution, and this change will have the positive effect of innovating all industry fields. However, due to the duality of technology, there will be positive and negative effects. With intelligence, threats to cyber dysfunction such as hacking, terrorism, privacy infringement, and illegal content distribution will become more serious. Until now, the security system of the Internet has been a proactive security system, but in recent years, a proposal for a trust network, a preventive security system, has been introduced. Therefore, this study aims to analyze the possibility of resolving cyber dysfunction of intelligent information society about Bright Internet, one of trust network technologies. This study defines the cyber dysfunction of the intelligent information society and analyzes the perceptions of changes in the cyber dysfunction of the intelligent information society on the introduction of the five principles of the Bright Internet. The change of cyber dysfunction severity of the intelligent information society due to the introduction of the trust network is analyzed to reflect the technical and social demands. This work will guide the structure of the trust network and the direction of practical technological introduction and its influence.

• Information Systems Review
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• v.22 no.4
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• pp.163-184
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• 2020

The information on SNS, which is created by the forms of postings and comments, is being magnified and redistributed to news media expanding its impacts on real words. This amplifying effects of SNS comments have been increasingly discussed but there still lacks the answers for which dimensions of information is magnified, and what affects the direction and the degree of the amplification. This study, therefore, explores the detailed dimensions that are magnified by SNS comments and how SNS posting structure and social network characteristics affect them by using sentiment analysis. By analyzing 2,378 Facebook postings and news articles and their 26,312 SNS and 74,730 news site comments, this study shows that SNS comments magnify the sentiments of the posting articles they are attached to. In comparison to news site comments, SNS comments magnify the cognitive and social dimensions more than the news site comments. In the affective dimension, they tend to magnify only the positive emotion more than news site comments. Also, the findings reveal that whether the article in the posting is written by the posting owner affects the degree of amplification when the comments are remained positive or switched positive, while the opposite determines the amplification when comments remain negatively, suggesting that the user relationship in social network is the important factor that affects the direction and the degree of the information amplification in SNS.

• Journal of Navigation and Port Research
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• v.48 no.3
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• pp.164-170
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• 2024

The light buoy, a floating structure at sea, is prone to drifting due to external factors such as oceanic weather. This makes it imperative to monitor for any loss or displacement of buoys. In order to address this issue, the Ministry of Oceans and Fisheries aims to issue alerts for buoy displacement by analyzing historical buoy position data to detect patterns. However, periodic lifting inspections, which are conducted every two years, disrupt the buoy's location pattern. As a result, new patterns need to be analyzed after each inspection for location monitoring. In this study, buoy position data from various periods were analyzed using convex hull and distance-based clustering algorithms. In addition, the optimal data collection period was identified in order to accurately recognize buoy location patterns. The findings suggest that a nine-week data collection period established stable location patterns, explaining approximately 89.8% of the variance in location data. These results can improve the management of light buoys based on location patterns and aid in the effective monitoring and early detection of buoy displacement.

• Information Systems Review
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• v.20 no.4
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• pp.79-96
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• 2018

This study started by focusing on the internalization of the technology appraisal model into the credit rating model to increase the discriminative power of the credit rating model not only for SMEs but also for all companies, reflecting the items related to the financial stability of the enterprises among the technology appraisal items. Therefore, it is aimed to verify whether the technology appraisal model can be applied to identify high-stability SMEs in advance. We classified companies into industries (manufacturing vs. non-manufacturing) and the age of company (initial vs. non-initial), and defined as a high-stability company that has achieved an average debt ratio less than 1/2 of the group for three years. The C5.0 was applied to verify the discriminant power of the model. As a result of the analysis, there is a difference in importance according to the type of industry and the age of company at the sub-item level, but in the mid-item level the R&D capability was a key variable for discriminating high-stability SMEs. In the early stage of establishment, the funding capacity (diversification of funding methods, capital structure and capital cost which taking into account profitability) is an important variable in financial stability. However, we concluded that technology development infrastructure, which enables continuous performance as the age of company increase, becomes an important variable affecting financial stability. The classification accuracy of the model according to the age of company and industry is 71~91%, and it is confirmed that it is possible to identify high-stability SMEs by using technology appraisal items.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.73-85
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• 2024

Predicting water quality of rivers and reservoirs is necessary for the management of water resources. Artificial Neural Networks (ANNs) have been used in many studies to predict water quality with high accuracy. Previous studies have used Gradient Descent (GD)-based optimizers as an optimizer, an operator of ANN that searches parameters. However, GD-based optimizers have the disadvantages of the possibility of local optimal convergence and absence of a solution storage and comparison structure. This study developed improved optimizers to overcome the disadvantages of GD-based optimizers. Proposed optimizers are optimizers that combine adaptive moments (Adam) and Nesterov-accelerated adaptive moments (Nadam), which have low learning errors among GD-based optimizers, with Harmony Search (HS) or Novel Self-adaptive Harmony Search (NSHS). To evaluate the performance of Long Short-Term Memory (LSTM) using improved optimizers, the water quality data from the Dasan water quality monitoring station were used for training and prediction. Comparing the learning results, Mean Squared Error (MSE) of LSTM using Nadam combined with NSHS (NadamNSHS) was the lowest at 0.002921. In addition, the prediction rankings according to MSE and R² for the four water quality indices for each optimizer were compared. Comparing the average of ranking for each optimizer, it was confirmed that LSTM using NadamNSHS was the highest at 2.25.

• Journal of Food Hygiene and Safety
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• v.39 no.3
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• pp.181-190
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• 2024

Bovine mastitis-associated Escherichia coli (BMEC) is considered the main causative agent of significant financial losses in the dairy industry worldwide, as it alters both the quantity and quality of milk produced and increases the rate of culling. This creates a variety of challenges for researchers, veterinarians, and farmers in understanding and determining the most effective therapies and diagnostic techniques. Subclinical mastitis is particularly concerning, as infected bovines exhibit no obvious symptoms and continue to secrete apparently normal milk over an extended period, allowing the causative pathogen, E. coli, to spread within the herd. For effective prevention, understanding the pathogenesis of mastitis through three stages invasion, infection, and inflammation is essential. To date, no clear correlation has been found between virulence factors and pathogenicity contributing to the clinical severity of BMEC. Multidrug-resistant E. coli and the evolution of novel resistance mechanisms have become concerns owing to the extensive use of antibiotics to treat mastitis. Therefore, it is vital to explore alternative controls to enhance the efficacy of BMEC treatment. Over the past 30 years, various genetic typing techniques have been used to examine the subspecies-level epidemiology of bovine mastitis. These studies have advanced our understanding of the origin, transmission pathway, population structure, and evolutionary relatedness of BMEC strains. In this review we provide an overview of BMEC, including insights into its etiology, genetic relationship, pathogenesis, and management of the disease, as well as new therapy options.

• Korean Journal of Environment and Ecology
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• v.38 no.3
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• pp.324-337
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• 2024

Aquatic macrophytes are important factors in determining species diversity and abundance of cladocerans, but the effects of cladocerans on plant species composition or structure have not been fully considered. In South Korea, wetlands and reservoirs that are prone to covering aquatic macrophytes are scattered across the country, so it is necessary to consider on aquatic macrophytes study, when aquatic animals including cladoceran were studied. in this study, the species and abundance of cladocerans community in six microhabitat types are investigated, and based on these results, habitat conservation and efficient management are suggested. The high species numbers and abundance of cladocerans communities were found in mixed plant communities consisting of free-floating, floating-leaved, and submerged plants. The inclusion of submerged plants in plant communities contributes significantly to the complexity of habitat structures, and may increase species and abundance of cladocenran communities. This can be compared to a plant community consisting only of free-floating and floating-leaved plants in the absence of submerged plants, thereby identifying the efficiency of submerged plants. In the mixed plant communities, species diversity was the highest due to the emergence of cladoceran species (Graptoleveris testudinaria, Ilyocryptus spinifer, and Leydigia acanthococcides) absent from other plant communities. The gradual increase in the biomass (g) of submerged plants in the mixed plant communities significantly increased the species numbers and abundance of cladoceran communities (p<0.05). This is strong evidence that the increase of submerged plants in mixed plant communities has a positive effect on efficiency as a habitat for cladocerans. Although submeged plants do not contribute significantly to their landscape/aesthetic value because they are submerged in water, they have the effect of increasing species diversity in terms of biology, so they should be considered important when creating/restoring wetlands.