• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.93-101
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• 2024

Accurate field crop classification is essential for various agricultural applications, yet existing methods face challenges due to diverse crop types and complex field conditions. This study aimed to address these issues by combining support vector machine (SVM) models with multi-seasonal unmanned aerial vehicle (UAV) images, texture information extracted from Gray Level Co-occurrence Matrix (GLCM), and RGB spectral data. Twelve high-resolution UAV image captures spanned March-October 2021, while field surveys on three dates provided ground truth data. We focused on data from August (-A), September (-S), and October (-O) images and trained four support vector classifier (SVC) models (SVC-A, SVC-S, SVC-O, SVC-AS) using visual bands and eight GLCM features. Farm maps provided by the Ministry of Agriculture, Food and Rural Affairs proved efficient for open-field crop identification and served as a reference for accuracy comparison. Our analysis showcased the significant impact of hyperparameter tuning (C and gamma) on SVM model performance, requiring careful optimization for each scenario. Importantly, we identified models exhibiting distinct high-accuracy zones, with SVC-O trained on October data achieving the highest overall and individual crop classification accuracy. This success likely stems from its ability to capture distinct texture information from mature crops.Incorporating GLCM features proved highly effective for all models,significantly boosting classification accuracy.Among these features, homogeneity, entropy, and correlation consistently demonstrated the most impactful contribution. However, balancing accuracy with computational efficiency and feature selection remains crucial for practical application. Performance analysis revealed that SVC-O achieved exceptional results in overall and individual crop classification, while soybeans and rice were consistently classified well by all models. Challenges were encountered with cabbage due to its early growth stage and low field cover density. The study demonstrates the potential of utilizing farm maps and GLCM features in conjunction with SVM models for accurate field crop classification. Careful parameter tuning and model selection based on specific scenarios are key for optimizing performance in real-world applications.

• Journal of Practical Engineering Education
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• v.15 no.3
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• pp.641-647
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• 2023

In the fintech environment, ensuring secure financial transactions with smartphones requires authenticating the device owner. Smartphone authentication techniques encompass a variety of approaches, such as passwords, biometrics, SMS authentication, and more. Among these, password-based authentication is commonly used and highly convenient for user authentication. Although it is a simple authentication mechanism, it is susceptible to eavesdropping and keylogging attacks, alongside other threats. Security keypads have been proposed to address vulnerabilities in password input on smartphones. One such innovation is a group keypad, resistant to attacks that guess characters based on touch location. However, improvements are needed for user convenience. In this study, we aim to propose a method that enhances convenience while being resistant to eavesdropping and recording attacks on the existing group keypad. The proposed method uses new signs to allow users to verify instead of the last character confirmation easily and employs dragging-to-touch for blocking recording attacks. We suggest diverse positioning methods tailored for domestic users, improving efficiency and security in password input compared to existing methods.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.4
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• pp.55-75
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• 2023

This study proposes the establishment of a joint preservation library in the Chungcheongbuk-do region. It aims to transfer low-utilization materials from various libraries in Chungcheongbuk-do to the joint preservation library, thereby improving the efficiency of existing spaces and actively supporting the educational curriculum of school libraries. To achieve this, the study conducted document analysis, a status survey, and case analysis. The research results indicate that a reasonable standard for the accommodating capacity of the preservation library space is calculated at 280 volumes per square meter. Specifically, an initial transfer of 45,580 volumes for public libraries and 121,894 volumes for school libraries is proposed, totaling 167,474 volumes. Depending on the saturation levels of Chungcheongbuk-do Office of Education-affiliated public libraries and school libraries, the initial volume is determined to be 167,477 volumes, with an annual increase of 10% calculated over 30 to 50 years after the library's opening.

• Korean Journal of Veterinary Research
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• v.63 no.4
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• pp.40.1-40.7
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• 2023

To optimize the most efficient method for porcine in vitro maturation (IVM), we compared the effects of supplementing extracellular vesicles (EVs) derived from porcine follicular fluid (pFF). The cumulus oocyte complexes were grouped into 4 groups with different supplementations as following: pFF (G1), pFF-depleted EVs (G2), EVs (G3) and control (G4) groups. After IVM with different supplementations, maturation rates and the developmental competences of porcine oocytes and blastocyst development were investigated. Additionally, glutathione (GSH) and reactive oxygen species (ROS) levels were measured in mature oocytes. The EVs were isolated and characterized with cryo-TEM and nanoparticle tracking analysis. The pFF significantly affected the maturation rate, whereas the presence of EVs did not show notable difference in the maturation rates. Although there were numerical increases in the measured parameters in EV and pFF-depleted EVs groups, no significant differences were observed between them. The EV group showed similar oocyte maturation rate for both positive and negative control groups. The GSH was not different among the groups, but ROS levels were significantly lower in pFF-supplemented group when compared with other groups with the highest level in the control group. G2 group wasn't significantly different G1 and G3 group. G3 group wasn't significantly different from G2 and G4 group. This suggests that EVs in IVM medium which probably effected partially to protect against oxidative stress and potentially enhance the quality of oocytes. This study indicates that the EVs in pFF play a significant role in improving the efficiency of oocyte maturation in porcine.

• Korea Trade Review
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• v.48 no.4
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• pp.47-66
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• 2023

Our study aims to explore the impact of China's foreign trade policy measures on the real exchange rate movement. We seek to provide specific references for the formulation of exchange rate and trade-related strategies. Our results indicate that China's bilateral trade is significantly influenced by movements in the Real Effective Exchange Rate (RER). When analyzing the relationship between aggregated trade flow and exchange rate movements, this paper finds that the depreciation of the real exchange rate leads to an increase in China's export volume and a slight decrease in its import volume. Moreover, China's export volume exhibits higher sensitivity to exchange rate volatility compared to the exchange rate level. Furthermore, the empirical findings regarding disaggregated trade flow suggest that different goods are affected differently by exchange rate movements. Capital goods and consumer goods, being in different stages of processing, show no negative impact on their import and export due to exchange rate depreciation. Consequently, we recommend deepening the industry's reform by improving production efficiency and transitioning the industrial structure to a higher processing stage. This approach can effectively reduce the negative impact of exchange rate depreciation.

• Food Science of Animal Resources
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• v.43 no.6
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• pp.1017-1030
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• 2023

Fetal bovine serum (FBS), which contains various nutrients, comprises 20% of the growth medium for cell-cultivated meat. However, ethical, cost, and scientific issues, necesitates identification of alternatives. In this study, we investigated commercially manufactured serum-free media capable of culturing Hanwoo satellite cells (HWSCs) to identify constituent proliferation enhancing factors. Six different serum-free media were selected, and the HWSC proliferation rates in these serum-free media were compared with that of control medium supplemented with 20% FBS. Among the six media, cell proliferation rates were higher only in StemFlex^TM Medium (SF) and Mesenchymal Stem Cell Growth Medium DXF (MS) than in the control medium. SF and MS contain high fibroblast growth factor 2 (FGF2) concentrations, and we found upregulated FGF2 protein expression in cells cultured in SF or MS. Activation of the fibroblast growth factor receptor 1 (FGFR1)-mediated signaling pathway and stimulation of muscle satellite cell proliferation-related factors were confirmed by the presence of related biomarkers (FGFR1, FRS2, Raf1, ERK, p38, Pax7, and MyoD) as indicated by quantitative polymerase chain reaction, western blotting, and immunocytochemistry. Moreover, PD173074, an FGFR1 inhibitor suppressed cell proliferation in SF and MS and downregulated related biomarkers (FGFR1, FRS2, Raf1, and ERK). The promotion of cell proliferation in SF and MS was therefore attributed to FGF2, which indicates that FGFR1 activation in muscle satellite cells may be a target for improving the efficiency of cell-cultivated meat production.

• Journal of Information Technology Services
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• v.22 no.5
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• pp.71-86
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• 2023

Recently, various geographic information systems have been used based on spatial information of geographic information systems. Accordingly, it is essential to produce a large-scale map as a small-scale map for various uses of spatial information. However, maps currently being produced have inconsistencies between data due to production timing and limitations in expression, and productivity efficiency is greatly reduced due to errors in products or overlapping processes. In order to improve this, various efforts are being made, such as publishing research and reports for automating domestic mapping, but because there is no specific result, it relies on editors to make maps. This is mainly done by hand, so the time required for mapping is excessive, and quality control for each producer is different. In order to solve these problems, technology that can be automatically produced through computer programs is needed. Research has been conducted to apply the rule base to geometric generalization. The algorithm tolerance setting applied to rule-based modeling is a factor that greatly affects the result, and the level of the result changes accordingly. In this paper, we tried to study the effectiveness of mapping according to tolerance setting. To this end, the utility was verified by comparing it with a manually produced map. In addition, the original data and reduction rate were analyzed by applying generalization algorithms and tolerance values. Although there are some differences by region, it was confirmed that the complexity decreased on average. Through this, it is expected to contribute to the use of spatial information-based services by improving tolerances suitable for small-scale mapping regulations in order to secure spatial information data that guarantees consistency and accuracy.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.999-1008
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• 2023

Early prediction of chronic diseases such as diabetes is an important issue, and improving the accuracy of diabetes prediction is especially important. Various machine learning and deep learning-based methodologies are being introduced for diabetes prediction, but these technologies require large amounts of data for better performance than other methodologies, and the learning cost is high due to complex data models. In this study, we aim to verify the claim that DNN using the pima dataset and k-fold cross-validation reduces the efficiency of diabetes diagnosis models. Machine learning classification methods such as decision trees, SVM, random forests, logistic regression, KNN, and various ensemble techniques were used to determine which algorithm produces the best prediction results. After training and testing all classification models, the proposed system provided the best results on XGBoost classifier with ADASYN method, with accuracy of 81%, F1 coefficient of 0.81, and AUC of 0.84. Additionally, a domain adaptation method was implemented to demonstrate the versatility of the proposed system. An explainable AI approach using the LIME and SHAP frameworks was implemented to understand how the model predicts the final outcome.

• Journal of KIBIM
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• v.13 no.3
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• pp.1-11
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• 2023

In order to use BIM as a tool for improving the productivity and quality of products in the construction industry, a BIM model must be created from the design stage first. Infrastructure structures such as bridges and tunnels are mainly created based on three-dimensional alignment in the generation of BIM models. Especially, generation of BIM models based on three-dimensional linearity has high task difficulty and algorithms for automating BIM modeling for railway infra structures have been suggested in previous studies. This study improved the BIM modeling automation algorithm of railway infrastructures and developed a system based on the algorithm so that it can be easily used by ordinary users. The system was built as an add-in system of Autodesk's Revit. As an improvement first, it is possible to arrange different libraries for each pattern, enabling various uses. In addition, it can be created models of several members with a single process and the system can automatically places structures that are added periodically, such as Rock Bolt and Fore Polling. Finally, 3D length information and volume for each pattern are automatically calculated for more accurate 3D-based volume calculation. This study contributes to increasing user accessibility by building a BIM modeling automation algorithm into a system. The system is expected to improve the efficiency of BIM modeling creation of linear-based infra structures, including railway infrastructure.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.59-73
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• 2023

Due to the steady growth of the online shopping market and contact-free consumption, the volume of parcels in South Korea continues to increase. However, there is a lack of manpower for delivery workers to handle the growing parcel volume, leading to frequent accidents related to delivery work. As a result, the government and local authorities strive to enhance last-mile logistics efficiency. As one of these measures, unmanned parcel storage lockers are installed and utilized to handle last-mile deliveries. However, the existing parcel storage involves the inconvenience of couriers having to put each parcel in each locker, and this is somewhat insufficient to relieve the workload of delivery workers. In this study, we propose parcel storage devices that use active loading technology to minimize the workload of delivery workers, extract operation risk factors to apply this system to actual sites, and establish risk reduction methods based on the ALARP concept. Through this study, we have laid the groundwork for improving the safety of the system by identifying and proposing mitigation measures for the risk factors associated with the proposed parcel storage devices utilizing active loading technology. When applied in practical settings in the future, this foundation will contribute to the development of a more efficient and secure system. By applying the ALARP concept, a systems engineering technique used in this research, to the development and maintenance of storage devices leveraging active loading technology, it is thought to make the development process more systematic and structured. Furthermore, through the risk management of the proposed system, it is anticipated that a systematic approach to quality management can be employed to minimize defects and provide a stable system. This is expected to be more useful than the existing unmanned parcel storage devices.