• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.542-552
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• 2022

The importance of the child-care teacher's job has recently been greatly emphasized due to changes in the transitional social environment, but the performance conditions are poor, requiring management of various job factors. For the purpose of providing information for practical application and institutional support related to child-care teachers, this study selected Flourish, Care that Respects the Rights of Child, and Job Crafting to verify the functional impact relationship and effectiveness. Since there are no domestic studies on child-care teachers using these variables, hierarchical regression analysis was performed on 223 child-care teachers to obtain initial information. As a result of the analysis, only the average difference between groups was found in terms of Flourish according to age and Negative Job Demand Reduction according to working hours. And it was found that the Enhancement of Social Job Resources had a moderating effect. Therefore, it is necessary to prepare a new job management strategy based on the information provided by this study and to develop a highly effective reinforcement program for each factor.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5B
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• pp.539-549
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• 2006

The performance of a pontoon-type floating breakwater (FB) is investigated numerically with the use of a second-order time domain model. The model has been developed based on potential theory, perturbation theory and boundary element method. This study is focused on the effects of weakly nonlinear wave on the hydrodynamic characteristics of the FB. Hydrodynamic forces, motion responses, surface elevation, and wave transmission coefficient around the floating breakwater are evaluated for various wave and geometric parameters. It is shown that the second-order wave component is of significant importance in calculating magnitudes of the hydrodynamic forces, mooring forces and the maximum response of a structure. The weak non-linearity of incident waves, however, can have little influence on the efficiency of the FB. From numerical simulations, the ratio of draft and depth, the relationship of wave number and width are presented for providing an effective means of reducing wave energy.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.509-509
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• 2022

Rice has always been the anchor of food security in the Philippines and the government is adamant about sustaining rice production by ensuring reliable irrigation water availability. Among the numerous irrigation schemes, the importance of the Pulangui River Irrigation System (PRIS) is undeniable, as it is the largest and primary irrigation source for rice production areas which are considered the food basket in Northern Mindanao. However, the ageing irrigation structures, unlined canals, long-standing water delivery systems, and climate change are compromising the performance of PRIS; and every year, during the dry and wet season, the maximum rice irrigable area is not achieved. From the field-scale water management perspective, untimely irrigation application, an unregulated roster of turn for irrigation among farmers, and the traditional practice of flooding the rice fields are the main causes of substantial water losses in conveyance, distribution, and farm application of irrigation water. Hence, proper irrigation scheduling is crucial to cultivate the maximum irrigable area by ensuring equity among the farmers and to increase the water use efficiency and yield. In this study, the FAO single crop coefficient approach was adopted to estimate rice water requirements, which were subsequently used to suggest appropriate irrigation schedules based on the recommended field-scale rice cultivation practices. The study results would improve the irrigation system management in the study area by facilitating in regulating the canal water flows and releases according to suggested irrigation schedules that could lead to increased benefited area, yield, and water efficiency without straining the available water resources.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.304-311
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• 2022

Construction inspection is a crucial stage that ensures that all contractual requirements of a construction project are verified. The construction inspection capabilities among state highway agencies have been greatly affected due to budget reduction. As a result, efficient inspection practices such as risk-based inspection are required to optimize the use of limited resources without compromising inspection quality. Automated prioritization of textual requirements according to their criticality would be extremely helpful since contractual requirements are typically presented in an unstructured natural language in voluminous text documents. The current study introduces a novel model for predicting the risk level of requirements using machine learning (ML) algorithms. The ML algorithms tested in this study included naïve Bayes, support vector machines, logistic regression, and random forest. The training data includes sequences of requirement texts which were labeled with risk levels (such as very low, low, medium, high, very high) using the fuzzy logic systems. The fuzzy model treats the three risk factors (severity, probability, detectability) as fuzzy input variables, and implements the fuzzy inference rules to determine the labels of requirements. The performance of the model was examined on labeled dataset created by fuzzy inference rules and three different membership functions. The developed requirement risk prediction model yielded a precision, recall, and f-score of 78.18%, 77.75%, and 75.82%, respectively. The proposed model is expected to provide construction inspectors with a means for the automated prioritization of voluminous requirements by their importance, thus help to maximize the effectiveness of inspection activities under resource constraints.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.88-88
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• 2022

Detection of stress responses in crops is important to diagnose crop growth and evaluate yield. Also, the multi-spectral sensor is effectively known to evaluate stress caused by nutrient and moisture in crops or biological agents such as weeds or diseases. Therefore, in this experiment, multispectral images were taken by an unmanned aerial vehicle(UAV) under field condition. The experiment was conducted in the long-term fertilizer field in the National Institute of Crop Science, and experiment area was divided into different status of NPK(Control, N-deficiency, P-deficiency, K-deficiency, Non-fertilizer). Total 11 vegetation indices were created with RGB and NIR reflectance values using python. Variations in nutrient content in plants affect the amount of light reflected or absorbed for each wavelength band. Therefore, the objective of this experiment was to evaluate vegetation indices derived from multispectral reflectance data as input into machine learning algorithm for the classification of nutritional deficiency in rice. RandomForest model was used as a representative ensemble model, and parameters were adjusted through hyperparameter tuning such as RandomSearchCV. As a result, training accuracy was 0.95 and test accuracy was 0.80, and IPCA, NDRE, and EVI were included in the top three indices for feature importance. Also, precision, recall, and f1-score, which are indicators for evaluating the performance of the classification model, showed a distribution of 0.7-0.9 for each class.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2436-2457
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• 2023

The elderly population is rapidly increasing worldwide, but many face challenges in using digital tools like the Internet due to health and incapacity issues. Existing online search user interfaces (UIs) often overlook the specific usability needs of the elderly. This study proposes an adaptable web search UI model for the elderly, based on their perspectives, to enhance search performance and usability. The proposed UI model is evaluated through comparative usability testing with 20 participants, comparing it to the Google search UI. Effectiveness, efficiency, and satisfaction are measured using task completion time, error rate, and subjective preferences. The results show significant differences (p > 0.05) between the proposed web search UI model and the Google search UI. The proposed UI model achieves higher subjective satisfaction levels, indicating better alignment with the needs and preferences of elderly users. It also reduces task completion time, indicating improved efficiency, and decreases the error rate, suggesting enhanced effectiveness. These findings emphasize the importance of considering the unique usability needs of the elderly when designing search UIs. The proposed adaptable web search UI model offers a promising approach to enhance the digital experiences of elderly users. This study lays the groundwork for further development and refinement of adaptable web search UI models that cater to the specific needs of elderly users, enabling designers to create more inclusive and user-friendly search interfaces for the growing elderly population.

• Journal of the Korean Geosynthetics Society
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• v.22 no.4
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• pp.1-8
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• 2023

Space exploration is at the forefront of human scientific endeavors, and planetary exploration rovers play a critical role in studying planetary surfaces. Rover performance is especially vital for safely navigating steep terrain and delicate landscapes found on planets like Mars and the Moon. This paper offers a comprehensive overview of a landing testbed designed to simulate challenging extraterrestrial terrain and loose regolith. The paper briefly outlines lunar crater region topographical features and highlights the importance of these simulations in rover testing. It then explores previous landing testbed developments and describes the design process for a landing testbed to be installed in the dirty thermal vacuum chamber at the Korea Institute of Civil Engineering and Building Technology. Once realized, this proposed landing testbed will enable precise evaluations of rover mobility and exploration capabilities under lunar-like conditions, including high vacuum and extreme temperatures.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.635-642
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• 2023

With the development of artificial intelligence technology, drones are evolving beyond simple remote control tools into intelligent drones that perform missions autonomously. The importance of drones is gradually gaining attention due to the use of drones in overseas military conflicts and the analysis of the future operational environment in Korea. AMAD is proposed for the rapid development of intelligent drones. In order to develop intelligent software based on AMAD, an integrated development environment (IDE) that supports users with functions such as debugging, performance evaluation, and monitoring is essential. In this paper, we define the concepts of the development environment required for intelligent software development and describe the results of reflecting them in the design of the IDE and AMAD's agents, SVI and MPD, which are interfaced with the IDE.

• Korea Trade Review
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• v.47 no.6
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• pp.97-117
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• 2022

Amid the growing importance and growth potential of venture firms worldwide, this study aimed to figure out the effect of new product development capabilities (NPDC) on the internationalization of Korean venture firms and the moderating impact of founders' human capital. NPDC is a core competency that can cope with the rapidly changing market environment and is required when entering multinational markets. Therefore, we subdivided founders' human capital into professional experience, startup experience, education level, and marketing capacity and examined each moderating effect on a venture firm's internationalization. As a result of empirical analysis of 1,362 Korean venture firms using the Tobit model, this study found that venture firms with excellent NPDC tend to achieve a higher level of internationalization. In addition, among the founder's human capitals, professional experience, education level, and marketing competency moderated the positive relationship between NPDC and internationalization. In contrast, the founder's startup experience was insignificant. The results of this empirical analysis explain the factors that trigger the internationalization performance of venture firms from the perspective of dynamic capabilities and suggest that the founder's human capital played an essential role in the internationalization.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.4
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• pp.69-78
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• 2023

With the rapid growth of artificial intelligence, the demand for semiconductors is enormously increasing everywhere. To ensure the manufacturing quality and quantity simultaneously, the importance of automatic defect detection during the packaging process has been re-visited by adapting various deep learning-based methodologies into automatic packaging defect inspection. Deep learning (DL) models require a large amount of data for training, but due to the nature of the semiconductor industry where security is important, sharing and labeling of relevant data is challenging, making it difficult for model training. In this study, we propose a new framework for securing sufficient data for DL models with fewer computing resources through a divide-and-conquer approach. The proposed method divides high-resolution images into pre-defined sub-regions and assigns conditional labels to each region, then trains individual sub-regions and boundaries with boundary loss inducing the globally coherent and seamless images. Afterwards, full-size image is reconstructed by combining divided sub-regions. The experimental results show that the images obtained through this research have high efficiency, consistency, quality, and generality.