• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.6
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• pp.627-632
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• 2023

Lithium-ion batteries are widely used in various applications, including electric vehicles and portable electronics, due to their high energy density and long cycle life. The performance of lithium-ion batteries can be improved by using solid electrolytes, in terms of higher safety, stability, and energy density. Li_1.5Al_0.5Ti_1.5(PO₄)₃ (LATP) is a promising solid electrolyte for all-solid-state lithium batteries due to its high ionic conductivity and excellent stability. However, the ionic conductivity of LATP needs to be improved for commercializing all-solid-state lithium battery systems. In this study, we investigate the microstructures and ionic conductivities of LATP by incorporating B₂O₃ glass ceramics. The smaller grain size and narrow size distribution were obtained after the introduction of B₂O₃ in LATP, which is attributed to the B₂O₃ glass on grain boundaries of LATP. Moreover, higher ionic conductivity can be obtained after B₂O₃ incorporation, where the optimal composition is 0.1 wt% B₂O₃ incorporated LATP and the ionic conductivity reaches 8.8×10^-5 S/cm, more than 3 times higher value than pristine LATP. More research could be followed for having higher ionic conductivity and density by optimizing the processing conditions. This facile approach for establishing higher ionic conductivity in LATP solid electrolytes could accelerate the commercialization of all-solid-state lithium batteries.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.971-979
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• 2023

Small ships (<499 GT) constitute 46% of the existing ships, therefore, it can be concluded that they produce relatively high CO₂ gas emissions. Operating in optimal trim conditions can reduce the resistance of the ship, which results in fewer greenhouse gases. An affordable way for trim optimization is to adjust the weight distribution to obtain an optimum longitudinal center of gravity (LCG). Therefore, in this study, the effect of LCG changes on the resistance of a small planing ship is studied using empirical and numerical analyses. The Savitsky method employing Maxsurf resistance and the STAR-CCM+ commercial computational fluid dynamics (CFD) software is used for the empirical and numerical analyses, respectively. Finally, the total resistance from the ship design process is compared to obtain the optimum LCG. To summarize, using numerical analysis, optimum LCG is achieved at the 46.2% length overall (LoA) at Froude Number 0.56, and 43.4% LoA at Froude Number 0.63, which provides a significant resistance reduction of 41.12 - 45.16% compared to the reference point at 29.2% LoA.

• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.503-515
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• 2023

The disconnection and fragmentation of ecological spaces that occur during the development process pose a significant threat to biodiversity. Urban center areas with high development pressure are particularly susceptible to low connectivity due to a scarcity of ecological space. This issue tends to be more pronounced in larger cities.To address this challenge, continuous efforts are needed to assess and improve the current state of ecological space connectivity at the level of individual projects and urban management. However, there is a lack of discussion regarding the analysis and improvement of ecological connectivity in metropolitan cities In line with this objective, this study evaluated the connectivity of ecological spaces in the city centers of Seoul, Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan. The evaluation revealed that city centers exhibited lower connectivity of ecological spaces compared to their peripheries or the overall city. In addition, in the ecological network analysis that reflected regional characteristics, such as the species distribution model conducted on Daejeon, 510 optimal paths connecting forests of more than 1ha were derived. This study is significant as an example of deriving an ecological network based on regional characteristics, including quantitative figures necessary for establishing goals to improve urban ecological connectivity and biodiversity. It is anticipated that the results can be utilized to propose directions for enhancing ecological connectivity in environmental impact assessments or urban management and to establish an evaluation framework.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.547-560
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• 2023

Recently, research on predicting ground classification using machine learning techniques, TBM excavation data, and ground data is increasing. In this study, a multi-classification prediction study for uniaxial compressive strength (UCS) was conducted by applying random forest model based on a decision tree among machine learning techniques widely used in various fields to machine data and ground data acquired at three slurry shield TBM sites. For the classification prediction, the training and test data were divided into 7:3, and a grid search including 5-fold cross-validation was used to select the optimal parameter. As a result of classification learning for UCS using a random forest, the accuracy of the multi-classification prediction model was found to be high at both 0.983 and 0.982 in the training set and the test set, respectively. However, due to the imbalance in data distribution between classes, the recall was evaluated low in class 4. It is judged that additional research is needed to increase the amount of measured data of UCS acquired in various sites.

• Journal of Dental Anesthesia and Pain Medicine
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• v.24 no.3
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• pp.187-193
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• 2024

Background: Patients with autism spectrum disorder (ASD) present challenges in dental treatment cooperation owing to deficits in communication skills and social interaction. Behavioral guidance, sedation, and general anesthesia may be employed to ensure the quality of dental care for individuals with ASD. This study aimed to examine the trends in dental treatment for patients with ASD who visited the Department of Pediatric Dentistry at Dankook University Jukjeon Dental Hospital, an oral health center for the disabled in the Gyeonggi region, over the past 10 years. Methods: This study utilized the order communication system to gather data on sex, age, cooperation level, number of quadrants treated, and administration of sedation or general anesthesia for patients with ASD who visited the Department of Pediatric Dentistry at Dankook University Jukjeon Dental Hospital between January 2013 and December 2022. Results: The total number of patients with ASD increased annually, possibly due to an increase in ASD prevalence and the hospital's designation as a center for disabled oral health. General anesthesia was predominant before 2017, with a shift towards N₂O-O₂ sedation. The most common age group for sedation or general anesthesia was 6-9 years, with a higher prevalence in males than in females. Notably, N₂O-O₂ and midazolam sedation resulted in better cooperation and fewer treated teeth than general anesthesia. Conclusion: This study highlights the evolving trends in dental treatment for individuals with ASD, indicating a shift towards outpatient methods, particularly N₂O-O₂ sedation. The sex distribution aligns with national statistics, emphasizing a higher prevalence of ASD in males than in females. These findings underscore the need for further research to establish evidence-based guidelines for optimal dental care strategies tailored to the unique needs of individuals with ASD.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.200-210
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• 2023

Background: Cambaroides similis is an endangered candidate species living in the stream of South Korea. Freshwater crayfish is known to decline rapidly not only domestically, but also internationally. Its decline is projected to be further exacerbated due to climate change. Understanding physical characteristics of the habitat is crucial for the conservation of an organism. However, comprehensive data regarding the distribution and physical habitat characteristics of C. similis are currently unavailable in South Korea. Thus, the objective of this study was to ascertain preferred ranges for water depth, current velocity, and streambed substrate of C. similis using Weibull model. Results: In this study, C. similis was found at 59 sites across 12 regions in South Korea. Its optimal water depth preferences ranged from 11.9 cm to 30.1 cm. Its current velocity preferences ranged from 9.8 cm s^-1 to 29.1 cm s^-1. Its substrate preferences ranged from -5.1 𝜱_m to -2.5 𝜱_m. Median values of central tendency were determined as follows: water depth of 21.4 cm, current velocity of 21.2 cm s^-1, and substrate of -4.1 𝜱_m. Mean values of central tendency were determined as follows: water depth of 21.8 cm, current velocity of 22.0 cm s^-1, and substrate of -4.4 𝜱_m. Mode values of central tendency were determined as follows: water depth of 21.7 cm, current velocity of 20.1 cm s^-1, and substrate of -3.7 𝜱_m. Conclusions: Based on habitat suitability analysis, physical microhabitat characteristics of C. similis within a stream were identified as Run section with coarse particle substrate, low water depth, and slow current velocity. Due to high sensitivity of these habitats to environmental changes, prioritized selection and assessment of threats should be carried out as a primary step.

• The Journal of Bigdata
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• v.9 no.1
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• pp.101-113
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• 2024

Federated learning has garnered attention as an efficient method for training machine learning models in a distributed environment while maintaining data privacy and security. This study proposes a novel FedRFBagging algorithm to optimize the performance of random forest models in such federated learning environments. By dynamically adjusting the trees of local random forest models based on client-specific data characteristics, the proposed approach reduces communication costs and achieves high prediction accuracy even in environments with numerous clients. This method adapts to various data conditions, significantly enhancing model stability and training speed. While random forest models consist of multiple decision trees, transmitting all trees to the server in a federated learning environment results in exponentially increasing communication overhead, making their use impractical. Additionally, differences in data distribution among clients can lead to quality imbalances in the trees. To address this, the FedRFBagging algorithm selects only the highest-performing trees from each client for transmission to the server, which then reselects trees based on impurity values to construct the optimal global model. This reduces communication overhead and maintains high prediction performance across diverse data distributions. Although the global model reflects data from various clients, the data characteristics of each client may differ. To compensate for this, clients further train additional trees on the global model to perform local optimizations tailored to their data. This improves the overall model's prediction accuracy and adapts to changing data distributions. Our study demonstrates that the FedRFBagging algorithm effectively addresses the communication cost and performance issues associated with random forest models in federated learning environments, suggesting its applicability in such settings.

• Research in Plant Disease
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• v.30 no.3
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• pp.256-267
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• 2024

We have developed FBcastS (Fire Blight Forecasting System), a cloud-based information system that leverages the K-Maryblyt forecasting model. The FBcastS provides an optimal timing for spraying antibiotics to prevent flower infection caused by Erwinia amylovora and forecasts the onset of disease symptoms to assist in scheduling field scouting activities. FBcastS comprises four discrete subsystems tailored to specific functionalities: meteorological data acquisition and processing, execution of the K-Maryblyt model, distribution of web-based information, and dissemination of spray timing notifications. The meteorological data acquisition subsystem gathers both observed and forecasted weather data from 1,583 sites across South Korea, including 761 apple or pear orchards where automated weather stations are installed for fire blight forecast. This subsystem also performs post-processing tasks such as quality control and data conversion. The model execution subsystem operates the K-Maryblyt model and stores its results in a database. The web-based service subsystem offers an array of internet-based services, including weather monitoring, mobile services for forecasting fire blight infection and symptoms, and nationwide fire blight monitoring. The final subsystem issues timely notifications of fire blight spray timing alert to growers based on forecasts from the K-Maryblyt model, blossom status, pesticide types, and field conditions, following guidelines set by the Rural Development Administration. FBcastS epitomizes a smart agriculture internet of things (IoT) by utilizing densely collected data with a spatial resolution of approximately 4.25 km to improve the accuracy of fire blight forecasts. The system's internet-based services ensure high accessibility and utility, making it a vital tool in data-driven smart agricultural practices.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.5
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• pp.533-549
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• 2024

Soil conditioning is a critical process when tunneling with an earth pressure balance (EPB) shield tunnel boring machine (TBM) to enhance performance. To determine the optimal additive injection conditions, it is important to understand the rheological properties of conditioned soil, which is typically assessed using a rheometer. However, a rheometer cannot simulate the actual process of muck discharge in a TBM. Therefore, in this study, a scaled-down model of an 8-meter-class EPB shield TBM chamber and screw conveyor, reduced by a factor of 1:20, was fabricated and its applicability was evaluated through laboratory experiments. A lab-scale model experiment was conducted on artificial sandy soil using foam and polymer as additives. The experimental results confirmed that screw torque was consistent with trends observed in previous laboratory pressurized vane shear test data, establishing a positive proportional relationship between screw torque and yield stress. The muck discharge efficiency according to foam injection ratio (FIR) showed similar values overall, but decreased slightly at 60% of FIR and when the polymer was added. In addition, the pressure distribution generated along the chamber and screw conveyor was assessed in a manner similar to the actual EPB TBM. This study demonstrates that the lab-scale screw conveyor model can be used to evaluate the shear properties and muck discharge efficiency.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.3
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• pp.147-153
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• 2013

There exist various types of the WEC (Wave Energy Converter), and among them, the point absorber is the most popularly investigated type. However, it is difficult to find examples of systematically measured data analysis for the design of the point absorber type of power buoy in the world. The study investigates the wave load acting on the point absorber type resonance power buoy wave energy extraction system proposed by Kweon et al. (2010). This study analyzes the time series spectra with respect to the three-year wave data (2002.05.01~2005.03.29) measured using the pressure type wave gage at the seaside of north breakwater of Hupo harbor located in the east coast of the Korean peninsula. From the analysis results, it could be deduced that monthly wave period and wave height variations were apparent and that monthly wave powers were unevenly distributed annually. The average wave steepness of the usual wave was 0.01, lower than that of the wind wave range of 0.02-0.04. The mode of the average wave period has the value of 5.31 sec, while mode of the wave height of the applicable period has the value of 0.29 m. The occurrence probability of the peak period is a bi-modal type, with a mode value between 4.47 sec and 6.78 sec. The design wave period can be selected from the above four values of 0.01, 5.31, 4.47, 6.78. About 95% of measured wave heights are below 1 m. Through this study, it was found that a resonance power buoy system is necessary in coastal areas with low wave energy and that the optimal design for overcoming the uneven monthly distribution of wave power is a major task in the development of a WEF (Wave Energy Farm). Finding it impossible to express the average spectrum of the usual wave in terms of the standard spectrum equation, this study proposes a new spectrum equation with three parameters, with which basic data for the prediction of the power production using wave power buoy and the fatigue analysis of the system can be given.