KSCE Journal of Civil and Environmental Engineering Research
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v.28
no.5B
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pp.575-589
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2008
In the present work, we investigate the hydrodynamic behavior of a turbulent bore, such as tsunami bore and tidal bore, generated by the removal of a gate with water impounded on one side. The bore generation system is similar to that used in a general dam-break problem. In order to the numerical simulation of the formation and propagation of a bore, we consider the incompressible flows of two immiscible fluids, liquid and gas, governed by the Navier-Stokes equations. The interface tracking between two fluids is achieved by the volume-of-fluid (VOF) technique and the M-type cubic interpolated propagation (MCIP) scheme is used to solve the Navier-Stokes equations. The MCIP method is a low diffusive and stable scheme and is generally extended the original one-dimensional CIP to higher dimensions, using a fractional step technique. Further, large eddy simulation (LES) closure scheme, a cost-effective approach to turbulence simulation, is used to predict the evolution of quantities associated with turbulence. In order to verify the applicability of the developed numerical model to the bore simulation, laboratory experiments are performed in a wave tank. Comparisons are made between the numerical results by the present model and the experimental data and good agreement is achieved.
Objectives: Heart failure is a chronic disease with increasing prevalence rates despite advancements in medical technology. Korean medicine utilizes herbal prescriptions to treat heart failure, but little is known about the specific herbal medicines comprising the network of herbal prescriptions for heart failure. This study proposes a novel methodology that can efficiently develop prescriptions and facilitate experimental research on heart failure by utilizing existing databases. Methods: Herbal medicine prescriptions for heart failure were identified through a PubMed search and compiled into a Google Sheet database. NetMiner 4 was used for network analysis, and the individual networks were classified according to the herbal medicine classification system to identify trends. K-HERB NETWORK was utilized to derive related prescriptions. Results: Network analysis of heart failure prescriptions and herbal medicines using NetMiner 4 produced 16 individual networks. Uhwangcheongsim-won (牛黃淸心元), Gamiondam-tang (加味溫膽湯), Bangpungtongseong-san (防風通聖散), and Bunsimgi-eum (分心氣飮) were identified as prescriptions with high similarity in the entire network. A total of 16 individual networks utilized K-HERB NETWORK to present prescriptions that were most similar to existing prescriptions. The results provide 1) an indication of existing prescriptions with potential for use to treat heart failure and 2) a basis for developing new prescriptions for heart failure treatment. Conclusion: The proposed methodology presents an efficient approach to developing new heart failure prescriptions and facilitating experimental research. This study highlights the potential of network pharmacology methodology and its possible applications in other diseases. Further studies on network pharmacology methodology are recommended.
Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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2021.10a
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pp.128-130
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2021
This study aims to implement a Regression Analysis system for predicting the appropriate production of flatfish. Due to Korea's signing of FTAs with countries around the world and accelerating market opening, Korean flatfish farming businesses are experiencing many difficulties due to the specificity and uncertainty of the environment. In addition, there is a need for a solution to problems such as sluggish consumption and price drop due to the recent surge in imported seafood such as salmon and yellowtail and changes in people's dietary habits. in this study, Using the python module, xlwings, it was used to obtain for the production amount of flatfish and to predict the amount of flatfish to be produced later. was used to predict the amount of flatfish to be produced in the future. Therefore, based on the analysis results of this prediction of flatfish production, the flatfish aquaculture industry will be able to come up with a plan to achieve an appropriate production volume and control supply and demand, which will reduce unnecessary economic loss and promote new value creation based on data. In addition, through the data approach attempted in this study, various analysis techniques such as artificial neural networks and multiple regression analysis can be used in future research in various fields, which will become the foundation of basic data that can effectively analyze and utilize big data in various industries.
KSCE Journal of Civil and Environmental Engineering Research
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v.30
no.2B
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pp.191-198
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2010
Assessing seasonality of precipitation is necessarily required to establish future plans and policies for water resources management. In this regard, a main objective of the study is to introduce an effective approach for assessing the seasonality of the precipitation and evaluate the seasonality through the proposed one. We have used circular statistics to characterize the seasonality on the precipitation in Korea. The circular statistics allow us to effectively assess changes in timing of the seasonality in detail. It was found that peak time on monthly rainfall occurred between end of June and early July in southern coastal area while the timing was delayed in northern part of Korea because of monsoon moving in from south to north. In case of annual daily peak precipitation, spatio-temporal variation of the peak time was increased. It is mainly because of geophysical effects, frequency and paths of typhoons. Finally, temporal variations on the timing of the peak seasons were evaluated through circular statistics by 30-year moving average data. The peak season in the Northen part of Korea (e.g. Seoul and Gangrung) has been moved back from early July to end of July while the peak season has been moved up from middle of July to early July in the Southern part of Korea (e.g. Busan and Mokpo). It seems that changes in seasonality are mostly modulated by variability in the east-asia monsoon system.
This study observed elderly women's adaptation process on separation by death in rural areas through grounded theory approach and developed its entity theory. Participants for this study were 14 elderly women who have lost their husbands in the last 12 months. The study was conducted for 8 months starting January 2010. Each interview per session took 40 to 90 minutes, study notes were taken on site, and recorded contents were transcribed by the researcher which was myself. The research data were collected by in-depth interview and with help of local community's nurses who were in charge of taking care of the participants. The collected data were analyzed by applying Strauss & Corbin's grounded theory (1998). As a result of study, 80 concepts, 28 subcategories, and 12 categories were deducted during open coding process. Adaptation process on separation by death was process of 'finding a way to live alone' which used strategy of 'attempting a make changes in life', and 'embracing the situation' which were influenced by conciliatory conditions of 'degree on economic condition', 'change in health', and 'supporting system' which focuses on phenomenon of 'bearing life alone' which is influenced by context condition of 'marital chemistry of couples during lifetime', and 'the couple's leadership during lifetime' together with casual conditions of 'the fall of wall'. The adaptation process accordance to time flow were divided into 4 steps which were step of 'shock and release of emotions', step of 'longing and resentment', step of 'resignation and acceptance', and step of 'life's restructure'. Above results suggest right directions for welfare for the aged and process of 'finding a way to live alone' for participants by controlling several factors and using intervention strategy, and provided basic data required for developing and applying practical welfare mediation.
The purpose of this study is a exploratory study for understanding the process of the social isolation of the socially isolated elderly through the approach to their life history. The research was analyzed by one of the methods of qualitative research on life history, the conceptual framework of 'Dimensions, turning, and adaptation' of Mandelbaum(1973). According to the results of this study, the socially isolated elderly people were found to be socially isolated by experiencing complex difficulties such as family disconnection, poverty, poor job and health deterioration. Specifically, in the area of life, there was experience of poor relationship with parent, absence of family, poverty of family and unfavorable relationship with surrounding people in life with original family before isolation. They had bad jobs in the labor market, such as hard labor, delivery, business, and chores. In the area of turning point, we experienced family break due to the separation of the original family and the spouse due to various reasons such as financial crisis, parental divorce and death, spouse affair, economic difficulty. In a transitional stage in the life, many reasons such as the financial crisis, the death of parents, the extramarital affair and economic difficulties led to the disconnection from their original family and their spouses. In an adaptive phase, participants accepted the changed life at each turning point in their lives, carrying out their roles, compromising and trying to adapt properly. He said that their current life, which has entered the social safety net system of the people's basic recipients, has led him to live a more stable life and is adapting to personal hobbies and vicarious satisfaction through networks. This result is somewhat different from previous studies in which isolated elderly people were severely exposed to the risk of depression and loneliness. However, we should also consider the characteristics of this study that interviewed elderly people with relatively low isolation. Based on the results of this research, he presented various practical policy implications.
This study serves the main research purpose of verifying the hypothetical relationship between antecedent and consequence variables of shopping experience based on the classification system by Schmitt (1999) who dimensionalized experience into five components (sense, feel, think, act, relate). Specifically, the study seeks to fulfill the following three research objectives. First, it substantiates dynamic relationships among the five experiential components comprising the strategic experiential modules that serve as the basis of the theoretical framework of the study. Especially, it focuses on interactive relationships among the experiential components by taking a holistic view of the experience. Second, the study seeks to uncover the effects of pre-experiential antecedents such as shopping motivation and shopping involvement, based on taxonomy of motivation as product-centered vs. experience-centered. Third, the study investigates the effects of shopping experience on intention to revisit with regard to department store, discount store, and Internet shops, based on customers' store experiences. The major findings from this study are as follows: first, the five experiential components were found to have a high level of correlations according to hypothesis verification. Second, shopping motivation was learned to have significant effects on preference toward thinking as well as feeling experiences. That is, product-centered (vs. experience-centered) shopping motivation exerted a greater influence on cognitive (vs. affective experience than affective (vs. cognitive) experience.
KIPS Transactions on Software and Data Engineering
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v.12
no.11
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pp.481-492
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2023
This study explores how to build a Korean dataset to extract information from text using generative large language models. In modern society, mixed information circulates rapidly, and effectively categorizing and extracting it is crucial to the decision-making process. However, there is still a lack of Korean datasets for training. To overcome this, this study attempts to extract information using text-based zero-shot learning using a generative large language model to build a purposeful Korean dataset. In this study, the language model is instructed to output the desired result through prompt engineering in the form of "system"-"instruction"-"source input"-"output format", and the dataset is built by utilizing the in-context learning characteristics of the language model through input sentences. We validate our approach by comparing the generated dataset with the existing benchmark dataset, and achieve 25.47% higher performance compared to the KLUE-RoBERTa-large model for the relation information extraction task. The results of this study are expected to contribute to AI research by showing the feasibility of extracting knowledge elements from Korean text. Furthermore, this methodology can be utilized for various fields and purposes, and has potential for building various Korean datasets.
In this study, a proposed ensemble learning technique aims to enhance the semantic segmentation performance of images captured by Unmanned Aerial Vehicles (UAVs). With the increasing use of UAVs in fields such as urban planning, there has been active development of techniques utilizing deep learning segmentation methods for land cover segmentation. The study suggests a method that utilizes prominent segmentation models, namely U-Net, DeepLabV3, and Fully Convolutional Network (FCN), to improve segmentation prediction performance. The proposed approach integrates training loss, validation accuracy, and class score of the three segmentation models to enhance overall prediction performance. The method was applied and evaluated on a land cover segmentation problem involving seven classes: buildings,roads, parking lots, fields, trees, empty spaces, and areas with unspecified labels, using images captured by UAVs. The performance of the ensemble model was evaluated by mean Intersection over Union (mIoU), and the results of comparing the proposed ensemble model with the three existing segmentation methods showed that mIoU performance was improved. Consequently, the study confirms that the proposed technique can enhance the performance of semantic segmentation models.
Journal of the Korean Institute of Landscape Architecture
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v.51
no.5
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pp.30-43
/
2023
Green infrastructure(GI) is considered a key strategy in establishing sustainable communities. However, research on GI from the perspective of urban system dynamics and resilience lacks depth, as does its integration with physical design. This research addresses two primary causes. First, there is a gap in methods between existing GI planning, which considers static variables, and urban modeling research, which addresses dynamic variables. Second, there is a gap in information between landscape design and urban modeling research. To address these issues, this study proposes an integrated modeling approach in consideration of design decision-making. By combining the LEAM model and MCDA model, this study evaluates the relationship between GI services and socioeconomic growth, while spatially forecasting the geographies of GI demand in 2050. The resulting information reveals a potential degradation in ecosystem services over the region due to Chicago's sub-urbanization. This indicates that there would be a spatial shift in GI demand, emphasizing the need for comprehensive, dynamic GI strategies. This study further discusses the applications of evidence-based design in a studio environment. This study aims to contribute to the GeoDesign literature in terms of the creation of a more resilient urban environment by facilitating efficient evidence-based decision-making.
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