Nguyen, Van Giang;Nguyen, Van Linh;Jung, Sungho;An, Hyunuk;Lee, Giha
Journal of Korea Water Resources Association
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v.56
no.12
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pp.939-953
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2023
Shallow water equations (SWE) serve as fundamental equations governing the movement of the water. Traditional numerical approaches for solving these equations generally face various challenges, such as sensitivity to mesh generation, and numerical oscillation, or become more computationally unstable around shock and discontinuities regions. In this study, we present a novel approach that leverages the power of physics-informed neural networks (PINNs) to approximate the solution of the SWE. PINNs integrate physical law directly into the neural network architecture, enabling the accurate approximation of solutions to the SWE. We provide a comprehensive methodology for formulating the SWE within the PINNs framework, encompassing network architecture, training strategy, and data generation techniques. Through the results obtained from experiments, we found that PINNs could be an accurate output solution of SWE when its results were compared with the analytical method. In addition, PINNs also present better performance over the Artificial Neural Network. This study highlights the transformative potential of PINNs in revolutionizing water resources research, offering a new paradigm for accurate and efficient solutions to the SVE.
Sound in the ocean is scattered by inhomogeneities of many different kinds, such as the sea surface, the sea bottom, or the randomly distributed bubble layer and school of fish. The total sum of the scattered signals from these scatterers is called reverberation. In order to simulate the reverberation signal precisely, combination of a propagation model with proper scattering models, corresponding to each scattering mechanism, is required. In this article, we develop a reverberation model based on the ray theory easily combined with the existing scattering models. Developed reverberation model uses (1) Chapman-Harris empirical formula and APL-UW model/SSA model for the sea surface scattering. For the sea bottom scattering, it uses (2) Lambert's law and APL-UW model/SSA model. To verify our developed reverberation model, we compare our results with those in Ellis' article and 2006 reverberation workshop. This verified reverberation model SNURM is used to simulate reverberation signal for the neighboring seas of South Korea at mid frequency and the results from model are compared with experimental data in time domain. Through comparison between experiment data and model results, the features of reverberation signal dependent on environment of each sea is investigated and this analysis leads us to select an appropriate scattering function for each area of interest.
The Journal of The Korea Institute of Intelligent Transport Systems
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v.23
no.4
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pp.37-53
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2024
This study selected bicycle road hazard detection factors for mobile IoT sensor device operation and developed service application plans. Twelve bicycle road hazard detection factors were derived through a focused group interview, and a fuzzy AHP-based importance analysis was conducted on 30 road and transportation experts. As a result, 'damage to pavement' (1st overall) and 'environmental obstacle' (2nd) with low visibility but a high risk of accidents were selected the most. The factors in terms of facility management, such as 'disconnected route occurrence' (4th), 'artificial obstacle' (5th), 'effective width' (6th), and 'poor drainage' (7th), were selected as the upper and middle areas. Factors that are not direct accident-inducing factors, such as 'loss of road markings' (11th) and 'free space width' (12th), were selected the least. Based on this, a plan was presented to apply the bicycle road hazard detection service and a service operation strategy according to real-time performance. Nevertheless, follow-up studies, such as human behavioral analysis based on bicycle operators, analysis according to the bicycle road type, service demonstration, and pilot operation, will be needed to develop safe bicycle road management is expected.
Currently, Korea's banking industry holds a sizable amount of non-performing loans which stem from the government-led bailout of many troubled firms in the 1980s. Although this burden was somewhat relieved with the aid of banks' recapitalization in the booming securities market between 1986-88, the insolvent credits still resulted in low profitability in the banking sector and have been detrimental to the progress of financial liberalization and internationalization. This paper surveys the corporate bailout experiences of major advanced countries and Korea in the past and derives a rationale for readjustment measures against non-performing loans, in which rescue plans depend on the nature of the financial system. Considering the features of Korea's financial system and the banking sector's recent performance, it discusses possible means of liquidation in keeping with the rationale. The conflict of interests among parties involved in non-performing loans is widely known as one of the major constraints in writing off the loans. Specifically, in the case of Korea, the government's excessive intervention in allocating credits has preempted the legitimate role of the banking sector, which now only passively manages its past loans, and has implicitly confused private with public risk. This paper argues that to minimize the incidence of insolvent loan readjustment, the government's role should be reduced and that the correspondent banks should be more active in the liquidation process, through the market mechanism, reflecting their access to detailed information on the troubled firms. One solution is that banks, after classifying the insolvent loans by the lateness or possibility of repayment, would swap the relatively sound loans for preferred stock and gradually write off the bad ones by expanding the banks' retained earnings and revaluing the banks' assets. Specifically, the debt-equity swap can benefit both creditors and debtors in the sense that it raises the liquidity and profitability of bank assets and strengthens the debtor's financial structure by easing the debt service burden. Such a creditor-led or market-led solution improves the financial strength and autonomy of the banking sector, thereby fostering more efficient resource allocation and risk sharing.
Modeling of longterm runoff is theoritically based on waterbalance analysis. Simplified equation of water balance with rainfall, evapotranspiration and soil moisture storage could be formulated into regression model with variables of rainfall, pan evaporation and previous-month streamflow. The hydrologic response of water shed could be represented lumpedly, qualitatively and deductively by regression coefficients of water-balance regression model. Characteristics of regression modeling of water-balance were summarized as follows; 1. Regression coefficient $b_1$ represents the rate of direct runoff component of precipitation. The bigger the drainage area, the less $b_1$ value. This means that there are more losses of interception, surface detension and transmission in the downstream watershed. 2. Regression coefficient $b_2$ represents the rate of baseflow due to changes of soil moisture storage. The bigger the drainage area and the milder the watershed slope, the bigger b, value. This means that there are more storage capacity of watershed in mild downstream watershed. 3. Regression coefficient $b_3$ represents the rate of watershed evaporation. This depends on the s oil type, soil coverage and soil moisture status. The bigger the drainage area, the bigger $b_3$ value. This means that there are more watershed evaporation loss since more storage of surface and subsurface water would be in down stream watershed. 4. It was possible to explain the seasonal variation of streamflow reasonably through regress ion coefficients. 5. Percentages of beta coefficients what is a relative measure of the importance of rainfall, evaporation and soil moisture storage to month streamflow are approximately 89%, 9% and 11% respectively.
With the development of the 4th industrial, research is being conducted to prevent diseases and reduce damage in various fields of science and technology such as medicine, health, and bio. As a result, artificial intelligence technology has been introduced and researched for image analysis of radiological examinations. In this paper, we will directly apply a deep learning model for classification and detection of pneumonia using chest X-ray images, and evaluate whether the deep learning model of the Inception series is a useful model for detecting pneumonia. As the experimental material, a chest X-ray image data set provided and shared free of charge by Kaggle was used, and out of the total 3,470 chest X-ray image data, it was classified into 1,870 training data sets, 1,100 validation data sets, and 500 test data sets. I did. As a result of the experiment, the result of metric evaluation of the Inception V3 deep learning model was 94.80% for accuracy, 97.24% for precision, 94.00% for recall, and 95.59 for F1 score. In addition, the accuracy of the final epoch for Inception V3 deep learning modeling was 94.91% for learning modeling and 89.68% for verification modeling for pneumonia detection and classification of chest X-ray images. For the evaluation of the loss function value, the learning modeling was 1.127% and the validation modeling was 4.603%. As a result, it was evaluated that the Inception V3 deep learning model is a very excellent deep learning model in extracting and classifying features of chest image data, and its learning state is also very good. As a result of matrix accuracy evaluation for test modeling, the accuracy of 96% for normal chest X-ray image data and 97% for pneumonia chest X-ray image data was proven. The deep learning model of the Inception series is considered to be a useful deep learning model for classification of chest diseases, and it is expected that it can also play an auxiliary role of human resources, so it is considered that it will be a solution to the problem of insufficient medical personnel. In the future, this study is expected to be presented as basic data for similar studies in the case of similar studies on the diagnosis of pneumonia using deep learning.
In Korea and the Philippines, as well as all over the world, with the recognition of the importance of marine ecological resources, the marine protected areas(MPA) have been established and managed to protect and preserve these resources. While the number of marine protected areas for marine ecological resources protection has been increased, there is main problem that the most of MPAs do not achieve their intended management objectives. the effective management. Because of the positive and negative impacts on local communities and fishermen as direct stockholders, there has been ongoing debate on the pros and cons of implementing MPAs. Accordingly, this research conducted a case study of establishing Marine Protected Areas in Guimaras, Philippines because Philippines fisheries code of 1998 (Republic Act 8550), which is enacted to manage, conserve and protect fishery resources, obliged local governments to designate no less than 15% of jurisdictional municipal water as fisheries resource protection areas for a long time. To do this, a dichotomous-choice contingent-valuation survey was conducted in the two municipalities of Guimaras, Philippines to investigate public opinion in debates over MPAs and to estimate willingness to pay (WTP) for MPAs to protect and conserve marine habitats for fishery resources. Because of the expected economic costs by prohibiting fishing activities within the establishing newMPA, 58.7% of respondents thought the costs should be compensated, but 91.4% respondents voted in favor of increasing MPAs for fisheries resources as a protective measure. Finally, with Contingent Valuation Method(CVM), the aggregate mean WTP (375.5ha) of San Lorenzo and Sibunag residents in Guimaras Province, Philippines for establishing the additional MPA in their municipality waters was estimated to $1,046,791. Therefore, these findings could be used as a valuable data for establishing effective management plan of MPAs in Korea.
The Journal of Korea Institute of Information, Electronics, and Communication Technology
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v.11
no.2
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pp.144-149
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2018
The eggs are incubated for 18 days through the generator and incubated in the developing incubator. During the developmental period, the weight loss of the fetus is correlated with the ventricular formation, and the proper ventricular formation is also associated with the healthy embryonic hatching and the egg hatching rate. However, in the incubator period of the domestic hatchery, it is a reality to acquire the resultant side by the Iranian standard weight measurement with the experience of the hatchery and the person concerned and the development period without the apparatus for measuring the present weight. As a result, prevalence of early mortality, hunger and illness during hatching are frequent. Monitoring the reduction of weaning weight is crucial to obtaining chick quality and hatching performance with weight changes within the development machine. Water loss is different depending on the size of eggs, egg shell, and elder group. We can expect to increase the hatching rate by measuring the weight change in real time and optimizing the ventilation change accordingly. There is a need to develop a real-time measurement system that can control 10 to 13% reduction of the total weight during hatching. The system through this study is a way to check the one - time directly when moving the existing egg, and it is impossible to control the measurement of the fetal water evaporation within the development period. Unlike systems that do not affect the hatching rate, four load cells are connected in parallel on the Arduino sketch board and the AT-command command is used to connect the mobile phone and computer in real time. The communication speed of Bluetooth was set to 15200 to match the communication speed of Arduino and Hyper-terminal program. The real - time monitoring system was designed to visually check the change of the weight of the fetus in the artificial incubator. In this way, we aimed to improve the hatching rate and health condition of the hatching eggs.
This study was carried out to investigate the differences in malt quality between high-protein Korean malting barley and low-protein Korean malting barley. The average protein content of each area in the 1996 crops was as follows; The protein content of Doosan-29 from Jeon-Nam was 14.1% (d.b), that of Sacheon-6 from kyung-Nam was 13.4% (d.b) and that of Doosan-8 from Je-Ju was 12.8% (d.b). In the micro malting trial for high and low protein malting barley, the original protein level of the malting barley was not changed and decreased during germination days. The malt friability of high-protein malting barley was very low, but that of low-protein malting barley was high. The malt friability of high-protein malting barley was 44.5% and that of low-protein malting barley was 84.2%. In proportion to an increase of +1% (d.b) in barley protein, the fine grind extract of malt was decreased -0.86% (d.b). Economically, it was the most negative factor for high-protein Korean malting barley. The ${\beta}-glucan$ content of high-protein malting barley was higher than that of low-protein malting barley. Wort viscosity and malt color were increased and Kolbach index was decreased in high-protein malting barley. Free amino nitrogen and diastatic power for high-protein malting barley were higher than those of low-protein malting barley. They were the most positive factors for high-protein Korean malting barley.
This study explored the sustainability of a blockchain-based cultural art performance video platform through the construction of Gyeonggi Art On, a new media art broadcasting station in Gyeonggi-do. In addition, the technical limitations of video content transaction using block chain, legal and institutional issues, and the protection of personal information and intellectual property rights were reviewed. As for the research method, participatory observation methods such as in-depth interviews with developers and operators and participation in meetings were conducted. The researcher participated in and observed the entire development process, including designing and developing blockchain nodes, smart contracts, APIs, UI/UX, and testing interworking between blockchain and content distribution services. Research Question 1: The results of the study on 'Which technology model is suitable for a blockchain-based performance video content distribution public platform?' are as follows. 1) The blockchain type suitable for the public platform for distribution of art performance video contents based on the blockchain is the private type that can be intervened only when the blockchain manager directly invites it. 2) In public platforms such as Gyeonggi ArtOn, among the copyright management model, which is an art based on NFT issuance, and the BC token and cloud-based content distribution model, the model that provides content to external demand organizations through API and uses K-token for fee settlement is suitable. 3) For public platform initial services such as Gyeonggi ArtOn, a closed blockchain that provides services only to users who have been granted the right to use content is suitable. Research question 2: What legal and institutional problems should be reviewed when operating a blockchain-based performance video distribution public platform? The results of the study are as follows. 1) Blockchain-based smart contracts have a party eligibility problem due to the nature of blockchain technology in which the identities of transaction parties may not be revealed. 2) When a security incident occurs in the block chain, it is difficult to recover the loss because it is unclear how to compensate or remedy the user's loss. 3) The concept of default cannot be applied to smart contracts, and even if the obligations under the smart contract have already been fulfilled, the possibility of incomplete performance must be reviewed.
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