This study purpose to examine the importer's risks that may arise from origin investigation by Customs authorities. We have drawn the important factors affecting the application of FTA preferential tariffs and divided the stages from the conclusion of the contract for the importer to the undergoing origin investigation. In addition, we demonstrate empirically that the risks that arise in areas where importers are difficult to control exist. As a management method of the uncontrollable risk from the importer, we have provided the methods that the seller stipulated the seller's responsibility in the trade contract, prepared for situations in which no one was responsible, and formulated a friendly and cooperative supply chain. Even if the seller's liability is clarified in the contract for sale, the risk of the investigation into the origin of the imported goods is not completely eliminated. This is because, under the current agreement and system, there is no way for the customs authority of the contracting party of the FTA to claim compensation for damages incurred by importers due to breach of agreement such as not returning the result of the origin verification. Importers are subject to customs duties, but there may actually be situations in which no one is responsible for them.
Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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v.7
no.4
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pp.593-601
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2017
In this paper, we constructed the model of production/investment, distribution, and screening by using variables that can be considered at each stage according to the value chain stage of the movie industry. To increase the predictive power of the model, a regression analysis was used to derive meaningful variables. Based on the given variables, we compared the difference in predictive power between the artificial neural network, which is a machine learning analysis method, and the decision tree analysis method. As a result, the accuracy of artificial neural network was higher than that of decision trees when all variables were added in production/ investment model and distribution model. However, decision trees were more accurate when selected variables were applied according to regression analysis results. In the screening model, the accuracy of the artificial neural network was higher than the accuracy of the decision tree regardless of whether the regression analysis result was reflected or not. This paper has an implication which we tried to improve the performance of movie prediction model by using machine learning analysis. In addition, we tried to overcome a limitation of linear approach by reflecting the results of regression analysis to ANN and decision tree model.
The rapid detection of bacteria in the oral cavity, its species identification, and bacterial count determination are important to diagnose oral diseases caused by pathogenic bacteria. The existing clinical microbial diagnosis methods are time-consuming as they involve observing patients' samples under a microscope or culturing and confirming bacteria using polymerase chain reaction (PCR) kits, making the process complex. Therefore, it is required to analyze the development status of substances and systems that can rapidly detect and analyze pathogenic microorganisms in the oral cavity. With research advancements, a close relationship between oral and systemic diseases has been identified, making it crucial to identify the changes in the oral cavity bacterial composition. Additionally, an early and accurate diagnosis is essential for better prognosis in periodontal disease. However, most periodontal disease-causing pathogens are anaerobic bacteria, which are difficult to identify using conventional bacterial culture methods. Further, the existing PCR method takes a long time to detect and involves complicated stages. Therefore, to address these challenges, the concept of point-of-care (PoC) has emerged, leading to the study and implementation of various chair-side test methods. This study aims to investigate the different PoC diagnostic methods introduced thus far for identifying pathogenic microorganisms in the oral cavity. These are classified into three categories: 1) microbiological tests, 2) microchemical tests, and 3) genetic tests. The microbiological tests are used to determine the presence or absence of representative causative bacteria of periodontal diseases, such as A. actinomycetemcomitans, P. gingivalis, P. intermedia, and T. denticola. However, the quantitative analysis remains impossible, and detecting pathogens other than the specific ones is challenging. The microchemical tests determine the activity of inflammation or disease by measuring the levels of biomarkers present in the oral cavity. Although this diagnostic method is based on increase in the specific biomarkers proportional to inflammation or disease progression in the oral cavity, its commercialization is limited due to low sensitivity and specificity. The genetic tests are based on the concept that differences in disease vulnerability and treatment response are caused by the patient's DNA predisposition. Specifically, the IL-1 gene is used in such tests. PoC diagnostic methods developed to date serve as supplementary diagnostic methods and tools for patient education, in addition to existing diagnostic methods, although they have limitations in diagnosing oral diseases alone. Research on various PoC test methods that can analyze and manage the oral cavity bacterial composition is expected to become more active, aligning with the shift from treatment-oriented to prevention-oriented approaches in healthcare.
Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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2021.10a
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pp.582-583
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2021
As the production of new and renewable energy such as solar and wind power has diversified, microgrid systems that can simultaneously produce and consume have been introduced. . In general, a decrease in electricity prices through solar power is expected in summer, so producer protection is required. In this paper, we propose a transparent and safe gift power transaction system between users using blockchain in a microgrid environment. A futures is simply a contract in which the buyer is obligated to buy electricity or the seller is obliged to sell electricity at a fixed price and a predetermined futures price. This system proposes a futures trading algorithm that searches for futures prices and concludes power transactions with automated operations without user intervention by using a smart contract, a reliable executable code within the blockchain network. If a power producer thinks that the price during the peak production period (Hajj) is likely to decrease during production planning, it sells futures first in the futures market and buys back futures during the peak production period (Haj) to make a profit in the spot market. losses can be compensated. In addition, if there is a risk that the price of electricity will rise when a sales contract is concluded, a broker can compensate for a loss in the spot market by first buying futures in the futures market and liquidating futures when the sales contract is fulfilled.
Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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2021.10a
/
pp.584-585
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2021
As the production of new and renewable energy such as solar and wind power has diversified, microgrid systems that can simultaneously produce and consume have been introduced. In general, a decrease in electricity prices through solar power is expected in summer, so producer protection is required. In this paper, we propose a transparent and safe gift power transaction system between users using blockchain in a microgrid environment. A futures is simply a contract in which the buyer is obligated to buy electricity or the seller is obliged to sell electricity at a fixed price and a predetermined futures price. This system proposes a futures trading algorithm that searches for futures prices and concludes power transactions with automated operations without user intervention by using a smart contract, a reliable executable code within the blockchain network. If a power producer thinks that the price during the peak production period is likely to decrease during production planning, it sells futures first in the futures market and buys back futures during the peak production period to make a profit in the spot market. losses can be compensated. In addition, if there is a risk that the price of electricity will rise when a sales contract is concluded, a broker can compensate for a loss in the spot market by first buying futures in the futures market and liquidating futures when the sales contract is fulfilled.
As advertising and promotions are categorized as operating expenses, managers tend to reduce marketing budget to improve their short term profitability. Gauging the value and accountability of marketing spending is therefore considered as a major research priority in marketing. To respond this call, recent studies have documented that financial market reacts positively to a firm's marketing activity or marketing related outcomes such as brand equity and customer satisfaction. However, prior studies focus on the relation of marketing variable and financial market variables. This study suggests a channel about how marketing activity increases firm valuation. Specifically, we propose that a firm's marketing activity increases the level of the firm's product market information and thereby the dispersion in financial analysts' earnings forecasts decreases. With less uncertainty about the firm's future prospect, the firm's managers and shareholders have less information asymmetry, which reduces the firm's cost of capital and thereby increases the valuation of the firm. To our knowledge, this is the first paper to examine how informational benefits can mediate the effect of marketing activity on firm value. To test whether marketing activity contributes to increase in firm value by mitigating information asymmetry, this study employs a longitudinal data which contains 12,824 firm-year observations with 2,337 distinct firms from 1981 to 2006. Firm value is measured by Tobin's Q and one-year-ahead buy-and-hold abnormal return (BHAR). Following prior literature, dispersion in analysts' earnings forecasts is used as a proxy for the information gap between management and shareholders. For model specification, to identify mediating effect, the three-step regression approach is adopted. All models are estimated using Markov chain Monte Carlo (MCMC) methods to test the statistical significance of the mediating effect. The analysis shows that marketing intensity has a significant negative relationship with dispersion in analysts' earnings forecasts. After including the mediator variable about analyst dispersion, the effect of marketing intensity on firm value drops from 1.199 (p < .01) to 1.130 (p < .01) in Tobin's Q model and the same effect drops from .192 (p < .01) to .188 (p < .01) in BHAR model. The results suggest that analysts' forecast dispersion partially accounts for the positive effect of marketing on firm valuation. Additionally, the same analysis was conducted with an alternative dependent variable (forecast accuracy) and a marketing metric (advertising intensity). The analysis supports the robustness of the main results. In sum, the results provide empirical evidence that marketing activity can increase shareholder value by mitigating problem of information asymmetry in the capital market. The findings have important implications for managers. First, managers should be cognizant of the role of marketing activity in providing information to the financial market as well as to the consumer market. Thus, managers should take into account investors' reaction when they design marketing communication messages for reducing the cost of capital. Second, this study shows a channel on how marketing creates shareholder value and highlights the accountability of marketing. In addition to the direct impact of marketing on firm value, an indirect channel by reducing information asymmetry should be considered. Potentially, marketing managers can justify their spending from the perspective of increasing long-term shareholder value.
Hyeon-Soo Shin;Chang-Hyeon Kim;Chang-Wan Ha;Hwan-Seong Kim
Proceedings of the Korean Institute of Navigation and Port Research Conference
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2023.05a
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pp.250-251
/
2023
The pallet, typically a form of tertiary packaging, is a flat structure used as a base for the unitization of goods in the supply chain. In addition, standard pallets such as T-11 and T-12 are used throughout the logistics industry to reduce the cost and enhance the efficiency of transportation. However, in the case of special cargo, it is impossible to handle such cargo using a standard pallet due to its size and weight, so many have developed and are now using their customized pallet. Therefore, this study suggests a pallet size optimization method to calculate the optimal pallet size, which minimizes the loss of space on a pallet. The main input features are the specifications and the storage quantity of each cargo, and the optimization method that has modified the Neighborhood Search Algorithm calculates the optimal pallet size. In order to verify the optimality of the developed algorithm, a comparative analysis has been conducted through simulation.
The purpose of this study is to analyze quantitatively and qualitatively the effects of the increase in online shopping and its effects on real-world commercial outlets. The empirical analysis of this study is based on the results of "Census on Establishments" and "Online Shopping Survey" that cover 15 years, from 2002 to 2016. According to the results of this study, the increase in the number of online transactions affects the decrease in the number of stores in the real-world retail sector. However, non-specialized large stores and chain convenience stores showed an increase in the number of stores. In addition, the number of F&B stores increased the most in line with the increase in online transactions. This is because the increase in online transactions and in internet users led to the use of more delivery applications and the introduction of popular places on blogs or through social media. Street-level rents for medium and large-sized locations increased. In other words, it is seen that the demand for differentiated real-world stores that provide a good user experience increases, even though online transactions also increase. These results suggest that real-world stores should provide good user experiences in their physical locations with a certain size and assortment of goods.
With the growth of the battery industry, a rapid increase in the production and usage of lithium-ion batteries is expected, and in line with this, much interest and effort is being paid to recycle waste batteries, including production scrap. Although much effort has been made to recycle cathode material, much attention has begun to recycle anode material to secure the supply chain of critical minerals and improve recycling rates. The proximate analysis that measures the content of coal can be used to analyze graphite in anode material, but it cannot accurately analyze due to the interaction between the components of the black mass. Therefore, in this study, thermogravimetric analysis of each component of black mass was measured as the temperature increased up to 950℃ in an oxygen atmosphere. As a result, in the case of cathode material, no change in mass was measured other than a mass reduction of about 5% due to oxidation of the binder and conductive material. In the case of anode material, except for a mass reduction of about 2% due to the binder, all mass reduction were due to the graphite(fixed carbon). In addition, metal conductors (Al, Cu) were oxidized and their mass increased as the temperature increased. Thermal analysis results of mixed samples of cathode/anode show similar results to the predictive values that can be calculated through each cathode and anode analysis results.
BACKGROUND/OBJECTIVES: Oxidative stress is a fundamental neurodegenerative disease trigger that damages and decimates nerve cells. Neurodegenerative diseases are chronic central nervous system disorders that progress and result from neuronal degradation and loss. Recent studies have extensively focused on neurodegenerative disease treatment and prevention using dietary compounds. Heseperetin is an aglycone hesperidin form with various physiological activities, such as anti-inflammation, antioxidant, and antitumor. However, few studies have considered hesperetin's neuroprotective effects and mechanisms; thus, our study investigated this in hydrogen peroxide (H2O2)-treated SH-SY5Y cells. MATERIALS/METHODS: SH-SY5Y cells were treated with H2O2 (400 µM) in hesperetin absence or presence (10-40 µM) for 24 h. Three-(4,5-Dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide assays detected cell viability, and 4',6-diamidino-2-phenylindole staining allowed us to observe nuclear morphology changes such as chromatin condensation and apoptotic nuclei. Reactive oxygen species (ROS) detection assays measured intracellular ROS production; Griess reaction assays assessed nitric oxide (NO) production. Western blotting and quantitative polymerase chain reactions quantified corresponding mRNA and proteins. RESULTS: Subsequent experiments utilized various non-toxic hesperetin concentrations, establishing that hesperetin notably decreased intracellular ROS and NO production in H2O2-treated SH-SY5Y cells (P < 0.05). Furthermore, hesperetin inhibited H2O2-induced inflammation-related gene expression, including interluekin-6, tumor necrosis factor-α, and nuclear factor kappa B (NF-κB) p65 activation. In addition, hesperetin inhibited NF-κB translocation into H2O2-treated SH-SY5Y cell nuclei and suppressed mitogen-activated protein kinase protein expression, an essential apoptotic cell death regulator. Various apoptosis hallmarks, including shrinkage and nuclear condensation in H2O2-treated cells, were suppressed dose-dependently. Additionally, hesperetin treatment down-regulated Bax/Bcl-2 expression ratios and activated AMP-activated protein kinase-mammalian target of rapamycin autophagy pathways. CONCLUSION: These results substantiate that hesperetin activates autophagy and inhibits apoptosis and inflammation. Hesperetin is a potentially potent dietary agent that reduces neurodegenerative disease onset, progression, and prevention.
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