• Parasites, Hosts and Diseases
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• v.29 no.3
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• pp.217-226
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• 1991

Three morphological types of the genus Metagonimus were found encysted in the dace, Tribolodon tacganowskii, caught from the Sumjin River, Korea. They include Metagonimus Yokogawa type (M. yokogawai) , Miyata type, and Koga type according to Saito's classification. The metacercariae were experimentally fed to rats and hamsters and a total of 1,624 Metagonimus worms were recovered from their small intestine. The number of each type was 820 for Yokogawa type, 688 for Miyata type, 46 for Koga type, and 70 undetermined. The major differential keys between Yokogawa and Miyata types were in the position of two testes, distribution of uterine tubules, and size of the eggs, and the keys between Miyata and Koga types were in the position of two testes, distribution of vitelline follicles, and size of the eggs. The validity of Miyata type as a specific level should be retained until more convincing evidences are obtained. Koga type is regarded as a synonym of M. takahashii. The present results reveal that there are 3 morphological types of Metagonimus whose larvae are encysted in the dace, T. tacganowskii, from the Sumjin River. Key words: Metagcnimus yokogawai, morphological types, rats, hamsters, dace ( Tribolodon tacxanowskii) , Sumjin Rver.

• Journal of Ginseng Research
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• v.45 no.6
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• pp.734-743
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• 2021

Background: The underlying mechanisms of the potential tumor-suppressive effects of ginsenoside Rh2 are complex. N6-methyladenosine (m6A) RNA methylation is usually dysregulated in cancer. This study explored the regulatory effect of ginsenoside Rh2 on m6A RNA methylation in cancer. Methods: m6A RNA quantification and gene-specific m6A RIP-qPCR assays were applied to assess total and gene-specific m6A RNA levels. Co-immunoprecipitation, fractionation western blotting, and immunofluorescence staining were performed to detect protein interactions and distribution. QRT-PCR, dual-luciferase, and ChIP-qPCR assays were conducted to check the transcriptional regulation. Results: Ginsenoside Rh2 reduces m6A RNA methylation and KIF26B expression in a dose-dependent manner in some cancers. KIF26B interacts with ZC3H13 and CBLL1 in the cytoplasm of cancer cells and enhances their nuclear distribution. KIF26B inhibition reduces m6A RNA methylation level in cancer cells. SRF bound to the KIF26B promoter and activated its transcription. SRF mRNA m6A abundance significantly decreased upon KIF26B silencing. SRF knockdown suppressed cancer cell proliferation and growth both in vitro and in vivo, the effect of which was partly rescued by KIF26B overexpression. Conclusion: ginsenoside Rh2 reduces m6A RNA methylation via downregulating KIF26B expression in some cancer cells. KIF26B elevates m6A RNA methylation via enhancing ZC3H13/CBLL1 nuclear localization. KIF26B-SRF forms a positive feedback loop facilitating tumor growth.

• Advances in concrete construction
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• v.9 no.3
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• pp.313-326
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• 2020

Glass fiber-reinforced polymer (GFRP) bars have been introduced as an effective alternative for the conventional steel reinforcement in concrete structures to mitigate the costly consequences of steel corrosion. However, despite the superior performance of these composite materials in terms of corrosion, the effect of replacing steel reinforcement with GFRP on the seismic performance of concrete structures is not fully covered yet. To address some of the key parameters in the seismic behavior of GFRP-reinforced concrete (RC) structures, two full-scale beam-column joints reinforced with GFRP bars and stirrups were constructed and tested under two phases of loading, each simulating a severe ground motion. The objective was to investigate the effect of damage due to earthquakes on the service and ultimate behavior of GFRP-RC moment-resisting frames. The main parameters under investigation were geometrical configuration (interior or exterior beam-column joint) and joint shear stress. The performance of the specimens was measured in terms of lateral load-drift response, energy dissipation, mode of failure and stress distribution. Moreover, the effect of concrete damage due to earthquake loading on the performance of beam-column joints under service loading was investigated and a modified damage index was proposed to quantify the magnitude of damage in GFRP-RC beam-column joints under dynamic loading. Test results indicated that the geometrical configuration significantly affects the level of concrete damage and energy dissipation. Moreover, the level of residual damage in GFRP-RC beam-column joints after undergoing lateral displacements was related to reinforcement ratio of the main beams.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.311-316
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• 2016

Breast cancer is one of the most common causes of cancer mortality in Iran. Social determinants of health are among the key factors affecting the pathogenesis of diseases. This cross-sectional study aimed to determine the social determinants of breast cancer survival time with parametric and semi-parametric regression models. It was conducted on male and female patients diagnosed with breast cancer presenting to the Cancer Research Center of Shohada-E-Tajrish Hospital from 2006 to 2010. The Cox proportional hazard model and parametric models including the Weibull, log normal and log-logistic models were applied to determine the social determinants of survival time of breast cancer patients. The Akaike information criterion (AIC) was used to assess the best fit. Statistical analysis was performed with STATA (version 11) software. This study was performed on 797 breast cancer patients, aged 25-93 years with a mean age of 54.7 (${\pm}11.9$) years. In both semi-parametric and parametric models, the three-year survival was related to level of education and municipal district of residence (P<0.05). The AIC suggested that log normal distribution was the best fit for the three-year survival time of breast cancer patients. Social determinants of health such as level of education and municipal district of residence affect the survival of breast cancer cases. Future studies must focus on the effect of childhood social class on the survival times of cancers, which have hitherto only been paid limited attention.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.7B
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• pp.647-659
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• 2003

LPM(Longest Prefix Matching)searching in If address lookup is a major bottleneck of IP packet processing in the high speed router. In the conventional lookup table for the LPM searching in CAM(Content Addressable Memory) the complexity of fast update take 0(1). In this paper, we designed pipeline architecture for fast update of 0(1) cycle of lookup table and high throughput and low area complexity on LPM searching. Lookup-table architecture was designed by CAM(Content Addressable Memory)away that uses 1bit RAM(Random Access Memory)cell. It has three pipeline stages. Its LPM searching rate is affected by both the number of key field blocks in stage 1 and stage 2, and distribution of matching Point. The RTL(Register Transistor Level) design is carried out using Verilog-HDL. The functional verification is thoroughly done at the gate level using 0.35${\mu}{\textrm}{m}$ CMOS SEC standard cell library.

• Journal of Platform Technology
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• v.11 no.5
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• pp.37-48
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• 2023

Since the announcement of the Financial Services Commission's 'Token Securities Issuance and Distribution System Improvement Plan' in February 2023, financial institutions, securities firms, and blockchain companies have been actively considering implementing IT platforms, but they are facing difficulties in selecting IT platforms for token securities because related legal regulations have not yet been clearly established. As a result, the need for rational and systematic criteria for the selection of blockchain-based token securities IT platforms has emerged, and this study explores and evaluates the key factors of token securities IT platform selection. Four factors were identified as the top-level factors, including 'maturity of the platform', 'operation and management of the platform', 'cost of introducing and maintaining the platform', and 'regulatory compliance for token securities', and 17 factors were identified as sub-level factors, including 'diversity', 'user authentication management', 'Adoption Costs', and 'financial regulations'. Among the 17 sub-factors, 'government financial regulation' and 'personal information protection' are selected as important factors, and the results of this study can help related organizations and financial companies make strategic decisions by providing systematic decision-making criteria for selecting token securities IT platforms.

• Journal of Distribution Science
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• v.13 no.11
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• pp.123-130
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• 2015

Purpose - Due to highly elevated levels of competition, many companies today have to face the problem of decreasing profits even when their actual sales volume is increasing. This is a common phenomenon that is seen occurring among companies that focus heavily on quantitative growth rather than qualitative growth. These two aspects of growth should be well balanced for a company to create a sustainable business model. For supply chain management (SCM) planners, the optimized, quantified flow of resources used to be of major interest for decades. However, this trend is rapidly changing so that managers can put the appropriate balance between sales volume and sales quality, which can be evaluated from the profit margin. Profit optimization is a methodology for companies to use to achieve solutions focused more on profitability than sales volume. In this study, we attempt to provide executional insight for companies considering implementation of the profit optimization system to enhance their business profitability. Research design, data, and methodology - In this study, we present a comprehensive explanation of the subject of profit optimization, including the fundamental concepts, the most common profit optimization logic algorithm -linear programming -the business functional scope of the profit optimization system, major key success factors for implementing the profit optimization system at a business organization, and weekly level detailed business processes to actively manage effective system performance in achieving the goals of the system. Additionally, for the purpose of providing more realistic and practical information, we carefully investigate a profit optimization system implementation case study project fulfilled for company S. The project duration was about eight months, with four full-time system development consultants deployed for the period. To guarantee the project's success, the organization adopted a proven system implementation methodology, supply chain management (SCM) six-sigma. SCM six-sigma was originally developed by a group of talented consultants within Samsung SDS through focused efforts and investment in synthesizing SCM and six-sigma to improve and innovate their SCM operations across the entire Samsung Organization. Results - Profit optimization can enable a company to create sales and production plans focused on more profitable products and customers, resulting in sustainable growth. In this study, we explain the concept of profit optimization and prerequisites for successful implementation of the system. Furthermore, the efficient way of system security administration, one of the hottest topics today, is also addressed. Conclusion - This case study can benefit numerous companies that are eagerly searching for ways to break-through current profitability levels. We cannot guarantee that the decision to deploy the profit optimization system will bring success, but we can guarantee that with the help of our study, companies trying to implement profit optimization systems can minimize various possible risks across various system implementation phases. The actual system implementation case of the profit optimization project at company S introduced here can provide valuable lessons for both business organizations and research communities.

• The Journal of Bigdata
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• v.7 no.2
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• pp.1-9
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• 2022

In the global era, the importance of imported food safety management is increasing. Address information of overseas food companies is key information for imported food safety management, and must be verified for prompt response and follow-up management in the event of a food risk. However, because each country's address system is different, one verification system cannot verify the addresses of all countries. Also, the purpose of address verification may be different depending on the field used. In this paper, we deal with the problem of classifying a given overseas food business address into the administrative district level of the country. This is because, in the event of harm to imported food, it is necessary to find the administrative district level from the address of the relevant company, and based on this trace the food distribution route or take measures to ban imports. However, in some countries the administrative district level name is omitted from the address, and the same place name is used repeatedly in several administrative district levels, so it is not easy to accurately classify the administrative district level from the address. In this study we propose a deep learning-based administrative district level classification model suitable for this case, and verify the actual address data of overseas food companies. Specifically, a method of training using a label powerset in a multi-label classification model is used. To verify the proposed method, the accuracy was verified for the addresses of overseas manufacturing companies in Ecuador and Vietnam registered with the Ministry of Food and Drug Safety, and the accuracy was improved by 28.1% and 13%, respectively, compared to the existing classification model.

• The KIPS Transactions:PartD
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• v.11D no.4
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• pp.991-1002
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• 2004

Online game business has emerged as the most lucrative entertainment industry, with over 20 million platers. The popularity of online games can be attributed to the presence of numerous PC Bangs around the country, which have pushed online games into the mainstream culture while broadband internet services facilitated online game play. The age distribution of online game players is expanding and a variety of new games are under development to target certain age groups. While the online game market continues to expand, with many new online game publishers entering the market, relatively little is known about which factors are strategically important for successful development of online games. A conceptual framework is proposed, and a structural equation modeling, for Identifying the factors affecting the market success of online games, is developed. The concept of online game community, idea generation, systematic development strategy, flexible development process, utilizing demo-version, outsourcing, etc, are ail introduced into the model, as the independent variables affecting the success level of online games directly and indirectly. Based on data collected from questionnaire survey, the validity of the model has been tested and interesting conclusions have been developed concerning the relationships between these variables. Statistical results show that utilizing online game community and system atic development strategy is the key for successful online game development. Other interesting results concerning game development strategy are also provided. It is hoped that this result might provide the useful guidelines for developing the successful online game contents. With a better understanding of key success factors, online game developers should be able to make adjustments in their development and marketing plans, providing them with a sustainable advantage over their competition.

• Journal of Distribution Science
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• v.12 no.4
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• pp.31-39
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• 2014

Purpose - This study investigates the following two issues. First, we attempt to find the important determinants of housing investment and to identify their significance rank using survey panel data. Recently, the expansion of global uncertainty in the real estate market has directly and indirectly influenced the Korean housing market; households demonstrate a sensitive reaction to changes in that market. Therefore, this study aims to draw conclusions from understanding how the impact of financial strength of the household is related to house investment. Second, we attempt to verify the effectiveness of diverse indices of financial strength such as DTI, LTV, and PIR as measures to monitor the housing market. In the continuous housing market recession after the global crisis, the government places top priority on residence stability. However, the government still imposes forceful restraints on indices of financial strength. We believe this study verifies the utility of these regulations when used in the housing market. Research design, data, and methodology - The data source for this study is the "National Survey of Tax and Benefit" from 2007 (1st) to 2011 (5th) by the Korea Institute of Public Finance. Based on this survey data, we use panel data of 3,838 households that have been surveyed continuously for 5 years. We sort the base variables according to relevance of house investment criteria using the decision tree model (DTM), which is the standard decision-making model for data-mining techniques. The DTM method is known as a powerful methodology to identify contributory variables for predictive power. In addition, we analyze how important explanatory variables and the financial strength index of households affect housing investment with the binary logistic multi-regressive model. Based on the analyses, we conclude that the financial strength index has a significant role in house investment demand. Results - The results of this research are as follows: 1) The determinants of housing investment are age, consumption expenditures, income, total assets, rent deposit, housing price, habits satisfaction, housing scale, number of household members, and debt related to housing. 2) The impact power of these determinants has changed more or less annually due to economic situations and housing market conditions. The level of consumption expenditure and income are the main determinants before 2009; however, the determinants of housing investment changed to indices of the financial strength of households, i.e., DTI, LTV, and PIR, after 2009. 3) Most of all, since 2009, housing loans has been a more important variable than the level of consumption in making housing market decisions. Conclusions - The results of this research show that sound financing of households has a stronger effect on housing investment than reduced consumption expenditures. At the same time, the key indices that must be monitored by the government under economic emergency conditions differ from those requiring monitoring under normal market conditions; therefore, political indices to encourage and promote the housing market must be divided based on market conditions.