• Journal of Korea Water Resources Association
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• v.44 no.12
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• pp.1015-1029
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• 2011

Conventional MCDA techniques have been used in the field of water resources in the past. A GIS can offer an effective spatial data-handling tool that can enhance water resources modeling through interfaces with sophisticated models. However, GIS systems have a limited capability as far as the analysis of the value structure is concerned. The MCDA techniques provide the tools for aggregating the geographical data and the decision maker's preferences into a one-dimensional value for analyzing alternative decisions. In other words, the MCDA allows multiple criteria to be used in deciding upon the best alternatives. The combination of GIS and MCDA capabilities is of critical importance in spatial multi-criteria analysis. The advantage of having spatial data is that it allows the consideration of the unique characteristics at every point. The purpose of this study is to identify, review, and evaluate the performance of a number of conventional MCDA techniques for integration with GIS. Even though there are a number of techniques which have been applied in many fields, this study will only consider the techniques that have been applied in floodplain decision-making problems. Two different methods for multi-criteria evaluation were selected to be integrated with GIS. These two algorithms are Compromise Programming (CP), Spatial Compromise Programming (SCP). The target region for a demonstration application of the methodology was the Suyoung River Basin in Korea.

• Korean Journal of Construction Engineering and Management
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• v.20 no.6
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• pp.107-116
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• 2019

Korean construction engineering firms want to pave the way for expansion of overseas markets through the World Bank's Official Development Assistance (ODA) projects as a way to improve their overseas project performance. However, since the World Bank project competes with global companies for limited projects, building partnerships with suitable business partners is essential to gain an upper hand in bidding competition and meet the institutional conditions of the recipient country. In this regard, many network studies have been conducted in the past through Social Network Analysis (SNA), but few have been analyzed based on the process of changes in the network. So, This study collected winning data from the three Southeast Asian countries that ended after the World Bank's ODA project performed smoothly, and established a learning-based link prediction model that reflected the dynamic nature of the network. As a result, the 11 main variables acting on building a cooperative relationship between winning companies were derived and the effect of each variables on the probability value of cooperation between individual links was identified.

• Journal of Korea Port Economic Association
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• v.30 no.1
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• pp.73-96
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• 2014

Competitiveness of container ports has been traditionally evaluated by capability of individual ports to provide services to customers or their service quality. However, since container ports are connected by container shipping networks to varying degrees, the status of the ports in liner shipping service networks also determines competitiveness of the ports. Sometimes same ports may play different roles in different forms of shipping networks. Shipping network connections that formulate in container ports therefore have more significant impact on their performance than service capabilities they have. This study aims to explore how the shipping and port network has been structured and changed in the past and to examine the network characteristics of ports using Social Network Analysis(SNA). In this SNA study, nodes in the network are the ports-of-call of the liner shipping services and links in the network are connections realized by vessel movements, such that the liner shipping networks determine the port networks. This study, therefore, investigates the liner shipping networks and through its results demonstrates the network characteristics of the ports that are represented by the four centrality indices. This provides port authorities and terminal operating companies with managerial implications to enhance competitiveness from customers' perspectives.

• Proceedings of the Ginseng society Conference
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• 2002.10a
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• pp.55-65
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• 2002

Ginseng has been used as a key constituent in traditional medicine prescriptions for centuries. Other than its well-known anti-stress and adaptogenic properties, ginseng has also been shown to be very effective in treating age-related deterioration in metabolic and memory functions. Although it is generally believed that the saponin (GS) fraction of the ginseng root accounts for the bioactivity of ginseng, a direct demonstration on which ginsenoside does what is still generally lacking. In the past decade, our laboratory has endeavored to identify the active GS components involved in energy metabolism, memory, and anti-neurotoxicity. To examine the ergogenic effects of GS in enhancing aerobic capacity, rats were subjected to either severe cold ($40^{\circ}C$ under helium-oxygen, two hours) or exercise workload $(70\%\;VO_{2}max,$ to exhaustion). Acute systemic injection (i.p.) of ginseng GS (5-20 mg/kg) significantly elevated both the total and maximum heat production in rats and improved their cold tolerance. However, pretreating the animal with the optimal dose (10 mg/kg) of GS devoid of $Rg_1\;and\;Rb_1$ failed to elicit any beneficial effects in improving cold tolerance. This indicates that either $Rb_1\;and/or\;Rg_1$ may be essential in exemplifying the thermogenic effect of GS. Further studies showed that only pretreating the animals with $Rb_1(2.5-5\;mg/kg),\;but\;not\;Rg_l,$ resulted in an increase in thermogenesis and cold tolerance. In contrast to the acute effect of GS on cold tolerance, enhancement of exercise performance in rats was only observed after chronic treatment (4 days). Further, we were able to demonstrate that both $Rb_1\;and\;Rg_1$ are effective in enhancing aerobic endurance by exercise. To illustrate the beneficial effects of GS in learning and memory, a passive avoidance paradigm (shock prod) was used. Our results indicated that the scopolamineinduced amnesia can be significantly reversed by chronically treating (4 days) the rats with either $Rb_1\;or\;Rg_1$ (1.25 - 2.5 mg/kg). To further examine its underlying mechanisms, the effects of various GS on ${\beta}-amyloid-modulated$ acetylcholine (ACh) release from the hippocampal slices were examined. It was found that inclusion of $Rb_1$ (0.1 ${\mu}M$), but not $Rg_1$, can attenuate ${\beta}-amyloid-suppressed$ ACh release from the hippocampal slices. Our results demonstrated that $Rb_1\;and\;Rg_1$ are the key components involved in various beneficial effects of GS but they may elicit their effects through different mechanisms.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.100-112
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• 2021

With the advent of big data, traffic prediction has been developed based on historical data analysis methods, but this method deteriorates prediction performance when a traffic incident that has not been observed occurs. This study proposes a method that can compensate for the reduction in traffic prediction accuracy in traffic incidents situations by hybrid approach of machine learning and traffic simulation. The blind spots of the data-driven method are revealed when data patterns that have not been observed in the past are recognized. In this study, we tried to solve the problem by reinforcing historical data using traffic simulation. The proposed method performs machine learning-based traffic prediction and periodically compares the prediction result with real time traffic data to determine whether an incident occurs. When an incident is recognized, prediction is performed using the synthetic traffic data generated through simulation. The method proposed in this study was tested on an actual road section, and as a result of the experiment, it was confirmed that the error in predicting traffic state in incident situations was significantly reduced. The proposed traffic prediction method is expected to become a cornerstone for the advancement of traffic prediction.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.247-254
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• 2021

As COVID-19 spread, non-face-to-face activities were required, and the use of service robots is gradually increasing. This paper analyzed the relationship between the increasing trend of service robots before and after COVID-19 through keyword search containing the keyword 'service robot AND non-face-to-face' over the past three years (2018.10-20219) using BigKines, a news big data analysis system. As a result, there were 0 cases in the first period (2018.10~2019.9), 52 cases in the second period (2019.10~2020.9) and 112 cases in the third period (2020.10~2021.9), an increase of 115% compared to the second period. The keywords commonly mentioned in the analysis of related words in the second and third periods were COVID-19, AI, the Ministry of Trade, Industry, and Energy, and LG Electronics, and the weight of COVID-19 was the largest, confirming that the analysis keyword. Due to the spread of Corona 19, non-face-to-face is required, and with the development of information and communication technology, the field of application of service robots is rapidly increasing. Accordingly, for the commercialization of service robots that will lead the non-face-to-face economy, there is an urgent need to nurture human resources that require standardization and expertise in safety and performance fields.

• Journal of Convergence for Information Technology
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• v.9 no.3
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• pp.140-145
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• 2019

With the development of IT technology, many changes are taking place in the health service environment over the past. However, even if medical technology is converged with IT technology, the problem of medical costs and management of health services are still one of the things that needs to be addressed. In this paper, we propose a model for hospitals that have established the IoT system to efficiently analyze and manage the personal information of users who receive medical services. The proposed model aims to efficiently check and manage users' medical information through an in-house IoT system. The proposed model can be used in a variety of heterogeneous cloud environments, and users' medical information can be managed efficiently and quickly without additional human and physical resources. In particular, because users' medical information collected in the proposed model is stored on servers through the IoT gateway, medical staff can analyze users' medical information accurately regardless of time and place. As a result of performance evaluation, the proposed model achieved 19.6% improvement in the efficiency of health care services for occupational health care staff over traditional medical system models that did not use the IoT system, and 22.1% improvement in post-health care for users who received medical services. In addition, the burden on medical staff was 17.6 percent lower on average than the existing medical system models.

• Journal of Veterinary Clinics
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• v.36 no.1
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• pp.7-14
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• 2019

In South Korea, six large outbreaks of highly pathogenic avian influenza (HPAI) have occurred since the first confirmation in 2003 from chickens. For the past 15 years, HPAI outbreaks have become an annual phenomenon throughout the country and has extended to wider regions, across rural and urban environments. An understanding of the spatial epidemiology of HPAI occurrence is essential in assessing and managing the risk of the infection; however, local spatial variations of relationship between HPAI incidences in Korea and related risk factors have rarely been derived. This study examined whether spatial heterogeneity exists in this relationship, using a geographically weighted Poisson regression (GWPR) model. The outcome variable was the number of HPAI-positive farms at 252 Si-Gun-Gu (administrative boundaries in Korea) level notified to government authority during the period from January 2014 to April 2016. This response variable was regressed to a set of sociodemographic and topographic predictors, including the number of wild birds infected with HPAI virus, the number of wintering birds and their species migrated into Korea, the movement frequency of vehicles carrying animals, the volume of manure treated per day, the number of livestock farms, and mean elevation. Both global and local modeling techniques were employed to fit the model. From 2014 to 2016, a total of 403 HPAI-positive farms were reported with high incidence especially in western coastal regions, ranging from 0 to 74. The results of this study show that local model (adjusted R-square = 0.801, AIC = 954.5) has great advantages over corresponding global model (adjusted R-square = 0.408, AIC = 2323.1) in terms of model fitting and performance. The relationship between HPAI incidence in Korea and seven predictors under consideration were significantly spatially non-stationary, contrary to assumptions in the global model. The comparison between global Poisson and GWPR results indicated that a place-specific spatial analysis not only fit the data better, but also provided insights into understanding the non-stationarity of the associations between the HPAI and associated determinants. We demonstrated that an empirically derived GWPR model has the potential to serve as a useful tool for assessing spatially varying characteristics of HPAI incidences for a given local area and predicting the risk area of HPAI occurrence. Considering the prominent burden of HPAI this study provides more insights into spatial targeting of enhanced surveillance and control strategies in high-risk regions against HPAI outbreaks.

• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.42-48
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• 2019

The significance of PNT information in the fourth industrial revolution is viewed differently in relation to the past. Autonomous vehicles, autonomous vessels, smart grids, and national infrastructure require sustainable and reliable services in addition to their high precision service. Satellite navigation system, which is the most representative system for providing PNT information, receive signals from satellites outside the earth so signal reception power is low and signal structures for civilian use are open to the public. Therefore, it is vulnerable to intentional and unintentional interference or hacking. Satellite navigation systems, which can easily acquire high performance of PNT information at low cost, require alternatives due to its vulnerability to the hacking. This paper proposed R-Mode (Ranging Mode) technology that utilizes currently operated navigation and communication infrastructure in terms of Signals of OPportunity (SoOP). For this, the Nationwide Differential Global Navigation Satellite System (NDGNSS), which currently gives a service of Medium Frequency (MF) navigation signal broadcasting, was used to validate the feasibility of a backup infrastructure in domestic maritime areas through simulation analysis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.464-466
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• 2019

Controllers used in nuclear power plants require high reliability. A controller including a Field Programmable Gate Array (FPGA) and a Complex Programmable Logic Device (referred to hereinafter as FPGA) has been applied to many Nuclear Power Plants (NPP) in the past, including the APR1400 (Advanced Power Reactor 1400), a Korean digital nuclear power plant. Initially, the FPGA was considered as a general IC (Integrated Circuit) and verified only by device verification and performance testing. In the 1990s, research on FPGA verification began, and until the FPGA became a chip, it was regarded as software and the software Verification and Validation (V&V) using IEEE 1012-2004 was implemented. Currently, IEC 62566, which is a European standard, has been applied for a lot of verification. This method has been evaluated as the most sensible method to date. This is because the method of verifying the characteristics of SoC (System on Chip), which has been a problem in the existing verification method, is sufficiently applied. However, IEC 62566 is a European standard that has not yet been adopted in the United States and maintains the application of IEEE 1012 for FPGA. IEEE 1012-2004 or IEC 62566 is a technical standard. In practice, various methods are applied to meet technical standards. In this paper, we describe the procedure and important points of verification method of Nuclear Safety Class FPGA applying SoC verification method.