• Asian Journal of Atmospheric Environment
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• v.11 no.4
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• pp.330-343
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• 2017

Climate change is an important issue, with many researches examining not only future climatic conditions, but also the interaction of climate and air quality. In this study, a new version of the emissions processing software tool - Python-based PRocessing Operator for Climate and Emission Scenarios (PROCES) - was developed to support climate and atmospheric chemistry modeling studies. PROCES was designed to cover global and regional scale modeling domains, which correspond to GEOS-Chem and CMAQ/CAMx models, respectively. This tool comprises of one main system and two units of external software. One of the external software units for this processing system was developed using the GIS commercial program, which was used to create spatial allocation profiles as an auxiliary database. The SMOKE-Asia emissions modeling system was linked to the main system as an external software, to create model-ready emissions for regional scale air quality modeling. The main system was coded in Python version 2.7, which includes several functions allowing general emissions processing steps, such as emissions interpolation, spatial allocation and chemical speciation, to create model-ready emissions and auxiliary inputs of SMOKE-Asia, as well as user-friendly functions related to emissions analysis, such as verification and visualization. Due to its flexible software architecture, PROCES can be applied to any pregridded emission data, as well as regional inventories. The application results of our new tool for global and regional (East Asia) scale modeling domain under RCP scenario for the years 1995-2006, 2015-2025, and 2040-2055 was quantitatively in good agreement with the reference data of RCPs.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.195-198
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• 2006

One of the major sources of error in precise GPS positioning since the turn-off the Selective Availability(SA) is the ionospheric propagation delay. For the last decades, a lot of the ionospheric researches based on a GPS network have been implemented throughout the world. Especially researches of the ionospheric modeling for Wide Area Argumentation System(WAAS) have been undertaken and published. In mid-latitude regions, typical spatial and temporal variations in ionospheric models delay tend to minimal. The developed ionospheric model calls for a 1.25 degree grid at latitudes and a 2.5 degree grid at longitudes. The precise grid TEC estimated by the inversion technique is also compared with global ionosphere maps(GIMs) which have been provided by several analysis centers(ACs). The results of initial investigations into the suitability of the proposed ionospheric modeling scheme in north-east Asia are presented.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.199-202
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• 2006

One of the major sources of error in precise GPS positioning since the turn-off the Selective Availability(SA) is the ionospheric propagation delay. For the last decades, a lot of the ionospheric researches based on a GPS network have been implemented throughout the world. Especially researches of the ionospheric modeling for Wide Area Argumentation System(WAAS) have been undertaken and published. In mid-latitude regions, typical spatial and temporal variations in ionospheric models delay tend to minimal. The developed ionospheric model calls for a 1.25 degree grid at latitudes and a 2.5 degree grid at longitudes. The precise grid TEC estimated by the inversion technique is also compared with global ionosphere maps(GIMs) which have been provided by several analysis centers(ACs). The results of initial investigations into the suitability of the proposed ionospheric modeling scheme in north-east Asia are presented.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.162-165
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• 2004

The authors' previous study found an interannual covariability between actual evapotranspiration (ET) and the Normalized Difference Vegetation Index (NDVI) over northern Asia. This result suggested that vegetation controls interannual variation in ET. In this prior study, NDVI data from the Pathfinder AVHRR Land (PAL) dataset were analyzed. However, studies of NDVI interannual change are subject to uncertainty, because NDVI data often contain errors associated with sensor- and atmosphere-related effects. This study is aimed toward reducing this uncertainty by employing NDVI dataset, from the Global Inventory Monitoring and Modeling Studies (GIMMS) group, in addition to PAL. The analysis was carried out for the northern Asia region from 1982 to 2000. 19-year interannual change in PAL-NDVI and GIMMS-NDVI were both compared with interannual change in model-assimilated ET. Although the correlation coefficient between GIMMS-NDVI and ET is slightly less than for PAL-NDVI and ET, for both NDVI datasets the annual maximum correlation with ET occurs in June, which is near the central period of the growing season. A significant positive correlation between GIMMS-NDVI and ET was observed over most of the vegetated land area in June as well as PAL-NDVI and ET. These results reinforce the authors' prior research that indicates the control of interannual change in ET is dominated by interannual change in vegetation activity.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.817-837
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• 2019

The medical industry is rapidly evolving into a combination of artificial intelligence (AI) and ICT technology, such as mobile health, wireless medical, telemedicine and precision medical care. Medical artificial intelligence can be diagnosed and treated, and autonomous surgical robots can be operated. For smart medical services, data such as medical information and personal medical information are needed. AI is being developed to integrate with companies such as Google, Facebook, IBM and others in the health care field. Telemedicine services are also becoming available. However, security issues of medical information for smart medical industry are becoming important. It can have a devastating impact on life through hacking of medical devices through vulnerable areas. Research on medical information is proceeding on the necessity of privacy and privacy protection. However, there is a lack of research on the practical measures for protecting medical information and the seriousness of security threats. Therefore, in this study, we want to confirm the research trend by collecting data related to medical information in recent 5 years. In this study, smart medical related papers from 2014 to 2018 were collected using smart medical topics, and the medical information papers were rearranged based on this. Research trend analysis uses topic modeling technique for topic information. The result constructs topic network based on relation of topics and grasps main trend through topic.

• Atmosphere
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• v.20 no.1
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• pp.49-61
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• 2010

Atmospheric aerosols play a crucial role for changing climate, resulting in a wide range of uncertainty for future climate prediction. In this paper we review current international research status and trend of climate-related aerosol science. There have been carried out a number of campaigns (including ACE-Asia, TRACE-P, ABC, and so on) and special experiments with some modeling studies over Korea, East Asia, and the Northwestern Pacific to characterize the various properties (physical, chemical, optical, and radiative) of Asian aerosols and evaluate their climate forcing impacts. But some parts of the aerosol research may need to be improved, advanced, or newly launched. Especially, a chemical transport model (CTM) embedded by a general circulation model (GCM) should be developed by the national scientific community with a high research priority, actively collaborating with international community in order to estimate direct and indirect global radiative forcing due to anthropogenic and natural aerosols.

• Asian Journal of Atmospheric Environment
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• v.10 no.3
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• pp.146-155
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• 2016

Spatial and temporal variations of mercury, including dry and wet deposition fluxes, were assessed over Northeast Asia, targeting the Yellow Sea, using meteorology and chemistry models. Four modeling periods, each representative of one of the four seasons, were selected. Modeling results captured general patterns and behaviors, and fell within similar ranges with respect to observations. However, temporal variations of mercury were not closely matched, possibly owing to the effects of localized emissions. Modeling results indicated that dry deposition is correlated with wind speed, while wet deposition is correlated with precipitation amount. Overall, the wet deposition flux of $66ng/m^2-day$ was about twice as large as the dry deposition flux of $32ng/m^2-day$, when averaged over the four modeling periods. Dry deposition occurred predominantly in the form of reactive gaseous mercury (RGM). In contrast, RGM accounted for only about two-thirds of wet deposition, while particulate mercury accounted for the remainder.

• Journal of Climate Change Research
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• v.2 no.4
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• pp.269-281
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• 2011

In this review, numerical model results from global and regional climate models are introduced to regional detailed climate changes over East Asia and Korea. In particular, regional climate change scenarios in this region, which are created by several research groups in Korea based on Special Report on Emissions Scenarios (SRES) of IPCC 4th assessment report are introduced and characteristics of the scenarios are investigated. Despite slight differences in intensity, all scenarios reveal prominent warming over the Korean peninsula in future climate. Changes in precipitation amount vary with given scenarios and periods, but the frequency and intensity of heavy precipitation generally tend to increase in all scenarios. South Korea except for mountainous regions is expected to change into subtropical climate in future, which accompanies distinct changes in ecosystems and seasons.

• The Journal of Asian Finance, Economics and Business
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• v.4 no.3
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• pp.57-73
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• 2017

In the current competitive marketplace of real estate business, tenant satisfaction measurement is one of the important indicators to monitor competitiveness in industrial property development. It has become an industry standard to measure tenant satisfaction, commonly called customer satisfaction. Customer satisfaction has become the widely used metric to manage customer loyalty (Keiningham, Gupta, Aksoy, & Buoye, 2014). The aim of this research is to determine the impact of property management services on tenants' satisfaction with the three identified variables i.e. facility management, perceived quality and lease management. Structural equation modeling (SEM) is applied to build constructs and test the hypotheses with the collected survey samples. Of the three variables, facility management is the most influential factor that leads to tenant satisfaction with industrial buildings. Next, perceived quality is another important factor that contributes to tenants' pleasure. Compared with these two, lease management fares worse, having the least extensive effect on tenant satisfaction, and could be disregarded. The ultimate impact of tenant satisfaction is about tenant retention and recommendation. The overall findings of this research will potentially help real estate developers to develop a better property management system, leasing program and tenant retention strategy.

• Proceedings of the Korea Port Economic Association Conference
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• 2006.08a
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• pp.1-12
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• 2006

As national economies globalize, demand for intercontinental container shipping services is growing rapidly, providing a potential economic boon for the countries and communities that provide port services. On the promise of profits, many governments are investing heavily in port infrastructure, leading to a possible glut in port capacity, driving down prices for port services and eliminating profits as ports compete for business. Further, existing ports are making strategic investments to protect their market share, increasing the chance new ports will be overcapitalized and unprofitable. Governments and port researchers need a tool for understanding how local competition in their region will affect demand for port services at their location, and thus better assess the profitability of a prospective port. We propose to develop such a tool by extending our existing simulation model of global container traffic to incorporate demand-side shipper preferences and supply-side strategic responses by incumbent ports to changes in the global port network, including building new ports, scaling up existing ports, and unexpected port closures. We will estimate shipper preferences over routes, port attributes and port services based on US and international shipping data, and redesign the simulation model to maximize the shipper's revealed preference functions rather than simply minimize costs. As demand shifts, competing ports will adjust their pricing (short term) and infrastructure (long term) to remain competitive or defend market share, a reaction we will capture with a game theoretic model of local monopoly that will predict changes in port characteristics. The model's hypotheses will be tested in a controlled laboratory experiment tailored to local port competition in Asia, which will also serve to demonstrate the subtle game theoretic concepts of imperfect competition to a policy and industry audience. We will apply the simulation model to analyze changes in global container traffic in three scenarios: addition of a new large port in the US, extended closure of an existing large port in the US, and cooperative and competitive port infrastructure development among Korean partner countries in Asia.