• Journal of Information Technology Applications and Management
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• v.14 no.3
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• pp.95-113
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• 2007

To minimize IT operational risks and the opportunity cost for lost business hours. it is necessary to have preparedness in advance and mitigation activities for minimization of a loss due to the business discontinuity. There are few cases that banks have a policy on systematic management, system recovery and protection activities against system failure. and most developers and system administrators response based on their experience and the instinct. This article focuses on the mitigation model development for minimizing the incidents of disk unit in IT operational risks. The model will be represented by a network model which is composed of the three items as following: (1) the risk factors(causes, attributes and indicators) of IT operational risk. (2) a periodic time interval through an analysis of historical data. (3) an index or an operational regulations related to the examination of causes of an operational risk. This article will be helpful when enterprise needs to hierarchically analyze risk factors from various fields of IT(information security, information telecommunication, web application servers and so on) and develop a mitigation model. and it will also contribute to the reduction of operational risks on information systems.

• Translational and Clinical Pharmacology
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• v.26 no.3
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• pp.115-117
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• 2018

This tutorial explains the basic principles of mechanistic ligand-receptor interaction model, which is an operational model of agonism. A growing number of agonist drugs, especially immune oncology drugs, is currently being developed. In this tutorial, time-dependent ordinary differential equation for simple $E_{max}$ operational model of agonism was derived step by step. The differential equation could be applied in a pharmacodynamic modeling software, such as NONMEM, for use in non-steady state experiments, in which experimental data are generated while the interaction between ligand and receptor changes over time. Making the most of the non-steady state experimental data would simplify the experimental processes, and furthermore allow us to identify more detailed kinetics of a potential drug. The operational model of agonism could be useful to predict the optimal dose for agonistic drugs from in vitro and in vivo animal pharmacology experiments at the very early phase of drug development.

• Journal of Korean Institute of Industrial Engineers
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• v.11 no.2
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• pp.173-187
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• 1985

A computer simulation model for optimum design and determination of optimal operational parameter values for modern container terminal systems was developed through the use of GASP-IV, a subset of SLAM. Input data reflecting current system configuration and operational practices at Pusan container terminal was used to test the model, which resulted in its validation. Possibilities for application of the model in areas of candidate system comparisons, operational parameter testing and forecasting operational performance under future traffic situations, are explained.

• Atmosphere
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• v.32 no.2
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• pp.87-101
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• 2022

In this paper, the performance improvement for the new KMA's Climate Prediction System (GloSea6), which has been built and tested in 2021, is presented by assessing the bias distribution of basic variables from 24 years of GloSea6 hindcasts. Along with the upgrade from GloSea5 to GloSea6, the performance of GloSea6 can be regarded as notable in many respects: improvements in (i) negative bias of geopotential height over the tropical and mid-latitude troposphere and over polar stratosphere in boreal summer; (ii) cold bias of tropospheric temperature; (iii) underestimation of mid-latitude jets; (iv) dry bias in the lower troposphere; (v) cold tongue bias in the equatorial SST and the warm bias of Southern Ocean, suggesting the potential of improvements to the major climate variability in GloSea6. The warm surface temperature in the northern hemisphere continent in summer is eliminated by using CDF-matched soil-moisture initials. However, the cold bias in high latitude snow-covered area in winter still needs to be improved in the future. The intensification of the westerly winds of the summer Asian monsoon and the weakening of the northwest Pacific high, which are considered to be major errors in the GloSea system, had not been significantly improved. However, both the use of increased number of ensembles and the initial conditions at the closest initial dates reveals possibility to improve these biases. It is also noted that the effect of ensemble expansion mainly contributes to the improvement of annual variability over high latitudes and polar regions.

• Journal of the military operations research society of Korea
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• v.24 no.2
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• pp.95-116
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• 1998

Many different kinds of wargame models have been developed and used in training and analysis purpose. However, there has been few wargame model which analyze corps or division level operational analysis. Recently KIDA develops corps level operational analysis model based on START(simplified tool for analysis of regional treats) model developed by RAND. This model runs in a PC level with 2MB memory and provides one day combat results within 30 seconds. Only one or three person can operate this model and evaluate multiple corps level operational analysis including chemical effects, $C^3I$ capacity, new weapon system effectiveness and other qualitative effects. We tested this model and evaluated input and output data. We showed that this model can be applied in division level operational analysis also. As an example division level application procedure and sensitivity analysis data was provided. We also find some limitation and problems in the model and suggest application areas and improving methods.

• Atmosphere
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• v.30 no.2
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• pp.141-154
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• 2020

Seasonal forecast is growing in demand, as it provides valuable information for decision making and potential to reduce impact on weather events. This study examines how operational climate prediction systems can be reliable, producing the probability forecast in seasonal scale. A reliability diagram was used, which is a tool for the reliability by comparing probabilities with the corresponding observed frequency. It is proposed for a method grading scales of 1-5 based on the reliability diagram to quantify the reliability. Probabilities are derived from ensemble members using hindcast data. The analysis is focused on skill for 2 m temperature and precipitation from climate prediction systems in KMA, UKMO, and ECMWF, NCEP and JMA. Five categorizations are found depending on variables, seasons and regions. The probability forecast for 2 m temperature can be relied on while that for precipitation is reliable only in few regions. The probabilistic skill in KMA and UKMO is comparable with ECMWF, and the reliabilities tend to increase as the ensemble size and hindcast period increasing.

• Korean Management Science Review
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• v.22 no.1
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• pp.1-13
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• 2005

This paper proposed a quantitative evaluation method to measure the operational effectiveness of the local military manpower administrations. The proposed method compared the relative operational effectiveness level for 12 local military manpower administrations in Korea.. The method used the IDEA (imprecise Data Envelopment Analysis) model which Is able to measure relative operational effectiveness level, and also used two input variables (labor cost, operational cost) and three output variables (number of military applicants, number of civil application approved & processed, management accuracy level). Through the model output analysis, we presented the relative effectiveness scores, the reason for non-effectiveness, and the relationship between non-effective ness level and input/output variables for each local military manpower administration. We also presented a few recommendations how to improve the effectiveness level on particular local military manpower administration.

• International Journal of Reliability and Applications
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• v.5 no.2
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• pp.75-80
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• 2004

Relationships between inventory policy and operational availability of military equipment maintained under a logistics support system are analyzed. A continuous review inventory model with a stochastic demand typically used in a military logistics support is considered and some numerical studies are provided.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.367-378
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• 2021

This paper develops a dynamic regression model to quantify the contribution of key external factors to operational energy efficiency of ships. On this basis, kernel density estimation is applied to explore distribution patterns of fluctuations in operational performance. An empirical analysis based on these methods show that distribution of fluctuations in Energy Efficiency Operational Indicator (EEOI) is leptokurtic and fat tailed, rather than a normal one. Around 85% of fluctuations in EEOI can be jointly explained by capacity utilization and sailing speed, while the rest depend on other external factors largely beyond control. The variations in capacity utilization and sailing speed cannot be fully passed on to the energy efficiency performance of ships, due to complex interactions between various external factors. The application of the methods is demonstrated, showing a potential approach to develop a rating mechanism for use in the legally binding framework on operational energy efficiency of ships.

• Atmosphere
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• v.30 no.2
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• pp.155-167
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• 2020

In order to produce more detailed and accurate information of river discharge and freshwater discharge, global high-resolution hydrodynamic model (CaMa-Flood) is applied to an operational land surface model of global seasonal forecast system. In addition, bias correction to grid runoff for the hydrodynamic model is attempted. CaMa-Flood is a river routing model that distributes runoff forcing from a land surface model to oceans or inland seas along continentalscale rivers, which can represent flood stage and river discharge explicitly. The runoff data generated by the land surface model are bias-corrected by using composite runoff data from UNH-GRDC. The impact of bias-correction on the runoff, which is spatially resolved on 0.5° grid, has been evaluated for 1991~2010. It is shown that bias-correction increases runoff by 30% on average over all continents, which is closer to UNH-GRDC. Two experiments with coupled CaMa-Flood are carried out to produce river discharge: one using this bias correction and the other not using. It is found that the experiment adapting bias correction exhibits significant increase of both river discharge over major rivers around the world and continental freshwater discharge into oceans (40% globally), which is closer to GRDC. These preliminary results indicate that the application of CaMa-Flood as well as bias-corrected runoff to the operational global seasonal forecast system is feasible to attain information of surface water cycle from a coupled suite of atmospheric, land surface, and hydrodynamic model.