• Journal of Electrical Engineering and Technology
• /
• v.7 no.2
• /
• pp.141-150
• /
• 2012

The present study examines an efficient congestion management system compatible with the evolving environment. The key is to build an information model shared and exchanged for marketbased solutions to alleviate congestion. Traditional methods for congestion management can be classified into two categories, i.e., the centralized scheme and the decentralized scheme, depending on the extent to which the independent system operator (ISO) is involved in market participants' (MPs) activities. Although the centralized scheme is more appropriate for providing reliable system operation and relieving congestion in near real-time, the decentralized scheme is preferred for supporting efficient market operation. The minimum set of information between the ISO and MPs for decentralized scheme is identified: i) congestion-based zone, ii) Power Transfer Distribution Factors, and iii) transmission congestion cost. The mathematical modeling of the proposed information is expressed, considering its process of making effective use of information. Numerical analysis is conducted to demonstrate both cost minimization from the MP perspective and the reliability enhancement from the ISO perspective based on the proposed information exchange scheme.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.64 no.11
• /
• pp.1535-1542
• /
• 2015

An increasing number of electric vehicles (EVs) in power system affects its reliability in various aspects. Especially under high EV penetration level, new generating units are required to satisfy system's adequacy criterion. Wind power generation is expected to take the major portion of the new units due to environmental and economic issues. In this paper, the system reliability is analyzed using Loss of Load Expectation (LOLE) and Expected Energy Not Served (EENS) under each and both cases of increasing wind power generation and EVs. A probabilistic multi-state modeling method of wind turbine generator under various power output for adequate reliability evaluation is presented as well. EVs are modeled as loads under charging algorithm with Time-Of-Use (TOU) rates in order to incorporate EVs into hour-to-hour yearly load curve. With the expected load curve, the impact of EVs on the system adequacy is analyzed. Simulations show the reliability evaluation of increasing wind power capacity and number of EVs. With this method, system operator becomes capable of measuring appropriate wind power capacity to meet system reliability standard.

• Safety and Health at Work
• /
• v.1 no.1
• /
• pp.43-50
• /
• 2010

Objectives: The objective of this study was to investigate the effect of chain installation condition on stress distribution that could eventually cause disastrous failure from sudden deformation and geometric rupture. Methods: Fractographic method used for the failed chain indicates that over-stress was considered as the root cause of failure. 3D modeling and finite element analysis for the chain, used in a crane hook, were performed with a three-dimensional interactive application program, CATIA, commercial finite element analysis and computational fluid dynamic software, ANSYS. Results: The results showed that the state of stress was changed depending on the initial position of the chain that was installed in the hook. Especially, the magnitude of the stress was strongly affected by the bending forces, which are 2.5 times greater (under the simulation condition currently investigated) than that from the plain tensile load. Also, it was noted that the change of load state is strongly related to the failure of parts. The chain can hold an ultimate load of about 8 tons with only the tensile load acting on it. Conclusion: The conclusions of this research clearly showed that a reduction of the loss from similar incidents can be achieved when an operator properly handles the installation of the chain.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.3
• /
• pp.1009-1019
• /
• 2021

This study examined the effect of market sensing capability and information technology competency (IT competency) on innovation and competitive advantage in small and medium-sized tour operators (SMTOs). This research was conducted on the SMTOs located in three major cities for a tourism destination, meeting, and exhibition in East Java, Indonesia. 175 directors or managers of SMTOs were sampled using the purposive sampling technique. Data was obtained from directors or managers using a structured questionnaire. The empirical data was then analyzed by using Structural Equation Modeling (SEM). This study showed that market sensing capability positively and significantly affects innovation. Furthermore, competitive advantage was positively and significantly affected by market sensing capability. Although results showed that IT competence positively and significantly affects innovation, in contrast, it did not positively and significantly affect competitive advantage. These research findings suggest that market sensing capability and innovation have a substantial role in creating a competitive advantage for SMTOs facing the Revolution Industry 4.0 and a dynamic environment. Thus, innovation for SMTOs can be achieved by optimizing the role of market sensing capability and IT competency. However, this study also suggests that the capability or competence will not have any impact on competitive advantage if neither is optimized.

• Journal of Korea Trade
• /
• v.23 no.3
• /
• pp.52-67
• /
• 2019

Purpose - This study analyzes the effect of the authorized economic operator-mutual recognition arrangement (AEO-MRA) on the performance of Korean exporters and importers. The effect of the import-export companies' characteristics, such as annual sales, the number of foreign markets, and overseas experience, on the AEO-MRA is deduced; the relationship between this effect and firm performance is analyzed. Design/methodology - An empirical research model was constructed and analyzed using structural equation modeling. The effect of AEO-MRA on logistics and operational performance was derived from the aforementioned characteristics as leading factors of the AEO-MRA. The regulatory influence of cooperation with logistics companies was analyzed in the AEO-MRA effect on logistics performance. Thus, 172 valid samples were obtained from import-export companies certified by the AEO-MRA. Findings - Among the aforementioned characteristics, only "annual sales" has a positive effect on the AEO-MRA, whose effect enhances logistics and operational performances. The AEO-MRA effect did not directly affect operational performance. Owing to the adjustment effect analysis, the AEO-MRA effect and logistics performance relationship is strengthened if the cooperative relationship with the logistics company is higher than a certain level. If this cooperation falls below a certain level, the AEO-MRA effect on logistics performance reduces. Thus, logistics cooperation is an important factor in the AEO-MRA effect and logistics performance relationship. Originality/value - Hinging on the resource-based theory and relational viewpoint, an empirical model that explains the relationship between the AEO-MRA effect and firm performance is established.

• Geomechanics and Engineering
• /
• v.29 no.5
• /
• pp.523-533
• /
• 2022

Several prediction model of penetration rate (PR) of tunnel boring machines (TBMs) have been focused on applying to design stage. In construction stage, however, the expected PR and its trends are changed during tunneling owing to TBM excavation skills and the gap between the investigated and actual geological conditions. Monitoring the PR during tunneling is crucial to rescheduling the excavation plan in real-time. This study proposes a sequential prediction method applicable in the construction stage. Geological and TBM operating data are collected from Gunpo cable tunnel in Korea, and preprocessed through normalization and augmentation. The results show that the sequential prediction for 1 ring unit prediction distance (UPD) is R²≥0.79; whereas, a one-step prediction is R²≤0.30. In modeling algorithm, a gradient boosted regression tree (GBRT) outperformed a least square-based linear regression in sequential prediction method. For practical use, a simple equation between the R² and UPD is proposed. When UPD increases R² decreases exponentially; In particular, UPD at R²=0.60 is calculated as 28 rings using the equation. Such a time interval will provide enough time for decision-making. Evidently, the UPD can be adjusted depending on other project and the R² value targeted by an operator. Therefore, a calculation process for the equation between the R² and UPD is addressed.

• Journal of the Korea Safety Management & Science
• /
• v.26 no.3
• /
• pp.101-106
• /
• 2024

The health and working conditions of employees have become increasingly important issues in modern society. In recent years, there has been a continuous rise in problems related to the deterioration of workers' alth, which seriously affects their safety and overall quality of life. Although existing research has investigated various factors affecting workers' health and working conditions, there is still a lack of studies that scientifically analyze and identify key variables from the vast number of factors. This study employs the Lasso (Least Absolute Shrinkage and Selection Operator) technique to mathematically analyze the key variables influencing workers' health status and satisfaction with their working environment. Lasso is a technique used in machine learning to identify a small number of variables that impact the dependent variable among a large set of variables, thereby reducing model complexity and improving predictive accuracy. The results of the study can be utilized in efficiently improving workers' health and working environments by focusing on a smaller set of impactful variables.

• Fire Science and Engineering
• /
• v.30 no.5
• /
• pp.74-81
• /
• 2016

This study evaluated the habitability of operators for main control room fires in nuclear power plants. Fire modeling (FDS v.6.0) was utilized for a fire safety assessment so that it could determine the performance of the smoke ventilation and operator habitability with the main control room. For this study, it categorized fire scenarios into three cases depending on the conditions in the HVAC system. As a result of fire modelling, it showed that Case 1 (with HVAC) would give rise to the worst situation associated with the absolute temperature, radiative heat flux, optical density, and smoke layer height as deliberating the habitability and smoke ventilation. On the other hand, it showed that Cases 2 (w/o HVAC) and 3 can maintain much safer situations than Case 1. In the case of temperature at 820 s, Cases 2 and 3 were up to approximately 63% greater than Case 1 in the wake of ignition. In addition, the influence of radiative heat flux of Case 1 was even larger than Cases 2 and 3. That is, the radiative heat fluxes of Cases 2 and 3 were approximately 68% higher than Case 1. Furthermore, when it comes to considering the optical density, Case 1 was approximately 93% greater than Cases 2 and 3. Accordingly, it expected that the HVAC system can influence a the performance on the smoke ventilation that can be sustainable for operator habitability. On the other hand, it revealed an inconsecutive pattern for the smoke layer height of Cases 2 and 3 because supply vents and exhaust vents were installed within the same surface.

• Ocean and Polar Research
• /
• v.39 no.3
• /
• pp.205-211
• /
• 2017

This paper seeks to provide a dynamic analysis of a 150 ton winch based on ocean environmental data. The winch model that was subjected to analysis was modeled from CAD to each subsystem by the commercial software DAFUL. The winch model has tree brake systems (disk brake, band brake and ratchet brake). The rotation motion of the motor and contact elements of the brake are applied to the winch model in order to analyze its dynamic characteristics. In addition, a crane-barge was modeled to apply ocean environmental data. The motion data of the crane-barge was produced by means of the RAO(Response Amplitude Operator) of the barge and wave spectrum. The reaction force of the translational joint was measured instead of the tension of the cable. The brake performance of the winch was produced and assessed based on the operating motion of the crane-barge.

• Genomics & Informatics
• /
• v.17 no.4
• /
• pp.47.1-47.12
• /
• 2019

The achievements of genome-wide association studies have suggested ways to predict diseases, such as type 2 diabetes (T2D), using single-nucleotide polymorphisms (SNPs). Most T2D risk prediction models have used SNPs in combination with demographic variables. However, it is difficult to evaluate the pure additive contribution of genetic variants to classically used demographic models. Since prediction models include some heritable traits, such as body mass index, the contribution of SNPs using unmatched case-control samples may be underestimated. In this article, we propose a method that uses propensity score matching to avoid underestimation by matching case and control samples, thereby determining the pure additive contribution of SNPs. To illustrate the proposed propensity score matching method, we used SNP data from the Korea Association Resources project and reported SNPs from the genome-wide association study catalog. We selected various SNP sets via stepwise logistic regression (SLR), least absolute shrinkage and selection operator (LASSO), and the elastic-net (EN) algorithm. Using these SNP sets, we made predictions using SLR, LASSO, and EN as logistic regression modeling techniques. The accuracy of the predictions was compared in terms of area under the receiver operating characteristic curve (AUC). The contribution of SNPs to T2D was evaluated by the difference in the AUC between models using only demographic variables and models that included the SNPs. The largest difference among our models showed that the AUC of the model using genetic variants with demographic variables could be 0.107 higher than that of the corresponding model using only demographic variables.