• Journal of Electrical Engineering and Technology
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• 제9권6호
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• pp.1812-1821
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• 2014

Wind has been a rapidly growing renewable power source for the last twenty years. Since wind behavior is chaotic in nature, its forecasting is not easy. At the same time, developing an accurate forecasting method is essential when wind farms are integrated into the power grid. In fact, wind speed forecasting tools can solve issues related to grid stability and reserve allocation. In this paper 30 hours ahead wind speed profile forecast is proposed using Adaptive Wavelet Neural Network (AWNN). The implemented AWNN uses a Mexican hat mother Wavelet, and Morlet Mother Wavelet for seven, eight and nine levels decompositions. For wind speed forecasting, the time series data on wind speed has been gathered from the National Renewable Energy Laboratory (NREL) website. In this work, hourly averaged 10-min wind speed data sets for the year 2004 in the Midwest ISO region (site number 7263) is taken for analysis. Data sets are normalized in the range of [-1, 1] to improve the training performance of forecasting models. Total 8760 samples were taken for this forecasting analysis. After the forecasting phase, statistical parameters are calculated to evaluate system accuracy, comparing different configurations.

• 전력전자학회논문지
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• 제26권6호
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• pp.390-396
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• 2021

Lithium-ion batteries have been designed and used as battery packs with series and parallel combinations that are suitable for use. However, due to its internal electrochemical properties, producing the battery's condition at the same value is impossible for individual cells. In addition, the management of characteristic deviations between individual cells is essential for the safe and efficient use of batteries as aging progresses with the use of batteries. In this work, we propose a method to manage deviation properties and detect abnormal behavior in the configuration of a combined battery pack of these multiple battery cells. The proposed method can separate and detect probabilistic low-frequency information according to statistical information based on Z-score. The verification of the proposed algorithm was validated using experimental results from 10S3P battery packs, and the implemented algorithm based on Z-score was validated as a way to effectively manage multiple individual cell information.

• 한국정밀공학회지
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• 제33권6호
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• pp.499-508
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• 2016

This paper describes a study of performance prediction of an electric propulsion system for multirotor UAVs. The electric propulsion system consists of motors, propellers, batteries and speed controllers, and significantly affects performance characteristics of the platform. The performance of the electric propulsion system for multirotor UAVs was predicted using an analytical model derived from the characteristics of each component, operation experiments and statistical analyses. Ground performance tests and endurance flights were performed to verify the reliability of the proposed performance prediction method. A quadrotor platform was designed to demonstrate the parcel delivery service used in the endurance flight. From the result of verification tests, it was confirmed that the proposed method has a good agreement.

• 제어로봇시스템학회논문지
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• 제20권9호
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• pp.971-976
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• 2014

Haptic device can be a useful rehabilitation tool in balance training. The proposed system is composed of a body-wear smartphone, Phantom Omni(R) device, and its control PC system. Ten young healthy subjects performed balance tasks with different postures during 30 seconds with their eyes closed. An Android program on the smartphone transferred mediolateral (ML) and anteroposterior (AP) tilt angles to the PC system, which can generate haptic command through haptic device. Statistical data analysis was performed using MATLAB(R). COP (Center of Pressure) related indexes were measured to see reduction in body sway. ANOVA showed that haptic device significantly reduced body sway. Intuitive balance guidance could be generated using an economical and small-sized commercial haptic device, making the system efficient.

• 한국정보통신학회논문지
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• 제26권2호
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• pp.321-324
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• 2022

The Korean halibut farming industry suffer from price instability and demand decrease due to various environmental and social issues. It is urgent to predict the appropriate amount of halibut production. However, it is not easy for employments working in the halibut farming industry to handle statistical tools in order to perform the prediction. In this paper, we implemented a Excel-based regression analysis tool that allows users to get a regression analysis result by just entering historical data in a sheet. Our tool will reduce workloads of employments working in the halibut farming industry by enabling them to perform a regression analysis with Excel on-the-fly. This study expect that by using the tool the halibut farming industry cope actively with the real-time change in the industry.

• Nuclear Engineering and Technology
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• 제55권6호
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• pp.2246-2255
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• 2023

Evacuation time estimation (ETE) is crucial for the effective implementation of resident protection measures as well as planning, owing to its applicability to nuclear emergencies. However, as confirmed in the Fukushima case, the ETE performed by nuclear operators does not reflect behavioral features, exposing thus, gaps that are likely to appear in real-world situations. Existing research methods including surveys and interviews have limitations in extracting highly feasible behavioral features. To overcome these limitations, we propose a VR-based immersive experiment system. The VR system realistically simulates nuclear emergencies by structuring existing disasters and human decision processes in response to the disasters. Evacuation behavioral features were quantitatively extracted through the proposed experiment system, and this system was systematically verified by statistical analysis and a comparative study of experimental results based on previous research. In addition, as part of future work, an application method that can simulate multi-level evacuation dynamics was proposed. The proposed experiment system is significant in presenting an innovative methodology for quantitatively extracting human behavioral features that have not been comprehensively studied in evacuation. It is expected that more realistic evacuation behavioral features can be collected through additional experiments and studies of various evacuation factors in the future.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2015년도 전력전자학술대회 논문집
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• pp.15-16
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• 2015

According to 2014 fire statistical yearbook in the National Fire Data System, a main cause of fire is electrical fire except carelessness fire. Joint/contact badness is the one of the main cause of electrical fire. Furthermore, power relays which are used in electric panel board, motor control center and automation controller, are main element of automation system in the industry field. Overload, voltage unbalance and open-phase due to joint/contact badness of terminal make electric accidents or electrical fires. In order to prevent joint/contact badness of terminal, this paper proposes a sensing circuit of chattering, tracking, arc current, voltage unbalance and open-phase etc. Some experimental tests of the proposed apparatus confirm practicality and validity of the theoretical results.

• 한국대기환경학회지
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• 제19권5호
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• pp.595-610
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• 2003

The statistical indexes such as RMSE (Root Mean Square Error), Mean Bias error, and IOA (Index of agreement) are used to evaluate 3 Dimensional wind and temperature fields predicted by operational meteorological model RAMS (Regional Atmospheric Meteorological System) implemented in CARIS (Chemical Accident Response Information System) for the dispersion forecast of hazardous chemicals in case of the chemical accidents in Korea. The operational atmospheric model, RAMS in CARIS are designed to use GDAPS, GTS, and AWS meteorological data obtained from KMA (Korean Meteorological Administration) for the generation of 3-dimensional initial meteorological fields. The predicted meteorological variables such as wind speed, wind direction, temperature, and precipitation amount, during 19 ∼ 23, August 2002, are extracted at the nearest grid point to the meteorological monitoring sites, and validated against the observations located over the Korean peninsula. The results show that Mean bias and Root Mean Square Error are 0.9 (m/s), 1.85 (m/s) for wind speed at 10 m above the ground, respectively, and 1.45 ($^{\circ}C$), 2.82 ($^{\circ}C$) for surface temperature. Of particular interest is the distribution of forecasting error predicted by RAMS with respect to the altitude; relatively smaller error is found in the near-surface atmosphere for wind and temperature fields, while it grows larger as the altitude increases. Overall, some of the overpredictions in comparisons with the observations are detected for wind and temperature fields, whereas relatively small errors are found in the near-surface atmosphere. This discrepancies are partly attributed to the oversimplified spacing of soil, soil contents and initial temperature fields, suggesting some improvement could probably be gained if the sub-grid scale nature of moisture and temperature fields was taken into account. However, IOA values for the wind field (0.62) as well as temperature field (0.78) is greater than the 'good' value criteria (> 0.5) implied by other studies. The good value of IOA along with relatively small wind field error in the near surface atmosphere implies that, on the basis of current meteorological data for initial fields, RAMS has good potentials to be used as a operational meteorological model in predicting the urban or local scale 3-dimensional wind fields for the dispersion forecast in association with hazardous chemical releases in Korea.

• 한국방사성폐기물학회:학술대회논문집
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• 한국방사성폐기물학회 2009년도 학술논문요약집
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• pp.186-186
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• 2009

The characterization strategy of fracture networks are classified into a deterministic or statistical characterization according to the type of required information. A deterministic characterization is most efficient for a sparsely fractured system, while the statistics are sufficient for densely fractured rock. In this study, the ensemble mean and variability of the effective connectivity is systematically analyzed with various density values for different network structures of a power law size distribution. The results of high resolution Monte Carlo analyses show that statistical characteristics can be a necessary information to determine the transport properties of a fracture system when fracture density is greater than a percolation threshold. When the percolation probability (II) approaches unity with increasing fracture density, the effective connectivity of the network can be safely estimated using statistics only (sufficient condition). It is inferred from conditional simulations that deterministic information for main pathways can reduce the uncertainty in estimation of system properties when the network becomes denser. Overall results imply that most pathways need to be identified when II < 0.5 statistics are sufficient when II $\rightarrow$ 1 and statistics are necessary and the identification of main pathways can significantly reduce the uncertainty in estimation of transport properties when 0.5$\ll$1. It is suggested that the proper estimation of the percolation probability of a fracture network is a prerequisite for an appropriate conceptualization and further characterization.

• 대한인간공학회지
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• 제27권1호
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• pp.1-7
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• 2008

Work related musculoskeletal disorders (WMSDs) have become a hot issue within the Korean workplace for the past several years. Recently, the effect of job related stress on WMSDs, cerebro-cardiovascular diseases, and psychiatric disorders has been steadily increasing. The study conducted questionnaire of Korea version job stress model, WMSDs from NIOSH, CES-D (Center for Epidemiologic Studies Depression Scale), and STAI (State-Trait Anxiety Inventory) against train drivers. The results of this study show that the job stress score of the train drivers is high in the areas of physical environment, job latitude, interpersonal conflict, job insecurity, and organization system. The relation between job stress and WMSDs nd, interpersonal conflict, job insecurity and organizational system. The relation between job stress and depressive disorders showed statistical significance in the areas of job demand, job insecurity and low reward. Finally, the relation between job stress and anxiety disorders showed statistical significance in areas of job demand, interpersonal conflict, job insecurity, organizational system and low reward.