• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.4
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• pp.75-86
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• 2019

Recently, natural disasters due to abnormal climates are frequently outbreaking, and there is rapid increase of damage to aged agricultural infrastructure. As agricultural infrastructure facilities are in contact with water throughout the year and the number of them is significant, it is important to build a maintenance management system. Especially, the current maintenance management system of pumping and drainage stations among the agricultural facilities has the limit of lack of objectivity and management personnel. The purpose of this study is to develop a performance evaluation model using the factors related to performance degradation of pumping and drainage facilities and to predict the performance of the facilities in response to climate change. In this study, we focused on the pumping and drainage stations belonging to each climatic zone separated by the Korea geographical climatic classification system. The performance evaluation model was developed using three different statistical models of POLS, RE, and LASSO. As the result of analysis of statistical models, LASSO was selected for the performance evaluation model as it solved the multicollinearity problem between variables, and showed the smallest MSE. To predict the performance degradation due to climate change, the climate change response variables were classified into three categories: climate exposure, sensitivity, and adaptive capacity. The performance degradation prediction was performed at each facility using the developed performance evaluation model and the climate change response variables.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.241-247
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• 2000

The reference model of an MRC (model reference control) provides the desired trajectory a plant should follow and thus the design of a reference model has a significant effect on control performance. In most control systems control input to a plant has some bounds and it is preferable to make use of as large control inputs as possible within the range of no saturation. In this paper a new approach of selecting the reference model is proposed for bounded control inputs. Design variables of the reference model are determined in such a way that maximizes the performance index within the range of no saturation. Moreover this variable reference model is regularly updated during control. This scheme is verified by application to the servo motor position control system in various simulations. The responses of the MRC with a variable reference model show better tracking performance than that with a fixed reference mode. Moreover by adjusting the update interval of the reference model the control performance can be further improved.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.1
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• pp.106-123
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• 2019

Demand for performance analysis is increasing for efficient use of limited budgets such as improving investment efficiency and strategic budget allocation in accordance with the continuous increase demand of R&D budget for developing advanced weapon systems in the future battlefields. In accordance with the Act on the Performance Evaluation and Performance Management of the National R&D Projects established in March 2006, the performance analysis has been conducted for the systematic management and utilization of the R&D project performance. It was recognized as a project to achieve self-defense through strengthening the weapons system development capability, however, efficiency evaluation of Defense R&D projects was not much emphasized. Research on the efficiency analysis of defense R&D projects has been conducted in recent years, but most studies focused on corporate efficiency and productivity of defense companies. In this study, we analyzed the three-stage performance of defence R&D projects based on the logical model using the data envelope analysis(DEA) model. We also analyzed performance analysis from various perspectives through R&D type, technology classification and performance model. This study is expected to help defense department improve defense R&D projects and make decision.

• Communications for Statistical Applications and Methods
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• v.30 no.3
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• pp.273-289
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• 2023

In this paper, we develop a new time series model for predicting IPO (initial public offering) data with non-negative integer value. The proposed model is based on integer-valued autoregressive (INAR) model with a Poisson thinning operator. Just as the heterogeneous autoregressive (HAR) model with daily, weekly and monthly averages in a form of cascade, the integer-valued heterogeneous autoregressive (INHAR) model is considered to reflect efficiently the long memory. The parameters of the INHAR model are estimated using the conditional least squares estimate and Yule-Walker estimate. Through simulations, bias and standard error are calculated to compare the performance of the estimates. Effects of model fitting to the Korea's IPO are evaluated using performance measures such as mean square error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE) etc. The results show that INHAR model provides better performance than traditional INAR model. The empirical analysis of the Korea's IPO indicates that our proposed model is efficient in forecasting monthly IPO volumes.

• Korean Journal of Agricultural Science
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• v.45 no.4
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• pp.859-870
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• 2018

Dried red peppers are a staple agricultural product used in Korean cuisine and as such, are an important aspect of agricultural producers' income. Correctly forecasting both their supply and demand situations and price is very important in terms of the producers' income and consumer price stability. The primary objective of this study was to compare the performance of time series forecasting models for dried red peppers in Korea. In this study, three models (an autoregressive model with exogenous variables [ARX], AR-exponential generalized autoregressive conditional heteroscedasticity [EGARCH], and ARX-EGARCH) are presented for forecasting the wholesale price of dried red peppers. As a result of the analysis, it was shown that the ARX model and ARX-EGARCH model, each of which adopt both the rolling window and the adding approach and use the agricultural cooperatives price as the exogenous variable, showed a better forecasting performance compared to the autoregressive model (AR)-EGARCH model. Based on the estimation methods and results, there was no significant difference in the accuracy of the estimation between the rolling window and adding approach. In the case of dried red peppers, there is limitation in building the price forecasting models with a market-structured approach. In this regard, estimating a forecasting model using only price data and identifying the forecast performance can be expected to complement the current pricing forecast model which relies on market shipments.

• The Journal of Information Systems
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• v.32 no.1
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• pp.147-178
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• 2023

Purpose The mail goal of this study is to find out factors influencing users' satisfaction of public application with the emphasis of service quality of public web and public value. For this purpose, we applied IS success model to develop the research model that explains users's satisfaction and public performance. Design/methodology/approach The proposed research model was developed based on IS success model along with two moderating effects - Service Quality of Public Web and Public Value in order to empirically test proposed causal relationships withing the model. A total of 377 survey responses were analyzed by forming the structural equation modeling with AMOS 24.0. Findings The analysis results show that the service, information, and system quality from IS success model are positively associated with user satisfaction, which in turn is positively associated with public app performance. The results also show that the relationship between user satisfaction and public app performance is positively moderated by public value. However, the relationship between public app service quality and user satisfaction isn't moderated by public web service quality.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.54.3-54
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• 2002

$\textbullet$ Introduction $\textbullet$ Token Passing Protocol : Profibus-FMS $\textbullet$ Performance Model of Profibus Token Passing Protocol $\textbullet$ Calculation of Communication Delay in Performance Model $\textbullet$ Summaries and Conclusions

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8753-8759
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• 2015

Establishment of analysis procedures and validated performance measurements for generator output is required to maintain stable management of generator output in turbine power generation cycle. We developed turbine expansion model and measurement validation model for the performance calculation of generator using turbine output based on ASME (American Society of Mechanical Engineers) PTC (Performance Test Code). We also developed verification model for uncertain measurement data related to the turbine and generator output. Although the model in previous researches was developed using artificial neural network and kernel regression, the verification model in this paper was based on algorithms through Support Vector Machine (SVM) model to overcome the problems of unmeasured data. The selection procedures of related variables and data window for verification learning was also developed. The model reveals suitability in the estimation procss as the learning error was in the range of about 1%. The learning model can provide validated estimations for corrective performance analysis of turbine cycle output using the predictions of measurement data loss.

• Journal of Information Technology and Architecture
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• v.10 no.4
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• pp.467-478
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• 2013

The necessity of research for EA service and performance is surfacing while nation-level and individual agency level performances utilizing Government-wide EA information. In this study, performance model for EA service has been developed categorizing characteristic elements of EA as service. And weight differences between quality items that constitute performance model have been calculated using AHP analysis method. To achieve the stated, SERVQUAL applied performance model for EA service has been developed working through logical reasoning and a broad range of theoretical studies concerning EA service. Moreover, relative weight differences between quality items that constitute the model have been calculated. The results of weight analysis find that importance differences between quality items in order of significance are as follows: EA administrator > EA information > EA education > EA policy > EA operating system. This study, as the nation's first research to graft the public-sector EA service onto SERVQUAL Model that is capturing remarkable attention, has considerable practical and theoretical implications.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.37 no.3
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• pp.261-273
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• 2024

This paper is an experimental study on the improvement of smoke and flame detection from different materials with YOLO. For the study, images of fires occurring in various materials were collected through an open dataset, and experiments were conducted by changing the main factors affecting the performance of the fire object detection model, such as the bounding box, polygon, and data augmentation of the collected image open dataset during data preprocessing. To evaluate the model performance, we calculated the values of precision, recall, F1Score, mAP, and FPS for each condition, and compared the performance of each model based on these values. We also analyzed the changes in model performance due to the data preprocessing method to derive the conditions that have the greatest impact on improving the performance of the fire object detection model. The experimental results showed that for the fire object detection model using the YOLOv5s6.0 model, data augmentation that can change the color of the flame, such as saturation, brightness, and exposure, is most effective in improving the performance of the fire object detection model. The real-time fire object detection model developed in this study can be applied to equipment such as existing CCTV, and it is believed that it can contribute to minimizing fire damage by enabling early detection of fires occurring in various materials.