• The Journal of Information Systems
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• v.13 no.2
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• pp.22-48
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• 2004

Information systems that are not used cannot be useful. In order to increase user acceptance, it is necessary to understand why people accept or reject information systems. Technology Acceptance Model(TAM) is one of the most influential research models for studying determinants how users accept information systems. Recently, Knowledge Management Systems(KMS) have become important components of corporate systems as the foundation of industrialized economics has shifted from natural resources to knowledge assets. This paper applies TAM to investigate users' acceptance of KMS in public administration institutions. It sampled 182 users who had experience in using KMS. Many empirical researches have suggested that TAM can be integrated with other organizational theories to improve its predictive and explanatory ower. We extended the basic TAM by the integration of appraisal and reward satisfaction theory. There are many external variables that influence the perception and the belief of system users. We introduced two external variables(job characteristics, IT self-efficacy) and one additional perception variable, perceived appraisal and reward(PAR) in the basic TAM model. The LISREL model analysis is used for finding out the causality among variables and testing the model fitness. As result, The IT self-efficacy influences to the perceived ease of use(PEOU) and the PAR, and the PEOU influences directly to the perceived usefulness(PU), the PAR, and the attitude toward KMS. The KMS participation intention(PI) was influenced by the PAR and the attitude directly,andbythePEOUindirectly. Finally, this paper suggests some guidelines for the adoption of KMS in public sectors on the basis of the study results.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.1
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• pp.15-26
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• 2022

3D open-field farm model developed from UAV (Unmanned Aerial Vehicle) data could make crop monitoring easier, also could be an important dataset for various fields like remote sensing or precision agriculture. It is essential to separate crops from the non-crop area because labeling in a manual way is extremely laborious and not appropriate for continuous monitoring. We, therefore, made a 3D open-field farm model based on UAV images and developed a crop segmentation model using a supervised machine learning algorithm. We compared performances from various models using different data features like color or geographic coordinates, and two supervised learning algorithms which are SVM (Support Vector Machine) and KNN (K-Nearest Neighbors). The best approach was trained with 2-dimensional data, ExGR (Excess of Green minus Excess of Red) and z coordinate value, using KNN algorithm, whose accuracy, precision, recall, F1 score was 97.85, 96.51, 88.54, 92.35% respectively. Also, we compared our model performance with similar previous work. Our approach showed slightly better accuracy, and it detected the actual crop better than the previous approach, while it also classified actual non-crop points (e.g. weeds) as crops.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.4
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• pp.169-176
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• 2000

Longitudinal and lateral forces acting on tires are known to be closely related to the tract-ability braking characteristics handling stability and maneuverability of ground vehicles. In thie paper in order to develop tire force monitoring systems a monitoring model is proposed utilizing not only the vehicle dynamics but also the roll motion. Based on the monitoring model three monitoring systems are developed to estimate the tire force acting on each tire. Two monitoring systems are designed utilizing the conventional estimation techniques such as SMO(Sliding Mode Observer) and EKF(Extended Kalman Filter). An additional monitoring system is designed based on a new SKFMEC(Scaled Kalman Filter with Model Error Compensator) technique which is developed to improve the performance of EKF method. Tire force estimation performance of the three monitoring systems is compared in the Matlab simulations where true tire force data is generated from a 14 DOF vehicle model with the combined-slip Magic Formula tire model. The built in our Lab. simulation results show that the SKFMEC method gives the best performance when the driving and road conditions are perturbed.

• Journal of Applied Reliability
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• v.17 no.4
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• pp.296-304
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• 2017

Purpose: Recent weapon systems in defense have increased the complexity and importance of software when developing multifunctional equipment. In this study, we analyze the accuracy of the proposed software reliability model when applied to weapon systems. Methods: Determine the similarity between software reliability analysis results (prediction/estimation) utilizing data from developing weapon systems and system failures data during operation of weapon systems. Results: In case of a software reliability prediction model, the predicted failure rate was higher than the actual failure rate, and the estimation model was consistent with actual failure history data. Conclusion: The software prediction model needs to adjust the variables that are appropriate for the domestic weapon system environment. As the reliability of software is increasingly important in the defense industry, continuous efforts are needed to ensure accurate reliability analysis in the development of weapon systems.

• Water Engineering Research
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• v.3 no.2
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• pp.123-134
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• 2002

A developed Quantitative Flood Forecasting (QFF) model was applied to the mid-Atlantic region of the United States. The model incorporated the evolving structure and frequency of intense weather systems of the study area for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters associated with synoptic atmospheric conditions as Input. Here, we present results from the application of the Quantitative Flood Forecasting (QFF) model in 2 small watersheds along the leeward side of the Appalachian Mountains in the mid-Atlantic region. Threat scores consistently above 0.6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 40% and up to 55 % were obtained.

• Journal of the Korean Society of Systems Engineering
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• v.8 no.1
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• pp.1-7
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• 2012

This research aims to propose a model to estimate the appropriate SE Cost rate to the total project cost when systems engineering applied to light rail transit project. In this research an investment cost estimation model is proposed with reference to COSYSMO (Constructive System Engineering Cost Model). This model includes four input factors such as requirement numbers, interface numbers, algorithm numbers, and scenario numbers. When 2600 requirement numbers are considered on a proposal document with 350 pages in a light rail transit specification of 500 billion~trillion won scale, COSYSMO demo version estimates 42.5 billion won of SE cost (about 5% of total project cost or about 10% of E&M cost).

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1669-1674
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• 2004

In this paper, a nonlinear information filter (IF) for curvilinear motions in an interacting multiple model (IMM) algorithm to track a maneuvering vehicle on a road is investigated. Driving patterns of vehicles on a road are modeled as stochastic hybrid systems. In order to track the maneuvering vehicles, two kinematic models are derived: A constant velocity model for linear motions and a constant-speed turn model for curvilinear motions. For the constant-speed turn model, a nonlinear IF is used in place of the extended Kalman filter in nonlinear systems. The suggested algorithm reduces the root mean squares error for linear motions and rapidly detects possible turning motions.

• International Journal of Quality Innovation
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• v.9 no.3
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• pp.1-14
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• 2008

Patient satisfaction with the Emergency Department(ED) in a hospital is related to the length of stay, and especially to the amount of waiting time for medical treatments. ED overcrowding decreases quality and efficiency, therefore affecting hospitals' profitability. This paper presents a forecasting and simulation model for resource management of the ED at Moses H. Cone Memorial Hospital. A linear regression forecasting model is proposed to predict the number of ED patient arrivals, and then a simulation model is provided to estimate the length of stay of ED patients, system throughput, and the utilization of resources such as triage nurses, patient beds, registered nurses, and medical doctors. The near future load level of each resource is presented using the proposed models.

• The Journal of Information Systems
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• v.17 no.2
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• pp.73-94
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• 2008

Knowledge is a fundamental assets, therefore, the ability to create, acquire, integrate, and share knowledge has emerged as a fundamental organizational capability(Sambamurthy and Subramani, 2005). This apaper reports the results of an empirical study investigating the factors of acceptance and the moderating role of resistance in Knowledge Management Systems(KMS). The research model is based on the theory of planned behavior(TPB) and technology acceptance model(TAM). It includes the perceived usefulness instead of attitude, subjective norm, perceived behavior control and intention of acceptance of KMS. Also, three external variables namely task-technology fit, organizational support, and perceived rewards are added. In the research model, all hypothrses of the baseline model and the moderating effects of resistance were found to be significant. The authors also of fred several implications based chi the findings.

• 시스템엔지니어링워크숍
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• s.4
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• pp.151-154
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• 2004

This paper presents the general system theory and its applications to the safety analysis method that is a recent trend over the traditional event-driven model. This new model is known as STAMP(Systems Theory Accident Modeling and Process)proposed by Nancy G. Leveson in MIT. The new model has benefits of systemic approaches concerning the system safety as a whole including the context it is in, its stimulants and outcomes, and its parts as well as the relationships among them in a holistic manner. The method consists of a hierarchical control structure, a process model, and the safety constraints governing the control. This paper demonstrates an example the contrasts the differences between the approaches of STAMP and the traditional safety models.