• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.95-103
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• 2016

In a dynamic environment autonomous robots often encounter unexpected situations that the robots have to deal with in order to continue proceeding their mission. We propose an adaptive goal-based model that allows cyber-physical systems (CPS) to update their environmental model and helps them analyze for attainment of their goals from current state using the updated environmental model and its capabilities. Information exchange approach utilizes Human-Agent-Robot-Machine-Sensor (HARMS) model to exchange messages between CPS. Model validation method uses NuSMV, which is one of Model Checking tools, to check whether the system can continue its mission toward the goal in the given environment. We explain a practical set up of the model in a situation in which homogeneous robots that has the same capability work in the same environment.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.1
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• pp.95-105
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• 2019

Evapotranpiration (ET) is one of the important factor in Hydrological cycle and irrigation planning. In this study, temperature-based artificial neural network (ANN) model for daily reference crop ET estimation was developed and compared with reference crop evapotranpiration ($ET_0$) from FAO-56 Penman-Monteith method (FAO-56 PM) and parameter regionalized Hargreaves method. The ANN model was trained and tested for 10 weather stations (5 inland stations and 5 costal stations) and two input climate factors, maximum temperature ($T_{max}$), minimum temperature ($T_{min}$), and extraterrestrial radiation (RA) were used for training and validation of temperature-based ANN model. Monthly reference ET by the ANN model also compared with parameter regionalized Hargreaves method for ANN model applicability evaluation. The ANN model evapotranspiration demonstrated more accordance to FAO-56 PM evapotranspiration than the $ET_0$ from parameter regionalized Hargreaves method(R-Hargreaves). The results of this study proposed that daily reference crop ET estimated by the ANN model could be used in the condition of no sufficient climate data.

• Nuclear Engineering and Technology
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• v.40 no.5
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• pp.365-374
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• 2008

Dependability-critical systems, such as digital instrumentation and control systems in nuclear power plants, necessitate engineering techniques and tools to provide assurances of their safety and reliability. Determining system reliability at the architectural design phase is important since it may guide design decisions and provide crucial information for trade-off analysis and estimating system cost. Despite this, reliability and system engineering remain separate disciplines and engineering processes by which the dependability analysis results may not represent the designed system. In this article we provide an overview and application of our approach to build architecture-based, dynamic system models for dependability-critical systems and then automatically generate dynamic fault trees (DFT) for comprehensive, tool-supported reliability analysis. Specifically, we use the Architectural Analysis and Design Language (AADL) to model the structural, behavioral and failure aspects of the system in a composite architecture model. From the AADL model, we seek to derive the DFT(s) and use Galileo's automated reliability analyses to estimate system reliability. This approach alleviates the dependability engineering - systems engineering knowledge expertise gap, integrates the dependability and system engineering design and development processes and enables a more formal, automated and consistent DFT construction. We illustrate this work using an example based on a dynamic digital feed-water control system for a nuclear reactor.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4684-4705
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• 2019

Collaborative filtering recommender systems are vulnerable to shilling attacks in which malicious users may inject biased profiles to promote or demote a particular item being recommended. To tackle this problem, many robust collaborative recommendation methods have been presented. Unfortunately, the robustness of most methods is improved at the expense of prediction accuracy. In this paper, we construct a robust Bayesian probabilistic matrix factorization model for collaborative filtering recommender systems by incorporating the detection of user anomaly rating behaviors. We first detect the anomaly rating behaviors of users by the modified K-means algorithm and target item identification method to generate an indicator matrix of attack users. Then we incorporate the indicator matrix of attack users to construct a robust Bayesian probabilistic matrix factorization model and based on which a robust collaborative recommendation algorithm is devised. The experimental results on the MovieLens and Netflix datasets show that our model can significantly improve the robustness and recommendation accuracy compared with three baseline methods.

• Journal of the Korean Society of Systems Engineering
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• v.14 no.2
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• pp.24-32
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• 2018

System Complexity one of the most common cause failure of the projects, it leads to a lack of understanding about the functions of the system. Hence, the model is developed for communication and furthermore modeling help analysis, design, and understanding of the system. On the other hand, the text-based specification is useful and easy to develop but is difficult to visualize the physical composition, structure, and behaviour or data exchange of the system. Therefore, it is necessary to transform system description into a diagram which clearly depicts the behaviour of the system as well as the interaction between components. According to the International Atomic Energy Agency (IAEA) Safety Glossary, The safety system is a system important to safety, provided to ensure the safe shutdown of the reactor or the residual heat removal from the reactor core, or to limit the consequences of anticipated operational occurrences and design basis accidents. Core Protection Calculator System (CPCS) in Advanced Power Reactor 1400 (APR 1400) Nuclear Power Plant is a safety critical system. CPCS was developed using systems engineering method focusing on Departure from Nuclear Boiling Ratio (DNBR) calculation. Due to the complexity of the system, many diagrams are needed to minimize the risk of ambiguities and lack of understanding. Using Model-Based Systems Engineering (MBSE) software for modeling the DNBR algorithm were used. These diagrams then serve as the baseline of the reverse engineering process and speeding up the development process. In addition, the use of MBSE ensures that any additional information obtained from auxiliary sources can then be input into the system model, ensuring data consistency.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.74-91
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• 2023

This study provides an in-depth comparison and analysis of various risk assessment models widely used in modern industries, and proposes the most suitable model for risk assessment of offshore wind power in Korea. The assessment models were selected by considering various factors such as the purpose of risk assessment, stakeholder requirements, and characteristics of offshore wind power. We also emphasized the importance of using different risk assessment models in combination in situations of high uncertainty. To systematize the combination of risk assessment models, we used systems engineering which is effective to develop a new system. Systems engineering was used to define the complete, traceable functions from site requirements, and model-based systems engineering was used to manage the design information from requirements to detailed functions in a single model. The developed risk assessment module provide automatic conversion between risk assessment models to enable risk assessment suitable for offshore wind power. The functionality and usability of the offshore wind risk assessment module were verified by the evaluation of three wind power experts.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.2
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• pp.203-212
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• 2024

This paper describes the establishment of defense systems test works architecture model for the efficient operation of an expanded test organization and the provision of standardized test services after the integration of proving grounds in ADD. The system engineering vee model is applied to the defense system test works to define the project management model and the unit-test management model. In order to establish the defense systems test works architecture model, the process flow of test works, artifacts by life cycle, and interrelations between regulations and test works are explained, and Integrated Test Information System for implementation of architecture model is discussed. Through the defense systems test works architecture model presented in this study, it will contribute to quickly responding to the test requirements of complex and diverse defense systems, efficiently managing projects, and providing standardized test services.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.333-334
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• 2006

A novel mathematical modeling in web transport systems for Continuous Annealing Processes (CAP) is proposed. Despite of thermal and weight effects in dynamics of web transport systems, the conventional mathematical model does not consider those effects. Disregard of these effects causes the low manufacturing quality of webs in CAP. In order to improve the manufacturing quality of webs in CAP, moreover, precise tension control is required based on the mathematical model. Therefore, an advanced mathematical model considering thermal and weight effects in CAP should be established. The effectiveness of a novel mathematical model is evaluated by comparing the performances of the PI tension control system based on the proposed mathematical model with that based on the conventional one through the computer simulation.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.24-34
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• 2008

A novel neural network model, termed the standard neural network model (SNNM), similar to the nominal model in linear robust control theory, is suggested to facilitate the synthesis of controllers for delayed (or non-delayed) nonlinear systems composed of neural networks. The model is composed of a linear dynamic system and a bounded static delayed (or non-delayed) nonlinear operator. Based on the global asymptotic stability analysis of SNNMs, Static state-feedback controller and dynamic output feedback controller are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based nonlinear systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Two application examples are given where the SNNMs are employed to synthesize the feedback stabilizing controllers for an SISO nonlinear system modeled by the neural network, and for a chaotic neural network, respectively. Through these examples, it is demonstrated that the SNNM not only makes controller synthesis of neural-network-based systems much easier, but also provides a new approach to the synthesis of the controllers for the other type of nonlinear systems.

• Journal of Communications and Networks
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• v.8 no.2
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• pp.187-193
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• 2006

In this paper, we study the coexistence of orthogonal frequency division multiplexing (OFDM)-based systems beyond 3G (B3G) and point-to-point (P-P) fixed service (FS) microwave systems. The advanced general analytical model derived via a power spectral density (PSD) analysis proposed in this paper has two advantages in comparison with the conventional minimum coupling loss (MCL) method. First, the interfering signal power that appears in the band of a victim system can be easily assessed without a spectrum emission mask. Second, when transmit power is not allocated to some subcarriers overlapping the band of the victim system in order to mitigate B3G OFDM-based systems interference with other systems, the general analytical model can successfully assess the interference from the B3G systems into FS systems, whereas the MCL method incorporating the spectrum emission mask cannot be applied in the presence of the same interference condition. The proposed model can be derived in a closed form and is simply implemented with the help of simulation, and thus the solution can be obtained in significantly reduced time. Through application of the proposed model, coexistence results are analyzed in a co-channel and adjacent channel with respect to guard band and minimum separation distance.