• The KIPS Transactions:PartA
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• v.14A no.4
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• pp.245-248
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• 2007

This paper provides some simple recursive formulas generation transition functions of finite cellular automata with triplet local transition functions under two states (0 and 1) and four different boundary conditions (0-0,0-1,1-0,1-1), and classify transition functions into several classes.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.438-438
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• 2010

The abnormal behavior of the argon metastable density during the E-H mode transition in argon ICP discharge was investigated. Lots of investigations including global models expected that during and after the mode transition of ICP discharge, the density of metastable increases with applied rf power (i.e. electron density). However, recent direct measurement of metastable density revealed that the metastable density of argon decreases with the applied power during and after the mode transition. This result may not be explained by the previous global model which is based on the assumption of the Maxwellian electron energy distribution function (EEDF). In this paper, to explain this abnormal behavior with simple manners, a simple global model taking account of the effect of the non-Maxwellian EEDFs incorporating into a set of coupled rate equations is proposed. The result showed that the calculated metastable density taking account of non-Maxwellian EEDF and its evolution during the transition has an abnormal behavior with electron density and is in good agreement with the previous measurement results, indicating the close coupling of electron kinetics and the behavior of metastable density. The proposed simple model is expected to provide qualitative kinetic insight to understand the behavior of the metastable density in various plasma discharges which typically exhibit non-Maxwellian distribution.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.5
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• pp.187-192
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• 2019

Majority problem and synchronization problem on cellular automata(CA) are hard to solve, since they are global problems while CA operate on local information. This paper proposes a way to find state transition rules of these problems. The rules of CA are represented as CMR(conditionally matching rules) and evolutionary algorithms are applied to find rules. We find many solution rules to these problems, compared the results with the previous studies, and demonstrated the effectiveness of CMR on one-dimensional cellular automata.

• Nuclear Engineering and Technology
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• v.20 no.3
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• pp.145-154
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• 1988

This paper is a study on an accurate and computationally efficient method for reconstructing pointwise power distributions from coarse-mesh nodal calculations. The modern nodal codes can calculate global reactor power shapes and criticality very efficiently and accurately. But inherent in the nodal procedures, there is inevitable loss of information on local heterogeneous quantities. In this study, an improved form function method which reflects the exponential transition of the thermal flux near the assembly surface is developed for the reconstruction of the heterogeneous fluxes. Use of the new form function method in several pressurized water reactor (PWR) benchmark problems reduces the maximum errors in the reconstructed thermal flux to those in the reconstructed fast flux. Even for assemblies adjacent to the steel baffle in realistic PWR cores, use of this method also results in improved pointwise power reconstruction.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10a
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• pp.124-140
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• 1995

The merit of fuzzy rule based systems stems from their capability of encoding qualitative knowledge of experts into quantitative rules. Recent advancement in automatic tuning or self-organization of fuzzy rules from experimental data further enhances their power, allowing the integration of the top-down encoding of knowledge with the bottom-up learning of rules. In this paper, methods of self-organizing fuzzy rules and of performing defuzzification and inference is presented based on a multi-resolution radial basis function network. The network learns an arbitrary input-output mapping from sample distribution as the union of hyper-ellipsoidal clusters of various locations, sizes and shapes. The hyper-ellipsoidal clusters, representing fuzzy rules, are self-organized based of global competition in such a way as to ensute uniform mapping errors. The cooperative interpolation among the multiple clusters associated with a mapping allows the network to perform a bidirectional many-to-many mapping, representing a particular from of defuzzification. Finally, an inference engine is constructed for the network to search for an optimal chain of rules or situation transitions under the constraint of transition feasibilities imposed by the learned mapping. Applications of the proposed network to skill acquisition are shown.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.855-862
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• 1998

This paper investigates the impact of the forecast error on performance of a reservoir system for hydropower production. Forecast error is measured as th Root Mean Square Error (RMSE) and parametrically varied within a Generalized Maintenance Of Variance Extension (GMOVE) procedure. A set of transition probabilities are calculated as a function of the RMSE of the GMOVE procedure and then incorporated into a Bayesian Stochastic Dynamic Programming model which derives monthly operating policies and assesses their performance. As a case study, the proposed methodology is applied to the Skagit Hydropower System (SHS) in Washington state. The results show that the system performance is a nonlinear function of RMSE and therefor suggested that continued improvements in the current forecast accuracy correspond to gradually greater increase in performance of the SHS.

• Advances in aircraft and spacecraft science
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• v.4 no.6
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• pp.613-637
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• 2017

The development systems for the Structural Health Monitoring has attracted considerable interest from several engineering fields during the last decades and more specifically in the aerospace one. In fact, the introduction of those systems could allow the transition of the maintenance strategy from a scheduled basis to a condition-based approach providing cost benefits for the companies. The research presented in this paper consists of a definition and next comparison of four methods applied to numerical measurements for the extraction of damage features. The first method is based on the determination of the Structural Intensity field at the on-resonance condition in order to acquire information about the dissipation of vibrational energy throughout the structure. The Damage Quantification Indicator and the Average Integrated Global Amplitude Criterion methods need the evaluation of the Frequency Response Function for a healthy plate and a damaged one. The main difference between these two parameters is their mathematical definition and therefore the accuracy of the scalar values provided as output. The fourth and last method is based on the Mode-shape Curvature, a FRF-based technique which requires the application of particular finite-difference schemes for the derivation of the curvature of the plate. All the methods have been assessed for several damage conditions (the shape, the extension and the intensity of the damage) on two test plates: an isotropic (steel) plate and a 4-plies composite plate.

• Journal of the Korean institute of surface engineering
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• v.56 no.1
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• pp.12-39
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• 2023

Diseases caused by air pollution and abnormal climate are occurring worldwide due to global warming. Accordingly, the international community has established a strategy to respond to climate change, and major countries have shifted their economic policies to eco-friendly industries. In this study, we investigate the current status of the renewable energy industry and that of responses to carbon neutrality and PM2.5 (air pollution) in the three major Northeast Asian countries of Japan, Korea, and China, covering changes in the corporate perceptions of Environment, Social, Governance and RE100. In more detail, the three major Northeast Asian countries, referred to as the climate villains in the international community, explain the importance of successful entry into the electric vehicles (EV) industry for a rapid transition to an eco-friendly industry. Moreover, we study the application of lightweight materials for vehicles to improve mileage in the EV industry and technical problems to be solved in the future.

• Computers and Concrete
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• v.19 no.4
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• pp.419-427
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• 2017

With the rising global environmental awareness on energy saving and carbon reduction, as well as the environmental transition and natural disasters resulted from the greenhouse effect, waste resources should be efficiently used to save environmental space and achieve environmental protection principle of "sustainable development and recycling". This study used recycled cement mortar and adopted the volumetric method for experimental design, which replaced cement (0%, 10%, 20%, 30%) with recycled materials (fly ash, slag, glass powder) to test compressive strength and ultrasonic pulse velocity (UPV). The hyperbolic function for nonlinear multivariate regression analysis was used to build prediction models, in order to study the effect of different recycled material addition levels (the function of $R_m$(F, S, G) was used and be a representative of the content of recycled materials, such as fly ash, slag and glass) on the compressive strength and UPV of cement mortar. The calculated results are in accordance with laboratory-measured data, which are the mortar compressive strength and UPV of various mix proportions. From the comparison between the prediction analysis values and test results, the coefficient of determination $R^2$ and MAPE (mean absolute percentage error) value of compressive strength are 0.970-0.988 and 5.57-8.84%, respectively. Furthermore, the $R^2$ and MAPE values for UPV are 0.960-0.987 and 1.52-1.74%, respectively. All of the $R^2$ and MAPE values are closely to 1.0 and less than 10%, respectively. Thus, the prediction models established in this study have excellent predictive ability of compressive strength and UPV for recycled materials applied in cement mortar.

• Journal of Radiation Protection and Research
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• v.38 no.4
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• pp.166-171
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• 2013

While high-dose ionizing radiation results in long term cellular cytotoxicity, chronic low-dose (<0.2 Gy) of X- or ${\gamma}$-ray irradiation can be beneficial to living organisms by inducing radiation hormesis, stimulating immune function, and adaptive responses. During chronic low-dose-rate radiation (LDR) exposure, whole body of mice is exposed to radiation, however, it remains unclear if LDR causes changes in gene expression of the whole brain. Therefore, we aim to investigate expressed genes (EGs) and signaling pathways specifically regulated by LDR-irradiation ($^{137}Cs$, a cumulative dose of 1.7 Gy for total 100 days) in the whole brain. Using microarray analysis of whole brain RNA extracts harvested from ICR and AKR/J mice after LDR-irradiation, we discovered that two mice strains displayed distinct gene regulation patterns upon LDR-irradiation. In ICR mice, genes involved in ion transport, transition metal ion transport, and developmental cell growth were turned on while, in AKR/J mice, genes involved in sensory perception, cognition, olfactory transduction, G-protein coupled receptor pathways, inflammatory response, proteolysis, and base excision repair were found to be affected by LDR. We validated LDR-sensitive EGs by qPCR and confirmed specific upregulation of S100a7a, Olfr624, and Gm4868 genes in AKR/J mice whole brain. Therefore, our data provide the first report of genetic changes regulated by LDR in the mouse whole brain, which may affect several aspects of brain function.