• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.273-275
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• 2006

In this paper, we introduce a new design of fuzzy neural networks using input-output data information of target system. The proposed fuzzy neural networks is constructed by input-output data information and used the center of data distance by HCM clustering to obtain the characteristics of data. A membership function is defined by HCM clustering and is applied input-output dat included each rule to conclusion polynomial functions. We use triangular membership functions and simplified fuzzy inference, linear fuzzy inference, and modified quadratic fuzzy inference in conclusion. In the networks learning, back propagation algorithm of network is used to update the parameters of the network. The proposed model is evaluated with benchmark data.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.552-554
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• 2003

The second harmonic component is commonly used for blocking differential relay in power transformers. However, it is difficult to distinguish between inrush and internal winding fault with differential current protective relaying. This paper proposed a new method using Nuro-Fuzzy System based on HCM(Hard C-Means). The proposed system is more objective and systematic than existing model. The data used in input are 3-phase primary voltage and fundamental harmonic of differential current. Various states of transformer are simulated using BCTRAN and HYSDAT of EMTP. As a result of the application of algorithm in various cases, the exact discrimination between internal winding fault and inrush is performed.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.654-656
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• 1998

This paper presents an optimal identification method of nonlinear and complex system that is based on fuzzy-neural network(FNN). The FNN used simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. And we use a HCM Algorithm to find initial parameters of membership function. And then to obtain optimal parameters, we use the genetic algorithm. Genetic algorithm is a random search algorithm which can find the global optimum without converging to local optimum. The parameters such as membership functions, learning rates and momentum coefficients are easily adjusted using the genetic algorithms. Also, the performance index with weighted value is introduced to achieve a meaningful balance between approximation and generalization abilities of the model. To evaluate the performance of the FNN, we use the time series data for 9as furnace and the sewage treatment process.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.83-86
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• 2015

We present observational results characterizing molecular outflows from very low-mass objects in ${\rho}$ Ophiuchi and Taurus. Our results provide us with important implications that clarify the formation process of very low-mass objects.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.7
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• pp.339-349
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• 2001

This paper suggests an optimal identification method for complex and nonlinear system modeling that is based on Fuzzy-Neural Networks(FNN). The proposed Hybrid Identification Algorithm is based on Yamakawa's FNN and uses the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. In this paper, the FNN modeling implements parameter identification using HCM algorithm and hybrid structure combined with two types of optimization theories for nonlinear systems. We use a HCM(Hard C-Means) clustering algorithm to find initial apexes of membership function. The parameters such as apexes of membership functions, learning rates, and momentum coefficients are adjusted using hybrid algorithm. The proposed hybrid identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregated objective function(performance index) with weighting factor is introduced to achieve a sound balance between approximation and generalization abilities of the model. According to the selection and adjustment of a weighting factor of an aggregate objective function which depends on the number of data and a certain degree of nonlinearity(distribution of I/O data), we show that it is available and effective to design an optimal FNN model structure with mutual balance and dependency between approximation and generalization abilities. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.

• International Journal of Highway Engineering
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• v.17 no.2
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• pp.123-134
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• 2015

PURPOSES : The key point of a multimodal LOS (level-of-service) evaluation system is that all of the modes are mutually associated to determine each mode's LOS. For example, the LOS of the bicycle mode is measured based on not only bicycle volumes, but also automobile volumes. However, the Korea Highway Capacity Manual (KHCM) still focuses on the automobile mode in evaluating the LOS of the roads. Additionally, the KHCM's LOS of the other modes, except for the automobile, is not consistent with actual road conditions. The KHCM, therefore, needs to develop and introduce a multimodal LOS system in order to evaluate the service conditions more accurately. METHODS: As a preliminary step to the introduction of multimodal LOS research, in this study the current problem of the KHCM's LOS system through a close review and comparison with other HCMs (highway capacity manuals) was identified. Secondly, a field survey and investigation of the urban streets to apply the HCM's multimodal LOS system was conducted. Finally, a comparison analysis of the results of the HCM and KHCM LOS was performed. RESULTS: In the study, it was found that the results of the LOS for the automobile mode did not show a significant difference between the HCM and KHCM. However, the LOS of the bicycle and pedestrian mode tended to be worse in the multimodal LOS system, which results from considering the effects of the automobile mode. Moreover, it was found that many cases have the potential to improve the overall LOS conditions, while reducing the automobile capacity. CONCLUSIONS: With the introduction of the multimodal LOS system, road diet and complete streets can be easily applied to ans actual road improvement project. Ultimately, the multimodal LOS system should be introduced into the KHCM, which can then be applied to traffic impact studies and other road improvement projects for more accurate evaluations.

• Korean Journal of Pharmacognosy
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• v.49 no.2
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• pp.182-187
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• 2018

Many plant derived phytochemicals have been considered as the main therapeutic strategy against Alzheimer's disease (AD). AD is a progressive neurodegenerative disorder, and the most predominant cause of dementia in the elderly. Cholinergic deficit, senile plaque/${\beta}$-amyloid ($A{\beta}$) peptide deposition and oxidative stress have been identified as three main pathogenic pathways which contribute to the progression of AD. We screened many different plant species for their effective use in both modern and traditional system of medicines. In this study, we tested that MeOH extract of the stem bark of Hopea chinensis (Merr.) Hand.-Mazz. (HCM) affects on the processing of Amyloid precursor portein (APP) from the APPswe over-expressing Neuro2a cell line. We showed that HCM reduced the secretion level of $A{\beta}42$ and $A{\beta}40$ in a dose dependent manner. We found that HCM increased over 1.5 folds of the secretion level of $sAPP{\alpha}$, a metabolite of ${\alpha}$-secretase. Furthermore, we found that HCM inhibited acetylcholinesterase activity in vitro. We suggest that the stem bark of Hopea chinensis may be a useful source to develop a therapeutics for AD.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.6
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• pp.57-65
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• 2015

Manufacturing optimization problem is to find the optimal solution under satisfying various and complicated constraints with the design variables of nonlinear types. To achieve the objective, this paper proposes a hybrid approach. The proposed hybrid approach is consist of genetic algorithm(GA), cuckoo search(CS) and hill climbing method(HCM). First, the GA is used for global search. Secondly, the CS is adapted to overcome the weakness of GA search. Lastly, the HCM is applied to search precisely the convergence space after the GA and CS search. In experimental comparison, various types of manufacturing optimization problems are used for comparing the efficiency between the proposed hybrid approach and other conventional competing approaches using various measures of performance. The experimental result shows that the proposed hybrid approach outperforms the other conventional competing approaches.

• Journal of Power Electronics
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• v.14 no.6
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• pp.1197-1207
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• 2014

Common-mode voltage (CMV) causes overvoltage stress to winding insulation and damages AC motors. CMV with high dv/dt causes leakage currents, which create noise problems for equipment installed near the converter. This study proposes a new pulse-width modulation (PWM) strategy for three-level T-type NPC inverters. This strategy substantially eliminates CMV. The principle for selecting suitable triangle carrier signals for the three-level T-type NPC is described. The proposed method can mitigate the peak value of CMV by 50% compared with the phase disposition pulse-width modulation method. Furthermore, the proposed method exhibits better harmonic spectrum and lower root mean square value for the CMV than those of the reduced-CMV method on the basis of the phase opposition disposition PWM scheme with modulation index higher than 0.5. The proposed modulation can easily be implemented using software without any additional hardware modifications. Both simulation and experimental results demonstrate that the proposed carrier phase-shift PWM method has good output waveform performance and reduces CMV.

• Journal of IKEEE
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• v.21 no.3
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• pp.309-319
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• 2017

The research investigates the inhibition of fatty acid biosynthesis of the human Acetyl-CoA Carboxylase enzyme by the aromatic-structure inhibitors (also known as ligands) containing variables of substituents, contributing an important role in the treatment of fatty-acid metabolic syndrome expressed by the group of cardiovascular risk factors increasing the incidence of coronary heart disease and type-2 diabetes. The effective interoperability between ligand and enzyme is characterized by a 50% concentration of enzyme inhibitor ($IC_{50}$) which was determined by experiment, and the factor of geometry structure of the ligands which are modeled by quantum mechanical methods using HyperChem 8.0.10 and Gaussian 09W softwares, combining with the calculation of quantum chemical and chemico-physical structural parameters using HyperChem 8.0.10 and Padel Descriptor 2.21 softwares. The result data are processed with the combination of classical statistical methods and modern bioinformatics methods using the statistical softwares of Department of Pharmaceutical Technology - Jadavpur University - India and R v3.3.1 software in order to accomplish a model of the quantitative structure - activity relationship between aromatic-structure ligands inhibiting fatty acid biosynthesis of the human Acetyl-CoA Carboxylase.