• Computers and Concrete
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• v.15 no.1
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• pp.103-126
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• 2015

Thermal effects are significant loads for assessing concrete dam behaviour during operation. A new methodology to estimate thermal loads on concrete dams taking into account processes which were previously unconsidered, such as: the evaporative cooling, the night radiating cooling or the shades, has been recently reported. The application of this novel approach in combination with a three-dimensional finite element method to solve the heat diffusion equation led to a precise characterization of the thermal field inside the dam. However, that approach may be computationally expensive. This paper proposes the use of a new one-dimensional model based on an explicit finite difference scheme which is improved by means of the reported methodology for computing the heat fluxes through the dam faces. The improved model has been applied to a case study where observations from 21 concrete thermometers and data of climatic variables were available. The results are compared with those from: (a) the original one-dimensional finite difference model, (b) the Stucky-Derron classical one-dimensional analytical solution, and (c) a three-dimensional finite element method. The results of the improved model match well with the observed temperatures, in addition they are similar to those obtained with (c) except in the vicinity of the abutments, although this later is a considerably more complex methodology. The improved model have a better performance than the models (a) and (b), whose results present larger error and bias when compared with the recorded data.

• Analytical Science and Technology
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• v.32 no.2
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• pp.35-47
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• 2019

In this study, high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) was employed to detect 26 antidiabetic compounds in adulterated dietary supplements using a simple, selective method. The work presented herein may help prevent incidents related to food adulteration and restrict the illegal food market. The best separation was obtained on a Shiseido Capcell Pak(R) C18 MG-II ($2.0mm{\times}100mm$, $3{\mu}m$), which improved the peak shape and MS detection sensitivity of the target compounds. A gradient elution system composed of 0.1 % (v/v) formic acid in distilled water and methanol at a flow rate of 0.3 mL/min for 18 min was utilized. A triple quadrupole mass spectrometer with an electrospray ionization source operated in the positive or negative mode was employed as the detector. The developed method was validated as follows: specificity was confirmed in the multiple reaction monitoring mode using the precursor and product ion pairs. For solid samples, LOD ranged from 0.16 to 20.00 ng/mL and LOQ ranged from 0.50 to 60.00 ng/mL, and for liquid samples, LOD ranged from 0.16 to 20.00 ng/mL and LOQ ranged from 0.50 to 60.00 ng/mL. Satisfactory linearity was obtained from calibration curves, with $R^2$ > 0.99. Both intra and inter-day precision were less than 13.19 %. Accuracies ranged from 80.69 to 118.81 % (intra/inter-day), with a stability of less than 14.88 %. Mean recovery was found to be 80.6-119.0 % and less than 13.4 % RSD. Using the validated method, glibenclamide and pioglitazone were simultaneously determined in one capsule at concentrations of 1.52 and 0.53 mg (per capsule), respectively.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.6
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• pp.415-424
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• 2004

In this paper, we introduce and investigate a new category of rule-based fuzzy inference system based on Information Granulation(IG). The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of “If..., then...” statements, and exploits the theory of system optimization and fuzzy implication rules. The form of the fuzzy rules comes with three types of fuzzy inferences: a simplified one that involves conclusions that are fixed numeric values, a linear one where the conclusion part is viewed as a linear function of inputs, and a regression polynomial one as the extended type of the linear one. By the nature of the rule-based fuzzy systems, these fuzzy models are geared toward capturing relationships between information granules. The form of the information granules themselves becomes an important design features of the fuzzy model. Information granulation with the aid of HCM(Hard C-Means) clustering algorithm hell)s determine the initial parameters of rule-based fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial function being used in the Premise and consequence Part of the fuzzy rules. And then the initial Parameters are tuned (adjusted) effectively with the aid of the improved complex method(ICM) and the standard least square method(LSM). In the sequel, the ICM and LSM lead to fine-tuning of the parameters of premise membership functions and consequent polynomial functions in the rules of fuzzy model. An aggregate objective function with a weighting factor is proposed in order to achieve a balance between performance of the fuzzy model. Numerical examples are included to evaluate the performance of the proposed model. They are also contrasted with the performance of the fuzzy models existing in the literature.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.4
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• pp.199-208
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• 2022

Korean is an agglutinative language, and one or more morphemes are combined to form a single word. Part-of-speech tagging method separates each morpheme from a word and attaches a part-of-speech tag. In this study, we propose a new Korean part-of-speech tagging method based on the Head-Tail tokenization technique that divides a word into a lexical morpheme part and a grammatical morpheme part without decomposing compound words. In this method, the Head-Tail is divided by the syllable boundary without restoring irregular deformation or abbreviated syllables. Korean part-of-speech tagger was implemented using the Head-Tail tokenization and deep learning technique. In order to solve the problem that a large number of complex tags are generated due to the segmented tags and the tagging accuracy is low, we reduced the number of tags to a complex tag composed of large classification tags, and as a result, we improved the tagging accuracy. The performance of the Head-Tail part-of-speech tagger was experimented by using BERT, syllable bigram, and subword bigram embedding, and both syllable bigram and subword bigram embedding showed improvement in performance compared to general BERT. Part-of-speech tagging was performed by integrating the Head-Tail tokenization model and the simplified part-of-speech tagging model, achieving 98.99% word unit accuracy and 99.08% token unit accuracy. As a result of the experiment, it was found that the performance of part-of-speech tagging improved when the maximum token length was limited to twice the number of words.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.701-706
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• 1998

A design method of rule -based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of " IF..., THEN,," statements. using the theories of optimization and linguistic fuzzy implication rules. The improved complex method, which is a powerful auto-tuning algorithm, is used for tuning of parameters of the premise membership functions in consideration of the overall structure of fuzzy rules. The optimized objective function, including the weighting factors, is auto-tuned for better performance of fuzzy model using training data and testing data. According to the adjustment of each weighting factor of training and testing data, we can construct the optimal fuzzy model from the objective function. The least square method is utilized for the identification of optimum consequence parameters. Gas furance and a sewage treatment proce s are used to evaluate the performance of the proposed rule-based fuzzy modeling.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.445-449
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• 2005

Various methods to detect the phytoplankton/red tide blooms in the oceanic waters have been developed and tested on satellite ocean color imagery since the last two and half decades, but accurate detection of blooms with these methods remains challenging in optically complex turbid waters, mainly because of the eventual interference of absorbing and scattering properties of dissolved organic and particulate inorganic matters with these methods. The present study introduces a new method called Red tide Index (Rl), providing indices which behave as a good measure of detecting red tide algal blooms in high scattering and absorbing waters of the Korean South Sea and Yellow Sea. The effectiveness of this method in identifying and locating red tides is compared with the standard Ocean Chlorophyll 4 (OC4) bio-optical algorithm applied to SeaWiFS ocean imagery, acquired during two bloom episodes on 27 March 2002 and 28 September 2003. The result revealed that OC4 bio-optical algorithm falsely identifies red tide blooms in areas abundance in colored dissolved organic and particulate inorganic matter constituents associated with coastal areas, estuaries and river mouths, whereas red tide index provides improved capability of detecting, predicting and monitoring of these blooms in both clear and turbid waters.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.501-503
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• 1999

In this paper, the design method of a hybrid fuzzy controller with an optimal auto-tuning method is proposed. The conventional PID controller becomes so sensitive to the control environments and the change of parameters that the efficiency of its utility for the complex and nonlinear plant has been questioned in transient state. In this paper, first, a hybrid fuzzy logic controller(HFLC) is proposed. The control input of the system in the HFLC is a convex combination by a fuzzy variable of the FLC's output in transient state and the PID's output in steady state. Second, a powerful auto-tuning algorithm is presented to automatically improve the Performance of controller, utilizing the improved complex method and the genetic algorithm. The algorithm estimates automatically the optimal values of scaling factors and PID coefficients. Controllers are applied to the plants with time-delay and the DC servo motor Computer simulations are conducted at the step input and the system performances are evaluated in the ITAE.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.719-722
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• 1998

Fault simulation for large and complex sequential circuits is highly cpu-intensive task in the intergrated circuit design process. In this paper, we propose CM-SIM, a concurrent fault simulator which employs an optimal memory management strategy and simple list operations. CM-SIM removes inefficiencies and uses new dynamic memory management strategies, using contiguous array memory. Consequently, we got improved performance and reduced memory usage in concurrent fault simulation.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2001.10a
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• pp.1-4
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• 2001

Dynamic analysis of laminated beams with a embedded damping layer under tension or compression axial load is investigated. Improved Layer-Wise Zig-Zag Beam Theory and Interdependent Kinematic Relation using the governing equations of motion are incorporated to model the laminated beams with a damping layer and a corresponding beam zig-zag finite element is developed. Flexural frequencies and modal loss actors under tension or compression axial load are calculated based on Complex Eigenvalue Method. The effect of the axial tension and compression load on the frequencies and loss factors is discussed.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.93-98
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• 1991

An improved and flexible matrix algorithm for solving interlinked separation problems which is based on the homotopy continuation method has been developed. A flexible model of the interlinked stream in standardized matrix form and JACOBIAN generation I algorithm for homotopy continuation are suggested. Also DOF analysis is performed for easy-understanding of equation based simulation of complex column systems. The Algorithm is tested on several problems of interlinked separation processes and some of results are documented.