• Journal of the Korean Society of Safety
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• v.29 no.6
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• pp.76-80
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• 2014

The flash point is one of the most important physical properties used to determine the fire hazard of flammable liquid mixture and defined as the lowest temperature at which a liquid produces sufficient vapor to form a combustible mixture with air. The main purpose of this paper is to measure and predict the flash point of binary flammable miscible mixtures. The flash points for n-hexanol+n-butyric acid and n-butanol+propionic acid, were measured by using Seta-flash closed cup method. The experimentally derived data were correlated with the binary interaction parameters of the van Laar and NRTL equations through the optimization method. The flash points estimated by these correlations were compared with those calculated by the method based on Raoult's law. The optimization method were found to be better than the method based on the Raoult's law.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1064_1065
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• 2009

PV (Photovoltaic) power generation system has been widely studied as a clean and renewable power source. Tracking the MPP (maximum power point) of a PV array is usually an essential part of a PV system. This paper describes POS (Photovoltaic Output Sensorless) MPPT method and optimization technique of its operational characteristics for grid-connected PV generation system. A DC-DC converter has been used to step-up the PV voltage and DC-AC converter has been used for connecting the system to the grid. Optimization technique has been implemented to optimize the current and voltage controller gain parameters and duty ratio increment of DC-DC converter. Simulation results reveal that the proposed control has better response.

• Biomolecules & Therapeutics
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• v.23 no.6
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• pp.493-509
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• 2015

Antibody-drug conjugates utilize the antibody as a delivery vehicle for highly potent cytotoxic molecules with specificity for tumor-associated antigens for cancer therapy. Critical parameters that govern successful antibody-drug conjugate development for clinical use include the selection of the tumor target antigen, the antibody against the target, the cytotoxic molecule, the linker bridging the cytotoxic molecule and the antibody, and the conjugation chemistry used for the attachment of the cytotoxic molecule to the antibody. Advancements in these core antibody-drug conjugate technology are reflected by recent approval of Adectris$^{(R)}$(anti-CD30-drug conjugate) and Kadcyla$^{(R)}$(anti-HER2 drug conjugate). The potential approval of an anti-CD22 conjugate and promising new clinical data for anti-CD19 and anti-CD33 conjugates are additional advancements. Enrichment of antibody-drug conjugates with newly developed potent cytotoxic molecules and linkers are also in the pipeline for various tumor targets. However, the complexity of antibody-drug conjugate components, conjugation methods, and off-target toxicities still pose challenges for the strategic design of antibody-drug conjugates to achieve their fullest therapeutic potential. This review will discuss the emergence of clinical antibody-drug conjugates, current trends in optimization strategies, and recent study results for antibody-drug conjugates that have incorporated the latest optimization strategies. Future challenges and perspectives toward making antibody-drug conjugates more amendable for broader disease indications are also discussed.

• Journal of Mechanical Science and Technology
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• v.19 no.3
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• pp.768-777
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• 2005

This paper shows that the performance of a nonlinear fluid engine mount can be improved by an optimal design process. The property of a hydraulic mount with inertia track and decoupler differs according to the disturbance frequency range. Since the excitation amplitude is large at low excitation frequency range and is small at high excitation frequency range, mathematical model of the mount can be divided into two linear models. One is a low frequency model and the other is a high frequency model. The combination of the two models is very useful in the analysis of the mount and is used for the first time in the optimization of an engine mount in this paper. Normally, the design of a fluid mount is based on a trial and error approach in industry because there are many design parameters. In this study, a nonlinear mount was optimized to minimize the transmissibilities of the mount at the notch and the resonance frequencies for low and high-frequency models by a popular optimization technique of sequential quadratic programming (SQP) supported by $MATLAB^{(R)}$subroutine. The results show that the performance of the mount can be greatly improved for the low and high frequencies ranges by the optimization method.

• Journal of Environmental Impact Assessment
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• v.15 no.6
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• pp.435-441
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• 2006

For the calibration of rainfall-runoff model, automatic calibration methods are used instead of manual calibration to obtain the reliable modeling results. When mathematical programming techniques such as linear programming and nonlinear programming are applied, there is a possibility to arrive at the local optimum. To solve this problem, genetic algorithm is introduced in this study. It is very simple and easy to understand but also applicable to any complicated mathematical problem, and it can find out the global optimum solution effectively. The objective of this study is to develope a parameter optimization program that integrate a genetic algorithm and a rainfall-runoff model. The program can calibrate the various parameters related to the runoff process automatically. As a rainfall-runoff model, SWMM is applied. The automatic calibration program developed in this study is applied to the Jangcheon watershed flowing into the Youngrang Lake that is in the eutrophic state. Runoff surveys were carried out for two storm events on the Jangcheon watershed. The peak flow and runoff volume estimated by the calibrated model with the survey data shows good agreement with the observed values.

• Earthquakes and Structures
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• v.11 no.4
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• pp.701-721
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• 2016

Base isolation is a well-established passive strategy for seismic response control of buildings. In this paper, an efficient framework is proposed for reliability-based design optimization (RBDO) of isolated buildings subjected to uncertain earthquakes. The framework uses reduced function evaluations method, as an efficient tool for structural reliability analysis, and an efficient optimization algorithm for optimal structural design. The probability of failure is calculated considering excessive base displacement, superstructure inter-storey drifts, member stress ratios and absolute accelerations of floors of the isolated building as failure events. The behavior of rubber bearing isolators is modeled using nonlinear hysteretic model and the variability of future earthquakes is modeled by applying a probabilistic approach. The effects of pulse component of stochastic near-fault ground motions, fixity-factor of semi-rigid beam-to-column connections, values of isolator parameters, earthquake magnitude and epicentral distance on the performance and safety of semi-rigidly connected base-isolated steel framed buildings are studied. Suitable RBDO examples are solved to illustrate the results of investigations.

• Structural Engineering and Mechanics
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• v.61 no.2
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• pp.283-293
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• 2017

The main contribution of the present paper is to propose an intelligent fuzzy inference system approach for modeling the debonding strength of masonry elements retrofitted with Fiber Reinforced Polymer (FRP). To achieve this, the hybrid of meta-heuristic optimization methods and adaptive-network-based fuzzy inference system (ANFIS) is implemented. In this study, particle swarm optimization with passive congregation (PSOPC) and real coded genetic algorithm (RCGA) are used to determine the best parameters of ANFIS from which better bond strength models in terms of modeling accuracy can be generated. To evaluate the accuracy of the proposed PSOPC-ANFIS and RCGA-ANFIS approaches, the numerical results are compared based on a database from laboratory testing results of 109 sub-assemblages. The statistical evaluation results demonstrate that PSOPC-ANFIS in comparison with ANFIS-RCGA considerably enhances the accuracy of the ANFIS approach. Furthermore, the comparison between the proposed approaches and other soft computing methods indicate that the approaches can effectively predict the debonding strength and that their modeling results outperform those based on the other methods.

• Journal of Microbiology and Biotechnology
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• v.25 no.10
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• pp.1714-1727
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• 2015

This work describes a new strategy for optimal design of Multiplex-PCR primer sequences. The process is based on the Particle Swarm Optimization-Simplex algorithm (Mult-PSOS). Diverging from previous solutions centered on heuristic tools, the Mult-PSOS is selfconfigured because it does not require the definition of the algorithm's initial search parameters. The successful performance of this method was validated in vitro using Multiplex-PCR assays. For this validation, seven gene sequences of the most prevalent bacteria implicated in urinary tract infections were taken as DNA targets. The in vitro tests confirmed the good performance of the Mult-PSOS, with respect to infectious disease diagnosis, in the rapid and efficient selection of the optimal oligonucleotide sequences for Multiplex-PCRs. The predicted sequences allowed the adequate amplification of all amplicons in a single step (with the correct amount of DNA template and primers), reducing significantly the need for trial and error experiments. In addition, owing to its independence from the initial selection of the heuristic constants, the Mult-PSOS can be employed by non-expert users in computational techniques or in primer design problems.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2888-2890
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• 2005

In this paper, we introduce a new structure of fuzzy-neural networks Fuzzy Set-based Polynomial Neural Networks (FSPNN). The two underlying design mechanisms of such networks involve genetic optimization and information granulation. The resulting constructs are Fuzzy Polynomial Neural Networks (FPNN) with fuzzy set-based polynomial neurons (FSPNs) regarded as their generic processing elements. First, we introduce a comprehensive design methodology (viz. a genetic optimization using Genetic Algorithms) to determine the optimal structure of the FSPNNs. This methodology hinges on the extended Group Method of Data Handling (GMDH) and fuzzy set-based rules. It concerns FSPNN-related parameters such as the number of input variables, the order of the polynomial, the number of membership functions, and a collection of a specific subset of input variables realized through the mechanism of genetic optimization. Second, the fuzzy rules used in the networks exploit the notion of information granules defined over systems variables and formed through the process of information granulation. This granulation is realized with the aid of the hard C- Means clustering (HCM). The performance of the network is quantified through experimentation in which we use a number of modeling benchmarks already experimented with in the realm of fuzzy or neurofuzzy modeling.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.181-186
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• 2002

Laser welding application for car body manufacturing has many advantages in the stiffness and the lightness of vehicle, the productivity of assembly line, and the degree of freedom in design. This presentation will express the innovation of car body manufacturing including parameter optimization, process modeling, and system integration. In this application the investment for systems was cut down dramatically by real time switching over the laser path between two welding stations. Points of technical discussion are as follows: optimization of parameters such as laser power, robot speed and trajectory, compact and useful design of jig & fixture to assure welding quality for 3 sheet-layer zinc-coated steel, system integration between 4kW Nd:YAG laser device and the other systems, on-line real time welding quality monitoring system, perfect safety standards for high power laser, minimization of consumption costs such as arc lamp, protective glass for optic, etc. Laser welding has found a place on Hyundai's production plant in conjunction with the startup of mass production of new sports car, and this production system is the result of a collaboration of its engineers. Outer side sheets are joined to inner side sheets by 122 stitch welds totally. And the length is about 2.4meter.