• Korean Chemical Engineering Research
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• v.50 no.3
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• pp.479-491
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• 2012

In this paper we performed evaluation of the economics of a district heating system (DHS) consisting of energy suppliers and consumers, heat generation and storage facilities and power transmission lines in the capital region, as well as identification of optimal operating conditions. The optimization problem is formulated as a mixed integer linear programming (MILP) problem where the objective is to minimize the overall operating cost of DHS while satisfying heat demand during 1 week and operating limits on DHS facilities. This paper also propose a new forecasting model of the system marginal price (SMP) using past data on power supply and demand as well as past cost data. In the optimization, both the forecasted SMP and actual SMP are used and the results are analyzed. The salient feature of the proposed approach is that it exhibits excellent predicting performance to give improved energy efficiency in the integrated DHS.

• Journal of Korea Water Resources Association
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• v.34 no.6
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• pp.617-625
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• 2001

Peace dam constructed against the water attack had stopped in the first step, linked with Hwacheon dam through bypass tunnels and had an effect of flood surcharging in its pocket on Hwacheon dam downstream. To study the utility of Peace dam, the flood control effects of Peace dam and the restricted water level (RWL) in Hwacheon dam were reviewed and identified with operating Hwacheon dam system. Analysing the results the ideas of expanding the usability of the water resources in Hwacheon dam system were suggested. To do that, the criteria and the model of reservoir operation were established frist and the optimization of the operation have done. Based on the results the performance of the optimization was evaluated as an reference coefficient with relative value of the registered data to the optimized. And examining several alternatives for the RWL in Hwacheon reservoir operation made more feasible RWL suggested. And its economic benefit was also reckoned.

• Journal of Information Technology Services
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• v.21 no.2
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• pp.97-107
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• 2022

Recently, interest in smart factories is increasing. Investments to improve intelligence/automation are also being made continuously in manufacturing plants. Facility automation based on sensor data collection is now essential. In addition, we are operating our factories based on data generated in all areas of production, including production management, facility operation, and quality management, and an integrated standard information system. When producing LCD polarizer products, it is most important to link trace information between data generated by individual production processes. All systems involved in production must ensure that there is no data loss and data integrity is ensured. The large-capacity data collected from individual systems is composed of key values linked to each other. A real-time quality analysis processing system based on connected integrated system data is required. In this study, large-capacity data collection, storage, integration and loss prevention methods were presented for optimization of LCD polarizer production. The identification Risk model of inspection products can be added, and the applicable product model is designed to be continuously expanded. A quality inspection and analysis system that maximizes the yield rate was designed by using the final inspection image of the product using big data technology. In the case of products that are predefined as analysable products, it is designed to be verified with the big data knn analysis model, and individual analysis results are continuously applied to the actual production site to operate in a virtuous cycle structure. Production Optimization was performed by applying it to the currently produced LCD polarizer production line.

• Journal of the Korea institute for structural maintenance and inspection
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• v.7 no.4
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• pp.121-128
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• 2003

In recent years, various artificial neural network algorithms are used in the damage assessment of civil infrastructures. So far, many researchers have used the artificial neural network as a pattern classifier for the structural damage assessment but, in this paper, the neural network is used as a structural reanalysis tool not as a pattern classifier. For the model updating using the optimization algorithm, the summation of the absolute differences in the structural vibration modes between undamaged structures and damaged ones is considered as an objective function. The stiffness of structural components are treated as unknown parameters to be determined. The structural damage detection is achieved using model updating based on the optimization techniques which determine the estimated stiffness of components minimizing the objective function. For the verification of the proposed damage identification algorithm, it is numerically applied to a simply supported bridge model.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.4
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• pp.231-238
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• 2014

In the buildings, the systems of structures are influenced by the gravity load changes due to room alteration or construction stage. This paper proposes a system identification method establishing mass as well as stiffness to parameters in model updating process considering mass change in the buildings. In this proposed method, modified genetic algorithm, which is optimization technique, is applied to search those parameters while minimizing the difference of dynamic characteristics between measurement and FE model. To search more global solution, the proposed modified genetic algorithm searches in the wider search space. It is verified that the proposed method identifies the system of structure appropriately through the analytical study on a steel beam structure in the building. The comparison for performance of modified genetic algorithm and existing simple genetic algorithm is carried out. Furthermore, the existing model updating method neglecting mass change is performed to compare with the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.46-51
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• 2004

his paper presents a novel design technique for the TS fuzzy classifier via linear matrix inequalities(LMI). To design the TS fuzzy classifier built by the TS fuzzy model, the consequent parameters are determined to maximize the classifier's performance. Differ from the conventional fuzzy classifier design techniques, convex optimization technique is used to resolve the determination problem. Consequent parameter identification problems are first reformulated to the convex optimization problem. The convex optimization problem is then efficiently solved by converting linear matrix inequality problems. The TS fuzzy classifier has the optimal consequent parameter via the proposed design procedure in sense of the minimum classification error. Simulations are given to evaluate the proposed fuzzy classifier; Iris data classification and Wisconsin Breast Cancer Database data classification. Finally, simulation results show the utility of the integrated linear matrix inequalities approach to design of the TS fuzzy classifier.

• BMB Reports
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• v.54 no.1
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• pp.59-69
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• 2021

The ability to read, write, and edit genomic information in living organisms can have a profound impact on research, health, economic, and environmental issues. The CRISPR/Cas system, recently discovered as an adaptive immune system in prokaryotes, has revolutionized the ease and throughput of genome editing in mammalian cells and has proved itself indispensable to the engineering of immune cells and identification of novel immune mechanisms. In this review, we summarize the CRISPR/Cas9 system and the history of its discovery and optimization. We then focus on engineering T cells and other types of immune cells, with emphasis on therapeutic applications. Last, we describe the different modifications of Cas9 and their recent applications in the genome-wide screening of immune cells.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.2
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• pp.62-69
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• 2014

The capability and cost effectiveness of UUV and USV bring to underwater survey, target detection and identification operations have been widely demonstrated and accepted in recent years. Future USV systems may deploy UUVs to gain the advantage of higher area coverage rates through multiple and simultaneous operations. In this paper, we present an architecture of USV and UUV for mine countermeasure with results of measures on effectiveness.

• 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.575-581
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• 1998

The noise sources in the outdoor unit of RAC(Room Air Conditioner) are identified by the sound intensity method. The main noise sources are compressor noise and fluid noise which is caused by the fan, heat exchanger and shroud. First, the fluid noise is reduced through the design ol new fan and shroud with high flow rate and low noise, reduction of the system resistance by rearrangement of heat exchanger, and optimization of the complex parameter between the fan and shroud. Next, in order to reduce the compressor noise, the new shape of compressor mount and sound-proof material was applied. As a result, the overall noise was reduced by 4-5dB(A).