• Korean Journal of Construction Engineering and Management
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• v.13 no.3
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• pp.14-24
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• 2012

Recently, a delivery system has been rapidly changed in the global construction market. Also, construction projects are becoming bigger and more technology-intensive. A lot of projects have been delivered by Design-Build(DB) System; from the standpoint of cost, approximately 40% of delivered constructions by a Public Procurement Service were DB in 2009. Nevertheless, the achievement has not surpassed our expectations on management of the project cost. On the characteristic of DB, the reasons why that happens are that projects contract have been signed after the Design Development Stage; the insufficient review about new technology and up-to-date construction methods; a lack of discussion in process of design. Those reasons cause a risk of increasing Cost of the projects. In order to solve these problems, it is desirable to find Cost-increasing factors in promoting the projects and select on the order of priority for Risk-Factor with careful management. Therefore, this study analyzed the weight of each phase of the project on the authority of properties of DB project, and identified Risk-factors which is increasing the cost on the aspect of project management. Based on this analysis, the impact assessment of Risk-factor is evaluated through the Failure Mode and Effect Analysis(FMEA).

• Proceedings of the IEEK Conference
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• 2000.06b
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• pp.213-216
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• 2000

Minimum-cost linear network flow problems could be transformed with equal to assignment problems. Traditional method to solve the linear network flow problems are improved source-cost by transform the simple cycle flow. Auction algorithm could be applied to same element using the initial target price and dispersion calculation. Also, each elements are obtained by $\varepsilon$-relaxation methods. In this paper we proposed; 1)minimum-cost flow problem, 2)minimum-cost flow problem by the mathematical equivalent and 3) extraction $\varepsilon$-relaxation & expand transfer problem with minimum-cost flow. It can be applicant to PCB design by above mentioned.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1270-1272
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• 1999

The generator cost function is one of the basic data for the generation scheduling. Generally the cost functions are obtained form design calculations or from heat rate tests. The real operating condition may be different from the condition of design or the tests. Some of the conditions may not be tested during the periodical maintenance. In order to improve the calculation of the generator cost function, this paper presents a new calculation method of the generator cost functions using the utilization factors of generators and the mixed fuel burning ratio of the generators.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.5
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• pp.369-381
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• 1991

In this paper, design algorithms for SMP(Single Mated Pair) and MMP (Multipli Mated Pair) structure of CCS (Common Channel Signaling) network are proposed through the study of the structure of CCS network. High reliability and fast messagy transfer time are the most important requirements for the CCS network. Based on it, three parameters such as monotraffic, reliability (maximum isolated SP(Signalling Point) number when any two STP(Signalling Transfer Points) fail and total network cost are defined. And the proposed algorithms different from preexisted algorithm that minimizes total network cost, maximize monotraffic with two constraints, reliability and total network cost. Comparing the experimental results of the proposed algorithms with those of the preexisted algorithm that minimizes total network cost, shows that the proposed algorithms produce a more reliable topology that has more monotraffic and a little higher total network cost. Additionaly, with the results of the proposed algorithms, SMP and MMP structures are compared.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.6
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• pp.581-588
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• 2007

In this paper, we propose a delayed feedback guaranteed cost controller design method for linear time-delay systems with norm-bounded parameter uncertainties and nonlinear perturbations. A quadratic cost function is considered as the performance measure for the given system. Based on the Lyapunov method, an LMI optimization problem is formulated to design a controller such that the closed-loop cost function value is not more than a specified upper bound for all admissible system uncertainties and nonlinear perturbations. Numerical example show the effectiveness of the proposed method.

• Proceedings of the Korea Concrete Institute Conference
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• 2004.11a
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• pp.773-776
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• 2004

The so-called Life Cycle Cost (LCC) analysis on reinforced concrete bridge can provide useful information for initial design and maintenance plan of the RC bridge. This paper proposes an LCC prediction equation and a sensitivity analysis method for RC bridges. An LCC equation for the RC bridge which includes initial investment cost, maintenance cost, and demolition cost was derived and verified from the data for design and construction of an RC slab bridge. In order to solve uncertainty problem on actual discount rate and material characteristics in the analysis of LCC of concrete bridges, a sensitivity analysis method on the LCC using the Monte Carlo simulation technique was suggested.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.2
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• pp.151-157
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• 2008

A non-fragile guaranteed cost control (GCC) problem is presented for a class of discrete time-delay nonlinear systems described by Takagi-Sugeno (T-S) fuzzy model. The systems are assumed to have norm-bounded time-varying uncertainties in the matrices of state, delayed state and control gains. Sufficient conditions are first obtained which guarantee that the closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound. Then the design method of the non-fragile guaranteed cost controller is formulated in terms of the linear matrix inequality (LMI) approach. A numerical example is given to illustrate the effectiveness of the proposed design method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.8
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• pp.1429-1433
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• 2008

In this paper, we consider the design method of robust guaranteed cost controller for discrete-time singular systems with norm-bounded time-varying parameter uncertainty. In order to get the optimum(minimum) value of guaranteed cost, an optimization problem is given by linear matrix inequality (LMI) approach. The sufficient condition for the existence of controller and the upper bound of guaranteed cost function are proposed in terms of strict LMIs without decompositions of system matrices. Numerical examples are provided to show the validity of the presented method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.8
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• pp.1491-1497
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• 2007

This paper considers robust and non-fragile guaranteed cost controller design method for descriptor systems with parameter uncertainties and time delay, and static state feedback controller with gain variations. The existence condition of controller, the design method of controller, the upper bound to minimize guaranteed cost function, and the measure of non-fragility in controller are proposed using linear matrix inequality (LMI) technique, which can be solved efficiently by convex optimization. Therefore, the presented robust and non-fragile guaranteed cost controller guarantees the asymptotic stability and non-fragility of the closed loop systems in spite of parameter uncertainties, time delay, and controller fragility.

• ETRI Journal
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• v.43 no.4
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• pp.684-693
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• 2021

This paper presents a low-cost two-stage approximate multiplier for bfloat16 (brain floating-point) data processing. For cost-efficient approximate multiplication, the first stage implements Mitchell's algorithm that performs the approximate multiplication using only two adders. The second stage adopts the exact multiplication to compensate for the error from the first stage by multiplying error terms and adding its truncated result to the final output. In our design, the low-cost multiplications in both stages can reduce hardware costs significantly and provide low relative errors by compensating for the error from the first stage. We apply our approximate multiplier to the convolutional neural network (CNN) inferences, which shows small accuracy drops with well-known pre-trained models for the ImageNet database. Therefore, our design allows low-cost CNN inference systems with high test accuracy.