• Journal of Institute of Control, Robotics and Systems
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• v.13 no.8
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• pp.790-797
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• 2007

This paper proposes a new measure of cost function ruggedness in local optimization with DEAS. DEAS is a computational optimization method developed since 2002 and has been applied to various engineering fields with success. Since DEAS is a recent optimization method which is rarely introduced in Korean, this paper first provides a brief overview and description of DEAS. In minimizing cost function with this non-gradient method, information on function shape measured automatically will enhance search capability. Considering the search strategies of DEAS are well designed with binary matrix structures, analysis of search behaviors will produce beneficial shape information. This paper deals with a simple quadratic function contained with various magnitudes of noise, and DEAS finds local minimum yielding ruggedness measure of given cost function. The proposed shape information will be directly used in improving DEAS performance in future work.

• Computational Structural Engineering : An International Journal
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• v.2 no.1
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• pp.11-17
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• 2002

Cost-effectiveness in design is considered for determining the target reliability of concrete bridges under seismic actions. This objective can be achieved based on the economic optimization of the expected life-cycle cost of a bridge, which includes initial cost, direct losses, and indirect losses of a bridge due to strong earthquakes over its lifetime. A separating factor is defined to consider the redundancy of a transportation network. The Park-Ang damage model is employed to define the damage of a bridge under seismic action, and a Monte Carlo method based on the DRAIN-2DX program is developed to assess the failure probability of a bridge. The results for an example bridge analyzed in this paper show that the optimal target failure probability depends on the traffic volume carried by the bridge and is between 1.0×10/sup -3/ to 3.0×10/sup -3/ over a life of 50 years.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.18 no.12
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• pp.992-998
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• 2006

This study is to optimize design parameters for waste heat recovery boiler with water tube and three drum. The design optimization considered here is to find the most economic dimension of the boiler considered which results in a minimum cost in producing a unit amount of steam per given period of operation. For this purpose, optimize design have to determine what are the main parameters of affecting the total cost of producing a unit amount of steam which is comprised of manufacturing cost of the boiler, operating cost of the fan etc.

• 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.

• Journal of Digital Convergence
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• v.18 no.2
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• pp.261-268
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• 2020

Machine learning is achieved by making a cost function from a given digital signal data and optimizing the cost function. The cost function here has local minimums in the cost function depending on the amount of digital signal data and the structure of the neural network. These local minimums make a problem that prevents learning. Among the many ways of solving these methods, our proposed method is to change the learning step-size. Unlike existed methods using the learning rate (step-size) as a fixed constant, the use of multivariate function as the cost function prevent unnecessary machine learning and find the best way to the minimum value. Numerical experiments show that the results of the proposed method improve about 3%(88.8%→91.5%) performance using the proposed method rather than the existed methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.35-57
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• 2021

Fog computing aims to provide the solution of bandwidth, network latency and energy consumption problems of cloud computing. Likewise, management of data generated by healthcare IoT devices is one of the significant applications of fog computing. Huge amount of data is being generated by healthcare IoT devices and such types of data is required to be managed efficiently, with low latency, without failure, and with minimum energy consumption and low cost. Failures of task or node can cause more latency, maximum energy consumption and high cost. Thus, a failure free, cost efficient, and energy aware management and scheduling scheme for data generated by healthcare IoT devices not only improves the performance of the system but also saves the precious lives of patients because of due to minimum latency and provision of fault tolerance. Therefore, to address all such challenges with regard to data management and fault tolerance, we have presented a Fault Tolerant Data management (FTDM) scheme for healthcare IoT in fog computing. In FTDM, the data generated by healthcare IoT devices is efficiently organized and managed through well-defined components and steps. A two way fault-tolerant mechanism i.e., task-based fault-tolerance and node-based fault-tolerance, is provided in FTDM through which failure of tasks and nodes are managed. The paper considers energy consumption, execution cost, network usage, latency, and execution time as performance evaluation parameters. The simulation results show significantly improvements which are performed using iFogSim. Further, the simulation results show that the proposed FTDM strategy reduces energy consumption 3.97%, execution cost 5.09%, network usage 25.88%, latency 44.15% and execution time 48.89% as compared with existing Greedy Knapsack Scheduling (GKS) strategy. Moreover, it is worthwhile to mention that sometimes the patients are required to be treated remotely due to non-availability of facilities or due to some infectious diseases such as COVID-19. Thus, in such circumstances, the proposed strategy is significantly efficient.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.35 no.1
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• pp.149-168
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• 2024

This study aims to propose methods for determining the minimum book purchase cost budget in university libraries in accordance with the "University Library Promotion Act" and efficiently allocating and executing the secured book purchase cost budget to each department. To achieve this, the current status of university libraries and legal standards were examined and strategies for securing the minimum book purchase cost budget in accordance with legal standards were suggested, and a method for efficiently distributing the secured budget to departments was proposed. First, we determined the material acquisition budget for university libraries by applying the average price of domestically published books to the standards set forth in the University Library Promotion Act. The allocated budget was distributed with 80% assigned to departments and 20% budget for librarians. The department's allocated budget of 80% was then recalculated to 100% and distributed by applying three criteria: book prices by topic, student enrollment, and utilization rates.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.561-568
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• 1994

A man model can be used as an effective tool to design ergonomically sound products and workplaces, and subsequently evaluate them properly. For a man model to be truly useful, it must be integrated with a posture prediction model which should be capable of representing the human arm reach posture in the context of equipments and workspaces. Since the human movement possesses redundant degrees of freedom, accurate representation or prediction of human movement was known to be a difficult problem. To solve this redundancy problem, a psychophysical cost function was suggested in this study which defines a cost value for each joint movement angle. The psychophysical cost function developed integrates the psychophysical discomfort of joints and the joint range availability concept which has been used for redundant arm manipulation in robotics to predict the arm reach posture. To properly predict an arm reach posture, an arm reach posture prediction model was then developed in which a posture configuration that provides the minimum total cost is chosen. The predictivity of the psychophysical cost function was compared with that of the biomechanical cost function which is based on the minimization of joint torque. Here, the human body is regarded as a two-dimensional multi-link system which consists of four links ; trunk, upper arm, lower arm and hand. Real reach postures were photographed from the subjects and were compared to the postures predicted by the model. Results showed that the postures predicted by the psychophysical cost function closely simulated human reach postures and the predictivity was more accurate than that by the biomechanical cost function.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.12
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• pp.663-672
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• 2017

Building information modeling (BIM) technology based on 3D modeling has been applied to the entire domestic construction industry since 2010. It can calculate quantity take-off considering construction productivity at design phase. Based on this, it is possible to improve the reliability of construction cost prediction of design phase in the process of cost estimation. However, Building Information Level (BIL) defined by Ministry of Land, Infrastructure and Transport and Public Procurement Service does not seem to offer doable environment due to the lack of detailed application items. By calculating construction cost that meets Construction Cost Estimate Accuracy by American Association of Cost Engineers (AACE) through quantity take-off and cost estimation based on 3D modeling of BIM technology, a BIL improvement proposal at design phase for Mechanical Contracts and Construction is provided here. Results showed that properties including outline and minimum specification of the main equipment, internal main piping, and internal main duct should be defined from the intermediate design phase to have reliable cost estimation.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.5
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• pp.285-295
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• 2004

The outage cost assessment has an important position for determination of the optimal level or optimal range of reliability for power system expansion planning. Establishing the worth of service reliability is a very difficult and subjective task. While the utility cost(reliability cost) will generally increase as consumers are provided with higher reliability, the consumer costs(reliability worth) associated with supply interruptions will decrease as the reliability increases. The total costs to society are the sum of these two individual costs and the optimum or target level of reliability is achieved at minimum point of the total cost curve. This paper addresses the role, need and assessment algorithms and methodologies of the outage cost in power system expansion planning. In a case study, the outage cost has been assessed using macro approach for our country 15years(1986-200l) in the case study. Additionally, determination processing of optimum reliability level is presented in another case study with the five buses MRBTS.