• Structural Engineering and Mechanics
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• v.14 no.3
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• pp.345-364
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• 2002

The scaling laws for vibration response of anti-symmetrically laminated plates are derived by applying the similitude transformation to the governing differential equations directly. With this approach, a closed-form solution of the governing equations is not required. This is a significant advantage over the method employed by other researchers where similitude transformation is applied to the closed-form solution. The scaling laws are tested by comparing the similitude fundamental frequencies to the theoretical fundamental frequencies determined from the available closed-form solutions. In case of complete similitude, similitude solutions from the scaling laws exactly agree with the theoretical solutions. Sometimes, it may not be feasible to select the model which obeys the similarity requirement completely, therefore partial similitude is theoretically investigated and approximate scaling laws are recommended. The distorted models in stacking sequences and laminated material properties demonstrate reasonable accuracy. On the contrary, a model with distortion in fiber angle is not recommended. The derived scaling laws are very useful to determine the vibration response of complex prototypes by performing the experiment on a model with required similarities.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.192-194
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• 1996

This paper propose an optimal scaling gain tuning method of the fuzzy PI controller using Genetic Algorithm(GA). Scaling gains can reflect the control resolution and fuzziness of input/output variables. By the scaling gain method, the design of a fuzzy logic controller(FLC) can be simplified without affecting the system performance in comparison with multi-decision table method. In designing a fuzzy logic controller, the analytic approach method for the optimization is unavailable. Therefore GA is excellent optimization algorithms for scaling gain tuning. Using this optimal scaling gain tuning method, a good performance can be achieved both in transient and steady state.

• Proceedings of the Korean Nuclear Society Conference
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• 1995.05b
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• pp.833-838
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• 1995

This study presents a method to predict plant-specific and operational history dependent scaling factors. Realistic and detailed approaches are taken to find scaling factors at reactor coolant. This approach begins with fission product release mechanisms and fundamental release properties of fuel-source nuclide such as fission product and transuranic nuclide. Scaling factors at various waste streams are derived from the predicted reactor coolant scaling factors with the use of radionuclide retention and build up model. This model makes use of radioactive material balance within the radioactive waste processing systems. According to input parameters of plant operation history, scaling factors predicted at reactor coolant and waste streams are well brought out the effects of plant operation history.

• ETRI Journal
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• v.44 no.3
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• pp.491-503
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• 2022

Metal-oxide-semiconductor field-effect transistors (MOSFETs) are continuously scaling down in the nanoscale region to improve the functionality of integrated circuits. The scaling down of MOSFET devices causes short-channel effects in the nanoscale region. In nanoscale region, leakage current components are increasing, resulting in substantial power dissipation. Very large-scale integration designers are constantly exploring different effective methods of mitigating the power dissipation. In this study, a transistor-level input-controlled stacking (ICS) approach is proposed for minimizing significant power dissipation. A low-power ICS approach is extensively discussed to verify its importance in low-power applications. Circuit reliability is monitored for process and voltage and temperature variations. The ICS approach is designed and simulated using Cadence's tools and compared with existing low-power and high-speed techniques at a 22-nm technology node. The ICS approach decreases power dissipation by 84.95% at a cost of 5.89 times increase in propagation delay, and improves energy dissipation reliability by 82.54% compared with conventional circuit for a ring oscillator comprising 5-inverters.

• Journal of the Korea Society of Computer and Information
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• v.18 no.7
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• pp.11-21
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• 2013

Recently operating a large scale computing resource like a data center becomes easier because of the virtualization technology that virtualize servers and enable flexible resource provision. The most of public cloud services provides automatic scaling in the form of scale-in or scale-out and these scaling approaches works well to satisfy the service level agreement (SLA) of users. However, a novel scaling approach is required to operate private clouds that has smaller amount of computing resources than vast resources of public clouds. In this paper, we propose a hybrid server scaling architecture and related algorithms using both scale-in and scale-out to achieve higher resource utilization rate for private clouds. We uses dynamic resource allocation and live migration to run our proposed algorithm. Our propose system aims to provide a fine-grain resource scaling by steps. Thus private cloud systems are able to keep stable service and to reduce server management cost by optimizing server utilization. The experiment results show that our proposed approach performs better in resource utilization than the scale-out approach based on the number of users.

• Journal of Korean Society for Quality Management
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• v.32 no.3
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• pp.68-80
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• 2004

This paper purports to uncover the underlying attributes used by customers to gauge service quality. Data was collected by administering questionnaires to 50 respondents and then analyzed by using Multidimensional Scaling methodology. The findings indicate that there are two primary dimensions to service quality. This analysis helped determine us two alternatives to naming the dimensions. Experience properties of service and Price value of the service, or Responsiveness of service provider employees and Reliability of service providers.

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.639-645
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• 2004

This paper purports to uncover the underlying attributes used by customers to gauge service quality. Data was collected by administering questionnaires to 50 respondents and then analyzed by using Multidimensional Scaling methodology. The findings indicate that there are two primary dimensions to service quality. A considerable analysis helped determine two alternatives to naming the dimensions: Experience properties of service and Price value of the service, or Responsiveness of service provider employees and Reliability of service providers.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.5
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• pp.819-826
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• 1994

This paper deals with a self-tuning fuzzy controller. The fuzzy controller is constructed with linguistic rules which consist of the fuzzy sets. Each fuzzy set is characterized by a membership function. The tuning fuzzy controller has paramenters that are input/output scaling factors to effect control output. In this paper we propose a tuning method for the scaling factor Computer simulations carried out on first-order and second-order processes will show how the present tuning approach improves the transient and the steady-state characteristics of the overall system.The applicability of the proposed algorithm is certified by computer simulation results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.438-441
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• 2004

In this study, we introduce a noble neurogenetic approach to the design of fuzzy controller. The design procedure dwells on the use of Computational Intelligence (CI), namely genetic algorithms and Fuzzy-Set based Neural Networks (FSNN). The crux of the design methodology is based on the selection and determination of optimal values of the scaling factors of the fuzzy controllers, which are essential to the entire optimization process. First, the tuning of the scaling factors of the fuzzy controller is carried out by using GAs, and then the development of a nonlinear mapping for the scaling factors is realized by using GA based FSNN. The developed approach is applied to a nonlinear system such as an inverted pendulum where we show the results of comprehensive numerical studies and carry out a detailed comparative analysis.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.93-97
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• 2002

In this paper, we propose personalized recommendation techniques based on multidimensional scaling (MDS) method for Business to Consumer Electronic Commerce. The multidimensional scaling method is traditionally used in marketing domain for analyzing customers' perceptional differences about brands and products. In this study, using purchase history data, customers in learning dataset are assigned to specific product categories, and after then using MDS a positioning map is generated to map product categories and alternative advertisements. The positioning map will be used to select personalized advertisement in real time situation. In this paper, we suggest the detail design of personalized recommendation method using MDS and compare with other approaches (random approach, collaborative filtering, and TOP3 approach)