• Steel and Composite Structures
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• v.50 no.2
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• pp.135-148
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• 2024

This paper analytically investigates the free vibration analysis of functionally graded-carbon nanotube reinforced composite (FG-CNTRC) plates by dynamic stiffness method (DSM). The properties of CNTRC are determined with the extended rule of mixture. The governing differential equations of motion based on the first-order shear deformation theory of CNTRC plate are derived using Hamilton's principle. The FG-CNTRC plates are studied for a uniform and two different distributions of carbon nanotubes (CNTs). The accuracy and performance of the DSM are compared with the results obtained from closed closed-form and semi-analytical solution methods in previous studies. In this study, the effects of boundary condition, distribution type of CNTs, plate aspect ratio, plate length to thickness ratio, and different values of CNTs volume fraction on the natural frequencies of the FG-CNTRC plates are investigated. Finally, various natural frequencies of the plates in different conditions are provided as a benchmark for comparing the accuracy and precision of the other analytical and numerical methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.102-105
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• 2010

Traditional Pub/Sub(Publish/Subscribe) Systems search all subscriptions that match an incoming event by broker(i.e. it is not considering the accuracy of matching between an incoming event and subscriptions and only consider that an event either matches a subscription or not). However, subscriptions that match an event may have priority, therefore, we need priority Pub/Sub system. In this paper, we define what the accuracy means in order to prioritize among subscriptions and propose the Priority Retrieval Technique based on accuracy that able to search subscriptions. The Priority Retrieval Technique is based on IS-Lists. We can search the results ordered by accuracy.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.453-457
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• 2001

One of the major limitations of productivity and quality in metal cutting is the machining accuracy of machine tools. The machining accuracy is affected by geometric and thermal errors of the machine tools. In this study, the compensation device is manufactured in order to compensate thermal error of machine tools under the real-time. This paper models of the thermal errors for error analysis and develops on-the-machine measurement system by which the volumetric error are measured and compensated. The thermal error is modeled by means of angularity errors of a column and thermal drift error of the spindle unit which are measured by the touch probe unit with a star type styluses, a designed spherical ball artifact, and five gap sensors. In order to compensate thermal characteristics under several operating conditions, experiments performed with five gap sensors and manufactured compensation device on the horizontal machining center.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.213-218
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• 1997

Thermal deformation of machine origin of machine tools due to internal and external heat sources has been the most important problem to fabricate products with higher accuracy and performance. In order to solve this problem, GMDH models were constructed to estimate thermal deformation of machine origin for a vertical machining ceneter through measurement of temperature data of specific points on the machine tool. These models are nonlinear equations with high-order polynomials and implemented in a multilayered perceptron type network structure. Input variables and orders are automatically selected by correlation and optimization procedure. Sensors with small influence are deleted automatically in this algorithm. It was shown that the points of temperature measurement can be reduced without sacrificing the estimation accuracy of $\pm$5${\mu}{\textrm}{m}$. From the experimental result, it was confirmed that GMDH methodology was superior to least square models to estimate the thermal behavior of machine tools.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.5 s.236
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• pp.716-725
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• 2005

The method of substructure synthesis o. component mode synthesis(CMS) provides an effective means of dynamic analysis of very large and/or complex structures. In this study, residual dynamic flexibility attachment modes in hybrid component mode synthesis are considered for the purpose of exactly compensating the effect of higher order truncated modes. Following this way, the analysis accuracy of the synthesized structure can be improved effectively with less computational effort. In order to show the accuracy and effectiveness of the proposed hybrid component mode synthesis(HCMS), numerical experiments were carried out for the models of a clamped-clamped beam. The results verified the effectiveness of the proposed method.

• Journal of the Korea Society of Computer and Information
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• v.20 no.10
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• pp.31-38
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• 2015

In this paper, we propose the ensemble-based classification model which extracts just new data patterns from the streaming-data by using clustering and generates new classification models to be added to the ensemble in order to reduce the number of data labeling while it keeps the accuracy of the existing system. The proposed technique performs clustering of similar patterned data from streaming data. It performs the data labeling to each cluster at the point when a certain amount of data has been gathered. The proposed technique applies the K-NN technique to the classification model unit in order to keep the accuracy of the existing system while it uses a small amount of data. The proposed technique is efficient as using about 3% less data comparing with the existing technique as shown the simulation results for benchmarks, thereby using clustering.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.471-474
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• 2001

Recently, due to demands of faster speed and extra features for the chip mounters, there has been ever-demanding needs for the basic technology. Until four or five years ago, chip mounters placing 0.3sec/chip were considered to be in the high speed category, but since then it has become a borderline for categorizing high speed machines capable of placing 0.1sec/chip. In this study, in order to analyze the vibration of head generated by the dynamic behavior of x-frame, FEM model is composed and modal analysis is performed to identify the dynamic characteristics of the structure. Those results are compared with the modal test in order to verify the model. In this paper, Several other factors, such as definition of dynamic accuracy, static accuracy and tolerance of the axis settling range, that might affect the dynamic behavior the head are discussed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1663-1667
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• 2003

This thesis is on tile development of LD(Laser Diode) chip tester and the control system based on graphical programming language(LabVIEW) to control the equipment. The LD chip tester is used to test the optic power and the optic spectrum of the LD Chip. The emitter size of LD chip and the diameter of the receiver(optic fiber) are very small. Therefore, in order to test each chip precisely, this tester needs high accuracy. However each motion part of the tester could not accomplish hish accuracy due to the limit of the mechanical performance. Hence. an image processing with machine vision was carried out in order to compensate for the error. and also a load test was carried out so as to reduce tile impact of load on chip while the probing motion device is working. The obtained results were within ${\pm}$5$\mu\textrm{m}$ error.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.3
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• pp.185-207
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• 1998

This research investigates computer generated hybrid second-order model of two numerically based approaches to risk classification : discriminant analysis and neural networks. The hybrid second-order models are derived by rule induction using the ID3 and tested in the several different kinds of data. This new hybrid approach is designed to combine the high prediction accuracy and robustness of DA or NN with perspicuity of ID3. The hybrid model also eliminates the problem of contradictory inputs of ID3. After doing empirical test for the validity of hybrid model using small and medium companies' bankrupt data, hybrid model shows high perspicuity, high prediction accuracy for bankrupt, and simplicity for rules. The hybrid model also shows high performance regardless the type of data such as numeric data, non-numeric data, and combined data.

• Proceedings of the Korea Society for Simulation Conference
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• 1998.03a
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• pp.101-105
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• 1998

A large system predictor, which can perform prediction of sales trend in a huge number of distribution centers, is presented using neural predictive model. There are 20,000 number of distribution centers, and each distribution center need to forecast future demand in order to establish a reasonable inventory policy. Therefore, the number of forecasting models corresponds to the number of distribution centers, which is not possible to estimate that kind of huge number of accurate models in ERP (Enterprise Resource Planning)module. Multilayer neural net as universal approximation is employed for fitting the prediction model. In order to improve prediction accuracy, a sequential simulation procedure is performed to get appropriate network structure and also to improve forecasting accuracy. The proposed simulation procedure includes neural structure identification and virtual predictive model generation. The predictive model generation consists of generating virtual signals and estimating predictive model. The virtual predictive model plays a key role in tuning the real model by absorbing the real model errors. The complement approach, based on real and virtual model, could forecast the future demands of various distribution centers.