• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.683-688
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• 2018

Recently, the demand for electric energy has been increasing due to the spread of hybrid electric vehicles. In this study, to meet this demand, the ANSYS MAXWELL electromagnetic simulation system was used to compare the power generation characteristics of three types of suspension system that can generate electricity using energy harvesting technology. Next, the optimal design was determined for each model by using the commercial PIDO (Process Integration and Design Optimization) tool, PIANO (Process Integration, Automation and Optimization). We selected three design variables and constructed an approximate model based on the experimental design method through electromagnetic analysis for 18 experimental points derived from Orthogonal Arrays among the experimental design methods. Then, we determined the optimal design by applying the Evolutionary Algorithm. Finally, the optimal design results were verified by electromagnetic simulation of the optimum design result model using the same analysis conditions as those of the initial model. After comparing the power generation characteristics for the optimal structure for each linear generator model, the maximum power generation amounts in the 8pole-8slot, 12pole-12slot, and 16pole-16slot structures were 366.5W, 466.7W and 579.7W, respectively, and it was found that as the number of slots and poles increases, the power generation increases.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.1
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• pp.79-83
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• 2010

The conventional welding technique such as shield metal arc welding has been mostly applied to the piping system of the nuclear power plants. It is well known that this welding technique causes the overheating and welding defects due to the large groove angle of weld. On the other hand, the narrow gap welding(NGW) technique has many merits, for instance, the reduction of welding time, the shrinkage of weld and the small deformation of the weld due to the small groove angle and welding bead width comparing with the conventional welds. These characteristics of NGW affect the deformation behavior and the distribution of welding residual stress of NGW, thus it is believed that the residual stress results obtained from conventional welding procedure may not be applied to structural integrity evaluation of NGW. In this paper, the welding residual stress of NGW was predicted using the nonlinear finite element analysis to simulate the thermal and mechanical effects of the NGW. The present results can be used as the important information to perform the flaw evaluation and to improve the weld procedure of NGW.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.5
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• pp.575-582
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• 2011

A cleaning blade is an attachment installed in the toner cartridge of a laser printer for removing the residual toner from an organic photo-conductive drum. There have been many studies on the performance and life of the rubber blade. We focus on optimally designing the blade shape parameters to minimize the maximum stress of the blade while satisfying design constraints on the cleaning performance and part interference. The blade is optimally designed using a design of experiments, meta-models and an optimization algorithm implemented in PIAnO (process integration, automation, and optimization), a commercial PIDO (process integration and design optimization) tool. We integrate the CAE tools necessary for the structural analysis of the cleaning blade, automate the analysis procedure, and optimize the solution using PIAnO. We decreased the maximum stress by 32.6% in comparison with that of the initial design.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.289-295
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• 2005

LMTT (Linear Motor-based Transfer Techn-ology) is a horizontal transfer system for the yard automation This system is based on PMLSM (Permanent Magnetic Linear Synchronous Motor) toot consists of stator modules on the rail and shuttle car. In this research, the kriging interpolation method with sequential sampling find the optimum design of mover in LMTT. The design variables are considered as the transverse, longitudinal and wheel beam's thicknesses. The objective function is set up as weight, while the constant function are set up as the stresses generated by four loading conditions. The objective function is set up as weight. The optimum results obtained by the suggested method are compared with those by the GENESIS.

• Knowledge Management Research
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• v.22 no.4
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• pp.283-301
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• 2021

RPA (Robotic Process Automation) technology has recently been spotlighted to preemptively respond to the 4th industrial revolution without spending a lot of time and money to improve various existing business and IT processes. In this study, variables affecting intention to use RPA technology were representatively identified into three positive factors and three negative factors, and the causal relationship between the effects of these variables on actual RPA acceptance intention was examined. After conducting an email survey for general office workers, structural equation analysis (SEM) was performed using SPSS 27.0 and SmartPLS 3.3.5. The second order factor of a positive perception consisting of security, accuracy, and efficiency, and the second order factor of a negative perception consisting of job security, execution error, and fear of introduction failure. The positive perception affected the intention to use RPA through perceived usefulness and perceived ease. It was confirmed that the negative perception has a mediating effect on the intention to use RPA through acceptance conflict. In addition, it was confirmed that the presence or absence of experience in using RPA interacts with perceived ease and has a moderating effect on intention to use RPA. It can be said that there is practical and theoretical implications from the point of view of knowledge management in that it allows companies to recognize and respond to which factors are important from the point of view of companies that want to use RPA.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.2
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• pp.69-80
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• 1999

Recently, social requirements of personal identification techniques are rapidly expanding in a number of new application ares. Especially fingerprint recognition is the most important technology. Fingerprint recognition technologies are well established, proven, cost and legally accepted. Therefore, it has more spot lighted among the any other biometrics technologies. In this paper we propose a new on-line fingerprint recognition algorithm for non-inked type live scanner to fit their increasing of security level under the computing environment. Fingerprint recognition system consists of two distinct structural blocks: feature extraction and feature matching. The main topic in this paper focuses on the feature matching using the fingerprint minutiae (ridge ending and bifurcation). Minutiae matching is composed in the alignment stage and matching stage. Success of optimizing the alignment stage is the key of real-time (on-line) fingerprint recognition. Proposed alignment algorithm using clique shows the strength in the search space optimization and partially incomplete image. We make our own database to get the generality. Using the traditional statistical discriminant analysis, 0.05% false acceptance rate (FAR) at 8.83% false rejection rate (FRR) in 1.55 second average matching speed on a Pentium system have been achieved. This makes it possible to construct high performance fingerprint recognition system.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.183-194
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• 2005

In this study, we introduce an advanced architecture of genetically optimized Hybrid Fuzzy Neural Networks (gHFNN) and develop a comprehensive design methodology supporting their construction. A series of numeric experiments is included to illustrate the performance of the networks. The construction of gHFNN exploits fundamental technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms (GAs). The architecture of the gHFNNs results from a synergistic usage of the genetic optimization-driven hybrid system generated by combining Fuzzy Neural Networks (FNN) with Polynomial Neural Networks (PNN). In this tandem, a FNN supports the formation of the premise part of the rule-based structure of the gHFNN. The consequence part of the gHFNN is designed using PNNs. We distinguish between two types of the linear fuzzy inference rule-based FNN structures showing how this taxonomy depends upon the type of a fuzzy partition of input variables. As to the consequence part of the gHFNN, the development of the PNN dwells on two general optimization mechanisms: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the gHFNN, the models are experimented with a representative numerical example. A comparative analysis demonstrates that the proposed gHFNN come with higher accuracy as well as superb predictive capabilities when comparing with other neurofuzzy models.

• International Journal of Control, Automation, and Systems
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• v.2 no.4
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• pp.423-434
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• 2004

In this paper, we introduce a new topology of Self-Organizing Polynomial Neural Networks (SOPNN) based on genetically optimized Multi-Layer Perceptron (MLP) and discuss its comprehensive design methodology involving mechanisms of genetic optimization. Let us recall that the design of the 'conventional' SOPNN uses the extended Group Method of Data Handling (GMDH) technique to exploit polynomials as well as to consider a fixed number of input nodes at polynomial neurons (or nodes) located in each layer. However, this design process does not guarantee that the conventional SOPNN generated through learning results in optimal network architecture. The design procedure applied in the construction of each layer of the SOPNN deals with its structural optimization involving the selection of preferred nodes (or PNs) with specific local characteristics (such as the number of input variables, the order of the polynomials, and input variables) and addresses specific aspects of parametric optimization. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between the approximation and generalization (predictive) abilities of the model. To evaluate the performance of the GA-based SOPNN, the model is experimented using pH neutralization process data as well as sewage treatment process data. A comparative analysis indicates that the proposed SOPNN is the model having higher accuracy as well as more superb predictive capability than other intelligent models presented previously.reviously.

• Structural Monitoring and Maintenance
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• v.2 no.1
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• pp.19-34
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• 2015

One of the main causes of a limited use of nondestructive evaluation (NDE) technologies in bridge deck assessment is the speed of data collection and analysis. The paper describes development and implementation of the RABIT (Robotics Assisted Bridge Inspection Tool) for data collection using multiple NDE technologies. The system is designed to characterize three most common deterioration types in concrete bridge decks: rebar corrosion, delamination, and concrete degradation. It implements four NDE technologies: electrical resistivity (ER), impact echo (IE), ground-penetrating radar (GPR), and ultrasonic surface waves (USW) method. The technologies are used in a complementary way to enhance the interpretation. In addition, the system utilizes advanced vision to complement traditional visual inspection. Finally, the RABIT collects data at a significantly higher speed than it is done using traditional NDE equipment. The robotic system is complemented by an advanced data interpretation. The associated platform for the enhanced interpretation of condition assessment in concrete bridge decks utilizes data integration, fusion, and deterioration and defect visualization. This paper concentrates on the validation and field implementation of two NDE technologies. The first one is IE used in the delamination detection and characterization, while the second one is the USW method used in the assessment of concrete quality. The validation of performance of the two methods was conducted on a 9 m long and 3.6 m wide fabricated bridge structure with numerous artificial defects embedded in the deck.

• Journal of Practical Engineering Education
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• v.7 no.2
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• pp.119-123
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• 2015

ABS material is easy to process, impact resistance and heat resistance is strong. ABS material is often used as a substitute for the interior and exterior metal material for an automobile. As the demand of ABS increases, fabricating education using ABS has also been increasing its importance. As part of its education, ABS material is used in the mold fabricating part of the regional and national skills competition. At this time, the force of the vise for fixing the ABS material in the processing using the ABS material can affect the final shape after machining. However, it has not been an accurate description of the notes and instructions of working in education. Therefore, in this study, we study the impact the force of vise affect structural shape in the fabricating education using ABS material and during fabricating education of ABS material, trying to present the notes of the appropriate it.