• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.3661-3666
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• 2015

The paper describes the integrated design system using MDO and approximation technique. In MDO related research, final target is an integrated and automated MDO framework systems. However, in order to construct the integrated design system, the prerequisite condition is how much save computational cost because of iterative process in optimization design and lots of data information in CAD/CAE integration. Therefore, this paper presents that an efficient approximation method, Adaptive approximation, is a competent strategy via MDO framework systems.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.6
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• pp.381-389
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• 2021

Most diagnosis approaches rely on historical failure data that might not be feasible in real operating conditions because the battery voltage and internal parameters are nonlinear according to various operating conditions, such as cell-to-cell configuration and initial condition. To overcome this issue, the estimator and the predictor require integrated approaches that consider comprehensive data, with the degradation process and measured data taken into account. In this paper, vector autoregressive models (VAR) with various parameters that affect overdischarge to the cell in the battery pack were constructed, and the cell-to-cell parameters were identified using an adaptive model to analyze the influence of failure prognosis. The theoretical analysis is validated using experimental results in terms of the feasibility and advantages of fault prognosis.

• Structural Engineering and Mechanics
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• v.43 no.3
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• pp.349-370
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• 2012

Variable-node finite element families, termed (4 + k + l + m + n)-node elements with an arbitrary number of nodes (k, l, m, and n) on each of their edges, are developed based on the generic point interpolation with special bases having slope discontinuities in two-dimensional domains. They retain the linear interpolation between any two neighboring nodes, and passes the standard patch test when subdomain-wise $2{\times}2$ Gauss integration is employed. Their shape functions are automatically generated on the master domain of elements although a certain number of nodes are inserted on their edges. The elements can provide a flexibility to resolve nonmatching mesh problems like mesh connection and adaptive mesh refinement. In the case of adaptive mesh refinement problem, so-called "1-irregular node rule" working as a constraint in performing mesh adaptation is relaxed by adopting the variable-node elements. Through several examples, we show the performance of the variable-node finite elements in terms of accuracy and efficiency.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1993.04a
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• pp.140-146
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• 1993

Active noise control uses the intentional superposition of acoustic waves to create a destructive interference pattern such that a reduction of the unwanted sound occurs. In active noise control system the choice of a control structure and design of the controller are the main issues of concern. In real acoustic fields there are a vast number of noise sources with time-varying nature and the characteristics of transducers and the geometric set-up of control system are subject to change. Accordingly the control system should be designed to adapt such circumstances so that required level of performance is maintained. In this paper, the adaptive control algorithm for self-tuning adaptive controller is presented for the application in active noise control system. Self-tuning is a direct integration of identification and controller design algorithm in such a manner that the two processes proceed sequentially. The least mean square algorithm was used for the identification schemes and adaptive weighted minimum variance control algorithm was applied for self-tuning controller. Computer simulation results for self-tuning feedback controller are presented. And simulation results was shown to be useful for the situation in which the periodic noise sources act on the acoustic field.

• Journal of Communications and Networks
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• v.15 no.3
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• pp.301-311
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• 2013

This paper proposes a policy-based quality of service (QoS) management framework for adaptive routing decisions. We present an approach considering interior gateway protocol (IGP) for path discovery mechanisms and QoS-aware policies for configuring the network elements. The integration of the aforementioned modules into this policy-based network management (PBNM) system is demonstrated by conducting experiments in a real environment, the hellenic public administration network SYZEFXIS. These experiments combine different traffic conditioning mechanisms through event detectors, consider IP service level agreement mechanisms that interoperate with the PBNM system and analyze the enforcement of IGP and QoS policies. Finally, validation and measurement tools are used to prove the efficiency of this framework. It is shown that this architecture offers significantly increased performance and learning capabilities, while the PBNM system achieves adaptive QoS routing through automated configuration considering the avoidance of suboptimal routing issues or under-performance conditions of the network entities.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4570-4575
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• 2023

Noise and Radio-frequency interference or RFI causes a significant restriction on the Free induction Decay or FID signal detection of the Nuclear Quadrupole Resonance procedure. Therefore, using this method in non-isolated environments such as industry and ports requires extraordinary measures. For this purpose, noise reduction algorithms and increasing signal-to-noise-and-interference ratio or SNIR have been used. In this research, sodium nitrite has been used as a sample and algorithms have been tested in a non-isolated environment. The resonant frequencies for the 150 g of test sample were measured at 303 K at about 1 MHz and 3.4 MHz. The main novelty in this study was, (1) using two types of antennas in the receiver to improve adaptive noise and interference cancellation, (2) using a separate helical antenna in the transmitter to eliminate the duplexer, (3) estimating the noise before sending the pulse to calculate the weighting factors and reduce the noise by adaptive noise cancellation, (3) reject the interference by blanking algorithm, (4) pulse integration in the frequency domain to increase the SNR, and (5) increasing the detection speed by new pulse integration technique. By interference rejection and noise cancellation, the SNIR is improved to 9.24 dB at 1 MHz and to 7.28 dB at 3.4 MHz, and by pulse integration 44.8 dB FID signal amplification is achieved, and the FID signals are detected at 1.057 MHz and 3.402 MHz at room temperature.

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.19-28
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• 2011

Adaptive Random Testing (ART) aims to enhance the performance of pure random testing by detecting failure region in a software. The ART algorithm generates effective test cases which requires less number of test cases than that of pure random testing. However, all ART algorithms currently proposed are designed for the tests of monolithic system or unit level. In case of integrated system tests, ART approaches do not achieve same performances as those of ARTs applied to the unit or monolithic system. In this paper, we propose an extended ART algorithm which can be applied to the integrated system testing environment without degradation of performance. The proposed approach investigates an input distribution of the unit under a test with limited number of seed input data and generates information to be used to resizing input domain partitions. The simulation results show that our approach in an integration environment could achieve similar level of performance as an ART is applied to a unit testing. Results also show resilient effectiveness for various failure rates.

• Coupled systems mechanics
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• v.8 no.1
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• pp.71-93
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• 2019

Finite element simulations of solid mechanics problems often involve the use of Non-Confirming Meshes (NCM) to increase accuracy in capturing nonlinear behavior, including damage and plasticity, in part of a solid domain without an undue increase in computational costs. In the presence of material nonlinearity and plasticity, higher-order variables are often needed to capture nonlinear behavior and material history on non-conforming interfaces. The most popular formulations for coupling non-conforming meshes are dual methods that involve the interpolation of a traction field on the interface. These methods are subject to the Ladyzhenskaya-Babuska-Brezzi (LBB) stability condition, and are therefore limited in their implementation with the higher-order elements needed to capture nonlinear material behavior. Alternatively, the enriched discontinuous Galerkin approach (EDGA) (Haikal and Hjelmstad 2010) is a primal method that provides higher order kinematic fields on the interface, and in which interface tractions are computed from local finite element estimates, therefore facilitating its implementation with nonlinear material models. The inclusion of higher-order interface variables, however, presents the issue of preserving material history at integration points when a increase in integration order is needed. In this study, the enriched discontinuous Galerkin approach (EDGA) is extended to the case of small-deformation plasticity. An interface-driven Gauss-Kronrod integration rule is proposed to enable adaptive enrichment on the interface while preserving history-dependent material data at existing integration points. The method is implemented using classical J2 plasticity theory as well as the pressure-dependent Drucker-Prager material model. We show that an efficient treatment of interface variables can improve algorithmic performance and provide a consistent approach for coupling non-conforming meshes in inelasticity.

• The Journal of Korean Academy of Sensory Integration
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• v.20 no.3
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• pp.48-59
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• 2022

Objective : This study was intended to systematically consider the sensory integration intervention methods offered in Korea for children with autism spectrum disorder and to provide an evidence base for the application of sensory integration interventions. Methods : The subjects of this study were published studies in a national journal for the last 10 years from January 2011 to December 2020. The databases used for the search were RISS and DBpia. The search terms were 'autism', 'autism spectrum', 'sensory integration', and 'intervention'. A total of 10 studies were used in the analysis, which were analyzed at the qualitative and methodological quality of the research evidence and the results were presented according to the PICO (Patient, Intervention, Comparison, Outcome). Results : In the research analysis, the quality level of the evidence was highest at level IV, followed by level II. The methodological quality of the evidence was the most common for 'Good' research, followed 'Fair'. The study subjects were children with autism spectrum disorder and their parents, and the experimental design had the highest frequency of single-subject studies. Interventions have the highest number of studies confirming adaptive behavior and sensory modulation, and the evaluation tools used to measure interventions have the highest frequency of sensory profiles and Canadian occupational performance measures (COPM). All 10 studies used in the analysis showed positive improvements and statistically significant effects on various outcome values from sensory integration interventions. Conclusion : In the recent clinical environment, sensory integration interventions have been continuously conducted in children with autism spectrum disorder. In future research, it is necessary to conduct research on various sensory integration intervention methods and the high quality of the evidence for the application of sensory integration interventions.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.808-813
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• 2003

Maintaining agility and responsiveness m designing and manufacturing activities are the key issues for manufacturing companies to cope with global competition. Distributed design and control systems are regarded as an efficient solution for agility and responsiveness. However, distributed nature of a manufacturing system complicates production activities such as design, simulation, scheduling, and execution control. Especially, existing simulation systems have limited external integration capabilities, which make it difficult to implement complex control mechanisms for the distributed manufacturing systems. Moreover, integration and coupling of heterogeneous components and models are commonly required for the simulation of complex distributed systems. In this paper, a collaborative and adaptive simulation architecture is proposed as an open framework for simulation and analysis of the distributed manufacturing enterprises. By incorporating agents with their distributed characteristics of autonomy, intelligence, and goal-driven behavior, the proposed agent-based simulation architecture can be easily adapted to support the agile and distributed manufacturing systems. The architecture supports the coordination and cooperation relations, and provides a communication middleware among the participants in simulation.