• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2199-2213
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• 2024

To enhance the quality of defect detection for Printed Circuit Board Assembly (PCBA) during electronic product manufacturing, this study primarily focuses on optimizing the YOLOv7-based method for PCBA defect detection. In this method, the Mish, a smoother function, replaces the Leaky ReLU activation function of YOLOv7, effectively expanding the network's information processing capabilities. Concurrently, a Squeeze-and-Excitation attention mechanism (SEAM) has been integrated into the head of the model, significantly augmenting the precision of small target defect detection. Additionally, considering angular loss, compared to the CIoU loss function in YOLOv7, the SIoU loss function in the paper enhances robustness and training speed and optimizes inference accuracy. In terms of data preprocessing, this study has devised a brightness adjustment data enhancement technique based on split-filtering to enrich the dataset while minimizing the impact of noise and lighting on images. The experimental results under identical training conditions demonstrate that our model exhibits a 9.9% increase in mAP value and an FPS increase to 164 compared to the YOLOv7. These indicate that the method proposed has a superior performance in PCBA defect detection and has a specific application value.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.679-690
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• 2011

Two widely used approaches for improving the quality of the output of a process are statistical process control (SPC) and automatic process control (APC). In recent hybrid processes that combine aspects of the process and parts industries, process variations due to both the inherent wandering and special causes occur commonly, and thus simultaneous application of APC and SPC schemes is needed to effectively keep such processes close to target. The simultaneous implementation of APC and SPC schemes is called integrated process control (IPC). In the IPC procedure, the output variables are monitored during the process where adjustments are repeatedly done by its controller. For monitoring the APC-controlled process, control charts can be generally applied to the output variable. However, as an alternative, some authors suggested that monitoring the input variable may improve the chance of detection. In this paper, we evaluate the performance of several monitoring statistics, such as the output variable, the input variable, and the difference variable, for efficiently monitoring the APC-controlled process when we assume IMA(1,1) noise model with a minimum mean squared error adjustment policy.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.4
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• pp.221-230
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• 2021

This paper proposes full waveform inversion (FWI) for estimating the physical properties of a layered half-space. An FWI solution is obtained using a genetic algorithm (GA), which is a well-known global optimization approach. The dynamic responses of a layered half-space subjected to a harmonic vertical disk load are measured and compared with those calculated using the estimated physical properties. The responses are calculated using the thin-layer method, which is accurate and efficient for layered media. Subsequently, a numerical model is constructed for a layered half-space using mid-point integrated finite elements and perfectly matched discrete layers. An objective function of the global optimization problem is defined as the L2-norm of the difference between the observed and estimated responses. A GA is used to minimize the objective function and obtain a solution for the FWI. The accuracy of the proposed approach is applied to various problems involving layered half-spaces. The results verify that the proposed FWI based on a GA is suitable for estimating the material properties of a layered half-space, even when the measured responses include measurement noise.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.12
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• pp.1205-1214
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• 2013

Recently spaceborne SAR systems are increasing image resolution and frequency. As a high quality image resolution, the wider bandwidth is required and a wideband signal generator with RF component is very complicated and RF impairments of device is increased. Therefore, it is very important to improve performance by reducing these errors. In this study, the transmission signal of the wideband signal generator is applied to the phase noise, IQ imbalance, ripple gain, nonlinear model of high power amplifier. And we define possible structures of wideband signal generator and measure the PSLR and ISLR for the performance assesment. Also, we extract error of the amplitude and phase from the waveform and use a quadratic polynomial curve fitting and examine the performance change due to nonlinear device. Finally, we apply a high power amplifier predistortion method for non-linear error compensation. And we confirm that distortion in the output of the amplifier by intermodulation component is decreased by 15 dB.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.5
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• pp.459-467
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• 2012

In this work, the configuration of a haptic gripper featuring magnetorheological(MR) brakes is proposed and an optimal design of the MR brakes for the haptic griper is performed considering the required braking torque, the uncontrollable torque(zero-field friction torque) and mass of the brakes. Several configurations of MR brake is proposed such as disc-type, serpentine-type and hybrid-type. After the configurations of the MR brakes are proposed, braking torque of the brakes is analyzed based on Bingham rheological model of the MR fluid. The zero-field friction torque of the MR brakes is also analyzed. An optimization procedure based on finite element analysis integrated with an optimization toolbox is developed for the MR brakes. The purpose of the optimal design is to find optimal geometric dimensions of the MR brake structure that can produce the required braking torque and minimize the mass of the MR brakes. In addition, the uncontrollable torque of the MR brakes is constrained to be much smaller than the required braking torque. Based on the developed optimization procedure, optimal solution of the proposed MR brakes are achieved and the best MR brake is determined. The working performance of the optimized MR brake is then investigated.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.10
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• pp.83-92
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• 2019

A pump is considered to be submersible when a motor and a pump are integrated and operate while submerged in water. Submersible pumps mainly function as rejection pumps to prevent foods in densely populated areas, as cold water circulation pumps in large power plants, as pumps to supply irrigation water, as drainage pumps to prevent flooding of agricultural lands, as water supply intake pumps, and as inflow pumps for sewage treatment. The flow in such turbomachines (submersible pumps) inevitably involves various eddy currents. Since it is almost impossible to accurately grasp the complex three-dimensional flow structure and characteristics of a rotating turbomachine through actual testing, three-dimensional numerical analysis using computational fluid dynamics techniques measuring the flow field, velocity, and the pressure can be accurately predicted. In this study, the shape of the impeller was developed to reduce vibration and noise. This was done by increasing the efficiency of the existing submersible pump and reducing turbulence. In order to evaluate the pump's efficiency and turbulence reduction, we tried to analyze the flow using ANSYS Fluent V15.0, a commercial finite element analysis program. The results show that the efficiency of the pump was improved by 4.24% and the Reynolds number was reduced by 15.6%. The performance of a developed pump with reduced turbulence, vibration, and noise was confirmed.

• Geophysics and Geophysical Exploration
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• v.9 no.1
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• pp.44-49
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• 2006

In this study, the resolution capabilities of electrical resistivity tomography (ERT) in the monitoring of $CO_2$ injection are investigated. The pole-pole and bipole-bipole electrode configuration types are used between two uncased boreholes straddling the $CO_2$ plume. Forward responses for an initial pre-injection model and three models for subsequent stages of $CO_2$ injection are calculated for the two different electrode configuration types, noise is added and the theoretical data are inverted with both L1- and L2-norm optimisation. The results show that $CO_2$ volumes over a certain threshold can be detected with confidence. The L1-norm proved superior to the L2-norm in most instances. Normalisation of the inverted models with the pre-injection inverse model gives good images of the regions of changing resistivity, and an integrated measure of the total change in resistivity proves to be a valid measure of the total injected volume.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1542-1550
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• 2019

Legacy studies for classifying arrhythmia have been studied to improve the accuracy of classification, Neural Network, Fuzzy, etc. Deep learning is most frequently used for arrhythmia classification using error backpropagation algorithm by solving the limit of hidden layer number, which is a problem of neural network. In order to apply a deep learning model to an ECG signal, it is necessary to select an optimal model and parameters. In this paper, we propose optimal parameter extraction method based on a deep learning. For this purpose, R-wave is detected in the ECG signal from which noise has been removed, QRS and RR interval segment is modelled. And then, the weights were learned by supervised learning method through deep learning and the model was evaluated by the verification data. The detection and classification rate of R wave and PVC is evaluated through MIT-BIH arrhythmia database. The performance results indicate the average of 99.77% in R wave detection and 97.84% in PVC classification.

• Journal of KIBIM
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• v.9 no.4
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• pp.51-61
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• 2019

In the general manufacturing sector, prototyping used to reduce the risks that can arise with new conceptual products. However, in AEC area, it does not mass-produce a building, so the prototype itself becomes a building. Therefore, it is challenging to have prototyping of the same scale as the real thing, and the prototyping process in architecture is very inefficient. The prototyping process in the design stage typically assumes making a scaled model, partial model, or digital model. However, it is difficult for these models to correspond to the actual building and the environment of time and space such as scale, material, environment, load, physical properties and deformation, corrosion, etc., unlike the actual building. When using the digital twin concept in the prototyping process, it is possible to measure performance from the design stage to the operation stage. The digital twin was found by a method for monitoring based on physical twins and real-time linkage in the operation stage. Therefore, if the digital twin concept is applied at the design stage, it is possible to predict performance using not only current performance but also history information using real-time information. In order to apply the digital twin concept to the prototyping design process, we analyze the theoretical considerations and the prototyping design process of the digital twin, analyze the cases and research results where the prototyping design was applied, Provide an applied prototyping design process. The proposed process is tested through a pilot project and analyzed for potential use.

• Safety and Health at Work
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• v.6 no.2
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• pp.77-84
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• 2015

Background: A unique framework for performance optimization of generation companies (GENCOs) based on health, safety, environment, and ergonomics (HSEE) indicators is presented. Methods: To rank this sector of industry, the combination of data envelopment analysis (DEA), principal component analysis (PCA), and Taguchi are used for all branches of GENCOs. These methods are applied in an integrated manner to measure the performance of GENCO. The preferred model between DEA, PCA, and Taguchi is selected based on sensitivity analysis and maximum correlation between rankings. To achieve the stated objectives, noise is introduced into input data. Results: The results show that Taguchi outperforms other methods. Moreover, a comprehensive experiment is carried out to identify the most influential factor for ranking GENCOs. Conclusion: The approach developed in this study could be used for continuous assessment and improvement of GENCO's performance in supplying energy with respect to HSEE factors. The results of such studies would help managers to have better understanding of weak and strong points in terms of HSEE factors.