• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.236-241
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• 2024

Due to the recent emphasis on carbon neutrality and environmental regulations, the global electric vehicle (EV) market is experiencing rapid growth. This surge has raised concerns about the recycling and disposal methods for EV batteries. Unlike traditional internal combustion engine vehicles, EVs require unique and safe methods for the recovery and disposal of their batteries. In this process, predicting the lifespan of the battery is essential. Impedance and State of Charge (SOC) analysis are commonly used methods for this purpose. However, predicting the lifespan of batteries with complex chemical characteristics through electrical measurements presents significant challenges. To enhance the accuracy and precision of existing measurement methods, this paper proposes using a Long Short-Term Memory (LSTM) model, a type of deep learning-based recurrent neural network, to diagnose battery performance. The goal is to achieve safe classification through this model. The designed structure was evaluated, yielding results with a Mean Absolute Error (MAE) of 0.8451, a Root Mean Square Error (RMSE) of 1.3448, and an accuracy of 0.984, demonstrating excellent performance.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.8
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• pp.2555-2560
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• 1996

Inspecting the dimensional accuracy of a car-body in assembly line is a very important process to assure high productivity. Now there exist two common inspecting methods in practice. One is to measure a sampled car-body with three dimensional measuring machine, and the other is to measure car-body with three dimensional measuring machine, and the other is to measure car-body in assembly line using many sensors fixed to a large jig frame. The formal method takes too long to inspect a sampled car-body of a same sort, and cannot therefore give an useful error trend for the whole production. On the other hand, the latter lacks flexibility and is very cost-intensive. By using industrial robots and sensors, an in-line Car-Body Measuring(CBM) system which ensured high flexiblity and sufficient accuracy was developed. This CBM cell operates in real production line and measures the check points by the non-contact type using camera and laser displacement sensor(LDS). This system can handle about 15 Measuring points within a cycle time of 40 seconds. A process computer controls whole process such as data acquisition file handling and data analysis. Robot arms changes in length due to ambient temperature fluctuation affecting the measuring accuracy. To compensate this error, a robot arm calibration process was developed.

• Journal of Sensor Science and Technology
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• v.6 no.3
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• pp.207-213
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• 1997

A field effect transistor(FET) type dissolved carbon dioxide($pCO_{2}$) sensor with a double layer structure of hydrogel membrane and $CO_{2}$ gas permeable membrane was fabricated by utilizing a $H^{+}$ ion selective field effect transistor(pH-ISFET) with Ag/AgCl reference electrode as a base chip. Formation of hydrogel membrane with photo-crosslinkable PVA-SbQ or PVP-PVAc/photosensitizer system was not suitable with the photolithographic process. Furthermore, hydrogel membrane on pH-ISFET base chip could be fabricated by photolithographic method with the aid of N,N,N',N'-tetramethyl othylenediarnine(TED) as $O_{2}$ quencher without using polyester film as a $O_{2}$ blanket during UV irradiation process. Photosensitive urethane acrylate type oligomer was used as gas permeable membrane on top of hydrogel layer. The FET type $pCO_{2}$ sensor fabricated by photolithographic method showed good linearity (linear calibration curve) in the range of $10^{-3}{\sim}10^{0}\;mol/{\ell}$ of dissolved $CO_{2}$ in aqueous solution with high sensitivity.

• Korean Chemical Engineering Research
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• v.48 no.1
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• pp.33-38
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• 2010

A microfluidic system has been developed using biomaterial for the measurement of cupric ion concentration. The cell-membrane-mimicking bilayer lipid membrane(BLM)-coated silver electrode was used for the sensing of cupric ion concentration. The silver-supported BLM could increase its stability. A silver-supported bilayer lipid membrane(s-BLM) was easily obtained using its self-assembling characteristics by immersing silver wire into lipid(phosphatidylcholine; PC) solution and then dipping into aqueous KCl solution. These s-BLMs were used to determine the relationship between $Cu^{2+}$ concentration and current crossing s-BLM. Their relationship showed high linearity and reproducibility. The calibration curve was constructed to express the relationship between $Cu^{2+}$ concentration and current in the $Cu^{2+}$ concentration range of 10 and $130{\mu}M$. This calibration curve was used to measure $Cu^{2+}$ concentration in an unknown sample. Microfluidic system with s-BLM was made of PDMS(polydimethyl siloxane) using typical soft photolithography and molding technique. This integrated system has various functions such as activation of the silver surface without cutting silver wire, coating of BLM on silver surface, injection of KCl buffer solution, injection of $Cu^{2+}$ sample and measurement of $Cu^{2+}$ concentration in the sample.

• Journal of the Korean Geotechnical Society
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• v.32 no.4
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• pp.5-14
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• 2016

Numerical simulation of dynamic soil-pile-structure interaction embedded in a dry sand was carried out. 3D model of the dynamic centrifuge model tests was formulated in a time domain to consider nonlinear behavior of soil using the finite difference method program, FLAC3D. As a modeling methodology, Mohr-Coulomb criteria was adopted as soil constitutive model. Soil nonlinearity was considered by adopting the hysteretic damping model, and an interface model which can simulate separation and slip between soil and pile was adopted. Simplified continuum modeling (Kim et al., 2012) was used as boundary condition to reduce analysis time. Calibration process for numerical modeling results and test results was performed through the parametric study. Verification process was then performed by comparing numerical modeling results with another test results. Based on the calibration and validation procedure, it is identified that proposed modeling method can properly simulate dynamic behavior of soil-pile system in dry condition.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.1
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• pp.11-20
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• 2010

The distributed rainfall-runoff model which is developed in the country requires a lot of time and effort to generate input data. Also, it takes a lot of time to calculate discharge by numerical analysis based on kinematic wave theory in runoff process. Therefore, most river basins using the distributed model are of limited scale, such as small river basins. However, recently, the necessity of integrated watershed management has been increasing due to change of watershed management concept and discharge calculation of whole river basin, including upstream and downstream of dam. Thus, in this study, the feasibility of the GIS based physical distributed rainfall-runoff model, K-DRUM(K-water hydrologic & hydraulic Distributed RUnoff Model) which has been developed by own technology was reviewed in the flood discharge process for the Geum River basin, including Yongdam and Daecheong Dam Watersheds. GIS hydrological parameters were extracted from basic GIS data such as DEM, land cover and soil map, and used as input data of the model. Problems in running time and inaccuracy setting using the existing trial and error method were solved by applying an auto calibration method in setting initial soil moisture conditions. The accuracy of discharge analysis for application of the method was evaluated using VER, QER and Total Error in case of the typhoon 'Ewiniar' event. and the calculation results shows a good agreement with observed data.

• Journal of IKEEE
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• v.27 no.3
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• pp.345-349
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• 2023

In this paper, we propose a study on the development of deep learning structure for defective pixel detection of next-generation smart LED display board using imaging device. In this research, a technique utilizing imaging devices and deep learning is introduced to automatically detect defects in outdoor LED billboards. Through this approach, the effective management of LED billboards and the resolution of various errors and issues are aimed. The research process consists of three stages. Firstly, the planarized image data of the billboard is processed through calibration to completely remove the background and undergo necessary preprocessing to generate a training dataset. Secondly, the generated dataset is employed to train an object recognition network. This network is composed of a Backbone and a Head. The Backbone employs CSP-Darknet to extract feature maps, while the Head utilizes extracted feature maps as the basis for object detection. Throughout this process, the network is adjusted to align the Confidence score and Intersection over Union (IoU) error, sustaining continuous learning. In the third stage, the created model is employed to automatically detect defective pixels on actual outdoor LED billboards. The proposed method, applied in this paper, yielded results from accredited measurement experiments that achieved 100% detection of defective pixels on real LED billboards. This confirms the improved efficiency in managing and maintaining LED billboards. Such research findings are anticipated to bring about a revolutionary advancement in the management of LED billboards.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.23-31
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• 2010

Due to the fact that fisheye lens can provide super wide angles with the minimum number of cameras, field-of-view over 180 degrees, many vehicles are attempting to mount the camera system. Not only use the camera as a viewing system, but also as a camera sensor, camera calibration should be preceded, and geometrical correction on the radial distortion is needed to provide the images for the driver's assistance. In this thesis, we introduce a geometric correction technique to minimize the loss of the image data from a vehicle fish-eye lens having a field of view over $180^{\circ}$, and a asymmetric distortion. Geometric correction is a process in which a camera model with a distortion model is established, and then a corrected view is generated after camera parameters are calculated through a calibration process. First, the FOV model to imitate a asymmetric distortion configuration is used as the distortion model. Then, we need to unify the axis ratio because a horizontal view of the vehicle fish-eye lens is asymmetrically wide for the driver, and estimate the parameters by applying a non-linear optimization algorithm. Finally, we create a corrected view by a backward mapping, and provide a function to optimize the ratio for the horizontal and vertical axes. This minimizes image data loss and improves the visual perception when the input image is undistorted through a perspective projection.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1797-1802
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• 2005

In this study, we were developed an accuracy of the proposed two dimensional statical inclinometer what used a position sensitive detector(PSD) by an error analysis. The inclinometer consists of a laser source, a mass, an optic-fiber, and a PSD. The gravity direction on a base platform of the inclinometer is changed by an unknown inclination angle. And a laser spot is moved from the origin to another position of a PSD following a variation of an optical path by the gravity. These processes enable the inclinometer to estimate the inclination angle from distance information of the moving spot. A design methodology on the basis of a sensitivity analysis was applied to improve the measurement performance such as a full measuring range and a resolution. But it still has error factors, so we analyze the uncertainty of the inclinometer to evaluate the systematic errors from alignments, assembly error and so on. The experimental performance evaluation about the design objectives as a measuring range and a resolution was performed. And the validity and the feasibility of the design process were certified by an experimental process. Systematic errors eliminated to improve the accuracy of the inclinometer by the corrected measuring model from the calibration process between the inclination angle and the PSD position instead of the nominal measuring model. The ANOVA(analysis of variance) confirmed the effect of eliminating the systematic errors in the inclinometer. From these methodologies, the proposed inclinometer was able to measure with a high resolution(35.14sec) and a wide range(from $-15^{\circ}\;to\;15^{\circ}$

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.29 no.2
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• pp.76-82
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• 1997

In paper the evenness of planar distribution of mass in a small scale is called formation (orbetter:mass formation). Traditionally formation has been assessed visually, by looking the sheet of paper against transmitted light. Different kinds of optieal testers are being usd to obtain quantitative rankings htat would be independent of the observer but would well correspond to the visual assessment. However, various raw-material and process factors do influence light trans-mittance in paper and do impair the correspondence between basis weight and the optical formation measurement (or visual assessment). As the optical formation test methods do not incorporate an efficient calib ration routine, the formation of the sophisticated paper grades of today the is rather difficult to measure optically and may lead to erroneous results. It may be concluded that the optical measurement is not suitable for paper grades with high filler content. coating, heavy calendering or that are made of heavily beaten pulp, nordoes it apply for dyed or printed papers. For this reason, visual assessment and optical evaluation shoild be replaced with a measurement that gives reliable results independent on paper grode and manufacturing process. Formation measuremend based on beta radiation is suitable for all paper grades regardless to the material contents or process treatment. It is possible to measure even dyed or printed samples. Thonks to a sim ple and relioble calibration, the results are converted to real basis weight balues that remain reliable even with time. The only beta tester commercially available is the AMBERTEC Beta Formation Tester. Formation of paper does vary locally in the web. Typically there exists a formation profile, too similarly to other properties of paper. Therefore, formation should ？ ays be expressed as a mean of a sufficient amount of parallel determinations. All formation measurements should be calibrated against basis weight.