• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.859-866
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• 2023

This paper focuses on configuring a user-friendly system of LED systems by applying improvement measures such as gamma correction, non-flicker, and driving noise removal using MCUs and LED drivers. As a result of the experiment, the 22kHz PWM mode of the LED driver generated noise outside the audible frequency range, making it practically imperceptible to users. The appropriate pull-up resistor values within the normal operating delay ratio of 5% were found to be 1kΩ to 10kΩ for the 3kHz PWM mode and 1kΩ to 2kΩ for the 22kHz PWM mode. In addition, gamma correction can be optimized for nonlinear human visual systems to express accurate contrast and as a result, it is expected to develop an LED system that can be expressed more naturally and accurately than conventional LED systems and improve users' visual experience.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.499-508
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• 2023

In this paper, we propose a technique to estimate the coordinates of feature points existing on a 2D planar object in the three dimensional space. The proposed method detects multiple 3D features from the image, and excludes those which are not located on the plane. The proposed technique estimates the planar homography between the planar object in the 3D space and the camera image plane, and computes back-projection error of each feature point on the planar object. Then any feature points which have large error is considered as off-plane points and are excluded from the feature estimation phase. The proposed method is archived on the basis of the planar homography without any additional sensors or optimization algorithms. In the expretiments, it was confirmed that the speed of the proposed method is more than 40 frames per second. In addition, compared to the RGB-D camera, there was no significant difference in processing speed, and it was verified that the frame rate was unaffected even in the situation that the number of detected feature points continuously increased.

• Composites Research
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• v.37 no.1
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• pp.15-20
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• 2024

Since the residual stress of hydrogen tank is directly related to durability, it is very important to reduce it for safety. Type II~IV hydrogen tank are manufactured by the filament winding method, in which the fiber is impregnated with resin and wound around the liner. Residual stress in composite is affected by curing conditions and fiber tension etc. In this study, the effect of curing conditions on residual stress was analyzed when manufacturing a Type III hydrogen tank using carbon fiber filament winding process. First, the curing behavior of the epoxy resin was analyzed using a differential scanning calorimetry. Through this, the curing temperature was set to 140℃. During the same curing time, the specimens were cured under 2-stage curing condition that reached 140℃ earlier and a 4-stage curing condition that reached 140℃ later, respectively. After curing, the residual stress of the composite material was measured by the ring slitting method, and the experimental values were compared with numerical values. It was confirmed that there was a significant difference in residual stress according to the optimization of curing conditions.

• Design & Manufacturing
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• v.17 no.4
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• pp.1-7
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• 2023

In the fabrication of curved multi-display glass for automotive use, the surface roughness of the mold is a critical quality factor. However, the difficulty in detecting micro-cutting signals in a micro-machining environment and the absence of a standardized model for predicting micro-cutting forces make it challenging to intuitively infer the correlation between cutting variables and actual surface roughness under machining conditions. Consequently, current practices heavily rely on machining condition optimization through the utilization of cutting models and experimental research for force prediction. To overcome these limitations, this study employs a surface roughness prediction formula instead of a cutting force prediction model and converts the surface roughness prediction formula into experimental data. Additionally, to account for changes in surface roughness during machining runtime, the theory of position variables has been introduced. By leveraging artificial neural network technology, the accuracy of the surface roughness prediction formula model has improved by 98%. Through the application of artificial neural network technology, the surface roughness prediction formula model, with enhanced accuracy, is anticipated to reliably perform the derivation of optimal machining conditions and the prediction of surface roughness in various machining environments at the analytical stage.

• Steel and Composite Structures
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• v.51 no.1
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• pp.25-41
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• 2024

The measurement of pile bearing capacity is crucial for the design of pile foundations, where in-situ tests could be costly and time needed. The primary objective of this research was to investigate the potential use of fuzzy-based techniques to anticipate the maximum weight that concrete driven piles might bear. Despite the existence of several suggested designs, there is a scarcity of specialized studies on the exploration of adaptive neuro-fuzzy inference systems (ANFIS) for the estimation of pile bearing capacity. This paper presents the introduction and validation of a novel technique that integrates the fire hawk optimizer (FHO) and equilibrium optimizer (EO) with the ANFIS, referred to as ANFIS_FHO and ANFIS_EO, respectively. A comprehensive compilation of 472 static load test results for driven piles was located within the database. The recommended framework was built, validated, and tested using the training set (70%), validation set (15%), and testing set (15%) of the dataset, accordingly. Moreover, the sensitivity analysis is performed in order to determine the impact of each input on the output. The results show that ANFIS_FHO and ANFIS_EO both have amazing potential for precisely calculating pile bearing capacity. The R² values obtained for ANFIS_FHO were 0.9817, 0.9753, and 0.9823 for the training, validating, and testing phases. The findings of the examination of uncertainty showed that the ANFIS_FHO system had less uncertainty than the ANFIS_EO model. The research found that the ANFIS_FHO model provides a more satisfactory estimation of the bearing capacity of concrete driven piles when considering various performance evaluations and comparing it with existing literature.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.47-52
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• 2024

The effects of annealing temperature on the optical and electrical properties of BZO thin films, grown on glass substrate, have been investigated. Analysis of the XRD shows that regardless of the annealing temperature, all BZO thin films indicate the c-axis orientation. The full width of half maximum (FWHM) decreases from 1.65 to 1.07° as the annealing temperature increases from 400 to 600℃. The average transmittance in the visible light region showed a high value of 85% without significantly affecting the annealing temperature. The results of Hall effect measurements indicate that the carrier concentration and mobility increased and the resistivity decreased as the annealing temperature increased. The resistivity and the carrier concentration of the BZO thin films annealed 600℃ were 9.75×10^-2 Ω·cm and 4.21×10¹⁹ cm^-3 respectively, showing the best value. The optimization of deposition and annealing conditions will certainly make the BZO thin films promising materials for the application to the next generation of optoelectronic devices.

• Journal of Advanced Technology Convergence
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• v.3 no.1
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• pp.13-20
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• 2024

This paper discusses a study on a mobile application aimed at making public transportation more convenient for people with mobility challenges on both Android and iOS platforms. The research analyzes the limitations and weaknesses of existing mobile applications for public transportation from the perspective of individuals with mobility challenges. The goal is to overcome these limitations and provide an optimized user experience. The motivation behind this research stems from the recognition that people with mobility challenges face difficulties in their daily commute, and current public transportation applications do not adequately cater to their needs. Consequently, the study aims to develop a specialized mobile application for individuals with mobility challenges to support them in achieving greater independence in their daily travels.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.453-458
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• 2024

Due to global issues such as climate crisis and rising energy costs, there is an increasing focus on energy conservation and management. In the case of South Korea, approximately 53.5% of the total energy consumption comes from industrial complexes. In order to address this, we aimed to improve issues through the 'Shared Network Utility Plant' among companies using similar energy utilities to find energy-saving points. For effective energy conservation, various techniques are utilized, and stable data supply is crucial for the reliable operation of factories. Many anomaly detection and alert systems for checking the stability of data supply were dependent on Energy Management Systems (EMS), which had limitations. The construction of an EMS involves large-scale systems, making it difficult to implement in small factories with spatial and energy constraints. In this paper, we aim to overcome these challenges by constructing a data collection system and anomaly detection alert system on embedded devices that consume minimal space and power. We explore the possibilities of utilizing anomaly detection alert systems in typical institutions for data collection and study the construction process.

• Transactions of Materials Processing
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• v.33 no.2
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• pp.103-111
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• 2024

With the increasing global interest in carbon neutrality, the automotive industry is also transitioning to the production of eco-friendly cars, specifically electric vehicles. In order to achieve comparable driving distances to internal combustion engine vehicles, the application of high-capacity battery packs has led to an increase in vehicle weight. To achieve light-weighting and durability requirements of automotive components simultaneously, there is a demand for research on the application of Ultra-High Strength Steel (UHSS). However, when manufacturing chassis components using UHSS, there are challenges related to fracture defects due to lower elongation compared to regular steel sheets, as well as spring-back issues caused by high tensile strength. In this study, a simulated specimen that is not affected by the property changes of four materials was designed to improve formability of the rear cross member, which is the most challenging automotive chassis component. The influence and correlation of material-specific variables were analyzed through finite element analysis (FEA) for each material with tensile strength of 440, 590, 780, and 980 MPa grades, resulting in the development of a predictive equation. To validate the equation, the simulated specimens of 980 MPa grade were produced from the test molds. Then the reliability of the FEA and predictive equation was verified with measured specimen data using a 3D scanner. The results of this study can be proposed to improve the formability of UHSS chassis components in future researches.

• Transactions of Materials Processing
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• v.33 no.3
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• pp.200-207
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• 2024

In this study, we developed a semi-analytical approach for the numerical analysis of residual stress in oxide scales formed on hot-rolled steels. The oxide scale, formed during the hot rolling process, experiences complex interactions due to thermal and mechanical influences, significantly affecting the material's integrity and performance. Our research focuses on integrating various stress components such as thermal stress, growth stress, and creep behavior to predict the residual stress within the oxide layer. The semi-analytical method combines analytical expressions for each stress component with numerical integration to account for their cumulative effects. Validation through instrumented indentation tests confirms the reliability of our model, which considers thermal expansion coefficient (CTE) differences, scale growth, and creep-induced stress relaxation. Our findings indicate that thermal stress resulting from CTE differences significantly impacts the overall residual stress, with growth stress contributing a compressive component during cooling, and creep behavior playing a minor role in stress relaxation. This comprehensive approach enhances the accuracy of residual stress prediction, facilitating the optimization of material design and processing conditions for hot-rolled steel products.