• Journal of IKEEE
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• v.25 no.3
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• pp.430-436
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• 2021

The non-contact body temperature measurement system is one of the key factors, which is manage febrile diseases in mass facilities using optical and thermal imaging cameras. Conventional systems can only be used for simple body temperature measurement in the face area, because it is used only a deep learning-based face detection algorithm. So, there is a limit to detecting abnormal symptoms of the infants and young children, who have difficulty expressing their opinions. This paper proposes an improved facial expression recognition algorithm for detecting abnormal symptoms in infants and young children. The proposed method uses an object detection model to detect infants and young children in an image, then It acquires the coordinates of the eyes, nose, and mouth, which are key elements of facial expression recognition. Finally, facial expression recognition is performed by applying a selective sharpening filter based on the obtained coordinates. According to the experimental results, the proposed algorithm improved by 2.52%, 1.12%, and 2.29%, respectively, for the three expressions of neutral, happy, and sad in the UTK dataset.

• Composites Research
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• v.32 no.5
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• pp.258-264
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• 2019

In this paper, a progressive failure analysis method was developed using the Hashin failure criterion and crack band model. Using the failure criterion, the failure initiation was evaluated. If the failure initiation is occurred, the damage variables at each failure modes (fiber tension & compression, matrix tension & compression) was calculated according to linear softening degradation behavior and the variables are used to derive the damaged stiffness matrix. The damaged stiffness matrix is reflected to damaged material and the progressive failure analysis is continued until the damage variables to be 1 that complete failure of material. A series of processes were performed using FE commercial code ABAQUS with user defined material subroutine (UMAT). To evaluate the proposed progressive failure model, the experimental results of open hole composite laminate tests was compared with numerical result. Using digital image correlation system, the strain behavior also was compared. The proposed numerical results were coincided well with the experimental results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.565-571
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• 2021

In this paper, a compensation scheme of frequency selective IQ mismatch for high-performance radar systems based on commercial RFIC's is proposed. Besides, an optimization model and its solution based on the dimension reduction scheme using singular value decomposition are also proposed to design the optimal IQ mismatch compensation digital filter with complex coefficients. The performance of the proposed method had been analyzed through experiments using the IQ mismatch measurement and compensation system implemented on an FPGA board with a target RFIC and compared with the previous method. The experiment result showed a performance improvement of the proposed method over the existing one without noticeable increments in complexities. These performance analysis results showed that the limitation of using commercial RFIC's in high-performance radar systems due to the undesirable maximum SNR cap caused by their IQ mismatches could be overcome by employing the proposed method.

• Journal of Space Technology and Applications
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• v.1 no.3
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• pp.364-374
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• 2021

This research discusses the change in radio frequency (RF) characteristics according to the number of Gores on the deployable mesh antennas for potential micro-satellite applications. The deployable type of lightweight mesh antenna can be used for various space missions such as communication/SAR/ SIGINT. In order to implement an ideal curvature of antenna surface, sufficient number of antenna rib structures are required. However, the increase in antenna ribs affects various design factors of the antenna system, especially total system mass, complexity of deployable mechanism and reliability. In this paper, the proper number of ribs for the mesh antenna were derived by comparison of electro-magnetic (EM) simulation results of example of antenna model in accordance with the various number of ribs.

• Journal of Broadcast Engineering
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• v.28 no.2
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• pp.178-184
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• 2023

Finding texts in general scene images and recognizing their contents is a very important task that can be used as a basis for robot vision, visual assistance, and so on. However, for the low-resolution text images, the degradations, such as noise or blur included in text images, are more noticeable, which leads to severe performance degradation of text recognition accuracy. In this paper, we propose a new Korean text image super-resolution based on a Transformer-based model, which generally shows higher performance than convolutional neural networks. In the experiments, we show that text recognition accuracy for Korean text images can be improved when our proposed text image super-resolution method is used. We also propose a new Korean text image dataset for training our model, which contains massive HR-LR Korean text image pairs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.123-138
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• 2023

The Fourth Industrial Revolution and sensor technology have led to increased utilization of sensor data. In our modern society, data complexity is rising, and the extraction of valuable information has become crucial with the rapid changes in information technology (IT). Recurrent neural networks (RNN) and long short-term memory (LSTM) models have shown remarkable performance in natural language processing (NLP) and time series prediction. Consequently, there is a strong expectation that models excelling in NLP will also excel in time series prediction. However, current research on Transformer models for time series prediction remains limited. Traditional RNN and LSTM models have demonstrated superior performance compared to Transformers in big data analysis. Nevertheless, with continuous advancements in Transformer models, such as GPT-2 (Generative Pre-trained Transformer 2) and ProphetNet, they have gained attention in the field of time series prediction. This study aims to evaluate the classification performance and interval prediction of remaining useful life (RUL) using an advanced Transformer model. The performance of each model will be utilized to establish a health index (HI) for cutting blades, enabling real-time monitoring of machine health. The results are expected to provide valuable insights for machine monitoring, evaluation, and management, confirming the effectiveness of advanced Transformer models in time series analysis when applied in industrial settings.

• Journal of Korean Association for Spatial Structures
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• v.24 no.3
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• pp.43-51
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• 2024

Dynamic responses of nuclear power plant structure subjected to earthquake loads should be carefully investigated for safety. Because nuclear power plant structure are usually constructed by material of reinforced concrete, the aging deterioration of R.C. have no small effect on structural behavior of nuclear power plant structure. Therefore, aging deterioration of R.C. nuclear power plant structure should be considered for exact prediction of seismic responses of the structure. In this study, a machine learning model for seismic response prediction of nuclear power plant structure was developed by considering aging deterioration. The OPR-1000 was selected as an example structure for numerical simulation. The OPR-1000 was originally designated as the Korean Standard Nuclear Power Plant (KSNP), and was re-designated as the OPR-1000 in 2005 for foreign sales. 500 artificial ground motions were generated based on site characteristics of Korea. Elastic modulus, damping ratio, poisson's ratio and density were selected to consider material property variation due to aging deterioration. Six machine learning algorithms such as, Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Artificial Neural Networks (ANN), eXtreme Gradient Boosting (XGBoost), were used t o construct seispic response prediction model. 13 intensity measures and 4 material properties were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks present good prediction performance considering aging deterioration.

• Magazine of the Korea Concrete Institute
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• v.7 no.3
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• pp.187-198
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• 1995

This paper develops practical and reallstic reliabllity models and methods for the evaluation of system rehability and system rellabllity based ratlng of R.C box glrder bridge superstructures. The precise prediction of reberved carrying capacity of bridge as d system is extremely difficult especially when the brldges are highly redundant and slgnlficantly deter 1or;itcd or dainagetl. Thls papel proposes a nt2w approach for the evaluation of reseived system c,drrying capaaty of br~dges in terms ot equ~vdleiit system strength, which may b~ ddcflned as a brtdge system strength correipcmdlng tu the system rehability of the bridge. This cm be ticrAvcd from an Inverse process bami or1 the con~ept of FOSM(F1rst Order Second Moment) form of system reliabihty index. The sf rength llmt state models for K C box girder br~dges suggested In the paper dre based on the basi~ bending and shear strength And thc system reliatxllty pro,~lerri of box gritier super structure 1s formuldted as parallel serles models obtalncd f ~ o m thc FMA(Fdilure blode Rp proath) based on major failure mc>clmusrns or c~itlcal fdure ,>tatcs of each nuder .WOSM(Ad-vanced First Order Second Moment) and IST(1mportance Sampling Technique) simulation algorithm are used for the reliability analysis of the proposed models.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9B
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• pp.1742-1754
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• 1999

In this paper, we propose a rate control scheme, using histogram based rate-distortion (R-D) estimation, which produces a consistent picture quality between consecutive frames. The histogram based R-D estimation used in our rate control scheme offers a closed-form mathematical model that enable us to predict the bits and the distortion generated from an encoded frame at a given quantization parameter (QP) and vice versa. The most attractive feature of the R-D estimation is low complexity of computing the R-D data because its major operation is just to obtain a histogram or weighted histogram of DCT coefficients from an input picture. Furthermore, it is accurate enough to be applied to the practical video coding. Therefore, the proposed rate control scheme using this R-D estimation model is appropriate for the applications requiring low delay and low complexity, and controls the output bit-rate ad quality accurately. Our rate control scheme ensures that the video buffer do not underflow and overflow by satisfying the buffer constraint and, additionally, prevents quality difference between consecutive frames from exceeding certain level by adopting the distortion constraint. In addition, a consistent considering the maximum tolerance BER of the voice service. Also in Rician fading channel of K=6 and K=10, considering CLP=$10^{-3}$ as a criterion, it is observed that the performance improment of about 3.5 dB and 1.5 dB is obtained, respectively, in terms of $E_b$/$N_o$ by employing the concatenated FEC code with pilot symbols.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.23 no.2
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• pp.75-81
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• 2017

Modified atmosphere packaging (MAP) of vacuum, 60% $N_2/40%$ $CO_2$, 100% $N_2$ and 100% $CO_2$ were examined to preserve fried fish cakes and extend their shelf life. When product packages in air were stored at 5, 10, and $15^{\circ}C$ with measurement in quality attributes, aerobic bacterial growth was found to be primary quality factor to determine the shelf life of the product. Huang's model was adopted to obtain the parameters for use in shelf life determination for a variety of packaging and storage conditions. Temperature dependence expressed in Arrhenius equation showed activation energies of 139.4 and 41.8 kJ/mol for inverse of lag time and growth rate of the microbial spoilage, respectively. MAP of 100% $CO_2$ could double the product shelf life at $10^{\circ}C$ compared to air package. High $CO_2$ concentration MAP at low temperature was found to be effective to prolong the shelf life.