• Journal of Broadcast Engineering
• /
• v.26 no.1
• /
• pp.14-25
• /
• 2021

Change detection, which finds changes in remote sensing images of the same location captured at different times, is very important because it is used in various applications. However, registration errors, building displacement errors, and shadow errors cause false positives. To solve these problems, we propose a novle deep convolutional network called CADNet (Change Attention Dense Siamese Network). CADNet uses FPN (Feature Pyramid Network) to detect multi-scale changes, applies a Change Attention Module that attends to the changes, and uses DenseNet as a feature extractor to use feature maps that contain both low-level and high-level features for change detection. CADNet performance measured from the Precision, Recall, F1 side is 98.44%, 98.47%, 98.46% for WHU datasets and 90.72%, 91.89%, 91.30% for LEVIR-CD datasets. The results of this experiment show that CADNet can offer better performance than any other traditional change detection method.

• Journal of the Korea Convergence Society
• /
• v.13 no.3
• /
• pp.33-41
• /
• 2022

In this article, we proposed to predict natural gas (NG) leakage levels through feature selection based on a factor analysis (FA) of the integrating the Korean Meteorological Agency data and natural gas leakage data for considering complex factors. The paper has been divided into three modules. First, we filled missing data based on the linear interpolation method on the integrated data set, and selected essential features using FA with OrdinalEncoder (OE)-based normalization. The dataset is labeled by K-means clustering. The final module uses four algorithms, K-nearest neighbors (KNN), decision tree (DT), random forest (RF), Naive Bayes (NB), to predict gas leakage levels. The proposed method is evaluated by the accuracy, area under the ROC curve (AUC), and mean standard error (MSE). The test results indicate that the OrdinalEncoder-Factor analysis (OE-F)-based classification method has improved successfully. Moreover, OE-F-based KNN (OE-F-KNN) showed the best performance by giving 95.20% accuracy, an AUC of 96.13%, and an MSE of 0.031.

• Korean Journal of Acupuncture
• /
• v.38 no.4
• /
• pp.267-274
• /
• 2021

Objectives : Acupoints education is important in that it can determine the clinical competency of Korean Medicine Doctors (KMDs). Accordingly, we aimed to develop a practical simulator for acupoints education, acupoints training, acupoints practice, and acupoints evaluation. Methods : Korean Medicine (KM) SMART Table can be divided into hardware, server and components, and is organically linked. We develop KM SMART Table that combines the hardware of a human-sized table with a UHD display capable of multi-touch in two cases and software that can teach acupoints. We make Augmented Reality (AR) contents linked with KM SMART Table contents and develop applications that can use contents using mobile devices. By developing an AR image tracking module to react with KM SMART Table, it enables acupoint learning according to the mobile device platform and human anatomy. Results : The current system is a prototype where some 3D technology has been implemented, but the AR function will be produced later. New learning using 3D and AR will be required during acupoints education and acupoints practice. It will be used a lot in OSCE (Objective Structured Clinical Examination) practices for strengthening the competency of KMDs, and it will be of great help not only in KM education as a unique simulator of KM, but also in the practice of acupuncture and chuna for musculoskeletal diseases. Conclusions : The KM SMART Table is a technology that combines 3D and AR to learn acupoints, and to conduct acupoints OSCE practice, and we suggest that it can be usefully used for educational evaluation.

• Nuclear Engineering and Technology
• /
• v.54 no.8
• /
• pp.3059-3072
• /
• 2022

A Jacobian-Free Newton Krylov Two-Nodal Coarse Mesh Finite Difference algorithm based on Nodal Expansion Method (NEM_TNCMFD_JFNK) is successfully developed and proposed to solve the three-dimensional (3D) and multi-group reactor physics models. In the NEM_TNCMFD_JFNK method, the efficient JFNK method with the Modified Incomplete LU (MILU) preconditioner is integrated and applied into the discrete systems of the NEM-based two-node CMFD method by constructing the residual functions of only the nodal average fluxes and the eigenvalue. All the nonlinear corrective nodal coupling coefficients are updated on the basis of two-nodal NEM formulation including the discontinuity factor in every few newton steps. All the expansion coefficients and interface currents of the two-node NEM need not be chosen as the solution variables to evaluate the residual functions of the NEM_TNCMFD_JFNK method, therefore, the NEM_TNCMFD_JFNK method can greatly reduce the number of solution variables and the computational cost compared with the JFNK based on the conventional NEM. Finally the NEM_TNCMFD_JFNK code is developed and then analyzed by simulating the representative PWR MOX/UO₂ core benchmark, the popular NEACRP 3D core benchmark and the complicated full-core pin-by-pin homogenous core model. Numerical solutions show that the proposed NEM_TNCMFD_JFNK method with the MILU preconditioner has the good numerical accuracy and can obtain higher computational efficiency than the NEM-based two-node CMFD algorithm with the power method in the outer iteration and the Krylov method using the MILU preconditioner in the inner iteration, which indicates the NEM_TNCMFD_JFNK method can serve as a potential and efficient numerical tool for reactor neutron diffusion analysis module in the JFNK-based multiphysics coupling application.

• Journal of the Korean Recycled Construction Resources Institute
• /
• v.10 no.2
• /
• pp.176-183
• /
• 2022

High-purity waste CNTs were mixed into cement mortar to manufacture heat-generating concrete that can use low voltage power, and carbon fiber and waste cathode materials were also used improve the conductivity of the mortar. The waste CNTs were analyzed to have a high concentration of multi-walled CNTs, and substituted liquid type waste CNTs were used during mortar mixing in order to increase dispersibility. The temperature change of the mortar with CNT was evaluated when using electric power below DC 24 V in order to utilize a small self-generation facility such as small solar power module when the mortar heats up and to minimize electromagnetic waves. When liquid-type waste CNTs were applied and a voltage of DC 24 V was introduced, it rose to 60 ℃ in a 200 × 100 × 50 mm mortar block specimen. The field applicability of self heating mortar with waste CNT was sufficient and also the amount of change in heat energy in mortar with liquid type waste CNT, carbon fiber and waste cathode materials is more effective compared to it of other variables.

• Journal of IKEEE
• /
• v.26 no.3
• /
• pp.456-461
• /
• 2022

In this paper, a two-stage single-ended power amplifier (PA) with broadband gain characteristics was presented by utilizing a radio frequency (RF) transformer (TF), which is essential for a differential amplifier. The bandwidth of a PA can be improved by designing TF to have broadband characteristics and then applying it to the inter-stage matching network (IMN) of a PA. For broadband gain characteristics while maintaining the performance and area of the existing PA, an IMN was implemented on an monolithic microwave integrated circuit (MMIC) and a multi-layer printed circuit board (PCB), and the simulation results were compared. As a result of simulating the PA module designed using InGaP/GaAs HBT model, it has been confirmed that the PA employing the proposed design method has an improved fractional bandwidth of 19.8% at a center frequency of 3.3GHz, while the conventional PA showed that of 11.2%.

• Journal of Broadcast Engineering
• /
• v.28 no.2
• /
• pp.185-193
• /
• 2023

As many different over-the-top (OTT) services become ubiquitous, demands for high-quality content are increasing. However, high dynamic range (HDR) contents, which can provide more realistic scenes, are still insufficient. In this regard, we propose a new HDR video reconstruction technique using multi-exposure low dynamic range (LDR) videos. First, we align a reference and its neighboring frames to compensate for motions between them. In the alignment stage, we perform content-based alignment to improve accuracy, and we also present a high-resolution (HR) module to enhance details. Then, we merge the aligned features to generate a final HDR frame. Experimental results demonstrate that our method outperforms existing methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.22 no.6
• /
• pp.113-119
• /
• 2022

In software fault prediction, a multi classification model that predicts the fault severity category of a module can be much more useful than a binary classification model that simply predicts the presence or absence of faults. A small number of severity-based fault prediction models have been proposed, but no classifier using deep learning techniques has been proposed. In this paper, we construct MLP models with 3 or 5 hidden layers, and they have a structure with a fixed or variable number of hidden layer nodes. As a result of the model evaluation experiment, MLP-based deep learning models shows significantly better performance in both Accuracy and AUC than MLPs, which showed the best performance among models that did not use deep learning. In particular, the model structure with 3 hidden layers, 32 batch size, and 64 nodes shows the best performance.

• The Transactions of the Korea Information Processing Society
• /
• v.13 no.4
• /
• pp.166-173
• /
• 2024

This study explores lip-sync detection, focusing on the synchronization between lip movements and voices in videos. Typically, lip-sync detection techniques involve cropping the facial area of a given video, utilizing the lower half of the cropped box as input for the visual encoder to extract visual features. To enhance the emphasis on the articulatory region of lips for more accurate lip-sync detection, we propose utilizing a pre-trained visual attention-based encoder. The Visual Transformer Pooling (VTP) module is employed as the visual encoder, originally designed for the lip-reading task, predicting the script based solely on visual information without audio. Our experimental results demonstrate that, despite having fewer learning parameters, our proposed method outperforms the latest model, VocaList, on the LRS2 dataset, achieving a lip-sync detection accuracy of 94.5% based on five context frames. Moreover, our approach exhibits an approximately 8% superiority over VocaList in lip-sync detection accuracy, even on an untrained dataset, Acappella.

• Nuclear Engineering and Technology
• /
• v.56 no.5
• /
• pp.1584-1602
• /
• 2024

It is vital to output the required electrical power following various task requirements when the space reactor power supply is operating in orbit. The dynamic performance of the closed Brayton cycle thermoelectric conversion system is initially studied and analyzed. Based on this, a load tracking power regulation method is developed for the liquid metal cooled space reactor power system, which takes into account the inlet temperature of the lithium on the hot side of the intermediate heat exchanger, the filling quantity of helium and xenon, and the input amount of the heat pipe radiator module. After comparing several methods, a power regulation method with fast response speed and strong system stability is obtained. Under various changes in power output, the dynamic response characteristics of the ultra-small liquid metal lithium-cooled space reactor concept scheme are analyzed. The transient operation process of 70 % load power shows that core power variation is within 30 % and core coolant temperature can operate at the set safety temperature. The second loop's helium-xenon working fluid has a 65K temperature change range and a 25 % filling quantity. The lithium at the radiator loop outlet changes by less than ±7 K, and the system's main key parameters change as expected, indicating safety. The core system uses less power during 30 % load power transient operation. According to the response characteristics of various system parameters, under low power operation conditions, the lithium working fluid temperature of the radiator circuit and the high-temperature heat pipe operation temperature are limiting conditions for low-power operation, and multiple system parameters must be coordinated to ensure that the radiator system does not condense the lithium working fluid and the heat pipe.