• Nuclear Engineering and Technology
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• v.40 no.6
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• pp.451-458
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• 2008

After more than 10 years construction, KSTAR (Korea Superconducting Tokamak Advanced Research) had finally completed its assembly in June 2007, and then achieved the goal of first-plasma in July 2008 through the four month's commissioning. KSTAR was constructed with fully superconducting magnets with material of $Nb_3Sn$ and NbTi, and their operation temperatures are maintained below 4.5K by the help of Helium Refrigerator System. During the first-plasma operation, plasmas of maximum current of 133kA and maximum pulse width of 865ms were obtained. The KSTAR Integrated Control System (KICS) has successfully fulfilled its missions of surveillance, device operation, machine protection interlock, and data acquisition and management. These and more were all KSTAR commissioning requirements. For reliable and safe operation of KSTAR, 17 local control systems were developed. Those systems must be integrated into the logically single control system, and operate regardless of their platforms and location installed. In order to meet these requirements, KICS was developed as a network-based distributed system and adopted a new framework, named as EPICS (Experimental Physics and Industrial Control System). Also, KICS has some features in KSTAR operation. It performs not only 24 hour continuous plant operation, but the shot-based real-time feedback control by exchanging the initiatives of operation between a central controller and a plasma control system in accordance with the operation sequence. For the diagnosis and analysis of plasma, 11 types of diagnostic system were implemented in KSTAR, and the acquired data from them were archived using MDSpius (Model Driven System), which is widely used in data management of fusion control systems. This paper will cover the design and implementation of the KSTAR integrated control system and the data management and visualization systems. Commissioning results will be introduced in brief.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.525-534
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• 2023

Gas leak detection system is a key to minimize the loss of life due to the explosiveness and toxicity of gas. Most of the leak detection systems detect by gas sensors or thermal imaging cameras. To improve the performance of gas leak detection system using single-modal methods, the paper propose multimodal approach to gas sensor data and thermal camera data in developing a gas type identification model. MultimodalGasData, a multimodal open-dataset, is used to compare the performance of the four models developed through multimodal approach to gas sensors and thermal cameras with existing models. As a result, 1D CNN and GasNet models show the highest performance of 96.3% and 96.4%. The performance of the combined early fusion model of 1D CNN and GasNet reached 99.3%, 3.3% higher than the existing model. We hoped that further damage caused by gas leaks can be minimized through the gas leak detection system proposed in the study.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.505-518
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• 2023

3D point cloud semantic segmentation is a computer vision task that involves dividing the point cloud into different objects and regions by predicting the class label of each point. Existing 3D semantic segmentation models have some limitations in performing sufficient fusion of multi-modal features while ensuring both characteristics of 2D visual features extracted from RGB images and 3D geometric features extracted from point cloud. Therefore, in this paper, we propose MMCA-Net, a novel 3D semantic segmentation model using 2D-3D multi-modal features. The proposed model effectively fuses two heterogeneous 2D visual features and 3D geometric features by using an intermediate fusion strategy and a multi-modal cross attention-based fusion operation. Also, the proposed model extracts context-rich 3D geometric features from input point cloud consisting of irregularly distributed points by adopting PTv2 as 3D geometric encoder. In this paper, we conducted both quantitative and qualitative experiments with the benchmark dataset, ScanNetv2 in order to analyze the performance of the proposed model. In terms of the metric mIoU, the proposed model showed a 9.2% performance improvement over the PTv2 model using only 3D geometric features, and a 12.12% performance improvement over the MVPNet model using 2D-3D multi-modal features. As a result, we proved the effectiveness and usefulness of the proposed model.

• Nuclear Engineering and Technology
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• v.41 no.2
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• pp.149-154
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• 2009

The microstructure, the corrosion behavior and the oxide properties were examined for Zr-1.5Nb-0.4Sn-0.2Fe-0.1Cr (HANA-4) alloys which were subjected to two different final annealing temperatures: $470^{\circ}C$ and $570^{\circ}C$. HANA-4 was shown to have $\ss$-enriched phase with a bcc crystal structure and Zr(Nb,Fe,Cr)$_2$ with a hcp crystal structure with $\ss$-enriched phase being more frequently observed compared with Zr(Nb,Fe,Cr)$_2$. The corrosion rate of HANA-4 was increased with an increase of the final annealing temperature in the PWR-simulating loop, $360^{\circ}C$ pure water and $400^{\circ}C$ steam conditions, which was correlated well with a reduction in the size of the columnar grains in the oxide/metal interface region. The oxide growth rate of HANA-4 was considerably affected by the alloy microstructure determined by the final annealing temperature.

• Journal of Fisheries and Marine Sciences Education
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• v.22 no.4
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• pp.589-603
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• 2010

The purpose of this study is to develop a integrated(fusion) utilization model aimed at maximizing the development/management functions of urban estuarine area and to present an integrated concept by analyzing the existing document and data. The main points of this study are as follows: 1) The integrated utilization model suggested in this paper goes beyond the existing idea of sustainable utilization and conservation, putting an emphasis on rational decision-making in estuary management and peaceful coexistence between human and nature. 2) Policies for utilization/development/conservation/regeneration of urban estuarine area include the establishment of communication system between human and nature and a safety net considering both human and nature, the support for environment-friendly community development and the importance of preserving valuable ecosystem and wetland habitat. 3) Lastly, this study suggested that the major tasks for the fusion utilization model development are the integrated management of estuary areas, the conservation and preservation of wetland ecosystem, proper utilization of estuary's productivity, and the introduction and action plans of the integrated management model including the best way to address contamination and disaster management.

• Nuclear Engineering and Technology
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• v.44 no.6
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• pp.673-682
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• 2012

Three dimensional atom probe tomography (3D APT) is applied to characterize the dissimilar metal joint which was welded between the Ni-based alloy, Alloy 690 and the low alloy steel, A533 Gr. B, with Alloy 152 filler metal. While there is some difficulty in preparing the specimen for the analysis, the 3D APT has a truly quantitative analytical capability to characterize nanometer scale particles in metallic materials, thus its application to the microstructural analysis in multi-component metallic materials provides critical information on the mechanism of nanoscale microstructural evolution. In this study, the procedure for 3D APT specimen preparation was established, and those for dissimilar metal weld interface were prepared near the fusion boundary by a focused ion beam. The result of the analysis in this study showed the precipitation of chromium carbides near the fusion boundary between A533 Gr. B and Alloy 152.

• Journal of Life Science
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• v.7 no.4
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• pp.282-288
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• 1997

To obtain a basic information on the development of Genus Viola, ultrastructure and electrofusion process between the two protoplasts from wild Viola callus cells and pansy mesophyll cells were observed with a scanning electron microscopy(SEM) and transmission electron microscopy(TEM). In the ultrastructural observation of wild viola callus protoplasts and pansy mesophyll protoplasts using SEM, their cell walls were removed completely. A knob-like formation was observed on the enlarge surface of viola callus protoplasts. On the surface of pansy mesophyll protoplasts net-like chloroplasts were observed. In SEM observation of pansy mesophyll protoplasts, chloroplasts devoid of membrane were observed on the surface the protoplasts. Pearl chain was formed by applying AC field of 200 V/cm at 1.0 MHz for 43 sec. The lysis of plasma membranes and fusion process occurred by applying a 1,600 V/cm DC pulse twice for 1 sec. After 1-2 hours of a DC pulse application, it was observed that the two protoplasts were fused completely into one cell. In TEM observation of the fused cell, many small vacuoles were located in the fusion area of the two protoplasts. Indeed, two distinct regions were observed during fusing process; in one region, a nucleus was found, while in the other region, both nucleus and nucleous were found.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1179-1191
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• 2019

We design an ingenious view-pooling method named learning-based multiple pooling fusion (LMPF), and apply it to multi-view convolutional neural network (MVCNN) for 3D model classification or retrieval. By this means, multi-view feature maps projected from a 3D model can be compiled as a simple and effective feature descriptor. The LMPF method fuses the max pooling method and the mean pooling method by learning a set of optimal weights. Compared with the hand-crafted approaches such as max pooling and mean pooling, the LMPF method can decrease the information loss effectively because of its "learning" ability. Experiments on ModelNet40 dataset and McGill dataset are presented and the results verify that LMPF can outperform those previous methods to a great extent.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2151-2161
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• 2021

Nuclear data (ND) sensitivity and uncertainty (S/U) quantification in shielding applications is performed using deterministic and probabilistic approaches. In this paper the validation of the newly developed deterministic program package ASUSD (ADVANTG + SUSD3D) is presented. ASUSD was developed with the aim of automating the process of ND S/U while retaining the computational efficiency of the deterministic approach to ND S/U analysis. The paper includes a detailed description of each of the programs contained within ASUSD, the computational workflow and validation results. ASUSD was validated on two shielding benchmark experiments from the Shielding Integral Benchmark Archive and Database (SINBAD) - the fission relevant ASPIS Iron 88 experiment and the fusion relevant Frascati Neutron Generator (FNG) Helium Cooled Pebble Bed (HCPB) Test Blanket Module (TBM) mock-up experiment. The validation process was performed in two stages. Firstly, the Denovo discrete ordinates transport solver was validated as a standalone solver. Secondly, the ASUSD program package as a whole was validated as a ND S/U analysis tool. Both stages of the validation process yielded excellent results, with a maximum difference of 17% in final uncertainties due to ND between ASUSD and the stochastic ND S/U approach. Based on these results, ASUSD has proven to be a user friendly and computationally efficient tool for deterministic ND S/U analysis of shielding geometries.

• Korean Journal of Artificial Intelligence
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• v.11 no.3
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• pp.17-22
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• 2023

In this paper, we propose a black ice detection system using Convolutional Neural Networks (CNNs). Black ice poses a serious threat to road safety, particularly during winter conditions. To overcome this problem, we introduce a CNN-based architecture for real-time black ice detection with an encoder-decoder network, specifically designed for real-time black ice detection using thermal images. To train the network, we establish a specialized experimental platform to capture thermal images of various black ice formations on diverse road surfaces, including cement and asphalt. This enables us to curate a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Additionally, in order to enhance the accuracy of black ice detection, we propose a multi-scale dilation convolution feature fusion (MsDC-FF) technique. This proposed technique dynamically adjusts the dilation ratios based on the input image's resolution, improving the network's ability to capture fine-grained details. Experimental results demonstrate the superior performance of our proposed network model compared to conventional image segmentation models. Our model achieved an mIoU of 95.93%, while LinkNet achieved an mIoU of 95.39%. Therefore, it is concluded that the proposed model in this paper could offer a promising solution for real-time black ice detection, thereby enhancing road safety during winter conditions.