• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.743-744
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• 2016

Due to the many amenities of a modern power with solar power and green energy alternative to injury by cutting down on the number of solar energy and pollution and environmental factors. There is still much research and trying to incorporate a variety of applications. In this paper, create a daytime energy by fusing solar panels and billboards, and at night has the advantage that you can save more energy used to sign by the sign serves also and at the same time energy acts like a tent when the day by using the power usage is expected to be higher.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2005.11a
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• pp.415-420
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• 2005

This paper presents the two lossless auxiliary inductors-assisted voltage source type half bridge (single ended push pull: SEPP) series resonant high frequency inverter for induction heated king roller in copy and printing machines. The simple high-frequency inverter treated here can completely achieve stable zero current soft switching (ZCS) commutation for wide its output power regulation ranges and load variations under its constant high frequency pulse density modulation (PDM) scheme. Its transient and steady state operating principle is originally described and discussed for a constant high-frequency PDM control strategy under a stable ZCS operation commutation, together with its output effective power regulation characteristics-based on the high frequency PDM strategy. The experimental operating performances of this voltage source SEPP ZCS-PDM series resonant high frequency inverter using IGBTs are illustrated as compared with computer simulation results and experimental ones. Its power losses analysis and actual efficiency are evaluated and discussed on the basis of simulation and experimental results. The feasible effectiveness of this high frequency inverter appliance implemented here is proved from the practical point of view.

• Journal of the Korean Chemical Society
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• v.15 no.4
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• pp.191-197
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• 1971

Ruthenium content in highly purified palladium metal (99.9%) was determined by counting $^{105}Rh$ nuclide which was produced by $^{104}Ru(n,{\gamma};{\beta}^-)^{105}Rh$ nuclear reaction. Palladium sample and ruthenium standard were irradiated by neutron with the Pneumatic Transfer System of TRIGA MARK II reactor. Palladium and ruthenium were dissolved by treating with aqua-regia and by fusing with sodium peroxide flux respectively. $^{105}Rh$ was separated through anion and cation exchange resin columns. The ruthenium content was determined by comparing the $^{105}Rh$ activities, obtained from the palladium sample, with that from pure ruthenium standard. The detection limit of ruthenium by the present method is about 1 ppm of ruthenium in 10 mg of palladium, which is approximately 40 times more sensitive than that of the conventional radioactivation method which employs $^{102}Ru(n,{\gamma})^{103}Ru$ nuclear reaction.

• Korean Chemical Engineering Research
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• v.57 no.3
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• pp.432-437
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• 2019

An atmospheric pressure floating electrode-dielectric barrier discharge (FE-DBD) system having flexible electrodes was developed and its plasma characteristics was investigated. Polytetrafluoroethylene (PTFE), polydiemethylsiloxane (PDMS), and polyethylene terephthalate (PET) were used as flexible dielectrics for flexible powered-electrodes. The optical intensity and electron temperature of the atmospheric pressure FE-DBD plasma increased with the voltage applied to the powered electrode, and increased in the order of PTFE < PDMS < PET at a fixed voltage. This behavior was explained in terms of the change in the capacitance of the flexible dielectrics with the dielectric type and voltage, implying that the plasma characteristics of an atmospheric pressure FE-DBD having flexible electrodes can be controlled by modulating the flexible dielectrics for the flexible powered-electrode and the voltage applied to the powered electrode. Because an atmospheric pressure FE-DBD system can generate a plasma along the curvature of skins, it is expected to have useful applications in plasma medicine.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.1-15
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• 2022

The MobileNetV3 is specially designed for mobile devices with limited memory and computing power. To reduce the network parameters and improve the network inference speed, a new lightweight network is proposed based on MobileNetV3. Firstly, to reduce the computation of residual blocks, a partial residual structure is designed by dividing the input feature maps into two parts. The designed partial residual structure is used to replace the residual block in MobileNetV3. Secondly, a dual-path feature extraction structure is designed to further reduce the computation of MobileNetV3. Different convolution kernel sizes are used in the two paths to extract feature maps with different sizes. Besides, a transition layer is also designed for fusing features to reduce the influence of the new structure on accuracy. The CIFAR-100 dataset and Image Net dataset are used to test the performance of the proposed partial residual structure. The ResNet based on the proposed partial residual structure has smaller parameters and FLOPs than the original ResNet. The performance of improved MobileNetV3 is tested on CIFAR-10, CIFAR-100 and ImageNet image classification task dataset. Comparing MobileNetV3, GhostNet and MobileNetV2, the improved MobileNetV3 has smaller parameters and FLOPs. Besides, the improved MobileNetV3 is also tested on CPU and Raspberry Pi. It is faster than other networks

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5465-5470
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• 2012

FPGA(Field Programmable Gate Array) devices are widely used due to their merits in circuit development time, and development cost. Among various FPGA technologies, SRAM-based FPGAs have large cell capacity so that they are attractive for complex circuit design and their reconfigurability. However, they are weak in space environment where radiation energy particles cause Single Event Upset(SEU). In this paper, we designed a controller supervising SRAM-based FPGA to protect configuration memory inside. The controller is implemented on an Anti-Fusing FPGA. Radiation test was performed on the implemented computer board and the result show that our controller provides better SEU-resilience than TMR-only system.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.1
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• pp.62-68
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• 2016

The fingerprint, which is one of the methods of indoor localization using WiFi, has been frequently studied because of its ability to be implemented via wireless access points. This method has low positioning resolution and high computational complexity compared to other methods, caused by its dependence of reference points in the radio map. In order to compensate for these problems, this paper presents a radio map designed algorithm based on the log-distance path loss model fusing a WiFi and BLE fingerprint. The proposed algorithm designs a radio map with variable values using the log-distance path loss model and reduces distance errors using a median filter. The experimental results of the proposed algorithm, compared with existing fingerprinting methods, show that the accuracy of positioning improved by from 2.747 m to 2.112 m, and the computational complexity reduced by a minimum of 33% according to the access points.

• Smart Structures and Systems
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• v.33 no.1
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• pp.55-64
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• 2024

This paper proposes a fusion imaging-based coating-defect classification method for steel structures that uses zero-shot learning. In the proposed method, a halogen lamp generates heat energy on the coating surface of a steel structure, and the resulting heat responses are measured by an infrared (IR) camera, while photos of the coating surface are captured by a charge-coupled device (CCD) camera. The measured heat responses and visual images are then analyzed using zero-shot learning to classify the coating defects, and the estimated coating defects are visualized throughout the inspection surface of the steel structure. In contrast to older approaches to coating-defect classification that relied on visual inspection and were limited to surface defects, and older artificial neural network (ANN)-based methods that required large amounts of data for training and validation, the proposed method accurately classifies both internal and external defects and can classify coating defects for unobserved classes that are not included in the training. Additionally, the proposed model easily learns about additional classifying conditions, making it simple to add classes for problems of interest and field application. Based on the results of validation via field testing, the defect-type classification performance is improved 22.7% of accuracy by fusing visual and thermal imaging compared to using only a visual dataset. Furthermore, the classification accuracy of the proposed method on a test dataset with only trained classes is validated to be 100%. With word-embedding vectors for the labels of untrained classes, the classification accuracy of the proposed method is 86.4%.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.109-116
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• 2020

With the advent of high-speed railways, railways are one of the most frequently used means of transportation at home and abroad. In addition, in terms of environment, carbon dioxide emissions are lower and energy efficiency is higher than other transportation. As the interest in railways increases, the issue related to railway safety is one of the important concerns. Among them, visual abnormalities occur when various obstacles such as animals and people suddenly appear in front of the railroad. To prevent these accidents, detecting rail tracks is one of the areas that must basically be detected. Images can be collected through cameras installed on railways, and the method of detecting railway rails has a traditional method and a method using deep learning algorithm. The traditional method is difficult to detect accurately due to the various noise around the rail, and using the deep learning algorithm, it can detect accurately, and it combines the two algorithms to detect the exact rail. The proposed algorithm determines the accuracy of railway rail detection based on the data collected.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.201-209
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• 2019

This study aimed to find out the morphological evolution process for future vision of world smart city. The contents and methods of study was divided and compared by 4 continents and Korea focused on the convergence numbers of ET and IT in smart city and did correlation analysis and analysis of convergence number in device/technology by periods. The analysis materials were 32 cases of smart city in whole world and times were 4 periods. The results of study were listed below. First, the smart city in period 1 was morphological evolutions preserved environment and kept natural form of existing city and filled up device/technology. Second, the smart city in period 2 was morphological evolutions through ET-centric development. Third, the smart city in period 3 was morphological evolutions through advancement of ET and device/technology related to production of energy. Forth, the smart city in period 4 was morphological evolutions fusing, dissipating and creating new ET and IT through the advancement process of all technologies. In conclusion, morphological evolution of smart city will change systematic city structure of convergence form, not each discriminating development between ET and IT, and the forming of smart city will be evolved by repetitive convergence process of technologies continually.