• Clean Technology
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• v.27 no.4
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• pp.277-290
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• 2021

A supercapacitor, also called an ultracapacitor or an electrochemical capacitor, stores electrochemical energy by the adsorption/desorption of electrolytic ions or a fast and reversible redox reaction at the electrode surface, which is distinct from the chemical reaction of a battery. A supercapacitor features high specific power, high capacitance, almost infinite cyclability (~ 100,000 cycle), short charging time, good stability, low maintenance cost, and fast frequency response. Supercapacitors have been used in electronic devices to meet the requirements of rapid charging/discharging, such as for memory back-up, and uninterruptible power supply (UPS). Also, their use is being extended to transportation and large industry applications that require high power/energy density, such as for electric vehicles and power quality systems of smart grids. In power generation using intermittent power sources such as solar and wind, a supercapacitor is configured in the energy storage system together with a battery to compensate for the relatively slow charging/discharging time of the battery, to contribute to extending the lifecycle of the battery, and to improve the system power quality. This article provides a concise overview of the principles, mechanisms, and classification of energy storage of supercapacitors in accordance with the electrode materials. Also, it provides a review of the status of recent research and patent, product, and market trends in supercapacitor technology. There are many challenges to be solved to meet industrial demands such as for high voltage module technologies, high efficiency charging, safety, performance improvement, and competitive prices.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.4
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• pp.44-57
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• 2019

Various studies have been conducted to solve traffic congestions in many metropolitan cities through accurate traffic flow prediction. Most studies are based on the assumption that past traffic patterns repeat in the future. Models based on such an assumption fall short in case irregular traffic patterns abruptly occur. Instead, the approaches such as predicting traffic pattern through big data analytics and artificial intelligence have emerged. Specifically, deep learning algorithms such as RNN have been prevalent for tackling the problems of predicting temporal traffic flow as a time series. However, these algorithms do not perform well in terms of long-term prediction. In this paper, we take into account various external factors that may affect the traffic flows. We model the correlation between the multi-dimensional context information with temporal traffic speed pattern using deep neural networks. Our model trained with the traffic data from TOPIS system by Seoul, Korea can predict traffic speed on a specific date with the accuracy reaching nearly 90%. We expect that the accuracy can be improved further by taking into account additional factors such as accidents and constructions for the prediction.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.7
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• pp.870-874
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• 2018

In the worst maritime accidents, people should abandon ship, but ship structures are narrow and complex and operation takes place on rough seas, so escape is not easy. In particular, passengers on cruise ships are untrained and varied, making evacuation prospects worse. In such a case, the evacuation management of the crew plays a very important role. If a rescuer enters a ship at distress and conducts rescue activities, which zones represent the most effective entry should be examined. Generally, crew and rescuers take the shortest route, but if an accident occurs along the shortest route, it is necessary to select the second-best alternative. To solve this situation, this study aims to calculate evacuation routes using Q-Learning of Reinforcement Learning, which is a machine learning technique. Reinforcement learning is one of the most important functions of artificial intelligence and is currently used in many fields. Most evacuation analysis programs developed so far use the shortest path search method. For this reason, this study explored optimal paths using reinforcement learning. In the future, machine learning techniques will be applicable to various marine-related industries for such purposes as the selection of optimal routes for autonomous vessels and risk avoidance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.16-22
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• 2019

Off-line programming and robot calibration through simulation are essential when setting up a robot in a robot automation production line. In this study, we developed a new robot calibration method to match the CAD data of the production line with the measurement data on the site using 3D scanner. The proposed method calibrates the robot using 3D point cloud data through Iterative Closest Point algorithm. Registration is performed in three steps. First, vertices connected by three planes are extracted from CAD data as feature points for registration. Three planes are reconstructed from the scan point data located around the extracted feature points to generate corresponding feature points. Finally, the transformation matrix is calculated by minimizing the distance between the feature points extracted through the ICP algorithm. As a result of applying the software to the automobile welding robot installation, the proposed method can calibrate the required accuracy to within 1.5mm and effectively shorten the set-up time, which took 5 hours per robot unit, to within 40 minutes. By using the developed system, it is possible to shorten the OLP working time of the car body assembly line, shorten the precision teaching time of the robot, improve the quality of the produced product and minimize the defect rate.

• Journal of Digital Convergence
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• v.17 no.8
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• pp.283-291
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• 2019

The aim of investigated the role of FABP5 in the hepatic lipogenesis and lipid metabolisms. Mice were overexpressed and silenced liver FABP5 using virus particles. Mice were fed a Western-type diet or regular chow for 1week and then sacrificed mouse after 24hr fasted. Liver homogenates were used for protein analysis by Western blot and mRNA levels by RT-PCR. Hepatic and serum lipids were analysed by thin-layer chromatography. Mice fed a Western-type or high saturated fat diet revealed large increases in FABP5 expression. However, FABP5 mRNA levels were drastically reduced under fasted. Hepatic TG was significantly increased FABP5-OEAV mice, but a significantly decreased hepatic free cholesterol under fed. The discovered a substantial decrease in hepatic TG mass with FABP5 silencing. In these data, presented evidence for an important role of FABP5 in hepatic lipogenesis and hepatic TG storage. FABP5 may also be a potential target in the treatment of NAFLD, metabolic syndrome, and obesity. Furthermore, studies to which transcription factors are involved in FABP5 expression and regulation.

• Journal of the Microelectronics and Packaging Society
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• v.25 no.4
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• pp.75-81
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• 2018

The effect of $Ar-N_2$ plasma treatment on Cu surface as one of solutions to realize reliable Cu-Cu wafer bonding was investigated. Structural characteristic of $Ar-N_2$ plasma treated Cu surface were analyzed using X-ray diffraction, X-ray photoelectron spectroscopy, atomic force microscope. Ar gas was used for a plasma ignition and to activate Cu surface by ion bombardment, and $N_2$ gas was used to protect the Cu surface from contamination such as -O or -OH by forming a passivation layer. The Cu specimen under high Ar partial pressure plasma treatment showed more copper oxide due to the activation on Cu surface, while Cu surface after high $N_2$ gas partial pressure plasma treatment showed less copper oxide due to the formation of Cu-N or Cu-O-N passivation layer. It was confirmed that nitrogen plasma can prohibit Cu-O formation on Cu surface, but nitrogen partial pressure in the $Ar-N_2$ plasma should be optimized for the formation of nitrogen passivation layer on the entire surface of Cu wafer.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.35-43
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• 2021

Citrus quality is generally determined by its sugar content and acidity. In particular, sugar content is a very important factor because it determines the taste of citrus. Currently, the most commonly used method of measuring citrus sugar content in farms is a portable juiced sugar meter and a non-destructive sugar meter. This method can be easily measured by individuals, but the accuracy of the sugar content is inferior to that of the citrus NongHyup official machine. In particular, there is an error difference of 0.5 Brix or more, which is still insufficient for use in the field. Therefore, in this paper, we propose an AI model that predicts the citrus sugar content of unmeasured days within the error range of 0.5 Brix or less based on the previously collected citrus sugar content and meteorological data (average temperature, humidity, rainfall, solar radiation, and average wind speed). In addition, it was confirmed that the prediction model proposed through performance evaluation had an mean absolute error of 0.1154 for Seongsan area and 0.1983 for the Hawon area in Jeju Island. Lastly, the proposed model supports an error difference of less than 0.5 Brix and is a technology that supports predictive measurement, so it is expected that its usability will be highly progressive.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.123-128
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• 2021

For accurate speed and current control in industrial applications, SRM (Switched Reluctance Motor) is very important to synchronize the stator phase excitation and rotor position in the drive due to its nature. In general, position sensors such as encoder and resolver are used to generate rotational force by exciting the stator winding according to the rotor position and to control the motor by using speed and position information. However, for these sensors, 1) the cost of the sensors is quite large in terms of price, so the proportion of the motor system to the total system cost is high. 2) In terms of mechanical, position sensors such as encoders and resolvers are attached to the stator to increase the size and weight. In conclusion, in order to drive the SRM, control based on the rotor position information should be basically performed, and it is important to design the SRM driving system according to the environment in consideration of the application field. Therefore, in this paper, we intend to study the driving and control characteristics of SRM through variable switching duty control by designing a low-cost analog driving device, deviating from the general control system using the conventional encoder and resolver.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.94-100
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• 2021

To improve the productivity of cargo containment construction for a membrane LNG carrier, it is important to shorten the installation period and process of the scaffolding system, which is a construction workbench of a cargo containment for a membrane LNG carrier. As an effective method, opinions are being gathered to enlarge the lifting unit from the existing two stages to eight stages. On the other hand, the stresses around the pin and hole will increase significantly because of the increase in lifting load according to the large size of the module. The purpose of this study was to establish a new large module-lifting plan by introducing TRIZ to solve these problems. This study adopted a method to utilize 40 inventive principles, which is one of the various problem-solving tools of TRIZ. First, technical contradictions were derived, the engineering parameters were selected. Second, efficient inventive principles were selected to overcome the technical contradictions using a contradiction matrix. Finally, the general and specific solutions were derived through the selected inventive principle, and structural analysis confirmed that the stress generated in the structure was low. The utility of TRIZ was confirmed by the successful lifting of large modules using the established lifting method.

• Journal of the Korean Society of Radiology
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• v.16 no.6
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• pp.761-769
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• 2022

Pads with high dielectric materials have been used in a variety of applications to locally improve the field sensitivity and homogeneity of RF pulses in clinical MRI studies. In this study, we aimed to improve such pads in consideration of the practical problems associated with the application of actual clinical images. A high permittivity pad to increase the attenuated B1 field strength was fabricated and tested in 7T MRI. Sim4Life simulation and experimental results show stronger and relatively uniform B1 near field. In order to improve the image quality in the whole cerebellum, known as a region with low sensitivity, a guide was made to reduce the mechanical change of the pad. In order to improve the wearing comfort, the pad was designed by dividing it into upper and lower parts. The facial pad showed an overall signal increase effect in areas such as the turbinate in the nasal cavity. Signal increase was expected in areas such as the frontal lobe and eyes, but the effect was either insignificant or it was difficult to see the effect in the imaging protocol. In conclusion, this paper showed a cerebellar-optimized pad with an improved nasal signal while maintaining its effectiveness.