• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1644-1649
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• 2019

With the rapid development of mobile communication systems, various mobile convergence services are appearing and data traffic is exploding accordingly. Because the number of base stations to support these surging devices is also increasing, from a network provider's point of view, reducing energy consumption through these mobile communication networks is one of the most important issues. Therefore, in this paper, we apply the DBSCAN (density-based spatial clustering of applications with noise) algorithm, one of the representative user-density based clustering algorithms, in order to extract the dense area with user density and apply the thinning process to each extracted sub-network to efficiently control the mode of the base stations. Extensive simulations show that the proposed algorithm has better performance results than the conventional algorithms with respect to area throughput and energy efficiency.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.135-140
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• 2022

Most machines are made of several types of . In particular, the shaft system of the ship consists of the brass of the propeller blade and the stainless steel of the shaft. When dissimilar the electrolyte solution of seawater, a voltaic cell and a shaft electromotive force is generated. This electromotive force causes electrical corrosion of the bearing and shaft supporting the shaft system. prevent this corrosion, a shaft grounding system is installed in ships. As for the experimental method, various information acquired by designing a program to periodically measure the electromotive force of the controllable pitchpropeller) system using an A/D converter of NI. This study analyzed the generation and characteristics of accumulator electromotive force for CPP and considered the installation location of the grounding system to remove the accumulator electromotive force.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.42-52
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• 2022

North Korea continues to upgrade and display its long-range rocket launchers to emphasize its military strength. Recently Republic of Korea kicked off the development of anti-artillery interception system similar to Israel's "Iron Dome", designed to protect against North Korea's arsenal of long-range rockets. The system may not work smoothly without the function assigning interceptors to incoming various-caliber artillery rockets. We view the assignment task as a dynamic weapon target assignment (DWTA) problem. DWTA is a multistage decision process in which decision in a stage affects decision processes and its results in the subsequent stages. We represent the DWTA problem as a Markov decision process (MDP). Distance from Seoul to North Korea's multiple rocket launchers positioned near the border, limits the processing time of the model solver within only a few second. It is impossible to compute the exact optimal solution within the allowed time interval due to the curse of dimensionality inherently in MDP model of practical DWTA problem. We apply two reinforcement-based algorithms to get the approximate solution of the MDP model within the time limit. To check the quality of the approximate solution, we adopt Shoot-Shoot-Look(SSL) policy as a baseline. Simulation results showed that both algorithms provide better solution than the solution from the baseline strategy.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.157-166
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• 2022

In the case of a die-casting process, defects that are difficult to confirm by visual inspection, such as shrinkage bubbles, may occur due to an error in maintaining a vacuum state. Since these casting defects are discovered during post-processing operations such as heat treatment or finishing work, they cannot be taken in advance at the casting time, which can cause a large number of defects. In this study, we propose an approach that can predict the occurrence of casting defects by defect type using machine learning technology based on casting parameter data collected from equipment in the die casting process in real time. Die-casting parameter data can basically be collected through the casting equipment controller. In order to perform classification analysis for predicting defects by defect type, labeling of casting parameters must be performed. In this study, first, the defective data set is separated by performing the primary clustering based on the total defect rate obtained during the post-processing. Second, the secondary cluster analysis is performed using the defect rate by type for the separated defect data set, and the labeling task is performed by defect type using the cluster analysis result. Finally, a classification learning model is created by collecting the entire labeled data set, and a real-time monitoring system for defect prediction using LabView and Python was implemented. When a defect is predicted, notification is performed so that the operator can cope with it, such as displaying on the monitoring screen and alarm notification.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.5
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• pp.84-94
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• 1996

In order to prevent shell sticking by providing sufficient lubrication between the strand and the mold, the mold oscillation has been used. Now it is well known that the shape of the oscillation curve has a decisive effect on the surface quality of the cast product. Besides, oscillation parameters such as stroke and frequency are also very important. In order to guarantee that parameters which have been found to be optimal for a certain grade of steel do not change with time, periodical checks of the physical condition of the whole equipment are necessary. The portable mold oscillation analyzer with integrated computer, developed by POSCO, records the movement of the mold in every spatial direction. The system uses the gap sensors to measure the mold movement (displacement ) in the two horizontal directions according to the mold narrow and broad faces and the vertical strokes in the four corners of mold. The gap sensor is a non-contacting minute displacement measuring device using the principle of high frequency eddy current loss. The mold oscillation diagnosis system integrates the gap sensors, their converters and the industrial portable computer with plug-in data acquisition boards. The all programs, such as the fast Fourier transformation module (amplitude and phase spectrums) and harmonic analysis module, was coded by LabVIEW$^{TM}$ software as the graphical language. In an own 'expert module' which is included in the diagnosis program, one can obtain much information about the mold oscillation equipment.

• Journal of the Korean Society of Safety
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• v.38 no.5
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• pp.1-7
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• 2023

This study analyzes the operational characteristics of 311 aged and non-aged residual current circuit breakers (RCCBs) in low-voltage consumer contexts. It investigates the influence of external temperature and harmonics based on the rated current multiples. To simulate temperature variations, a convectional oven was used around the circuit breakers. Additionally, the generation of harmonic reference signals and data measurement for overcurrent experiments were conducted using NI SCXI, myDAQ, and LabVIEW. An observation revealed that as the ambient temperature increased, the operating time of RCCBs decreased in the time delay region. This was attributed to the faster response or bending of the bimetal, which is the tripping element. However, aged RCCBs encountered challenges with tripping outside the protective curve. The operating time of the circuit breakers exhibited an acceleration influenced by the order and content of harmonic currents, potentially leading to malfunctions. Aged RCCBs demonstrated faster operating times than their non-aged counterparts. However, the difference in operating time varied based on the manufacturer's and operating environment of the RCCBs. Frequent malfunctions of RCCBs can result in power outages. In cases where these circuit breakers fail to operate, they can lead to secondary damages, including electrical fires and shocks. Consequently, it is imperative to consider the operating environment of RCCBs and provide appropriate replacement cycles to mitigate these risks.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.37 no.2
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• pp.175-181
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• 2024

In electrical power substations, bulky iron-core potential transformers (PTs) are installed in a tank of gas-insulated switchgear (GIS) to measure system voltages. This paper proposed a low-power voltage transformer (LPVT) that can replace the conventional iron-core PTs in response to the demand for the digitalization of substations. The prototype LPVT consists of a capacitive voltage divider (CVD) which is embedded in a spacer and an impedance matching circuit using passive components. The CVD was fabricated with a flexible PCB to acquire enough insulation performance and withstand vibration and shock during operation. The performance of the LPVT was evaluated at 80%, 100%, and 120% of the rated voltage (38.1 kV) according to IEC 61869-11. An accuracy correction algorithm based on LabVIEW was applied to correct the voltage ratio and phase error. The corrected voltage ratio and phase error were +0.134% and +0.079 min., respectively, which satisfies the accuracy CL 0.2. In addition, the voltage ratio of LPVT was analyzed in ranges of -40~+40℃, and a temperature correction coefficient was applied to maintain the accuracy CL 0.2. By applying the LPVT proposed in this paper to the same rating GIS, it can be reduced the length per GIS bay by 11%, and the amount of SF6 by 5~7%.

• Progress in Medical Physics
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• v.23 no.1
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• pp.8-14
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• 2012

In order to develop a Patient respiratory management system includinga biofeedback function for4-dimentional radiation therapy, this study investigated anoptimal tracking algorithmfor moving target using IR (Infra-red) camera as well as commercial camera. A tracking system was developed by LabVIEW 2010. Motion phantom images were acquired using a camera (IR or commercial). After image process were conducted to convert acquired image to binary image by applying a threshold values, several edge enhance methods such as Sobel, Prewitt, Differentiation, Sigma, Gradient, Roberts, were applied. The targetpattern was defined in the images, and acquired image from a moving targetwas tracked by matching pre-defined tracking pattern. During the matching of imagee, thecoordinateof tracking point was recorded. In order to assess the performance of tracking algorithm, the value of score which represents theaccuracy of pattern matching was defined. To compare the algorithm objectively, we repeat experiments 3 times for 5 minuts for each algorithm. Average valueand standard deviations (SD) of score were automatically calculatedsaved as ASCII format. Score of threshold only was 706, and standard deviation was 84. The value of average and SD for other algorithms which combined edge detection method and thresholdwere 794, 64 in Sobel, 770, 101 in Differentiation, 754, 85 in Gradient, 763, 75 in Prewitt, 777, 93 in Roberts, and 822, 62 in Sigma, respectively. According to score analysis, the most efficient tracking algorithm is the Sigma method. Therefore, 4-dimentional radiation threapy is expected tobemore efficient if threshold and Sigma edge detection method are used together in target tracking.

• Proceedings of the Ginseng society Conference
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• 2007.12a
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• pp.57-58
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• 2007

Purpose: Ginseng is a well-known medical plant used in traditional Oriental medicine. Korean red ginseng (KRG) has been known to have potent biological activities such as radical scavenging, vasodilating, anti-tumor and anti-diabetic activities. However, the mechanism of the beneficial effects of KRG on diabetes is yet to be elucidated. The present study was designed to investigate the anti-diabetic effect and mechanism of KRG extract in C57BL/KsJ db/db mice. Methods: The db/db mice were randomly divided into six groups: diabetic control group (DC), red ginseng extract low dose group (RGL, 100 mg/kg), red ginseng extract high dose group (RGH, 200 mg/kg), metformin group (MET, 300 mg/kg), glipizide group (GPZ, 15 mg/kg) and pioglitazone group (PIO, 30 mg/kg), and treated with drugs once per day for 10 weeks. During the experiment, body weight and blood glucose levels were measured once every week. At the end of treatment, we measured Hemoglobin A1c (HbA1c), blood glucose, insulin, triglyceride (TG), adiponectin, leptin, non-esterified fatty acid (NEFA). Morphological analyses of liver, pancreas and white adipose tissue were done by histological observation through hematoxylin-eosin staining. Pancreatic islet insulin and glucagon levels were detected by double-immunofluorescence staining. To elucidate an action of mechanism of KRG, DNA microarray analyses were performed, and western blot and RT-PCR were conducted for validation. Results: Compared to the DC group mice, body weight gain of PIO treated group mice showed 15.2% increase, but the other group mice did not showed significant differences. Compared to the DC group, fasting blood glucose levels were decreased by 19.8% in RGL, 18.3% in RGH, 67.7% in MET, 52.3% in GPZ, 56.9% in PIO-treated group. With decreased plasma glucose levels, the insulin resistance index of the RGL-treated group was reduced by 27.7% compared to the DC group. Insulin resistance values for positive drugs were all markedly decreased by 80.8%, 41.1% and 68.9%, compared to that of DC group. HbA1c levels in RGL, RGH, MET, GPZ and PIO-treated groups were also decreased by 11.0%, 6.4%, 18.9%, 16.1% and 27.9% compared to that of DC group, and these figure revealed a similar trend shown in plasma glucose levels. Plasma TG and NEFA levels were decreased by 18.8% and 16.8%, respectively, and plasma adiponectin and leptin levels were increased by 20.6% and 12.1%, respectively, in the RGL-treated group compared to those in DC group. Histological analysis of the liver of mice treated with KRG revealed a significantly decreased number of lipid droplets compared to the DC group. The control mice exhibited definitive loss and degeneration of islet, whereas mice treated with KRG preserved islet architecture. Compared to the DC group mice, KRG resulted in significant reduction of adipocytes. From the pancreatic islet double-immunofluorescence staining, we observed KRG has increased insulin production, but decreased glucagon production. KRG treatment resulted in stimulation of AMP-activated protein kinase (AMPK) phosphorylation in the db/db mice liver. To elucidate mechanism of action of KRG extract, microarray analysis was conducted in the liver tissue of mice treated with KRG extract, and results suggest that red ginseng affects on hepatic expression of genes responsible for glycolysis, gluconeogenesis and fatty acid oxidation. In summary, multiple administration of KRG showed the hypoglycemic activity and improved glucose tolerance. In addition, KRG increased glucose utilization and improved insulin sensitivity through inhibition of lipogenesis and activation of fatty acid $\beta$-oxidation in the liver tissue. In view of our present data, we may suggest that KRG could provide a solid basis for the development of new anti-diabetic drug.

• Journal of Science and Technology Studies
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• v.19 no.3
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• pp.247-289
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• 2019

By examining the experiences of three social economy organizations who participated in the social problem-solving R&D projects, we discuss the conditions which may encourage the participation of civil society in national R&D programs in South Korea. By calling for the inclusion of social economy organizations along with the living-lab, the social problem-solving R&D projects introduced a new type of civic participation in the national R&D programs. It is the requirement in the RFP of the social problem-solving R&D which led PIs to inviting social economy organizations into their projects. But the invites occurred rather abruptly and accidently without adequate mutual understanding between scientific experts and social economy organizations. While helping social economy organizations participate in R&D processes, this form of institutional arrangement also led them into a position in subordination to scientific experts. Social economy organizations were supposed to coordinate the living lab in the social problem-solving R&D projects which they felt familiar as an extension of what they have been doing. In contrast, they felt administrative work such as accounts following complicate administrative rules as the most unfamiliar challenge. The difference in their emphases between scientific experts and social economy organizations was also evident. Social economy organizations viewed that, while they and ordinary people are primarily interested in a practical use of the developed products or services, scientific experts tend to focus on research and development. Not only did such difference produce a friction in the R&D processes but also it had social economy organizations view the R&D projects they participated in as unsuccessful. Nevertheless, all these experiences provided a great opportunity for the social economy organizations for learning and growing as a new actor in the national R&D.