• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.704-711
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• 2023

This paper discusses the control method of BLDC(Brushless Direct Current) motor that has similar electrical characteristics with DC motor but has improved its lifespan and reliability. The BLDC motor can improve durability and speed stability by using rotor position information to eliminate commutators that require mechanical contact with DC motors. In this study, a controller for a DC motor was designed based on the fact that the current in the windings of a BLDC motor is a square-wave current like the current flowing in the armature of a DC motor. Next, the designed controller was applied to a 3-phase BLDC motor to confirm the effectiveness of the controller. In detail, a single-phase DC motor with electrical parameter values of a three-phase BLDC motor was modeled and a PI controller for motor speed control was designed by applying the root locus method to the derived system. The speed control simulation of the DC motor was performed to confirm the validity of the controller, and the same controller was applied to the speed control of the 3-phase BLDC motor implemented in MATLAB. From the simulation, similar results of the DC motor were obtained in the 3 phase BLDC motor and confirmed the usefulness of the proposed control scheme.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.229-249
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• 2022

This paper investigates machine learning models for predicting the designation of administrative issues in the KOSDAQ market through various techniques. When a company in the Korean stock market is designated as administrative issue, the market recognizes the event itself as negative information, causing losses to the company and investors. The purpose of this study is to evaluate alternative methods for developing a artificial intelligence service to examine a possibility to the designation of administrative issues early through the financial ratio of companies and to help investors manage portfolio risks. In this study, the independent variables used 21 financial ratios representing profitability, stability, activity, and growth. From 2011 to 2020, when K-IFRS was applied, financial data of companies in administrative issues and non-administrative issues stocks are sampled. Logistic regression analysis, decision tree, support vector machine, random forest, and LightGBM are used to predict the designation of administrative issues. According to the results of analysis, LightGBM with 82.73% classification accuracy is the best prediction model, and the prediction model with the lowest classification accuracy is a decision tree with 71.94% accuracy. As a result of checking the top three variables of the importance of variables in the decision tree-based learning model, the financial variables common in each model are ROE(Net profit) and Capital stock turnover ratio, which are relatively important variables in designating administrative issues. In general, it is confirmed that the learning model using the ensemble had higher predictive performance than the single learning model.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.59-71
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• 2014

System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.9
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• pp.279-287
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• 2018

Sealants are an important element of modern architecture and serve as a building protection against weathering by providing barriers against ingress of moisture, air, and other materials. Exposure to a variety of environments often reduces lifespan due to changes in physical, chemical and mechanical characteristics, and UV, humidity, and temperature expansion are important issues that are directly related to durability. In this study, a combined deterioration test chamber was developed to simulate the environment of the open air as an instrument for verifying the durability of structural sealing materials indoors. In order to replicate special weather conditions, such as yellow dust, acid rain, and contamination by microorganisms, it was deemed impossible to replicate the outdoor environment by 100 %, and the results of the results of the results of the external exposure test of the structural sealant and the combined deterioration testing device. As a result of the displacement test of the outdoor exposure test, it was determined that the sealant was breaking apart and that it would be smooth, and the displacement would be up to three times greater than the initial material value of 1 year. The displacement test results of the combined deterioration test device show the tendency to deteriorate, decreasing the elasticity and tensile characteristics. In the case of denatured silicon, the current 400 cycles have been completed to confirm 12 months of degradation of the external exposure. The deformation of the test specimen cannot be verified with the naked eye, so it is considered that the conditions of the specimen are more stable than the silicon sealant. As a result of the outdoor exposure test, if the combined deterioration test device is structured and proposed in the relevant guidance or specification, the anticipated lifespan of 12 months in the actual use environment can be verified indoors and below 3 months later, economically.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.561-568
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• 2006

WPS(Wearable Personal Station) for next generation PC can define as a core terminal of 'Ubiquitous Computing' that include information processing and network function and overcome spatial limitation in acquisition of new information. As a way to acquire significant dynamic gesture data of user from haptic devices, traditional gesture recognizer based on desktop-PC using wire communication module has several restrictions such as conditionality on space, complexity between transmission mediums(cable elements), limitation of motion and incommodiousness on use. Accordingly, in this paper, in order to overcome these problems, we implement hand gesture recognition system using fuzzy algorithm and neural network for Post PC(the embedded-ubiquitous environment using blue-tooth module and WPS). Also, we propose most efficient and reasonable hand gesture recognition interface for Post PC through evaluation and analysis of performance about each gesture recognition system. The proposed gesture recognition system consists of three modules: 1) gesture input module that processes motion of dynamic hand to input data 2) Relational Database Management System(hereafter, RDBMS) module to segment significant gestures from input data and 3) 2 each different recognition modulo: fuzzy max-min and neural network recognition module to recognize significant gesture of continuous / dynamic gestures. Experimental result shows the average recognition rate of 98.8% in fuzzy min-nin module and 96.7% in neural network recognition module about significantly dynamic gestures.

• Journal of the Korean Society of Radiology
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• v.15 no.6
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• pp.781-788
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• 2021

Due to the high sensitivity to radiation, excessive exposure needs to be prevented by accurately measuring the dose irradiated to the skin during radiation therapy. Although clinical trials use dosimeters such as film, OSLD, TLD, glass dosimeter, etc. to measure skin dose, these dosimeters have difficulty in accurate dosimetry on skin curves. In this study, to solve these problems, we developed a skin dosimeter that can be attached according to human flexion and evaluated its response characteristics. For the manufacture of the dosimeter, lead oxide (PbO) with high atomic number (Z_Pb: 82, Z_O: 8) and density (9.53 g/cm³) and silicon binders that can bend according to human flexion were used. In the case of a dosimeter made of PbO material, the performance degradation has been prevented by using parylene and others due to the presence of degradation due to oxidation, but the previously used parylene is affected by bending, so a new form of passive layer was produced and applied to the skin dosimeter. The characteristic evaluation of the skin dosimeter was evaluated by analyzing SEM, reproducibility, and linearity. Through SEM analysis, bending was evaluated, reproducibility and linearity at 6 MeV energy were evaluated, and applicability was assessed with a skin dosimeter. As a result of observing the dosimeter surface through SEM analysis, the parylene passive layer PbO dosimeter with the positive layer raised to the parylene produced cracks on the surface when bent. On the other hand, no crack was observed in the silicon passive layer PbO dosimeter, which was raised to silicon passive layer. In the reproducibility measurement results, the RSD of the silicon passive layer PbO dosimeter was 1.47% which satisfied the evaluation criteria RSD 1.5% and the linearity evaluation results showed the R² value of 0.9990, which satisfied the evaluation criteria R² 9990. The silicon passive layer PbO dosimeter was evaluated to be applicable to skin dosimeters by demonstrating high signal stability, precision, and accuracy in reproducibility and linearity, without cracking due to bending.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9B
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• pp.610-618
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• 2005

As developed Internet and Computer Capability, Many Users take the many information through the network. So requirement of User that use to network was rapidly increased and become various. But it spend much time to accept user requirement on current network, so studied such as Active network for solved it. This Active node on Active network have the capability that stored and processed execution code aside from capability of forwarding packet on current network. So required execution code for executed packet arrived in active node, if execution code should not be in active node, have to take by request previous Action node and Code Server to it. But if this execution code take from previous active node and Code Server, bring to time delay by transport execution code and increased traffic of network and execution time. So, As used execution code stored in cache on active node, it need to increase execution time and decreased number of request. So, our paper suggest ANC caching technique that able to decrease number of execution code request and time of execution code by efficiently store execution code to active node. ANC caching technique may decrease the network traffic and execution time of code, to decrease request of execution code from previous active node.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1053-1066
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• 2020

Sulfur dioxide (SO₂) is primarily released through industrial, residential, and transportation activities, and creates secondary air pollutants through chemical reactions in the atmosphere. Long-term exposure to SO₂ can result in a negative effect on the human body causing respiratory or cardiovascular disease, which makes the effective and continuous monitoring of SO₂ crucial. In South Korea, SO₂ monitoring at ground stations has been performed, but this does not provide spatially continuous information of SO₂ concentrations. Thus, this research estimated spatially continuous ground-level SO₂ concentrations at 1 km resolution over South Korea through the synergistic use of satellite data and numerical models. A stacking ensemble approach, fusing multiple machine learning algorithms at two levels (i.e., base and meta), was adopted for ground-level SO₂ estimation using data from January 2015 to April 2019. Random forest and extreme gradient boosting were used as based models and multiple linear regression was adopted for the meta-model. The cross-validation results showed that the meta-model produced the improved performance by 25% compared to the base models, resulting in the correlation coefficient of 0.48 and root-mean-square-error of 0.0032 ppm. In addition, the temporal transferability of the approach was evaluated for one-year data which were not used in the model development. The spatial distribution of ground-level SO₂ concentrations based on the proposed model agreed with the general seasonality of SO₂ and the temporal patterns of emission sources.

• Journal of Animal Environmental Science
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• v.13 no.1
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• pp.13-20
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• 2007

Sawdust biofiltration is an emerging bio-technology for control of ammonia emissions including compost odors from composting of biological wastes. Although sawdust is widely used as a medium for bulking agent in composting system and for microbial attachment in biofiltration systems, the performance of agitated bed composting and sawdust biofiltration are not well established. A pilot-scale composting of hog manure amended with sawdust and sawdust biofiltration systems for practical operation were investigated using aerated and agitated rectangular reactor with compost turner and sawdust biofilter operated under controlled conditions, each with a working capacity of approximately $40m^3\;and\;4.5m^3$ respectively. These were used to investigate the effect of compost temperature, seed germination rate and the C/N ratio of the compost on ammonia emissions, compost maturity and sawdust biofiltration performance. Temperature profiles showed that the material in three runs had been reached to temperature of 55 to $65^{\circ}C$ and above. The ammonia concentration in the exhaust gas of the sawdust biofilter media was below the maximum average value as 45 ppm. Seed germination rate levels of final compost was maintained from 70 to 93% and EC values of the finished compost varied between 2.8 and 4.8 ds/m, providing adequate conditions for plant growth.