• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1143-1150
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• 2023

The global climate crisis and the implementation of low-carbon policies have led to a growing interest in renewable energy and a growing number of related industries. Among them, solar power is attracting attention as a representative eco-friendly energy that does not deplete and does not emit pollutants or greenhouse gases. As a result, the supplement of solar power facility is increasing all over the world. However, solar power is easily affected by the environment such as geography and weather, so accurate solar power forecast is important for stable operation and efficient management. However, it is very hard to predict the exact amount of solar power using statistical methods. In addition, the conventional prediction methods have focused on only short- or long-term prediction, which causes to take long time to obtain various prediction models with different prediction horizons. Therefore, this study utilizes a many-to-many structure of a recurrent neural network (RNN) to integrate short-term and long-term predictions of solar power generation. We compare various RNN-based very short- and long-term prediction methods for solar power in terms of MSE and R² values.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.939-953
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• 2023

Shallow water equations (SWE) serve as fundamental equations governing the movement of the water. Traditional numerical approaches for solving these equations generally face various challenges, such as sensitivity to mesh generation, and numerical oscillation, or become more computationally unstable around shock and discontinuities regions. In this study, we present a novel approach that leverages the power of physics-informed neural networks (PINNs) to approximate the solution of the SWE. PINNs integrate physical law directly into the neural network architecture, enabling the accurate approximation of solutions to the SWE. We provide a comprehensive methodology for formulating the SWE within the PINNs framework, encompassing network architecture, training strategy, and data generation techniques. Through the results obtained from experiments, we found that PINNs could be an accurate output solution of SWE when its results were compared with the analytical method. In addition, PINNs also present better performance over the Artificial Neural Network. This study highlights the transformative potential of PINNs in revolutionizing water resources research, offering a new paradigm for accurate and efficient solutions to the SVE.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.400-405
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• 2023

Currently, inverted pendulums are being studied in many fields, including posture control of missiles, rockets, etc, and bipedal robots. In this study, the vertical posture control of the pendulum was studied by constructing a rotary inverted pendulum using a 256-pulse rotary encoder and a DC motor. In the case of nonlinear systems, complex algorithms and controllers are required, but a control method using the classic and relatively simple PID(Proportional Integral Derivation) algorithm was applied to the rotating inverted pendulum system, and a simple but desired method was studied. The rotating inverted pendulum system used in this study is a nonlinear and unstable system, and a PID controller using Microchip's dsPIC30F4013 embedded processor was designed and implemented in linear modeling. Usually, PID controllers are designed by combining one or two or more types, and have the advantage of having a simple structure compared to excellent control performance and that control gain adjustment is relatively easy compared to other controllers. In this study, the physical structure of the system was analyzed using mathematical methods and control for vertical balance of a rotating inverted pendulum was realized through modeling. In addition, the feasibility of controlling with a PID controller using a rotating inverted pendulum was verified through simulation and experiment.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.31-38
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• 2024

The digital phase-locked loop(DPLL) is one of the circuits composed of a digital detector, digital loop filter, voltage-controlled oscillator, and divider as a fundamental circuit, widely used in many fields such as electrical and circuit fields. A state estimator using various mathematical algorithms is used to improve the performance of a digital phase-locked loop. Traditional state estimators have utilized Kalman filters of infinite impulse response state estimators, and digital phase-locked loops based on infinite impulse response state estimators can cause rapid performance degradation in unexpected situations such as inaccuracies in initial values, model errors, and various disturbances. In this paper, we propose a two-layer Frobenius norm-based finite impulse state estimator to design a new digital phase-locked loop. The proposed state estimator uses the estimated state of the first layer to estimate the state of the first layer with the accumulated measurement value. To verify the robust performance of the new finite impulse response state estimator-based digital phase locked-loop, simulations were performed by comparing it with the infinite impulse response state estimator in situations where noise covariance information was inaccurate.

• Journal of Sensor Science and Technology
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• v.6 no.1
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• pp.35-42
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• 1997

The optical biosensor using the electrically controlled release of reactive reagent is developed for the detection of peroxide. Rapid degradation of polymer complex of PEOx and PMAA occurs as the applied current increases and thus released amount of HPA increases. The degradation velocity of polymer and the amount of HPA released are linearly proportional to the applied current. Peroxide is reacted with the released reagent by peroxidase and then the product, a fluorescent dimer DBDA, is formed. The monochromic light from light source (150W Xe arc ramp) excites the DBDA and the excited light is transmitted through an optical fiber to be detected by a photodiode array. The change of fluorescence intensity is related to the change of peroxide concentration. The peroxidase is entrapped in Ca-alginate get on the inner surface. The biosensor has the linear signal range of 0.025mM-10.mM peroxide. By applying the step function of peroxide, reproducibility of biosensor has been investigated. The mathematical model is constructed by the combination of enzyme kinetics with reactor flow model. Good agreement is obtained between the experimental result and model prediction in the sensor signal.

• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.869-874
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• 2005

In the recent years there has been an increase of service competition in the activity of product selling, especially in the extension of warranty coverage and qualify. The variables in connection with the service competition are not crisp, and required the expertise of the production line. It thus becomes all the more necessary to use subtler tools as decision supports. These problems are typical not only of product companies but also of financial organizations, credit institutions, insurance, which need predictions of credibility for firms or persons in which they have any kind of interest. A suitable approach for minimizing the risk is to use a knowledge-based system. Most often expert systems are not standalone programs, but are embedded into a larger application. The aim of this paper is to discuss an approach for developing an embedded fuzzy expert system with respect to the product selling policy, especially to present the decision system of automobile selling activity around the extension of warranty coverage and quality. We use the MATLAB tools which integrates computation, visualization, and programming in an easy-to-use environment where problems and solutions are expressed in familiar mathematical notation. Also, we present the API functions embedding into the existing application.

• Environmental and Resource Economics Review
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• v.13 no.4
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• pp.735-761
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• 2004

As a possible alternative to Traditional Discounted Cash Flow Method, "Option Pricing Model" has drawn academic attentions for the last a few decades. However, it has failed to replace traditional DCF method practically due to its mathematical complexity. This paper introduces an option pricing valuation model specifically adjusted for the natural resource development projects. We add market information and industry-specific features into the model so that the model remains objective as well as realistic after the adjustment. The following two features of natural resource development projects take central parts in model construction; product price is a unique source of cash flow's uncertainty, and the projects have cost structure from capital-intense industry, in which initial capital cost takes most part of total cost during the projects. To improve the adaptability of Option Pricing Model specifically to the natural resource development projects, we use Two-Factor Model and Long-term Asset Model for the analysis. Although the model introduced in this paper is still simple and reflects limited reality, we expect an improvement in applicability of option pricing method for the evaluation of natural resource development projects can be made through the process taken in this paper.

• Information Systems Review
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• v.16 no.2
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• pp.61-76
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• 2014

Recently, students have raised negative awareness of the test because of school records and irrational difficulty level of the College Scholastic Ability Test. They go so far as to commit suicide because of failure in entering school. It becomes a social problem and it is rising more and more interested in entering school. The educational game was created based on considering this social environment. Namely, students can enter university as playing online or mobile game through Enter Literacy Assessment game service. The Enter Literacy Assessment game service provides various tests which are math, english, science or essay that real university wants through online or mobile game. For this, general concept about Enter Literacy Assessment game service and characteristic establishment and limitation of existing research should be understood. The research refers to relationship between Self-Determination Theory which is the representative theory related with psychological desire of human intrinsic and Enter Literacy Assessment game service. Therefore, development of Enter Literacy assessment Serious Game is a new opportunity factor to take two dominants which are secure of university competitive power and excellent personnel and challenge for development of serious game.

• Journal of The Korean Association of Information Education
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• v.18 no.1
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• pp.13-23
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• 2014

For this paper, we developed a game-addiction therapy program for students with gaming addiction based on multiple intelligences (MI) and verified its effects. The participants were 54 elementary students selected through a game addiction test in Incheon City, Korea. We tested the students' MI to facilitate program development. the students with gaming addiction showed strengths in the Bodily-kinesthetic, Naturalist, and Spatial intelligences whilst showing weaknesses in the Logical-mathematical, Intrapersonal, and Interpersonal intelligences as opposed to normal students who had opposite results. We arranged the program around various gaming and playing activities to engage their stronger intelligences; we added activities to address their weakness (i.e., Logical-mathematical, Intrapersonal, and Interpersonal intelligences). This study has shown that this program lowered the game immersion level of the students and was helpful in turning their attention to other activities. There were significant differences between pretest and posttest game addiction scores (p<0.001). Their weekly gaming time and computer usage decreased rapidly. Satisfaction with the game addiction therapy program based on MI was very high.

• Korean Chemical Engineering Research
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• v.50 no.5
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• pp.850-859
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• 2012

Devolatilization is an important mechanism in the gasification and pyrolysis of woody biomass, and has to be accordingly considered in designing a gasifier. In order to describe the devolatilization process of wood particle, there have been proposed a number of empirical correlations based on experimental data. However, the correlations are limited to apply for various reaction conditions due to the complex nature of wood devolatilization. In this study, a simple model was developed for predicting the devolatilization of a wood particle in a fluidized bed reactor. The model considered the drying, shrinkage and heat generation of intra-particle for a spherical biomass. The influence of various parameters such as size, initial moisture content, heat transfer coefficient, kinetic model and temperature, was investigated. The devolatilization time linearly increased with increasing initial moisture content and size of a wood particle, whereas decreases with reaction temperature. There is no significant change of results when the external heat transfer coefficient is over 300 $W/m^2K$, and smaller particles are more sensitive to the outer heat transfer coefficient. Predicted results from the model show a similar tendency with the experimental data from literatures within a deviation of 10%.