• The Journal of Society for e-Business Studies
• /
• v.24 no.1
• /
• pp.1-16
• /
• 2019

Recently, since responding to meteorological changes depending on increasing greenhouse gas and electricity demand, the importance prediction of photovoltaic power (PV) is rapidly increasing. In particular, the prediction of PV power generation may help to determine a reasonable price of electricity, and solve the problem addressed such as a system stability and electricity production balance. However, since the dynamic changes of meteorological values such as solar radiation, cloudiness, and temperature, and seasonal changes, the accurate long-term PV power prediction is significantly challenging. Therefore, in this paper, we propose PV power prediction model based on deep learning that can be improved the PV power prediction performance by learning to use meteorological and seasonal information. We evaluate the performances using the proposed model compared to seasonal ARIMA (S-ARIMA) model, which is one of the typical time series methods, and ANN model, which is one hidden layer. As the experiment results using real-world dataset, the proposed model shows the best performance. It means that the proposed model shows positive impact on improving the PV power forecast performance.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.5
• /
• pp.612-620
• /
• 2019

The increasing use of curved beams in buildings, vehicles, ships, and aircraft has results in considerable effort being directed toward developing an accurate method for analyzing the dynamic behavior of such structures. The stability behavior of elastic curved beams has been the subject of a large number of investigations. Solutions of the relevant differential equations have traditionally been obtained by the standard finite difference. These techniques require a great deal of computer time as the number of discrete nodes becomes relatively large under conditions of complex geometry and loading. One of the efficient procedures for the solution of partial differential equations is the method of differential quadrature. The differential quadrature method(DQM) has been applied to a large number of cases to overcome the difficulties of the complex algorithms of programming for the computer, as well as excessive use of storage due to conditions of complex geometry and loading. In this study, the in-plane extensional vibration for asymmetric curved beams with linearly varying cross-section is analyzed using the DQM. Fundamental frequency parameters are calculated for the member with various parameter ratios, boundary conditions, and opening angles. The results are compared with the result by other methods for cases in which they are available. According to the analysis of the solutions, the DQM, used only a limited number of grid points, gives results which agree very well with the exact ones.

• Asian-Australasian Journal of Animal Sciences
• /
• v.32 no.5
• /
• pp.721-733
• /
• 2019

Objective: The objectives of this study were to investigate the thermal gelation properties and molecular forces of actomyosin extracted from two classes of chicken breast meat qualities (normal and pale, soft and exudative [PSE]-like) during heating process to further improve the understanding of the variations of functional properties between normal and PSE-like chicken breast meat. Methods: Actomyosin was extracted from normal and PSE-like chicken breast meat and the gel strength, water-holding capacity (WHC), protein loss, particle size and distribution, dynamic rheology and protein thermal stability were determined, then turbidity, active sulfhydryl group contents, hydrophobicity and molecular forces during thermal-induced gelling formation were comparatively studied. Results: Sodium dodecyl sulphate-polyacrylamide gel electrophoresis showed that protein profiles of actomyosin extracted from normal and PSE-like meat were not significantly different (p>0.05). Compared with normal actomyosin, PSE-like actomyosin had lower gel strength, WHC, particle size, less protein content involved in thermal gelation forming (p<0.05), and reduced onset temperature ($T_o$), thermal transition temperature ($T_d$), storage modulus (G') and loss modulus (G"). The turbidity, reactive sulfhydryl group of PSE-like actomyosin were higher when heated from $40^{\circ}C$ to $60^{\circ}C$. Further heating to $80^{\circ}C$ had lower transition from reactive sulfhydryl group into a disulfide bond and surface hydrophobicity. Molecular forces showed that hydrophobic interaction was the main force for heat-induced gel formation while both ionic and hydrogen bonds were different significantly between normal and PSE-like actomyosin (p<0.05). Conclusion: These changes in chemical groups and inter-molecular bonds affected protein-protein interaction and protein-water interaction and contributed to the inferior thermal gelation properties of PSE-like meat.

• Journal of the Korean Society of Propulsion Engineers
• /
• v.25 no.1
• /
• pp.1-11
• /
• 2021

POGO is a dynamic axial instability phenomenon that occurs in liquid-propelled rockets. As the natural frequencies of the fuselage and those of the propellant supply system become closer, the entire system will become unstable. To predict POGO, the propellant (oxidant and fuel) tank in the first stage is modeled as a shell element, and the remaining components, the engine and the upper part, are modeled as mass-spring, and structural analysis is performed. The transmission line model is used to predict the pressure and flow perturbation of the propellant supply system. In this paper, the closed-loop transfer function is constructed by integrating the fuselage structure and fluid modeling as described above. The pogo suppressor consists of a branch pipe and an accumulator that absorbs pressure fluctuations in a passive manner and is located in the middle of the propellant supply system. The design parameters for its design optimization to suppress the decay phenomenon are set as the diameter, length of the branch pipe, and accumulator. Multiple-objective function optimization is performed by setting the energy minimization of the closed loop transfer function in terms of to the mass of the pogo suppressor and that of the propellant as the objective function.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.22 no.1
• /
• pp.43-56
• /
• 2012

Wireless sensor networks consist of numerous small-sized nodes equipped with limited computing power and storage as well as energy-limited disposable batteries. In this networks, nodes are deployed in a large given area and communicate with each other in short distances via wireless links. For energy efficient networks, dynamic clustering protocol is an effective technique to achieve prolonged network lifetime, scalability, and load balancing which are known as important requirements. this technique has a characteristic that sensing data which gathered by many nodes are aggregated by cluster head node. In the case of cluster head node is exposed by attacker, there is no guarantee of safe and stable network. Therefore, for secure communications in such a sensor network, it is important to be able to encrypt the messages transmitted by sensor nodes. Especially, cluster based sensor networks that are designed for energy efficient, strongly recommended suitable key management and authentication methods to guarantee optimal stability. To achieve secured network, we propose a key management scheme which is appropriate for hierarchical sensor networks. Proposed scheme is based on polynomial key pool pre-distribution scheme, and sustain a stable network through key authentication process.

• Journal of the Korean Geosynthetics Society
• /
• v.20 no.1
• /
• pp.1-8
• /
• 2021

In urban areas, structures are installed deep underground in the lower part of the structure to utilize space. Therefore, a retaining wall is used to prevent earth pressure from the ground when constructing a structure. Due to the development of construction technology, retaining wall applied to excavation work are used to prevent danger such as falling rocks and landslides in temporary facilities when construction or retaining walls are installed. In general, the application of a retaining wall to a temporary facility during the embankment construction is the case of expanding an existing roads or railways. Therefore, it is necessary to study the retaining wall applied to the embankment construction such as the double-track site of the high-speed railway. In this study, two types of common one row H-pile retaining wall and two types of IER retaining wall were analyzed, and the stability of the retaining wall applied to the construction of double-track of the high-speed railway was analyzed. The earth retaining wall is a construction method that combines forced pile applied to the stabilization of the slope with the wall of the earth retaining wall. As a result of the analysis, the IER retaining wall had maximum lateral displacement of 19.0% compared to the type with H-plie installed only in the front while dynamic load was applied. In addition, the slower the speed of high-speed railway, the more displacement occurred, and the results show that more caution is needed when designing the ground in low-speed sections.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.1
• /
• pp.9-17
• /
• 2021

Curved beams are increasingly used in buildings, vehicles, ships, and aircraft, which has resulted in considerable effort being directed toward developing an accurate method for analyzing the dynamic behavior of such structures. The stability behavior of elastic circular arches has been the subject of a large number of investigations. One of the efficient procedures for the solution of ordinary differential equations or partial differential equations is the differential quadrature method DQM. This method has been applied to a large number of cases to overcome the difficulties of the complex computer algorithms, as well as excessive use of storage due to conditions of non-linear geometries, loadings, or material properties. This study uses DQM to analyze the in-plane vibration of the circular arches considering the effects of midsurface extension and rotatory inertia. Fundamental frequency parameters are calculated for the member with various parameter ratios, boundary conditions, and opening angles. The solutions from DQM are compared with exact solutions or other numerical solutions for cases in which they are available and given to analyze the effects of midsurface extension and rotatory inertia on the frequency parameters of the circular arches.

• Journal of the Korean Recycled Construction Resources Institute
• /
• v.9 no.1
• /
• pp.109-116
• /
• 2021

In order to replace mineral aggregate used as road pavement materials with steel slag aggregate, this present study evaluated mechanical properties of SMA Concrete mixtures using steel slag aggregate as oxidized slag from electric furnace in iron works. The variables of this experiment are the aggregate type of mineral and steel slag and the sieve sized of 10mm and 13mm. The physical properties inclu ding the specific gravity and absorption rate etc. of the slag aggregate mixtu res satisfied the KS standard as asphalt mixtu re. As a resu lt of evalu ating the mechanical properties of the asphalt mixtures, the optimum asphalt content of the slag aggregate mixtures were lower than that of the mineral aggregate mixtures, but other quality standards were all satisfied. In the deformation strength evaluation, the slag aggregate mixtures were measu red slightly higher than that of the mineral aggregate mixtu res, and the dynamic stability test satisfied the 2,000pass/mm standard value in all specimens. And, the moduli of resilient of the slag aggregate mixtures showed an improved value compared with the mineral aggregate mixtures. Therefore, as the resilient rate of the slag aggregate mixtures improved, it is speculated that there will be an effect of improving public performance according to the repeated traffic load of the vehicle.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.27 no.1
• /
• pp.13-21
• /
• 2021

The purpose of this study is to develop the ship valuation model by utilizing the neural network model. The target of the valuation was secondhand VLCC. The variables were set as major factors inducing changes in the value of ship through prior research, and the corresponding data were collected on a monthly basis from January 2000 to August 2020. To determine the stability of subsequent variables, a multi-collinearity test was carried out and finally the research structure was designed by selecting six independent variables and one dependent variable. Based on this structure, a total of nine simulation models were designed using linear regression, neural network regression, and random forest algorithm. In addition, the accuracy of the evaluation results are improved through comparative verification between each model. As a result of the evaluation, it was found that the most accurate when the neural network regression model, which consist of a hidden layer composed of two layers, was simulated through comparison with actual VLCC values. The possible implications of this study first, creative research in terms of applying neural network model to ship valuation; this deviates from the existing formalized evaluation techniques. Second, the objectivity of research results was enhanced from a dynamic perspective by analyzing and predicting the factors of changes in the shipping. market.

• Journal of Ginseng Research
• /
• v.45 no.2
• /
• pp.228-235
• /
• 2021

Backgroud: Ginsenoside compound K (GK) is a major metabolite of protopanaxadiol-type ginsenosides and has remarkable anticancer activities in vitro and in vivo. This work used an ionic cross-linking method to entrap GK within O-carboxymethyl chitosan (OCMC) nanoparticles (Nps) to form GK-loaded OCMC Nps (GK-OCMC Nps), which enhance the aqueous solubility and stability of GK. Methods: The GK-OCMC Nps were characterized using several physicochemical techniques, including x-ray diffraction, transmission electron microscopy, zeta potential analysis, and particle size analysis via dynamic light scattering. GK was released from GK-OCMC Nps and was conducted using the dialysis bag diffusion method. The effects of GK and GK-OCMC Nps on PC3 cell viability were measured by using the 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide assay. Fluorescent technology based on Cy5.5-labeled probes was used to explore the cellular uptake of GK-OCMC Nps. Results: The GK-OCMC NPs had a suitable particle size and zeta potential; they were spherical with good dispersion. In vitro drug release from GK-OCMC NPs was pH dependent. Moreover, the in vitro cytotoxicity study and cellular uptake assays indicated that the GK-OCMC Nps significantly enhanced the cytotoxicity and cellular uptake of GK toward the PC3 cells. GK-OCMC Nps also significantly promoted the activities of both caspase-3 and caspase-9. Conclusion: GK-OCMC Nps are potential nanocarriers for delivering hydrophobic drugs, thereby enhancing water solubility and permeability and improving the antiproliferative effects of GK.