• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.465-470
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• 2020

Complex materials are widely used in aviation industries where lightweighting is essential because they have lighter properties than metals. However, composite materials can cause defects such as internal void formation, poor adhesive mixing, and non-adhesive parts during the production process, and there is a risk of micro-cracking and interlayer separation due to low energy impact. Therefore, a structural damage test is essential. As a result, structural integrity monitoring using FBG is drawing attention. Compared to conventional electrical sensors, FBG has the advantage of being more corrosion-resistant and multiplexed without being affected by electrical noise. However, interloggers measuring FBG are expensive and have a large disadvantage because they are made on the premise of measuring large structures. In this paper, low-cost interloggers were designed for use in unmanned or small aircraft using optical switche, WDM filter, and LTFs, and compared to conventional high-priced interrogator.

• Journal of Microbiology and Biotechnology
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• v.32 no.5
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• pp.564-574
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• 2022

Microbial diversity in the soil is responsive to changes in soil composition. However, the impact of soil amendments on the diversity and structure of rare and abundant sub-communities in agricultural systems is poorly understood. We investigated the effects of different Chinese herb residue (CHR) soil amendments and cropping systems on bacterial rare and abundant sub-communities. Our results showed that the bacterial diversity and structure of these sub-communities in soil had a specific distribution under the application of different soil amendments. The CHR soil amendments with high nitrogen and organic matter additives significantly increased the relative abundance and stability of rare taxa, which increased the structural and functional redundancy of soil bacterial communities. Rare and abundant sub-communities also showed different preferences in terms of bacterial community composition, as the former was enriched with Bacteroidetes while the latter had more Alphaproteobacteria and Betaproteobacteria. All applications of soil amendments significantly improved soil quality of newly created farmlands in whole maize cropping system. Rare sub-communitiy genera Niastella and Ohtaekwangia were enriched during the maize cropping process, and Nitrososphaera was enriched under the application of simple amendment group soil. Thus, Chinese medicine residue soil amendments with appropriate additives could affect soil rare and abundant sub-communities and enhance physicochemical properties. These findings suggest that applying soil composite amendments based on CHR in the field could improve soil microbial diversity, microbial redundancy, and soil fertility for sustainable agriculture on the Loess Plateau.

• Smart Media Journal
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• v.11 no.5
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• pp.48-55
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• 2022

Tomato crops are easy to expose to disease and spread in a short period of time, so late measures against disease are directly related to production and sales, which can cause damage. Therefore, there is a need for a service that enables early prevention by simply and accurately diagnosing tomato diseases in the field. In this paper, we construct a system that applies a deep learning-based model in which ImageNet transition is learned in advance to classify and serve nine classes of tomatoes for disease and normal cases. We use the input of MobileNet, ResNet, with a deep learning-based CNN structure that builds a lighter neural network using a composite product for the image set of leaves classifying tomato disease and normal from the Plant Village dataset. Through the learning of two proposed models, it is possible to provide fast and convenient services using MobileNet with high accuracy and learning speed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.5
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• pp.367-379
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• 2022

In this paper, a multilayer radar absorbing structure was designed using the Particle Swarm Optimization (PSO) algorithm, and the characteristics of the multilayer radar absorbing structure were analyzed. It was shown that design values can be derived quickly and accurately by applying PSO to the design of a multilayer radar absorbing structure, and it is also shown that the optimal multilayer radar absorbing structure can be designed especially for an oblique incident. In addition, it was shown that the optimal value that meets the performance requirements can be determined even in a combination of various design parameters. It is presented through a comprehensive flowchart including the equations and detailed descriptions of all variables for each step. From the results of this paper, it is possible to omit complex and many calculations for designing a multilayer radar absorbing structure, and it is possible to use various composite materials. It can be utilized in the design and development of multilayer radar absorbing structures.

• Composites Research
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• v.35 no.6
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• pp.469-476
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• 2022

In this paper, the microwave absorbing characteristics after the impact of the radar-absorbing structure (RAS) consisting of periodic pattern sheet (PPS) and glass fiber-reinforced plastic (GFRP) were experimentally investigated. The fabricated RAS effectively absorbed the microwave in the X-band (8.2-12.4 GHz). In order to induce the damage to the RAS, a low-velocity impact test with various impact energy of 15, 40, and 60 J was conducted. Afterward, the impact damage was observed by using visual inspection, non-destructive test, and image processing method. Moreover, the absorbing performance of intact and damaged RAS was measured by the free-space measurement system. The experiment results revealed that the delamination damage from the impact energy of 15 J did not considerably affect the microwave absorbing performance of the RAS. However, fiber breakage and penetration damage with a relatively large damaged area were occuured when the impact energy was increased up to 40 J and 60 J, and these failures significantly degraded the microwave absorbing characteristics of the RAS.

• Steel and Composite Structures
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• v.44 no.2
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• pp.241-254
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• 2022

The cables in a cable-stayed bridge are critical load-carrying parts. The potential damage to cables should be identified early to prevent disasters. In this study, an efficient deep learning model is proposed for the damage identification of cables using both a multi-layer perceptron (MLP) and a graph neural network (GNN). Datasets are first generated using the practical advanced analysis program (PAAP), which is a robust program for modeling and analyzing bridge structures with low computational costs. The model based on the MLP and GNN can capture complex nonlinear correlations between the vibration characteristics in the input data and the cable system damage in the output data. Multiple hidden layers with an activation function are used in the MLP to expand the original input vector of the limited measurement data to obtain a complete output data vector that preserves sufficient information for constructing the graph in the GNN. Using the gated recurrent unit and set2set model, the GNN maps the formed graph feature to the output cable damage through several updating times and provides the damage results to both the classification and regression outputs. The model is fine-tuned with the original input data using Adam optimization for the final objective function. A case study of an actual cable-stayed bridge was considered to evaluate the model performance. The results demonstrate that the proposed model provides high accuracy (over 90%) in classification and satisfactory correlation coefficients (over 0.98) in regression and is a robust approach to obtain effective identification results with a limited quantity of input data.

• Steel and Composite Structures
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• v.42 no.6
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• pp.805-826
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• 2022

The free and live load-forced vibration behaviour of porous functionally graded (PFG) higher order nanobeams in the thermal and magnetic fields is investigated comprehensively through this work in the framework of nonlocal strain gradient theory (NLSGT). The porosity effects on the dynamic behaviour of FG nanobeams is investigated using four different porosity distribution models. These models are exploited; uniform, symmetrical, condensed upward, and condensed downward distributions. The material characteristics gradation in the thickness direction is estimated using the power-law. The magnetic field effect is incorporated using Maxwell's equations. The third order shear deformation beam theory is adopted to incorporate the shear deformation effect. The Hamilton principle is adopted to derive the coupled thermomagnetic dynamic equations of motion of the whole system and the associated boundary conditions. Navier method is used to derive the analytical solution of the governing equations. The developed methodology is verified and compared with the available results in the literature and good agreement is observed. Parametric studies are conducted to show effects of porosity parameter; porosity distribution, temperature rise, magnetic field intensity, material gradation index, non-classical parameters, and the applied moving load velocity on the vibration behavior of nanobeams. It has been showed that all the analyzed conditions have significant effects on the dynamic behavior of the nanobeams. Additionally, it has been observed that the negative effects of moving load, porosity and thermal load on the nanobeam dynamics can be reduced by the effect of the force induced from the directed magnetic field or can be kept within certain desired design limits by controlling the intensity of the magnetic field.

• Steel and Composite Structures
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• v.41 no.5
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• pp.761-773
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• 2021

This study presents a 3D non-linear finite element (FE) assessment of dynamic soil-structure interaction (SSI). The numerical investigation has been performed on the time domain through a Finite Element (FE) system, while considering the nonlinear behavior of soil and the multi-directional nature of genuine seismic events. Later, the FE outcomes are analyzed to the recorded in-situ free-field and structural movements, emphasizing the numerical model's great result in duplicating the observed response. In this work, the soil response is simulated using an isotropic hardening elastic-plastic hysteretic model utilizing HSsmall. It is feasible to define the non-linear cycle response from small to large strain amplitudes through this model as well as for the shift in beginning stiffness with depth that happens during cyclic loading. One of the most difficult and unexpected tasks in resolving soil-structure interaction concerns is picking an appropriate ground motion predicted across an earthquake or assessing the geometrical abnormalities in the soil waves. Furthermore, an artificial neural network (ANN) has been utilized to properly forecast the non-linear behavior of soil and its multi-directional character, which demonstrated the accuracy of the ANN based on the RMSE and R² values. The total result of this research demonstrates that complicated dynamic soil-structure interaction processes may be addressed directly by passing the significant simplifications of well-established substructure techniques.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.81-94
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• 2022

Real estate and artworks were considered challenging investment targets for individual investors because of their relatively high average transaction price despite their long investment history. Recently, the so-called fractional investment, generally known as investing in a share of the ownership right for real-life assets, etc., and most investors perceive that they actually own a piece (fraction) of the ownership right through their investments, is gaining popularity. Founded in 2016, Musicow started the first service that allows users to invest in copyright fees related to music distribution. Using the LSTM algorithm, one of the deep learning algorithms, this research predict the price of right to participate in copyright fees traded in Musicow. In addition to variables related to claims such as transfer price, transaction volume of claims, and copyright fees, comprehensive indicators indicating the market conditions for music copyright fees participation, exchange rates reflecting economic conditions, KTB interest rates, and Korea Composite Stock Index were also used as variables. As a result, it was confirmed that the LSTM algorithm accurately predicts the transaction price even in the case of fractional investment which has a relatively low transaction volume.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.2
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• pp.1-13
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• 2022

Agrivoltaic facility is the composite system that the solar panel is installed above the farmland, and it enables crop and electricity production simultaneously. Solar panels of the agrivoltaic facilities can block and reduce the amount of solar irradiance arriving at the farmland, but it can help the crop growth by preventing excessive solar irradiance. Therefore, to clarify how the agrivoltaic facilities affect the crop growth, precise solar irradiance distribution under the solar panel should be modeled. In this study, PAR (photosynthetically active radiation), radiation from 400 to 700 nm, which crops usually use to grow, was extracted from the total irradiance and its distribution model under various conditions was developed. Monthly irradiance distributions varied because the elevation of the sun was changed over time, which made the position changed that the local maximum and minimum irradiance appear. The higher panel height did not cause any significant difference in the amount of irradiance reaching below the solar panel, but its distribution became more uniform. Furthermore, the panel angles with the most irradiance arriving below the solar panel were different by month, but its difference was up to 2%p between the irradiance with 30° angle which is usually recommended in Korea. Finally, the interval between panels was adjusted; when the ratio of the length of the panel to the empty space was 1:2, the irradiance of 0.719 times was reached compared to when there was no panel, 0.579 times for 1:1 and 0.442 times for 2:1.