• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.2
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• pp.329-338
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• 2021

This study predicts the amount of wind power generation for rational operation plan of wind power generation and capacity calculation of ESS. For forecasting, we present a method of predicting wind power generation by combining a physical approach and a statistical approach. The factors of wind power generation are analyzed and variables are selected. By collecting historical data of the selected variables, the amount of wind power generation is predicted using deep learning. The model used is a hybrid model that combines a bidirectional long short term memory (LSTM) and a convolution neural network (CNN) algorithm. To compare the prediction performance, this model is compared with the model and the error which consist of the MLP(:Multi Layer Perceptron) algorithm, The results is presented to evaluate the prediction performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4041-4059
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• 2019

Key establishment method based on channel reciprocity for time division duplex (TDD) system has earned a vital consideration in the majority of recent research. While most of the cellular systems rely on frequency division duplex (FDD) systems, especially the 5G network, which is not characterized by the channel reciprocity feature. This paper realizes the generation of a group secret key for multi-terminals communicated through a wireless network in FDD mode, by utilizing the nature of the physical layer for the wireless links between them. I consider a new group key generation approach, which using bitwise XOR with a modified pairwise secret key generation approach not based on the channel reciprocity feature. Precisely, this multi-node secret key agreement technique designed for three wireless network topologies: 1) the triangle topology, 2) the multi-terminal star topology, and 3) the multi-node chain topology. Three multi-node secret key agreement protocols suggest for these wireless communication topologies in FDD mode, respectively. I determine the upper bound for the generation rate of the secret key shared among multi-node, for the three multi-terminals topologies, and give numerical cases to expose the achievement of my offered technique.

• Wind and Structures
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• v.28 no.2
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• pp.111-128
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• 2019

In this paper an octagon plan shaped building (study building) in presence of three square plan shaped building is subjected to boundary layer wind flow and the interference effects on the study building is investigated using Computational fluid dynamics. The variation of the pressure coefficients on different faces of the octagon building is studied both in isolated and interference conditions. Interference Factors (IF) are calculated for different faces of the study building which can be a powerful tool for designing similar plan shaped buildings in similar conditions. A metamodel of the IF, in terms of the distances among buildings is also established using Response Surface Method (RSM). This set of equations are optimized to get the optimum values of the distances where the IF is unity. An upstream Interference zone for this building setup and wind environment is established from these data. Uncertainty principle is also utilised to determine the optimum positions of the interfering buildings considering the uncertain nature of wind flow for minimum interference effect. The proposed procedure is observed to be computationally efficient in deciding optimum layout at buildings often required in city planning. The results show that the proposed RSM-based optimization approach captures the interference zone accurately with substantially less number of experiments.

• Journal of Auto-vehicle Safety Association
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• v.11 no.2
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• pp.29-34
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• 2019

This paper presents a new method for construction of a static obstacle map. A static obstacle is important since it is utilized to path planning and decision. Several established approaches generate static obstacle map by grid method and counting algorithm. However, these approaches are occasionally ineffective since the density of LiDAR layer is low. Our approach solved this problem by applying probability theory. First, we converted all LiDAR point to Gaussian distribution to considers an uncertainty of LiDAR point. This Gaussian distribution represents likelihood of obstacle. Second, we modeled dynamic transition of a static obstacle map by adopting the Hidden Markov Model. Due to the dynamic characteristics of the vehicle in relation to the conditions of the next stage only, a more accurate map of the obstacles can be obtained using the Hidden Markov Model. Experimental data obtained from test driving demonstrates that our approach is suitable for mapping static obstacles. In addition, this result shows that our algorithm has an advantage in estimating not only static obstacles but also dynamic characteristics of moving target such as driving vehicles.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.51-62
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• 2021

Plant disease is one of the issues that can create losses in the production and economy of the agricultural sector. Early detection of this disease for finding solutions and treatments is still a challenge in the sustainable agriculture field. Currently, image processing techniques and machine learning methods have been applied to detect plant diseases successfully. However, the effectiveness of these methods still needs to be improved, especially in multiclass plant diseases classification. In this paper, a convolutional neural network with a batch normalization-based deep learning approach for classifying plant diseases is used to develop an automatic diagnostic assistance system for leaf diseases. The significance of using deep learning technology is to make the system be end-to-end, automatic, accurate, less expensive, and more convenient to detect plant diseases from their leaves. For evaluating the proposed model, an experiment is conducted on a public dataset contains 20654 images with 15 plant diseases. The experimental validation results on 20% of the dataset showed that the model is able to classify the 15 plant diseases labels with 96.4% testing accuracy and 0.168 testing loss. These results confirmed the applicability and effectiveness of the proposed model for the plant disease detection task.

• Journal of Sensor Science and Technology
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• v.31 no.1
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• pp.41-44
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• 2022

In this study, we have fabricated and characterized vertical double-gate (DG) InGaAs tunnel field-effect-transistors (TFETs) with Al₂O₃/HfO₂ = 1/5 nm bi-layer gate dielectric by employing a top-down approach. The device exhibited excellent characteristics including a minimum subthreshold swing of 60 mV/decade, a maximum transconductance of 141 µS/㎛, and an on/off current ratio of over 10³ at 20℃. Although the TFETs were fabricated using a dry etch-based top-down approach, the values of DIBL and hysteresis were as low as 40 mV/V and below 10 mV, respectively. By evaluating the effects of constant voltage and hot carrier injection stress on the vertical DG InGaAs TFET, we have identified the dominant charge trapping mechanism in TFETs.

• Geomechanics and Engineering
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• v.30 no.1
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• pp.1-10
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• 2022

Seismic ground response evaluation is one of the main issues in geotechnical earthquake engineering. These analyses are subsequently divided into one-, two- and three-dimensional methods, and each of which can perform in time or frequency domain. In this study, a novel approach is proposed to assess the seismic site response using two-dimensional transfer functions in frequency domain analysis. Using the proposed formulation, a program is written in MATLAB environment and then promoted utilizing the equivalent linear approach. The accuracy of the written program is evaluated by comparing the obtained results with those of actual recorded data in the Gilroy region during Loma Prieta (1989) and Coyote Lake (1979) earthquakes. In order to precise comparison, acceleration time histories, Fourier amplitude spectra and acceleration response spectra diagrams of calculated and recorded data are presented. The proposed 2D transfer function diagrams are also obtained using mentioned earthquakes which show the amount of amplification or attenuation of the input motion at different frequencies while passing through the soil layer. The results of the proposed method confirm its accuracy and efficiency to evaluate ground motion during earthquakes using two-dimensional model. Then, studies on irregular topographies are carried out, and diagrams of amplification factors are shown.

• Advances in materials Research
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• v.11 no.3
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• pp.171-190
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• 2022

In this paper, the problem of interfacial stresses in steel cantilever beams strengthened with bonded composite laminates is analyzed using linear elastic theory. The analysis is based on the deformation compatibility approach, where both the shear and normal stresses are assumed to be invariant across the adhesive layer thickness. The original study in this paper carried out an analytical solution to estimate shear and peel-off stresses, as, interfacial stress analysis concentration under the uniformly distributed load and shear lag deformation. The theoretical prediction is compared with authors solutions from numerous researches. This phenomenon of deformation of the members, which gives probably approach on the study of interface of the reinforced structures, is called "shear lag effect". The resolution in this paper shows that the shear stress and the normal stress are significant and, are concentrated at the end of the composite plate of reinforcement, called "edge effect". A parametric study is carried out to show the effects of the variables of design and the physical properties of materials. This research is helpful for the understanding on mechanical behaviour of the interface and design of such structures.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.3975-3984
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• 2022

Distributed control system architecture is adopted for I&C systems of Prototype Fast Breeder Reactor, where the geographically distributed control systems are connected to centralized servers & display stations via switched Ethernet networks. TCP/IP communication plays a significant role in the successful operations of this architecture. The communication tasks at control nodes are taken care by TCP/IP offload modules; local area switched network is realized using layer-2/3 switches, which are finally connected to network interfaces of centralized servers & display stations. Safety, security, reliability, and fault tolerance of control systems used for safety-related applications of nuclear power plants is ensured by indigenous design and qualification as per guidelines laid down by regulatory authorities. In the case of commercially available components, appropriate suitability analysis is required for getting the operation clearances from regulatory authorities. This paper details the proposed approach for the suitability analysis of TCP/IP communication nodes, including control systems at the field, network switches, and servers/display stations. Development of test platform using commercially available tools and diagnostics software engineered for control nodes/display stations are described. Each TCP link behavior with impaired packets and multiple traffic loads is described, followed by benchmarking of the network switch's routing characteristics and security features.

• Geomechanics and Engineering
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• v.34 no.5
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• pp.561-575
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• 2023

This study investigates to provide a fast solution to the problem of bearing capacity in layered soils with easily obtainable parameters that does not require the use of any charts or calculations of different parameters. Therefore, a hybrid approach including both the finite element (FE) method and machine learning technique have been applied. Firstly, a FE model has been generated which is validated by the results of in-situ loading tests. Then, a total of 192 three-dimensional FE analyses have been performed. A data set has been created utilizing the soil properties, footing sizes, layered conditions used in the FE analyses and the ultimate bearing capacity values obtained from the FE analyses to be used in multigene genetic programming (MGGP). Problem has been modeled with five input and one output parameter to propose a bearing capacity formula. Ultimate bearing capacity values estimated from the proposed formula using data set consisting of 20 data independent of total data set used in MGGP modelling have been compared to the bearing capacities calculated with semi-empirical methods. It was observed that the MGGP method yielded successful results for the problem considered. The proposed formula provides reasonable predictions and efficient enough to be used in practice.