• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2004.03a
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• pp.155-164
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• 2004

In order for studying pressure-coupled dynamic responses of droplet vaporization, open-loop experiment of an isolated droplet vaporization exposed to pressure perturbations in stagnant gaseous environment is numerically conducted, Governing equations are solved for flow parameters at gas and liquid phases separately and thermodynamic parameters at the interfacial boundary are matched for problem closure. For high-pressure effects, vapor-liquid interfacial thermodynamics is rigorously treated. A series of parametric calculations in terms of mean pressure level and wave frequencies are carried out employing a n-pentane droplet in stagnant gaseous nitrogen. Results show that wave instability in view of pressure-coupled vaporization response seems more susceptible at higher pressures and higher wave frequencies. Mass evaporation rate responding to pressure waves is amplified with increase in pressure due to substantial reduction in latent heat of vaporization. Augmentation of perturbation frequency also enhances amplification due to the reduction of phase differences between pressure perturbation and surface temperature fluctuation.

• Proceedings of the Korea Water Resources Association Conference
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• 2001.05b
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• pp.1133-1138
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• 2001

The focus of this paper is on the numerical investigation of obliquely incident wane interactions with a system composed of full submerged and floating dual buoy/vertical-flexible-membrane breakwaters placed in parallel with spacing. The fully submerged systems allow surface and bottom clearances to enable wave transmission over and under the system. The problem is formulated based on the two-dimensional multi-domain hydro-elastic linear wave-body interaction theory. The hydrodynamic interaction of oblique incident waves with the combination of the rigid and flexible bodies was solved by the distribution of the simple sources (modified Bessel function of fille second kind) tat satisfy the Helmholz governing equation. Using this computer program, the performance of various dual systems varying buoy radiuses and drafts, membrane lengths, clearances. spacing, mooring-lines stiffness, mooring types, water depth, and wave characteristics is thoroughly examined. It is found that the fully submerged and floating dual buoy/membrane breakwaters call, if it is properly tuned to the coming waves, have good performances ill reflecting the obliquely incident waves over a tilde range of wave frequency and headings.

• Journal of Information Processing Systems
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• v.19 no.2
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• pp.211-218
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• 2023

In order to improve the low accuracy of traditional wireless network health information retrieval methods, a wireless network health information retrieval method is designed based on data mining algorithm. The invalid health information stored in wireless network is filtered by data mapping, and the health information is clustered by data mining algorithm. On this basis, the high-frequency words of health information are classified to realize wireless network health information retrieval. The experimental results show that exactitude of design way is significantly higher than that of the traditional method, which can solve the problem of low accuracy of the traditional wireless network health information retrieval method.

• The Journal of Korea Robotics Society
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• v.18 no.2
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• pp.216-224
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• 2023

Guide robots that provide services in public places have recently emerged as a non-face-to-face solution with the spread of COVID-19 and are growing. However, most guide robots provide only the same level of intelligence and the same interaction in different and changing environments. Therefore, its usefulness is limited and customers' interest is quickly lost. To solve this problem, it is necessary to develop social intelligence that can improve the robot's environment and situational awareness performance, and to continuously maintain customer interest by providing personalized and situational services. In this study, we developed guide robot services based on social HRI components that provides multi-modal context-aware. We evaluated service usefulness by measuring user satisfaction and frequency of use of the service through the survey. We analyzed the service quality attributes to identify the differentiating factors of guide robot based on social HRI components.

• Steel and Composite Structures
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• v.46 no.3
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• pp.335-344
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• 2023

This investigation presents nonlinear free vibration of a carbon nanotube reinforced composite beam based on the Von Kármán nonlinearity and the Euler-Bernoulli beam theory The material properties of the structure is considered as made of a polymeric matrix by reinforced carbon nanotubes according to different material distributions. The governing equations of the nonlinear vibration problem is delivered by using Hamilton's principle and the Galerkin's decomposition technique is utilized to discretize the governing nonlinear partial differential equation to nonlinear ordinary differential equation and then is solved by using of multiple time scale method. The nonlinear natural frequency and the nonlinear free response of the system is obtained with the effect of different patterns of reinforcement.

• Earthquakes and Structures
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• v.24 no.2
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• pp.111-126
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• 2023

Highly reliable and versatile methods artificial intelligence (AI) have found multiple application in the different fields of science, engineering and health care system. In the present study, we aim to utilize AI method to investigated vibrations in the human leg bone. In this regard, the bone geometry is simplified as a thick cylindrical shell structure. The deep neural network (DNN) is selected for prediction of natural frequency and critical buckling load of the bone cylindrical model. Training of the network is conducted with results of the numerical solution of the governing equations of the bone structure. A suitable optimization algorithm is selected for minimizing the loss function of the DNN. Generalized differential quadrature method (GDQM), and Hamilton's principle are used for solving and obtaining the governing equations of the system. As well as this, in the results section, with the aid of AI some predictions for improving the behaviors of the various sport systems will be given in detail.

• Advances in nano research
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• v.13 no.4
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• pp.341-350
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• 2022

The continuous elements method, also known as the dynamic stiffness method, is effective for solving structural dynamics problems, especially over a large frequency range. Before applying this method to fluid-structure interactions, it is advisable to check its validity for pure acoustics, without considering the different coupling parameters. This paper describes a procedure for taking wave propagation into account in the formulation of a Dynamic Stiffness Matrix. The procedure is presented in the context of the harmonic response of acoustic pressure. This development was validated by comparing the harmonic response calculations performed using the continuous element model with the analytical solution. In addition, this paper illustrates the application of this method to a simple compressible flow problem, since it has been applied solely to structural problems to date.

• The Journal of Information Systems
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• v.32 no.4
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• pp.189-210
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• 2023

Purpose This study aims to investigate factors that positively influence the continuous Artificial Intelligence(AI) Learning Continuity of business major students. Design/methodology/approach To evaluate the impact of AI education, a survey was conducted among 119 business-related majors who completed a software/AI course. Frequency analysis was employed to examine the general characteristics of the sample. Furthermore, factor analysis using Varimax rotation was conducted to validate the derived variables from the survey items, and Cronbach's α coefficient was used to measure the reliability of the variables. Findings Positive correlations were observed between business major students' AI Learning Continuity and their AI Interest, AI Awareness, and Data Analysis Capability related to their majors. Additionally, the study identified that AI Project Awareness and AI Literacy Capability play pivotal roles as mediators in fostering AI Learning Continuity. Students who acquired problem-solving skills and related technologies through AI Projects Awareness showed increased motivation for AI Learning Continuity. Lastly, AI Self-Efficacy significantly influences students' AI Learning Continuity.

• Journal of Drive and Control
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• v.20 no.4
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• pp.54-63
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• 2023

High and intermittent loading cycles induce fatigue damage to transmission components, resulting in premature gearbox failure. To identify gearbox defects, numerous vibration-based diagnostics techniques, using several artificial intelligence (AI) algorithms, have recently been presented. In this paper, an optimized deep belief network (DBN) model for gearbox problem diagnosis was designed based on time-frequency visual pattern identification. To optimize the hyperparameters of the model, a particle swarm optimization (PSO) approach was integrated into the DBN. The proposed model was tested on two gearbox datasets: a wind turbine gearbox and an experimental gearbox. The optimized DBN model demonstrated strong and robust performance in classification accuracy. In addition, the accuracy of the generated datasets was compared using traditional ML and DL algorithms. Furthermore, the proposed model was evaluated on different partitions of the dataset. The results showed that, even with a small amount of sample data, the optimized DBN model achieved high accuracy in diagnosis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.653-669
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• 2024

Dynamic scene deblurring is a complex computer vision problem owing to its difficulty to model mathematically. In this paper, we present a novel approach for image deblurring with the help of the sharp reference image, which utilizes the reference image for high-quality and high-frequency detail results. To better utilize the clear reference image, we develop an encoder-decoder network and two novel modules are designed to guide the network for better image restoration. The proposed Reference Extraction and Aggregation Module can effectively establish the correspondence between blurry image and reference image and explore the most relevant features for better blur removal and the proposed Spatial Feature Fusion Module enables the encoder to perceive blur information at different spatial scales. In the final, the multi-scale feature maps from the encoder and cascaded Reference Extraction and Aggregation Modules are integrated into the decoder for a global fusion and representation. Extensive quantitative and qualitative experimental results from the different benchmarks show the effectiveness of our proposed method.