• 한국정보전자통신기술학회논문지
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• 제11권6호
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• pp.658-663
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• 2018

본 논문에서는 콘텐츠 큐레이션 플랫폼의 성능평가 알고리즘을 제안하였다. 성능평가는 초기조건과 종료조건을 설정하고, 4개의 파라미터를 측정하여 수행하였다. 성능평가에 사용되는 파라미터는 서비스 응답속도, 응답결과 정확도, 분석결과 정밀도, 분석결과 재현율이다. 제안한 성능평가 알고리즘의 유효성을 확인하기 위해 118,738건의 데이터베이스를 직접 구축한 후, 인터넷에서 콘텐츠를 오픈하여 이를 클릭한 사용자 행위를 기반으로 실험을 수행하였다. 실험에 사용된 페이지 뷰는 6,975,365건이었다, 실험결과, 4개의 파라미터를 이용하면 콘텐츠 큐레이션 플랫폼의 종합평가와 단위 평가가 객관적으로 수행될 수 있음을 확인하였다.

• Structural Engineering and Mechanics
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• 제70권5호
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• pp.623-637
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• 2019

This paper analyzes the non-stationary vibration and super-harmonic resonances in nonlinear dynamic motion of viscoelastic nano-resonators. For this purpose, a new coupled size-dependent model is developed for a plate-shape nano-resonator made of nonlinear viscoelastic material based on modified coupled stress theory. The virtual work induced by viscous forces obtained in the framework of the Leaderman integral for the size-independent and size-dependent stress tensors. With incorporating the size-dependent potential energy, kinetic energy, and an external excitation force work based on Hamilton's principle, the viscous work equation is balanced. The resulting size-dependent viscoelastically coupled equations are solved using the expansion theory, Galerkin method and the fourth-order Runge-Kutta technique. The Hilbert-Huang transform is performed to examine the effects of the viscoelastic parameter and initial excitation values on the nanosystem free vibration. Furthermore, the secondary resonance due to the super-harmonic motions are examined in the form of frequency response, force response, Poincare map, phase portrait and fast Fourier transforms. The results show that the vibration of viscoelastic nanosystem is non-stationary at higher excitation values unlike the elastic ones. In addition, ignoring the small-size effects shifts the secondary resonance, significantly.

• Structural Engineering and Mechanics
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• 제70권4호
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• pp.431-443
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• 2019

The present paper illustrates a numerical investigation on the failure behaviour of ring-stiffened cylinder subjected to external hydrostatic pressure. The published test data of steel welded ring-stiffened cylinder are surveyed and collected. Eight test models are chosen for the verification of the modelling and FE analyses procedures. The imperfection as the consequences of the fabrication processes, such as initial geometric deformation and residual stresses due to welding and cold forming, which reduced the ultimate strength, are simulated. The results show that the collapse pressure and failure mode predicted by the nonlinear FE analyses agree acceptably with the experimental results. In addition, the failure mode parameter obtained from the characteristic pressure such as interframe buckling pressure known as local buckling pressure, overall buckling pressure, and yield pressure are also examined through the collected data and shows a good correlation. A parametric study is then conducted to confirm the failure progression as the basic parameters such as the shell radius, thickness, overall length of the compartment, and stiffener spacing are varied.

• 한국기계가공학회지
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• 제18권4호
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• pp.34-40
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• 2019

We performed shape optimization of an anti-vibration rubber assembly which is used in the field option cabin of agricultural tractors to improve the vibration isolation capability. To characterize the hyper-elastic material property of rubber, we performed uniaxial and biaxial tension tests and used the data to calibrate the material model applied in the finite element analyses. We conducted a field test to characterize the input excitation from the tractor and the output response at the cabin frame. To account for the nonlinear behavior of rubber, we performed static analyses to derive the load-displacement curve of the anti-vibration rubber assembly. The stiffness of the rubber assembly could be calculated from this curve and was input to the harmonic analyses of the cabin. We compared the results with the test data for verification. We utilized Taguchi's parameter design method to determine the optimal shape of the anti-vibration rubber assembly and found two distinct shapes with reduced stiffness. Results show that the vibration at the cabin frame was reduced by approximately 35% or 47.6% compared with the initial design using the two optimized models.

• 인터넷정보학회논문지
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• 제22권3호
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• pp.9-16
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• 2021

This study aims to develop a human activity recognition (HAR) system as a Deep-Learning (DL) classification model, distinguishing various human activities. We solely rely on the signals from a wristband accelerometer worn by a person for the user's convenience. 3-axis sequential acceleration signal data are gathered within a predefined time-window-slice, and they are used as input to the classification system. We are particularly interested in developing a Deep-Learning model that can outperform conventional machine learning classification performance. A total of 13 activities based on the laboratory experiments' data are used for the initial performance comparison. We have improved classification performance using the Convolutional Neural Network (CNN) combined with an auto-encoder feature reduction and parameter tuning. With various publically available HAR datasets, we could also achieve significant improvement in HAR classification. Our CNN model is also compared against Recurrent-Neural-Network(RNN) with Long Short-Term Memory(LSTM) to demonstrate its superiority. Noticeably, our model could distinguish both general activities and near-identical activities such as sitting down on the chair and floor, with almost perfect classification accuracy.

• Coupled systems mechanics
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• 제11권2호
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• pp.93-106
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• 2022

The total embankment settlement consists of three stages: the initial settlement, the primary consolidation settlement, and the secondary consolidation settlement. The total embankment settlement is largely controlled by the primary consolidation settlement, which is usually computed with numerical models that implement Biot's theory of consolidation. The key parameter that affects the primary consolidation time is the coefficient of permeability. Due to the complex stress and strain states in the foundation soil under the embankment, to be able to predict the consolidation time more precisely, aside from porosity-dependency, the strain-dependency of the coefficient of permeability should be also taken into account in numerical analyses. In this paper, we propose a two-dimensional plane strain numerical model of embankment primary consolidation, which implements Biot's theory of consolidation with both porosity-dependent and strain-dependent coefficient of permeability. We perform several numerical simulations. First, we demonstrate the influence of the strain-dependent coefficient of permeability on the computed results. Next, we validate our numerical model by comparing computed results against in-situ measurements for two road embankments: one near the city of Saga, and the other near the city of Boston. Finally, we give our concluding remarks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권8호
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• pp.2587-2605
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• 2022

In order to efficiently detect community structure in complex networks, community detection algorithms can be designed from the perspective of node similarity. However, the appropriate parameters should be chosen to achieve community division, furthermore, these existing algorithms based on the similarity of common neighbors have low discrimination between node pairs. To solve the above problems, a noval community detection algorithm using closeness similarity based on common neighbor node clustering entropy is proposed, shorted as CSCDA. Firstly, to improve detection accuracy, common neighbors and clustering coefficient are combined in the form of entropy, then a new closeness similarity measure is proposed. Through the designed similarity measure, the closeness similar node set of each node can be further accurately identified. Secondly, to reduce the randomness of the community detection result, based on the closeness similar node set, the node leadership is used to determine the most closeness similar first-order neighbor node for merging to create the initial communities. Thirdly, for the difficult problem of parameter selection in existing algorithms, the merging of two levels is used to iteratively detect the final communities with the idea of modularity optimization. Finally, experiments show that the normalized mutual information values are increased by an average of 8.06% and 5.94% on two scales of synthetic networks and real-world networks with real communities, and modularity is increased by an average of 0.80% on the real-world networks without real communities.

• 한국작물학회지
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• 제32권3호
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• pp.268-276
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• 1987

대두종자의 퇴화과정에서 일어나는 생리ㆍ화학적인 변화를 탐색하여 종자세의 차이를 비교하고 종자세 예측에 적합한 방법을 구명하기 위하여 대두 5품종의 종자를 인위노화처리시켰다. 대두종자세의 지표로서 발아율$\times$배축의 길이로 나타낸 값을 매개변수로 하여 각종 종자세 검정성적과 비교검토하였다. 종자세검정의 가장 적합한 방법으로는 발아시험에 의한 방법임을 알 수 있었다. ATP와 GADA 검정법을 제외하고는 모든 검정법이 종자세 지표와 고도의 유의성이 있었다. 대두종자세 검정을 위하여는 배축의 길이. 전기전도도에 의한 검정 및 저온발아 검정법이 적합한 방법임을 알 수 있었다.

• Advances in nano research
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• 제14권2호
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• pp.155-164
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• 2023

Grain size in sheet metals in one of the main parameters in determining formability. Grain size control in industry requires delicate process control and equipment. In the present study, effects of grain size on the formability of steel sheets is investigated. Experimental investigation of effect of grain size is a cumbersome method which due to existence of many other effective parameters are not conclusive in some cases. On the other hand, since the average grain size of a crystalline material is a statistical parameter, using traditional methods are not sufficient for find the optimum grain size to maximize formability. Therefore, design of experiment (DoE) and artificial intelligence (AI) methods are coupled together in this study to find the optimum conditions for formability in terms of grain size and to predict forming limits of sheet metals under bi-stretch loading conditions. In this regard, a set of experiment is conducted to provide initial data for training and testing DoE and AI. Afterwards, the using response surface method (RSM) optimum grain size is calculated. Moreover, trained neural network is used to predict formability in the calculated optimum condition and the results compared to the experimental results. The findings of the present study show that DoE and AI could be a great aid in the design, determination and prediction of optimum grain size for maximizing sheet formability.

• Journal of applied mathematics & informatics
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• 제40권3_4호
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• pp.675-694
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• 2022

In this article, we investigate the solution of the inverse problem for one dimensional heat equation with Neumann and Robin boundary conditions, that is, we determine the temperature and source term with given initial and boundary conditions. Three radial basis functions(RBFs) have been used for numerical solution, and Homotopy perturbation method for analytic solution. Numerical solutions which are obtained by considering each of the three RBFs are compared to the exact solution. For appropriate value of shape parameter c, numerical solutions best approximates exact solutions. Furthermore, we have shown the impact of noisy data on the numerical solution of u and f.