• Journal of computational fluids engineering
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• v.21 no.1
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• pp.72-77
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• 2016

In this study, effects of thurster axis tilting angle on the thruster-hull interaction and propulsion performance in a dynamic positioning system of offshore plant are numerically investigated. Straight and 7-degree tilted downward thruster models as a form of ducted propeller are considered. For numerical simulations, Reynolds averaged Navier-Stokes equations with SST turbulence model are solved by using STAR-CCM+. Results show that thruster-hull interaction is reduced in 7-degree tilted thruster model with lower vortex strength between thruster and hull bottom, although the propulsion performance does not have noticeable difference in a bollard condition.

• Proceedings of the KSR Conference
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• 2000.11a
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• pp.366-373
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• 2000

This paper represents the results carried out to determine the dynamic response characteristics of Korea High Speed Rail(KHSR) bridges. The responses of the KHSR bridges subjected to the moving train loading are obtained through the simplified method for the 2-dimensional train/track/bridge interaction analysis in which the eccentricity of axle loads and the effect of the torsional forces acting on the bridge are included for the more accurate train/track/bridge interaction analysis. The results of the analyses are compared with the field test data to verify the performance of the 2-dimensional train/track/bridge interaction analysis method.

• Proceedings of the KSR Conference
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• 2002.10b
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• pp.1059-1064
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• 2002

The behavior of an opening and the performance of support system depend upon the load-deformation characteristics of ground and support as well as of the manner and of timing of support installation. The load-deformation characteristics of ground and support are derived by the interaction between ground and support. The interaction between ground and support is qualitatively illustrated by a ground response curve. The behavior of an opening and the performance of support system depend upon the load-deformation characteristics of ground and support as well as of the manner and of timing of support installation. The interaction between ground and support is qualitatively illustrated by a ground response curve. The convergence-confinement method don't need the basic assumptions for a mathematical model. Also This is applicable to general tunnel. Consequently the stability of tunnel must be qualitatively investigated by a ground response curve and quantitatively adjudged by a numerical analysis for the reasonable design of tunnel.

• Geomechanics and Engineering
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• v.38 no.3
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• pp.231-247
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• 2024

The use of lime stabilization and geosynthetic reinforcement is a common approach to improve the performance of fine-grained soils in geotechnical applications. However, the impact of this combination on the soil-geosynthetic interaction remains unclear. This study addresses this gap by evaluating the interface efficiency and soil-geosynthetic interaction parameters of lime-stabilized clay (2%, 4%, 6%, and 8% lime content) reinforced with geotextile or geogrid using direct shear tests at various curing times (1, 7, 14, and 28 days). Additionally, machine learning algorithms (Support Vector Machine and Artificial Neural Network) were employed to predict soil shear strength. Findings revealed that lime stabilization significantly increased soil shear strength and interaction parameters, particularly at the optimal lime content (4%). Notably, stabilization improved the performance of soil-geogrid interfaces but had an adverse effect on soil-geotextile interfaces. Furthermore, machine learning algorithms effectively predicted soil shear strength, with sensitivity analysis highlighting lime percentage and geosynthetic type as the most significant influencing factors.

• Korea-Australia Rheology Journal
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• v.21 no.2
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• pp.91-102
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• 2009

This paper describes an extension of viscoelastic Group Interaction Modelling (GIM) to predict the relaxation response of linear, branched and cross-linked structures. This model is incorporated into a Monte Carlo percolation grid simulation used to generate the topological structure during the isothermal cure of a gel, so enabling the chemorheological response to be predicted at any point during the cure. The model results are compared to experimental data for an epoxy-amine systems and good agreement is observed. The viscoelastic model predicts the same exponent power-law behaviour of the loss and storage moduli as a function of frequency and predicts the cross-over in the loss tangent at the percolation condition for gelation. The model also predicts the peak in the loss tangent which occurs when the glass transition temperature surpasses the isothermal cure temperature and the system vitrifies.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1266-1269
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• 2003

Many studies have indicated that most of a product's cost is fixed early in its lift cycle, before the original design cycle is complete. This implies that we should consider various aspects of product lift cycle at the design stage. This means the need of collaboration in design stage. Because the Internet provides instant access to a wealth of design information, the Internet is used by the collaborative design team members as a medium to share data, information and knowledge, and in some cases for product data management and project management by integrating the Web with appropriate technologies. This paper presents a real-time collaborative design system for powerful interaction performance, based on the Internet and Web technologies. Using The system use the client/server architecture and the purpose of the system is to provide a method that enables real-time view, review and modification of the 3D model through the Internet.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.677-678
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• 2013

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.677-684
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• 2009

With various sensor network and ubiquitous technologies, we can extend interaction area from a virtual domain to physical space domain. This spatial interaction is differ in that traditional interaction is mainly processed by direct interaction with the computer machine which is a target machine or provides interaction tools and the spatial interaction is performed indirectly between users with smart interaction tools and many distributed components of space. So, this interaction gives methods to users to control whole manageable space components by registering and recognizing objects. Finally, this paper provides an effective spatial interaction method with template-based task mapping algorithm which is sorted by historical interaction data for support of users' intended task. And then, we analyze how much the system performance would be improved with the task mapping algorithm and conclude with an introduction of a GUI method to visualize results of spatial interaction.

• The Journal of the Korea Contents Association
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• v.13 no.5
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• pp.377-386
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• 2013

The purposes of this study is to examine the effect of fitness Among Characteristics of CEO, Company's innovation and Management Control on Organization Performance. CEO characteristics are investigated by the risk-taking propensity, need for achievement. Company's Innovation are measured by product innovation, technological innovation. Management control are applied by action control and result control. Organization performances are analyzed by internal performance, growth performance, financial performance. the research methodology applied in this paper is contingency theory by Drazin and Van de Ven(1985) - selective approach, Interaction approach, system approach. This paper was applied by the Three way interaction term among CEO characteristics, Company's Innovation and Management control to analyze the influences to the organization performances. As a result of this paper, there are the differences between Two way interaction terms or three way interaction terms to affect the organization performances. this paper can confirm the desirable combinations between two or three variables(CEO characteristics, Company's Innovation and Management control) to affect significantly to the particular organization performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.751-770
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• 2019

Action recognition is an essential task in computer vision due to the variety of prospective applications, such as security surveillance, machine learning, and human-computer interaction. The availability of more video data than ever before and the lofty performance of deep convolutional neural networks also make it essential for action recognition in video. Unfortunately, limited crafted video features and the scarcity of benchmark datasets make it challenging to address the multi-person action recognition task in video data. In this work, we propose a deep convolutional neural network-based Effective Hybrid Learning (EHL) framework for two-person interaction classification in video data. Our approach exploits a pre-trained network model (the VGG16 from the University of Oxford Visual Geometry Group) and extends the Faster R-CNN (region-based convolutional neural network a state-of-the-art detector for image classification). We broaden a semi-supervised learning method combined with an active learning method to improve overall performance. Numerous types of two-person interactions exist in the real world, which makes this a challenging task. In our experiment, we consider a limited number of actions, such as hugging, fighting, linking arms, talking, and kidnapping in two environment such simple and complex. We show that our trained model with an active semi-supervised learning architecture gradually improves the performance. In a simple environment using an Intelligent Technology Laboratory (ITLab) dataset from Inha University, performance increased to 95.6% accuracy, and in a complex environment, performance reached 81% accuracy. Our method reduces data-labeling time, compared to supervised learning methods, for the ITLab dataset. We also conduct extensive experiment on Human Action Recognition benchmarks such as UT-Interaction dataset, HMDB51 dataset and obtain better performance than state-of-the-art approaches.