• Korean Journal of Computational Design and Engineering
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• v.14 no.1
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• pp.10-17
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• 2009

Surface detection and parameter estimation in point cloud is a relevant subject in CAD/CAM, reverse engineering, computer vision, coordinate metrology and digital factory. In this paper we present a software for a fully automatic surface detection and parameter estimation in unordered, incomplete and error-contaminated point cloud with a large number of data points. The software consists of three algorithmic modules each for object identification, point segmentation, and model fitting, which work interactively. Our newly developed algorithms for orthogonal distance fitting(ODF) play a fundamental role in each of the three modules. The ODF algorithms estimate the model parameters by minimizing the square sum of the shortest distances between the model feature and the measurement points. We demonstrate the performance of the software on a variety of point clouds generated by laser radar, computer tomography, and stripe-projection method.

• Journal of the Korea Society of Computer and Information
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• v.23 no.1
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• pp.9-15
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• 2018

Policy polls, which investigate the degree of support that the policy has for policy implementation, play an important role in making decisions. As the number of Internet users increases, the public is actively commenting on their policy news stories. Current policy polls tend to rely heavily on phone and offline surveys. Collecting and analyzing policy articles is useful in policy surveys. In this study, we propose a method of analyzing comments using deep learning technology showing outstanding performance in various fields. In particular, we designed various models based on the recurrent neural network (RNN) which is suitable for sequential data and compared the performance with the support vector machine (SVM), which is a traditional machine learning model. For all test sets, the SVM model show an accuracy of 0.73 and the RNN model have an accuracy of 0.83.

• Journal of Korea Multimedia Society
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• v.22 no.3
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• pp.395-402
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• 2019

Star characters play a key role in the background of contents that secure global competitiveness. In this study, we study the growth factors and transitional forms of Nintendo Super Mario Bros. and suggest the direction of nurturing Korean star characters. As a result of the analysis of Super Mario Bros., it was possible to derive the growth factors of Originality, repeatability, Continuity, Pertain, and Star Fame and the transition result of step development method. Robot Taekwon V was presented as a reference model while Korean game characters with global competitiveness were excavated. Robot Taekwon V, which combines the features of friendly, unique, symbolism, and narrative, could be used to present a development model of the type of jump development. In the jump development model, character development and Upbringing, diversification of genre, pioneering of new markets combined with new technology, and fostering of characters through linkage with other industries were presented.

• Structural Engineering and Mechanics
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• v.78 no.2
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• pp.187-197
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• 2021

This paper harnesses a micropolar thermoelastic medium consisting of voids to scrutinize the impacts of a magnetic field on it. To assess the problem, the three-phase-lag model (3PHL) has been employed and the analytical expressions of various variables under consideration have been derived using normal model analysis. The paper presents a graphical illustration of the material's stress, temperature, and dimensionless displacement. It has also been ensured that the predictions associated with results by different theories are not neglected instead; they are used to carry out appropriate comparisons in scenarios where the magnetic field is present as well as absent. The numerical results indicate that the magnetic field and the phase-lag of heat flux play a vital role in determining the distribution of field quantities. Thus, the investigation helped derive various interesting cases.

• Structural Engineering and Mechanics
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• v.78 no.5
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• pp.573-583
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• 2021

This paper presents a theoretical approach of the structures reinforced with bonded FRP composites, taking into account loading model, shear lag effect and the thermal effect. These composites are used, in particular, for rehabilitation of structures by stopping the propagation of the cracks. They improve rigidity and resistance, and prolong their lifespan. In this paper, an original model is presented to predict and to determine the stresses concentration at the FRP end, with the new theory analysis approach. The model is based on equilibrium and deformations compatibility requirements in and all parts of the strengthened beam, i.e., the concrete beam, the FRP plate and the adhesive layer. The theoretical predictions are compared with other existing solutions. The numerical resolution was finalized by taking into account the physical and geometric properties of materials that may play an important role in reducing the stress values. This solution is general in nature and may be applicable to all kinds of materials.

• Advances in concrete construction
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• v.13 no.5
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• pp.377-384
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• 2022

The present paper deals with nonlinear deflection analysis of hyperelastic plates rested on elastic foundation and subject to a transverse point force. For modeling of hyperelastic material, three-parameter Ishihara model has been employed. The plate formulation is based on classic plate theory accounting for von-Karman geometric nonlinearity. Therefore, both material and geometric nonlinearities have been considered based on Ishihara hyperelastic plate model. The governing equations for the plate have been derived based on Hamilton's rule and then solved via Galerkin's method. Obtained results show that material parameters of hyperelastic material play an important role in defection analysis. Also, the effects of foundation parameter and load location on plate deflections will be discussed.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1474-1478
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• 2009

The cooperation and trust among the project participants play a critical role in the success or failure of any delivery system in construction industry. But it is very difficult to establish trust between an owner and a contractor when rational people only pursue only their own material self-interest. Based on the principal-agent theory, this paper will introduce the altruistic behavior into the traditional principal-agent model, and model the reciprocal behavior between the owner and contractor. We will show that both the owner and the contractor benefit from their reciprocal behavior, and hence trust establishing between them is possible. More importantly, we will proof that the higher the project uncertainty is, the more important trust establishing is.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.4_2
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• pp.1001-1007
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• 2024

Recent deep learning algorithms for object detection in real-time play a crucial role in various applications such as autonomous driving, traffic monitoring, health care, and water quality monitoring. The size of small objects, in particular, significantly impacts the accuracy of detection models. However, data containing small objects can lead to underfitting issues in models. Therefore, this study developed a deep learning model capable of quickly detecting small objects to provide more accurate predictions. The RE-SOD (Residual block based Small Object Detector) developed in this research enhances the detection performance for small objects by using RGB separation preprocessing and residual blocks. The model achieved an accuracy of 1.0 in image classification and an mAP50-95 score of 0.944 in object detection. The performance of this model was validated by comparing it with real-time detection models such as YOLOv5, YOLOv7, and YOLOv8.

• Journal of Integrative Natural Science
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• v.8 no.1
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• pp.75-79
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• 2015

Thromboxane A2 receptors (TXA2-R) are the G protein coupled receptors localized on cell membranes and intracellular structures and play pathophysiological role in various thrombosis/hemostasis, modulation of the immune response, acute myocardial infarction, inflammatory lung disease, hypertension and nephrotic disease. TXA2 receptor antagonists have been evaluated as potential therapeutic agents for asthma, thrombosis and hypertension. The role of TXA2 in wide spectrum of diseases makes this as an important drug target. Hence in the present study, homology modeling of TXA2 receptor was performed using the crystal structure of squid rhodopsin and night blindness causing G90D rhodopsin. 20 models were generated using single and multiple templates based approaches and the best model was selected based on the validation result. We found that multiple template based approach have given better accuracy. The generated structures can be used in future for further binding site and docking analysis.

• World Technopolis Review
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• v.6 no.2
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• pp.113-129
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• 2017

Universities are considered important actors and drivers of socio-economic development in the regional innovation eco-system. This article investigates the role Kenyan universities and research institutes play in the development of regional innovation eco-system in the context of triple and Quadruple helices. A model involving Government, Industry, Universities and Society (Public) linkages in the regional innovation eco-system and with Information and Communication Technology as an enabler is used as a framework for analysing the nature of linkages in Kenya. The article uses literature review and case study methods to examine how universities and research institutes can spur the development of the innovation eco-systems. The research question is: what is the role of Kenyan universities and research institutes in spurring innovation ecosystems? Six cases of Kenyan universities and research institutes are considered in the light of Government Policy on Science, Technology and Innovation (STI) which is underpinned in Kenyan constitution 2010. The study contributes to the understanding of how deep collaboration among universities, government, research institutes, Science Cities, local, regional, national and international players spurs the creation of world-class innovation ecosystems which can contribute to regional development in developing countries like Kenya.