• Structural Engineering and Mechanics
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• v.50 no.5
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• pp.605-616
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• 2014

When the periodic cellular structure is loaded or swelling beyond the critical value, the structure may undergo a pattern transformation owing to the local elastic instabilities, thus leading to structural collapse and the structure changing to a new configuration. Based on this deformation-triggered pattern, we have proposed the novel composite gel materials. This designed material is a type of architectural material possessing special mechanical properties. In this study, the mechanical behavior of the composite gel periodic structure with various gel inclusions is studied further through numerical simulations. When pattern transformation occurs, it results in a different elastic relationship compared with the material at untransformed state. Based on the obtained nominal stress versus nominal strain behavior, the Poisson's ratio and corresponding deformed structure patterns, we investigate the performance of designed composite materials and the effects of the uniformly distributed gel inclusions on composite materials. A better understanding of the characteristics of these composite gel materials is a key to develop its potential applications on new soft machines.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.315-324
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• 2021

The study aims to investigate new theoretical approaches in an effort to resolve conceptual contradictions regarding the impact of organizational culture on developing culture for change, first by providing socio-structural frameworks supporting intrapreneurship, and second through encouraging professional culture behavior with management practices or organizational members acting as agents of change forming a deeper culture of values and behavior. The design of this research is quantitative. This study employs survey data of managers and section heads, which met the sampling requirements. Data analysis in this research used structural equation modeling (SEM) with the help of the AMOS program. The results show that all hypotheses are supported. The findings of this study suggest that the organizational culture transformation and dyadic social intrapreneurship based on professional culture (DSIBPC) have significant positive influence as antecedents of competitive advantage. This research also shows that DSIBPC is able to act as an important mediator that fills a gap in the relationship between organizational culture transformation toward competitive advantage, as well as being an alternative strategy for organizations in an effort to increase their competitive advantage. Referring to the results of this research, organizations need to focus and pay attention to the DSIBPC.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.1
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• pp.1-7
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• 2020

The wind responses of twin buildings are determined by the characteristics of wind loads and the dynamic characteristics of the structural systems of the buildings. In this study, the characteristics of wind pressure that influence wind responses were identified for two different spacings between the twin buildings using a wind tunnel test and the proper orthogonal decomposition (POD) method. Structural dynamic characteristics were also identified using 3D structural system modeling. The double modal transformation method was utilized to evaluate the characteristics of wind pressure for across-wind and along-wind conditions and the effect of the dynamic characteristics of each structure on the wind responses. The channeling and vortex effects were identified through the POD method. Across-wind loads were significantly affected by the spacings between the twin buildings, whereas along-wind loads were minimally affected. Similarly, while using the double modal transformation method, a significant difference was noticed in case of the cross-participation coefficients in the across-wind direction condition for the different spacings between the buildings; however, the along-wind direction condition showed negligible difference. Therefore, the spacing between the two buildings plays a more important role in across-wind responses compared to along-wind responses.

• Journal of Information Technology Applications and Management
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• v.21 no.4
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• pp.187-201
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• 2014

As the complexity of business environment increases rapidly the use advanced information technology start to affect not only the business processes of individual companies but also the fundamental nature of business and industrial ecosystem. The changes observed at the level of business and industrial ecosystem encompasses a broad range of transformation. This unit of analysis is not sufficiently dealt with by existing information system research. This research attempted to analyze the changes in business ecosystem caused by digital transformation using Social Network Analysis. We studied structural change of the Korea film industry ecosystem chronologically divided by critical events. The film industry is chosen because it is an industry very sensitive to the changes in technology and has gone through massive transformation during the last three decade by way of using modern information technology.

• Structural Engineering and Mechanics
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• v.90 no.3
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• pp.313-323
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• 2024

Most of existing buildings in Mexico City are made of reinforced concrete (RC), however, it has been shown that they are very susceptible to narrow-band long duration ground motions. In recent years, the use of dual systems composed by Buckling Restrained Braces (BRB) has increased due to its high energy dissipation capacity under reversible cyclical loads. Therefore, in this work the behavior of RC buildings with BRB is studied in order to know their performance, specifically, the energy distribution through height and response transformation factors between the RC and simplified systems are estimated. For this propose, seven RC buildings with different heights were designed according to the Mexico City Seismic Design Provisions (MCSDP), in addition, equivalent single degree of freedom (SDOF) systems were obtained. Incremental dynamic analyses on the buildings under 30 narrow-band ground motions in order to compute the relationship between normalized hysteretic energy, maximum inter-story drift and roof displacement demands were performed. The results shown that the entire structural frames participate in energy dissipation and their distribution is independent of the global ductility. The results let propose energy distribution equations through height. Finally, response transformation factors between the SDOF and multi degree of freedom (MDOF) systems were developed aimed to propose a new energy-based approach of BRB reinforced concrete buildings.

• Structural Engineering and Mechanics
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• v.7 no.5
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• pp.485-502
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• 1999

Using the continuous Hopfield network model as the basis to solve the general crisp and fuzzy constrained optimization problem is presented and examined. The model lies in its transformation to a parallel algorithm which distributes the work of numerical optimization to several simultaneously computing processors. The method is applied to different structural engineering design problems that demonstrate this usefulness, satisfaction or potential. The computing algorithm has been given and discussed for a designer who can program it without difficulty.

• Journal of Contemporary Eastern Asia
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• v.7 no.2
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• pp.29-48
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• 2008

• Structural Engineering and Mechanics
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• v.67 no.5
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• pp.439-455
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• 2018

Within a probabilistic framework, this paper addresses the determination of the static structural response of beams and frames with partially restrained (semi-rigid) connections. The flexibility of the nodal connections is incorporated via an idealized linear-elastic behavior of the beam constraints through the use of rotational springs, which are here considered uncertain for taking into account the largely scattered results observed in experimental findings. The analysis is conducted via the Probabilistic Transformation Method, by modelling the spring stiffness terms (or equivalently, the fixity factors of the beam) as uniformly distributed random variables. The limit values of the Eurocode 3 fixity factors for steel semi-rigid connections are assumed. The exact probability density function of a few indicators of the structural response is derived and discussed in order to identify to what extent the uncertainty of the beam constraints affects the resulting beam response. Some design considerations arise which point out the paramount importance of probability-based approaches whenever a comprehensive experimental background regarding the stiffness of the beam connection is lacking, for example in steel frames with semi-rigid connections or in precast reinforced concrete framed structures. Indeed, it is demonstrated that resorting to deterministic approaches may lead to misleading (and in some cases non-conservative) outcomes from a design viewpoint.

• Computers and Concrete
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• v.33 no.3
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• pp.285-299
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• 2024

Recently, many engineering computations have realized their digital transformation to Machine Learning (ML)-based systems. Predicting the behavior of a structure, which is mainly computed with structural analysis software, is an essential step before construction for efficient structural analysis. Especially in the seismic-based design procedure of the structures, predicting the lateral load capacity of reinforced concrete (RC) columns is a vital factor. In this study, a novel ML-based model is proposed to predict the maximum lateral load capacity of RC columns under varying axial loads or cyclic loadings. The proposed model is generated with a Deep Neural Network (DNN) and compared with traditional ML techniques as well as a popular commercial structural analysis software. In the design and test phases of the proposed model, 319 columns with rectangular and square cross-sections are incorporated. In this study, 33 parameters are used to predict the maximum lateral load capacity of each RC column. While some traditional ML techniques perform better prediction than the compared commercial software, the proposed DNN model provides the best prediction results within the analysis. The experimental results reveal the fact that the performance of the proposed DNN model can definitely be used for other engineering purposes as well.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.1
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• pp.57-65
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• 2023

A vibration response-based detection system was used to investigate the adhesive areas of single-lap joints using a nonlinear transformation approach for deep learning. In industry or engineering fields, it is difficult to know the condition of an invisible part within a structure that cannot easily be disassembled and the conditions of adhesive areas of adhesively bonded structures. To address these issues, a detection method was devised that uses nonlinear transformation to determine the adhesive areas of various single-lap-jointed specimens from the vibration response of the reference specimen. In this study, a frequency response function with nonlinear transformation was employed to identify the vibration characteristics, and a virtual spectrogram was used for classification in convolutional neural network based deep learning. Moreover, a vibration experiment, an analytical solution, and a finite-element analysis were performed to verify the developed method with aluminum, carbon fiber composite, and ultra-high-molecular-weight polyethylene specimens.