• Structural Engineering and Mechanics
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• v.87 no.3
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• pp.231-242
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• 2023

A novel combinatorial type-2 adaptive neuro-fuzzy inference system (T2-ANFIS) and robust proportional integral derivative (PID) control framework for intelligent vibration mitigation of uncertain structural system is introduced. The fuzzy logic controllers (FLCs), are designed independently of the mathematical model of the system. The type-1 FLCs, have a limited ability to reduce the effect of uncertainty, due to their fuzzy sets with a crisp degree of membership. In real applications, the consequent part of the fuzzy rules is uncertain. The type-2 FLCs, are robust to the fuzzy rules and the process parameters due to the fuzzy degree of membership functions and footprint of uncertainty (FOU). The adaptivity of the proposed method is provided with the optimum tuning of the parameters using the neural network training algorithms. In our approach, the PID control force is obtained using the generalized type-2 neuro-fuzzy in such a way that the stability and robustness of the controller are guaranteed. The robust performance and stability of the presented framework are demonstrated in a numerical study for an eleven-story seismically-excited building structure combined with an active tuned mass damper (ATMD). The results indicate that the introduced type-2 neuro-fuzzy PID control scheme is effective to attenuate plant states in the presence of the structured and unstructured uncertainties, compared to the conventional, type-1 FLC, type-2 FLC, and type-1 neuro-fuzzy PID controllers.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.39-58
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• 2014

As the importance of big data and related technologies continues to grow in the industry, it has become highlighted to visualize results of processing and analyzing big data. Visualization of data delivers people effectiveness and clarity for understanding the result of analyzing. By the way, visualization has a role as the GUI (Graphical User Interface) that supports communications between people and analysis systems. Usually to make development and maintenance easier, these GUI parts should be loosely coupled from the parts of processing and analyzing data. And also to implement a loosely coupled architecture, it is necessary to adopt design patterns such as MVC (Model-View-Controller) which is designed for minimizing coupling between UI part and data processing part. On the other hand, big data can be classified as structured data and unstructured data. The visualization of structured data is relatively easy to unstructured data. For all that, as it has been spread out that the people utilize and analyze unstructured data, they usually develop the visualization system only for each project to overcome the limitation traditional visualization system for structured data. Furthermore, for text data which covers a huge part of unstructured data, visualization of data is more difficult. It results from the complexity of technology for analyzing text data as like linguistic analysis, text mining, social network analysis, and so on. And also those technologies are not standardized. This situation makes it more difficult to reuse the visualization system of a project to other projects. We assume that the reason is lack of commonality design of visualization system considering to expanse it to other system. In our research, we suggest a common information model for visualizing text data and propose a comprehensive and reusable framework, TexVizu, for visualizing text data. At first, we survey representative researches in text visualization era. And also we identify common elements for text visualization and common patterns among various cases of its. And then we review and analyze elements and patterns with three different viewpoints as structural viewpoint, interactive viewpoint, and semantic viewpoint. And then we design an integrated model of text data which represent elements for visualization. The structural viewpoint is for identifying structural element from various text documents as like title, author, body, and so on. The interactive viewpoint is for identifying the types of relations and interactions between text documents as like post, comment, reply and so on. The semantic viewpoint is for identifying semantic elements which extracted from analyzing text data linguistically and are represented as tags for classifying types of entity as like people, place or location, time, event and so on. After then we extract and choose common requirements for visualizing text data. The requirements are categorized as four types which are structure information, content information, relation information, trend information. Each type of requirements comprised with required visualization techniques, data and goal (what to know). These requirements are common and key requirement for design a framework which keep that a visualization system are loosely coupled from data processing or analyzing system. Finally we designed a common text visualization framework, TexVizu which is reusable and expansible for various visualization projects by collaborating with various Text Data Loader and Analytical Text Data Visualizer via common interfaces as like ITextDataLoader and IATDProvider. And also TexVisu is comprised with Analytical Text Data Model, Analytical Text Data Storage and Analytical Text Data Controller. In this framework, external components are the specifications of required interfaces for collaborating with this framework. As an experiment, we also adopt this framework into two text visualization systems as like a social opinion mining system and an online news analysis system.

• Structural Engineering and Mechanics
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• v.76 no.2
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• pp.193-205
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• 2020

The growing need for assuring efficient and sustainable investments in civil engineering structures has determined a renovated interest in the rational design of such structures from designers, clients and authorities. As a result, risk-informed decision-making methodologies are increasingly being used as a direct decision tool or as an upper-level layer from which performance-based approaches are then calibrated against. One of the most important and challenging aspects of today's structural design is to adequately handle the system-level effects, the known unknowns and the unknown unknowns. These aspects revolve around assessing and evaluating relevant damage scenarios, namely those involving unacceptable/intolerable damage levels. Hence, the importance of risk analysis of disproportionate collapse, and along with it of robustness. However, the way robustness has been used in modern design codes varies substantially, from simple provisions of prescriptive rules to complex risk analysis of the disproportionate collapse. As a result, implementing design for robustness is still very much a grey area and more so when it comes to defining means to quantify robustness. This paper revisits the most common robustness frameworks, highlighting their merits and limitations, and identifies one among them which is very promising as a way forward to solve the still open challenges.

• Structural Engineering and Mechanics
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• v.12 no.6
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• pp.685-698
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• 2001

In this paper, a general method for the automatic search for Strut-and-Tie (S&T) models representative of possible resistant mechanisms in reinforced concrete elements is proposed. The representativeness criterion here adopted is inspired to the principle of minimum strain energy and requires the consistency of the model with a reference stress field. In particular, a highly indeterminate pin-jointed framework of a given layout is generated within the assigned geometry of the concrete element and an optimum truss is found by the minimisation of a suitable objective function. Such a function allows us to search the optimum truss according to a reference stress field deduced through a F.E.A. and assumed as representative of the given continuum. The theoretical principles and the mathematical formulation of the method are firstly explained; the search for a S&T model suitable for the design of a deep beam shows the method capability in handling the reference stress path. Finally, since the analysis may consider the structure as linear-elastic or cracked and non-linear in both the component materials, it is shown how the proposed procedure allows us to verify the possibilities of activation of the design model, oriented to the serviceability condition and deduced in the linear elastic field, by following the evolution of the resistant mechanisms in the cracked non-linear field up to the structural failure.

• Structural Engineering and Mechanics
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• v.28 no.6
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• pp.727-747
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• 2008

In the framework of the SPEAR (Seismic PErformance Assessment and Rehabilitation) research Project, an under-designed three storey RC frame structure, designed to sustain only gravity loads, was subjected, in three different configurations 'as-built', Fiber Reinforced Polymer (FRP) retrofitted and rehabilitated by reinforced concrete (RC) jacketing, to a series of bi-directional pseudodynamic (PsD) tests under different values of peak ground acceleration (PGA) (from a minimum of 0.20g to a maximum of 0.30g). The seismic deficiencies exhibited by the 'as-built' structure after the test at PGA level of 0.20g were confirmed by a post - test assessment of the structural seismic capacity performed by a nonlinear static pushover analysis implemented on the structure lumped plasticity model. To improve the seismic performance of the 'as-built' structure', two rehabilitation interventions by using either FRP laminates or RC jacketing were designed. Assumptions for the analytical modeling, design criteria and calculation procedures along with local and global intervention measures and their installation details are herein presented and discussed. Nonlinear static pushover analyses for the assessment of the theoretical seismic capacity of the structure in each retrofitted configuration were performed and compared with the experimental outcomes.

• Smart Structures and Systems
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• v.4 no.6
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• pp.779-794
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• 2008

Observer-based fault detection and isolation (FDI) filter design method is a model-based method. By carefully choosing the observer gain, the residual outputs can be projected onto different independent subspaces. Each subspace corresponds to the monitored structural element so that the projected residual will be nonzero when the associated structural element is damaged and zero when there is no damage. The key point of detection filter design is how to find an appropriate observer gain. This problem can be interpreted in a geometric framework and is found to be equivalent to the problem of finding a decentralized static output feedback gain. But, it is still a challenging task to find the decentralized controller by either analytical or numerical methods because its solution set is, generally, non-convex. In this paper, the concept of detection filter and iterative LMI technique for decentralized controller design are combined to develop an algorithm to compute the observer gain. It can be used to monitor structural element state: healthy or damaged. The simulation results show that the developed method can successfully identify structural damages.

• Smart Structures and Systems
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• v.29 no.1
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• pp.141-151
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• 2022

In recent years, the industry and research communities have focused on developing autonomous crack inspection approaches, which mainly include image acquisition and crack detection. In these approaches, mobile devices such as cameras, drones or smartphones are utilized as sensing platforms to acquire structural images, and the deep learning (DL)-based methods are being developed as important crack detection approaches. However, the process of image acquisition and collection is time-consuming, which delays the inspection. Also, the present mobile devices such as smartphones can be not only a sensing platform but also a computing platform that can be embedded with deep neural networks (DNNs) to conduct on-site crack detection. Due to the limited computing resources of mobile devices, the size of the DNNs should be reduced to improve the computational efficiency. In this study, an architecture called pruned crack recognition network (PCR-Net) was developed for the detection of structural cracks. A dataset containing 11000 images was established based on the raw images from bridge inspections. A pruning method was introduced to reduce the size of the base architecture for the optimization of the model size. Comparative studies were conducted with image processing techniques (IPTs) and other DNNs for the evaluation of the performance of the proposed PCR-Net. Furthermore, a modularly designed framework that integrated the PCR-Net was developed to realize a DL-based crack detection application for smartphones. Finally, on-site crack detection experiments were carried out to validate the performance of the developed system of smartphone-based detection of structural cracks.

• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.115-121
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• 2020

This study aims to develop a framework of structural scenarios for chatbot docent that supports visitors' activities in science centers and museums, and to suggest the application examples. For this study, the author adapted Focus Group Interview. As a result, the frameworks of scenarios could be categorized into the Collection of Science and Technology(CST) and Inquiry-Based Exhibition(IBE). These frameworks had dimensions of the primary and storytelling in common. Especially, framework of IBE scenario was added the usage dimension considering the characteristics of interaction between exhibits and visitors. This study could be basic materials for AI chatbot to support exhibition descriptions using the built data, and is expected to be help develop a more visitor-oriented scenarios of activities.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.106-113
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• 2009

Recently, due to many industrial accidents at construction sites, a variety of researches for structural health monitoring (SHM) of buildings are progressing. For real site application of SHM, one of the advanced technologies has blown as wireless sensor networks (WSN). In this paper, we proposed WIVA(WSN Monitoring framework based on 3D Visualization and Augmented Reality in Mobile Devices) system that applies 3D visualization and AR technology to mobile devices with camera based on WSN in order to expand the extent of information can observe. Moreover, we performed experiments to validate effectiveness in 3D and AR mode that utilize WSN data based on IEEE 802.15.4. In real implementation scenario, we demonstrated a fire occurrence test in 3-story building miniature.

• Computers and Concrete
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• v.29 no.2
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• pp.93-105
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• 2022

The degrees of freedom (DOFs) of high-rise structures increase rapidly due to the need for refined analysis, which poses a challenge toward a computationally efficient method for numerical analysis of high-rise structures using the finite element method (FEM). This paper presented an efficient iterative method, an algebraic multigrid (AMG) with a Jacobi overrelaxation smoother preconditioned conjugate gradient method (AMG-CG) used for solving large-scale structural system equations running on heterogeneous platforms with parallel accelerator graphics processing units (GPUs) enabled. Furthermore, an AMG-CG FEM application framework was established for the numerical analysis of high-rise structures. In the proposed method, the coarsening method, the optimal relaxation coefficient of the JOR smoother, the smoothing times, and the solution method for the coarsest grid of an AMG preconditioner were investigated via several numerical benchmarks of high-rise structures. The accuracy and the efficiency of the proposed FEM application framework were compared using the mature software Abaqus, and there were speedups of up to 18.4x when using an NVIDIA K40C GPU hosted in a workstation. The results demonstrated that the proposed method could improve the computational efficiency of solving structural system equations, and the AMG-CG FEM application framework was inherently suitable for numerical analysis of high-rise structures.