• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.61-68
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• 2008

A set of modal parameters of a stay-cable have been extracted from a moving picture captured by a digital camera supported by shaking hands. It is hard to identify the center of targets attached on the cable surface from the blurred cable motion image, because of the high speed motion of cable, low sampling frequency of camera, and the shaking effect of camera. This study proposes a multi-template matching algorithm to resolve such difficulties. In addition, a sensitivity-based system identification algorithm is introduced to extract the natural frequencies and damping ratios from the ambient cable vibration data. Three sets of vibration tests are conducted to examine the validity of the proposed algorithms. The results show that the proposed technique is pretty feasible for extracting modal parameters from the severely shaking motion pictures.

• Structural Engineering and Mechanics
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• v.10 no.1
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• pp.37-51
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• 2000

Identification of damage location based on modal measurement is an important problem in structural health monitoring. The damage index method that attempts to evaluate the changes in modal strain energy distribution has been found to be effective under certain circumstances. In this paper two damage index methods using bending strain energy and shear strain energy have been evaluated for numerous cases at different locations and degrees of damage. The objective is to evaluate the feasibility of the damage index method to localize the damage on large span concrete bridge. Finite element models were used as the test structures. Finally this method was used to predict the damage location in an actual structure, using the results of a modal survey from a large concrete bridge.

• Journal of KSNVE
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• v.9 no.3
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• pp.493-501
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• 1999

The vibration modes of resilient mounting system and foundation structure which support diesel engine/generator set and acoustic enclosure walls play an important role in the vibration transmission process. So, it is necessary to perform vibration mode analysis of resilient mounting system and foundation structure. For some reasons, if the vibration modal analysis of resilient mounting system and foundation structure of acoustic enclosure could be simultaneously done by finite element method, it would be very efficient approach. In this paper, vibration modal analysis method using finite element method for multi stage mounting system having n d.o.f model was proposed. Vibration analysis of single and double stage resilient mounting system was performed to verify the validity of the proposed method. Also frequency response results were compared in case of rigid foundation model and finite element foundation model which was compared with experimental modal analysis results.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.12
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• pp.1229-1236
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• 2008

A set of modal parameters of a stay-cable have been extracted fi:on a moving picture captured by a digital camera supported by shaking hands. It is hard to identify the center of targets attached on the cable surface from the blurred cable motion image, because of the high speed motion of cable, low sampling frequency of camera, and the shaking effect of camera. This study proposes a multi-template matching algorithm to resolve such difficulties. In addition, a sensitivity-based system identification algorithm is introduced to extract the natural frequencies and damping ratios from the ambient cable vibration data. Three sets of vibration tests are conducted to examine the validity of the proposed algorithms. The results show that the proposed technique is pretty feasible for extracting modal parameters from the severely shaking motion pictures.

• Earthquakes and Structures
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• v.1 no.2
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• pp.163-175
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• 2010

The vertical axis through the modal center of rigidity (m-CR) is used for interpreting the code torsional provisions in the design of eccentric multi-story building structures. The concept of m-CR has been demonstrated by the author in an earlier paper and the particular feature of this point is that when the vertical line of the centers of mass at the floor levels is passing through m-CR, minimum base torsion is developed. For this reason the aforesaid axis is used as reference axis for implementing the code provisions required by the equivalent static analysis. The study examines uniform mixed-bent-type multistory buildings with simple eccentricity, ranging from torsionally stiff to torsionally flexible systems. Using the results of a dynamic response spectrum analysis as a basis for comparisons, it is shown that the results of the code static design are on the safe side in torsionally stiff buildings, but unable to predict the required strength of bents on the stiff side of systems with a predominantly torsional response. Suggestions are made for improving the code provisions in such cases.

• Smart Structures and Systems
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• v.14 no.3
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• pp.285-305
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• 2014

This study employs a novel beam-type wavelet finite element model (WFEM) to fulfill an adaptive-scale damage detection strategy in which structural modeling scales are not only spatially varying but also dynamically changed according to actual needs. Dynamical equations of beam structures are derived in the context of WFEM by using the second-generation cubic Hermite multiwavelets as interpolation functions. Based on the concept of modal strain energy, damage in beam structures can be detected in a progressive manner: the suspected region is first identified using a low-scale structural model and the more accurate location and severity of the damage can be estimated using a multi-scale model with local refinement in the suspected region. Although this strategy can be implemented using traditional finite element methods, the multi-scale and localization properties of the WFEM considerably facilitate the adaptive change of modeling scales in a multi-stage process. The numerical examples in this study clearly demonstrate that the proposed damage detection strategy can progressively and efficiently locate and quantify damage with minimal computation effort and a limited number of sensors.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.235-250
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• 2013

Optimal sensor placement (OSP) technique plays a key role in the structural health monitoring (SHM) of large-scale structures. According to the mathematical background and implicit assumptions made in the triaxial effective independence (EfI) method, this paper presents a novel multi-dimensional OSP method for the Canton Tower focusing on application demands. In contrast to existing methods, the presented method renders the corresponding target mode shape partitions as linearly independent as possible and, at the same time, maintains the stability of the modal matrix in the iteration process. The modal assurance criterion (MAC), determinant of the Fisher Information Matrix (FIM) and condition number of the FIM have been taken as the optimal criteria, respectively, to demonstrate the feasibility and effectiveness of the proposed method. Numerical investigations suggest that the proposed method outperforms the original EfI method in all instances as expected, which is looked forward to be even more pronounced should it be used for other multi-dimensional optimization problems.

• The Journal of Society for e-Business Studies
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• v.27 no.1
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• pp.15-28
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• 2022

Due to recent expansion of online market such as clothing, utilizing customer review has become a major marketing measure. User review has been used as a tool of analyzing sentiment of customers. Sentiment analysis can be largely classified with machine learning-based and lexicon-based method. Machine learning-based method is a learning classification model referring review and labels. As research of sentiment analysis has been developed, multi-modal models learned by images and video data in reviews has been studied. Characteristics of words in reviews are differentiated depending on products' and customers' categories. In this paper, sentiment is analyzed via considering review data and metadata of products and users. Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM), Self Attention-based Multi-head Attention models and Bidirectional Encoder Representation from Transformer (BERT) are used in this study. Same Multi-Layer Perceptron (MLP) model is used upon every products information. This paper suggests a multi-modal sentiment analysis model that simultaneously considers user reviews and product meta-information.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.13-26
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• 2024

Multi-modal generation is the process of generating results based on a variety of information, such as text, images, and audio. With the rapid development of AI technology, there is a growing number of multi-modal based systems that synthesize different types of data to produce results. In this paper, we present an AI system that uses speech and text recognition to describe a person and generate a montage image. While the existing montage generation technology is based on the appearance of Westerners, the montage generation system developed in this paper learns a model based on Korean facial features. Therefore, it is possible to create more accurate and effective Korean montage images based on multi-modal voice and text specific to Korean. Since the developed montage generation app can be utilized as a draft montage, it can dramatically reduce the manual labor of existing montage production personnel. For this purpose, we utilized persona-based virtual person montage data provided by the AI-Hub of the National Information Society Agency. AI-Hub is an AI integration platform aimed at providing a one-stop service by building artificial intelligence learning data necessary for the development of AI technology and services. The image generation system was implemented using VQGAN, a deep learning model used to generate high-resolution images, and the KoDALLE model, a Korean-based image generation model. It can be confirmed that the learned AI model creates a montage image of a face that is very similar to what was described using voice and text. To verify the practicality of the developed montage generation app, 10 testers used it and more than 70% responded that they were satisfied. The montage generator can be used in various fields, such as criminal detection, to describe and image facial features.

• The Journal of Society for e-Business Studies
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• v.21 no.1
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• pp.147-163
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• 2016

Gender information of a smart device user is essential to provide personalized services, and multi-modal data obtained from the device is useful for predicting the gender of the user. However, the method for utilizing each of the multi-modal data for gender prediction differs according to the characteristics of the data. Therefore, in this study, an ensemble method for predicting the gender of a smart device user by using three classifiers that have text, application, and acceleration data as inputs, respectively, is proposed. To alleviate privacy issues that occur when text data generated in a smart device are sent outside, a classification method which scans smart device text data only on the device and classifies the gender of the user by matching text data with predefined sets of word. An application based classifier assigns gender labels to executed applications and predicts gender of the user by comparing the label ratio. Acceleration data is used with Support Vector Machine to classify user gender. The proposed method was evaluated by using the actual smart device log data collected from an Android application. The experimental results showed that the proposed method outperformed the compared methods.