• Smart Structures and Systems
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• v.16 no.1
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• pp.47-65
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• 2015

A novel finite element (FE) model updating method based on multi-resolution analysis (MRA) is proposed. The true stiffness of the FE model is considered as the superposition of two pieces of stiffness information of different resolutions: the pre-defined stiffness information and updating stiffness information. While the resolution of former is solely decided by the meshing density of the FE model, the resolution of latter is decided by the limited information obtained from the experiment. The latter resolution is considerably lower than the former. Second generation wavelet is adopted to describe the updating stiffness information in the framework of MRA. This updating stiffness in MRA is realized at low level of resolution, therefore, needs less number of updating parameters. The efficiency of the optimization process is thus enhanced. The proposed method is suitable for the identification of multiple irregular cracks and performs well in capturing the global features of the structural damage. After the global features are identified, a refinement process proposed in the paper can be carried out to improve the performance of the MRA of the updating information. The effectiveness of the method is verified by numerical simulations of a box girder and the experiment of a three-span continues pre-stressed concrete bridge. It is shown that the proposed method corresponds well to the global features of the structural damage and is stable against the perturbation of modal parameters and small variations of the damage.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.31-48
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• 2023

The popularization of smart devices and subsequent optimization of their sensing capacity has resulted in a novel mobile crowdsensing (MCS) pattern, which employs smart devices as sensing nodes by recruiting users to develop a sensing network for multiple-task performance. This technique has garnered much scholarly interest in terms of sensing range, cost, and integration. The MCS is prevalent in various fields, including environmental monitoring, noise monitoring, and road monitoring. A complete MCS life cycle entails task allocation, data collection, and data aggregation. Regardless, specific drawbacks remain unresolved in this study despite extensive research on this life cycle. This article mainly summarizes single-task, multi-task allocation, and space-time multi-task allocation at the task allocation stage. Meanwhile, the quality, safety, and efficiency of data collection are discussed at the data collection stage. Edge computing, which provides a novel development idea to derive data from the MCS system, is also highlighted. Furthermore, data aggregation security and quality are summarized at the data aggregation stage. The novel development of multi-modal data aggregation is also outlined following the diversity of data obtained from MCS. Overall, this article summarizes the three aspects of the MCS life cycle, analyzes the issues underlying this study, and offers developmental directions for future scholars' reference.

• Steel and Composite Structures
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• v.26 no.2
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• pp.197-211
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• 2018

The study presents the earthquake performance of the Bosphorus Bridge under multi-point earthquake excitation considering the spatially varying site-specific earthquake motions. The elaborate FE model of the bridge is firstly established depending on the new considerations of the used FEM software specifications, such as cable-sag effect, rigid link and gap elements. The modal analysis showed that singular modes of the deck and the tower were relatively effective in the dynamic behavior of the bridge due to higher total mass participation mass ratio of 80%. The parameters and requirements to be considered in simulation process are determined to generate the spatially varying site-specific ground motions. Total number of twelve simulated ground motions are defined for the multi-support earthquake analysis (Mp-sup). In order to easily implement multi-point earthquake excitation to the bridge, the practice-oriented procedure is summarized. The results demonstrated that the Mp-sup led to high increase in sectional forces of the critical components of the bridge, especially tower base section and tensile force of the main and back stay cables. A close relationship between the dynamic response and the behavior of the bridge under the Mp-sup was also obtained. Consequently, the outcomes from this study underscored the importance of the utilization of the multi-point earthquake analysis and the necessity of considering specifically generated earthquake motions for suspension bridges.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.419-431
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• 2018

In this paper, we propose a novel method for monitoring mood trend of Twitter users by analyzing their daily tweets for a long period. Then, to more accurately understand their tweets, we analyze all types of content in tweets, i.e., texts and emoticons, and images, thus develop a multimodal sentiment analysis method. In the proposed method, two single-modal analyses first are performed to extract the users' moods hidden in texts and images: a lexicon-based and learning-based text classifier and a learning-based image classifier. Thereafter, the extracted moods from the respective analyses are combined into a tweet mood and aggregated a daily mood. As a result, the proposed method generates a user daily mood flow graph, which allows us for monitoring the mood trend of users more intuitively. For evaluation, we perform two sets of experiment. First, we collect the data sets of 40,447 data. We evaluate our method via comparing the state-of-the-art techniques. In our experiments, we demonstrate that the proposed multimodal analysis method outperforms other baselines and our own methods using text-based tweets or images only. Furthermore, to evaluate the potential of the proposed method in monitoring users' mood trend, we tested the proposed method with 40 depressive users and 40 normal users. It proves that the proposed method can be effectively used in finding depressed users.

• Archives of design research
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• v.19 no.2 s.64
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• pp.91-98
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• 2006

The product convergence and complex application environment raise the need of multi-modal interface which enables us to interact products through various human senses. The sense of vision has been used predominantly more than any other senses for the traditional and general information gathering situation, but in the future which will be developed based on the digital network technology, the practical use of the various senses will be desired for more convenient and rational usage of the information appliances. The sense of auditory which possibility of practical use is becoming higher than ever with the sense of vision, the possible usage will be developed broader and in the various ways in the future. Based on this situation, the characteristics of the written language and the colloquial language and the comparative analysis of the difference between male and female's reaction for each language were examined through this study. To achieve this purpose, the literature research about the diverse components of the language system was peformed. Then, some peculiar characters of the sense of vision and auditory were reviewed and the appropriate experimentation was planned and carried out. The result of the accomplished experimentation was examined by the objective analysis method. The main results of this study are as follows: first, the reaction time for written language is shorter than colloquial language, second, there is a partial difference between the male's and female's reaction for those two stimuli, third, there is no selection bias between the sense of sight and the sense of hearing. I think the continuous development of the broad and diverse ways of study for various senses is needed based on this study.

• Smart Media Journal
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• v.3 no.1
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• pp.9-15
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• 2014

In these days, along with the extreme popularity of online social network services, it becomes an important problem understanding the role of social network in the research of message dissemination. Past studies of message dissemination over online social network services mostly consider the coverage of message dissemination and the methods to maximize it. But, these works lack of the consideration of the impact of multi channel social network, which has multiple communication channel with distinct properties of message transfer and various users with distinct channel preferences. In this paper, the new message dissemination model over multi-modal multi-channel social network, the Delay Weighted Independent Cascade Model, is proposed. The proposed model considers various channels including online social network service, email, SMS messaging, phone and mouth-to-mouth and their distinct message transfer properties. In order to consider the various user properties, the different value of probability of forwarding a message and the different preference of communication channel is considered. Moreover, the proposed model considers the distribution of user location and allows to analyze the properties of message dissemination under various scenarios. Based on the proposed model, a message dissemination simulator is generated and the message disseminations on various scenarios are analyzed.

• The Journal of the Acoustical Society of Korea
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• v.39 no.4
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• pp.270-278
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• 2020

In this paper, sound transmission of Micro-Perforated Plates (MPPs) installed in an impedance tube with a circular cross-section is described using an analytic method. Vibration of the plates is expressed in terms of an infinite series of modal functions, where modal function in the radial direction is given by the Bessel function. Under the plane wave assumption, a low frequency approximation is derived, and a formula for the sound transmission coefficient of multi-layered MPPs is presented using the transfer matrix method. The Sound Transmission Losses (STLs) of single and double MPPs are computed using the proposed method and compared with those done by the Finite Element Method (FEM), which shows an excellent agreement. As the perforation increases, the STL is degraded, since the STL becomes dominated by the perforation ratio rather than by vibration of the plate. The STL shows dips at natural frequencies as well as at the mass-spring-mass resonance frequency. The proposed model for the STL prediction in this study can be applied to an arbitrary number of MPPs, where each MPP may or may not have a perforation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.91-108
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• 2022

In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.8
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• pp.583-591
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• 2014

The mathematical modeling on the free vibration and stability of a multi-stepped shaft of turbo compressor is performed in this study. The multi-stepped shaft is modeled as a non-uniform Timoshenko beam supported by anisotropic bearings. It is assumed that the shaft is spinning with constant speed about its longitudinal axis and subjected to a conservative axial force induced by front and rear impellers attached to the shaft. The structural model incorporates non-classical features such as transverse shear and rotary inertia. A structural coupling between vertical and lateral motions is induced by Coriolis acceleration terms. The governing equations are derived via Hamilton's variational principle and the equations are transformed to the standard form of an eigenvalue problem. The implications of combined gyroscopic effect, conservative axial force, bearing stiffness and damping are revealed and a number of pertinent conclusions are outlined. In this study analytical results are compared with those from ANSYS finite element analysis and experimental modal testing.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.95-104
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• 2017

This paper deals with solution methods for discrete and multi-valued optimization problems. The objective function of the problem incorporates noise effects generated in case that fitness evaluation is accomplished by computer based experiments such as Monte Carlo simulation or discrete event simulation. Meta heuristics including Genetic Algorithm (GA) and Discrete Particle Swarm Optimization (DPSO) can be used to solve these simulation based multi-valued optimization problems. In applying these population based meta heuristics to simulation based optimization problem, samples size to estimate the expected fitness value of a solution and population (particle) size in a generation (step) should be carefully determined to obtain reliable solutions. Under realistic environment with restriction on available computation time, there exists trade-off between these values. In this paper, the effects of sample and population sizes are analyzed under well-known multi-modal and multi-dimensional test functions with randomly generated noise effects. From the experimental results, it is shown that the performance of DPSO is superior to that of GA. While appropriate determination of population sizes is more important than sample size in GA, appropriate determination of sample size is more important than particle size in DPSO. Especially in DPSO, the solution quality under increasing sample sizes with steps is inferior to constant or decreasing sample sizes with steps. Furthermore, the performance of DPSO is improved when OCBA (Optimal Computing Budget Allocation) is incorporated in selecting the best particle in each step. In applying OCBA in DPSO, smaller value of incremental sample size is preferred to obtain better solutions.