• Title/Summary/Keyword: Structure-mapping Model

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Structural Response and Reliability of a Cylindrical Array Sensor due to Underwater Explosion (수중폭발에 의한 원통형 배열센서의 구조 응답 및 안정성 해석)

  • Jeon, Soo-Hong;Hong, Chin-Suk;Jeong, Weui-Bong;Seo, Hee-Seon;Cho, Yo-Han
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.22 no.1
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    • pp.81-87
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    • 2012
  • This paper establishes a modeling and simulation procedure for structural response and reliability of a cylindrical array sensor on submarines under the shock generated by underwater explosion. The structural reliability of SONAR is important because the submarine could get out of combat ability by the structural damage of the SONAR upon explosion. A cylindrical array sensor was first modeled using the finite element method. Modal analysis was then performed for the check of the reliability of the modeling. The shock resistance simulations were performed for the responses to the structural shock waves and for the responses to the directly applied underwater shock waves, according to BV-043 and MIL-STD-901D, respectively. The stresses of the structure were evaluated with von-Mises scheme. Vulnerable regions were exposed through mapping the maximum stress to the structural model. Maximum stress of the SONAR was compared with the yield stress of the material to examine the structural reliability.

Emergent damage pattern recognition using immune network theory

  • Chen, Bo;Zang, Chuanzhi
    • Smart Structures and Systems
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    • v.8 no.1
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    • pp.69-92
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    • 2011
  • This paper presents an emergent pattern recognition approach based on the immune network theory and hierarchical clustering algorithms. The immune network allows its components to change and learn patterns by changing the strength of connections between individual components. The presented immune-network-based approach achieves emergent pattern recognition by dynamically generating an internal image for the input data patterns. The members (feature vectors for each data pattern) of the internal image are produced by an immune network model to form a network of antibody memory cells. To classify antibody memory cells to different data patterns, hierarchical clustering algorithms are used to create an antibody memory cell clustering. In addition, evaluation graphs and L method are used to determine the best number of clusters for the antibody memory cell clustering. The presented immune-network-based emergent pattern recognition (INEPR) algorithm can automatically generate an internal image mapping to the input data patterns without the need of specifying the number of patterns in advance. The INEPR algorithm has been tested using a benchmark civil structure. The test results show that the INEPR algorithm is able to recognize new structural damage patterns.

Business Collaborative System Based on Social Network Using MOXMDR-DAI+

  • Lee, Jong-Sub;Moon, Seok-Jae
    • International Journal of Advanced Culture Technology
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    • v.8 no.3
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    • pp.223-230
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    • 2020
  • Companies have made an investment of cost and time to optimize processing of a new business model in a cloud environment, applying collaboration technology utilizing business processes in a social network. The collaborative processing method changed from traditional BPM to the cloud and a mobile cloud environment. We proposed a collaborative system for operating processes in social networks using MOXMDR-DAI+ (eXtended Metadata Registry-Data Access & Integration based multimedia ontology). The system operating cloud-based collaborative processes in application of MOXMDR-DAI+, which was suitable for data interoperation. MOXMDR-DAI+ applied to this system was an agent effectively supporting access and integration between multimedia content metadata schema and instance, which were necessary for data interoperation, of individual local system in the cloud environment, operating collaborative processes in the social network. In operating the social network-based collaborative processes, there occurred heterogeneousness such as schema structure and semantic collision due to queries in the processes and unit conversion between instances. It aimed to solve the occurrence of heterogeneousness in the process of metadata mapping using MOXMDR-DAI+ in the system. The system proposed in this study can visualize business processes. And it makes it easier to operate the collaboration process through mobile support. Real-time status monitoring of the operation process is possible through the dashboard, and it is possible to perform a collaborative process through expert search using a community in a social network environment.

ANALYSIS OF THE CHARACTERISTICS ABOUT GYEONG-GANG FAULT ZONE THROUGH REMOTE SENSING TECHNIQUES

  • Hwang, Jin-Kyong;Choi, Jong-Kuk;Won, Joong-Sun
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.196-199
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    • 2008
  • Lineament is defined generally as a linear feature or pattern on interpretation of a satellite image and indicates the geological structures such as faults and fractures. For this reason, a lineament extraction and analysis using remote sensing images have been widely used for mapping large areas. The Gyeong-gang Fault is a NNE trending structure located in Gangwon-do and Kyeonggi-do district. However, a few geological researches on that fault have been carried out and its trace or continuity is ambiguous. In this study, we investigate the geologic features at Gyeong-gang Fault Zone using LANDSAT ETM+ satellite image and SRTM digital elevation model. In order to extract the characteristics of geologic features effectively, we transform the LANDSAT ETM+ image using Principal Component Analysis (PCA) and create a shade relief from SRTM data with various illumination angles. The results show that it is possible to identify the dimensions and orientations of the geologic features at Gyeong-gang Fault Zone using remote sensing data. An aerial photograph interpretation and a field work will be future tasks for more accurate analysis in this area.

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A Study on XML Document Repository Management System using ODMG Object Model (ODMG 객체 모델 기반의 XML 문서 저장 관리 시스템에 관한 연구)

  • 박준범;박경우;오수열
    • Journal of the Korea Society of Computer and Information
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    • v.8 no.2
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    • pp.16-23
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    • 2003
  • In most organizations, the relational DBMS was used for store and manage XML documents due to the pre-established relational DBMS. But, relational DBMS has some problems. They has the possibilities of informational loses in the process of mapping the structure of XML documents to RDB, and they require expensive cost to reflect all XML properties. Thus, this paper was intended to design and implement XML document management system which utilize O2 DBMS-object oriented DBMS in order to overcome the existing problem and reflect all XML Properties. The XML document management system purposed in this thesis has multiple function, such as the library service function for XML documents-check-in/check-out, versioning, user access management-, dynamic indexing and retrieval, and publishing function using style sheet.

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A Semi-automated Method to Extract 3D Building Structure

  • Javzandulam, Tsend-Ayush;Kim, Tae-Jung;Kim, Kyung-Ok
    • Korean Journal of Remote Sensing
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    • v.23 no.3
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    • pp.211-219
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    • 2007
  • Building extraction is one of the essential issues for 3D city modelling. In recent years, high-resolution satellite imagery has become widely available and it brings new methodology for urban mapping. In this paper, we have developed a semi-automatic algorithm to determine building heights from monoscopic high-resolution satellite data. The algorithm is based on the analysis of the projected shadow and actual shadow of a building. Once two roof comer points are measured manually, the algorithm detects (rectangular) roof boundary automatically. Then it estimates a building height automatically by projecting building shadow onto the image for a given building height, counting overlapping pixels between the projected shadow and actual shadow, and finding the height that maximizes the number of overlapping pixels. Once the height and roof boundary are available, the footprint and a 3D wireframe model of a building can be determined. The proposed algorithm is tested with IKONOS images over Deajeon city and the result is compared with the building height determined by stereo analysis. The accuracy of building height extraction is examined using standard error of estimate.

Estimating the maximum pounding force for steel tall buildings in proximity subjected to wind

  • Tristen Brown;Ahmed Elshaer;Anas Issa
    • Wind and Structures
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    • v.39 no.1
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    • pp.47-69
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    • 2024
  • Pounding of structures may result in considerable damages, to the extent of total failure during severe lateral loading events (e.g., earthquakes and wind). With the new generation of tall buildings in densely occupied locations, wind-induced pounding becomes of higher risk due to such structures' large deflections. This paper aims to develop mathematical formulations to determine the maximum pounding force when two adjacent structures come into contact. The study will first investigate wind-induced pounding forces of two equal-height structures with similar dynamic properties. The wind loads will be extracted from the Large Eddy Simulation models and applied to a Finite Element Method model to determine deflections and pounding forces. A Genetic Algorithm is lastly utilized to optimize fitting parameters used to correlate the maximum pounding force to the governing structural parameters. The results of the wind-induced pounding show that structures with a higher natural frequency will produce lower maximum pounding forces than those of the same structure with a lower natural frequency. In addition, taller structures are more susceptible to stronger pounding forces at closer separation distances. It was also found that the complexity of the mathematical formula from optimization depends on achieving a more accurate mapping for the trained database.

Measurement Accuracy for 3D Structure Shape Change using UAV Images Matching (UAV 영상정합을 통한 구조물 형상변화 측정 정확도 연구)

  • Kim, Min Chul;Yoon, Hyuk Jin;Chang, Hwi Jeong;Yoo, Jong Soo
    • Journal of Korean Society for Geospatial Information Science
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    • v.25 no.1
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    • pp.47-54
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    • 2017
  • Recently, there are many studies related aerial mapping project and 3 dimensional shape and model reconstruction using UAV(unmanned aerial vehicle) system and images. In this study, we create 3D reconstruction point data using image matching technology of the UAV overlap images, detect shape change of structure and perform accuracy assessment of area($m^2$) and volume($m^3$) value. First, we build the test structure model data and capturing its images of shape change Before and After. Second, for post-processing the Before dataset is convert the form of raster format image to ensure the compare with all 3D point clouds of the After dataset. The result shows high accuracy in the shape change of more than 30 centimeters, but less is still it becomes difficult to apply because of image matching technology has its own limits. But proposed methodology seems very useful to detect illegal any structures and the quantitative analysis of the structure's a certain amount of damage and management.

Error Analysis of Linear Mixture Model using Laboratory Spectral Measurements (실내 분광 측정자료를 이용한 선형혼합모델의 오차 분석)

  • Kim, Sun-Hwa;Shin, Jung-Il;Shin, Sang-Min;Lee, Kyu-Sung
    • Korean Journal of Remote Sensing
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    • v.23 no.6
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    • pp.537-546
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    • 2007
  • In hyperspectral remote sensing, linear spectral mixture model is a common procedure decomposing into the components of a mixed pixel and estimating the fraction of each end-member. Although linear spectral mixture model is frequently used in geology and mineral mapping because this model is simple and easy to apply, this model is not always valid in forest and urban area having rather complex structure. This study aims to analyze possible error for applying linear spectral mixture model. For the study, we measured laboratory spectra of mixture sample, having various materials, fractions, distributions. The accuracy of linear mixture model is low with the mixture sample having similar fraction because the multi-scattering between components is maximum. Additionally, this multi-scattering is related to the types, fraction, and distribution of components. Further analysis is necessary to quantify errors from linear spectral mixture model.

An Artificial Neural Networks Model for Predicting Permeability Properties of Nano Silica-Rice Husk Ash Ternary Blended Concrete

  • Najigivi, Alireza;Khaloo, Alireza;zad, Azam Iraji;Rashid, Suraya Abdul
    • International Journal of Concrete Structures and Materials
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    • v.7 no.3
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    • pp.225-238
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    • 2013
  • In this study, a two-layer feed-forward neural network was constructed and applied to determine a mapping associating mix design and testing factors of cement-nano silica (NS)-rice husk ash ternary blended concrete samples with their performance in conductance to the water absorption properties. To generate data for the neural network model (NNM), a total of 174 field cores from 58 different mixes at three ages were tested in the laboratory for each of percentage, velocity and coefficient of water absorption and mix volumetric properties. The significant factors (six items) that affect the permeability properties of ternary blended concrete were identified by experimental studies which were: (1) percentage of cement; (2) content of rice husk ash; (3) percentage of 15 nm of $SiO_2$ particles; (4) content of NS particles with average size of 80 nm; (5) effect of curing medium and (6) curing time. The mentioned significant factors were then used to define the domain of a neural network which was trained based on the Levenberg-Marquardt back propagation algorithm using Matlab software. Excellent agreement was observed between simulation and laboratory data. It is believed that the novel developed NNM with three outputs will be a useful tool in the study of the permeability properties of ternary blended concrete and its maintenance.