• Journal of the Korean BIBLIA Society for library and Information Science
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• v.29 no.3
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• pp.339-359
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• 2018

The purpose of this study is to suggest a strategy of introduction of Larchiveum, which is a concept of multi cultural space in libraries. Problem of library space programs are discussed in terms of Larchiveum and Maker space, and recently it has been studied in various aspects such as Europeana, GLAM and DPLA from the view point of digital Larchiveum. As a multi cultural space, it is a strategy for constructing Larchiveum that reflects the recent maker's movement. Maker space that explores new ideas and encourages active participation of users, nature and health, curiosity and the construction of an attractive space using ecological concepts as key words. The processes and methods for constructing Larchiveum are classified into 3 types of space configuration, service, program, and operating regulation, and twelve details are laid out to derive the process and method of building Larchiveum as a future type library.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.363-379
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• 2013

Dynamic displacement of structures is an important index for in-service structural condition and behavior assessment, but accurate measurement of structural displacement for large-scale civil structures such as long-span bridges still remains as a challenging task. In this paper, a vision-based dynamic displacement measurement system with the use of digital image processing technology is developed, which is featured by its distinctive characteristics in non-contact, long-distance, and high-precision structural displacement measurement. The hardware of this system is mainly composed of a high-resolution industrial CCD (charge-coupled-device) digital camera and an extended-range zoom lens. Through continuously tracing and identifying a target on the structure, the structural displacement is derived through cross-correlation analysis between the predefined pattern and the captured digital images with the aid of a pattern matching algorithm. To validate the developed system, MTS tests of sinusoidal motions under different vibration frequencies and amplitudes and shaking table tests with different excitations (the El-Centro earthquake wave and a sinusoidal motion) are carried out. Additionally, in-situ verification experiments are performed to measure the mid-span vertical displacement of the suspension Tsing Ma Bridge in the operational condition and the cable-stayed Stonecutters Bridge during loading tests. The obtained results show that the developed system exhibits an excellent capability in real-time measurement of structural displacement and can serve as a good complement to the traditional sensors.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.251-269
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• 2013

Measurement of deflections of certain bridges is usually hampered by corruption of the GPS signal by multipath associated with passing vehicles, resulting to unrealistically large apparent displacements. Field data from the Gorgopotamos train bridge in Greece and systematic experiments revealed that such bias is due to superimposition of two major effects, (i) changes in the geometry of satellites because of partial masking of certain satellites by the passing vehicles (this effect can be faced with solutions excluding satellites that get temporarily blocked by passing vehicles) and (ii) dynamic multipath caused from reflection of satellite signals on the passing trains, a high frequency multipath effect, different from the static multipath. Dynamic multipath seems to have rather irregular amplitude, depending on the geometry of measured satellites, but a typical pattern, mainly consisting of a baseline offset, wide base peaks correlating with the sequence of main reflective surfaces of the vehicles passing next to the antenna. In cases of limited corruption of GPS signal by dynamic multipath, corresponding to scale distortion of the short-period component of the GPS waveforms, we propose an algorithm which permits to reconstruct the waveform of bridge deflections using a weak fusion of GPS and RTS data, based on the complementary characteristics of the two instruments. By application of the proposed algorithm we managed to extract semi-static and dynamic displacements and oscillation frequencies of a historical railway bridge under train loading by using noisy GPS and RTS recordings. The combination of GPS and RTS is possible because these two sensors can be fully collocated and have complementary characteristics, with RTS and GPS focusing on the long- and short-period characteristics of the displacement, respectively.

• Smart Structures and Systems
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• v.20 no.6
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• pp.683-696
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• 2017

In this study, the reliability of nonlinear ultrasonic modulation based fatigue crack detection is improved using a feature-level data fusion approach. When two ultrasonic inputs at two distinct frequencies are applied to a specimen with a fatigue crack, modulation components at the summation and difference of these two input frequencies appear. First, the spectral amplitudes of the modulation components and their spectral correlations are defined as individual features. Then, a 2D feature space is constructed by combining these two features, and the presence of a fatigue crack is identified in the feature space. The effectiveness of the proposed fatigue crack detection technique is experimentally validated through cyclic loading tests of aluminum plates, full-scale steel girders and a rotating shaft component. Subsequently, the improved reliability of the proposed technique is quantitatively investigated using receiver operating characteristic analysis. The uniqueness of this study lies in (1) improvement of nonlinear ultrasonic modulation based fatigue crack detection reliability using feature-level data fusion, (2) reference-free fatigue crack diagnosis without using the baseline data obtained from the intact condition of the structure, (3) application to full-scale steel girders and shaft component, and (4) quantitative investigation of the improved reliability using receiver operating characteristic analysis.

• Smart Structures and Systems
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• v.20 no.6
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• pp.769-780
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• 2017

Cable force monitoring is an essential and critical part of the safety evaluation of cable-supported bridges. A reasonable cable force monitoring scheme, particularly, sensor placement related to accurate safety assessment and budget cost-saving becomes a major concern of bridge administrative authorities. This paper presents optimal sensor placement for cable force monitoring by selecting representative sensor positions, which consider the spatial correlativeness existing in the cable group. The limited sensors would be utilized for maximizing useful information from the monitored bridges. The maximum information coefficient (MIC), mutual information (MI) based kernel density estimation, as well as Pearson coefficients, were all employed to detect potential spatial correlation in the cable group. Compared with the Pearson coefficient and MIC, the mutual information is more suitable for identifying the association existing in cable group and thus, is selected to describe the spatial relevance in this study. Then, the bond energy algorithm, which collects clusters based on the relationship of surrounding elements, is used for the optimal placement of cable sensors. Several optimal placement strategies are discussed with different correlation thresholds for the cable group of Nanjing No.3 Yangtze River Bridge, verifying the effectiveness of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1239-1244
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• 2013

In the field of clinical medicine and research, the analysis of such as protein and DNA at the molecular level and even at the cell level are necessary for disease diagnosis and treatment. In many cases, a real time image of samples is needed for the accurate analysis and manipulation of samples since experimental samples are degenerated with time. In this research, a three-dimensional fluorescence microscope device was developed for taking images of protein and DNA inside a single cell and the server-client based image analysis system was made for an integrated management of the real-time images taken from the microscope device. The system consists of a fluorescent measurement device, the associated software and a client program on smartphone. The developed system allows doctors or experimental managers to receive and look at the real-time experimental images taken from the samples of patients anywhere in the emergency, to analyze results and to instantly diagnose the disease and to transfer the results to the patients. As a result, the system is able to be utilized in the implementation of ubiquitous health as well.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1954-1961
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• 2011

The concept of sustainability in residential area is closely related to the notion of amenity, livability, health and interchangeably used with the terms of urban growth management, urban regeneration, new urbanism, urban village movement, compact development, smart growth and the quality of residential environment. Residential Performance Management System (RPMS This system is developed granted by 'Korea Institute of Construction & Transportation Technology Evaluation and Planning' (KICTEP) during 2005-2008.)is a kind of decision making supportive program developed for the evaluation and assessment of various urban performances. It can be utilized for various purposes by many of urban related expert like planner, manager, etc. This study investigate the schematic model for the applying the indicators of quality of residential environment developed by SDI (Seoul Development Institute) using RPMS.

• Journal of Fashion Business
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• v.20 no.4
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• pp.153-171
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• 2016

With the advent of smart clothing for health care and sports, the sophisticated designs with curved seams are drawing attention. One of the problems in those clothing is to determine the design curves in 2D pattern, such that it corresponds to the lines on the intended 3D body. Moreover, the difficulty increases when the original pattern needs to be changed for various sizes and body types. We compare two methods of pattern enlargement in this paper: one is the offset/projection type, and the other is the split grading type. For the enlarged pattern with offset/projection type, the 3D surface offset was first adopted to transform the standard lower body to the target larger size; next, the design lines were projected to the new 3D surface, following which the 3D pattern was developed from the newly transformed 3D surface. In the second method, the enlarged pant patterns were developed by the split grading method. Here, a 3D pattern was developed from the initial body, and then enlarged to the target size by the conventional split grading method. Two feminine pants patterns were examined by 3D virtual fitting. We observed that the 3D offset/projection pants pattern was well fitted, having an evenly distributed surplus, as compared with the sample developed using the split grading method. The difference between the two patterns were apparent at the location where several curved lines merged.

• Smart Structures and Systems
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• v.25 no.3
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• pp.369-384
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• 2020

A wavefield sparse reconstruction technique based on compressed sensing is developed in this work to dramatically reduce the number of measurements. Firstly, a severely underdetermined representation of guided wavefield at a snapshot is established in the spatial domain. Secondly, an optimal compressed sensing model of guided wavefield sparse reconstruction is established based on l₁-norm penalty, where a suite of discrete cosine functions is selected as the dictionary to promote the sparsity. The regular, random and jittered undersampling schemes are compared and selected as the undersampling matrix of compressed sensing. Thirdly, a gradient projection method is employed to solve the compressed sensing model of wavefield sparse reconstruction from highly incomplete measurements. Finally, experiments with different excitation frequencies are conducted on an aluminum plate to verify the effectiveness of the proposed sparse reconstruction method, where a scanning laser Doppler vibrometer as the true benchmark is used to measure the original wavefield in a given inspection region. Experiments demonstrate that the missing wavefield data can be accurately reconstructed from less than 12% of the original measurements; The reconstruction accuracy of the jittered undersampling scheme is slightly higher than that of the random undersampling scheme in high probability, but the regular undersampling scheme fails to reconstruct the wavefield image; A quantified mapping relationship between the sparsity ratio and the recovery error over a special interval is established with respect to statistical modeling and analysis.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.9
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• pp.29-35
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• 2019

The structure of the machinery industry due to the 4th industrial revolution is changing from precision and durability to intelligent and smart machinery through sensing and interconnection(IoT). There is a growing need for research on prognostics and health management(PHM) that can prevent abnormalities in processing machines and accurately predict and diagnose conditions. PHM is a technology that monitors the condition of a mechanical system, diagnoses signs of failure, and predicts the remaining life of the object. In this study, the vibration generated during machining is measured and a classification algorithm for normal and fault signals is developed. Arbitrary fault signal is collected by changing the conditions of un stable supply cutting oil and fixing jig. The signal processing is performed to apply the measured signal to the learning model. The sampling rate is changed for high speed operation and performed machine learning using raw signal without FFT. The fault classification algorithm for 1D convolution neural network composed of 2 convolution layers is developed.