• Smart Structures and Systems
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• v.6 no.3
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• pp.335-347
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• 2010

Recent advances in hardware and instrumentation technology have allowed the possibility of deploying very large sensor arrays on structures. Exploiting the huge amount of data that can result in order to perform vibration-based structural health monitoring (SHM) is not a trivial task and requires research into a number of specific problems. In terms of pressing problems of interest, this paper discusses: the design and optimisation of appropriate sensor networks, efficient data reduction techniques, efficient and automated feature extraction methods, reliable methods to deal with environmental and operational variability, efficient training of machine learning techniques and multi-scale approaches for dealing with very local damage. The paper is a result of the ESF-S3T Eurocores project "Smart Sensing For Structural Health Monitoring" (S3HM) in which a consortium of academic partners from across Europe are attempting to address issues in the design of automated vibration-based SHM systems for structures.

• Smart Structures and Systems
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• v.15 no.3
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• pp.699-715
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• 2015

A modal parameter based damage sensitive feature (DSF) is defined to mimic the relative change in any diagonal element of the stiffness matrix of a model of a structure. The damage assessment is performed in a statistical pattern recognition framework using empirical complementary cumulative distribution functions (ECCDFs) of the DSFs extracted from measured operational vibration response data. Methods are discussed to perform probabilistic structural health assessment with respect to the following questions: (a) "Is there a change in the current state of the structure compared to the baseline state?", (b) "Does the change indicate a localized stiffness reduction or increase?", with the latter representing a situation of retrofitting operations, and (c) "What is the severity of the change in a probabilistic sense?". To identify a range of normal structural variations due to environmental and operational conditions, lower and upper bound ECCDFs are used to define the baseline structural state. Such an approach attempts to decouple "non-damage" related variations from damage induced changes, and account for the unknown environmental/operational conditions of the current state. The damage assessment procedure is discussed using numerical simulations of ambient vibration testing of a bridge deck system, as well as shake table experimental data from a 4-story steel frame.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.345-361
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• 2013

Locating and assessing the severity of damage in large or complex structures is one of the most challenging problems in the field of civil engineering. Considering that the wavelet packet transform (WPT) has the ability to clearly reflect the damage characteristics of structural response signals and the artificial neural network (ANN) is capable of learning in an unsupervised manner and of forming new classes when the structural exhibits change, this paper investigates a multi-stage structural damage diagnosis method by using the WPT and ANN based on "energy-damage" theory, in which, the wavelet packet component energies are first extracted to be damage sensitive feature and then adopted as input into an improved back propagation (BP) neural network model for damage diagnosis in a step by step mode. To validate the efficacy of the presented approach of the damage diagnosis, the benchmark structure of the American Society of Civil Engineers (ASCE) is employed in the case study. The results of damage diagnosis indicate that the method herein is computationally efficient and is able to detect the existence of different damage patterns in the simulated experiment where minor, moderate and severe damages corresponds to involving in the loss of stiffness on braces or the removal bracing in various combinations.

• Smart Structures and Systems
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• v.4 no.6
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• pp.759-777
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• 2008

A wireless sensing system is designed for application to structural monitoring and damage detection applications. Embedded in the wireless monitoring module is a two-tier prediction model, the auto-regressive (AR) and the autoregressive model with exogenous inputs (ARX), used to obtain damage sensitive features of a structure. To validate the performance of the proposed wireless monitoring and damage detection system, two near full scale single-story RC-frames, with and without brick wall system, are instrumented with the wireless monitoring system for real time damage detection during shaking table tests. White noise and seismic ground motion records are applied to the base of the structure using a shaking table. Pattern classification methods are then adopted to classify the structure as damaged or undamaged using time series coefficients as entities of a damage-sensitive feature vector. The demonstration of the damage detection methodology is shown to be capable of identifying damage using a wireless structural monitoring system. The accuracy and sensitivity of the MEMS-based wireless sensors employed are also verified through comparison to data recorded using a traditional wired monitoring system.

• East Asian Economic Review
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• v.18 no.1
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• pp.55-81
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• 2014

This study aims to answer two questions using input-output decomposition analysis: 1) Have emerging Asian economies decoupled? 2) What are the sources of structural changes in gross outputs and value-added of emerging Asian economies related to the first question? The main findings of the study are as follows: First, since 1990, there has been a trend of increasing dependence on exports to extra-regions such as G3 and the ROW, indicating no sign of "decoupling", but rather an increasing integration of emerging Asian countries into global trade. Second, there is a contrasting feature in the sources of structural changes between non-China emerging Asia and China. Dependence of non-China emerging Asia on intra-regional trade has increased in line with strengthening economic integration in East Asia, whereas China has disintegrated from the region. Therefore, it can be said that China has contributed to no sign of decoupling of emerging Asia as a whole.

• Smart Structures and Systems
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• v.23 no.3
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• pp.279-293
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• 2019

To ensure high quality data being used for data mining or feature extraction in the bridge structural health monitoring (SHM) system, a practical sensor fault diagnosis methodology has been developed based on the similarity of symmetric structure responses. First, the similarity of symmetric response is discussed using field monitoring data from different sensor types. All the sensors are initially paired and sensor faults are then detected pair by pair to achieve the multi-fault diagnosis of sensor systems. To resolve the coupling response issue between structural damage and sensor fault, the similarity for the target zone (where the studied sensor pair is located) is assessed to determine whether the localized structural damage or sensor fault results in the dissimilarity of the studied sensor pair. If the suspected sensor pair is detected with at least one sensor being faulty, field test could be implemented to support the regression analysis based on the monitoring and field test data for sensor fault isolation and reconstruction. Finally, a case study is adopted to demonstrate the effectiveness of the proposed methodology. As a result, Dasarathy's information fusion model is adopted for multi-sensor information fusion. Euclidean distance is selected as the index to assess the similarity. In conclusion, the proposed method is practical for actual engineering which ensures the reliability of further analysis based on monitoring data.

• Korean Journal of Social Welfare
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• v.61 no.3
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• pp.283-305
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• 2009

The purpose of this study is to develop a scale for the social network of college students in Korea. The social network scale for college students in this paper was developed through 1) literature review and item development 2) focus-group meeting 3) depth-interview with college students 4) pilot-studies and 5) study. The scale of 23 items has been constructed with three features : The first is 'relational feature' with 2 items; the second 'structural feature' with 7 items; and the third 'functional feature' with 14 items. The functional feature in this social network scale has consisted of emotional, economic, spiritual, and socio-relational aspects and has been revealed to the validity and the reliability of Cronbach's ${\alpha}$ 0.716. This study would contribute for college students to solve the many problems in their own lives through the social networks.

• Korean Journal of Human Ecology
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• v.23 no.3
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• pp.515-527
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• 2014

This study is intended to develop the creative and high value-added products as well as the development of diversity for jump suit for the future by analyzing the trend and feature shown in jump suit in the modern fashion. In the research methodology, the analysis was carried out over a total of 351 work pieces on jump suit among those presented in the collection of Paris, Milan, New York and London from 2006S/S to 2013F/W as well as literature review. The aesthetic features on suit jump design introduced in the modern fashion could be characterized as the following. First, both upper and lower garments are composed with a simple array of items and the stress was put on modernity feature through minimal expression technique. The feature of solid simplicity was also given with achromatic color or neutral monochrome. Second, the feminity image was emphasized with adoption of such highlighting items as detailed add-ons, tops, camisoles and blouses that stress the organically curved streamline including silhouette, material itself, crease and drape that enable the direct and indirect exposition of human body and the expression of smooth curve in human body. Third, jump suit revealed the multipurpose feature as item available for the diverse wear such as working habiliment, sports wear, uniform, office wear and evening wear, depending on the terms and conditions. Fourth, the deconstructive characteristic appeared through integration with various items, destruction of formative structure, non-structural shape, and ambiguity in wearing method.

• The Journal of Industrial Distribution & Business
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• v.12 no.5
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• pp.47-58
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• 2021

Purpose - Current research aimed at exploring the effect differences between the two types of processing product information such as the imagining and the considering on psychological product ownership which could influence the intent to purchase or use the product, and focused on identifying the interaction effects of activated memory information type and advertising information type on each of the information processing types. Research design, data, and methodology - This study divided the information processing types into imagining and considering, and the consumer's memories were divided into autobiographical or episodic and semantic memory. The advertising information was approached in each of event information being together with the product and product feature information. At empirical study, 2(two types of memory activation: episodic and semantic memory activation) ∗ 2(two types of advertising information: event-focused and product feature-focused advertising information) between-subjects design was used to make four types of questionnaire according to the type of experimental groups. Through the survey platform, 'questionnaire stars' of 'WeChat' in China, 219 questionnaire data were collected for empirical study. The structural equation model in AMOS 26 and Anova were used to verify hypotheses. Results - First, the ownership affected the usage intent positively. Second, the imagining did not affect the psychological ownership but did directly affect the usage intention, and the considering affected the ownership positively. Third, the episodic memory activation positively influenced the imagining and negatively affected the considering, whereas the semantic memory activation positively influenced the considering and negatively affected the imagining. Fourth, event-advertising information increased the effects of the activated episodic memory on the imagining, and feature-advertising information increased the effects of the activated semantic memory on the considering. Conclusions - marketers should develop and advertise their product-related event message to trigger the imaging that directly increase the intent to purchase or use their product, when consumers are under the activation of their episodic memory. And marketers should advertise their product feature-related message to trigger the considering that could induce consumers' ownership for their product to increase the intent to purchase or use their product, when they are under the activation of their semantic memory.

• The Journal of the Acoustical Society of Korea
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• v.37 no.1
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• pp.73-81
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• 2018

The quality of side scan sonar images is determined by the frequency of a sonar. A side scan sonar with a low frequency creates low-quality images. One of the factors that lead to low quality is a high-level noise. The noise is occurred by the underwater environment such as equipment noise, signal interference and so on. In addition, in order to compensate for the transmission loss of sonar signals, the received signal is recovered by TVG (Time-Varied Gain), and consequently the side scan sonar images contain non-homogeneous noise which is opposite to optic images whose noise is assumed as homogeneous noise. In this paper, the SSCS (Structural Sparsity based Compressive Sensing) is proposed for removing non-homogeneous noise. The algorithm incorporates both local and non-local models in a structural feature domain so that it guarantees the sparsity and enhances the property of non-local self-similarity. Moreover, the non-local model is corrected in consideration of non-homogeneity of noises. Various experimental results show that the proposed algorithm is superior to existing method.