• Journal of Consumption Culture
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• v.15 no.3
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• pp.67-90
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• 2012

When consumers choose healthy foods, they base their buying decisions on health-related food labeling and quality assessment of taste, health, and price. Moreover, both purchase experience and opinions of family and friends affect consumer choices. Focusing on these points, this study examined the effects of health-related food labeling on consumer choices by adding two variables-quality assessment of taste, health, and price and purchase experience-to the model of the theory of planned behavior. We also used structural equation modeling to test our hypotheses. In the study, health-related food labeling includes organic labeling, nutrient claims, and food additive labeling. We conducted a mail survey among 300 married women who buy cheese slices for their children more than once a month. It was discovered that health-related food labeling positively affected the level of quality assessment of taste, health, and price, and consequently led to positive attitudes and purchase intentions. Particularly, health-related food labeling positively influenced attitude toward using products without assessing the quality of taste, health, and price. The level of quality assessment of price positively affected attitude toward using and purchasing products, and purchase experience positively affected attitude toward using and purchasing products, and purchase intentions. The relationship between attitude to purchasing products and purchase intentions was the most positive, and the relationship between perceived behavioral control and purchase intentions was not significant. Overall, this study essentially contributes to the development of a theoretical framework of food labeling and consumer choices, which includes quality assessment of taste, health, and price and purchase experience, by using the theory of planned behavior.

• Journal of Korean Academy of Nursing
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• v.54 no.1
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• pp.106-117
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• 2024

Purpose: This study examined the effects of stress vulnerability and parental burnout on the mental health of women with early school-aged children, with a focus on the mediating role of spirituality. Methods: A survey was conducted among 171 women with early schoolaged children in Gyeonggi Province, Gangwon Province, and Seoul. Data were collected from September to December 2022 using the Korean-Symptom Check List 95, the Parental Burnout Assessment, and the Spirituality Assessment Scale. The data were analyzed using structural equation modeling with SPSS/WIN 22.0 and AMOS 20.0. Results: The study model demonstrated a good fit, explaining 40.5% of the variance in mental health through stress vulnerability, parental burnout, and spirituality. Spirituality had a significant direct impact on mental health. Additionally, participants' spirituality directly influenced their mental health, while stress vulnerability and parental burnout indirectly affected their mental health and were mediated through spirituality. Conclusion: Stress vulnerability and parental burnout are negatively associated with mental health, while spirituality partially mediates these effects. Implementing a program to promote spirituality is suggested to assist mothers in recognizing the value and meaning of parenting activities during nursing interventions for mental health.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.4
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• pp.349-354
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• 2009

To rationally secure and maintain the safety and serviceability of a high-rise building, monitoring of structural responses of members is necessary. As such health monitoring of large-scale building structures has received growing attention by researchers in recent years. However, due to a very large number of members complexity of structural responses of a high-rise building structure, practical difficulties exist in selection of structural members to be sensored for assessment of structural safety of a structure. In this paper, a selection technique for active members for safety monitoring of a high-rise building based on displacement participation factor and strain energy density of a member is investigated.

• Structural Engineering and Mechanics
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• v.23 no.1
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• pp.75-95
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• 2006

Two-step identification approaches for effective bridge health monitoring are proposed to alleviate the issues associated with many unknown parameters faced in real structures and to improve the accuracy in the estimate results. It is suitable for on-line monitoring scheme, since the damage assessment is not always needed to be carried out whereas the alarming for damages is to be continuously monitored. In the first step for screening potentially damaged members, a damage indicator method based on modal strain energy, probabilistic neural networks and the conventional neural networks using grouping technique are utilized and then the conventional neural networks technique is utilized for damage assessment on the screened members in the second step. The effectiveness of the proposed methods is investigated through a field test on the northern-most span of the old Hannam Grand Bridge over the Han River in Seoul, Korea.

• Structural Engineering and Mechanics
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• v.49 no.4
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• pp.509-521
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• 2014

In this paper two protocols of Wireless Sensor Networks (WSN) are examined through both a simulation and a case study. The simulation was performed with the optimized network (OPNET) simulator while comparing the performance of the Ad-Hoc on demand Distance Vector (AODV) and the Dynamic Source Routing (DSR) protocols. This is compared and shown with real-world measurement of deflection from eight wireless sensor nodes. The wireless sensor response results were compared with accelerometer sensors for validation purposes. It was found that although the computer simulation suggests the AODV protocol is more accurate, in the case study no distinct difference was found. However, it was shown that AODV is still more beneficial in the field as it has a longer battery life enabling longer surveying times. This is a significant finding as a large factor in determining the use of wireless network sensors as a method of assessing structural response has been their short battery life. Thus if protocols which enhance battery life, such as the AODV protocol, are employed it may be possible in the future to couple wireless networks with solar power extending their monitoring periods.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.21-32
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• 2003

Developments and applications of the structural health monitoring (SHM) systems have become active particularity for long-span bridges in Korea. They are composed of sensors, data acquisition system, data transmission system, information processing, damage assessment, and information management. In this paper, current status of research and application activities on SHM systems for civil infra-structures in Korea are briefly introduced by 4 parts: (1) current status of bridge monitoring systems on existing and newly constructed bridges, (2) research and development activities on smart sensors such as optical fiber sensors and piezo-electric sensors, (3) structural damage detection methods using measured data, and (4) a test road project for pavement design verification and enhancement by the Korea Highway Corporation. Finally the R＆D activities of a new engineering research center entitled Smart Infra-Structure Technology Center at Korea Advanced Institute of Science and Technology are also briefly described.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.751-760
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• 2017

In recent years, multifractal-based analysis methods have been widely applied in engineering. Among these methods, multifractal detrended cross-correlation analysis (MFDXA), a branch of fractal analysis, has been successfully applied in the fields of finance and biomedicine. For its great potential in reflecting the subtle characteristic among signals, a structural health monitoring (SHM) system based on MFDXA is proposed. In this system, damage assessment is conducted by exploiting the concept of multifractal theory to quantify the complexity of the vibration signal measured from a structure. According to the proposed algorithm, the damage condition is first distinguished by multifractal detrended fluctuation analysis. Subsequently, the relationship between the q-order, q-order detrended covariance, and length of segment is further explored. The dissimilarity between damaged and undamaged cases is visualized on contour diagrams, and the damage location can thus be detected using signals measured from different floors. Moreover, a damage index is proposed to efficiently enhance the SHM process. A seven-story benchmark structure, located at the National Center for Research on Earthquake Engineering (NCREE), was employed for an experimental verification to demonstrate the performance of the proposed SHM algorithm. According to the results, the damage condition and orientation could be correctly identified using the MFDXA algorithm and the proposed damage index. Since only the ambient vibration signal is required along with a set of initial reference measurements, the proposed SHM system can provide a lower cost, efficient, and reliable monitoring process.

• Structural Engineering and Mechanics
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• v.50 no.1
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• pp.105-119
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• 2014

This study presents a steel container crane movement analysis and assessment based on structural health monitoring (SHM). The accelerometers are used to monitor the dynamic crane behavior and a 3-D finite element model (FEM) was designed to express the static displacement of the crane under the different load cases. The multi-input single-output nonlinear autoregressive neural network with external input (NNARX) model is used to identify the crane dynamic displacements. The FEM analysis and the identification model are used to investigate the safety and the vibration state of the crane in both time and frequency domains. Moreover, the SHM system is used based on the FEM analysis to assess the crane behavior. The analysis results indicate that: (1) the mean relative dynamic displacement can reveal the relative static movement of structures under environmental load; (2) the environmental load conditions clearly affect the crane deformations in different load cases; (3) the crane deformations are shown within the safe limits under different loads.

• Smart Structures and Systems
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• v.5 no.4
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• pp.357-367
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• 2009

Structural Health Monitoring (SHM), particularly remote monitoring, is an emerging field with great potential to help infrastructure owners obtain more and up-to-date knowledge of their structures. The methodology could provide supplemental information to guide the frequency and extent of visual inspections, and the possible need for maintenance. The instrumentation for a SHM system needs to be developed with longevity and the objectives for the system in mind. Sensors need to be selected for reliability and durability, sited where they provide the maximum information for the objectives, and where they can be accessed and replaced should the need arise over the monitoring period. With the rapid changes now occurring with sensors and software, flexibility needs to be in place to allow the system to be upgraded over time. Damage detection needs to be considered in terms of the type of damage that needs to be detected, informing maintenance requirements, and how detection can be achieved. Current vibration analysis techniques appear not yet to have achieved the necessary sensitivity for that purpose. Societal factors will influence the design of a SHM system in terms of the sophistication of the instrumentation and methodology employed.

• Smart Structures and Systems
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• v.17 no.6
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• pp.995-1015
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• 2016

In the design and condition assessment of bridges, it is usually necessary to take into consideration the extreme conditions which are not expected to occur within a short time period and thus require an extrapolation from observations of limited duration. Long-term structural health monitoring (SHM) provides a rich database to evaluate the extreme conditions. This paper focuses on the extrapolation of extreme traffic load effects on bridges using long-term monitoring data of structural strain. The suspension Tsing Ma Bridge (TMB), which carries both highway and railway traffic and is instrumented with a long-term SHM system, is taken as a testbed for the present study. Two popular extreme value extrapolation methods: the block maxima approach and the peaks-over-threshold approach, are employed to extrapolate the extreme stresses induced by highway traffic and railway traffic, respectively. Characteristic values of the extreme stresses with a return period of 120 years (the design life of the bridge) obtained by the two methods are compared. It is found that the extrapolated extreme stresses are robust to the extrapolation technique. It may owe to the richness and good quality of the long-term strain data acquired. These characteristic extremes are also compared with the design values and found to be much smaller than the design values, indicating conservative design values of traffic loading and a safe traffic-loading condition of the bridge. The results of this study can be used as a reference for the design and condition assessment of similar bridges carrying heavy traffic, analogous to the TMB.