• The Mathematical Education
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• v.56 no.4
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• pp.407-434
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• 2017

The purpose of this study is to develop and verify the TPACK measurement tool for middle and high school mathematics teachers in the Korean context. Also, by clarifying the relationship between subordinate factors of Mathematics teachers' TPACK, an attempt was made to provide suggestions on the designs and directions for the in-service and pre-service teacher education and the programs for improving mathematics teachers' TPACK in the future. In order to achieve this goal, TPACK factors of mathematics teachers were extracted by reviewing literature on PCK, MKT, and TPACK. Then, content validity, basic statistical survey, reliability verification, exploratory factor analysis, confirmatory factor analysis, and structural equation model verification were conducted sequentially. At first, preliminary analysis was carried out on 79 mathematics teachers, and 76 items excluding the items with extreme value and reliability were included in the basic statistical analysis. And secondly, an exploratory factor analysis was conducted on 376 mathematics teachers, and this instrument consisted of 7 subordinate factors(CK, PK, TK, PCK, TCK, TPK, TPACK) and 61 items. Also by conducting confirmatory factor analysis and structural equation model test with 254 mathematics teachers, the measurement tool was confirmed the validity and reliability through statistically significant analysis. Then, the importance of integrated knowledge was confirmed by looking at the relationship between the TPACK factors of in-service mathematics teachers. The integrated knowledge(PCK, TCK, TPK) has played a crucial role in the formation of TPACK rather than the knowledge of CK, PK, and TK alone. Finally, the validity of TCK was confirmed through the structural equation modeling of TPACK. TCK not only directly affected TPACK, but also indirectly through TPK. According to these affirmative results, this measurement tool is claimed to be suitable for measuring the factors of Mathematics teachers' TPACK, and also the structural equation model can be regarded as a suitable model for analyzing the structural relationship of mathematics teachers' TPACK.

• Structural Engineering and Mechanics
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• v.76 no.1
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• pp.83-99
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• 2020

Shear walls are structural members in buildings that are used extensively in reinforced concrete frame buildings, and almost exclusively in the UK, regardless of whether or not they are actually required. In recent years, the UK construction industry, led by the Concrete Centre, has questioned the need for such structural elements in low to mid-rise reinforced concrete frame buildings. In this context, a typical modern, 5-storey residential building is studied, and its existing shear walls are replaced with columns as used elsewhere in the building. The aim is to investigate the impact of several design variables, including concrete grade, column size, column shape and slab thickness, on the building's structural performance, considering two punching shear limits (V_Ed/V_Rd,c), lateral drift and accelerations, to evaluate its maximum possible height under wind actions without the inclusion of shear walls. To facilitate this study, a numerical model has been developed using the ETABS software. The results demonstrate that the building examined does not require shear walls in the design and has no lateral displacement or acceleration issues. In fact, with further analysis, it is shown that a similar building could be constructed up to 13 and 16 storeys high for 2 and 2.5 punching shear ratios (V_Ed/V_Rd,c), respectively, with adequate serviceability and strength, without the need for shear walls, albeit with thicker columns.

• Structural Monitoring and Maintenance
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• v.2 no.3
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• pp.283-300
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• 2015

Visual condition inspections remain paramount to assessing the current deterioration status of a bridge and assigning remediation or maintenance tasks so as to ensure the ongoing serviceability of the structure. However, in recent years, there has been an increasing backlog of maintenance activities. Existing research reveals that this is attributable to the labour-intensive, subjective and disruptive nature of the current bridge inspection method. Current processes ultimately require lane closures, traffic guidance schemes and inspection equipment. This not only increases the whole-of-life costs of the bridge, but also increases the risk to the travelling public as issues affecting the structural integrity may go unaddressed. As a tool for bridge condition inspections, Unmanned Aerial Vehicles (UAVs) or, drones, offer considerable potential, allowing a bridge to be visually assessed without the need for inspectors to walk across the deck or utilise under-bridge inspection units. With current inspection processes placing additional strain on the existing bridge maintenance resources, the technology has the potential to significantly reduce the overall inspection costs and disruption caused to the travelling public. In addition to this, the use of automated aerial image capture enables engineers to better understand a situation through the 3D spatial context offered by UAV systems. However, the use of UAV for bridge inspection involves a number of critical issues to be resolved, including stability and accuracy of control, and safety to people. SLAM (Simultaneous Localisation and Mapping) is a technique that could be used by a UAV to build a map of the bridge underneath, while simultaneously determining its location on the constructed map. While there are considerable economic and risk-related benefits created through introducing entirely new ways of inspecting bridges and visualising information, there also remain hindrances to the wider deployment of UAVs. This study is to provide a context for use of UAVs for conducting visual bridge inspections, in addition to addressing the obstacles that are required to be overcome in order for the technology to be integrated into current practice.

• Smart Structures and Systems
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• v.31 no.4
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• pp.351-363
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• 2023

Visual structural inspections are an inseparable part of post-earthquake damage assessments. With unmanned aerial vehicles (UAVs) establishing a new frontier in visual inspections, there are major computational challenges in processing the collected massive amounts of high-resolution visual data. We propose twin deep learning models that can provide accurate high-resolution structural components and damage segmentation masks efficiently. The traditional approach to cope with high memory computational demands is to either uniformly downsample the raw images at the price of losing fine local details or cropping smaller parts of the images leading to a loss of global contextual information. Therefore, our twin models comprising Trainable Resizing for high-resolution Segmentation Network (TRS-Net) and DmgFormer approaches the global and local semantics from different perspectives. TRS-Net is a compound, high-resolution segmentation architecture equipped with learnable downsampler and upsampler modules to minimize information loss for optimal performance and efficiency. DmgFormer utilizes a transformer backbone and a convolutional decoder head with skip connections on a grid of crops aiming for high precision learning without downsizing. An augmented inference technique is used to boost performance further and reduce the possible loss of context due to grid cropping. Comprehensive experiments have been performed on the 3D physics-based graphics models (PBGMs) synthetic environments in the QuakeCity dataset. The proposed framework is evaluated using several metrics on three segmentation tasks: component type, component damage state, and global damage (crack, rebar, spalling). The models were developed as part of the 2^nd International Competition for Structural Health Monitoring.

• Journal of Korean Academy of Nursing
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• v.47 no.1
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• pp.14-24
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• 2017

Purpose: The purpose of this study was to construct and test a hypothetical model of self-management in patients with hemodialysis based on the Self-Regulation Model and resource-coping perspective. Methods: Data were collected from 215 adults receiving hemodialysis in 17 local clinics and one tertiary hospital in 2016. The Hemodialysis Self-management Instrument, the Revised Illness Perception Questionnaire, Herth Hope Index and Multidimensional Scale of Perceived Social Support were used. The exogenous variable was social context; the endogenous variables were cognitive illness representation, hope, self-management behavior, and illness outcome. For data analysis, descriptive statistics, Pearson correlation analysis, factor analysis, and structural equation modeling were performed. Results: The hypothetical model with six paths showed a good fitness to the empirical data: GFI=.96, AGFI=.90, CFI=.95, RMSEA=.08, SRMR=.04. The factors that had an influence on self-management behavior were social context (${\beta}=.84$), hope and cognitive illness representation (${\beta}=.37$ and ${\beta}=.27$) explaining 92.4% of the variance. Self-management behavior mediated the relationship between psychosocial coping resources and illness outcome. Conclusion: This research specifies a more complete spectrum of the self-management process. It is important to recognize the array of clinical resources available to support patients' self-management. Healthcare providers can facilitate self-management through collaborative care and understanding the ideas and emotions that each patient has about the illness, and ultimately improve the health outcomes. This framework can be used to guide self-management intervention development and assure effective clinical assessment.

• Smart Structures and Systems
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• v.29 no.1
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• pp.251-266
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• 2022

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

• Journal of Ocean Engineering and Technology
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• v.35 no.2
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• pp.131-140
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• 2021

The paper deals with comparative study of various surrogate models based approximate optimization in the structural design of the passive type deck support frame under design load conditions. The passive type deck support frame was devised to facilitate both transportation and installation of 20,000 ton class topside. Structural analysis was performed using the finite element method to evaluate the strength performance of the passive type deck support frame in its initial design stage. In the structural analysis, the strength performances were evaluated for various design load conditions. The optimum design problem based on surrogate model was formulated such that thickness sizing variables of main structure members were determined by minimizing the weight of the passive type deck support frame subject to the strength performance constraints. The surrogate models used in the approximate optimization were response surface method, Kriging model, and Chebyshev orthogonal polynomials. In the context of numerical performances, the solution results from approximate optimization were compared to actual non-approximate optimization. The response surface method among the surrogate models used in the approximate optimization showed the most appropriate optimum design results for the structure design of the passive type deck support frame.

• Journal of Information Technology Services
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• v.17 no.1
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• pp.105-119
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• 2018

The healthcare business is growing as a global core business because of the phenomenon of global aging, as well as in South Korea, skyrocketing health care costs accordingly, and changing the paradigm from treatment to the prevention-centered medical service. Especially, as the digital healthcare service stands out as a solution, major countries actively promote and support policies at the government level. Thus, this study will present attributes of a market-oriented service that would vitalize the digital healthcare service industry by investigating major attributes of the digital healthcare service. To analyze the relationships of the influences of attributes, this study used Interpretive Structural Modeling. As a result of literature research and ISM, this study can understand the eight basic attributes of the digital healthcare service (network scalability, context awareness, connection among information platforms, cost, trust, security, ease of use, usefulness) and analyze the relationships of the influences among the attributes. In addition, as this study finds some significant differences in Order Winner and Order Qualifier between the experts' group (security) and the users' group (trust, ease of use, usefulness), It provides meaningful implications for revitalization and promotion of digital healthcare service industry.

• Structural Engineering and Mechanics
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• v.87 no.5
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• pp.405-418
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• 2023

This study focused on the effectiveness of seismic isolation technique in case of a reinforced concrete structure with soft story defined as the stiffness irregularity between adjacent stories. In this context, a seismically isolated 3-story reinforced concrete structure was analyzed by gradually increasing the first story height (3.0, 4.5, and 6.0 m). The seismic isolation system of the structure is assumed to be composed of lead rubber bearings (LRB). In the analyses, isolators were modeled by both deteriorating (temperature-dependent analyses) and non-deteriorating (bounding analyses) hysteretic representations. The deterioration in strength of isolator is due to temperature rise in the lead core during cyclic motion. The ground motion pairs used in bi-directional nonlinear dynamic analyses were selected and scaled according to codified procedures. In the analyses, different isolation periods (Tiso) and characteristic strength to weight ratios (Q/W) were considered in order to determine the sensitivity of structural response to the isolator properties. Response quantities under consideration are floor accelerations, and interstory drift ratios. Analyses results are compared for both hysteretic representations of LRBs. Results are also used to assess the significance of the ratio between the horizontal stiffnesses of soft story and isolation system. It is revealed that seismic isolation is a viable method to reduce structural damage in structures with soft story.

• Steel and Composite Structures
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• v.49 no.6
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• pp.667-684
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• 2023

In the context of finite element method, a computational simulation is presented to study and analyze the dynamic behavior of regularly perforated functionally graded rotating beam for the first time. To investigate the effect of perforation configurations, both regular circular and squared perforation patterns are studied. To explore impacts of graded material distributions, both axial and transverse gradation profiles are considered. The material characteristics of graded materials are assumed to be smoothly and continuously varied through the axial or the thickness direction according the nonlinear power gradation law. A computational finite elements procedure is presented. The accuracy of the numerical procedure is verified and compared. Resonant frequencies, axial displacements as well as internal stress distributions throughout the perforated graded rotating cantilever beam are studied. Effects of material distributions, perforation patterns, as well as the rotating beam speed are investigated. Obtained results proved that the graded material distribution has remarkable effects on the dynamic performance. Additionally, circular perforation pattern produces more softening effect compared with squared perforation configuration thus larger values of axial displacements and maximum principal stresses are detected. Moreover, squared perforation provides smaller values of nondimensional frequency parameters at most of vibration modes compared with circular pattern.