• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.6
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• pp.381-388
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• 2018

This paper presents a generalized finite element formulation for plastic hinge modeling based on lumped plasticity in the classical Euler-Bernoulli beam elements. In this approach, the plastic hinges are effectively modeled using proper enrichment functions describing weak discontinuities of the solution. The proposed methodology enables the insertion of plastic hinges at an arbitrary location without modifying the connectivity of elements. The formations of plastic hinges are instead achieved by hierarchically adding degrees of freedom to existing elements. Convergence analyses such as h- and p-extensions are performed to investigate the effectiveness of the proposed method. The analysis results indicate that the proposed generalized finite element method can achieve theoretical convergence rates for both cases where plastic hinges are located at nodes and within an element, thus demonstrating its accuracy.

• Journal of Korea Multimedia Society
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• v.22 no.5
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• pp.613-625
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• 2019

The rise of the Internet of Things (IoT) devices have greatly influenced many industries and one of them is healthcare where wearable devices started to track all your daily activities for better health monitoring accuracy and even down to tracking daily food intake in some cases. With the amounts of data that are being tracked and shared between from these devices, questions were raised on how to uphold user's data privacy when data is shared between these IoT devices and third party. With the blockchain platforms started to mature since its inception, the technology can be implemented according to a variety of use case scenarios. In this paper, we present a system architecture based on the healthcare system and IoT network by leveraging on multiple blockchain networks as the medium in between that should enable users to have direct authority on data accessibility of their shared data. We provide proof of concept implementation and highlight the results from our testing to show how the efficiency and scalability of the healthcare system improved without having a significant impact on the performance of the Electronic Medical Record (EMR) that mostly affected by the previous solution since these solutions directly connected to a public blockchain network and which resulted in significant delays and high cost of operation when a large amount of data or complicated functions are involved.

• Journal of Advanced Navigation Technology
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• v.23 no.3
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• pp.228-236
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• 2019

Recently, multi-sensor integration techniques have been actively studied to obtain reliable and accurate navigation solution in GPS (Global Positioning System)-denied harsh environments such as urban canyons, tunnels, and underground roads. In this paper, we propose a low-cost ultrasonic-speedometer utilizing the characteristics of the ultrasonic propagation. An efficient integrated INS (inertial navigation system)/ultrasonic-speedometer navigation system is also proposed to improve the accuracy of positioning in GPS-denied environments. To evaluate the proposed system, car experiments with field-collected measurements were performed. By the experiment results, it was confirmed that the proposed INS/ultrasonic-speedometer system bounds the positioning error growth effectively even though GPS signal is blocked more than 10 seconds and a low-cost MEMS IMU (micro electro mechanical systems inertial measurement unit) is utilized.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.4
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• pp.265-272
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• 2019

In this paper, a vision-based deep learning algorithm and image processing method are proposed to detect bolt-loosening in steel connections. To achieve this objective, the following approaches are implemented. First, a bolt-loosening detection method that includes regional convolutional neural network(RCNN)-based deep learning algorithm and Hough line transform(HLT)-based image processing algorithm are designed. The RCNN-based deep learning algorithm is developed to identify and crop bolts in a connection image. The HLT-based image processing algorithm is designed to estimate the bolt angles from the cropped bolt images. Then, the proposed vision-based method is evaluated for verifying bolt-loosening detection in a lab-scale girder connection. The accuracy of the RCNN-based bolt detector and HLT-based bolt angle estimator are examined with respect to various perspective distortions.

• Smart Structures and Systems
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• v.24 no.3
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• pp.303-317
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• 2019

Magneto-rheological fluid (MRF) rotatory dampers are normally used for controlling the constant rotation of machines and engines. In this research, such a device is proposed to act as variable stiffness device to alleviate the rotational oscillation existing in the many engineering applications, such as motor. Under such thought, the main purpose of this work is to characterize the nonlinear torque-angular displacement/angular velocity responses of an MRF based variable stiffness device in oscillatory motion. A rotational hysteresis model, consisting of a rotatory spring, a rotatory viscous damping element and an error function-based hysteresis element, is proposed, which is capable of describing the unique dynamical characteristics of this smart device. To estimate the optimal model parameters, a modified whale optimization algorithm (MWOA) is employed on the captured experimental data of torque, angular displacement and angular velocity under various excitation conditions. In MWOA, a nonlinear algorithm parameter updating mechanism is adopted to replace the traditional linear one, enhancing the global search ability initially and the local search ability at the later stage of the algorithm evolution. Additionally, the immune operation is introduced in the whale individual selection, improving the identification accuracy of solution. Finally, the dynamic testing results are used to validate the performance of the proposed model and the effectiveness of the proposed optimization algorithm.

• Steel and Composite Structures
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• v.31 no.5
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• pp.503-516
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• 2019

This work presents a dynamic investigation of functionally graded (FG) plates resting on elastic foundation using a simple quasi-3D higher shear deformation theory (quasi-3D HSDT) in which the stretching effect is considered. The culmination of this theory is that in addition to taking into account the effect of thickness extension (${\varepsilon}_z{\neq}0$), the kinematic is defined with only 4 unknowns, which is even lower than the first order shear deformation theory (FSDT). The elastic foundation is included in the formulation using the Pasternak mathematical model. The governing equations are deduced through the Hamilton's principle. These equations are then solved via closed-type solutions of the Navier type. The fundamental frequencies are predicted by solving the eigenvalue problem. The degree of accuracy of present solutions can be shown by comparing it to the 3D solution and other closed-form solutions available in the literature.

• Journal of Radiation Protection and Research
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• v.44 no.1
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• pp.32-42
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• 2019

Background: There have been much efforts to develop the proper and realistic machine Quality Assurance (QA) reflecting on real Volumetric Modulated Arc Therapy (VMAT) plan. In this work we propose and test a special VMAT plan of plan-class specific (pcsr) QA, as a machine QA so that it might be a good solution to supplement weak point of present machine QA to make it more realistic for VMAT treatment. Materials and Methods: We divided human body into 5 treatment sites: brain, head and neck, chest, abdomen, and pelvis. One plan for each treatment site was selected from real VMAT cases and contours were mapped into the computational human phantom where the same plan as real VMAT plan was created and called plan-class specific reference (pcsr) QA plan. We delivered this pcsr QA plan on a daily basis over the full research period and tracked how much MLC movement and dosimetric error occurred in regular delivery. Several real patients under treatments were also tracked to test the usefulness of pcsr QA through comparisons between them. We used dynalog file viewer (DFV) and Dynalog file to analyze position and speed of individual MLC leaf. The gamma pass rate from portal dosimetry for different gamma criteria was analyzed to evaluate analyze dosimetric accuracy. Results and Discussion: The maxRMS of MLC position error for all plans were all within the tolerance limit of < 0.35 cm and the positional variation of maxPEs for both pcsr and real plans were observed very stable over the research session. Daily variations of maxRMS of MLC speed error and gamma pass rate for real VMAT plans were observed very comparable to those in their pcsr plans in good acceptable fluctuation. Conclusion: We believe that the newly proposed pcsr QA would be useful and helpful to predict the mid-term quality of real VMAT treatment delivery.

• Research in Community and Public Health Nursing
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• v.30 no.2
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• pp.130-140
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• 2019

Purpose: The aim of this study is to explore levels of suicidal ideation and identify subgroups of high suicidal risk among the depressed elderly in Korea. Methods: A descriptive cross-sectional design was adopted on secondary data from the 6th (1st year) Korean national health and nutrition examination survey (KNHANES). A total of 239 depressed elders aged 60 or over who participated in the KNHANES. The prevalence of suicidal ideation and its related factors, including sociodemographic, physical, psychological characteristics and quality of life (EQ-5D index) were examined. Descriptive statistics and a decision tree analysis were performed using the SPSS/WIN 23.0 and SPSS Modeler 14.2 programs. Results: Of the depressed elderly, 28.9% had suicidal ideation. Three groups with high suicidal ideation were identified. Predictive factors included perceived stress level, household income level, quality of life and restriction of activity. In the highest risk group were those depressed elderly with moderate and low levels of stress, less than .71 of EQ-5D index and restriction of activity, and 80.0% of these participants had suicidal ideation. The accuracy of the model was 80.8%, its sensitivity 85.9%, and its specificity 68.1%. Conclusion: Multi-dimensional intervention should be designed to decrease suicide among the depressed elderly, particularly focusing on subgroups with high risk factors. This research is expected to contribute itself to the policy design and solution building in the future as it suggests policy implications in preventing the suicide of the depressed elderly.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.5
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• pp.487-494
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• 2019

A Small-Sat Power System Design and Development should be depend on space environment such as solar wind with Electromagnetic field by hurdle of techniques. It is surmount solution of trend that will unitize and converge with power module in these days. The level of modularize means that applying Universal Middleware for payload power module requirements. The scope of target system is a main power provider module and operational subunit that can be implemented with the final power module distribution loads to consume for continuous process. A Universal Middleware strengthen to build power module from satellite power system should be accuracy and consuming data. A Power Service Module and dynamic system drive interactive management between power distribution and consumer module by Range Control. Consequently, suggesting evaluation, unexpecting payload system power consumer that makes fine variable resources in the development design process and efficiency.

• Smart Media Journal
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• v.10 no.3
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• pp.23-30
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• 2021

Although the manufacturing time series data clustering technique is an important grouping solution in the field of detecting and improving manufacturing large data-based equipment and process defects, it has a disadvantage of low accuracy when applying the existing static data target clustering technique to time series data. In this paper, an evolutionary computation-based time series cluster analysis approach is presented to improve the coherence of existing clustering techniques. To this end, first, the image shape resulting from the manufacturing process is converted into one-dimensional time series data using linear scanning, and the optimal sub-clusters for hierarchical cluster analysis and split cluster analysis are derived based on the Pearson distance metric as the target of the transformation data. Finally, by using a genetic algorithm, an optimal cluster combination with minimal similarity is derived for the two cluster analysis results. And the performance superiority of the proposed clustering is verified by comparing the performance with the existing clustering technique for the actual manufacturing process image.