• Child Health Nursing Research
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• v.25 no.2
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• pp.234-243
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• 2019

Purpose: The purpose of this study was to investigate associations between self-management and diabetes knowledge, diabetes-related attitudes, family support, and self-efficacy in adolescents with type 1 diabetes mellitus based on the information-motivation-behavior skills model. Methods: Data collection was conducted between March 18 and September 30, 2018. Patients (N=87) aged 12 to 19 years were recruited from the outpatient clinic of S children's hospital and an online community for patient with type 1 diabetes mellitus. Data were analyzed using descriptive statistics, the independent t-test, one-way ANOVA, Pearsons correlation, and hierarchical multiple linear regression with SPSS IBM 23.0, with the two-tailed level of significance set at 0.05. Results: The mean score of self-management in adolescents with type 1 diabetes mellitus was $61.23{\pm}10.00$ out of 80. The regression analysis showed that self-efficacy and family support significantly explained 56.9% of the variance in self-management (F=21.38, p<.001). Self-efficacy (${\beta}=.504$, p<.001) and family support (${\beta}=.188$, p<.001) were significant predictors of self-management. Conclusion: It is necessary to develop individual interventions to improve self-efficacy and family support for adolescents with type 1 diabetes mellitus to help them enhance their self-management.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.593-603
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• 2019

In wearable healthcare systems, sensor devices can be deployed in places around the human body such as the stomach, back, arms, and legs. The sensors use tiny batteries, which have limited resources, and old sensor batteries must be replaced with new batteries. It is difficult to deploy sensor devices directly into the human body. Therefore, instead of replacing sensor batteries, increasing the lifetime of sensor devices is more efficient. A transmission power control (TPC) algorithm is a representative technique to increase the lifetime of sensor devices. Sensor devices using a TPC algorithm control their transmission power level (TPL) to reduce battery energy consumption. The TPC algorithm operates on a closed-loop mechanism that consists of two parts, such as sensor and sink devices. Most previous research considered only the sink part of devices in the closed-loop. If we consider both the sensor and sink parts of a closed-loop mechanism, sensor devices reduce energy consumption more than previous systems that only consider the sensor part. In this paper, we propose a new approach to consider both the sensor and sink as part of a closed-loop mechanism for efficient energy management of sensor devices. Our proposed approach judges the current channel condition based on the values of various body sensors. If the current channel is not optimal, sensor devices maintain their current TPL without communication to save the sensor's batteries. Otherwise, they find an optimal TPL. To compare performance with other TPC algorithms, we implemented a TPC algorithm and embedded it into sensor devices. Our experimental results show that our new algorithm is better than other TPC algorithms, such as linear, binary, hybrid, and ATPC.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.3
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• pp.46-57
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• 2019

Generally speeding appeared to be the most contributing factor of fatalities occurred in work zones, and highway agencies in South Korea have concerned of the safety of workers and drivers in the poor circumstances. In this study, a portable variable message signs (PVMS) system as an alternative of control speeding in work zones was implemented. This study evaluated the safety effectiveness of the PVMS based on speeds and the compliance with the speed limit. Linear regression and logistic regression models were adopted to quantify the safety effect of the PVMS between the 'before' and 'after'. The results showed that most of points had statistically significant speeds reduction experience after PVMS installation. Also, the percentage of vehicle exceeding the speed limit by 10 km/h or more was decreased significantly between 50 and 80% in the 'after' periods compared to the 'before' periods. Therefore, the PVMS would be contributed to benefit safety in work zones which there is a difference in design speed of the adjacent normal section.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.1
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• pp.60-69
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• 2019

In this paper, we deal with forward-looking imaging, and focus on forward-looking synthetic inverse scattering imaging for a vehicle with curved motion. For image formation, time domain correlation(TDC) is used and a 2D image of the ground in front of the vehicle is generated. Because TDC is a technique that implements matched filtering for a space-variant system, it is robust to Gaussian additive noise of measurements. Furthermore, comparison and analysis between images from linear motion and curved motion show that the resolution of the image is improved; however, the entropy of the image is increased owing to curved motion.

• Journal of Biomedical and Translational Research
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• v.19 no.4
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• pp.130-139
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• 2018

This study aimed to analyze a high-performance liquid chromatography (HPLC) separation using a pentafluorophenyl column of parent drug hydroxychloroquine (HCQ) and its active metabolite, desethylhydroxchloroquine (DHCQ) applying to determine bioequivalence of two different formulations administered to patients. A rapid, simple, sensitive and specific liquid chromatography-tandem mass spectrometry (LC-MS/MS) method has been developed and validated for bioanalysis of HCQ and its metabolite DHCQ in human whole blood using deuterium derivative $hydroxychloroquine-D_4$ as an internal standard (IS). A triple-quadrupole mass spectrometer was operated using electrospray ionization in multiple reaction monitoring (MRM) mode. Sample preparation involves a two-step precipitation of protein techniques. The removed protein blood samples were chromatographed on a pentafluorophenyl (PFP) column ($50mm{\times}4.6mm$, $2.6{\mu}m$) with a mobile phase (ammonium formate solution containing dilute formic acid) in an isocratic mode at a flow rate of 0.45 mL/min. The standard curves were found to be linear in the range of 2 - 500 ng/mL for HCQ; 2 - 2,000 ng/mL for DHCQ in spite of lacking a highly sensitive MS spectrometry system. Results of intra- and inter-day precision and accuracy were within acceptable limits. A run time of 2.2 min for HCQ and 2.03 min for DHCQ in blood sample facilitated the analysis of more than 300 human whole blood samples per day. Taken together, we concluded that the assay developed herein represents a highly qualified technology for the quantification of HCQ in human whole blood for a parallel design bioequivalence study in a healthy male.

• Journal of Trauma and Injury
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• v.32 no.1
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• pp.40-46
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• 2019

Purpose: We perform an analysis of infection risk factors for fracture patients and confirm that the risk factors reported in previous studies increase the risk of actual infection among fractured patients. In addition, injury severity score (ISS) which is used as an evaluation tool for morbidity of trauma patients, confirms whether there is a relationship with infection after orthopedic fracture surgery. Methods: We retrospectively reviewed 1,818 patients who underwent fixation surgery at orthopedic trauma team, focused trauma center from January 1, 2015 to December 31, 2017. Thirty-five patients were infected after fracture surgery. We analyzed age, sex, open fracture criteria based on Gustilo-Aderson classification 3b, anatomical location (upper extremity or lower extremity) of fracture, diabetes, smoking, ISS. Results: Of 1,818 patients, 35 (1.9%) were diagnosed with postoperative infection. Of the 35 infected patients, nine (25.7%) were female and five (14.0%) were upper extremity fractures. Three (8.6%) were diagnosed with diabetes and eight (22.8%) were smokers. Thirteen (37.1%) had ISS less than nine points and six (17.1%) had ISS 15 points or more. Of 1,818 patients, 80 had open fractures. Surgical site infection were diagnosed in 12 (15.0%) of 80. And nine of 12 were checked with Gustilo-Aderson classification 3b or more. Linear logistic regression analysis was performed using statistical analysis program Stata 15 (Stata Corporation, College Station, TX, USA). In addition, independent variables were logistic regression analyzed individually after Propensity scores matching. In all statistical analyzes, only open fracture was identified as a risk factor. Conclusions: The risk factors for infection in fracture patients were found to be significantly influenced by open fracture rather than the underlying disease or anatomical feature of the patient. In the case of ISS, it is considered that there is a limitation. It is necessary to develop a new scoring system that can appropriately approach the morbidity of fracture trauma patients.

• The Journal of Korean Institute of Information Technology
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• v.16 no.11
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• pp.35-41
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• 2018

Electrical impedance tomography (EIT) is a kind of nondestructive testing technique that obtains the internal resistivity distribution from the voltages measured at the electrodes located outside the area of interest. However, an image reconstruction problem in EIT has innate non-linearity and ill-posedness, so that it is difficult to obtain satisfactory reconstructed results. In general, a neural network can efficiently model the input and output relationships of a non-linear system. This paper proposes a method for estimating the position and size of a circular target using a multi-layer neural network. To verify the performance of the proposed method, neural network was trained and various computer simulations were performed and satisfactory performance was verified.

• Structural Engineering and Mechanics
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• v.68 no.5
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• pp.603-619
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• 2018

In this research, an effective computational technique is carried out for nonlinear and post-buckling analyses of cracked imperfect composite plates. The laminated plates are assumed to be moderately thick so that the analysis can be carried out based on the first-order shear deformation theory. Geometric non-linearity is introduced in the way of von-Karman assumptions for the strain-displacement equations. The Ritz technique is applied using Legendre polynomials for the primary variable approximations. The crack is modeled by partitioning the entire domain of the plates into several sub-plates and therefore the plate decomposition technique is implemented in this research. The penalty technique is used for imposing the interface continuity between the sub-plates. Different out-of-plane essential boundary conditions such as clamp, simply support or free conditions will be assumed in this research by defining the relevant displacement functions. For in-plane boundary conditions, lateral expansions of the unloaded edges are completely free while the loaded edges are assumed to move straight but restricted to move laterally. With the formulation presented here, the plates can be subjected to biaxial compressive loads, therefore a sensitivity analysis is performed with respect to the applied load direction, along the parallel or perpendicular to the crack axis. The integrals of potential energy are numerically computed using Gauss-Lobatto quadrature formulas to get adequate accuracy. Then, the obtained non-linear system of equations is solved by the Newton-Raphson method. Finally, the results are presented to show the influence of crack length, various locations of crack, load direction, boundary conditions and different values of initial imperfection on nonlinear and post-buckling behavior of laminates.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.5
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• pp.277-286
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• 2019

In this paper, we propose an efficient hyperplane generation technique to classify human activity from combination of events and sequence information obtained from multiple-event sensors. By generating hyperplane efficiently, our machine learning algorithm classify with less memory and run time than the LSVM (Linear Support Vector Machine) for embedded system. Because the fact that light weight and high speed algorithm is one of the most critical issue in the IoT, the study can be applied to smart home to predict human activity and provide related services. Our approach is based on reducing numbers of hyperplanes and utilizing robust string comparing algorithm. The proposed method results in reduction of memory consumption compared to the conventional ML (Machine Learning) algorithms; 252 times to LSVM and 34,033 times to LSTM (Long Short-Term Memory), although accuracy is decreased slightly. Thus our method showed outstanding performance on accuracy per hyperplane; 240 times to LSVM and 30,520 times to LSTM. The binarized image is then divided into groups, where each groups are converted to binary number, in order to reduce the number of comparison done in runtime process. The binary numbers are then converted to string. The test data is evaluated by converting to string and measuring similarity between hyperplanes using Levenshtein algorithm, which is a robust dynamic string comparing algorithm. This technique reduces runtime and enables the proposed algorithm to become 27% faster than LSVM, and 90% faster than LSTM.

• Composites Research
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• v.32 no.5
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• pp.258-264
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• 2019

In this paper, a progressive failure analysis method was developed using the Hashin failure criterion and crack band model. Using the failure criterion, the failure initiation was evaluated. If the failure initiation is occurred, the damage variables at each failure modes (fiber tension & compression, matrix tension & compression) was calculated according to linear softening degradation behavior and the variables are used to derive the damaged stiffness matrix. The damaged stiffness matrix is reflected to damaged material and the progressive failure analysis is continued until the damage variables to be 1 that complete failure of material. A series of processes were performed using FE commercial code ABAQUS with user defined material subroutine (UMAT). To evaluate the proposed progressive failure model, the experimental results of open hole composite laminate tests was compared with numerical result. Using digital image correlation system, the strain behavior also was compared. The proposed numerical results were coincided well with the experimental results.