• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.21 no.3
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• pp.359-370
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• 2023

The thermal integrity of spent nuclear fuels has to be maintained during their long-term dry storage. The detailed temperature distributions of spent fuel assemblies are essential for evaluating the integrity of their dry storage systems. In this study, a subchannel analysis model was developed for a canister of a single fuel assembly using the COBRA-SFS code. The thermal parameters affecting the peak cladding temperature (PCT) of the spent fuel assembly were identified, and sensitivity analyses were performed based on these parameters. The subchannel analysis results indicated the presence of a recirculation flow, based on natural convection, between the fuel assembly and downcomer region. The sensitivity analysis of the thermal parameters indicated that the PCT was affected by the emissivity of the fuel cladding and basket, convective heat transfer coefficient, and thermal conductivity of the fluid. However, the effects of the wall friction factor of the canister, form loss coefficient of the grid spacers, and thermal conductivities of the solid materials, on the PCT were predominantly ignored.

• Textile Coloration and Finishing
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• v.35 no.3
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• pp.179-187
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• 2023

In this study, we developed a microfiber-based flexible pressure sensor with high sensitivity and excellent skin breathability. A nonwoven fabric composed of microfibers was prepared by electrospinning, which resulted in excellent moisture permeability of the sensor (143 g∙m^-2∙h^-1). In particular, high-pressure sensitivity (0.36 kPa^-1) was achieved by introducing submicron structures on the microfiber surface by controlling the ambient humidity during electrospinning. The fabrication technology of the microfiber-based flexible pressure sensors reported in this study is expected to contribute to the commercialization of flexible pressure sensors applicable to long-term wearable health monitoring as well as virtual/augmented reality and electronic skin applications.

• Mass Spectrometry Letters
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• v.7 no.2
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• pp.50-54
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• 2016

Multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) is currently used in our laboratory for isotopic and quantitative analyses of nuclear materials at ultra-trace levels in environmental swipe samples, which is a very useful for monitoring undeclared nuclear activities. In this study, to improve measurement precisions of uranium isotopes at ultratrace levels, we adopted a desolvating nebulizer system (Aridus-II, CETAC., USA), which can improve signal sensitivity and reduce formation of uranium hydride. A peristaltic pump was combined with Aridus-II in the sample introduction system of MC-ICP-MS to reduce long-term signal fluctuations by maintaining a constant flow rate of the sample solution. The signal sensitivity in the presence of Aridus-II was improved more than 10-fold and the formation ratio of UH/U decreased by 16- to 17- fold compared to a normal spray chamber. Long-term signal fluctuations were significantly reduced by using the peristaltic pump. Detailed optimizations and evaluations with uranium standards are also discussed in this paper.

• Journal of the Korean Society of Physical Medicine
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• v.13 no.1
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• pp.11-26
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• 2018

PURPOSE: The aim of this study was to review the effects of exercise intervention on blood glucose control in obese type 2 diabetic patients. METHODS: The PubMed and KERISS search engines were used and 61 papers that met the key questions were selected. RESULTS: Exercise is an effective intervention for the control of blood glucose in type 2 diabetic patients because it does not impair glucose transport in the skeletal muscle induced by muscle contractions. Insulin resistance, which is characteristic of type 2 diabetes, is caused by decreased insulin sensitivity or insulin responsiveness. Acute exercise improves the glucose metabolism by increasing the insulin-independent signaling pathways and insulin sensitivity in the skeletal muscle, and regular long-term exercise improves the skeletal muscle insulin responsiveness and systemic glucose metabolism by increasing the mitochondrial and GLUT4 protein expression in the skeletal muscle. CONCLUSION: The improvement of the glucose metabolism through exercise shows a dose-response pattern, and if exercise consumes the same number of calories, high intensity exercise will be more effective for the glucose metabolism. On the other hand, it is practically difficult for a patient with obese type 2 diabetes to control their blood glucose with high intensity or long-term exercise. Therefore, it will be necessary to study safe adjuvants (cinnamic acid, lithium) that can produce similar effects to high-intensity and high-volume exercises in low-intensity and low-volume exercises.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.787-790
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• 2008

The SWAT(Soil and Water Assesment Tool) is a relatively large scale model for the complicated watershed or river basin. The model was developed to predict the effect of land management practices on water, sediment and agricultural chemical yields in large complex watershed with varying soils, land use and management conditions over long periods of time. Usually streams are divided into urban stream and natural stream in accordance with the development level. In case of urban stream, according to urbanization, as impermeable areas are increasing due to the change of land use condition and land cover condition, dry stream phenomenon at urban stream is rapidly progressed. In this study, long term run-off simulations in urban stream are performed by using SWAT model. Especially, the model is applied in small scale water shed, Joman River basin. The optimization by the sensitivity analysis is also performed for the model parameter estimations.

• Journal of Biomedical Engineering Research
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• v.40 no.6
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• pp.242-249
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• 2019

Forearm electromyography (EMG) generated by wrist movements has been widely used to develop an electrical prosthetic hand, but EMG generated by finger movements has been rarely used even though 20% of amputees lose fingers. The goal of this study is to improve the classification performance of different finger movements using a deep learning algorithm, and thereby contributing to the development of a high-performance finger-based prosthetic hand. Ten participants took part in this study, and they performed seven different finger movements forty times each (thumb, index, middle, ring, little, fist and rest) during which EMG was measured from the back of the right hand using four bipolar electrodes. We extracted mean absolute value (MAV), root mean square (RMS), and mean (MEAN) from the measured EMGs for each trial as features, and a 5x5-fold cross-validation was performed to estimate the classification performance of seven different finger movements. A long short-term memory (LSTM) model was used as a classifier, and linear discriminant analysis (LDA) that is a widely used classifier in previous studies was also used for comparison. The best performance of the LSTM model (sensitivity: 91.46 ± 6.72%; specificity: 91.27 ± 4.18%; accuracy: 91.26 ± 4.09%) significantly outperformed that of LDA (sensitivity: 84.55 ± 9.61%; specificity: 84.02 ± 6.00%; accuracy: 84.00 ± 5.87%). Our result demonstrates the feasibility of a deep learning algorithm (LSTM) to improve the performance of classifying different finger movements using EMG.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1649-1654
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• 2021

In this paper, we introduce a regularization of long short-term memory (LSTM) based fall detection system using TensorFlow that can detect falls that can occur in the elderly. Fall detection uses data from a 3-axis acceleration sensor attached to the body of an elderly person and learns about a total of 7 behavior patterns, each of which is a pattern that occurs in daily life, and the remaining 3 are patterns for falls. During training, a normalization process is performed to effectively reduce the loss function, and the normalization performs a maximum-minimum normalization for data and a L2 regularization for the loss function. The optimal regularization conditions of LSTM using several falling parameters obtained from the 3-axis accelerometer is explained. When normalization and regularization rate λ for sum vector magnitude (SVM) are 127 and 0.00015, respectively, the best sensitivity, specificity, and accuracy are 98.4, 94.8, and 96.9%, respectively.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.216-221
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• 2008

Shape design optimization for linear elasticity problem is performed using isogeometric analysis method. In many design optimization problems for real engineering models, initial raw data usually comes from CAD modeler. Then designer should convert this CAD data into finite element mesh data because conventional design optimization tools are generally based on finite element analysis. During this conversion there is some numerical error due to a geometry approximation, which causes accuracy problems in not only response analysis but also design sensitivity analysis. As a remedy of this phenomenon, the isogeometric analysis method is one of the promising approaches of shape design optimization. The main idea of isogeometric analysis is that the basis functions used in analysis is exactly same as ones which represent the geometry, and this geometrically exact model can be used shape sensitivity analysis and design optimization as well. In shape design sensitivity point of view, precise shape sensitivity is very essential for gradient-based optimization. In conventional finite element based optimization, higher order information such as normal vector and curvature term is inaccurate or even missing due to the use of linear interpolation functions. On the other hands, B-spline basis functions have sufficient continuity and their derivatives are smooth enough. Therefore normal vector and curvature terms can be exactly evaluated, which eventually yields precise optimal shapes. In this article, isogeometric analysis method is utilized for the shape design optimization. By virtue of B-spline basis function, an exact geometry can be handled without finite element meshes. Moreover, initial CAD data are used throughout the optimization process, including response analysis, shape sensitivity analysis, design parameterization and shape optimization, without subsequent communication with CAD description.

• Computers and Concrete
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• v.30 no.5
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• pp.301-310
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• 2022

Cement-based sensors have been widely used as structural health monitoring systems, however, their long-term sensing performance have not actively investigated. In this study, a deep learning-based methodology is adopted to predict the long-term piezoresistive properties of cement-based sensors. Samples with different multi-walled carbon nanotube contents (0.1, 0.3, and 0.5 wt.%) are fabricated, and piezoresistive tests are conducted over 10,000 loading cycles to obtain the training data. Time-dependent degradation is predicted using a modified long short-term memory (LSTM) model. The effects of different model variables including the amount of training data, number of epochs, and dropout ratio on the accuracy of predictions are analyzed. Finally, the effectiveness of the proposed approach is evaluated by comparing the predictions for long-term piezoresistive sensing performance with untrained experimental data. A sensitivity of 6% is experimentally examined in the sample containing 0.1 wt.% of MWCNTs, and predictions with accuracy up to 98% are found using the proposed LSTM model. Based on the experimental results, the proposed model is expected to be applied in the structural health monitoring systems to predict their long-term piezoresistice sensing performances during their service life.

• Advances in Traditional Medicine
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• v.9 no.1
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• pp.39-48
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• 2009

We have evaluated the effect of long term treatment of Enicostemma littorale (E. littorale) in type 2 diabetic patients taking pills of aqueous extract of E. littorale regularly as a complimentary medicine for at least 9 months. The effects of E. littorale on glycemic control, lipid profile, cardiac function and DNA damage in these patients were compared with those who had not been regular in taking E. littorale but regular in taking other conventional anti-diabetics. Our data suggest that, E. littorale can maintain normal blood glucose, serum insulin, serum triglycerides levels of type 2 diabetic patients if taken regularly. E. littorale also improves insulin sensitivity, and normalize disturbed lipogram and elevated creatinine levels, thereby produces beneficial effect in preventing cardiovascular complications and may preserve the kidney function. The finding that E. littorale also prevents DNA damage suggest a long term effect in diabetic patients. E. littorale thus can be considered as safe supplementary therapy for a long term and effective management of type 2 diabetic patients.