• Earthquakes and Structures
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• v.11 no.6
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• pp.1027-1041
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• 2016

Different incident angles of ground motions have been considered to evaluate the relationship between floor rotation and torsional irregularity coefficient. The issues specifically addressed are (1) variability in torsional irregularity coefficient and floor rotations with varying incident angles of ground motion (2) contradictory relationship between floor rotation and torsional irregularity coefficient. To explore the stated issues, an evaluation based on relative variation in seismic response quantities of linear asymmetric structure under the influence of horizontal bi-directional excitation with varying seismic orientations has been carried out using response history analysis. Several typical earthquake records are applied to the structure to demonstrate the relative variations of floor rotation and torsional irregularity coefficient for different seismic orientations. It is demonstrated that (1) Torsional irregularity coefficient (TIC) increases as the story number decreases when the ground motion is considered along reference axes of the structure. For incident angles other than structure's reference axes, TIC either decreases as the story number decreases or there is no specific trend for TIC. Floor rotation increases in proportion to the story number when the ground motion is considered along reference axes of structure. For incident angles other than structure's reference axes, floor rotation either decreases as the story number increases or there is no specific trend for floor rotation and (2) TIC and floor rotation seems to be approximately inversely proportional to each other when the ground motion is considered along reference axes of the structure. For incident angles other than structure's reference axes, the relationship can even become directly proportional instead of inversely proportional.

• Journal of the Korea Safety Management & Science
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• v.22 no.1
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• pp.23-32
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• 2020

There has been a significant decline in the number of rail accidents in Korea since system safety management activities were introduced. Nonetheless, analyzing and preventing human error-related accidents is still an important issue in railway industry. As a railway system is increasingly automated and intelligent, the mechanism and process of an accident occurrence are more and more complicated. It is now essential to consider a variety of factors and their intricate interactions in the analysis of rail accidents. However, it has proved that traditional accident models and methods based on a linear cause-effect relationship are inadequate to analyze and to assess accidents in complex systems such as railway systems. In order to supplement the limitations of traditional safety methods, recently some systemic safety models and methods have been developed. Of those, FRAM(Functional Resonance Analysis Method) has been recognized as one of the most useful methods for analyzing accidents in complex systems. It reflects the concepts of performance adjustment and performance variability in a system, which are fundamental to understanding the processes of an accident in complex systems. This study aims to apply FRAM to the analysis of a rail accident involving human errors, which occurred recently in South Korea. Through the application of FRAM, we found that it can be a useful alternative to traditional methods in the analysis and assessment of accidents in complex systems. In addition, it was also found that FRAM can help analysts understand the interactions between functional elements of a system in a systematic manner.

• Korean Journal of Veterinary Research
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• v.32 no.4
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• pp.543-553
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• 1992

Properties of unitary ATP-sensitive $K^+$ channels were studied using planar lipid bilayer technique. Vesicles were prepared from bullfrog (Rana catesbeiana) skeletal muscle. ATP-sensitive $K^+$ (K (ATP)) channels were identified by their unitary conductance and sensitivity to ATP. In the symmetrical solution containing 200mM KCI, 10mM Hepes, 1mM EGTA and pH 7.2, single K (ATP) channels showed a linear current-voltage relations with slight inward rectification. Slope conductance at reversal potential was $60.1{\pm}0.43$ pS(n=3)). Micromolar ATP reversibly inhibited the channel activity when applied to the cytoplasmic side. In the range of -50~＋50 mV, the channel activity was not voltage-dependent, but the channel gating within a burst was more frequent at negative voltage range. Varying the concentrations of external/internal KCl(mM) to 40/200, 200/200, 200/100 and 200/40 shifted reversal potentials to $-30.8{\pm}2.9$(n=3), $-1.1{\pm}2.7$(n=3), 10.5 and 30.6(mV), respecrivety. These reversal potentials were close to the expected values by the Nernst equation, indicating nearly ideal selectivity for $K^+$ over $Cl^-$. Under bi-ionic conditions of 200mM external test ions and 200mM internal $K^+$, the reversal potentials for each test ion/K pair were measured. The measured reversal potentials were used for the calculation of the releative permeability of alkali cations to $K^+$ ions using the Goldman-Hodgkin-Katz equation. The permeability sequence of 5 cations relative to $K^+$ was $K^+$(1), $Rb^+$(0.49), $Cs^+$(0.27), $Na^+$(0.027) and $Li^+$(0.021). This sequence was recognized as Eisenman's selectivity sequence IV. In addition, modelling the permeation of $K^+$ ion through ATP-sensitive $K^+$ channel revealed that a 3-barrier 2-site multiple occupancy model can reasonably predict the observed current-voltage relations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2774-2796
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• 2015

Quality-of-service (QoS) provisioning for a cognitive mesh network (CMN) with heterogeneous services has become a challenging area of research in recent days. Considering both real-time (RT) and non-real-time (NRT) traffic in a multihop CMN, [1] studied cross-layer resource management, including joint access control, route selection, and resource allocation. Due to the complexity of the formulated resource allocation problems, which are mixed-integer non-linear programming, a low-complexity yet efficient algorithm was proposed there to approximately solve the formulated optimization problems. In contrast, in this work, we present an application of genetic algorithm (GA) to re-address the hard resource allocation problems studied in [1]. Novel initialization, selection, crossover, and mutation operations are designed such that solutions with enough randomness can be generated and converge with as less number of attempts as possible, thus improving the efficiency of the algorithm effectively. Simulation results show the effectiveness of the newly proposed GA-based algorithm. Furthermore, by comparing the performance of the newly proposed algorithm with the one proposed in [1], more insights have been obtained in terms of the tradeoff among QoS provisioning for RT traffic, throughput maximization for NRT traffic, and time complexity of an algorithm for resource allocation in a multihop network such as CMN.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1904-1926
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• 2016

Iris recognition for biometric personnel identification has gained much interest owing to the increasing concern with security today. The image quality plays a major role in the performance of iris recognition systems. When capturing an iris image under uncontrolled conditions and dealing with non-cooperative people, the chance of getting non-ideal images is very high owing to poor focus, off-angle, noise, motion blur, occlusion of eyelashes and eyelids, and wearing glasses. In order to improve the accuracy of iris recognition while dealing with non-ideal iris images, we propose a novel algorithm that improves the quality of degraded iris images. First, the iris image is localized properly to obtain accurate iris boundary detection, and then the iris image is normalized to obtain a fixed size. Second, the valid region (iris region) is extracted from the segmented iris image to obtain only the iris region. Third, to get a well-distributed texture image, bilinear interpolation is used on the segmented valid iris gray image. Using contrast-limited adaptive histogram equalization (CLAHE) enhances the low contrast of the resulting interpolated image. The results of CLAHE are further improved by stretching the maximum and minimum values to 0-255 by using histogram-stretching technique. The gray texture information is extracted by 1D Gabor filters while the Hamming distance technique is chosen as a metric for recognition. The NICE-II training dataset taken from UBRIS.v2 was used for the experiment. Results of the proposed method outperformed other methods in terms of equal error rate (EER).

• Journal of Biomedical Engineering Research
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• v.10 no.2
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• pp.117-124
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• 1989

The intelligent trajectory control method that controls moving direction and average velocity for a prosthetic arm is proposed by pattern recognition and force estimations using EMG signals. Also, we propose the real time trajectory planning method which generates continuous accelleration paths using 3 stage linear filters to minimize the impact to human body induced by arm motions and to reduce the muscle fatigue. We use combination of MLP and fuzzy filter for pattern recognition to estimate the direction of a muscle and Hogan`s method for the force estimation. EMG signals are acquired by using a amputation simulator and 2 dimensional joystick motion. The simulation results of proposed prosthetic arm control system using the EMf signals show that the arm is effectively followed the desired trajectory depended on estimated force and direction of muscle movements.

• Smart Structures and Systems
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• v.17 no.4
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• pp.593-610
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• 2016

In this study, an innovative and smart glass fiber-reinforced polymer (GFRP) hybrid bar was developed for stronger durability of concrete structures. As comparing with the conventional GFRP bar, the smart GFRP Hybrid bar can promise to enhance the modulus of elasticity so that it makes the cracking reduced than the case when the conventional GFRP bar is used. Besides, the GFRP Hybrid bar can effectively resist the corrosion of conventional steel bar by the GFRP outer surface on the steel bar. In order to verify the bond performance of the GFRP hybrid bar for structural reinforcement, uniaxial pull-out test was conducted. The variables were the bar diameter and the number of strands and pitch of the fiber ribs. Tensile tests showed a excellent increase in the modulus of elasticity, 152.1 GPa, as compared to that of the pure GFRP bar (50 GPa). The stress-strain curve was bi-linear, so that the ductile performance could be obtained. For the bond test, the entire GFRP hybrid bar test specimens failed in concrete splitting due to higher shear strength resulting in concrete crushing as a function of bar deformation. Investigation revealed that an increase in the number of strands of fiber ribs enhanced the bond strength, and the pitch guaranteed the bond strength of 19.1 mm diameter hybrid bar with 15.9 mm diameter of core section of deformed steel the ACI 440 1R-15 equation is regarded as more suitable for predicting the bond strength of GFRP hybrid bars, whereas the CSA S806-12 prediction is considered too conservative and is largely influenced by the bar diameter. For further study, various geometrical and material properties such as concrete cover, cross-sectional ratio, and surface treatment should be considered.

• Journal of the Korea Computer Graphics Society
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• v.22 no.5
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• pp.1-16
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• 2016

In this paper, we propose and efficient curve reconstruction method based on the classical least-square fitting scheme. Specifically, given planar sample points equipped with normals, we reconstruct the objective curve as the zero set of a hierarchical implicit ZP(Zwart-Powell)-spline that can recover large holes of dataset without loosing the fine details. As regularizers, we adopted two: a Tikhonov regularizer to reduce the singularity of the linear system and a discrete Laplacian operator to smooth out the isocurves. Benchmark tests with quantitative measurements are done and our method shows much better quality than polynomial methods. Compared with the hierarchical bi-quadratic spline for datasets with holes, our method results in compatible quality but with less than 90% computational overhead.

• Korea Journal of Hospital Management
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• v.25 no.1
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• pp.46-57
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• 2020

Objectives: The purpose of this study is to evaluate the factors affecting patient satisfaction for the nursing service of comprehensive nursing care service unit in Tertiary hospital Methods: This study employed a descriptive survey to investigate the nursing satisfaction and the study data was collected from 74 patients among 83 patient who were admitted to the nursing care integration service ward of an tertiary hospital for 10 days from May 9, 2018 to May 19, 2018. Data was analyzed by descriptive statistics, t-test, ANOVA, and multiple linear regression using SPSS 21 program. Results: The average with nursing satisfaction was significantly different according to marriage type and KPCS level. It was found that physical factor and educational factor have statistically significant effect on nursing satisfaction. As physical care increase by one unit, patient satisfaction increase by 0.226(95% CI; 0.061-0.390) and also satisfaction increase by 0.443(95% CI; 0.070-0.816) as education care increase by one unit. Conclusions: As a result of study, it was found that it is necessary to provide patients with more careful nursing service in physical and educational perspective, in order to improve the service quality of comprehensive nursing care service unit.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.2
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• pp.164-173
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• 2013

In this paper, we propose multi-frame based super resolution algorithm by using motion vector normalization and edge pattern analysis. Existing algorithms have constraints of sub-pixel motion and global translation between frames. Thus, applying of algorithms is limited. And single-frame based super resolution algorithm by using discrete wavelet transform which robust to these problems is proposed but it has another problem that quantity of information for interpolation is limited. To solve these problems, we propose motion vector normalization and edge pattern analysis for 2*2 block motion estimation. The experimental results show that the proposed algorithm has better performance than other conventional algorithms.