• Journal of Power Electronics
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• v.19 no.6
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• pp.1366-1379
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• 2019

High-gain DC/DC converters have become one of the key technologies for the grid-connected operation of new energy power generation, and its research provides a significant impetus for the rapid development of new energy power generation. Inspired by the transformer effect and the ripple-suppressed ability of a coupled inductor, a double-coupled inductor high gain DC/DC converter with a ripple absorption circuit is proposed in this paper. By integrating the diode-capacitor voltage multiplying unit into the quadratic Boost converter and assembling the independent inductor into the magnetic core of structure coupled inductors, the adjustable range of the voltage gain can be effectively extended and the limit on duty ratio can be avoided. In addition, the volume of the magnetic element can be reduced. Very small ripples of input current can be obtained by the ripple absorption circuit, which is composed of an auxiliary inductor and a capacitor. The leakage inductance loss can be recovered to the load in a switching period, and the switching-off voltage spikes caused by leakage inductance can be suppressed by absorption in the diode-capacitor voltage multiplying unit. On the basis of the theoretical analysis, the feasibility of the proposed converter is verified by test results obtained by simulations and an experimental prototype.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.13-21
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• 2010

IEEE 1149.1 test architecture was proposed to support the test of elements within the boards. It is a large serial shift register that uses the TDI pin as an input and the TDO pin as an output. Even though it performs the board level test perfectly, there is a problems of running system level test when the boards are equipped to the system. To test real time operation signal on test pin, output speed of serial shift register chain must be above double clock speed of shift register. In this paper, we designed a runtime test architecture and a runtime test procedure under running system environments to capture runtime signal at system clock rate. The suggested runtime test architecture are simulated by Altera Max+Plus 10.0. through the runtime test procedure. The simulation results show that operations of the suggested runtime test architecture are very accurate.

• Journal of The Korean Society of Integrative Medicine
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• v.7 no.1
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• pp.27-36
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• 2019

Purpose : The purpose of this study figures out how the biofeedback exercise combined with a Shaker exercise and a jaw-opening exercise affects the suprahyoid muscle activation of stroke with a swallowing disorder. Methods : The study period was from June, 2018 to September, 2018, to 45 patients who were suitable for selection criteria. Participants were divided into three groups: a visuoauditory biofeedback group (VABG), and a visual biofeedback group (VBG), and a self-exercise group (SG). The three groups were divided into the Shaker exercise and the jaw-opening exercise, and the biofeedback training by themselves. Three groups performed an intervention three times a day, five times a week, and four weeks long. Also, suprahyoid muscle activity was measured with a pre-test, a post-test and a follow-up test. Results : To know the suprahyoid muscle activity after the intervention, there were statistically significant differences between the pre-test and the post-intervention (p< .01). All three groups showed the improvement with the mean comparing followed by VABG, VBG and SG. Comparing between the post- test and the follow-up test, all three groups showed the reduction of suprahyoid muscle activity with the mean comparing, followed VABG, VBG and SG. Conclusion : It found that it was more effective when providing a double-sensory biofeedback than when training with a single-sensory biofeedback. Therefore, it is necessary to provide a multi-sensory input when applying the biofeedback in rehabilitation of the swallowing disorder.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.3
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• pp.214-221
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• 2021

SiC MOSFETs require a faster and more reliable short-circuit protection circuit than conventional methods due to narrow short-circuit withstand times. Therefore, this research proposes a short-circuit protection circuit using a current-sensing circuit based on Rogowski coil. The method of designing the current-sensing circuit, which is a component of the proposed circuit, is presented first. The integrator and input/output filter that compose the current-sensing circuit are designed to have a wide bandwidth for accurately measuring short-circuit currents with high di/dt. The precision of the designed sensing circuit is verified on a double pulse test (DPT). In addition, the sensing accuracy according to the bandwidth of the filters and the number of turns of the Rogowski coil is analyzed. Next, the entire short-circuit protection circuit with the current-sensing circuit is designed in consideration of the fast short-circuit shutdown time. To verify the performance of this circuit, a short-circuit test is conducted for two cases of short-circuit conditions that can occur in the half-bridge structure. Finally, the short-circuit shutdown time is measured to confirm the suitability of the proposed protection circuit for the SiC MOSFET short-circuit protection.

• Journal of Convergence for Information Technology
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• v.12 no.1
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• pp.172-179
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• 2022

Unlike other processes such as washing, the ironing process in the laundry process is difficult to standardize and thus relies on manual labor. Unlike upper garments, pants have pleats at the waist as well as a crease line below the waist, Therefore, two separate ironing devices have been developed and used. However, in this method, problems such as additional worker input, space loss, and wrinkling of pants occur due to manual movement between processes, Consequently, a pants ironing device that combines the two equipments is required. The all-in-one pants ironing system described in this paper automatically sequentially irons the upper part and side of the pants regardless of the length, shape, and upper pleats of the pants. It also performs a self-diagnosis function while displaying the ironing progress on the user's monitor. As a result of this study, it became possible to double the amount of ironing and reduce power consumption by more than 20% compared to the case of using two independent equipment.

• Journal of Industrial Convergence
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• v.19 no.6
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• pp.145-153
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• 2021

This study empirically verified whether there is a dual mediating effect of individual optimistic bias and information security intention in the relationship between information security attitude and information security behavior of social welfare college students. The subjects were 295 college students majoring in social welfare. Spss Process macro was used for analysis. As a result. first there was a significant positive correlation between the variables. Second in the relationship between information security attitude and information security behavior, individual optimistic bias and information security intent each had a simple mediating effect. Third when an individual's optimistic bias and information security intent were simultaneously input, each had a simple mediating effect. Fourth there was a double mediating effect between individual optimistic bias and information security intent. This study provided basic data for the expansion of information security model and information security education of social welfare students.

• Structural Engineering and Mechanics
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• v.83 no.3
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• pp.327-340
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• 2022

The Collapse Margin Ratio (CMR) is a notable index used for seismic assessment of the structures. As proposed by FEMA P695, a set of analyses including the Nonlinear Static Analysis (NSA), Incremental Dynamic Analysis (IDA), together with Fragility Analysis, which are typically time-taking and computationally unaffordable, need to be conducted, so that the CMR could be obtained. To address this issue and to achieve a quick and efficient method to estimate the CMR, the Artificial Neural Network (ANN), Response Surface Method (RSM), and Adaptive Neuro-Fuzzy Inference System (ANFIS) will be introduced in the current research. Accordingly, using the NSA results, an attempt was made to find a fast and efficient approach to derive the CMR. To this end, 5016 IDA analyses based on FEMA P695 methodology on 114 various Reinforced Concrete (RC) frames with 1 to 12 stories have been carried out. In this respect, five parameters have been used as the independent and desired inputs of the systems. On the other hand, the CMR is regarded as the output of the systems. Accordingly, a double hidden layer neural network with Levenberg-Marquardt training and learning algorithm was taken into account. Moreover, in the RSM approach, the quadratic system incorporating 20 parameters was implemented. Correspondingly, the Analysis of Variance (ANOVA) has been employed to discuss the results taken from the developed model. Additionally, the essential parameters and interactions are extracted, and input parameters are sorted according to their importance. Moreover, the ANFIS using Takagi-Sugeno fuzzy system was employed. Finally, all methods were compared, and the effective parameters and associated relationships were extracted. In contrast to the other approaches, the ANFIS provided the best efficiency and high accuracy with the minimum desired errors. Comparatively, it was obtained that the ANN method is more effective than the RSM and has a higher regression coefficient and lower statistical errors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1611-1633
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• 2022

At EUROCRYPT 2019, a new block cipher algorithm called BISON was proposed by Canteaut et al. which uses a novel structure named as Whitened Swap-Or-Not (WSN). Unlike the traditional wide trail strategy, the differential and linear properties of this algorithm can be easily determined. However, the encryption speed of the BISON algorithm is quite low due to a large number of iterative rounds needed to ensure certain security margins. Commonly, denoting by n is the data block length, this design requires 3n encryption rounds. Moreover, the block size n of BISON is always odd, which is not convenient for operations performed on a byte level. In order to overcome these issues, we propose a new block cipher, named DBISON, which more efficiently employs the ideas of double layers typical to the BISON-like construction. More precisely, DBISON divides the input into two parts of size n/2 bits and performs the round computations in parallel, which leads to an increased encryption speed. In particular, the data block length n of DBISON can be even, which gives certain additional implementation benefits over BISON. Furthermore, the resistance of DBISON against differential and linear attacks is also investigated. It is shown the maximal differential probability (MDP) is 1/2^n-1 for n encryption rounds and that the maximal linear probability (MLP) is strictly less than 1/2^n-1 when (n/2+3) iterative encryption rounds are used. These estimates are very close to the ideal values when n is close to 256.

• The Journal of the Acoustical Society of Korea
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• v.28 no.5
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• pp.483-490
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• 2009

In this paper, we develop a speech interface that has acoustic echo cancelling and barge-in functionalities in the car environment. In the echo canceller, DT (Double-Talk) detection algorithm using the correlation coefficients between reference and desired signals can make DT detection errors often in the background noise. We reduce the DT detection errors by using the average power of noise and echo estimated from the input signal. In addition, to make it possible for drivers to give speech command to the system by interrupting the speaker output, barge-in functionality is implemented with the combination of DT detection and appropriate gain control of the speaker output. Through the computer simulation with the assumed car environment and experiment in the real laboratory environment, implemented speech interface has shown good performance in removing acoustic echo signals in the noisy environment with proper operation of barge-in functionality.

• Steel and Composite Structures
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• v.51 no.6
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• pp.679-695
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• 2024

This paper presents a novel technique that combines machine learning (ML) with moth-flame optimization (MFO) methods to predict the axial compressive strength (ACS) of concrete filled double skin steel tubes (CFDST) columns. The proposed model is trained and tested with a dataset containing 125 tests of the CFDST column subjected to compressive loading. Five ML models, including extreme gradient boosting (XGBoost), gradient tree boosting (GBT), categorical gradient boosting (CAT), support vector machines (SVM), and decision tree (DT) algorithms, are utilized in this work. The MFO algorithm is applied to find optimal hyperparameters of these ML models and to determine the most effective model in predicting the ACS of CFDST columns. Predictive results given by some performance metrics reveal that the MFO-CAT model provides superior accuracy compared to other considered models. The accuracy of the MFO-CAT model is validated by comparing its predictive results with existing design codes and formulae. Moreover, the significance and contribution of each feature in the dataset are examined by employing the SHapley Additive exPlanations (SHAP) method. A comprehensive uncertainty quantification on probabilistic characteristics of the ACS of CFDST columns is conducted for the first time to examine the models' responses to variations of input variables in the stochastic environments. Finally, a web-based application is developed to predict ACS of the CFDST column, enabling rapid practical utilization without requesting any programing or machine learning expertise.