• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.123-128
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• 2022

The torque of the SRM((Switched Reluctance Motor)) is proportional to the inductance slope, so it has a non-linear torque characteristic, and has a disadvantage in that the torque pulsation is large and noise is severe. In particular, the biggest obstacle to the commercialization of SRM is the pulsating torque generated from the rotating shaft, which has various adverse effects not only on the device itself but also on the peripheral devices. Therefore, various methods for reducing the pulsating torque have been published by domestic and foreign researchers, and there is a study result that the hysteresis controller has an advantage in that it can flow a smooth current compared to the chopping control. However, in determining the hysteresis band, if the band is too small, it has a disadvantage in that it may cause a switching loss due to many switching and an unstable initial start when the encoder is used. Therefore, in this paper, a variable hysteresis controller that can reduce torque ripple in a steady state while having a more stable and fast speed response through the change of the hysteresis band according to the speed error.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.36-48
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• 2022

As a valid numerical method to obtain a high-resolution result of a flow field, computational fluid dynamics (CFD) have been widely used to study coolant flow and heat transfer characteristics in fuel rod bundles. However, the time-consuming, iterative calculation of Navier-Stokes equations makes CFD unsuitable for the scenarios that require efficient simulation such as sensitivity analysis and uncertainty quantification. To solve this problem, a reduced-order model (ROM) based on proper orthogonal decomposition (POD) and machine learning (ML) is proposed to simulate the flow field efficiently. Firstly, a validated CFD model to output the flow field data set of the rod bundle is established. Secondly, based on the POD method, the modes and corresponding coefficients of the flow field were extracted. Then, an deep feed-forward neural network, due to its efficiency in approximating arbitrary functions and its ability to handle high-dimensional and strong nonlinear problems, is selected to build a model that maps the non-linear relationship between the mode coefficients and the boundary conditions. A trained surrogate model for modes coefficients prediction is obtained after a certain number of training iterations. Finally, the flow field is reconstructed by combining the product of the POD basis and coefficients. Based on the test dataset, an evaluation of the ROM is carried out. The evaluation results show that the proposed POD-ROM accurately describe the flow status of the fluid field in rod bundles with high resolution in only a few milliseconds.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.31 no.6
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• pp.258-263
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• 2021

ZnO varistor is a semiconductor device which can serve to protect the circuit from surge voltage because its non-linear I-V characteristics by controlling the microstructure of grain and grain boundaries. In order to obtain desired electrical properties, it is important to control microstructure evolution during the sintering process. In this research, we defined a dataset composed of process conditions of sintering and relative permittivity of sintered body, and collected experimental dataset with DOE. Meta-models can predict permittivity were developed by learning the collected experimental dataset on various machine learning algorithms. By utilizing the meta-model, we can derive optimized sintering conditions that could show the maximum permittivity from the numerical-based HMA (Hybrid Metaheuristic Algorithm) optimization algorithm. It is possible to search the optimal process conditions with minimum number of experiments if meta-model-based optimization is applied to ceramic processing.

• Journal of the Korea Society for Simulation
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• v.19 no.3
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• pp.109-117
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• 2010

In this study, we consider stationary waiting times in a simple fork-and-join type queue which consists of three single-server machines, Machine 1, Machine 2, and Assembly Machine. We assume that the queue has a renewal arrival process and that independent service times at each node are either deterministic or non-overlapping. We also assume that the Machines 1 and 2 have an infinite buffer capacity whereas the Assembly Machine has two finite buffers, one for each machine. Services at each machine are given by FIFO service discipline and a communication blocking policy. We derive the explicit expressions for stationary waiting times at all nodes as a function of finite buffer capacities by using (max,+)-algebra. Various characteristics of stationary waiting times such as mean, higher moments, and tail probability can be computed from these expressions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.216-238
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• 2023

In intelligent transportation systems, traffic management is an important task. The accurate forecasting of traffic characteristics like flow, congestion, and density is still active research because of the non-linear nature and uncertainty of the spatiotemporal data. Inclement weather, such as rain and snow, and other special events such as holidays, accidents, and road closures have a significant impact on driving and the average speed of vehicles on the road, which lowers traffic capacity and causes congestion in a widespread manner. This work designs a model for multivariate short-term traffic congestion prediction using SLSTM_AE-BiLSTM. The proposed design consists of a Bidirectional Long Short Term Memory(BiLSTM) network to predict traffic flow value and a Convolutional Neural network (CNN) model for detecting the congestion status. This model uses spatial static temporal dynamic data. The stacked Long Short Term Memory Autoencoder (SLSTM AE) is used to encode the weather features into a reduced and more informative feature space. BiLSTM model is used to capture the features from the past and present traffic data simultaneously and also to identify the long-term dependencies. It uses the traffic data and encoded weather data to perform the traffic flow prediction. The CNN model is used to predict the recurring congestion status based on the predicted traffic flow value at a particular urban traffic network. In this work, a publicly available Caltrans PEMS dataset with traffic parameters is used. The proposed model generates the congestion prediction with an accuracy rate of 92.74% which is slightly better when compared with other deep learning models for congestion prediction.

• Journal of radiological science and technology
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• v.47 no.2
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• pp.117-123
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• 2024

This study was to assessment of quality assurance (QA) and noise characteristics of Noise Power Spectrum (NPS) according to the time of by using electronic portal imaging device (EPID) for LINAC (Linear Accelerator). LINAC device was (Varian Clinac^R iX LINAC, USA) used and the were 40 × 30 cm² of detector size were 1024 × 768 photo-electric diode array size. Signal could be obtained the K-space image of white noise images for NPS and we used to Overlap, Non-Overlap, Out of Penumbra, Flatness, Symmetry, Symmetry Rt, Lt methods. The 2013s NPS image Out of Penumbra quantitatively value more than 2013s NPS image Symmetry Rt, Lt methods quantitatively NPS based on the frequency of 1.0 mm^-1. Thus, the 2022s NPS image Out of Penumbra quantitatively value more than 2022s NPS image Symmetry Rt, Lt methods quantitatively NPS based on the frequency of 1.0 mm^-1. The assessment of comparison of white noise for NPS image noise and intensity of this study were to that should be used efficiently of the LINAC EPID detector system for Overlap method for International Electro-technical Commission (IEC).

• The Journal of the Acoustical Society of Korea
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• v.27 no.5
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• pp.215-220
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• 2008

The kerfs between arrayed piezoelectric elements in a medical ultrasonic transducer or a piezoelectric composite transducer are generally filled by polymeric materials. The boundary condition of the elements for lateral mode vibration is changed according to the kerf-filling materials, so that the resonance frequency for longitudinal mode of the transducer is also varied. In this study, to investigate the resonance frequency variation for an arrayed transducer experimentally, the piezoelectric vibration elements of $14mm{\times}0.22mm{\times}0.44mm$ were fabricated and those were linearly arrayed. And, the resonance frequencies were measured for three cases of kerf-filling condition, non-filling and two different kinds of epoxy filling. Conclusively, it is confirmed that the resonant frequency variation shows the similar tendency with the theoretical one for the longitudinal mode.

• Korea Journal of Hospital Management
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• v.28 no.4
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• pp.23-32
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• 2023

Purposes: Caregivers are placed in a poor working environment because there is no special legal basis or definition in the current medical system, and they have difficulty in supplying manpower due to frequent job change and retirement. Therefore, this study aimed to find out the effect on job consciousness, job stress, job satisfaction, and turnover intention of caregivers in nursing hospitals for the elderly. Methodology: In this study, a survey was conducted from May 2nd to 16th, 2022, targeting caregivers with more than 6 months of work experience working at 10 nursing hospitals in D City. Data were collected through convenience sampling, and a self-administered questionnaire method was used, in which subjects filled out a questionnaire. A total of 240 questionnaires were distributed, and 220 copies were considered for the final analysis after excluding non-response or inappropriate questionnaires for data use. Data analysis used t-test, ANOVA, Pearson's correlation coefficient, and multiple linear regression analysis, and the main results are as follows. Findings: Job stress and job satisfaction showed a significant correlation with the level of turnover intention, and were also found to be major determinants. On the other hand, among the occupational characteristics of the study subjects, employment type, job motivation, service period, number of patients, injury experience, and license status showed a significant difference from turnover intention. Conclusion: As a result of the above research, in order to prevent job turnover and retirement by improving job stress and job satisfaction of caregivers engaged in nursing hospitals, it is necessary not only to legalize caregivers, but also to secure an appropriate level of caregivers for nursing hospitals and improve specific treatment for caregivers. Ultimately, a policy alternative that can provide quality nursing service is required.

• Structural Engineering and Mechanics
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• v.90 no.3
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• pp.219-232
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• 2024

In current study, for the first time, Nonlinear Bending of a skew microplate made of a laminated composite strengthened with graphene nanosheets is investigated. A mixture of mechanical and thermal stresses is applied to the plate, and the reaction is analyzed using the First Shear Deformation Theory (FSDT). Since different percentages of graphene sheets are included in the multilayer structure of the composite, the characteristics of the composite are functionally graded throughout its thickness. Halpin-Tsai models are used to characterize mechanical qualities, whereas Schapery models are used to characterize thermal properties. The microplate's non-linear strain is first calculated by calculating the plate shear deformation and using the Green-Lagrange tensor and von Karman assumptions. Then the elements of the Couple and Cauchy stress tensors using the Modified Coupled Stress Theory (MCST) are derived. Next, using the Hamilton Principle, the microplate's governing equations and associated boundary conditions are calculated. The nonlinear differential equations are linearized by utilizing auxiliary variables in the nonlinear solution by applying the Frechet approach. The linearized equations are rectified via an iterative loop to precisely solve the problem. For this, the Differential Quadrature Method (DQM) is utilized, and the outcomes are shown for the basic support boundary condition. To ascertain the maximum values of microplate deflection for a range of circumstances-such as skew angles, volume fractions, configurations, temperatures, and length scales-a parametric analysis is carried out. To shed light on how the microplate behaves in these various circumstances, the resulting results are analyzed.

• Journal of The Korean Society of Grassland and Forage Science
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• v.40 no.3
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• pp.167-176
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• 2020

The objective of the present study was to determine the best model to describe and quantify the changes in live body weight, height at withers, height at rump, body length and chest girth of Holstein cows raised under Korean feeding conditions for 50 months. The five standard growth models namely polynomial linear regression models, regression of growth variables on the first and second-order of ages in days (model 1) and regression of growth variables on age covariates from first to the third-order (model 2) as well as non-linear models were fitted and evaluated for representing growth pattern of Holstein cows raised in Korean feeding circumstances. Nonlinear models fitted were three exponential growth curve models; Brody, Gompertz, and von Bertalanffy functional models. For this purpose, a total of 22 Holstein cows raised in Korea used in the period from April 2016 to May 2020. Each model fitted to monthly growth curve records of dairy cows by using PROC NLIN procedure in SAS program. On the basis of the results, nonlinear models showed the lower root mean square of error (RMSE) for live body weight, height at withers, height at rump, body length and chest girth (12.22, 1.95, 1.55, 4.04, 2.06) with higher correlation coefficiency (R²) values for live body weight, height at withers, height at rump, body length and chest girth (0.99, 0.99, 0.99, 1.00, 1.00). Overall, the evaluation of the different growth models indicated that the Gompertz model used in the study seemed to be the most appropriate one for standard growth of Holstein cows raised under Korean feeding system.