• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.43.5-44
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• 2021

In the local Universe, the gravitational effects of mass density fluctuations exert perturbations on galaxies' redshifts on top of Hubble's Law, called 'peculiar velocities'. These peculiar velocities provide an excellent way to test the cosmological model in the nearby Universe. In this talk, we present new cosmological constraints using peculiar velocities measured with the 2MASS Tully-Fisher survey (2MTF), 6dFGS peculiar-velocity survey (6dFGSv), the Cosmicflows-3 and Cosmicflows-4TF compilation. Firstly, the dipole and the quadrupole of the peculiar velocity field, commonly named 'bulk flow' and 'shear' respectively, enable us to test whether our cosmological model accurately describes the motion of galaxies in the nearby Universe. We develop and use a new estimators that accurately preserves the error distribution of the measurements to measure these moments. In all cases, our results are consistent with the predictions of the Λ cold dark matter model. Additionally, measurements of the growth rate of structure, fσ8 in the low-redshift Universe allow us to test different gravitational models. We developed a new estimator of the "momentum" (density weighted peculiar velocity) power spectrum and use joint measurements of the galaxy density and momentum power spectra to place new constraints on the growth rate of structure from the combined 2MTF and 6dFGSv data. We recover a constraint of fσ8=0.404+0.082-0.081 at an effective redshift zeff=0.03. This measurement is also fully consistent with the expectations of General Relativity and the Λ Cold Dark Matter cosmological model.

• Computers and Concrete
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• v.32 no.4
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• pp.399-410
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• 2023

This study proposes a novel use of backpropagated Levenberg-Marquardt neural networks based on computational intelligence heuristics to comprehend the examination of hybrid nanoparticles on the flow of dusty liquid via stretched cylinder. A two-phase model is employed in the present work to describe the fluid flow. The use of desulphated nanoparticles of silver and molybdenum suspended in water as base fluid. The mathematical model represented in terms of partial differential equations, Implementing similarity transformationsis model is converted to ordinary differential equations for the analysis . By adjusting the particle mass concentration and curvature parameter, a unique technique is utilized to generate a dataset for the proposed Levenberg-Marquardt neural networks in various nanoparticle circumstances on the flow of dusty liquid via stretched cylinder. The intelligent solver Levenberg-Marquardt neural networks is trained, tested and verified to identify the nanoparticles on the flow of dusty liquid solution for various situations. The Levenberg-Marquardt neural networks approach is applied for the solution of the hybrid nanoparticles on the flow of dusty liquid via stretched cylinder model. It is validated by comparison with the standard solution, regression analysis, histograms, and absolute error analysis. Strong agreement between proposed results and reference solutions as well as accuracy provide an evidence of the framework's validity.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.15-20
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• 2023

Machine learning is comprised of supervised learning, unsupervised learning and reinforcement learning as the type of data and processing mechanism. In this paper, as input and output are unclear and it is difficult to apply the concrete modeling mathematically, reinforcement learning method are applied for crawling robot in this paper. Especially, Q-Learning is the most effective learning technique in model free reinforcement learning. This paper presents a method to implement a crawling robot that is operated by finding the most optimal crawling method through trial and error in a dynamic environment using a Q-learning algorithm. The goal is to perform reinforcement learning to find the optimal two motor angle for the best performance, and finally to maintain the most mature and stable motion about EV3 Crawling robot. In this paper, for the production of the crawling robot, it was produced using Lego Mindstorms with two motors, an ultrasonic sensor, a brick and switches, and EV3 Classroom SW are used for this implementation. By repeating 3 times learning, total 60 data are acquired, and two motor angles vs. crawling distance graph are plotted for the more understanding. Applying the Q-learning reinforcement learning algorithm, it was confirmed that the crawling robot found the optimal motor angle and operated with trained learning, and learn to know the direction for the future research.

• Structural Engineering and Mechanics
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• v.90 no.2
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• pp.189-208
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• 2024

Artificial intelligence is one of the efficient methods that can be developed to simulate nonlinear behavior and predict the response of building structures. In this regard, an adaptive method based on optimization algorithms is used to train the TSK model of the fuzzy inference system to estimate the seismic behavior of building structures based on analytical data. The optimization algorithm is implemented to determine the parameters of the TSK model based on the minimization of prediction error for the training data set. The adaptive training is designed on the feedback of the results of previous time steps, in which three training cases of 2, 5, and 10 previous time steps were used. The training data is collected from the results of nonlinear time history analysis under 100 ground motion records with different seismic properties. Also, 10 records were used to test the inference system. The performance of the proposed inference system is evaluated on two 3 and 20-story models of nonlinear steel moment frame. The results show that the inference system of the TSK model by combining the optimization method is an efficient computational method for predicting the response of nonlinear structures. Meanwhile, the multi-vers optimization (MVO) algorithm is more accurate in determining the optimal parameters of the TSK model. Also, the accuracy of the results increases significantly with increasing the number of previous steps.

• New & Renewable Energy
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• v.20 no.2
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• pp.17-25
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• 2024

In this study, the effect of the time step specified in a computational fluid dynamics (CFD) simulation on load response is analyzed and the drag coefficients of the floating body of floating offshore wind turbines (FOWTs) are estimated. By evaluating the error in the FOWT load response and the change in the drag-coefficient values based on the density of the time intervals, this study aims to establish a time-interval setting that minimizes the time and cost of CFD simulations for selecting drag-coefficient values. Practical CFD utilization strategies necessary for the calibration of medium-to high-fidelity analysis tools are presented. Based on a comparative analysis of CFD simulations conducted at various time intervals, the results confirmed that under a certain time interval that sufficiently considers various factors, the accuracy of the FOWT response with respect to density shows minimal differences, thereby providing an efficient utilization method for CFD simulations in FOWT design and analysis.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.71-78
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• 2024

In indoor environments, since global positioning system (GPS) signals can be blocked by obstacles, such as building structure. the performance of GPS-based positioning methods can be degraded because of the loss of GPS signals. To solve this problem, various localization schemes using inertial measurement unit (IMU) sensors, such as gyroscope, accelerometer, and magnetometer, have been proposed to enhance the positioning accuracy in indoor environments. IMU-based positioning methods can estimate the location of the user by calculating the velocity and heading angle of the user without the help of GPS. However, low-cost MEMS IMUs may lead to drift error and large bias. In addition, positioning errors in IMU-based positioning approaches can be caused by the irrelevant motion of the pedestrian. In this study, we propose an enhanced indoor positioning method that provides more reliable localization results by using the camera, light detection and right (LiDAR), and ARKit framework on the iPhone. Through reliable positioning results and augmented reality (AR) experiences, our indoor positioning system can provide indoor space guidance services.

• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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• v.13 no.2
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• pp.31-44
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• 2007

The purposes of this study were to examine the normal lumbar proprioception and identify the effect of vision and proprioception on lumbar movement accuracy through measuring a reposition error in visual and non-visual conditions and to provide the basic data for use of vision when rehabilitation program is applied. The subjects of this study were 39 healthy university students who have average physical activity level. They were measured the ability to reproduce the target position(50% of maximal range of motion) of flexion, extension, dominant and non-dominant side flexion in visual and non-visual conditions. Movement accuracy was assessed by reposition error(differences between intended and actual positions) that is calculated by the average of absolute value of 3 repeated measures at each directions. The data were analysed by paired samples t-test, independent samples t-test, and repeated measures ANOVA. The results were as follows : 1. Movement accuracy of flexion, extension, dominant side flexion, and non-dominant side flexion was increased in visual condition. 2. There were no differences in the lumbar movement accuracy between sexes in visual and non-visual conditions. 3. In non-visual condition, the movement in coronal plane(dominant and non dominant side flexion) is more accurate than that in sagittal plane(flexion and extension). 4. In non-visual condition, there were no differences in the lumbar movement accuracy between dominant and non-dominant side flexion. In conclusion, this study demonstrates that the movement is more accurate when the visual information input is available than proprioception is only available. When proprioception is decreased by injury or disease, it disturbs the control of posture and movement. In this case, human controls the posture and movement by using visual compensation. However it is impossible to prevent an injury or trauma because most of injuries occur in an unexpected situation. For this reason, it is important to improve the proprioception. Therefore, proprioceptive training or exercise which improve the ability to control of posture and movement is performed an appropriate control of permission or interception of the visual information input to prevent an excessive visual compensation.

• Geophysics and Geophysical Exploration
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• v.10 no.4
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• pp.241-251
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• 2007

The observed spectra from Odaesan earthquake were fitted to a point-source spectral model to evaluate the source spectrum and spatial features of the modelling error. The source spectrum was calculated by removing from the observed spectra the path and site dependent responses (Yun, 2007) that were previously revealed through an inversion process applied to a large accumulated spectral dataset. The stress drop parameter of one-corner Brune's ${\omega}^2$ source model fitted to the estimated source spectrum was well predicted by the scaling relation between magnitude and stress drop developed by Yun et al. (2006). In particular, the estimated spectrum was quite comparable to the two-corner source model that was empirically developed for recent moderate earthquakes occurring around the Korean Peninsula, which indicates that Odaesan earthquake is one of typical moderate earthquakes representative of Korean Peninsula. Other features of the observed spectra from Odaesan earthquake were also evaluated based on the commonly treated random error between the observed data and the estimated point-source spectral model. Radiation pattern of the error according to azimuth angle was found to be similar to the theoretical estimate. It was also observed that the spatial distribution of the errors was correlated with the geological map and the $Q_0$ map which are indicatives of seismic boundaries.

• Journal of Broadcast Engineering
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• v.13 no.2
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• pp.188-199
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• 2008

In conventional video coding, encoder complexity is much higher than that of decoder. However, investigations for lightweight encoder to eliminate motion prediction/compensation claiming most complexity in encoder have recently become an important issue. The Wyner-Ziv coding is one of the representative schemes for the problem and, in this scheme, since encoder generates only parity bits of a current frame without performing any type of processes extracting correlation information between frames, it has an extremely simple structure compared to conventional coding techniques. However, in Wyner-Ziv coding, channel decoding errors occur when noisy side information is used in channel decoding process. These channel decoding errors appear more frequently, especially, when there is not enough correlation between frames to generate accurate side information and, as a result, those errors look like Salt & Pepper type noise in the reconstructed frame. Since this noise severely deteriorates subjective video quality even though such noise rarely occurs, previously we proposed a computationally extremely light encoding method based on selective median filter that corrects such noise using spatial correlation of a frame. However, in the previous method, there is a problem that loss of texture from filtering may exceed gain from error correction by the filter for video sequences having complex torture. Therefore, in this paper, we propose an improved lightweight encoding method that minimizes loss of texture detail from filtering by allowing information of texture and that of noise in side information to be utilized by the selective median filter. Our experiments have verified average PSNR gain of up to 0.84dB compared to the previous method.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.309-316
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• 2022

Advances in technology have improved people's lives comfortably and have developed more easily, safely and simply. We usually turn on hot water to set the temperature of the water in the bathroom and gradually adjust the temperature to find the temperature we want with our skin. In this situation, I thought, "What if there is a device that can see the temperature of water with my eyes and help with the interior of the bathroom while including a safe system," and tried to create a system that values stability. For example, if a child accidentally changes the temperature of the water to high temperature while washing, he or she can get burned. And the biggest purpose is to secure better safety by adding LCDs and LEDs so that we can visually know the temperature before feeling it tactilely. As a result of the experiment, there was no error between the temperature detected by the water temperature sensor and the temperature displayed on the LCD, and no error occurred up to 27 cm in the distance measurement experiment using the ultrasonic sensor. There has been an error of about 2% since 28cm or older, but there is no significant inconvenience in using it within the category of faucets.