• Title/Summary/Keyword: Gaussian density

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Comparison of the Machine Learning Models Predicting Lithium-ion Battery Capacity for Remaining Useful Life Estimation (리튬이온 배터리 수명추정을 위한 용량예측 머신러닝 모델의 성능 비교)

  • Yoo, Sangwoo;Shin, Yongbeom;Shin, Dongil
    • Journal of the Korean Institute of Gas
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    • v.24 no.6
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    • pp.91-97
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    • 2020
  • Lithium-ion batteries (LIBs) have a longer lifespan, higher energy density, and lower self-discharge rates than other batteries, therefore, they are preferred as an Energy Storage System (ESS). However, during years 2017-2019, 28 ESS fire accidents occurred in Korea, and accurate capacity estimation of LIB is essential to ensure safety and reliability during operations. In this study, data-driven modeling that predicts capacity changes according to the charging cycle of LIB was conducted, and developed models were compared their performance for the selection of the optimal machine learning model, which includes the Decision Tree, Ensemble Learning Method, Support Vector Regression, and Gaussian Process Regression (GPR). For model training, lithium battery test data provided by NASA was used, and GPR showed the best prediction performance. Based on this study, we will develop an enhanced LIB capacity prediction and remaining useful life estimation model through additional data training, and improve the performance of anomaly detection and monitoring during operations, enabling safe and stable ESS operations.

Application of Non-Open Cut H.A.S Method to Improve Constructability (시공성 향상을 위한 비개착 H.A.S 공법 적용에 관한 연구)

  • Choi, Jung-Youl;Jang, Sung-Ho;Chung, Jee-Seung
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.6
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    • pp.765-773
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    • 2022
  • This study is a study on the application of a horizontal excavation machine system to improve constructability. In this study, the structural stability of non-covered temporary facilities was evaluated by comparing field measurements and numerical analysis. In addition, the appropriateness of the measurement results was analyzed by comparing and analyzing the results of numerical analysis with the analysis results applying the Gaussian probability density function to the measurement results. In this study, structural safety and long-term durability of the linkage were analyzed based on numerical analysis. As a result of the study, it was analyzed that the non-open cut method (H.A.S. method) of this study secures structural safety and constructability as the behavior in the actual construction process is more safe than the numerical analysis results, even if the uncertainty of the ground condition is taken into account.

A grid-line suppression technique based on the nonsubsampled contourlet transform in digital radiography

  • Namwoo Kim;Taeyoung Um;Hyun Tae Leem;Bon Tack Koo;Kyuseok Kim;Kyu Bom Kim
    • Nuclear Engineering and Technology
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    • v.55 no.2
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    • pp.655-668
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    • 2023
  • In radiography, an antiscatter grid is a well-known device for eliminating unexpected x-ray scatter. We investigate a new stationary grid artifact suppression method based on a nonsubsampled contourlet transform (NSCT) incorporated with Gaussian band-pass filtering. The proposed method has an advantage that extracts the Moiré components while minimizing the loss of image information and apply the prior information of Moiré component positions in multi-decomposition sub-band images. We implemented the proposed algorithm and performed a simulation and an experiment to demonstrate its viability. We did this experiment using an x-ray tube (M-113T, Varian, focal spot size: 0.1 mm), a flat-panel detector (ROSE-M Sensor, Aspenstate, pixel dimension: 3032 × 3800 pixels, pixel size: 0.076 mm), and carbon graphite-interspaced grids (JPI Healthcare, 18 cm × 24 cm, line density: 103 LP/inch and 150 LP/inch, ratio: 5:1, focal distance: 65 cm). Our results indicate that the proposed method successfully suppressed grid artifacts by reducing them without either reducing the spatial resolution or causing negative side effects. Consequently, we anticipate that the proposed method can improve image acquisition in a stationary grid x-ray system as well as in extended x-ray imaging.

Gas kinematics and star formation in NGC 6822

  • Park, Hye-Jin;Oh, Se-Heon;Wang, Jing;Zheng, Yun;Zhang, Hong-Xin;de Blok, W.J.G.
    • The Bulletin of The Korean Astronomical Society
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    • v.45 no.1
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    • pp.61.4-62
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    • 2020
  • We present H I gas kinematics and star formation activities of NGC 6822, a dwarf galaxy located in the Local Volume at a distance of ~490 kpc. We perform profile decomposition of the line-of-sight velocity profiles of the high-resolution (~42.4" × 12") spatial; ~1.6 km/s spectral) H I data cube taken with the Australia Telescope Compact Array (ATCA). For this, we use a new tool, the so-called BAYGAUD (BAYesian GAUssian Decompositor) which is based on Bayesian Markov Chain Monte Carlo (MCMC) techniques, allowing us to decompose a line-of-sight velocity profile into an optimal number of Gaussian components in a quantitative manner. We classify the decomposed H I gas components of NGC 6822 into kinematically cold, warm or hot ones with respect to their velocity dispersion: 1) cold: < 4 km/s, 2) warm: 4 ~ 8 km/s, 3) hot: > 8 km/s. We then derive the Toomre-Q parameters of NGC 6822 using the kinematically decomposed H I gas maps. We also correlate their gas surface densities with the surface star formation rates derived using both GALEX far-ultraviolet and WISE 22 micron data to examine the impact of gas turbulence caused by stellar feedback on the Kennicutt-Schmidt (K-S) law. The kinematically cold component is likely to better follow the linear extension of the Kennicutt-Schmidt (K-S) law for molecular hydrogen (H2) at the low gas surface density regime where H I is not saturated.

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Landslide risk zoning using support vector machine algorithm

  • Vahed Ghiasi;Nur Irfah Mohd Pauzi;Shahab Karimi;Mahyar Yousefi
    • Geomechanics and Engineering
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    • v.34 no.3
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    • pp.267-284
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    • 2023
  • Landslides are one of the most dangerous phenomena and natural disasters. Landslides cause many human and financial losses in most parts of the world, especially in mountainous areas. Due to the climatic conditions and topography, people in the northern and western regions of Iran live with the risk of landslides. One of the measures that can effectively reduce the possible risks of landslides and their crisis management is to identify potential areas prone to landslides through multi-criteria modeling approach. This research aims to model landslide potential area in the Oshvand watershed using a support vector machine algorithm. For this purpose, evidence maps of seven effective factors in the occurrence of landslides namely slope, slope direction, height, distance from the fault, the density of waterways, rainfall, and geology, were prepared. The maps were generated and weighted using the continuous fuzzification method and logistic functions, resulting values in zero and one range as weights. The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. Modeling procedure was done using four linear, polynomial, Gaussian, and sigmoid kernels. The efficiency of each model was compared using the area under the receiver operating characteristic curve; the root means square error, and the correlation coefficient . Finally, the landslide potential model that was obtained using Gaussian's kernel was selected as the best one for susceptibility of landslides in the Oshvand watershed.

Characterization of the wind-induced response of a 356 m high guyed mast based on field measurements

  • Zhe Wang;Muguang Liu;Lei Qiao;Hongyan Luo;Chunsheng Zhang;Zhuangning Xie
    • Wind and Structures
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    • v.38 no.3
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    • pp.215-229
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    • 2024
  • Guyed mast structures exhibit characteristics such as high flexibility, low mass, small damping ratio, and large aspect ratio, leading to a complex wind-induced vibration response mechanism. This study analyzed the time- and frequency-domain characteristics of the wind-induced response of a guyed mast structure using measured acceleration response data obtained from the Shenzhen Meteorological Gradient Tower (SZMGT). Firstly, 734 sets of 1-hour acceleration samples measured from 0:00 October 1, 2021, to 0:00 November 1, 2021, were selected to study the vibration shapes of the mast and the characteristics of the generalized extreme value (GEV) distribution. Secondly, six sets of typical samples with different vibration intensities were further selected to explore the Gaussian property and modal parameter characteristics of the mast. Finally, the modal parameters of the SZMGT are identified and the identification results are verified by finite element analysis. The findings revealed that the guyed mast vibration shape exhibits remarkable diversity, which increases nonlinearly along the height in most cases and reaches a maximum at the top of the tower. Moreover, the GEV distribution characteristics of the 734 sets of samples are closer to the Weibull distribution. The probability distribution of the structural wind vibration response under strong wind is in good agreement with the Gaussian distribution. The structural response of the mast under wind loading exhibits multiple modes. As the structural response escalates, the first three orders of modal energy in the tower display a gradual increase in proportion.

Improvement of the PFCM(Possibilistic Fuzzy C-Means) Clustering Method (PFCM 클러스터링 기법의 개선)

  • Heo, Gyeong-Yong;Choe, Se-Woon;Woo, Young-Woon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.1
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    • pp.177-185
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    • 2009
  • Cluster analysis or clustering is a kind of unsupervised learning method in which a set of data points is divided into a given number of homogeneous groups. Fuzzy clustering method, one of the most popular clustering method, allows a point to belong to all the clusters with different degrees, so produces more intuitive and natural clusters than hard clustering method does. Even more some of fuzzy clustering variants have noise-immunity. In this paper, we improved the Possibilistic Fuzzy C-Means (PFCM), which generates a membership matrix as well as a typicality matrix, using Gath-Geva (GG) method. The proposed method has a focus on the boundaries of clusters, which is different from most of the other methods having a focus on the centers of clusters. The generated membership values are suitable for the classification-type applications. As the typicality values generated from the algorithm have a similar distribution with the values of density function of Gaussian distribution, it is useful for Gaussian-type density estimation. Even more GG method can handle the clusters having different numbers of data points, which the other well-known method by Gustafson and Kessel can not. All of these points are obvious in the experimental results.

Geostatistical Approach to Integrated Modeling of Iron Mine for Evaluation of Ore Body (철광산의 광체 평가를 위한 지구통계학적 복합 모델링)

  • Ahn, Taegyu;Oh, Seokhoon;Kim, Kiyeon;Suh, Baeksoo
    • Geophysics and Geophysical Exploration
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    • v.15 no.4
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    • pp.177-189
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    • 2012
  • Evaluation of three-dimensional ore body modeling has been performed by applying the geostatistical integration technique to multiple geophysical (electrical resistivity, MT) and geological (borehole data, physical properties of core) information. It was available to analyze the resistivity range in borehole and other area through multiple geophysical data. A correlation between resistivity and density from physical properties test of core was also analyzed. In the case study results, the resistivity value of ore body is decreased contrast to increase of the density, which seems to be related to a reason that the ore body (magnetite) includes heavy conductive component (Fe) in itself. Based on the lab test of physical properties in iron mine region, various geophysical, geological and borehole data were used to provide ore body modeling, that is electrical resistivity, MT, physical properties data, borehole data and grade data obtained from borehole data. Of the various geostatistical techniques for the integrated data analysis, in this study, the SGS (sequential Gaussian simulation) method was applied to describe the varying non-homogeneity depending on region through the realization that maintains the mean and variance. With the geostatistical simulation results of geophysical, geological and grade data, the location of residual ore body and ore body which is previously reported was confirmed. In addition, another highly probable region of iron ore bodies was estimated deeper depth in study area through integrated modeling.

Characteristics of Impulse Radios for Mu1tipath Channels (다중 경로 채널에서 임펄스 라디오의 특징)

  • 이호준;한병칠
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.26 no.11B
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    • pp.1501-1509
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    • 2001
  • Recently, the use of wireless communication systems has been rapidly increasing, which results in a difficult problem in efficient control of limited frequency resources. As a way of solving this problem, the ultra wideband time hopping impulse radio system attracts much attention. The impulse radio system communicates pulse position modulated data using Gaussian monocycle pulses of very short duration less than 1 nsec. Thus the transmitted signal has very low power spectral density and ultra wide bandwidth from near D.C. to a few GHz. It is blown that it hardly interferes with the existing communication systems because of its very low power spectral density. The purpose of this paper is to characterize multipath propagation of the impulse radio signal and to evaluate the performance of the correlator-based receiver for the multipath environments. In this paper, we consider the deterministic two-path model and the statistical indoor multipath model of Saleh and Valenzuela. For the two-path model the output of the correlator with the ideal reference waveform varies according to the relative difference between the indirect path delay and the time interval of PPM, and to the indirect path gains. In addition, the characteristics of bit error rates is measured for the two models through computer simulation. The simulation results indicate that the performance of the impulse radio system depends both on the relative difference between the indirect path delay and the time interval of PPM, and on the indirect path gains. Furthermore, it is observed that the reference signal designed for the AWGN channel can not be applied to the multipath channels.

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A Small-area Hardware Implementation of EGML-based Moving Object Detection Processor (EGML 기반 이동객체 검출 프로세서의 저면적 하드웨어 구현)

  • Sung, Mi-ji;Shin, Kyung-wook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.12
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    • pp.2213-2220
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    • 2017
  • This paper proposes an efficient approach for hardware implementation of moving object detection (MOD) processor using effective Gaussian mixture learning (EGML)-based background subtraction method. Arithmetic units used in background generation were implemented using LUT-based approximation to reduce hardware complexity. Hardware resources used for both background subtraction and Gaussian probability density calculation were shared. The MOD processor was verified by FPGA-in-the-loop simulation using MATLAB/Simulink. The MOD performance was evaluated by using six types of video defined in IEEE CDW-2014 dataset, which resulted the average of recall value of 0.7700, the average of precision value of 0.7170, and the average of F-measure value of 0.7293. The MOD processor was implemented with 882 slices and block RAM of $146{\times}36kbits$ on Virtex5 FPGA, resulting in 60% hardware reduction compared to conventional design based on EGML. It was estimated that the MOD processor could operate with 75 MHz clock, resulting in real-time processing of $800{\times}600$ video with a frame rate of 39 fps.