• Title/Summary/Keyword: Cosine Component

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Estimating pile setup parameter using XGBoost-based optimized models

  • Xigang Du;Ximeng Ma;Chenxi Dong;Mehrdad Sattari Nikkhoo
    • Geomechanics and Engineering
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    • v.36 no.3
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    • pp.259-276
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    • 2024
  • The undrained shear strength is widely acknowledged as a fundamental mechanical property of soil and is considered a critical engineering parameter. In recent years, researchers have employed various methodologies to evaluate the shear strength of soil under undrained conditions. These methods encompass both numerical analyses and empirical techniques, such as the cone penetration test (CPT), to gain insights into the properties and behavior of soil. However, several of these methods rely on correlation assumptions, which can lead to inconsistent accuracy and precision. The study involved the development of innovative methods using extreme gradient boosting (XGB) to predict the pile set-up component "A" based on two distinct data sets. The first data set includes average modified cone point bearing capacity (qt), average wall friction (fs), and effective vertical stress (σvo), while the second data set comprises plasticity index (PI), soil undrained shear cohesion (Su), and the over consolidation ratio (OCR). These data sets were utilized to develop XGBoost-based methods for predicting the pile set-up component "A". To optimize the internal hyperparameters of the XGBoost model, four optimization algorithms were employed: Particle Swarm Optimization (PSO), Social Spider Optimization (SSO), Arithmetic Optimization Algorithm (AOA), and Sine Cosine Optimization Algorithm (SCOA). The results from the first data set indicate that the XGBoost model optimized using the Arithmetic Optimization Algorithm (XGB - AOA) achieved the highest accuracy, with R2 values of 0.9962 for the training part and 0.9807 for the testing part. The performance of the developed models was further evaluated using the RMSE, MAE, and VAF indices. The results revealed that the XGBoost model optimized using XGBoost - AOA outperformed other models in terms of accuracy, with RMSE, MAE, and VAF values of 0.0078, 0.0015, and 99.6189 for the training part and 0.0141, 0.0112, and 98.0394 for the testing part, respectively. These findings suggest that XGBoost - AOA is the most accurate model for predicting the pile set-up component.

Study On The Robustness Of Face Authentication Methods Under illumination Changes (얼굴인증 방법들의 조명변화에 대한 견인성 비교 연구)

  • Ko Dae-Young;Kim Jin-Young;Na Seung-You
    • The KIPS Transactions:PartB
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    • v.12B no.1 s.97
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    • pp.9-16
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    • 2005
  • This paper focuses on the study of the face authentication system and the robustness of fact authentication methods under illumination changes. Four different face authentication methods are tried. These methods are as fellows; PCA(Principal Component Analysis), GMM(Gaussian Mixture Modeis), 1D HMM(1 Dimensional Hidden Markov Models), Pseudo 2D HMM(Pseudo 2 Dimensional Hidden Markov Models). Experiment results involving an artificial illumination change to fate images are compared with each other. Face feature vector extraction based on the 2D DCT(2 Dimensional Discrete Cosine Transform) if used. Experiments to evaluate the above four different fate authentication methods are carried out on the ORL(Olivetti Research Laboratory) face database. Experiment results show the EER(Equal Error Rate) performance degrade in ail occasions for the varying ${\delta}$. For the non illumination changes, Pseudo 2D HMM is $2.54{\%}$,1D HMM is $3.18{\%}$, PCA is $11.7{\%}$, GMM is $13.38{\%}$. The 1D HMM have the bettor performance than PCA where there is no illumination changes. But the 1D HMM have worse performance than PCA where there is large illumination changes(${\delta}{\geq}40$). For the Pseudo 2D HMM, The best EER performance is observed regardless of the illumination changes.

Word Sense Similarity Clustering Based on Vector Space Model and HAL (벡터 공간 모델과 HAL에 기초한 단어 의미 유사성 군집)

  • Kim, Dong-Sung
    • Korean Journal of Cognitive Science
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    • v.23 no.3
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    • pp.295-322
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    • 2012
  • In this paper, we cluster similar word senses applying vector space model and HAL (Hyperspace Analog to Language). HAL measures corelation among words through a certain size of context (Lund and Burgess 1996). The similarity measurement between a word pair is cosine similarity based on the vector space model, which reduces distortion of space between high frequency words and low frequency words (Salton et al. 1975, Widdows 2004). We use PCA (Principal Component Analysis) and SVD (Singular Value Decomposition) to reduce a large amount of dimensions caused by similarity matrix. For sense similarity clustering, we adopt supervised and non-supervised learning methods. For non-supervised method, we use clustering. For supervised method, we use SVM (Support Vector Machine), Naive Bayes Classifier, and Maximum Entropy Method.

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Raining Image Enhancement and Its Processing Acceleration for Better Human Detection (사람 인식을 위한 비 이미지 개선 및 고속화)

  • Park, Min-Woong;Jeong, Geun-Yong;Cho, Joong-Hwee
    • IEMEK Journal of Embedded Systems and Applications
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    • v.9 no.6
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    • pp.345-351
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    • 2014
  • This paper presents pedestrian recognition to improve performance for vehicle safety system or surveillance system. Pedestrian detection method using HOG (Histograms of Oriented Gradients) has showed 90% recognition rate. But if someone takes a picture in the rain, the image may be distorted by rain streaks and recognition rate goes down by 62%. To solve this problem, we applied image decomposition method using MCA (Morphological Component Analysis). In this case, rain removal method improves recognition rate from 62% to 70%. However, it is difficult to apply conventional image decomposition method using MCA on vehicle safety system or surveillance system as conventional method is too slow for real-time system. To alleviate this issue, we propose a rain removal method by using low-pass filter and DCT (Discrete Cosine Transform). The DCT helps separate the image into rain components. The image is removed rain components by Butterworth filtering. Experimental results show that our method achieved 90% of recognition rate. In addition, the proposed method had accelerated processing time to 17.8ms which is acceptable for real-time system.

United Electromagnetic Characteristics and Online Monitoring Method of Static Air-gap Eccentricity of Turbo-Generator

  • Tang, Gui-Ji;Ke, Meng-Qiang;He, Yu-Ling;Wang, Fa-Lin
    • Journal of Electrical Engineering and Technology
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    • v.11 no.6
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    • pp.1614-1627
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    • 2016
  • The purpose of this paper is to investigate the united Electromagnetic characteristics for the effective monitoring on the static air-gap eccentricity (SAGE) of turbo-generator. Different from other studies, this paper not only studies on the unbalanced magnetic pull (UMP) and the vibration characteristics of the stator and the rotor, but also investigates the harmonic features of the magnetic flux density and the circulating current inside the parallel branches (CCPB). The theoretical calculation, together with the finite-element-method (FEM) simulation and the experiment verification, is taken for a SDF-9 type non-salient generator. It is shown that, when SAGE occurs, apparent double-frequency UMP and vibrations will be produced both on the stator and the rotor, while the CCPB will have an obvious increment at the $1^{st}$ harmonic component. In addition, the amplitude of the magnetic flux density will be of cosine distribution in the circumferential position of the air-gap, while in normal condition it is a constant. Moreover, the pass-band amplitude, together with the $1^{st}$ harmonic of the magnetic flux density, will be enlarged as well. These united electromagnetic characteristics can be used as the diagnosis and monitoring criterion for SAGE.

Digital Image Watermarking Schemes Based on GCST and SVD (GCST-SVD 기반 디지털 영상 워터마킹 방법)

  • Lee, Juck-Sik
    • Journal of the Institute of Convergence Signal Processing
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    • v.14 no.3
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    • pp.154-161
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    • 2013
  • In this paper, Gabor cosine and sine transform considered as human visual filter is applied to watermarking methods for digital images. Four algorithms by using singular values or principal components of SVD in the frequency domain are proposed for watermark embedding and extraction. Two dimensional image is used as an embedded watermark. To measure the similarity between the embedded watermark image and the extracted one, a normalized correlation value is computed for the comparison of the four proposed methods with various attacks. Extracted watermark images are also provided for visual inspection. The proposed GCST-SVD method which embeds a watermark image into the lowest vertical or horizontal ac frequency band can provide useful watermarking algorithm with high correlation values and visual watermark features from experimental results for various attacks.

Shuffled Discrete Sine Transform in Inter-Prediction Coding

  • Choi, Jun-woo;Kim, Nam-Uk;Lim, Sung-Chang;Kang, Jungwon;Kim, Hui Yong;Lee, Yung-Lyul
    • ETRI Journal
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    • v.39 no.5
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    • pp.672-682
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    • 2017
  • Video compression exploits statistical, spatial, and temporal redundancy, as well as transform and quantization. In particular, the transform in a frequency domain plays a major role in energy compaction of spatial domain data into frequency domain data. The high efficient video coding standard uses the type-II discrete cosine transform (DCT-II) and type-VII discrete sine transform (DST-VII) to improve the coding efficiency of residual data. However, the DST-VII is applied only to the Intra $4{\times}4$ residual block because it yields relatively small gains in the larger block than in the $4{\times}4$ block. In this study, after rearranging the data of the residual block, we apply the DST-VII to the inter-residual block to achieve coding gain. The rearrangement of the residual block data is similar to the arrangement of the basis vector with a the lowest frequency component of the DST-VII. Experimental results show that the proposed method reduces the luma-chroma (Cb+Cr) BD rates by approximately 0.23% to 0.22%, 0.44% to 0.58%, and 0.46% to 0.65% for the random access, low delay B, and low delay P configurations, respectively.

Digital Watermarking using HVS and Neural Network (HVS와 신경회로망을 이용한 디지털 워터마킹)

  • Lee, Young-Hee;Lee, Mun-Hee;Cha, Eui-Young
    • The Journal of Korean Association of Computer Education
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    • v.9 no.2
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    • pp.101-109
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    • 2006
  • We propose an adaptive digital watermarking algorithm using HVS(human visual system) and SOM(Self-Organizing Map) among neural networks. This method adjusts adaptively the strength of the watermark which is embedded in different blocks according to block classification in DCT(Discrete Cosine Transform) domain. All blocks in 3 classes out of 4 are selected to embed a watermark. Watermark sequences are embedded in 6 lowest frequency coefficients of each block except the DC component. The experimental results are excellent.

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ULTRAVIOLET ISOPHOTE SHAPES OF NEARBY ELLIPTICAL GALAXIES AND SPIRAL BULGES

  • SOHN YOUNG-JONG
    • Journal of The Korean Astronomical Society
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    • v.34 no.2
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    • pp.59-66
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    • 2001
  • In this paper, we investigate the correlation between the radial ultraviolet color distribution and the shapes of the ultraviolet isophote for elliptical galaxies (M32, NGC 1399) and spiral bulges (of M31, M81) by using their archival UIT images. For M31, M81, and NGC 1399, the radial ultraviolet color distributions show a two-component trend; as the distance from the galactic center increase the color becomes redder in the inner region while it becomes bluer in the outer region. On the other hand, the color of M32 continues to become bluer with the increasing galactocentric distance. We also find, unlike the optical/IR images, significant variations of the position angle and the ellipticity in the ultraviolet isophotes of M31, M81, and NGC 1399 through the inner regions. For M32, the variation is significant in the outer region. Since these variation implies the triaxiality of their intrinsic shapes, we suggest that the early-type galaxies and spiral bulges with a radial color gradient in ultraviolet tend to have a triaxiality. On the other hand, the shape parameter characterized by the fourth order cosine Fourier coefficient of the isophote, a(4)/a, indicates that the systematic deviations of the ultraviolet isophotes of the four galaxies are smaller than $\~0.2\%$ in units of the semi-major axis. The latter result implies that the ultraviolet isophotes of the galaxies have a pure elliptical shape rather than the boxy or disky shapes. Therefore, there is no clear evidence of correlation between the radial ultra-violet color gradient and the boxy/disky shapes of isophotes.

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An Efficient Coding Technique of Holographic Video Signal using 3D Segment Scanning (분할영역의 3차원 스캐닝을 이용한 홀로그래픽 비디오 신호의 효율적인 부호화 기술)

  • Seo, Young-Ho;Choi, Hyun-Jun;Kim, Dong-Wook
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.2C
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    • pp.132-140
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    • 2007
  • In this paper, we proposed a new technique to encode and decode the digital hologram. Since the digital hologram (or fringe pattern) is generated by interference of light, it has much different property from natural 2D (2 dimensional) images. First, we acquisite optical-sensed or computer-generated hologram by digital type, and then extract a chrominance component. The extracted digital hologram for coding is separated into segments to use multi-view properties. The segmented hologram shows the similar characteristics with picturing an object with 2D cameras in various point of view. Since fringe pattern is visually observed like as noise, we expect that the fringe pattern has poor coding efficiency. To obtain high efficiency, the segment is transformed with DCT (Discrete Cosine Transform) which resembles hologram generation process with high performance. Each transformed segment passes the 3D scanning process according to time and spatial correlation, and is organized into a video stream. Since the segment which correspond to frame of a video stream consists of the transformed coefficients with wide range of value, it is classified and re-normalized. Finally it is compressed with coding tools. The proposed algorithm illustrated that it has better properties for reconstruction of 16 times higher compression rate than the previous researches.