• Title/Summary/Keyword: Data normalization

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Elastic α-12C Scattering with the Ground State of 16O at Low Energies in Effective Field Theory

  • Ando, Shung-Ichi
    • Journal of the Korean Physical Society
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    • v.73 no.10
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    • pp.1452-1457
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    • 2018
  • Inclusion of the ground state of $^{16}O$ is investigated for a study of elastic ${\alpha}-^{12}C$ scattering for the l = 0 channel at low energies in effective field theory. We employ a Markov chain Monte Carlo method for the parameter fitting and find that the uncertainties of the fitted parameters are significantly improved compared to those of our previous study. We then calculate the asymptotic normalization constants of the $0^+$ states of $^{16}O$ and compare them with the experimental data and the previous theoretical estimates. We discuss implications of the results of the present work.

Artificial Neural Network-based Thermal Environment Prediction Model for Energy Saving of Data Center Cooling Systems (데이터센터 냉각 시스템의 에너지 절약을 위한 인공신경망 기반 열환경 예측 모델)

  • Chae-Young Lim;Chae-Eun Yeo;Seong-Yool Ahn;Sang-Hyun Lee
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.6
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    • pp.883-888
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    • 2023
  • Since data centers are places that provide IT services 24 hours a day, 365 days a year, data center power consumption is expected to increase to approximately 10% by 2030, and the introduction of high-density IT equipment will gradually increase. In order to ensure the stable operation of IT equipment, various types of research are required to conserve energy in cooling and improve energy management. This study proposes the following process for energy saving in data centers. We conducted CFD modeling of the data center, proposed an artificial intelligence-based thermal environment prediction model, compared actual measured data, the predicted model, and the CFD results, and finally evaluated the data center's thermal management performance. It can be seen that the predicted values of RCI, RTI, and PUE are also similar according to the normalization used in the normalization method. Therefore, it is judged that the algorithm proposed in this study can be applied and provided as a thermal environment prediction model applied to data centers.

On using the LPC parameter for Speaker Identification (LPC에 의한 화자 식별)

  • 조병모
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1987.11a
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    • pp.82-85
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    • 1987
  • Preliminary results of using the LPC parameter for text-independent speaker identification problem are presented. The idetification process includes log likelihood ratio for distance measure and dynamic programming for time normalization. To generate the data base for experiments, ten times. Experimental results show 99.4% of identification accuracy, incorrect identification were made when the speaker uses a dialect.

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Comparative Analysis of BP and SOM for Partial Discharge Pattern Recognition (부분방전 패턴인식에 대한 BP 및 SOM 알고리즘 비교 분석)

  • Lee, Ho-Keun;Kim, Jeong-Tae;Lim, Yoon-Seok;Kim, Ji-Hong;Koo, Ja-Yoon
    • Proceedings of the KIEE Conference
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    • 2004.07c
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    • pp.1930-1932
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    • 2004
  • SOM(Self Organizing Map) algorithm which has some advantages such as data accumulation ability and the degradation trend trace ability was compared with conventionally used BP(Back Propagation) algorithm. For the purpose, partial discharge data were acquired and analysed from the artificial defects in GIS. As a result, basically the pattern recognition rate of BP algorithm was found out to be better than that of SOM algorithm. However, SOM algorithm showed a great on-site-applicability such as ability of suggesting new-pattern-possibility. Therefore, through increasing pattern recognition rate it is possible to apply SOM algorithm to partial discharge analysis. Also, for the image processing method it is required the normalization of the PRPDA graph. However, due to the normalization both BP and SOM algorithm have shown worse results, so that it is required further study to solve the problem.

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Deep Learning Based 3D Gesture Recognition Using Spatio-Temporal Normalization (시 공간 정규화를 통한 딥 러닝 기반의 3D 제스처 인식)

  • Chae, Ji Hun;Gang, Su Myung;Kim, Hae Sung;Lee, Joon Jae
    • Journal of Korea Multimedia Society
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    • v.21 no.5
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    • pp.626-637
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    • 2018
  • Human exchanges information not only through words, but also through body gesture or hand gesture. And they can be used to build effective interfaces in mobile, virtual reality, and augmented reality. The past 2D gesture recognition research had information loss caused by projecting 3D information in 2D. Since the recognition of the gesture in 3D is higher than 2D space in terms of recognition range, the complexity of gesture recognition increases. In this paper, we proposed a real-time gesture recognition deep learning model and application in 3D space using deep learning technique. First, in order to recognize the gesture in the 3D space, the data collection is performed using the unity game engine to construct and acquire data. Second, input vector normalization for learning 3D gesture recognition model is processed based on deep learning. Thirdly, the SELU(Scaled Exponential Linear Unit) function is applied to the neural network's active function for faster learning and better recognition performance. The proposed system is expected to be applicable to various fields such as rehabilitation cares, game applications, and virtual reality.

Shape Recognition Using Skeleton Image Based on Mathematical Morphology (수리형태론적 스켈리턴 영상을 이용한 형상인식)

  • Jang, Ju-Seok;Son, Yun-Gu
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.4
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    • pp.883-898
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    • 1996
  • In this paper, we propose improved method to recognize the shape for enhancing the quality of the pattern recognition system by compressing the source images. In the proposed method, we reduced the data amount by skeletonizing the source images using mathematical morphology, and then matched patterns after accomplishing the translation and scale normalization, and rotation invariance on the transformed images. Through the scale normalization, it was possible for the shape recognition at minimum amount of the pixel by giving the weight to the skeleton pixel. As the source images was replaced by the skeleton images, it was possible to reduce the amount of data and computational loads dramatically, and so become much faster even with a smaller memory capacity. Through the experiment, we investigated the optimum scale factor and good result was proved when realizing the pattern recognition system.

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Computation for Deformation Modes of a Flexible Body in Multibody System using Experimental Modal Analysis (실험적 모드해석을 이용한 다물체계내 유연체의 변형보드 계산)

  • Kim, Hyo-Sig;Kim, Sang-Sup
    • Proceedings of the KSME Conference
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    • 2003.11a
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    • pp.1718-1723
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    • 2003
  • This paper presents a computational method for deformation modes of a flexible body in multibody system from the experimental modal analysis and an efficient method for flexible multibody dynamic analysis by use of the modes. It is difficult to directly use experimental modal parameters in flexible multibody dynamic analysis. The major reasons are that there are many inconsistencies between experimental and analytical modal data and experimental noises are inherent in the experimental data. So two methods, such as, a method for ortho-normalization of experimental modes and the other one for mode expansion, are suggested to gain deformation modes of a flexible body from the experimental modal parameters. Using the virtual work principle, the equation of motion of a flexible body is derived. The effectiveness of the proposed method will be verified in the numerical example of cab vibration of a truck by comparing analysis and test results.

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Parenting Experience of Parents with Chronically Ill Children (만성질환아동 부모의 부모되기 경험)

  • Park, Eun Sook;Lee, Kee Hyoung;Oh, Won Oak;Im, Yeo jin;Cho, Eun ji
    • Child Health Nursing Research
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    • v.21 no.3
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    • pp.272-284
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    • 2015
  • Purpose: The purpose of the study was to describe the parenting experience of parents of children with chronic illness in Korea. Methods: A conventional contents analysis was used for the study. Twelve mothers of chronically ill children participated in the study. Qualitative data were analyzed using the Morse and Field method. Results: Four categories, 10 subcategories and 42 codes emerged from the data on the parenting experience of parents of children with chronic illness. The four categories were 'Sacrifice and full-engagement within self-mortification', 'Re-normalization of collapsed daily life', 'Paving a new way for independence' and 'Growing together of myself and the family'. Conclusion: Parents of children with chronic illness experienced not only negative aspects such as a confusion but also re-normalization and growing together. Based on the results, health professionals need to develop effective nursing interventions toward positive parenting for these parents and their children with chronic illnesses.

Normalizing interval data and their use in AHP (구간데이터 정규화와 계층적 분석과정에의 활용)

  • Kim, Eun Young;Ahn, Byeong Seok
    • Journal of Intelligence and Information Systems
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    • v.22 no.2
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    • pp.1-11
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    • 2016
  • Entani and Tanaka (2007) presented a new approach for obtaining interval evaluations suitable for handling uncertain data. Above all, their approach is characterized by the normalization of interval data and thus the elimination of redundant bounds. Further, interval global weights in AHP are derived by using such normalized interval data. In this paper, we present a heuristic method for finding extreme points of interval data, which basically extends the method by Entani and Tanaka (2007), and also helps to obtain normalized interval data. In the second part of this paper, we show that the solutions to the linear program for interval global weights can be obtained by a simple inspection. In the meantime, the absolute dominance proposed by the authors is extended to pairwise dominance which makes it possible to identify at least more dominated alternatives under the same information.

Semantic Correspondence of Database Schema from Heterogeneous Databases using Self-Organizing Map

  • Dumlao, Menchita F.;Oh, Byung-Joo
    • Journal of IKEEE
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    • v.12 no.4
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    • pp.217-224
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    • 2008
  • This paper provides a framework for semantic correspondence of heterogeneous databases using self- organizing map. It solves the problem of overlapping between different databases due to their different schemas. Clustering technique using self-organizing maps (SOM) is tested and evaluated to assess its performance when using different kinds of data. Preprocessing of database is performed prior to clustering using edit distance algorithm, principal component analysis (PCA), and normalization function to identify the features necessary for clustering.

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