• Title/Summary/Keyword: 바람벡터

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A study on the robust speaker recognition algorithm in noise surroundings (주변 잡음 환경에 강한 화자인식 알고리즘 연구)

  • Jung Jong-Soon
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.6 s.38
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    • pp.47-54
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    • 2005
  • In the most of speaker recognition system, speaker's characteristics is extracted from acoustic parameter by speech analysis and we make speaker's reference pattern. Parameters used in speaker recognition system are desirable expressing speaker's characteristics fully and being a few difference whenever it is spoken. Therefore we su99est following to solve this problem. This paper is proposed to use strong spectrum characteristic in non-noise circumstance and prosodic information in noise circumstance. In a stage of making code book, we make the number of data we need to combine spectrum characteristic and Prosodic information. We decide acceptance or rejection comparing test pattern and each model distance. As a result, we obtained more improved recognition rate than we use spectrum and prosodic information especially we obtained stational recognition rate in noise circumstance.

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A 4 kbps PSI-VSELP Speech Coding Algorithm (4 kbps PSI-VSELP 음성 부호화 알고리듬)

  • Choi, Yong-Soo;Kang, Hong-Goo;Park, Sang-Wook;Youn, Dae-Hee
    • The Journal of the Acoustical Society of Korea
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    • v.15 no.6
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    • pp.59-65
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    • 1996
  • This paper proposes a 4 kbps PSI-VSELP(Pitch Synchronous Innovation-Vector Sum Excited Linear Prediction) speech coder which produces speech equivalent to that of the conventional 4.8 kbps VSELP. Since the 'half-rate' is differently defined from country to country, there may be a need to reduce the bit rate of conventional half-rate coder. To minimize the degradation of speech quality caused by bit-rate reduction, it is desirable to perform bit-allocation based on the carefull consideration of the effect of various transmission parameters. This paper adopts this analytical approach for bit-allocation at 4 kbps. To improve the quality of the VSELP coder at 4 kbps, basis vectors which play the most important role in the performance, are optimized by an iterative closed-loop training process and the PSI technique is employed in the VSELP performance, are optimized by an iterative closed-loop training process and the PSI technique is employed in the VSELP coder. To demonstrate the performance of the proposed speech coder, we peformed experiments under the noiseless and error free conditions. From experimental results, even though the proposed 4 kbps PSI-VSELP coder showed lower scores in the objective measure, higher scores in subjective measure was obtained compared with those of the conventional 4.8 kbps VSELp.

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Improving the Performance of Document Clustering with Distributional Similarities (분포유사도를 이용한 문헌클러스터링의 성능향상에 대한 연구)

  • Lee, Jae-Yun
    • Journal of the Korean Society for information Management
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    • v.24 no.4
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    • pp.267-283
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    • 2007
  • In this study, measures of distributional similarity such as KL-divergence are applied to cluster documents instead of traditional cosine measure, which is the most prevalent vector similarity measure for document clustering. Three variations of KL-divergence are investigated; Jansen-Shannon divergence, symmetric skew divergence, and minimum skew divergence. In order to verify the contribution of distributional similarities to document clustering, two experiments are designed and carried out on three test collections. In the first experiment the clustering performances of the three divergence measures are compared to that of cosine measure. The result showed that minimum skew divergence outperformed the other divergence measures as well as cosine measure. In the second experiment second-order distributional similarities are calculated with Pearson correlation coefficient from the first-order similarity matrixes. From the result of the second experiment, secondorder distributional similarities were found to improve the overall performance of document clustering. These results suggest that minimum skew divergence must be selected as document vector similarity measure when considering both time and accuracy, and second-order similarity is a good choice for considering clustering accuracy only.

Performance Comparison of Machine Learning Based on Neural Networks and Statistical Methods for Prediction of Drifter Movement (뜰개 이동 예측을 위한 신경망 및 통계 기반 기계학습 기법의 성능 비교)

  • Lee, Chan-Jae;Kim, Gyoung-Do;Kim, Yong-Hyuk
    • Journal of the Korea Convergence Society
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    • v.8 no.10
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    • pp.45-52
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    • 2017
  • Drifter is an equipment for observing the characteristics of seawater in the ocean, and it can be used to predict effluent oil diffusion and to observe ocean currents. In this paper, we design models or the prediction of drifter trajectory using machine learning. We propose methods for estimating the trajectory of drifter using support vector regression, radial basis function network, Gaussian process, multilayer perceptron, and recurrent neural network. When the propose mothods were compared with the existing MOHID numerical model, performance was improve on three of the four cases. In particular, LSTM, the best performed method, showed the imporvement by 47.59% Future work will improve the accuracy by weighting using bagging and boosting.

A Survey on Oil Spill and Weather Forecast Using Machine Learning Based on Neural Networks and Statistical Methods (신경망 및 통계 기법 기반의 기계학습을 이용한 유류유출 및 기상 예측 연구 동향)

  • Kim, Gyoung-Do;Kim, Yong-Hyuk
    • Journal of the Korea Convergence Society
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    • v.8 no.10
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    • pp.1-8
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    • 2017
  • Accurate forecasting enables to effectively prepare for future phenomenon. Especially, meteorological phenomenon is closely related with human life, and it can prevent from damage such as human life and property through forecasting of weather and disaster that can occur. To respond quickly and effectively to oil spill accidents, it is important to accurately predict the movement of oil spills and the weather in the surrounding waters. In this paper, we selected four representative machine learning techniques: support vector machine, Gaussian process, multilayer perceptron, and radial basis function network that have shown good performance and predictability in the previous studies related to oil spill detection and prediction in meteorology such as wind, rainfall and ozone. we suggest the applicability of oil spill prediction model based on machine learning.

Development of Load-Cell-Based Anemovane (로드셀형 풍향풍속계 개발)

  • Jeon, Byeong Ha;Han, Dong Seop;Lee, Kwon-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.37 no.5
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    • pp.685-691
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    • 2013
  • A load-cell-type anemovane operates based on wind vector properties. The developed load-cell-type anemovane is of a fixed type in which the wing does not rotate, unlike in the case of existing anemovanes. The load-cell-type anemovane is required to accurately derive the correlation between the load ratio and the wind direction in order to develop a qualified product. This is because the load ratio repeats every $90^{\circ}$ owing to the use of four load cells, and its value varies nonlinearly according to the wind direction. In this study, we compared analytical results with experimental results. Fluid analysis was carried out using ANSYS CFX. Furthermore, the prototype was tested using a self-manufactured wind tunnel. The wind direction was selected as the design variable. 13 selected wind direction conditions ranging from $0^{\circ}$ to $90^{\circ}$ with an interval of $7.5^{\circ}$ for analysis were defined. Furthermore, 10 wind direction conditions with an interval of $10^{\circ}$ for the experiment were defined. We derived the relations between the pressure ratio and the wind direction through the experiment and fluid analysis.

Establishment and characterization of porcine mammary gland epithelial cell line using three dimensional culture system (3차원 배양 시스템을 이용한 돼지 유선 상피 세포 주 특성과 설정)

  • Chung, Hak-Jae
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.10
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    • pp.551-558
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    • 2017
  • To study and validate tissue-specific promoters and vectors, it is important to develop cell culture systems that retain the tissue and species specificity. Such systems are attractive alternatives to transgenic animal models. This study established a line of porcine mammary gland epithelial cells (PMECs) from a primary culture based on the cellular morphology and mRNA levels of porcine beta-casein (CSN2). The selected PMECs were stained with the cytokeratin antibody, and were shown to express milk protein genes (CSN2, lactoferrin, and whey acidic protein). In addition, to confirm the acini structure of PMEC932-7 in 3D culture, live cells were stained with SYTO-13 dye, which binds to nucleic acid. The acini of these PMECs on matrigel were formed by the aggregation of peripheral cells and featured a hollow lumens. The system was demonstrated by testing the effects of the culture conditions to cell culture including cell density and matrigel methods of the PMECs. These results suggest that PMECs possess the genetic and structural features of mammary epithelial cells.

Methods for Swing Recognition and Shuttle Cock's Trajectory Calculation in a Tangible Badminton Game (체감형 배드민턴 게임을 위한 스윙 인식과 셔틀콕 궤적 계산 방법)

  • Kim, Sangchul
    • Journal of Korea Game Society
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    • v.14 no.2
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    • pp.67-76
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    • 2014
  • Recently there have been many interests on tangible sport games that can recognize the motions of players. In this paper, we propose essential technologies required for tangible games, which are methods for swing motion recognition and the calculation of shuttle cock's trajectory. When a user carries out a badminton swing while holding a smartphone with his hand, the motion signal generated by smartphone-embedded acceleration sensors is transformed into a feature vector through a Daubechies filter, and then its swing type is recognized using a k-NN based method. The method for swing motion presented herein provides an advantage in a way that a player can enjoy tangible games without purchasing a commercial motion controller. Since a badminton shuttle cock has a particular flight trajectory due to the nature of its shape, it is not easy to calculate the trajectory of the shuttle cock using simple physics rules about force and velocity. In this paper, we propose a method for calculating the flight trajectory of a badminton shuttle cock in which the wind effect is considered.

A Warning and Forecasting System for Storm Surge in Masan Bay (마산만 국지해일 예경보 모의 시스템 구축)

  • Han, Sung-Dae;Lee, Jung-Lyul
    • Journal of the Korean Society of Hazard Mitigation
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    • v.9 no.5
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    • pp.131-138
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    • 2009
  • In this paper, a dynamic warning system to forecast inland flooding associated with typhoons and storms is described. The system is used operationally during the typhoon season to anticipate the potential impact such as inland flooding on the coastal zone of interest. The system has been developed for the use of the public and emergency management officials. Simple typhoon models for quick prediction of wind fields are implemented in a user-friendly way by using a Graphical User Interface (GUI) of MATLAB. The main program for simulating tides, depth-averaged tidal currents, wind-driven surges and currents was also vectorized for the fast performance by MATLAB. By pushing buttons and clicking the typhoon paths, the user is able to obtain real-time water level fluctuation of specific points and the flooding zone. This system would guide local officials to make systematic use of threat information possible. However, the model results are sensitive to typhoon path, and it is yet difficult to provide accurate information to local emergency managers.

Development of Geometric Moments Based Ellipsoid Model for Extracting Spatio-Temporal Characteristics of Rainfall Field (강우장의 시공간적 특성 추출을 위한 기하학적 모멘트 기반 등가타원 모형 개발)

  • Kwon, Hyun-Han;So, Byung-Jin;Kim, Min-Ji;Pack, Se-Hoon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.31 no.6B
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    • pp.531-539
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    • 2011
  • It has been widely acknowledged that climate system associated with extreme rainfall events was difficult to understand and extreme rainfall simulation in climate model was more difficult. This study developed a new model for extracting rainfall filed associated with extreme events as a way to characterize large scale climate system. Main interests are to derive location, size and direction of the rainfall field and this study developed an algorithm to extract the above characteristics from global climate data set. This study mainly utilized specific humidity and wind vectors driven by NCEP reanalysis data to define the rainfall field. Geometric first and second moments have been extensively employed in defining the rainfall field in selected zone, and an ellipsoid based model were finally introduced. The proposed geometric moments based ellipsoid model works equally well with regularly and irregularly distributed synthetic grid data. Finally, the proposed model was applied to space-time real rainfall filed. It was found that location, size and direction of the rainfall field was successfully extracted.