• Title/Summary/Keyword: Non-Linear Algorithm

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Adaptive Threshold for Speech Enhancement in Nonstationary Noisy Environments (비정상 잡음환경에서 음질향상을 위한 적응 임계 치 알고리즘)

  • Lee, Soo-Jeong;Kim, Sun-Hyob
    • The Journal of the Acoustical Society of Korea
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    • v.27 no.7
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    • pp.386-393
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    • 2008
  • This paper proposes a new approach for speech enhancement in highly nonstationary noisy environments. The spectral subtraction (SS) is a well known technique for speech enhancement in stationary noisy environments. However, in real world, noise is mostly nonstationary. The proposed method uses an auto control parameter for an adaptive threshold to work well in highly nonstationary noisy environments. Especially, the auto control parameter is affected by a linear function associated with an a posteriori signal to noise ratio (SNR) according to the increase or the decrease of the noise level. The proposed algorithm is combined with spectral subtraction (SS) using a hangover scheme (HO) for speech enhancement. The performances of the proposed method are evaluated ITU-T P.835 signal distortion (SIG) and the segment signal to-noise ratio (SNR) in various and highly nonstationary noisy environments and is superior to that of conventional spectral subtraction (SS) using a hangover (HO) and SS using a minimum statistics (MS) methods.

A Basic Study on the Differential Diagnostic System of Laryngeal Diseases using Hierarchical Neural Networks (다단계 신경회로망을 이용한 후두질환 감별진단 시스템의 개발)

  • 전계록;김기련;권순복;예수영;이승진;왕수건
    • Journal of Biomedical Engineering Research
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    • v.23 no.3
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    • pp.197-205
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    • 2002
  • The objectives of this Paper is to implement a diagnostic classifier of differential laryngeal diseases from acoustic signals acquired in a noisy room. For this Purpose, the voice signals of the vowel /a/ were collected from Patients in a soundproof chamber and got mixed with noise. Then, the acoustic Parameters were analyzed, and hierarchical neural networks were applied to the data classification. The classifier had a structure of five-step hierarchical neural networks. The first neural network classified the group into normal and benign or malign laryngeal disease cases. The second network classified the group into normal or benign laryngeal disease cases The following network distinguished polyp. nodule. Palsy from the benign laryngeal cases. Glottic cancer cases were discriminated into T1, T2. T3, T4 by the fourth and fifth networks All the neural networks were based on multilayer perceptron model which classified non-linear Patterns effectively and learned by an error back-propagation algorithm. We chose some acoustic Parameters for classification by investigating the distribution of laryngeal diseases and Pilot classification results of those Parameters derived from MDVP. The classifier was tested by using the chosen parameters to find the optimum ones. Then the networks were improved by including such Pre-Processing steps as linear and z-score transformation. Results showed that 90% of T1, 100% of T2-4 were correctly distinguished. On the other hand. 88.23% of vocal Polyps, 100% of normal cases. vocal nodules. and vocal cord Paralysis were classified from the data collected in a noisy room.

Development of FURA Code and Application for Load Follow Operation (FURA 코드 개발과 부하 추종 운전에 대한 적용)

  • Park, Young-Seob;Lee, Byong-Whi
    • Nuclear Engineering and Technology
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    • v.20 no.2
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    • pp.88-104
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    • 1988
  • The FUel Rod Analysis(FURA) code is developed using two-dimensional finite element methods for axisymmetric and plane stress analysis of fuel rod. It predicts the thermal and mechanical behavior of fuel rod during normal and load follow operations. To evaluate the exact temperature distribution and the inner gas pressure, the radial deformation of pellet and clad, the fission gas release are considered over the full-length of fuel rod. The thermal element equation is derived using Galerkin's techniques. The displacement element equation is derived using the principle of virtual works. The mechanical analysis can accommodate various components of strain: elastic, plastic, creep and thermal strain as well as strain due to swelling, relocation and densification. The 4-node quadratic isoparametric elements are adopted, and the geometric model is confined to a half-pellet-height region with the assumption that pellet-pellet interaction is symmetrical. The pellet cracking and crack healing, pellet-cladding interaction are modelled. The Newton-Raphson iteration with an implicit algorithm is applied to perform the analysis of non-linear material behavior accurately and stably. The pellet and cladding model has been compared with both analytical solutions and experimental results. The observed and predicted results are in good agreement. The general behavior of fuel rod is calculated by axisymmetric system and the cladding behavior against radial crack is used by plane stress system. The sensitivity of strain aging of PWR fuel cladding tube due to load following is evaluated in terms of linear power, load cycle frequency and amplitude.

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Development of an Image Processing Algorithm for Paprika Recognition and Coordinate Information Acquisition using Stereo Vision (스테레오 영상을 이용한 파프리카 인식 및 좌표 정보 획득 영상처리 알고리즘 개발)

  • Hwa, Ji-Ho;Song, Eui-Han;Lee, Min-Young;Lee, Bong-Ki;Lee, Dae-Weon
    • Journal of Bio-Environment Control
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    • v.24 no.3
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    • pp.210-216
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    • 2015
  • Purpose of this study was a development of an image processing algorithm to recognize paprika and acquire it's 3D coordinates from stereo images to precisely control an end-effector of a paprika auto harvester. First, H and S threshold was set using HSI histogram analyze for extracting ROI(region of interest) from raw paprika cultivation images. Next, fundamental matrix of a stereo camera system was calculated to process matching between extracted ROI of corresponding images. Epipolar lines were acquired using F matrix, and $11{\times}11$ mask was used to compare pixels on the line. Distance between extracted corresponding points were calibrated using 3D coordinates of a calibration board. Non linear regression analyze was used to prove relation between each pixel disparity of corresponding points and depth(Z). Finally, the program could calculate horizontal(X), vertical(Y) directional coordinates using stereo camera's geometry. Horizontal directional coordinate's average error was 5.3mm, vertical was 18.8mm, depth was 5.4mm. Most of the error was occurred at 400~450mm of depth and distorted regions of image.

P Wave Detection Algorithm through Adaptive Threshold and QRS Peak Variability (적응형 문턱치와 QRS피크 변화에 따른 P파 검출 알고리즘)

  • Cho, Ik-sung;Kim, Joo-Man;Lee, Wan-Jik;Kwon, Hyeog-soong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.8
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    • pp.1587-1595
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    • 2016
  • P wave is cardiac parameters that represent the electrical and physiological characteristics, it is very important to diagnose atrial arrhythmia. However, It is very difficult to detect because of the small size compared to R wave and the various morphology. Several methods for detecting P wave has been proposed, such as frequency analysis and non-linear approach. However, in the case of conduction abnormality such as AV block or atrial arrhythmia, detection accuracy is at the lower level. We propose P wave detection algorithm through adaptive threshold and QRS peak variability. For this purpose, we detected Q, R, S wave from noise-free ECG signal through the preprocessing method. And then we classified three pattern of P wave by peak variability and detected adaptive window and threshold. The performance of P wave detection is evaluated by using 48 record of MIT-BIH arrhythmia database. The achieved scores indicate the average detection rate of 92.60%.

Member Sizing Optimization for Seismic Design of the Inverted V-braced Steel Frames with Suspended Zipper Strut (Zipper를 가진 역V형 가새골조의 다목적 최적내진설계기법)

  • Oh, Byung-Kwan;Park, Hyo-Seon;Choi, Se-Woon
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.29 no.6
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    • pp.555-562
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    • 2016
  • Seismic design of braced frames that simultaneously considers economic issues and structural performance represents a rather complicated engineering problem, and therefore, a systematic and well-established methodology is needed. This study proposes a multi-objective seismic design method for an inverted V-braced frame with suspended zipper struts that uses the non-dominated sorting genetic algorithm-II(NSGA-II). The structural weight and the maximum inter-story drift ratio as the objective functions are simultaneously minimized to optimize the cost and seismic performance of the structure. To investigate which of strength- and performance-based design criteria for braced frames is the critical design condition, the constraint conditions on the two design methods are simultaneously considered (i.e. the constraint conditions based on the strength and plastic deformation of members). The linear static analysis method and the nonlinear static analysis method are adopted to check the strength- and plastic deformation-based design constraints, respectively. The proposed optimal method are applied to three- and six-story steel frame examples, and the solutions improved for the considered objective functions were found.

Rainfall Forecasting Using Satellite Information and Integrated Flood Runoff and Inundation Analysis (I): Theory and Development of Model (위성정보에 의한 강우예측과 홍수유출 및 범람 연계 해석 (I): 이론 및 모형의 개발)

  • Choi, Hyuk Joon;Han, Kun Yeun;Kim, Gwangseob
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.6B
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    • pp.597-603
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    • 2006
  • The purpose of this study is to improve the short term rainfall forecast skill using neural network model that can deal with the non-linear behavior between satellite data and ground observation, and minimize the flood damage. To overcome the geographical limitation of Korean peninsula and get the long forecast lead time of 3 to 6 hour, the developed rainfall forecast model took satellite imageries and wide range AWS data. The architecture of neural network model is a multi-layer neural network which consists of one input layer, one hidden layer, and one output layer. Neural network is trained using a momentum back propagation algorithm. Flood was estimated using rainfall forecasts. We developed a dynamic flood inundation model which is associated with 1-dimensional flood routing model. Therefore the model can forecast flood aspect in a protected lowland by levee failure of river. In the case of multiple levee breaks at main stream and tributaries, the developed flood inundation model can estimate flood level in a river and inundation level and area in a protected lowland simultaneously.

Active Stabilization for Surge Motion of Moored Vessel in Irregular Head Waves (불규칙 선수파랑 중 계류된 선박의 전후동요 제어)

  • Lee, Sang-Do;Truong, Ngoc Cuong;Xu, Xiao;You, Sam-Sang
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.26 no.5
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    • pp.437-444
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    • 2020
  • This study was focused on the stabilization of surge motions of a moored vessel under irregular head seas. A two-point moored vessel shows strong non-linearity even in regular sea, owing to its inherent non-linear restoring force. A long-crested irregular wave is subjected to the vessel system, resulting in more complex nonlinear behavior of the displacement and velocities than in the case of regular waves. Sliding mode control (SMC) is implemented in the moored vessel to control both surge displacement and surge velocity. The SMC can provide a closed-loop system with performance and robustness against parameter uncertainties and disturbances; however, chattering is the main drawback for implementing SMC. The goal of minimizing the chattering and state convergence with accuracy is achieved using a quasi-sliding mode that approximates the discontinuous function via a continuous sigmoid function. Numerical simulations were conducted to validate the effectiveness of the proposed control algorithm.

Fast Detection of Power Lines Using LIDAR for Flight Obstacle Avoidance and Its Applicability Analysis (비행장애물 회피를 위한 라이다 기반 송전선 고속탐지 및 적용가능성 분석)

  • Lee, Mijin;Lee, Impyeong
    • Spatial Information Research
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    • v.22 no.1
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    • pp.75-84
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    • 2014
  • Power lines are one of the main obstacles causing an aircraft crash and thus their realtime detection is significantly important during flight. To avoid such flight obstacles, the use of LIDAR has been recently increasing thanks to its advantages that it is less sensitive to weather conditions and can operate in day and night. In this study, we suggest a fast method to detect power lines from LIDAR data for flight obstacle avoidance. The proposed method first extracts non-ground points by eliminating the points reflected from ground surfaces using a filtering process. Second, we calculate the eigenvalues for the covariance matrix from the coordinates of the generated non-ground points and obtain the ratio of eigenvalues. Based on the ratio of eigenvalues, we can classify the points on a linear structure. Finally, among them, we select the points forming horizontally long straight as power-line points. To verify the algorithm, we used both real and simulated data as the input data. From the experimental results, it is shown that the average detection rate and time are 80% and 0.2 second, respectively. If we would improve the method based on the experiment results from the various flight scenario, it will be effectively utilized for a flight obstacle avoidance system.

Effect of Inhomogeneity correction for lung volume model in TPS (Lnug Volume을 모델로 한 방사선치료계획 시 불균질 조직 보정에 따른 효과)

  • Chung SeYoung;Lee SangRok;Kim YoungBum;Kwon YoungHo
    • The Journal of Korean Society for Radiation Therapy
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    • v.16 no.1
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    • pp.57-65
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    • 2004
  • Introduction : The phantom that includes high density materials such as steel was custom-made to fix lung and bone in order to evaluation inhomogeneity correction at the time of conducting radiation therapy to treat lung cancer. Using this, values resulting from the inhomogeneous correction algorithm are compared on the 2 and 3 dimensional radiation therapy planning systems. Moreover, change in dose calculation was evaluated according to inhomogeneous by comparing with the actual measurement. Materials and Methods : As for the image acquisition, inhomogeneous correction phantom(Pig's vertebra, steel(8.21g/cm3), cork(0.23 g/cm3)) that was custom-made and the CT(Volume zoom, Siemens, Germany) were used. As for the radiation therapy planning system, Marks Plan(2D) and XiO(CMS, USA, 3D) were used. To compare with the measurement value, linear accelerator(CL/1800, Varian, USA) and ion chamber were used. Image, obtained from the CT was used to obtain point dose and dose distribution from the region of interest (ROI) while on the radiation therapy planning device. After measurement was conducted under the same conditions, value on the treatment planning device and measured value were subjected to comparison and analysis. And difference between the resulting for the evaluation on the use (or non-use) of inhomogeneity correction algorithm, and diverse inhomogeneity correction algorithm that is included in the radiation therapy planning device was compared as well. Results : As result of comparing the results of measurement value on the region of interest within the inhomogeneity correction phantom and the value that resulted from the homogeneous and inhomogeneous correction, gained from the therapy planning device, margin of error of the measurement value and inhomogeneous correction value at the location 1 of the lung showed $0.8\%$ on 2D and $0.5\%$ on 3D. Margin of error of the measurement value and inhomogeneous correction value at the location 1 of the steel showed $12\%$ on 2D and $5\%$ on 3D, however, it is possible to see that the value that is not correction and the margin of error of the measurement value stand at $16\%$ and $14\%$, respectively. Moreover, values of the 3D showed lower margin of error compared to 2D. Conclusion : Revision according to the density of tissue must be executed during radiation therapy planning. To ensure a more accurate planning, use of 3D planning system is recommended more so than the 2D Planning system to ensure a more accurate revision on the therapy plan. Moreover, 3D Planning system needs to select and use the most accurate and appropriate inhomogeneous correction algorithm through actual measurement. In addition, comparison and analysis through TLD or film dosimetry are needed.

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