scholarly journals Efficient methods for macroscopic magnetization simulation described by the assembly of simplified domain structure models

2015 ◽  
Vol 4 (1) ◽  
pp. 16 ◽  
Author(s):  
T. Matsuo ◽  
T. Nakamura ◽  
S. Ito ◽  
T. Mifune ◽  
C. Kaido
Keyword(s):  
Equilibrium Point ◽  
Domain Structure ◽  
Efficient Method ◽  
Computation Time ◽  
Structure Model ◽  
Fast Computation ◽  
Demagnetizing Field ◽  
Searching Method

This article presents two methods for the fast computation of macroscopic magnetization model called assembled domain structure model. First, an efficient method for computing the demagnetizing field is proposed. Secondly, a direct searching method of equilibrium point is developed, which greatly reduces the computation time.

scholarly journals The four-domain structure model of a depression scale for medical students: A cross-sectional study in Haiphong, Vietnam

PLoS ONE ◽  
2018 ◽  
Vol 13 (3) ◽  
pp. e0194550 ◽  
Author(s):  
Thao Thi Thu Nguyen ◽  
Ngoc Thi Minh Nguyen ◽  
Manh Van Pham ◽  
Han Van Pham ◽  
Hiroyuki Nakamura
Keyword(s):  
Medical Students ◽  
Domain Structure ◽  
Depression Scale ◽  
Cross Sectional Study ◽  
Structure Model ◽  
Sectional Study ◽  
Cross Sectional

scholarly journals Partially Implicit Method for Fast Magnetization Analysis Using Assembled Domain Structure Model

2017 ◽  
Vol 53 (6) ◽  
pp. 1-4 ◽  
Author(s):  
Shogo Tejima ◽  
Shumpei Ito ◽  
Takeshi Mifune ◽  
Tetsuji Matsuo ◽  
Tomoo Nakai
Keyword(s):  
Domain Structure ◽  
Implicit Method ◽  
Structure Model

Surface domain structure and local demagnetizing field in NdFeB permanent magnets

1994 ◽  
Vol 142 (1) ◽  
pp. K41-K45 ◽  
Author(s):  
Yu. G. Pastushenkov ◽  
L. E. Afanasieva ◽  
R. M. Grechishkin
Keyword(s):  
Domain Structure ◽  
Permanent Magnets ◽  
Demagnetizing Field

scholarly journals Visual MAV Tracker with Adaptive Search Region

2021 ◽  
Vol 11 (16) ◽  
pp. 7741
Author(s):  
Wooryong Park ◽  
Donghee Lee ◽  
Junhak Yi ◽  
Woochul Nam
Keyword(s):  
Real Time ◽  
Computation Time ◽  
Adaptive Strategy ◽  
Adaptive Search ◽  
Fast Computation ◽  
Search Region ◽  
Micro Aerial Vehicle ◽  
Aerial Vehicle ◽  
Online Tracking ◽  
Computation Speed

Tracking a micro aerial vehicle (MAV) is challenging because of its small size and swift motion. A new model was developed by combining compact and adaptive search region (SR). The model can accurately and robustly track MAVs with a fast computation speed. A compact SR, which is slightly larger than a target MAV, is less likely to include a distracting background than a large SR; thus, it can accurately track the MAV. Moreover, the compact SR reduces the computation time because tracking can be conducted with a relatively shallow network. An optimal SR to MAV size ratio was obtained in this study. However, this optimal compact SR causes frequent tracking failures in the presence of the dynamic MAV motion. An adaptive SR is proposed to address this problem; it adaptively changes the location and size of the SR based on the size, location, and velocity of the MAV in the SR. The compact SR without adaptive strategy tracks the MAV with an accuracy of 0.613 and a robustness of 0.086, whereas the compact and adaptive SR has an accuracy of 0.811 and a robustness of 1.0. Moreover, online tracking is accomplished within approximately 400 frames per second, which is significantly faster than the real-time speed.

Numerical Solution of the Stefan's Problem

2015 ◽  
Vol 1 (3) ◽  
pp. 164-175 ◽  
Author(s):  
Stanislav Borodin
Keyword(s):  
Numerical Methods ◽  
Efficient Method ◽  
Computation Time ◽  
Oscillating Solution ◽  
Implicit Scheme ◽  
Advantages And Disadvantages ◽  
Symmetric Scheme ◽  
Computational Speed ◽  
Ice Water ◽  
The Mathematical Model

All of the most well-known numerical methods for solving the Stefan’s problem, as well as a new method developed by the author are considered for the purpose of choosing the most efficient of them from a perspective of accuracy and computational speed. A comparison is carried out on the results of solving the problem for the boundary motion of “ice-water” phase transition around the vertical well passing through the thickness of permafrost. The conclusions, which are distributed to other multidimensional and multi-front statements of the Stefan’s problem, are made. The mathematical model, the brief description of the considered numerical methods and the boundaries of their applicability are presented. The comparison shows the advantages and disadvantages of different methods. It is demonstrated that the use of the explicit scheme leads to a marked increase in computation time, the six-point symmetric scheme may have oscillating solution; therefore, the implicit scheme is the most preferred. It is concluded that the most efficient method for one-dimensional and one front Stefan’s problems is the method of catching the front in the grid node using the implicit scheme, and the most efficient method for multi-dimensional and multi-front Stefan’s problems is the enthalpy method using the implicit scheme, which has been developed by the author.

scholarly journals Fast Computation of LSP Frequencies Using the Bairstow Method

Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 387 ◽  
Author(s):  
Yuqun Xue ◽  
Zhijiu Zhu ◽  
Jianhua Jiang ◽  
Yi Zhan ◽  
Zenghui Yu ◽  
...  
Keyword(s):  
Speech Processing ◽  
Linear Prediction ◽  
Predictive Coding ◽  
Computation Time ◽  
Fast Computation ◽  
Linear Predictive Coding ◽  
Polynomial Roots ◽  
Alternative Representation ◽  
Perceptual Evaluation ◽  
Initial Method

Linear prediction is the kernel technology in speech processing. It has been widely applied in speech recognition, synthesis, and coding, and can efficiently and correctly represent the speech frequency spectrum with only a few parameters. Line Spectrum Pairs (LSPs) frequencies, as an alternative representation of Linear Predictive Coding (LPC), have the advantages of good quantization accuracy and low spectral sensitivity. However, computing the LSPs frequencies takes a long time. To address this issue, a fast computation algorithm, based on the Bairstow method for computing LSPs frequencies from linear prediction coefficients, is proposed in this paper. The algorithm process first transforms the symmetric and antisymmetric polynomial to general polynomial, then extracts the polynomial roots. Associated with the short-term stationary property of speech signal, an adaptive initial method is applied to reduce the average iteration numbers by 26%, as compared to the statics in the initial method, with a Perceptual Evaluation of Speech Quality (PESQ) score reaching 3.46. Experimental results show that the proposed method can extract the polynomial roots efficiently and accurately with significantly reduced computation complexity. Compared to previous works, the proposed method is 17 times faster than Tschirnhus Transform, and has a 22% PESQ improvement on the Birge-Vieta method with an almost comparable computation time.

scholarly journals Improved Distorted Configuration Space Path Planning and Its Application to Robot Manipulators

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6060
Author(s):  
Yangmin Xie ◽  
Rui Zhou ◽  
Yusheng Yang
Keyword(s):  
Path Planning ◽  
Configuration Space ◽  
Path Length ◽  
Robot Manipulators ◽  
Computational Cost ◽  
Computation Time ◽  
Planning Strategy ◽  
Automatic Planning ◽  
Searching Method ◽  
Space Method

Real-time obstacle avoidance path planning is critically important for a robot when it operates in a crowded or cluttered workspace. At the same time, the computational cost is a big concern once the degree of freedom (DOF) of a robot is high. A novel path planning strategy, the distorted configuration space (DC-space) method, was proposed and proven to outperform the traditional search-based methods in terms of computational efficiency. However, the original DC-space method did not sufficiently consider the demands on automatic planning, convex space preservation, and path optimization, which makes it not practical when applied to the path planning for robot manipulators. The treatments for the problems mentioned above are proposed in this paper, and their applicability is examined on a three DOFs robot. The experiments demonstrate the effectiveness of the proposed improved distorted configuration space (IDCS) method on rapidly finding an obstacle-free path. Besides, the optimized IDCS method is presented to shorten the generated path. The performance of the above algorithms is compared with the classic Rapidly-exploring Random Tree (RRT) searching method in terms of their computation time and path length.

AN EFFICIENT METHOD FOR IMPROVING THE COMPUTATIONAL PERFORMANCE OF THE CUBIC LUCAS CRYPTOSYSTEM

2014 ◽  
Vol 90 (1) ◽  
pp. 160-171
Author(s):  
REZA NAGHIZADEH MAJID ◽  
ELANKOVAN SUNDARARAJAN ◽  
ZULKARNAIN MD ALI
Keyword(s):  
Experimental Data ◽  
Recurrence Relation ◽  
Efficient Method ◽  
Mathematical Analysis ◽  
Computation Time ◽  
Rsa Cryptosystem ◽  
Computational Performance ◽  
Encryption And Decryption ◽  
Mathematical Techniques ◽  
Set Up

AbstractThe cubic version of the Lucas cryptosystem is set up based on the cubic recurrence relation of the Lucas function by Said and Loxton [‘A cubic analogue of the RSA cryptosystem’, Bull. Aust. Math. Soc.68 (2003), 21–38]. To implement this type of cryptosystem in a limited environment, it is necessary to accelerate encryption and decryption procedures. Therefore, this paper concentrates on improving the computation time of encryption and decryption in cubic Lucas cryptosystems. The new algorithm is designed based on new properties of the cubic Lucas function and mathematical techniques. To illustrate the efficiency of our algorithm, an analysis was carried out with different size parameters and the performance of the proposed and previously existing algorithms was evaluated with experimental data and mathematical analysis.

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