Influence of Skewing Design for Reduction of Force Ripples in DSL-SynRM using 3D FEA

Double Sided Linear Synchronous Reluctance Motors(DSL-SynRM)are being increasingly used in high force density applications.The force ripples are one of the major issue in machine which is due to nonlinear nature of current in the machines.This paper focuses on the reduction of force ripples for increasing the force density of the motor.In order to reduce the force ripples,DSL-SynRM with a skewed translator is proposed.The proposed structure is designed and developed by using computational magnetic tools.This concept is effective for reduction of the force ripples and improves the force density of the machine.The proposed design has been reduced the percentage of force ripples by 21.62%,improved the force density by 10.32 N/mm³and efficiency by 0.89%.

Analysis and evaluation of electromagnetic vibration and noise in permanent magnet synchronous motor with rotor step skewing

In this paper, a multi-physics simulation model capable of electromagnetic noise prediction is established, and the effectiveness of the established simulation model in predicting and evaluating electromagnetic noise is verified. Based on the verified motor model, a rotor step skewing model which can affect electromagnetic noise is proposed, and the influence of the skewing angle on electromagnetic noise is investigated in detail. By studying the spectral characteristics of the low-order radial magnetic force which has a great influence on electromagnetic noise, the distribution of electromagnetic noise characteristics of the permanent magnet synchronous motor(PMSM) with or without the rotor step skewing is compared and analyzed. Therefore, it lays a technological foundation for predicting and suppressing the electromagnetic vibration noise of electric vehicle(EV) driving motor in the electromagnetic design.

Sliding mode control design for oblique wing aircraft in wing skewing process

When the wing of Oblique Wing Aircraft(OWA) is skewed, the center of gravity, inertia and aerodynamic characteristics of the aircraft all significantly change, causing an undesirable flight dynamic response, affecting the flying qualities, and even endangering the flight safety. In this study,the dynamic response of an OWA in the wing skewing process is simulated, showing that the threeaxis movements of the OWA are highly coupled and present nonlinear characteristics during the wing skewing. As the roll control efficiency of the aileron decreases due to the shortened control arm in an oblique configuration, the all-moving horizontal tail is used for additional roll and the control allocation is performed based on minimum control energy. Given the properties of pitchroll-yaw coupling and control input and state coupling, and the difficulty of establishing an accurate aerodynamic model in the wing skewing process due to unsteady aerodynamic force, a multi-loop sliding mode controller is formulated by the time-scale separation method. The closed-loop simulation results show that the asymmetric aerodynamics can be balanced and that the velocity and altitude of the aircraft maintain stable, which means that a smooth transition is obtained during the OWA's wing skewing.

Arabidopsis AGC protein kinases IREH1 and IRE3 control root skewing

AGC protein kinases play important roles in plant growth and development.Several AGC kinases in Arabidopsis have been functionally characterized.However,the"AGC Other"subfamily,including IRE,IREH1,IRE3 and IRE4,has not been well understood.Here,we reported that ireh1 mutants displayed a root skewing phenotype,which can be enhanced by ire3 mutation.IREH1 and IRE3 were expressed in roots,consistent with their function in controlling root skewing.The fluorescence intensities of the microtubule marker KNpro:EGFP-MBD were decreased in ireh1,ire3 and ireh1 ire3 mutants compared to wild type.The microtubule arrangements in ireh1 and ireh1 ire3 mutants were also altered.IREH1 physically interacted with IRE3 in vitro and in planta.Thus,our findings demonstrate that IREH1 and IRE3 protein kinases play important roles in controlling root skewing,and maintaining microtubule network in Arabidopsis.

Modeling the frictional torque of a dry-lubricated tapered roller bearing considering the roller skewing

In this paper, an equation for the calculation of the frictional torque of a dry-lubricated tapered roller bearing(TRB) is provided in which the effect of the roller skewing is emphasized. Calculations were performed to investigate the effect of the roller skewing on the torque of dry-lubricated TRB for two representative preload methods, that is, axial force preload and axial displacement preload. The results show that a proper roller skewing angle under axial force preload benefits the reduction of the TRB torque. However, the roller skewing angle should not exceed a certain critical value;otherwise, it will cause a steep rise in the TRB torque. Finally, the critical value of the roller skewing angle as a function of the friction coefficient and cage pocket clearance is presented. The developed torque model provides a tool for the internal design and torque optimization of dry-lubricated TRBs.

Diophantine equations and Fermat's last theorem for multivariate(skew-)polynomials

Fermat’s Last Theorem is a famous theorem in number theory which is difficult to prove.However,it is known that the version of polynomials with one variable of Fermat’s Last Theorem over C can be proved very concisely.The aim of this paper is to study the similar problems about Fermat’s Last Theorem for multivariate(skew)-polynomials with any characteristic.

一种校准线延时差异的方法分析

阐述一种在发送端通过自发自收的方式自动校准并行数据不同PIN延时的方法,可以有效提高接收芯片Clock和Data的相位裕度,降低因并行传输信号完整性指标较差,整个系统不稳定而出现花屏,闪屏的现象。

Application of ACP Nonlinear Math in Analyzing Arithmetic and Radiation Transmission Data (Application 1 & 2) [4-21-2024, 820P] (V)

In this study, we explore the application of ACP (asymptotic curve based and proportionality oriented) Alpha Beta (αβ) Nonlinear Math to analyze arithmetic and radiation transmission data. Specifically, we investigate the relationship between two variables. The novel approach involves collecting elementary “y” data and subsequently analyzing the asymptotic cumulative or demulative (opposite of cumulative) Y data. In part I, we examine the connection between the common linear numbers and ideal nonlinear numbers. In part II, we delve into the relationship between X-ray energy and the radiation transmission for various thin film materials. The fundamental physical law asserts that the nonlinear change in continuous variable Y is negatively proportional to the nonlinear change in continuous variable X, expressed mathematically as dα = −Kdβ. Here: dα {Y, Yu, Yb} represents the change in Y, with Yu and Yb denoting the upper and baseline asymptote of Y. dβ {X, Xu, Xb} represents the change in X, with Xu and Xb denoting the upper and baseline asymptote of X. K represents the proportionality constant or rate constant, which varies based on equation arrangement. K is the key inferential factor for describing physical phenomena.

Severity Based Light-Weight Encryption Model for Secure Medical Information System

As the amount of medical images transmitted over networks and kept on online servers continues to rise,the need to protect those images digitally is becoming increasingly important.However,due to the massive amounts of multimedia and medical pictures being exchanged,low computational complexity techniques have been developed.Most commonly used algorithms offer very little security and require a great deal of communication,all of which add to the high processing costs associated with using them.First,a deep learning classifier is used to classify records according to the degree of concealment they require.Medical images that aren’t needed can be saved by using this method,which cuts down on security costs.Encryption is one of the most effective methods for protecting medical images after this step.Confusion and dispersion are two fundamental encryption processes.A new encryption algorithm for very sensitive data is developed in this study.Picture splitting with image blocks is nowdeveloped by using Zigzag patterns,rotation of the image blocks,and random permutation for scrambling the blocks.After that,this research suggests a Region of Interest(ROI)technique based on selective picture encryption.For the first step,we use an active contour picture segmentation to separate the ROI from the Region of Background(ROB).Permutation and diffusion are then carried out using a Hilbert curve and a Skew Tent map.Once all of the blocks have been encrypted,they are combined to create encrypted images.The investigational analysis is carried out to test the competence of the projected ideal with existing techniques.

基于抗退化混沌系统和初等元胞自动机的动态S盒设计

S盒是多数分组密码算法的基本非线性模块,可以满足分组密码算法的混淆、扩散要求。为了提高混沌S盒的安全性,文中利用抗退化混沌系统生成S盒元素,基于初等元胞自动机生成S盒检索表的方式来生成S盒。抗退化混沌系统可以避免发生Skew Tent系统进入不动点的情况,消除低精度下系统进入短周期的现象。因为初等元胞自动机的迭代规则为二元域上的运算,且满足时空上的离散性,所以,将初等元胞自动机运用到混沌分组密码中时,不用考虑动力学退化的问题。当初等元胞自动机的迭代规则为全局混沌规则时,只要元胞个数足够,就可以保证输出的伪随机性。利用初等元胞自动机生成S盒的检索表,在保证S盒设计的混淆原则的同时还可以简化S盒的生成步骤。最后对所设计的S盒进行安全性分析对比,实验结果表明,所提方法生成的S盒具有良好的安全性,满足分组密码的混淆、扩散原则,可用于混沌分组密码算法设计中。

Attenuate Class Imbalance Problem for Pneumonia Diagnosis Using Ensemble Parallel Stacked Pre-Trained Models

Pneumonia is an acute lung infection that has caused many fatalitiesglobally. Radiologists often employ chest X-rays to identify pneumoniasince they are presently the most effective imaging method for this purpose.Computer-aided diagnosis of pneumonia using deep learning techniques iswidely used due to its effectiveness and performance. In the proposed method,the Synthetic Minority Oversampling Technique (SMOTE) approach is usedto eliminate the class imbalance in the X-ray dataset. To compensate forthe paucity of accessible data, pre-trained transfer learning is used, and anensemble Convolutional Neural Network (CNN) model is developed. Theensemble model consists of all possible combinations of the MobileNetv2,Visual Geometry Group (VGG16), and DenseNet169 models. MobileNetV2and DenseNet169 performed well in the Single classifier model, with anaccuracy of 94%, while the ensemble model (MobileNetV2+DenseNet169)achieved an accuracy of 96.9%. Using the data synchronous parallel modelin Distributed Tensorflow, the training process accelerated performance by98.6% and outperformed other conventional approaches.

Radon CLF:A Novel Approach for Skew Detection Using Radon Transform

In the digital world,a wide range of handwritten and printed documents should be converted to digital format using a variety of tools,including mobile phones and scanners.Unfortunately,this is not an optimal procedure,and the entire document image might be degraded.Imperfect conversion effects due to noise,motion blur,and skew distortion can lead to significant impact on the accuracy and effectiveness of document image segmentation and analysis in Optical Character Recognition(OCR)systems.In Document Image Analysis Systems(DIAS),skew estimation of images is a crucial step.In this paper,a novel,fast,and reliable skew detection algorithm based on the Radon Transform and Curve Length Fitness Function(CLF),so-called Radon CLF,was proposed.The Radon CLF model aims to take advantage of the properties of Radon spaces.The Radon CLF explores the dominating angle more effectively for a 1D signal than it does for a 2D input image due to an innovative fitness function formulation for a projected signal of the Radon space.Several significant performance indicators,including Mean Square Error(MSE),Mean Absolute Error(MAE),Peak Signal-to-Noise Ratio(PSNR),Structural Similarity Measure(SSIM),Accuracy,and run-time,were taken into consideration when assessing the performance of our model.In addition,a new dataset named DSI5000 was constructed to assess the accuracy of the CLF model.Both two-dimensional image signal and the Radon space have been used in our simulations to compare the noise effect.Obtained results show that the proposed method is more effective than other approaches already in use,with an accuracy of roughly 99.87%and a run-time of 0.048(s).The introduced model is far more accurate and timeefficient than current approaches in detecting image skew.

Mathematical Insight into Moderate Inversion Gate Delay Variability for Ultradeep Submicron Digital Circuit Design

Voltage scaling has been extensively used in industry for decades to reduce power consumption.In recent years,exploring digital circuit operation in moderate inversion has created an interest among researchers due to its immense capability to provide a perfect tradeoff between high performance and low energy operation.But circuits operating in moderate inversion are susceptible to process variations and variability.To compute variability,statistical parameters such as the probability density function(PDF)and cumulative distribution function(CDF)are required.This paper presents an analytical model framework for delay calculations utilizing log skew normal distribution for ultradeep submicron technology nodes up to 22 nm.The CDF of the proposed model is utilized to calculate minimum and maximum delays with 3σ-accuracy providing better accuracy than the conventional methods.The obtained results are also compared with Monte Carlo simulations with errors lying within the acceptable range of 2%-4%.

Optimizing Designed Variable Speed Control Moment Gyroscopes with Variable Skew Angle

Large torque can be output by the single gimbal control momentum gyroscope (SGCMG) based on the principle of the gyroscopic precession. However, the singularity is a major obstacle to successfully implement the task of the attitude control. The singularity can be avoided by the additional variable flywheel speed of variable speed control moment gyroscopes (VSCMG). Unfortunately, some kind of singularity cannot be effectively avoided. Consequently, the output toque can be only supported by the reaction torque of the flywheel when the singularity is encountered, and the consume power that is determined by the flywheel speed and reaction torque can be greatly increased when the flywheel spin rate over one thousand revolutions per minute. In this paper, the pyramid configuration with variable skew angle of the VSCMG is considered. A new steering law for the VSCMG with variable skew angle is proposed. The singularity that cannot be avoided by the varying flywheel speed can be effectively avoided with assisting of varying the skew angle. Consequently, the requirement of flywheel torque can be reduced. At last, the optimizing VSCMG with variable skew angle can be cast as a multi-objective function with multi-constraints. The particle swarm optimization method is used to solve the optimizing problem. In summary, the VSCMG with variable skew angle can be redesigned with considering of the singularity avoidance and minimizing system power.

Zeno’s Paradoxes and Lie Tzu’s Dichotomic Wisdom Explained with Alpha Beta (αβ) Asymptotic Nonlinear Math (Including One Example on Second Order Nonlinear Phenomena)

Zeno’s paradoxes are a set of philosophical problems that were first introduced by the ancient Greek philosopher Zeno of Elea. Here is the first attempt to use asymptotic approach and nonlinear concepts to address the paradoxes. Among the paradoxes, two of the most famous ones are Zeno’s Room Walk and Zeno’s Achilles. Lie Tsu’s pole halving dichotomy is also discussed in relation to these paradoxes. These paradoxes are first-order nonlinear phenomena, and we expressed them with the concepts of linear and nonlinear variables. In the new nonlinear concepts, variables are classified as either linear or nonlinear. Changes in linear variables are simple changes, while changes in nonlinear variables are nonlinear changes relative to their asymptotes. Continuous asymptotic curves are used to describe and derive the equations for expressing the relationship between two variables. For example, in Zeno’s Room Walk, the equations and curves for a person to walk from the initial wall towards the other wall are different from the equations and curves for a person to walk from the other wall towards the initial wall. One walk has a convex asymptotic curve with a nonlinear equation having two asymptotes, while the other walk has a concave asymptotic curve with a nonlinear equation having a finite starting number and a bottom asymptote. Interestingly, they have the same straight-line expression in a proportionality graph. The Appendix of this discussion includes an example of a second-order nonlinear phenomenon. .

一种新型Skew Tent映射的混沌混合优化算法

针对已有的混沌优化算法几乎都是利用Logistic映射作为混沌序列发生器,而该混沌序列的概率密度函数呈两头多、中间少的切比雪夫型的分布性质,不利于搜索的效率和能力,为此,首先构造一种新型混沌映射序列发生器—Skew Tent映射并结合迭代优化特点加以改进,然后分析了它的混沌特性．其次,将改进的混沌映射与Alopex启发算法相结合,充分发挥Alopex算法的快速搜索能力和混沌优化全局寻优的特性,提出一种混沌混合优化算法,提高了算法的收敛速度和有效搜索全局最优解．最后,仿真算例验证了该算法的有效性和Skew Tent混沌映射的应用前景．

银行间同业拆放利率风险度量:基于EGARCH-SGED模型的实证分析

根据上海银行间同业拆放利率(SHIBOR)数据的基本特性,分析SHIBOR收益率序列呈尖峰厚尾、偏态和波动集聚等特征,利用EGARCH模型来刻画收益率的波动性,同时利用Skew-GED(SGED)分布来描述收益率的概率分布特征,构建EGARCH-SGED模型来测度SHIBOR收益率的风险价值,并与GED和Skew-t分布下的EGARCH模型的风险测度能力进行了比较。研究结果表明,与其他两类模型相比较而言,EGARCH-SGED模型能更好地描述SHIBOR收益率特性,并且能够显著提高风险价值预测的准确性。

基于ARMA-APARCH-SGED模型的原油价格风险度量研究

从原油现货市场收益率的特征分析着手,为了更好地描述原油现货市场收益率的尖峰厚尾、偏态和波动集聚等特性,利用APARCH模型来刻画收益率的波动性,同时利用Skew GED(SGED)分布来描述收益率的概率分布特征;进而运用ARMA-APARCH-SGED模型对原油现货市场收益率的VaR进行估计和分析,并与基于Skew-t和GED分布的ARMA-APARCH模型进行比较。通过返回检验,结果表明,AR-MA-APARCH-SGED模型能更加准确地度量原油现货市场的风险价值。

AFDX网络冗余管理技术分析

为实现AFDX以太网的冗余管理功能,分析了AFDX网络冗余管理技术和冗余管理接收与发送帧过程中的完整性检查以及冗余管理配置参数最大偏移参数(Skew Max)。文中根据完整性检查来分析顺序号在接收端与发送端的作用以及冗余管理配置参数,设计了冗余管理算法。并对设计的冗余管理算法进行了仿真验证,结果表明,该设计的冗余管理算法可靠准确,设计符合ARINC664 Part7规定的协议要求。

基于修正Sharpe指数的我国开放式基金业绩评价研究

国内外大量实证研究发现基金收益率呈明显的尖峰、厚尾性和有偏性的非正态分布。针对Sharpe指数前提假设是收益率服从正态分布及使用标准差来度量投资风险的缺陷。本文提出用能更好的刻画投资基金收益率分布的非对称性和尖峰、厚尾性的Skewed-t分布来拟合基金收益率分布。在此基础上分别给出了基于Skewed-t分布标准差和Skewed-t分布下的FIGARCH-SKST模型测算的VaR值的修正夏普指数;然后对22只开放式基金数据进行了实证分析。结果表明,基于Skewed-t分布修正的Sharpe指数是有效的。