Winding Function Model-based Performance Evaluation of a PM Transverse Flux Generator for Applications in Direct-drive Systems

The magnetic flux in a permanent magnet transverse flux generator(PMTFG) is three-dimensional(3D), therefore, its efficacy is evaluated using 3D magnetic field analysis. Although the 3D finite-element method(FEM) is highly accurate and reliable for machine simulation, it requires a long computation time, which is crucial when it is to be used in an iterative optimization process. Therefore, an alternative to 3DFEM is required as a rapid and accurate analytical technique. This paper presents an analytical model for PMTFG analysis using winding function method. To obtain the air gap MMF distribution, the excitation magneto-motive force(MMF) and the turn function are determined based on certain assumptions. The magnetizing inductance, flux density, and back-electro-magnetomotive force of the winding are then determined. To assess the accuracy of the proposed method, the analytically calculated parameters of the generator are compared to those obtained by a 3D-FEM. The presented method requires significantly shorter computation time than the 3D-FEM with comparable accuracy.

Exploration of Innovative Practical Teaching Model for English Education Majors under New Education Policies

The“Double Reduction”policy has been implemented for more than three years,and the 5+2 Model has also been fully implemented for one year.Changes in education policies inevitably affect undergraduate majors related to primary school education in normal universities because the new education policies have put forward higher requirements for prospective English teachers on how to integrate into primary school teaching,research,management and other work more quickly.This paper,based on the Theory of Constructivism,explores innovative practical teaching model for English education majors from two dimensions:integration and immersion.By integrating professional skills courses,knowledge courses,and comprehensive training courses,this practical teaching model aims to achieve integrated development of English education majors by linking in-class and after-class,on-line and off-line,on-campus and off-campus resources.Project-based management and circular progression measures are adopted to cultivate students’practical and innovative abilities.

Parallel Control for Continuous-Time Linear Systems:A Case Study

In this paper,a new parallel controller is developed for continuous-time linear systems.The main contribution of the method is to establish a new parallel control law,where both state and control are considered as the input.The structure of the parallel control is provided,and the relationship between the parallel control and traditional feedback controls is presented.Considering the situations that the systems are controllable and incompletely controllable,the properties of the parallel control law are analyzed.The parallel controller design algorithms are given under the conditions that the systems are controllable and incompletely controllable.Finally,numerical simulations are carried out to demonstrate the effectiveness and applicability of the present method.Index Terms-Continuous-time linear systems,digital twin,parallel controller,parallel intelligence,parallel systems.

Novel method for searching ontologies on semantic web

In order to solve the problem of information retrieval on the semantic web, a new semantic information retrieval （SIR） model for searching ontologies on the semantic web is proposed. First, SIR transformed domain ontologies into global ontologies. Then semantic index terms were extracted from these global ontologies. Based on semantic index terms, logical inferences can be performed and the logical views of the concept can be obtained. These logical views represent the expanded meaning of the concept. Using logical views, SIR can perform the information retrieval and inferences based on the semantic relationships in the documents, not only on the syntactic analysis of the documents. SIR can significantly enhance the recall and precision of the information retrieval by the semantic inference. Finally, the practicability of the SIR model is analyzed.

New edge detection method for high-resolution SAR images

A new edge detection method combining the scanning window central edge （SWCE） detector and an improved active contour model is proposed. The method first emploies the SWCE detector based on the difference of area pixel value means to perform an optimal edge detection, and then proposes an improved active contour model with modified energy functions to refine the location of the edges. The initial nodes of the improved active contour model are automatically found from the vectorised results of the SWCE detector. Tests on simulated speckled images and real airborne SAR images show that the combined method can benefit from the advantages of the both techniques and get satisfactory edge detection and localization abilities at the same time.

Sparse Planar Retrodirective Antenna Array Using Improved Adaptive Genetic Algorithm

An improved adaptive genetic algorithm is presented in this paper. It primarily includes two modified methods： one is novel adaptive probabilities of crossover and mutation, the other is truncated selection approach. This algorithm has been validated to be superior to the simple genetic algorithm （SGA） by a complicated binary testing function. Then the proposed algorithm is applied to optimizing the planar retrodirective array to reduce the cost of the hardware. The fitness function is discussed in the optimization example. After optimization, the sparse planar retrodirective antenna array keeps excellent retrodirectivity, while the array architecture has been simplified by 34%. The optimized antenna array can replace uniform full array effectively. Results show that this work will gain more engineering benefits in practice.

Dynamics and Operation-State Estimation of Current-Mode Controlled Flyback Converter

By utilizing total magnetic flux φ of the primary and secondary windings of the flyback transformer as a state variable, the discrete-time model of current-mode controlled flyback converter is established, upon which the bifurcation behaviors of the converter are analyzed and two boundary classification equations of the orbit state shifting are obtained. The operation state regions of the current-mode controlled flyback converter are well classified by two boundary classification equations. The theoretical analysis results are verified by power electronics simulator （PSIM）. The estimation of operation-state regions for the flyback converter is useful for the design of circuit parameters, stability control of chaos, and chaos-based applications.

Maneuvering Angle Rigid Formations With Global Convergence Guarantees

Angle rigid multi-agent formations can simultaneously undergo translational,rotational,and scaling maneuvering,therefore combining the maneuvering capabilities of both distance and bearing rigid formations.However,maneuvering angle rigid formations in 2D or 3D with global convergence guarantees is shown to be a challenging problem in the existing literature even when relative position measurements are available.Motivated by angle-induced linear equations in 2D triangles and 3D tetrahedra,this paper aims to solve this challenging problem in both 2D and3D under a leader-follower framework.For the 2D case where the leaders have constant velocities,by using local relative position and velocity measurements,a formation maneuvering law is designed for the followers governed by double-integrator dynamics.When the leaders have time-varying velocities,a sliding mode formation maneuvering law is proposed by using the same measurements.For the 3D case,to establish an angle-induced linear equation for each tetrahedron,we assume that all the followers'coordinate frames share a common Z direction.Then,a formation maneuvering law is proposed for the followers to globally maneuver Z-weakly angle rigid formations in 3D.The extension to Lagrangian agent dynamics and the construction of the desired rigid formations by using the minimum number of angle constraints are also discussed.Simulation examples are provided to validate the effectiveness of the proposed algorithms.

An Event Alarm System Based on Single and Group Human Behavior Analysis

Due to the increasing demand for security, the development of intelligent surveillance systems has attracted considerable attention in recent years. This study aims to develop a system that is able to identify whether or not the people need help in a public place. Different from previous work, our work considers not only the behaviors of the target person but also the interaction between him and nearby people. In the paper, we propose an event alarm system which can detect the human behaviors and recognize the happening event through integrating the results generated from the single and group behavior analysis. Several new effective features are proposed in the study. Besides, a mechanism capable of extracting one-to-one and multiple-to-one relations is also developed. Experimental results show that the proposed approach can correctly detect human behaviors and provide the alarm messages when emergency events occur.

The Current Situation of Chinese College Students' English Pronunciation

Nowadays, we can find the expression"dumb English"in newspapers and websites. The phrase exposes a situation that many Chinese college students, who earn high scores in English proficiency tests, such as CET-4, cannot speak fluent English. When they started to work after graduation, they cannot perform effective communication with foreigners verbally in many occasions. This paper aims to illustrate the current situation of Chinese college students' English pronunciation and analyze it in detail.

Augmented Industrial Data-Driven Modeling Under the Curse of Dimensionality

The curse of dimensionality refers to the problem o increased sparsity and computational complexity when dealing with high-dimensional data.In recent years,the types and vari ables of industrial data have increased significantly,making data driven models more challenging to develop.To address this prob lem,data augmentation technology has been introduced as an effective tool to solve the sparsity problem of high-dimensiona industrial data.This paper systematically explores and discusses the necessity,feasibility,and effectiveness of augmented indus trial data-driven modeling in the context of the curse of dimen sionality and virtual big data.Then,the process of data augmen tation modeling is analyzed,and the concept of data boosting augmentation is proposed.The data boosting augmentation involves designing the reliability weight and actual-virtual weigh functions,and developing a double weighted partial least squares model to optimize the three stages of data generation,data fusion and modeling.This approach significantly improves the inter pretability,effectiveness,and practicality of data augmentation in the industrial modeling.Finally,the proposed method is verified using practical examples of fault diagnosis systems and virtua measurement systems in the industry.The results demonstrate the effectiveness of the proposed approach in improving the accu racy and robustness of data-driven models,making them more suitable for real-world industrial applications.

An Enhanced Automated Signature Generation Algorithm for Polymorphic Malware Detection

Polymorphic malware is a secure menace for application of computer network systems because hacker can evade detection and launch stealthy attacks. In this paper, a novel enhanced automated signature generation （EASG） algorithm to detect polymorphic malware is proposed. The EASG algorithm is composed of enhanced-expectation maximum algorithm and enhanced K-means clustering algorithm. In EASG algorithm, the fixed threshold value is replaced by the decision threshold of interval area. The false positive ratio can be controlled at low level, and the iterative operations and the execution time are effectively reduced. Moreover, the centroid updating is realized by application of similarity metric of Mahalanobis distance and incremental learning. Different malware group families are partitioned by the centroid updating.

Evaluation of Chaotic Demodulator for EBPSK Signals

Based on the theory of Duffing oscillator weak signal detection and the technology of extended binary phase shift keying （EBPSK） modulation, the chaotic demodulator using the Duffing oscillator for EBPSK signals was proposed. The proposed demodulator could avoid the problem of demodulation filters design, and shows the excellent anti-noise capability of chaotic oscillator detection. Numerical and experimental tests were taken to investigate the impact of modulation parameters T and 0 on bit error performance of the proposed method, and the performance limits were gotten. The results show that the proposed chaotic demodulator works well under a very low signal-to-noise ratio （SNR） conditions, and gets SNR gains about 20 dB to 30 dB from the impulse filter.

High Accuracy and Real-Time Gated Viewing Laser Radar

A gated viewing laser radar has an excellent performance in underwater low light level imaging, and it also provides a viable solution to inhibit backscattering. In this paper, a gated viewing imaging system according to the demand for real-time imaging is presented, and then the simulation is used to analyze the performance of the real-time gated viewing system. The range accuracy performance is limited by the slice number, the width of gate, the delay time step, the initial delay time, as well as the system noise and atmospheric turbulence. The simulation results indicate that the highest range accuracy can be achieved when the system works with the optimal parameters. Finally, how to choose the optimal parameters has been researched.

Correcting Image Distortion for Adaptive Cruise Control

One of the main drivers for intelligent transportation systems is safety. Adaptive cruise control, as a common solution for traffic safety, lias extended from radars to cameras. Due to high mobility of vehicles and unevenness of roads, the picture quality of cameras has been great challenges for camera-based adaptive cruise control. In this paper, an image distortion correction algorithm is addressed. Our method is based on optical flow technology which is normally applied in motion estimation and video compression research. We are the first to attempt to adapt it in image distortion correction. Two optical flow approaches, the Lucas-Kanade method and the Horn-Schunck method, are selected and compared. The procedure of image distortion correction using the optical flow method has been tested by both synthetic test images and camera images. The experimental results show that the Lucas-Kanade method is more suitable in the correction of image distortion.

Method Investigation for Fabricating Micro-Optical Elements by Use of Half Tone Masks

Several approaches to fabricate micro optical elements by use of half tone masks are studied and compared. It is shown that half tone masks employed in filtering image systems can obtain gray patterns with considerably high precision, but it is hard to operate from the viewpoint of operation. The method using contacting lithography technology or laser ablation can be easily operated with the cost of reducing fabrication precision and the trouble of choosing appropriate materials. For all of these methods, the coding of half tone masks with corrections for the nonlinear characteristics of coding, imaging and photoresist is recommended.

Access Control Mechanism for Blog Posts with Fine- Grained Ability Using Simple Operations

Access control enables the owners to assign different users different permissions to see different views. The current blog system does not support fine-grained authorization. That is, the bloggers disallow to just assign partial contents of the blog posts （i.e., a paragraph or several paragraphs） to readers. The management cost is no doubt to be significantly increased while handling the authorizations on the huge amount of blog articles. In this paper, we propose a scheme for supporting a fine-grained access control mechanism on blog articles. The advantage is that bloggers are able to authorize partial contents of blog posts to different users or groups of users.

Structured scene modeling using micro stereo vision system with large field of view

This paper presents a method for structured scene modeling using micro stereo vision system with large field of view. The proposed algorithm includes edge detection with Canny detector, line fitting with principle axis based approach, finding corresponding lines using feature based matching method, and 3D line depth computation.

A novel localization and orientation method for an objective embedded with a rectangle magnet

To wirelessly obtain the accurate location and orientation of an objective and exert an appropriate guidance for the objective, a feasible approach is to enclose a small rectangular permanent mag- net in the objective. The magnetic field, produced by the rectangular magnet can be detected by magnetic sensors outside the objective. With these sensor data, the 3D localization and 3D orienta- tion parameters can be computed based on the mathematic model of the rectangular magnet magnetic field. In this 6D localization and orientation system, we first obtain 5D parameters of the objective by dipole model, then based on these parameters we can obtain 6D parameters by the model of rectangular magnet magnetic field using the particle swarm optimization （PSO） algorithm. Simulation experiments show that the proposed approach achieves ~ood performance.

Effect of ACTN3 gene polymorphism on the pathogenic phenotype of related diseases and its treatment prospect

Theα-actin-3 protein expressed by ACTN3 gene cod is a troponin binding protein,which is mainly located in the Z disk on skeletal muscle fibers.Due to the homozygous nonsense polymorphism(R577X)of the gene,about 1.5 billion people in the world have lost the expression of this protein.Because the presence ofα-actin-3 protein increases skeletal muscle cells to be compliant,the gene is often referred to as the“speed gene”,and current studies suggest that this gene polymorphism has varying degrees of influence on muscle injury,decreased endurance,hypomyopathy,osteoporosis,endocrine disease,cardiovascular disease.This is a review of the current effects of ACTN3 gene polymorphisms on a variety of diseases,as well as its possible intervention treatment options.