静电场中电子轨这的三维计算机模拟

本文讨论了静电场中电子轨这的三维计算机模拟，给出了其相应的计算公式，文中还对几各轨迹存在解析解的三维解电结构进行了计算，结果表明，本文所述方法精度较高，能满足电子光学ＣＡＤ的实际需要，是数值求解非轴对称静电结构下电子轨迹的有效方法。     

微尖场致发射三极管的FDM-NOCCS算法模拟

本文将非正交曲线坐标系下的有限差分算法和四阶龙格-库塔法结合起来研究了微尖场致发射三极管的静电特性．计算模型中的阴极为塔形（Tower）结构．本文给出了尖端场强与几何结构的关系曲线、电子轨迹图以及阳极电流密度分布．     

电子束静电折板偏转系统研究

以SDS-3电子束曝光机为基础,用折板结构静电偏转替代直板结构静电偏转,探讨了电子束曝光机折板静电偏转场的电子轨迹与电位分布应满足的要求。导出了折板静电偏转灵敏度与电位分布之间的关系,给出静电偏转像差方程及像差系数。用矢量描写电子轨迹,以积分式表示像差系数,给出了折板结构方程与参量。像差系数适应计算机辅助运算。结果表明,折板结构静电偏完成的图像像差明显优于原直板结构静电偏。提供了静电折板偏转与直板偏转的相关计算数据及摩尔栅条纹图。     

三电极全静电摄像管

磁聚焦静电偏转和静电聚焦静电偏转型摄像管具有图像失真小，分辨率高且均匀，电子束易于垂直上靶，阴影小等优点，所以受到人们的重视，但图案偏转电极的形状复杂，非对称场的计算较困难，本文对静电偏转型聚焦偏转系统的结构作了分析研究，运用分离变量法给出了圆柱坐标中静电聚焦（旋转对称）场和静电偏转（非旋转对称）场的解析解，讨论了静电聚焦静电偏转型聚焦偏转系统设计中有关电子轨迹的计算方法，最后给出了计算实例和Ｉｉ     

三维非对称静电系统边界元素法的数值分析及应用软件

在对旋转对称系统进行研究的基础上,本文进一步探讨边界元素法(BEM)运用于三维非对称静电电子光学系统的数值分析以及适于程序设计的计算方法,并且编制成功了可用于设计与分析各种非对称的静电聚焦、偏转、宽电子束成像以及多极场等电子光学系统的应用软件。用Fortran语言编制的静电系统三维BEM分析设计通用程序,不但能够精确计算出系统电极上块状边界元的表面电荷密度、空间电位及电场分布,还能追迹计算不同方位、不同初始条件的电子轨迹,并计算出系统的成像参量、轴上和轴外的各种像差(包括描述系统非对称性质的像差)。通用程序已经过反复的优化,能够应用于各种非对称实际系统精确的分析设计。     

PRPM聚焦多注速调管电子光学系统的研究

该文采用边界元( BEM )软件TAU对具有周期反转永磁(PRPM)聚焦结构的多注速调管电子光学系统进行研究。通过编写程序增加TAU读入三维磁场数据的功能,从MAFIA中导入三维磁场,分别模拟了处于径向不同位置处电子注的轨迹。通过对磁聚焦系统进行优化设计,外层电子注轨迹得到明显改善。使用软件TAU进行三维模拟可以大大缩短模拟时间,便于多注速调管电子光学系统的工程设计。     

栅极对电子注性能的影响分析

在三维仿真的基础上分析了无截获栅控电子枪中栅极对电子轨迹的影响因素,设计中使用非球面栅极结构的方法可有效减小因栅极的引入对电子注层流性的破坏。     

静电纺丝技术制备三维纳米结构研究进展

静电纺丝技术可制备形貌可控并且连续的纳米纤维,在三维纳米结构制备领域得到了广泛应用。综述了国内外三维静电纺丝技术的研究现状,介绍了三维静电纺丝技术的基本原理。概述了目前制备三维纳米结构常用的四种静电纺丝技术涉及的方法,即自组装法、固体模板辅助收集法、液体辅助收集法和气体辅助收集法。对制备原理、实验装置、制备方法、所获得的纳米纤维的主要工艺参数及适用范围进行了比较和总结,并且详细分析了影响其纺丝质量的因素,为三维静电纺丝技术进一步发展提供了参考。     

W波段折叠波导慢波结构设计及三维注波互作用模拟

本文综合分析了折叠波导的几何尺寸和电子束参数，运用电磁场软件MAFIA的粒子模拟程序对三维折叠波导慢波结构进行了模拟．模型中，电磁波通过波导模式导入；为了克服较大空间电荷效应造成的电子注发散，使用了纵向聚焦磁场．基于三维互作用模型得到了W波段折叠波导的模拟结果，该结果可以对折叠波导慢波结构的三维互作用性能进行预测和分析．     

角向周期结构静电脉塞

本文在研究同轴静电脉塞的基础上,系统地分析了角向周期结构静电脉塞的静态场、高频场、电子注在脉塞中的静态运动、群聚机理以及与高频场的能量交换。分析表明:在角向周期结构静电脉塞中,电子注存在同轴静电脉塞所没有的群聚机理;电子注与高频场的能量交换效率比较高。     

Optimal Regulation of Electric Drives With Constant Load Torque

Optimal time trajectories, based on the Pontryagin's maximum principle, are deduced for a squirrel-cage induction motor with constant load torque. These trajectories are valid for acceleration and deceleration with or without the load torque and for a loaded or unloaded motor, and ensure the minimal time transients with the stator current limited to the previously fixed value. Moreover, the optimal trajectories place the motor at the end of the transient at the minimum current point, which is close to the one of maximum efficiency, thus combining the brevity of the transients with the saving of energy. An optimal-time control system that implements these trajectories is designed. The results of the simulation of the proposed control system and the results of the experiments on a real drive are presented     

Novel reference signal generation for two-degree-of-freedomcontrollers for hard disk drives

This paper considers the determination of reference trajectories for use with a two-degree of-freedom (2-DOF) controller for the head positioning of hard disk drives (HDD). The reference trajectories are designed in two stages-off-line simulation and online reference generation. The HDD model used for the design includes the back electromotive force of the voice coil motor. In the second stage, the idea of structural vibration minimized acceleration trajectory is utilized to adjust the errors at the end of the trajectories. 2-DOF control with the proposed reference trajectory is compared to conventional mode-switching control, and its effectiveness is verified     

A Human-Centered Multiple Instance Learning Framework for Semantic Video Retrieval

This paper proposes a human-centered interactive framework for automatically mining and retrieving semantic events in videos. After preprocessing, the object trajectories and event models are fed into the core components of the framework for learning and retrieval. As trajectories are spatiotemporal in nature, the learning component is designed to analyze time series data. The human feedback to the retrieval results provides progressive guidance for the retrieval component in the framework. The retrieval results are in the form of video sequences instead of contained trajectories for user convenience. Thus, the trajectories are not directly labeled by the feedback as required by the training algorithm. A mapping between semantic video retrieval and multiple instance learning (MIL) is established in order to solve this problem. The effectiveness of the algorithm is demonstrated by experiments on real-life transportation surveillance videos.      

Moving-Window Dynamic Optimization: Design of Stimulation Profiles for Walking

The overall goal of the research is to improve control for electrical stimulation-based assistance of walking in hemiplegic individuals. We present the simulation for generating offline input (sensors)–output (intensity of muscle stimulation) representation of walking that serves in synthesizing a rule-base for control of electrical stimulation for restoration of walking. The simulation uses new algorithm termed moving-window dynamic optimization (MWDO). The optimization criterion was to minimize the sum of the squares of tracking errors from desired trajectories with the penalty function on the total muscle efforts. The MWDO was developed in the MATLAB environment and tested using target trajectories characteristic for slow-to-normal walking recorded in healthy individual and a model with the parameters characterizing the potential hemiplegic user. The outputs of the simulation are piecewise constant intensities of electrical stimulation and trajectories generated when the calculated stimulation is applied to the model. We demonstrated the importance of this simulation by showing the outputs for healthy and hemiplegic individuals, using the same target trajectories. Results of the simulation show that the MWDO is an efficient tool for analyzing achievable trajectories and for determining the stimulation profiles that need to be delivered for good tracking.      

Incorporating duration and region association information in trajectory classification

Trajectory classification is the process of predicting the class label of moving objects based on their trajectories and other features. Existing works on building trajectory classification model discover features by using spatial distribution and shape of sub-trajectory. However, they do not utilise duration and region association information available in trajectory data during feature generation. In this study, trajectory features are generated using spatial distribution, duration and region association information of trajectories. In particular, two types of features, region rules and path rules, are generated from trajectories for classification. Region rules consider the spatial distribution of trajectories, the time spent (duration) by the trajectories in the region and the association information with other regions. Path rules differentiate objects based on their travelling patterns and speed. Efficient algorithms are devised to obtain region rules and path rules. Based on the discovered rule, trajectory classification model is built to predict the class label of new trajectory. Experimental results on various real-world data-sets show that incorporating duration and region association information in trajectory classification improves accuracy.     

A movement pattern generator model using artificial neural networks

Artificial neural networks (ANN's) allow a new approach to biological modeling. The main applications of ANN's have been geared towards the modeling of the association and learning mechanisms of the brain; only a few researchers have explored them for motor control. The fact that ANN's are based on biological systems indicates their potential application for a biological act such as locomotion. Towards this goal, we have developed a "movement pattern generator," using an ANN for generating periodic movement trajectories. This model is based on the concept of "central pattern generators." Jordan's sequential network, which is capable of learning sequences of patterns, was modified and used to generate several bipedal trajectories (or gaits), coded in task space, at different frequencies. The network model successfully learned all of the trajectories presented to it. The model has many attractive properties such as limit cycle behavior, generalization of trajectories and frequencies, phase maintenance, and fault tolerance. The movement pattern generator model is potentially applicable for improved understanding of animal locomotion and for use in legged robots and rehabilitation medicine.     

电子在磁镜系统中的运动

本文研究具有任意初始入射条件的电子在磁镜系统中的运动。研究发现,在中心轨道确定之后,任何其它轨道可以区分为正常轨道或非正常轨道。在正常轨道上运动的电子接受动量选择狭缝的选择,而在非正常轨道上运动的电子不受动量选择狭缝的作用。文中给出了正常轨道上的任一微分弧元在中心轨道坐标系中的投影的计算方法,并且经大量的数值计算证明是可靠的。这一工作对于了解带电粒子束在通过磁镜系统时的运动的详细过程有重要意义。     

The methodology of simulating particle trajectories throughtunneling structures using a Wigner distribution approach

The authors introduce a trajectory methodology to describe elementary space- and time-dependent events in a tunneling process in the resonant tunneling diode (RTD). A methodology for constructing quantum particle trajectories is presented. The trajectories for a RTD are presented and their behavior, as a function of scattering and self-consistency, is shown to be consistent with the steady-state current-voltage/quantum well electron density characteristics of the RTD, and with the response of the RTD to a sudden bias switch. The trajectories also exhibit a conservation-of-energy-like behavior. The trajectory formulation is thus shown to be potentially useful for incorporating into a multidimensional particle Monte Carlo simulation of quantum-based devices in which the tunneling region is small compared to the dimensions of the device     

Trajectory Sampling With Unreliable Reporting

We define and evaluate methods to perform robust network monitoring using trajectory sampling in the presence of report loss. The first challenge is to reconstruct an unambiguous set of packet trajectories from the reports on sampled packets received at a collector. In this paper we extend the reporting paradigm of trajectory sampling to enable the elimination of ambiguous groups of reports, but without introducing bias into any characterization of traffic based on the surviving reports. Even after the elimination, a proportion of trajectories are incomplete due to report loss. A second challenge is to adapt measurement based applications (including network engineering, path tracing, and passive performance measurement) to incomplete trajectories. To achieve this, we propose a method to join multiple incomplete trajectories for inference, and analyze its performance. We also show how applications can distinguish between packet and report loss at the statistical level.     

Optimal-time quadcopter descent trajectories avoiding the vortex ring and autorotation states

It is well-known that helicopters descending fast may enter the so-called Vortex Ring State (VRS), a region in the velocity space where the blade’s lift differs significantly from regular regions and high amplitude fluctuations are often present. These fluctuations may lead to instability and, therefore, this region is avoided, typically by increasing the horizontal speed. This paper researches this phenomenon in the context of small-scale quadcopters. The region corresponding to the VRS is identified by combining first-principles modeling and wind-tunnel experiments. Moreover, we propose that the so-called Windmill-Brake State (WBS) or autorotation region should also be avoided for quadcopters, which is not necessarily the case for helicopters. A model is proposed for the velocity constraints that the quadcopter must meet in order to avoid these regions. Then, the problem of designing optimal time descent trajectories that avoid the VRS and WBS regions is tackled. Finally, the optimal trajectories are implemented on a quadcopter. The flight tests show that by following the designed trajectories, the quadcopter can descend considerably faster than purely vertical trajectories that also avoid the VRS and WBS.