并行通讯格雷码多圈旋转编码器和S7-200型PLC在石灰炉提升机上的应用

本文系统分析了各种旋转编码器和S7-200型PLC的特点,解决了用S7-200型PLC将格雷码翻译成二进制码等难题,选用并行通讯格雷码旋转编码器、S7-200型PLC和中文TD200人机界面组成控制系统,成功实现石灰炉提升机自动控制,控制系统必将在小规模精度定位领域中得到广泛应用。     

On Dual-Mode Driving Control Method for a Novel Unmanned Tractor With High Safety and Reliability

Due to the non-standardization and complexity of the farmland environment, it is always a huge challenge for tractors to achieve fully autonomy (work at Self-driving mode) all the time in agricultural industry. Whereas, when tractors work in the Tele-driving (or Remote driving) mode, the operators are prone to fatigue because they need to concentrate for long periods of time. In response to these, a dual-mode control strategy was proposed to integrate the advantages of both approaches, i.e., by combing Self-driving at most of the time with Tele-driving under special (complex and hazardous) conditions through switching control method. First, the state switcher was proposed, which is used for smooth switching the driving modes according to different working states of a tractor. Then, the state switching control law and the corresponding subsystem tracking controllers were designed. Finally, the effectiveness and superiority of the dual-mode control method were evaluated via actual experimental testing of a tractor whose results show that the proposed control method can switch smoothly, stably, and efficiently between the two driving modes automatically. The average control accuracy has been improved by 20% and 15% respectively, compared to the conventional Tele-driving control and Self-driving control with low-precision navigation. In conclusion, the proposed dual-mode control method can not only satisfy the operation in the complex and changeable farmland environment, but also free drivers from high-intensity and fatiguing work. This provides a perfect application solution and theoretical support for the intelligentization of unmanned farm agricultural machinery with high safety and reliability.      

使用Conformer增强的混合CTC/Attention端到端中文语音识别

最近,基于自注意力的Transformer结构在不同领域的一系列任务上表现出非常好的性能。探索了基于Transformer编码器和LAS（listen,attend and spell）解码器的Transformer-LAS语音识别模型的效果,并针对Transformer不善于捕捉局部信息的问题,使用Conformer代替Transformer,提出Conformer-LAS模型。由于Attention过于灵活的对齐方式,使得在嘈杂环境中的效果急剧下降,采用连接时序分类（connectionist temporal classification,CTC）辅助训练以加快收敛,并加入音素级别的中间CTC损失联合优化,提出了效果更好的Conformer-LAS-CTC语音识别模型。在开源中文普通话Aishell-1数据集上对提出来的模型进行验证,实验结果表明,Conformer-LAS-CTC相对于采用的基线BLSTM-LAS和Transformer-LAS模型在测试集上的字错率分别相对降低了22.58%和48.76%,模型最终字错误率为4.54%。     

A hierarchical attention-based neural network architecture, based on human brain guidance, for perception, conceptualisation, action and reasoning

We present a neural network software architecture, guided by that of the human and more generally primate brain, for the construction of an autonomous cognitive system (which we have named GNOSYS). GNOSYS is created so as to be able to attend to stimuli, to conceptualise them, to learn their predicted reward value and reason about them so as to attain those stimuli in the environment with greatest predicted value. We apply this software system to an embodied version in a robot, and describe the activities in the various component modules of GNOSYS, as well as the overall results. We briefly compare our system with some others proposed to have cognitive powers, and finish by discussion of future developments we propose for our system, as well as expanding on the arguments for and against our approach to creating such a software system.     

异构环境下实时多媒体信息组播技术

该文先介绍了组播骨干网(Mbone)和组播的相关概念,然后讨论了Internet和Mbone的异构性,在此基础上论述了如何有效地在异构环境下传输实时多媒体信息,并比较了两种对异构性的不同解决方案.     

电力数字调度机软件系统的设计与实现

电力调度交换机正被逐渐地应用于电力生产调度,它在电力通信中具有举足轻重的作用.文章首先介绍了一种新型程控调度交换机软件的基本结构和设计思想,讨论了在实现此软件系统中涉及到的操作系统设计、呼叫处理程序和其他关键问题.     

基于Multi-Agent的农业专家系统在Internet上的系统设计

该文充分考虑了农业专家系统中需要不同领域知识进行协作,以及领域知识的分布性、易于更新性、可重用性等特点,同时也考虑对原有的各领域专家系统进行利用,提出一个新的基于Multi－Agent的农业专家系统的实现模式.最后,提出一个在Internet环境下的系统实现方案.     

SET协议的支付模型分析

文章对安全电子交易协议SET的核心部分&&安全支付模型&&进行了详细分析,给出了有关协议数据的形式化描述,叙述了安全支付过程中的购买请求、支付授权、资金清算等处理流程,为进一步研究电子商务的安全支付问题,给出了一个参考模型.     

近线性神经和元非线性神经元

人工神经网络(ANN)中普遍采用的神经元模型具有单调有界的I／O特性,该文称其为近线性神经元(ALN,approximate－linear neuron),ALN既简化了网络的复杂性,也是限制ANN能力的一个瓶径.通过比较Hopfield神经网络的稳定性和Conway生命游戏的复杂行为,该文提出非线性神经元(NLN,non－linear neuron)的概念,其I／O特性是完全非线性的.ALN可以进一步提高ANN的非线性,从而增强它的功能,余数制神经网络是一个例子.     

动态可扩展操作系统的研究

动态扩展技术的研究能够解决操作系统设计中许多长期存在并难以解决的问题。这些问题包括：如何在提高应用程序的性能同时保证系统的安全性;如何提高操作系统使用的灵活性;如何包容和管理随着操作系统发展而不断增加的复杂性。文章对当前各种操作系统扩展类型进行详细分类,具体介绍了各种动态扩展技术,评估了不同的扩展技术对操作系统性能和安全性的影响,最后提出了需要研究的内容以及其中的关键问题。