基于多线程和消息的局域网通信程序实现

目前大多数的局域网通信程序工作在服务器/客户机模式下.在此模式下的应用程序工作过程相对复杂且消耗资源较多.介绍了一种基于多线程技术和Windows消息机制的局域网通信程序的实现过程,使得两台网内主机可以在对等模式而不是传统的服务器/客户机模式下进行数据传输,从而简化了常见局域网通信程序编制中较为复杂的工作过程,实现了一种相对便捷的网络数据传输方式.     

变频器综合实践 第2讲： 变频器在总线控制系统中的综合实践

现场总线是将自动化最底层的现场控制器和现场智能仪表设备等互连的实时控制通讯网络,而变频总线控制系统的特点,就是通过总线可以控制和监控变频器。变频总线控制系统既可联动控制也可单独控制,能充分满足传动系统的可靠性、实时性、实用性的要求,并为实现传动系统的＂无人值班＂运行提供技术准备。     

网络安全始于密码

密码成为现代生活不可缺少的部分,本文介绍了使用密码的常识,提供了忘记密码时的一些补救措施。     

Addressing agent loss in vehicle formations and sensor networks

In this paper, we address the problem of agent loss in vehicle formations and sensor networks via two separate approaches: (1) perform a ‘self‐repair’ operation in the event of agent loss to recover desirable information architecture properties or (2) introduce robustness into the information architecture a priori such that agent loss does not destroy desirable properties. We model the information architecture as a graph G(V, E), where V is a set of vertices representing the agents and E is a set of edges representing information flow amongst the agents. We focus on two properties of the graph called rigidity and global rigidity, which are required for formation shape maintenance and sensor network self‐localization, respectively. For the self‐repair approach, we show that while previous results permit local repair involving only neighbours of the lost agent, the repair cannot always be implemented using only local information. We present new results that can be applied to make the local repair using only local information. We describe implementation and illustrate with algorithms and examples. For the robustness approach, we investigate the structure of graphs with the property that rigidity or global rigidity is preserved after removing any single vertex (we call the property as 2‐vertex‐rigidity or 2‐vertex‐global‐rigidity, respectively). Information architectures with such properties would allow formation shape maintenance or self‐localization to be performed even in the event of agent failure. We review a characterization of a class of 2‐vertex‐rigidity and develop a separate class, making significant strides towards a complete characterization. We also present a characterization of a class of 2‐vertex‐global‐rigidity. Copyright © 2008 John Wiley & Sons, Ltd.     

A method for diagnosis of current faults in antenna arrays using neural networks

A method for detection of faulty elements in antenna arrays from far‐field radiation pattern is presented. The proposed technique finds variation of current from correct values in the faulty elements. A step wise approach is proposed to determine magnitude and phase of current excitation and location of faulty element using neural networks. The results with radial basis function neural network and probabilistic neural network are compared. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2009.     

网络时代杂志形态的转变与发展

信息化浪潮给人们的生活带来剧变,随着计算机和网络的普及,网络数字化阅读开始成为人们新型的阅读方式。多媒体互动电子杂志作为一种融合了平面杂志、网络多媒体技术特点的新型期刊形式,符合阅读方式发展的潮流。本文通过对传统纸媒杂志与多媒体互动电子杂志的比较分析,总结出了电子杂志自身的无可比拟的优势和目前发展中存在的问题,并对网络时代下杂志未来的发展趋势进行了展望。     

基于动态贝叶斯网络的社交圈归属匹配模型

为了帮助社交网中新成员寻找与之最为合适的社交圈,尝试采用动态贝叶斯网（DBN）理论解决社交网分析应用中成员（节点）与社交圈（集合）的匹配问题。将圈内成员个人的多项兴趣爱好程度作为描述社交圈基本属性的特征向量,对每一类圈子建立了带有辅助信息形式的DBN模型,求解最大输出概率即为最佳匹配对象。结果表明,在客观测试和主观评价两方面,该模型都收到了较为满意的结果。     

无线传感器网络路由协议及安全问题研究

无线传感器网络在军事和民用领域得到广泛的应用。由于传感器节点的资源有限以及通信的开放性使得其安全性显得尤为重要。出于对能量消耗的考虑,目前的路由协议设计得比较简单,作者对路由的安全性能以及可能受到的攻击进行分析,并给出相应的防范对策。     

Error compensation in machine tools: a neural network approach

For a non-idealized machine tool, each point in the workspace is associated with a tool point positioning error vector. If this error map can be determined, then it is possible to substantially improve the positioning performance of the machine by introducing suitable compensation into the control loop. This paper explores the possibility of using an artifical neural network (ANN) to compute this mapping. The training set for the ANN is obtained by mounting a physical artifact whose dimensions are precisely known in the machine's workspace. The machine, equipped with a touch trigger probe, measures the positions of features on the artifact. The difference between the machine reading and the known dimension is the machine error at that point in the workspace. Using standard modeling techniques, the kinematic error model for a CNC turning center was developed. This model was parameterized by measurement of the parametric error functions using a laser interferometer, electronic levels and a precision square. The kinematic model was then used to simulate the artifact-measuring process and develop the ANN training set. The effect of changing artifact geometry was explored and a machining operation was simulated using the ANN output to provide compensation. The results show that the ANN is capable of learning the error map of a real machine, and that ANN-based compensation can significantly reduce part-dimensional errors.     

Ship detection based on multi-scale weighted fusion

Ship surveillance plays an important role in ensuring the safety of maritime transportation and navigation. Due to the influence of factors such as waves and special weather, the existing detection methods still cannot balance the accuracy, speed and the parameters of the model in the changeable and complex marine environment. To solve this problem, this paper proposes an improved real-time method based on YOLOv5, which has few parameters and achieves high detection accuracy with little memory and computation cost. Collaborative Attention (CA) mechanism is added to the network structure, which enables the model to more accurately locate and identify target regions. We also design a Spatial Pyramid Pooling module (SPP) and a weighted pyramid network called Bidirectional Feature Pyramid Network (BiFPN) based on the characteristics of the ships to better fuse feature information. Transformer encoder is introduced to capture long-distance dependencies and preserve global and local features to the greatest extent. Furthermore, the ability of our proposed structure to localize objects at each stage is improved through integrating the output of multiple modules. The experimental results show that, the comprehensive performance of this method is better than the existing technology in ship detection on different evaluation criteria.