基于“网络通”的以太网家庭数据终端

以社区综合服务系统为例,介绍一种新型的基于“网络通”的以太网家庭数据终端。系统以以太网为通信媒介,利用“网络通”进行家庭内外信息交换,采用分时操作系统对家庭的各种信息进行实时、有效的管理和调度,为现代家庭生活提供智能服务。

基于“网络通”的单片机以太网-CAN网关的应用

利用“网络通”可做成基于单片机的以太-CAN网关,将CAN总线系统直接连接在以太网上。它既可以将普通CAN接口测控设备变成以太网络测控设备,通过互联网进行数据的传送;也可以在一些大型分布式测控系统中,采用以太网-CAN接口模块,很方便地将原来现场总线控制系统改造为以太网络分布式控制系统。

加速进入广告业数字化时代——本刊为读者免费提供“网络通”软件下载服务

在宽带时代,广告创意为什么还要放在MO或者磁盘上送来送去?因为e-mail容不下您的'大作'?从我们的观点看,这只对快递这个行业有好处。它太'大'了吗?你的创意,再伟大,也不必离开电脑传递。有这样一个软件,可以把你的电脑硬盘和互联网上任意一个电脑硬盘直接相连,就像在局域网里一样,您的作品再大,也可以通过网络传到另外一台电脑上去。如果您还生活在窄带的干涸土地上,你当然也可以从水龙头里挤出水来。

AB系统的工业网络通信--EtherNet/IP网络

随着现代信息技术和计算机技术的不断发展,分布式控制系统在企业自动化和过程自动化中应用迅速增长,现场总线技术已成为工业网络通信中的佼佼者。网络通信方式的多样化和通信效率的提高,使信息交换领域从现场设备控制层发展到企业管理层,以网络为主的自动化分布式控制系统成为行业趋势。

Pseudo channel:time embedding for motor imagery decoding

Motor imagery(MI)based electroencephalogram(EEG)represents a frontier in enabling direct neural control of external devices and advancing neural rehabilitation.This study introduces a novel time embedding technique,termed traveling-wave based time embedding,utilized as a pseudo channel to enhance the decoding accuracy of MI-EEG signals across various neural network architectures.Unlike traditional neural network methods that fail to account for the temporal dynamics in MI-EEG in individual difference,our approach captures time-related changes for different participants based on a priori knowledge.Through extensive experimentation with multiple participants,we demonstrate that this method not only improves classification accuracy but also exhibits greater adaptability to individual differences compared to position encoding used in Transformer architecture.Significantly,our results reveal that traveling-wave based time embedding crucially enhances decoding accuracy,particularly for participants typically considered“EEG-illiteracy”.As a novel direction in EEG research,the traveling-wave based time embedding not only offers fresh insights for neural network decoding strategies but also expands new avenues for research into attention mechanisms in neuroscience and a deeper understanding of EEG signals.

依托“人人通”建设 助推县域教育发展均衡化

新课程标准明确指出要致力于学生基本素质的形成和发展,为学生全面发展和终身发展奠定基础,而＂云空间＂环境下的教育教学能提供更加人性化的管理,以及形象直观的交互式学习环境,为拓宽教育教学的发展创造了条件。国家颁布实施《教育信息化十年发展规划》,强调＂应用驱动＂核心理念,本文探讨了临沭县通过＂网络学习空间人人通＂工程建设,全面推进教育信息化与教育教学管理相结合、与教育资源建设相结合、与学生素质提升相结合,实现了教育信息互联互通、教育资源共建共享,促进了教育教学管理方式的变革,提升了教育教学质量,有效促进了县域教育均衡协调持续发展。

Resource allocation method for device-to-device communications in cellular networks

Based on the conflict graph model which is formulated as a binary integer optimization problem, a resource allocation method to support device-to-device （D2D） communications in ceUular networks is proposed. First, a frequency resource assignment algorithm is presented which assigns each D2D link one frequency resource block. For this algorithm, frequency resource blocks are assigned so that the frequency resource spatial reuse opportunities in the cellular networks can be fully exploited. Then a slot scheduling algorithm is presented which schedules time slots among D2D links assigned the same frequency resource block. For this algorithm, time slot resources are scheduled so that the proportional fairness among D2D links which are assigned the same frequency resource block can be achieved. The performance of the proposed method is evaluated via computer simulations. The simulation results show that the proposed method can well support D2D communications in cellular networks.

Research and Implementation on HTTP Tunneling

The security problem of the Web system in the Internet based Intranet and the shortcomings of the methods used in solving this problem are analyzed and our system model of Web communication security are discussed, i.e, adding local proxy to browser and reverse proxy to Web server based on present Web browser and server. The transformation between HTTP message and secure HTTP message is implemented in these two proxy modules. The architecture and implementing method is given and the features of this module is also discussed.

(α,β)-constraints connected dominating set algorithm in wireless sensor network

To cope with the constraint problem of power consumption and transmission delay in the virtual backbone of wireless sensor network, a distributed connected dominating set （CDS） algorithm with （α,β）-constraints is proposed. Based on the （α, β）-tree concept, a new connected dominating tree with bounded transmission delay problem（CDTT） is defined and a corresponding algorithm is designed to construct a CDT-tree which can trade off limited total power and bounded transmission delay from source to destination nodes. The CDT algorithm consists of two phases： The first phase constructs a maximum independent set（MIS）in a unit disk graph model. The second phase estimates the distance and calculates the transmission power to construct a spanning tree in an undirected graph with different weights for MST and SPF, respectively. The theoretical analysis and simulation results show that the CDT algorithm gives a correct solution to the CDTF problem and forms a virtual backbone with（ α,β）-constraints balancing the requirements of power consumption and transmission delay.

Performance analysis of graph-based scheduling for device-to-device communications overlaying cellular networks

The performance of the graph-based scheduling for device-to-device communications overlaying cellular networks is studied. The graph-based scheduling consists of two stages, the frequency assignment stage and the time slot scheduling stage. For such scheduling, a theoretical method to analyze the average spectrum efficiency of the D2D subsystem is proposed. The method consists of three steps. First, the frequency assignment stage is analyzed and the approximate formula of the average number of the D2D links which are assigned the same frequency is derived. Secondly, the time slot scheduling stage is analyzed and the approximate formula of the average probability of a D2D link being scheduled in a time slot is derived. Thirdly, the average spectrum efficiency of the D2D subsystem is analyzed and the corresponding approximate formula is derived. Analysis results show that the average spectrum efficiency of the D2D subsystem is approximately inversely linearly proportional to the second- order origin moment of the normalized broadcast radius of D2D links. Simulation results show that the proposed method can correctly predict the average spectrum efficiency of the D2D subsystem.

Design and Realization of CPW Circuits Using EC-ANN Models for CPW Discontinuities

Novel accurate and efficient equivalent circuit trained artificial neural-network （EC-ANN） models,which inherit and improve upon EC model and EM-ANN models＇ advantages,are developed for coplanar waveguide （CPW） discontinuities. Modeled discontinuities include ： CPW step, interdigital capacitor, symmetric cross junction, and spiral inductor, for which validation tests are performed. These models allow for circuit design, simulation, and optimization within a CAD simulator. Design and realization of a coplanar lumped element band pass filter on GaAs using the developed CPW EC-ANN models are demonstrated.

STUDY ON SEAMLESS AND MULTILEVEL VPN

The virtual private network (VPN) system, which is one of the construction methods for private networks over the Internet, is gaining prominence. VPNs are currently used for corporate networks to support end to end communications. But if they are applied to private networks for distributed departments in organizations, some problems should be concerned, such as low efficiency of packet transfer and nonsupport of unsymmetrical VPN connections. At first this paper analyzes the limitations of VPN used in the environment of multiple subnets, and then brings up a distributed module of VPN with low cost, high packet transfer efficiency and powerful functions of user authentication and access control.

Cooperative algorithm for improving network connectivity in clustered wireless sensor networks

In order to improve network connectivity in clustered wireless sensor networks,a node cooperative algorithm based on virtual antenna arrays is proposed.All the nodes in the network are assumed to be clustered via Poisson Voronoi tessellation（PVT）.The activation of the node cooperative algorithm is determined by the cluster heads（CHs） according to communication links.When the cooperative algorithm is activated,the CH selects cooperative nodes（CNs） from its members to form a virtual antenna array.With the cooperation,nodes can extend the inter-cluster communication range to directly contact with further nodes after a coverage hole is detected,or compensate for channel gains while inter-cluster transmission fails due to deep channel fading.Simulation results show that the proposed algorithm achieves better network connectivity and energy efficiency.It can reduce outage probability,sustain network connectivity and maintain operations as long as possible,which prolongs network operation time.

Modeling of Intelligent Integrated Network Management System Using Object Oriented Approach *

The concept of intelligent integrated network management (IINM) is briefly introduced. In order to analyze, design and implement IINM successfully, object oriented approach is testified to be an effective and efficient way. In this paper, object oriented technique is applied to the structural model of IINM system, The Domain object class and the MU object class are used to represent the manager and the managed resources. Especially, NM IA is introduced which is a special object class with intelligent behaviors to manage the resources efficiently.

Analysis of Mine Ventilation Network Using Genetic Algorithm

Aim To determine the global optimal solution for a mine ventilation network under given network topology and airway characteristics. Methods\ The genetic algorithm was used to find the global optimal solution of the network. Results\ A modified genetic algorithm is presented with its characteristics and principle. Instead of working on the conventional bit by bit operation, both the crossover and mutation operators are handled in real values by the proposed algorithms. To prevent the system from turning into a premature problem, the elitists from two groups of possible solutions are selected to reproduce the new populations. Conclusion\ The simulation results show that the method outperforms the conventional nonlinear programming approach whether from the viewpoint of the number of iterations required to find the optimum solutions or from the final solutions obtained.

An efficient reliability evaluation method for industrial wireless sensor networks

Aimed at the difficulties in accurately, comprehensively and systematically evaluating the reliability of industrial wireless sensor networks （WSNs）, a time-evolving state transition-Monte Carlo （TEST-MC） evaluation method and a novel network function value representation method are proposed to evaluate the reliability of the IWSNs. First, the adjacency matrix method is used to characterize three typical topologies of WSNs including the mesh network, tree network and ribbon network. Secondly, the network function value method is used to evaluate the network connectivity, and the TEST-MC evaluation method is used to evaluate network reliability and availability. Finally, the variations in the reliability, connectivity and availability of these three topologies are presented. Simulation results show that the proposed method can quickly analyze the reliability of the networks containing typical WSN topologies, which provides an effective method for the comprehensive and accurate evaluation of the reliability of WSNs.

Distribution algorithm of entangled particles for wireless quantum communication mesh networks

With ensured network connectivity in quantum channels, the issue of distributing entangled particles in wireless quantum communication mesh networks can be equivalently regarded as a problem of quantum backbone nodes selection in order to save cost and reduce complexity. A minimum spanning tree（ MST）-based quantum distribution algorithm（ QDMST） is presented to construct the mesh backbone network. First, the articulation points are found,and for each connected block uncovered by the articulation points, the general centers are solved. Then, both articulation points and general centers are classified as backbone nodes and an M ST is formed. The quantum path between every two neighbor nodes on the MST is calculated. The nodes on these paths are also classified as backbone nodes. Simulation results validate the advantages of QDMST in the average backbone nodes number and average quantum channel distance compared to the existing random selection algorithm under multiple network scenarios.

Proactive traffic responsive control based on state-space neural network and extended Kalman filter

The state-space neural network and extended Kalman filter model is used to directly predict the optimal timing plan that corresponds to futuristic traffic conditions in real time with the purposes of avoiding the lagging of the signal timing plans to traffic conditions. Utilizing the traffic conditions in current and former intervals, the network topology of the state-space neural network （SSNN）, which is derived from the geometry of urban arterial routes, is used to predict the optimal timing plan corresponding to the traffic conditions in the next time interval. In order to improve the effectiveness of the SSNN, the extended Kalman filter （EKF） is proposed to train the SSNN instead of conventional approaches. Raw traffic data of the Guangzhou Road, Nanjing and the optimal signal timing plan generated by a multi-objective optimization genetic algorithm are applied to test the performance of the proposed model. The results indicate that compared with the SSNN and the BP neural network, the proposed model can closely match the optimal timing plans in futuristic states with higher efficiency.

Lazy loading algorithm for traffic assignment of road networks under fixed charge condition

The measures of path charge are important considerations in traffic assignment of road networks. Factors, such as travel time, fixed charge and traffic congestion which affect road users＇ choices of trip paths, are analyzed. Travelers usually decide their trip paths based on their personal habits, preferences and the information at hand. By considering both deterministic and stochastic factors which affect the value of time （VOT） during the process of path choosing, a variational inequality model is proposed to describe the problem of traffic assignment. A lazy loading algorithm for traffic assignment is designed to solve the proposed model, and the calculation steps are given. Numerical experiment results show that compared with the all-or-nothing assignment, the proposed model and the algorithm can provide more optimal traffic assignments for road networks. The results of this study can be used to optimize traffic planning and management.