Data-Driven Control of Distributed Event-Triggered Network Systems

The present paper deals with data-driven event-triggered control of a class of unknown discrete-time interconnected systems(a.k.a.network systems).To this end,we start by putting forth a novel distributed event-triggering transmission strategy based on periodic sampling,under which a model-based stability criterion for the closed-loop network system is derived,by leveraging a discrete-time looped-functional approach.Marrying the model-based criterion with a data-driven system representation recently developed in the literature,a purely data-driven stability criterion expressed in the form of linear matrix inequalities(LMIs)is established.Meanwhile,the data-driven stability criterion suggests a means for co-designing the event-triggering coefficient matrix and the feedback control gain matrix using only some offline collected state-input data.Finally,numerical results corroborate the efficacy of the proposed distributed data-driven event-triggered network system(ETS)in cutting off data transmissions and the co-design procedure.

Application of a neural network system combined with genetic algorithm to rank coalbed methane reservoirs in the order of exploitation priority

A new method based on the combination of a neural network and a genetic algorithm was proposed to rank the order of exploitation priority of coalbed methane reservoirs. The neural network was used to acquire the weights of reservoir parameters through sample training and genetic algorithm was used to optimize the initial connection weights of nerve cells in case the neural network fell into a local minimum. Additionally, subordinate functions of each parameter were established to normalize the actual values of parameters of coalbed methane reservoirs in the range between zero and unity. Eventually, evaluation values of all coalbed methane reservoirs could be obtained by using the comprehensive evaluation method, which is the basis to rank the coalbed methane reservoirs in the order of exploitation priority. The greater the evaluation value, the higher the exploitation priority. The ranking method was verified in this paper by ten exploited coalbed methane reservoirs in China. The evaluation results are in agreement with the actual exploitation cases. The method can ensure the truthfulness and credibility of the weights of parameters and avoid the subjectivity caused by experts. Furthermore, the probability of falling into local minima is reduced, because genetic the algorithm is used to optimize the neural network system.

Dependability in Future Battle Network System —Transport Layer Ability to Maintain Quality of Service

Modernization of armies is a constant process and is driven by intuitive fact that those who do not modernize will become extinct. In last five decades, the development of modern armies has taken place around Colonel John Boyd’s theory of OODA loop that deals with information superiority. Building a robust, mobile and capable network that could provide for novel appliances and information superiority is the main challenge which modernizers are facing. Network, suitable for future combat operations, and able to transport a vast amount of information on a battlefield, is expensive to build. Every mistake in design and the need to correct those mistakes could halt development in an army for years. Therefore, system dependability analysis during system design phase is needed. In this report, the concept of a future Battle Network System is described. The Report evaluates operational environment of BNS and possible failure reasons of the service, and illustrates the change in BNS Quality of Service due to probable transport layer errors. This paper describes the method of testing the concept of proposed network systems on the drawing board, and emphasizes design points for a new system. Nevertheless, the proposed method is by no means conclusive. Rather, it describes an engineering approach to define the main problems while creating MANET-based networking systems.

On-line Condition Monitoring and Diagnostic Network System for Rotating Machine Set

Several industrial computers and a server are combined to set up the on-line monitoring and diagnostic system of turbo-generator sets. The main function of the system is to monitor machine sets' running condition. Through analyzing running data, technicians can detect whether there exist faults and where they occur. To share and transmit the dynamic information of the turbo-generator sets, a distributed network system is introduced. NetWare network operating system is used in the LAN (Local Area Network) system. The LAN is extended to realize the sharing of data and remote transmission of information. Furthermore, functions of monitoring and diagnostic clients are listed.

LONG-TIME BEHAVIOR OF TRANSIENT SOLUTIONS FOR CELLULAR NEURAL NETWORK SYSTEMS

By establishing concept an transient solutions of general nonlinear systems converging to its equilibrium set, long-time behavior of solutions for cellular neural network systems is studied. A stability condition in generalized sense is obtained. This result reported has an important guide to concrete neural network designs.

Information Network System for WDCDS/NCSDI

World Data Center-D for Seismology(WDCDS)is a member of the World Data Center System under ICSU and is one of the nine World Data Centers located in China(WDC-D).During the period from 1993 to 1996,an information network system,called CSDInet,was developed in National Center for Seismic Data and Information(NCSDI)and has become the basic technical supporting system for WDC-D for Seismology.CSDInet consists of four basic parts:computer network center,LAN(Local Area Network),link to Internet,and nationwide PSTN(with dialing-up telephone line)user network.In this paper a "multi-layer multi-mode" management of data flow for this system will be explained and the data and information services will be described.

The Construction of Applied Writing Training Network System

This document explains and demonstrates how to construct the applied writing training in network system. This system which is used in network consists of four modules, including task module, structure training module, text training module and study evaluation module. With the advantages of instantaneity, interactivity, authenticity and adequation of learning resources, the applied writing abilities of the students can be improved effectively by using the network system. And the problems during the process of applied writing teaching, for example, the teaching contents lose contract with social life, the textbook contents are lack of innovation, and writing training goes against cognizing system, can be solved effectively.

Modeling and Stability Analysis of a Communication Network System

In this work, the modeling and stability problem for a communication network system is addressed. The communication network system consists of a transmitter which sends messages to a receiver. The proposed model considers two possibilities. The first one, that messages are successfully received, while in the second one, during the sending process the transmitter breaks down and as a result the message does not reach the receiver. Timed Petrinets is the mathematical and graphical modeling technique utilized. Lyapunov stability theory provides the required tools needed to aboard the stability problem. Employing Lyapunov methods, a sufficient condition for stabilization is obtained. It is shown that it is possible to restrict the communication network system state space in such a way that boundedness is guaranteed. However, this restriction results to be vague. This inconvenience is overcome by considering a specific recurrence equation, in the max-plus algebra, which is assigned to the timed Petri net graphical model.

China’s Global Space-based TT&C Network System Established

The Tianlian 1-03 satellite, the third geosynchronous data relay satellite of China, was successfully launched into space on a LM-3C launch vehicle from the Xichang Satellite Launch Center at 23:43 Beijing time on July 25. Twenty-six minutes after the liftoff, the satellite

Reliability Evaluation of Two-Stage Directed Semi-Markov Repairable Network Systems

A two-stage directed Semi-Markov repairable network system is presented in this paper to model the performance of many transmission systems, such as power or oil transmission network, water or gas supply network, etc. The availability of the system is discussed by using Markov renewal theory, Laplace transform and probability analysis methods. A numerical example is given to illustrate the results obtained in the paper.

Application of Windows Socket Technique to Communication Process of the Train Diagram Network System Based on Client/Server Structure

This paper is focused on the technique for de si gn and realization of the process communications about the computer-aided train diagram network system. The Windows Socket technique is adopted to program for the client and the server to create system applications and solve the problems o f data transfer and data sharing in the system.

Development of an integrated dynamic model for supply security and resilience analysis of natural gas pipeline network systems

An integrated dynamic model of natural gas pipeline networks is developed in this paper.Components for gas supply,e.g.,pipelines,junctions,compressor stations,LNG terminals,regulation stations and gas storage facilities are included in the model.These components are firstly modeled with respect to their properties and functions and,then,integrated at the system level by Graph Theory.The model can be used for simulating the system response in different scenarios of operation,and evaluate the consequences from the perspectives of supply security and resilience.A case study is considered to evaluate the accuracy of the model by benchmarking its results against those from literature and the software Pipeline Studio.Finally,the model is applied on a relatively complex natural gas pipeline network and the results are analyzed in detail from the supply security and resilience points of view.The main contributions of the paper are:firstly,a novel model of a complex gas pipeline network is proposed as a dynamic state-space model at system level;a method,based on the dynamic model,is proposed to analyze the security and resilience of supply from a system perspective.

A hybrid neural network system for prediction and recognition of promoter regions in human genome

This paper proposes a high specificity and sensitivity algorithm called PromPredictor for recognizing promoter regions in the human genome. PromPredictor extracts compositional features and CpG islands information from genomic sequence,feeding these features as input for a hybrid neural network system (HNN) and then applies the HNN for prediction. It combines a novel promoter recognition model, coding theory, feature selection and dimensionality reduction with machine learning algorithm.Evaluation on Human chromosome 22 was ～66% in sensitivity and ～48% in specificity. Comparison with two other systems revealed that our method had superior sensitivity and specificity in predicting promoter regions. PromPredictor is written in MATLAB and requires Matlab to run. PromPredictor is freely available at http://www.whtelecom.com/Prompredictor.htm.

Analysis on Design of Kohonen-network System Based on Classification of Complex Signals

The key methods of detection and classification of the electroencephalogram(EEG) used in recent years are introduced . Taking EEG for example, the design plan of Kohonen neural network system based on detection and classification of complex signals is proposed, and both the network design and signal processing are analyzed, including pre-processing of signals, extraction of signal features, classification of signal and network topology, etc.

Development and application of a GIS-based artificial neural network system for water quality prediction: a case study at the Lake Champlain area

Artificial Neural Network(ANN)models have been extensively applied in the prediction of water resource variables,and Geographical Information System(GIS)includes powerful functions to visualize spatial data.In order to provide an efficient tool for environmental assessment and management that combines the advantages of these two modules,a GIS-based ANN water quality prediction system was developed in the present study.The ANN module and ArcGIS Engine module,along with a dynamic database,were imbedded in the system,which integrates water quality prediction via the ANN model and spatial presentation of the model results.The structure of the ANN model could be modified through the graphical user interface to optimize the model performance.The developed system was applied to a real case study for the prediction of the total phosphorus concentration in the Lake Champlain area.The prediction results were verified with the monitoring data,and the performance of the developed model was further evaluated through graphical techniques and quantitative statistical methods.Overall,the developed system provided satisfactory prediction results,and spatial distribution maps of the predicted results were obtained,which coincided with the monitored values.The developed GIS-based ANN water quality prediction system could serve as an efficient tool for engineers and decision makers.

The Design of Wireless Sensor Network System based on ZigBee Technology

The paper design hardware platform based on network node, and analyze ZigBee protocol architecture and standards of each layer; on based of ZigBee protocol stack, we design the application program of network coordinator and terminal node to realize the data acquisition; design of network system has the characteristics of low cost, small volume, test results show that the mesh topology, network support, can be rapidly deployed, temperature, humidity, light intensity information of the smooth reading environment, that can be used for domestic environmental monitoring field.

Hierarchical Modeling by Recursive Unsupervised Spectral Clustering and Network Extended Importance Measures to Analyze the Reliability Characteristics of Complex Network Systems

The complexity of large-scale network systems made of a large number of nonlinearly interconnected components is a restrictive facet for their modeling and analysis. In this paper, we propose a framework of hierarchical modeling of a complex network system, based on a recursive unsupervised spectral clustering method. The hierarchical model serves the purpose of facilitating the management of complexity in the analysis of real-world critical infrastructures. We exemplify this by referring to the reliability analysis of the 380 kV Italian Power Transmission Network (IPTN). In this work of analysis, the classical component Importance Measures (IMs) of reliability theory have been extended to render them compatible and applicable to a complex distributed network system. By utilizing these extended IMs, the reliability properties of the IPTN system can be evaluated in the framework of the hierarchical system model, with the aim of providing risk managers with information on the risk/safety significance of system structures and components.

Network systems biology for targeted cancer therapies

The era of targeted cancer therapies has arrived.However,due to the complexity of biological systems,the current progress is far from enough.From biological network modeling to structural/dynamic network analysis,network systems biology provides unique insight into the potential mechanisms underlying the growth and progression of cancer cells.It has also introduced great changes into the research paradigm of cancer-associated drug discovery and drug resistance.

Application of Global Dynamic Reconfiguration in Artificial Neural Network System based on Field Programmable Gate Array

Presented is a global dynamic reconfiguration design of an artificial neural network based on field programmable gate array(FPGA). Discussed are the dynamic reconfiguration principles and methods. Proposed is a global dynamic reconfiguration scheme using Xilinx FPGA and platform flash. Using the revision capabilities of Xilinx XCF32P platform flash, an artificial neural network based on Xilinx XC2V30P Virtex-Ⅱ can be reconfigured dynamically from back propagation(BP) learning algorithms to BP network testing algorithms. The experimental results indicate that the scheme is feasible, and that, using dynamic reconfiguration technology, FPGA resource utilization can be reduced remarkably.

Calculation of the Behavior Utility of a Network System： Conception and Principle

The service and application of a network is a behavioral process that is oriented toward its operations and tasks, whose metrics and evaluation are still somewhat of a rough comparison, This paper describes sce- nes of network behavior as differential manifolds, Using the homeomorphic transformation of smooth differential manifolds, we provide a mathematical definition of network behavior and propose a mathe- matical description of the network behavior path and behavior utility, Based on the principle of differen- tial geometry, this paper puts forward the function of network behavior and a calculation method to determine behavior utility, and establishes the calculation principle of network behavior utility, We also provide a calculation framework for assessment of the network＇s attack-defense confrontation on the strength of behavior utility, Therefore, this paper establishes a mathematical foundation for the objective measurement and precise evaluation of network behavior,