Chain-type wireless sensor network node scheduling strategy

In order to reduce power consumption of sensor nodes and extend network survival time in the wireless sensor network （WSN）, sensor nodes are scheduled in an active or dormant mode. A chain-type WSN is fundamental y different from other types of WSNs, in which the sensor nodes are deployed along elongated geographic areas and form a chain-type network topo-logy structure. This paper investigates the node scheduling prob-lem in the chain-type WSN. Firstly, a node dormant scheduling mode is analyzed theoretical y from geographic coverage, and then three neighboring nodes scheduling criteria are proposed. Sec-ondly, a hybrid coverage scheduling algorithm and dead areas are presented. Final y, node scheduling in mine tunnel WSN with uniform deployment （UD）, non-uniform deployment （NUD） and op-timal distribution point spacing （ODS） is simulated. The results show that the node scheduling with UD and NUD, especial y NUD, can effectively extend the network survival time. Therefore, a strat-egy of adding a few mobile nodes which activate the network in dead areas is proposed, which can further extend the network survival time by balancing the energy consumption of nodes.     

Multi-agent consensus with time-varying delays and switching topologies

The consensus problems of multi-agents with time-varying delays and switching topologies are studied. First, assume that an agent receives state information from its neighbors with fixed communication delays and processes its own state information with time-varying self-delay respectively. The state time-delay feedback is introduced into the existing consensus protocol to begenerate an improved protocol. Then a sufficient condition is derived which can make the system with time-varying self-delays achieve the consensus. On this basis, a specific form of consensus equilibrium influenced by the initial states of agents, time-delays and state feedback intensity is figured out. In addition, the multi-agent consensus is considered with time-varying topologies. Finally, simulations are presented to il ustrate the validity of theoretical results.     

Ripple-effect analysis for operational architecture of air defense systems with supernetwork modeling

In order to solve the problem that the ripple-effect analy- sis for the operational architecture of air defense systems （OAADS） is hardly described in quantity with previous modeling approaches, a supernetwork modeling approach for the OAADS is put for- ward by extending granular computing. Based on that operational units and links are equal to different information granularities, the supernetwork framework of the OAADS is constructed as a “four- network within two-layer” structure by forming dynamic operating coalitions, and measuring indexes of the ripple-effect analysis for the OAADS are given combining with Laplace spectral radius. In this framework, via analyzing multidimensional attributes which inherit relations between operational units in different granular scales, an extended granular computing is put forward integrating with a topological structure. Then the operation process within the supernetwork framework, including transformation relations be- tween two layers in the vertical view and mapping relations among functional networks in the horizontal view, is studied in quantity. As the application case shows, comparing with previous modeling approaches, the supernetwork model can validate and analyze the operation mechanism in the air defense architecture, and the ripple-effect analysis can be used to confirm the key operational unit with micro and macro viewpoints.     

Comprehensive multivariate grey incidence degree based on principal component analysis

To overcome the too fine-grained granularity problem of multivariate grey incidence analysis and to explore the comprehensive incidence analysis model, three multivariate grey incidences degree models based on principal component analysis （PCA） are proposed. Firstly, the PCA method is introduced to extract the feature sequences of a behavioral matrix. Then, the grey incidence analysis between two behavioral matrices is transformed into the similarity and nearness measure between their feature sequences. Based on the classic grey incidence analysis theory, absolute and relative incidence degree models for feature sequences are constructed, and a comprehensive grey incidence model is proposed. Furthermore, the properties of models are researched. It proves that the proposed models satisfy the properties of translation invariance, multiple transformation invariance, and axioms of the grey incidence analysis, respectively. Finally, a case is studied. The results illustrate that the model is effective than other multivariate grey incidence analysis models.     

EXISTENCE AND ANALYTICAL APPROXIMATIONS OF LIMIT CYCLES IN A THREE-DIMENSIONAL NONLINEAR AUTONOMOUS FEEDBACK CONTROL SYSTEM

This paper is concerned with the existence and the analytical approximations of limit cycles in a three-dimensional nonlinear autonomous feedback control system. Based on three-dimensional Hopf bifurcation theorem, the existence of limit cycles is first proved. Then the homotopy analysis method （HAM） is applied to obtain the analytical approximations of the limit cycle and its frequency. In deriving the higher-order approximations, the authors utilized the idea of a perturbation procedure proposed for limit cycles＇ approximation in van der Pol equation. By comparing with the numerical integration solutions, it is shown that the accuracy of the analytical results obtained in this paper is very high, even when the amplitude of the limit cycle is large.     

Performance evaluation from stochastic statecharts repre-sentation of flexible reactive systems：a simulation approach

This paper focuses on the performance analysis of flexible reactive systems. The performance analysis consists of two phases： first system modeling, second performance evalua-tion. The paper models the flexible reactive system by the stochas-tic statecharts method, and uses the simulation method to evalu-ate the performance. To make use of the feature of event-triggered state transitions in the statecharts, a new method of simulation is proposed based on the techniques of the discrete-event system simulation. The new method solves the problem of computer imple-mentation of stochastic events, probabilistic transition, concurrent states, paral el actions, and broadcast communication mechanism in the stochastic statecharts. An example of a flexible manufactur-ing system is presented. The simulation result of the example is consistent with the analytical result, which shows the feasibility of the proposed new simulation method.     

Self-alignment of full skewed RSINS：observability analysis and full-observable Kalman filter

Traditional orthogonal strapdown inertial navigation sys-tem （SINS） cannot achieve satisfactory self-alignment accuracy in the stationary base： taking more than 5 minutes and al the iner-tial sensors biases cannot get ful observability except the up-axis accelerometer. However, the ful skewed redundant SINS （RSINS） can not only enhance the reliability of the system, but also improve the accuracy of the system, such as the initial alignment. Firstly, the observability of the system state includes attitude errors and al the inertial sensors biases are analyzed with the global perspective method： any three gyroscopes and three accelerometers can be assembled into an independent subordinate SINS （sub-SINS）;the system state can be uniquely confirmed by the coupling connec-tions of al the sub-SINSs;the attitude errors and random constant biases of al the inertial sensors are observable. However, the ran-dom noises of the inertial sensors are not taken into account in the above analyzing process. Secondly, the ful-observable Kalman filter which can be applied to the actual RSINS containing random noises is established; the system state includes the position, ve-locity, attitude errors of al the sub-SINSs and the random constant biases of the redundant inertial sensors. At last, the initial self-alignment process of a typical four-redundancy ful skewed RSINS is simulated： the horizontal attitudes （pitch, rol ） errors and yaw error can be exactly evaluated within 80 s and 100 s respectively, while the random constant biases of gyroscopes and accelero-meters can be precisely evaluated within 120 s. For the ful skewed RSINS, the self-alignment accuracy is greatly improved, mean-while the self-alignment time is widely shortened.     

Novel magnetic field computation model in pattern classification

Field computation, an emerging computation technique, has inspired passion of intelligence science research. A novel field computation model based on the magnetic field theory is constructed. The proposed magnetic field computation （MFC） model consists of a field simulator, a non-derivative optimization algo- rithm and an auxiliary data processing unit. The mathematical model is deduced and proved that the MFC model is equivalent to a quadratic discriminant function. Furthermore, the finite element prototype is derived, and the simulator is developed, combining with particle swarm optimizer for the field configuration. Two benchmark classification experiments are studied in the numerical experiment, and one notable advantage is demonstrated that less training samples are required and a better generalization can be achieved.     

Response surface method using grey relational analysis for decision making in weapon system selection

A proper weapon system is very important for a na- tional defense system. Generally, it means selecting the optimal weapon system among many alternatives, which is a multiple- attribute decision making （MADM） problem. This paper proposes a new mathematical model based on the response surface method （RSM） and the grey relational analysis （GRA）. RSM is used to obtain the experimental points and analyze the factors that have a significant impact on the selection results. GRA is used to an- alyze the trend relationship between alternatives and reference series. And then an RSM model is obtained, which can be used to calculate all alternatives and obtain ranking results. A real world application is introduced to illustrate the utilization of the model for the weapon selection problem. The results show that this model can be used to help decision-makers to make a quick comparison of alternatives and select a proper weapon system from multiple alternatives, which is an effective and adaptable method for solving the weapon system selection problem.     

Computational mission analysis and conceptual system design for super low altitude satellite

This paper deals with system engineering and design methodology for super low altitude satel ites in the view of the com-putational mission analysis. Due to the slight advance of imaging instruments, such as the focus of camera and the image element of charge coupled device （CCD）, it is an innovative and economical way to improve the camera’s resolution to enforce the satel ite to fly on the lower altitude orbit. DFH-3, the mature satel ite bus de-veloped by Chinese Academy of Space Technology, is employed to define the mass and power budgets for the computational mis-sion analysis and the detailed engineering design for super low altitude satel ites. An effective iterative algorithm is proposed to solve the ergodic representation of feasible mass and power bud-gets at the flight altitude under constraints. Besides, boundaries of mass or power exist for every altitude, where the upper boundary is derived from the maximum power, while the minimum thrust force holds the lower boundary before the power reaching the initial value. What’s more, an analytical algorithm is employed to numerical y investigate the coverage percentage over the altitude, so that the nominal altitude could be selected from al the feasi-ble altitudes based on both the mass and power budgets and the repetitive ground traces. The local time at the descending node is chosen for the nominal sun-synchronous orbit based on the average evaluation function. After determining the key orbital ele-ments based on the computational mission analysis, the detailed engineering design on the configuration and other subsystems, like power, telemetry telecontrol and communication （TT＆amp;C）, and attitude determination and control system （ADCS）, is performed based on the benchmark bus, besides, some improvements to the bus are also implemented to accommodate the flight at a super low altitude. Two operation strategies, drag-free closed-loop mode and on/off open-loop mode, are presented to maintain the satel-lite’s altitude. Final y, a flight planning schedule for the satel ite is demonstrated from its launch into the initial altitude at the very beginning to its decay to death in the end.     

WHO WON THE 2008 OLYMPICS？ A MULTICRITERIA DECISION OF MEASURING INTANGIBLES

It often happens that at the end of Olympics games the medals won by more than one country are many and close in total number as in the 2008 games where China won 100 medals with many gold ones and the United States won 110 medals but with a lesser number of gold medals. The question is： Although it is often done arbitrarily, is there a way to quantify the values of gold, silver and bronze medals legitimately to resolve this concern？ This short exposition shows that there is by using the author＇s theory for the measurement of intangibles, the Analytic Hierarchy Process.     

Asymptotic and stable proper ties of general stochastic functional differential equations

The asymptotic and stable properties of general stochastic functional differential equations are investigated by the multiple Lyapunov function method, which admits non-negative up-per bounds for the stochastic derivatives of the Lyapunov functions, a theorem for asymptotic properties of the LaSal e-type described by limit sets of the solutions of the equations is obtained. Based on the asymptotic properties to the limit set, a theorem of asymptotic stability of the stochastic functional differential equations is also established, which enables us to construct the Lyapunov functions more easily in application. Particularly, the wel-known classical theorem on stochastic stability is a special case of our result, the operator LV is not required to be negative which is more general to fulfil and the stochastic perturbation plays an important role in it. These show clearly the improvement of the traditional method to find the Lyapunov functions. A numerical simulation example is given to il ustrate the usage of the method.     

Interactive multigraph visualization and exploration with a two-phase strategy

While it is very reasonable to use a multigraph consisting of multiple edges between vertices to represent various relationships, the multigraph has not drawn much attention in research. To visualize such a multigraph, a clear layout representing a global structure is of great importance, and interactive visual analysis which allows the multiple edges to be adjusted in appropriate ways for detailed presentation is also essential. A novel interactive two-phase approach to visualizing and exploring multigraph is proposed. The approach consists of two phases： the first phase improves the previous popular works on force-directed methods to produce a brief drawing for the aggregation graph of the input multigraph, while the second phase proposes two interactive strategies, the magnifier model and the thematic-oriented subgraph model. The former highlights the internal details of an aggregation edge which is selected interactively by user, and draws the details in a magnifying view by cubic Bezier curves; the latter highlights only the thematic subgraph consisting of the selected multiple edges that the user concerns. The efficiency of the proposed approach is demonstrated with a real-world multigraph dataset and how it is used effectively is discussed for various potential applications.     

Adaptive actuator failure compensation and disturbance rejection scheme for spacecraft

An adaptive actuator failure compensation scheme is proposed for attitude tracking control of spacecraft with unknown disturbances and uncertain actuator failures. A new feature of this adaptive control scheme is the adaptation of the failure pattern parameter estimates, as well as the failure signal parameter estimates, for direct adaptive actuator failure compensation. Based on an adaptive backstepping control design, the estimates of the disturbance parameters are used to solve the disturbance rejection problem. The unknown disturbances are compensated completely with the stability of the whole closed-loop system. The scheme is not only able to accommodate uncertain actuator failures, but also robust against unknown external disturbances. Simulation results verify the desired adaptive actuator failure compensation performance.     

FAMILIES OF p-ARY SEQUENCES WITH LOW CORRELATION AND LARGE LINEAR COMPLEXITY

This paper generalizes a method of generating shift sequences in the interleaved construc- tion proposed by Gong. With the new shift sequences, some new families of p-ary sequences with desired properties can be obtained. A lower bound on the number of new families of binary sequences is also established.     

Spectral analysis and stabilization of a coupled wave-ODE system

In this paper, an interconnected wave-ODE system with K-V damping in the wave equation and unknown parameters in the ODE is considered. It is found that the spectrum of the system operator is composed of two parts： Point spectrum and continuous spectrum. The continuous spectrum consists of an isolated point 1 1/d, and there are two branches of the asymptotic eigenvalues： The first branch is accumulating towards 1 -2, and the other branch tends to -∞. It is shown that there is a sequence of generalized eigenfunctions, which forms a Riesz basis for the Hilbert state space. As a consequence, the spectrum-determined growth condition and exponential stability of the system are concluded.     

Spiking neural P systems with anti-spikes and without annihilating priority as number acceptors

Spiking neural P systems with anti-spikes （ASN P systems） are variant forms of spiking neural P systems, which are inspired by inhibitory impulses/spikes or inhibitory synapses. The typical feature of ASN P systems is when a neuron contains both spikes and anti-spikes, spikes and anti-spikes wil immediately annihilate each other in a maximal way. In this paper, a restricted variant of ASN P systems, cal ed ASN P systems without anni-hilating priority, is considered, where the annihilating rule is used as the standard rule, i.e., it is not obligatory to use in the neuron associated with both spikes and anti-spikes. If the annihilating rule is used in a neuron, the annihilation wil consume one time unit. As a result, such systems using two categories of spiking rules （identified by （a, a） and （a,a^-）） can achieve Turing completeness as number accepting devices.     

Optimal binary codes from one-lee weight codes and two-lee weight projective codes over ℤ4

This paper investigates the structures and properties of one-Lee weight codes and two-Lee weight projective codes over Z4.The authors first give the Pless identities on the Lee weight of linear codes over Z4.Then the authors study the necessary conditions for linear codes to have one-Lee weight and two-Lee projective weight respectively,the construction methods of one-Lee weight and two-Lee weight projective codes over Z4 are also given.Finally,the authors recall the weight-preserving Gray map from（Z4n,Lee weight）to（F2（2n）,Hamming weight）,and produce a family of binary optimal oneweight linear codes and a family of optimal binary two-weight projective linear codes,which reach the Plotkin bound and the Griesmer bound.     

Robust bounded control for uncertain flight dynamics using disturbance observer

The robust bounded flight control scheme is developed for the uncertain longitudinal flight dynamics of the fighter with control input saturation invoking the backstepping technique. To enhance the disturbance rejection ability of the robust flight control for fighters, the sliding mode disturbance observer is designed to estimate the compounded disturbance including the unknown external disturbance and the effect of the control input saturation. Based on the backstepping technique and the compounded disturbance estimated output, the robust bounded flight control scheme is proposed for the fighter with the unknown external disturbance and the control input saturation. The closed-loop system stability under the developed robust bounded flight control scheme is rigorously proved using the Lyapunov method and the uniformly asymptotical convergences of all closed-loop signals are guaranteed. Finally, simulation results are presented to show the effectiveness of the proposed robust bounded flight control scheme for the uncertain longitudinal flight dynamics of the fighter.     

Exact inference for two exponential populations with competing risks data

In a reliability comparative test, the joint censoring model is usually adopted to evaluate the performances of units with the same facility. However, most researchers ignore the pos- sibility that there is more than one factor for the failure when a test unit fails. To solve this problem, we consider a joint Type-II hybrid censoring model for the analysis of exponential competing failure data. Based on the maximum likelihood theory, we compute the maximum likelihood estimators （MLEs） of parameters and then obtain the condition ensuring MLEs existence for every unknown parameter. Then we derive the conditional exact distributions and corresponding moment properties for parameters by the moment generating function （MGF）. A Monte-Carlo simulation is conducted to compare the performances of different ways. And finally, we conduct a numerical example to illustrate the proposed method.