Collaborative optimization of maintenance and spare ordering of continuously degrading systems

A collaborative optimization model for maintenance and spare ordering of a single-unit degrading system is proposed in this paper based on the continuous detection. A gamma distribution is used to model the material degradation. The degrading decrement after the imperfect maintenance action is assumed as a random variable normal distribution. This model aims to ob- tain the optimal maintenance policy and spare ordering point with the expected cost rate within system lifecycle as the optimization objective. The rationality and feasibility of the model are proved through a numerical example.

Heuristics Scheduling Algorithm on the Links Scheduling of Satellite-Ground Clock Synchronization and Ephemeris Uploading in COMPASS System

The execution process of satellite-ground clock synchronization and ephemeris uploading in the system is analyzed,as well as their characterized operation and their relationship.Based on the analysis of the scheduling goal and constraint character,a heuristics rule-based multi-stage link scheduling algorithm was put forward.The algorithm distinguishes the on-off-frontier satellites from the others and schedules them by turns.The paper presented the main flow as well as the detailed design of the rule.Finally based on the current COMPASS global system,some typical resources and constraints are selected to generate an instance.Then the comparison analysis between the heuristics scheduling algorithm and three other traditional scheduling strategies are carried out.The result shows the validity and reasonability of the multi-stage strategy.

Research on Collaboration Decision Design of Complex C2 System

The design of collaboration decision of C2 system is one of the puzzles which dicision science studies in complex system. To solve the contravention between the theory of collaboration decision design and development requirement in distributed C2 system,three-stage design approach is proposed to research coherence and optimization by which decision-maker carries out decision regulations. First,getting information and decision process are described; decision indexes and regulation models of collaboration are established. And then,a test circumstance is designed and established for measuring various decision-maker’s capabilities of carrying out decision regulation by simulation and getting their load capability parameters. Finally,the obtained parameters from the experiment are disposed and substituted into the original models for proving the coherence of decision regulations. As a result,it is feasible for three-stage approach to design collaboration decision,and decision regulations can satisfy various decision-maker requirements.

Global Mission Sensitivity Study for Phased MissionSystem with Analysis of Variance Method

A comprehensive mission sensitivity analysis index based on Sobol's index called global mission sensitivity( GMS) was proposed in this paper which focused on analyzing the mission sensitivity of components of phased mission systems( PMS). The simulation strategy of GMS based on a Petri net and Monte Carlo method was presented which had broad applicability. Finally,the GMS and Birnbaum's sensitivity of components in a PMS example were compared. The GMS of component is demonstrated to be more adaptable to reflect the component mission sensitivity when the rated reliability parameters of components cannot be obtained, and components have state dependency or the system is subjected to common cause failure.

IDENTIFICATION OF INPAINTED IMAGES AND NATURAL IMAGES FOR DIGITAL FORENSICS

Image forensics is a form of image analysis for finding out the condition of an image in the complete absence of any digital watermark or signature.It can be used to authenticate digital images and identify their sources.While the technology of exemplar-based inpainting provides an approach to remove objects from an image and play visual tricks.In this paper, as a first attempt, a method based on zero-connectivity feature and fuzzy membership is proposed to discriminate natural images from inpainted images.Firstly, zero-connectivity labeling is applied on block pairs to yield matching degree feature of all blocks in the region of suspicious, then the fuzzy memberships are computed and the tampered regions are identified by a cut set.Experimental results demonstrate the effectiveness of our method in detecting inpainted images.

Framework for a System of Systems Design Oriented to Evolution

A framework was proposed for designing a system of systems(SoS) that takes account of the system' s evolution over time.Given the design space of the SoS analysis,construct a multiepoch scenario design,SoS optimization,and robust designs.A hybrid model based on multi-agent and system dynamic models was used to analyze the evolution of an SoS and find robust designs.The framework can help decision makers generate a robust SoS structure based on the SoS' s capabilities over multiple epochs.

Optimal maintenance decisions for gamma deteriorating systems

An optimal replacement model for gamma deteriorating systems is studied. This methodology uses a gamma distribution to model the material degradation, and the impact of imperfect maintenance actions on the system reliability is investigated. The state of a degrading system immediately after the imperfect maintenance action is assumed as a random variable and the maintenance time follows a geometric process. A maintenance policy （N） is applied by which the system will be repaired whenever it experiences Nth preventive maintenance （PM）, and an optimal policy （N＊） could be determined numerically or analytically for minimizing the long-run average cost per unit time. Finally, a numerical example is presented to demonstrate the use of this policy.

Time Optimization of Multiple Knowledge Transfers in the Big Data Environment

In the big data environment, enterprises must constantly assimilate big dataknowledge and private knowledge by multiple knowledge transfers to maintain theircompetitive advantage. The optimal time of knowledge transfer is one of the mostimportant aspects to improve knowledge transfer efficiency. Based on the analysis of thecomplex characteristics of knowledge transfer in the big data environment, multipleknowledge transfers can be divided into two categories. One is the simultaneous transferof various types of knowledge, and the other one is multiple knowledge transfers atdifferent time points. Taking into consideration the influential factors, such as theknowledge type, knowledge structure, knowledge absorptive capacity, knowledge updaterate, discount rate, market share, profit contributions of each type of knowledge, transfercosts, product life cycle and so on, time optimization models of multiple knowledgetransfers in the big data environment are presented by maximizing the total discountedexpected profits (DEPs) of an enterprise. Some simulation experiments have beenperformed to verify the validity of the models, and the models can help enterprisesdetermine the optimal time of multiple knowledge transfer in the big data environment.

Study on semantic-oriented hybrid indexing strategy of resource metadata in peer-to-peer network

Applying ontology to describe resource metadata richly in the peer-to-peer environment has become current research trend. In this semantic peer-to-peer environment, indexing semantic element of resource description to support efficient resource location is a difficult and challenging problem. This paper provided a hybrid indexing architecture, which combines local indexing and global indexing. It uses community strategy and semantic routing strategy to organize key layer metadata element and uses DHT (distributed hash table) to index extensional layer metadata element. Compared with related system, this approach is more efficient in resource location and more scalable.

Influence of Missile Fusillade Engagement Mode on Operation Efficiency

Shoot efficiency is one of the most important evaluation indexes of the operation efficiency of weapon system.In this paper,based on definitions of the probability and the expected number of missed attacking missiles,the expected numbers of anti-missiles and attacking missiles hit by single anti-missile,fusillade mechanism of multi-missile is analyzed systematically.The weapon operation efficiency in various engagement patterns is also studied.The results show that double missiles fusillade is the most feasible manner for increasing the weapon operation efficiency.

Estimation of transition redshift based on Reinsch splines

Many schemes have been proposed to define a model-independent con- straint on cosmological dynamics, such as the nonparametric dark energy equation of state ω（z） or the deceleration parameter q（z）. These methods usually contain deriva- tives with respect to observational data with noise. However, there can be large un- certainties when one estimates values with numerical differentiation, especially when noise is significant. We introduce a global numerical differentiation method, first for- mulated by Reinsch, which is smoothed by cubic spline functions, and apply it to the estimation of the transition redshift zt with a simulated expansion rate E（z） based on observational Hubble parameter data. We also discuss some deficiencies and limita-tions of this method.

Scenario-based approach for project portfolio selection in army engineering and manufacturing development

The decisions concerning portfolio selection for army engineering and manufacturing development projects determine the benefit of those projects to the country concerned.Projects are typically selected based on ex ante estimates of future return values,which are usually difficult to specify or only generated after project launch.A scenario-based approach is presented here to address the problem of selecting a project portfolio under incomplete scenario information and interdependency constraints.In the first stage,the relevant dominance concepts of scenario analysis are studied to handle the incomplete information.Then,a scenario-based programming approach is proposed to handle the interdependencies to obtain the projects,whose return values are multi-criteria with interval data.Finally,an illustrative example of army engineering and manufacturing development shows the feasibility and advantages of the scenario-based multi-objective programming approach.

Handling epistemic uncertainties in PRA using evidential networks

In order to overcome the limitations of traditional methods in uncertainty analysis, a modified Bayesian network(BN), which is called evidence network(EN), was proposed with evidence theory to handle epistemic uncertainty in probabilistic risk assessment(PRA). Fault trees(FTs) and event trees(ETs) were transformed into an EN which is used as a uniform framework to represent accident scenarios. Epistemic uncertainties of basic events in PRA were presented in evidence theory form and propagated through the network. A case study of a highway tunnel risk analysis was discussed to demonstrate the proposed approach. Frequencies of end states are obtained and expressed by belief and plausibility measures. The proposed approach addresses the uncertainties in experts' knowledge and can be easily applied to uncertainty analysis of FTs/ETs that have dependent events.

Sliding mode control of solid state transformer using a three-level hysteresis function

The solid state transformer(SST) can be viewed as an energy router in energy internet. This work presents sliding mode control(SMC) to improve dynamic state and steady state performance of a three-stage(rectifier stage, isolated stage and inverter stage) SST for energy internet. SMC with three-level hysteresis sliding functions is presented to control the input current of rectifier stage and output voltage of inverter stage to improve the robustness under external disturbance and parametric uncertainties and reduce the switching frequency. A modified feedback linearization technique using isolated stage simplified model is presented to achieve satisfactory regulation of output voltage of the isolated stage. The system is tested for steady state operation, reactive power control, dynamic load change and voltage sag simulations, respectively. The switching model of SST is implemented in Matlab/ Simulink to verify the SST control algorithms.

Flocking behavior with multiple leaders and global trajectory

Aiming at the group of autonomous agents consisting of multiple leader agents and multiple follower ones,a flocking behavior method with multiple leaders and a global trajectory was proposed.In this flocking method,the group leaders can attain the information of the global trajectory,while each follower can communicate with its neighbors and corresponding leader but does not have global knowledge.Being to a distributed control method,the proposed method firstly sets a movable imaginary point on the global trajectory to ensure that the center and average velocity of the leader agents satisfy the constraints of the global trajectory.Secondly,a two-stage strategy was proposed to make the whole group satisfy the constraints of the global trajectory.Moreover,the distance between the center of the group and the desired trajectory was analyzed in detail according to the number ratio of the followers to the leaders.In this way,on one hand,the agents of the group emerge a basic flocking behavior; on the other hand,the center of the group satisfies the constraints of global trajectory.Simulation results demonstrate the effectiveness of the proposed method.

Optimal Model of Continuous Knowledge Transfer in the Big Data Environment

With market competition becoming fiercer,enterprises must update their products by constantly assimilating new big data knowledge and private knowledge to maintain their market shares at different time points in the big data environment.Typically,there is mutual influence between each knowledge transfer if the time interval is not too long.It is necessary to study the problem of continuous knowledge transfer in the big data environment.Based on research on one-time knowledge transfer,a model of continuous knowledge transfer is presented,which can consider the interaction between knowledge transfer and determine the optimal knowledge transfer time at different time points in the big data environment.Simulation experiments were performed by adjusting several parameters.The experimental results verified the model’s validity and facilitated conclusions regarding their practical application values.The experimental results can provide more effective decisions for enterprises that must carry out continuous knowledge transfer in the big data environment.

Research on Integrated Analysis Method for Equipment and Tactics Based on Intervention Strategy Discussion

As the increase of the complexity of the information warfare,its intervention strategy needs to be designed in an integrated environment.However,the current research always breaks the internal relation between equipment and tactics,and it is difficult to meet the requirements of their integrated analysis.In this paper,the research status quo of the integrated analysis about equipment and tactics is discussed first,some shortages of the current methods are summarized then,and an evolvement mechanism of the integrated analysis for equipment and tactics is given finally.Based on these,a framework of integrated analysis is proposed.This method's effectiveness is validated by an example.

Bayesian serial revision method for RLLC cluster systems failure prediction

Failure prediction plays an important role for many tasks such as optimal resource management in large-scale system. However, accurately failure number prediction of repairable large-scale long-running computing （RLLC） is a challenge because of the reparability and large-scale. To address the challenge, a general Bayesian serial revision prediction method based on Bootstrap approach and moving average approach is put forward, which can make an accurately prediction for the failure number. To demonstrate the performance gains of our method, extensive experiments on the data of Los Alamos National Laboratory （LANL） cluster is implemented, which is a typical RLLC system. And experimental results show that the prediction accuracy of our method is 80.2 %, and it is a greatly improvement with 4 % compared with some typical methods. Finally, the managerial implications of the models are discussed.