Critical Relation Path Aggregation-Based Industrial Control Component Exploitable Vulnerability Reasoning

With the growing discovery of exposed vulnerabilities in the Industrial Control Components(ICCs),identification of the exploitable ones is urgent for Industrial Control System(ICS)administrators to proactively forecast potential threats.However,it is not a trivial task due to the complexity of the multi-source heterogeneous data and the lack of automatic analysis methods.To address these challenges,we propose an exploitability reasoning method based on the ICC-Vulnerability Knowledge Graph(KG)in which relation paths contain abundant potential evidence to support the reasoning.The reasoning task in this work refers to determining whether a specific relation is valid between an attacker entity and a possible exploitable vulnerability entity with the help of a collective of the critical paths.The proposed method consists of three primary building blocks:KG construction,relation path representation,and query relation reasoning.A security-oriented ontology combines exploit modeling,which provides a guideline for the integration of the scattered knowledge while constructing the KG.We emphasize the role of the aggregation of the attention mechanism in representation learning and ultimate reasoning.In order to acquire a high-quality representation,the entity and relation embeddings take advantage of their local structure and related semantics.Some critical paths are assigned corresponding attentive weights and then they are aggregated for the determination of the query relation validity.In particular,similarity calculation is introduced into a critical path selection algorithm,which improves search and reasoning performance.Meanwhile,the proposed algorithm avoids redundant paths between the given pairs of entities.Experimental results show that the proposed method outperforms the state-of-the-art ones in the aspects of embedding quality and query relation reasoning accuracy.

Optimal Strategies Trajectory with Multi-Local-Worlds Graph

This paper constructs a non-cooperative/cooperative stochasticdifferential game model to prove that the optimal strategies trajectory ofagents in a system with a topological configuration of a Multi-Local-Worldgraph would converge into a certain attractor if the system’s configuration isfixed. Due to the economics and management property, almost all systems aredivided into several independent Local-Worlds, and the interaction betweenagents in the system is more complex. The interaction between agents inthe same Local-World is defined as a stochastic differential cooperativegame;conversely, the interaction between agents in different Local-Worldsis defined as a stochastic differential non-cooperative game. We construct anon-cooperative/cooperative stochastic differential game model to describethe interaction between agents. The solutions of the cooperative and noncooperativegames are obtained by invoking corresponding theories, and thena nonlinear operator is constructed to couple these two solutions together.At last, the optimal strategies trajectory of agents in the system is proven toconverge into a certain attractor, which means that strategies trajectory arecertainty as time tends to infinity or a large positive integer. It is concluded thatthe optimal strategy trajectory with a nonlinear operator of cooperative/noncooperativestochastic differential game between agents can make agentsin a certain Local-World coordinate and make the Local-World paymentmaximize, and can make the all Local-Worlds equilibrated;furthermore, theoptimal strategy of the coupled game can converge into a particular attractorthat decides the optimal property.

基于声强向量法和声压梯度法的水中目标定向

本文论述了适合于水雷引信的基于声强向量法和声压梯度法对水中目标的特定部位 ,特别是辐射低频线谱分量的主机和辅机部位定向的方法 ,并对它们的定向原理以及在海洋环境噪声干扰场情况下的误差特性进行了分析。

A dynamic performance evaluation method based on SD-BSC

Taking into consideration the disadvantage of Balanced Scorecard(BSC)not being able to reflect time delay,nonlinear problems of causal relationship and being lack of effective simulation,we combined it with the characteristics of the System Dynamics(SD).Basing on the background of manufacturing enterprises,through SD integrating with the BSC we established a new performance evaluation method-SD-BSC method to overcome the disadvantage of BSC.A performance evaluation model of SD-BSC is provided and the simulation results are analyzed which show different production policies will lead to different customer's satisfaction degrees.The SD-BSC dynamic performance evaluation method can reflect dynamic,complex causal feedback relationship and time delay,so it compensates for the disadvantage of traditional financial performance evaluation method,and at the same time makes the BSC perfect.

ANALYTICAL SOLUTION OF RADIATION SOUND PRESSURE OF DOUBLE CYLINDRICAL SHELLS IN FLUID MEDIUM

The Donnell theory of shell was applied to describe shell motion. The inner and outer shells were stiffened by transverse components. Using deformation harmonious conditions of the interface, the effects of stiffeners were treated as reverse forces and moments on the double cylindrical shell. In the acoustic field produced by vibration and sound radiation of the double shell, the structure dynamic equation, Helmholtz equation in the fluid field and the continuity conditions of the surface of fluid-structure compose the vibration equation coupled by the sound-fluid-structure. The extract of acoustic pressure comes down to the extract of coupling vibration equation. The near field acoustic pressure can be solved directly by complicated calculational methods.

A Coarse Alignment Based on the Sliding Fixed-Interval Least Squares Denoising Method

The observation vectors in traditional coarse alignment contain random noise caused by the errors of inertial instruments,which will slow down the convergence rate.To solve the above problem,a real-time noise reduction method,sliding fixed-interval least squares(SFI-LS),is devised to depress the noise in the observation vectors.In this paper,the least square method,improved by a sliding fixed-interval approach,is applied for the real-time noise reduction.In order to achieve a better-performed coarse alignment,the proposed method is utilized to de-noise the random noise in observation vectors.First,the principles of proposed SFI-LS algorithm and coarse alignment are devised.A simulation test and turntable experiment were executed to demonstrate the availability of the designed method.It is indicated that,from the results of the simulation and turntable tests,the designed algorithm can effectively reduce the random noise in observation vectors.Therefore,the proposed method can enhance the performance of coarse alignment availably.

Plasticity and melting characteristics of metal Al with Ti-cluster under shock loading

Impurity agglomeration has a significant influence on shock response of metal materials.In this paper,the mechanism of Ti-clusters in metal Al under shock loading is investigated by non-equilibrium molecular dynamics simulations.Our results show that the Ti-cluster has obvious effects on the dislocation initiation and melting of bulk Al.First,the Ti clusters induces the strain concentrate and leads the dislocations to be initiated from the interface of Ti cluster.Second,dislocation distribution from the Ti-cluster model results in a formation of a grid-like structure,while the dislocation density is reduced compared with that from the perfect Al model.Third,the critical shock velocity of dislocation from the Ti-cluster model is lower than from perfect Al model.Furthermore,it is also found that the temperature near the interface of Ti-cluster is100 K–150 K higher than in the other areas,which means that Ti-cluster interface melts earlier than the bulk area.

Multiple Music Sentiment Classification Model Based on Convolutional Neural Network

The network community is a platform for people to communicate. In order to accurately analyze the emotions displayed in music community, this paper proposes a convolutional neural network classification model based on multi-dimensional emotions. Firstly, to solve the problem of feature extraction of emotion words under similar sentence patterns, it proposed a multi-emotion classification method and emotion vector splicing method that conform to music community emotion characteristics. Secondly, aiming at the coexistence of multiple categories of emotions in music comment text, it applied an emotional value measurement method based on music characteristics. Finally, the classification model was constructed with combining methods of emotion vector splicing and emotion value measurement. Through experimental analysis, this model is proved to have good performance in accuracy.

Reliability analysis on civil engineering project based on integrated adaptive simulation annealing and gray correlation method

Dynamic reliability is a very important issue in reliability research. The dynamic reliability analysis for the project is still in search of domestic and international research in the exploration stage. By now, dynamic reliability research mainly concentrates on the reliability assessment; the methods mainly include dynamic fault tree, extension of event sequence diagram and Monte Carlo simulation, and et al. The paper aims to research the dynamic reliability optimization. On the basis of analysis of the four quality influence factors in the construction engineering, a method based on gray correlation degree is employed to calculate the weights of factors affecting construction process quality. Then the weights are added into the reliability improvement feasible index （RIFI）. Furthermore, a novel nonlinear programming mathematic optimization model is established. In the Insight software environment, the Adaptive Simulated Annealing （ASA） algorithm is used to get a more accurate construction subsystem optimal reliability under different RIFI conditions. In addition, the relationship between construction quality and construction system reliability is analyzed, the proposed methods and detailed processing can offer a useful reference for improving the construction system quality level.

Formation Tracking for Nonlinear Multi-agent Systems with Input and Output Quantization via Adaptive Output Feedback Control

Signal quantization can reduce communication burden in multi-agent systems,whereas it brings control challenge to multi-agent formation tracking.This paper studies the output feedback control problem for formation tracking of multi-agent systems with both quantized input and output.The agents are described by a nonlinear dynamic model with unknown parameters and immeasurable states.To estimate immeasurable states and solve the uncertainties,state observers are developed by using dynamic high-gain tools.Through proper parameter designs,an output feedback quantized controller is established based on quantized output signals,and the quantization effect on the control system is eliminated.Stability analysis proves that,with the proposed control scheme,multi-agent systems can track the reference trajectory while forming and maintaining the desired formation shape.In addition,all the signals in the closed-loop systems are bounded.Finally,the numerical simulation and practical experiment are provided to verify the theoretical analysis.

Reconfigurable Muscle Strength Training Robot with Multi-mode Training for 17 Joint Movements

Different from limb rehabilitation training,the purpose of muscle strength training is to reduce muscle atrophy and increase muscle strength and tolerance through strength training of limb muscles,and then improve the muscle strength level of muscles(groups),mainly for sports fitness and muscle strengthening groups and patients with muscle atrophy or muscle weakness caused by various diseases.In this paper,we developed a new reconfigurable muscle strength training robot,a bionic robot by imitating physicians to conduct muscle strength training for patients,which was developed with six training modes for 17 joint movements,that is,the shoulder flexion/extension,the shoulder internal/external rotation,the shoulder adduction/abduction,the elbow flexion/extension,the wrist supination/pronation,the wrist flexion/extension,the wrist radial/ulnar deviation,the hip flexion/extension,the hip internal/external rotation,the hip adduction/abduction,the knee flexion/extension,the ankle dorsiflexion/plantarflexion,the ankle adduction/abduction,the ankle inversion/eversion,the waist flexion/extension,the waist left/right rotation,and the waist left/right flexion.The reconfigurable mechanism was designed with fully electric adjuster and reconfigurable adaptors deployed on the driving unit,and six training modes were developed,namely,continuous passive motion,active exercise,passive–active exercise,isotonic exercise,isometric exercise and isokinetic exercise.Experiments with knee joint and elbow joint have shown that the developed reconfigurable muscle strength training robot can realize the multi-mode trainings for the 17 joint movements.

Admission Control of VL in AFDX Under HRT Constraints

Avionics full duplex switched ethernet（AFDX） is a switched interconnection technology developed to provide reliable data exchange with strong data transmission time guarantees in internal communication of the spacecraft or aircraft.Virtual link（VL） is an important concept of AFDX to meet quality of service（QoS） requirements in terms of end-to-end message deadlines.A VL admission control algorithm in AFDX network under hard real-time（HRT） constraints is studied.Based on the scheduling prin-ciple of AFDX protocol,a packet scheduling scheme under HRT constraints is proposed,and after that an efficient VL admission control algorithm is presented.Analytical proof that the algorithm can effectively determine whether VL should be admitted is given.Finally simulative examples are presented to promote the conclusion.

Distributed Estimation in Sensor Networks with Repetition Coding

This paper considers the distributed estimation of a source parameter using quantized sensor observations in a wireless sensor network with noisy channels. Repetition codes are used to transmit quantization bits of sensor observations and a quasi best linear unbiased estimate is constructed to estimate the source parameter. Simulations show that the estimation scheme achieves a better power and spectral efficiency than the previous scheme.

Distributed Estimation for Sensor Networks with Channel Estimation Errors

This paper describes the effect of channel estimation error （CEE） on the performance of distributed estimations of an unknown parameter in a wireless sensor network. Both the classical and Bayesian estimators are derived to mitigate the adverse effects caused by the CEE. Power scheduling among sensors and the power ratio between the training and data transmission at each individual node are optimized by directly minimizing the final average mean squared error to compensate for the CEE. A closed-form power scheduling policy is given for a homogeneous environment, which shows that more than 50% of the power should be allocated to sensor observation transmissions. For an inhomogeneous environment, a multilevel waterfilling type solution is developed for the power scheduling among sensors for only the sum power constraint with a ＂cave＂ waterfilling solution for both the sum and individual power constraints. Simulations show that the proposed power scheduling schemes achieve better performance than the equal power scheduling scheme.

Modeling method for integration of air command and security process

Air command and security(ACS)process is a kind of typical complex operation process.Its modeling issue has become a hot spot and challenge in the research field of complex operation process.Combining the demand on the application of air command and support,this paper proposes a simulation-based modeling method of integrating air command and support process,emphatically describing such aspects as the meta-model of the concept of aviation support process,work flow service modeling and arrangement of multi-aircraft process,etc.Finally,based on actual cases of application,this paper unfolds simulating verification and assessment on the whole process of control and support operation process of a flight task involving multiple aircrafts.

High-resolution deconvolved beamforming for three-dimensional imaging sonars

Three-dimensional(3D) imaging sonars based on the conventional beamforming(CBF) suffers from relatively wide main-lobes and high sidelobe level.To improve the spatial resolution of 3D imaging sonars,a deconvolved beamforming method is proposed with the iterative Richardson-Lucy algorithm in this paper.At first,each distance slice can be processed to obtain images by the CBF.For the near field,the Fresnel approximation is used.Then,the deconvolution technique is applied to the CBF outputs to obtain high-resolution images and suppress the sidelobe level.The simulations demonstrate that the proposed algorithm is able to improve the spatial resolution significantly and suppress the sidelobes for 3D imaging sonars.Meanwhile,the algorithm shows similar robustness with the CBF in the case of wideband and sparse array.The priority of the proposed algorithm is also validated by the tank experiment data.The presented results indicate that the spatial resolution is increased by one time and the average sidelobe level is reduced by 20 dB.