Search

In wireless communication system, buildings or active eavesdroppers by illegal devices can block the communication link between the transmitter and receiver. Utilizing the flexible mobility of unmanned aerial vehicle (UAV) and the intelligent controllable characteristic of intelligent reflective surface (IRS) in wireless environment, this paper proposed a safe transmission scheme of physical layer for IRS assisted UAV to maximize the averaged secrecy rate of the legitimate link. The scheme firstly utilized block coordinate descent method to decompose the average secrecy rate maximization problem of the system into three sub-problems: UAV-IRS flight trajectory optimization, IRS phase shift optimization and transmission power optimization. And then, this scheme transformed each subproblem into a convex optimization subproblem by utilizing relaxation variables, phase alignment and successive convex approximation methods, respectively. Furthermore, this paper used the alternating optimization method to obtain the maximum average secrecy rate of the system. Numerical simulation results show that the transmission power of the source node, the flight position and altitude of UAV-IRS and the number of IRS reflective elements are the main factors for improving the averaged secrecy rate of the legitimate link. The proposed scheme can effectively improve the average secrecy rate of the system with good convergence by comparing with the other two benchmark schemes. [ABSTRACT FROM AUTHOR]

In order to solve the problems of inadequate global search and easy to fall into local extremum, this paper proposed a multi-strategy fusion improved adaptive tunicate swarm algorithm（MITSA）. Firstly, this paper used the best point set strategy to improve population diversity during initialization. Secondly, it offered a multi-elite cooperative guidance mechanism to optimize the tunicates’ location information, and enhance the global exploration ability of the algorithm by increasing the exploration possibility of unknown search area. Then, the algorithm achieved dynamic global and local search balance by introducing adaptive weight factors into the group behavior stage. Meanwhile, probabilistic wavelet variation strategy promoted individual dynamic fine-tuning to enhance the anti-stagnation ability of the algorithm, while using the greedy principle to retain excellent information to help the population to the food source. Finally, this paper proved the global convergence of the improved algorithm based on Markov chain theory. Through the numerical simulation of the benchmark test function and CEC2014 complex function, the experimental results and Wilcoxon rank sum test results comprehensively verify MITSA’s excellent convergence accuracy, robust robustness and high-dimensional scalability. [ABSTRACT FROM AUTHOR]

This paper fused the characteristics of cloud security and the point-to-group networks, proposed a new malware propagation model based on cloud-edge combination, namely, cloud security environment and point-to-group information sharing networks, and formed the cloud-edge combination defense against malicious code. Firstly, this paper introduced cloud security node based on the classical susceptibility-infection-immune propagation model, and added additional immune pathways of nodes in cloud security environment. Secondly, this paper analyzed the dynamics of the new model, and calculated the equilibrium point and propagation threshold of the model, and proved the local stability and global stability of the equilibrium point. Finally, the results of numerical simulation and simulation experiments show that, the malware propagation model based on cloud-edge joint defense can better curb the spread of malware in the network, and with the improvement of node detection and feedback ability, the containment effect of malware will be better. [ABSTRACT FROM AUTHOR]

The spread of epidemics poses a significant threat to the entire human community. Therefore, it is critical to identify the sources of transmission quickly and take timely control measures. However, the diversity of epidemic transmission processes and information uncertainty makes it challenging to identify the sources of transmission quickly and accurately. This paper proposed a new algorithm for identifying transmission sources in a metapopulation network by combining the reverse infection algorithm and Markov chain theory. The algorithm first uses a Markov chain to initially estimate the time when a subpopulation is infected, and the infected subpopulation obtains its own identity information based on the infection time. Then, it traverses all subpopulations that obtain the identity information of the infected subpopulation and spreads the collected identity information of the infected subpopulation to all its neighbors. Finally, the spreading source of the metapopulation network can be inferred based on the temporal order in which all the identity information of the infected subpopulation is obtained. Simulation experiments conducted on real airports networks and artificial networks show that the accuracy of this algorithm is significantly improved compared to other algorithms, regardless of whether all or partial of the infection snapshots are known. This algorithm is well-suited for metapopulation networks such as aviation networks and is also useful for real-world epidemic transmission tracing and control. [ABSTRACT FROM AUTHOR]

To improve the throughput and energy efficiency of wireless sensor network ( WSN) in intelligent transportation system (ITS), this paper proposed a cooperative multiple input multiple output automatic repeat request protocol with spatial modulation( CMIMO-SM-ARQ). It considered a four-node WSN with dual sending nodes and dual receiving nodes, in which both receiving nodes could act as relays to each other to assist the sender transmitting data, to reduce the probability of system outage. The paper established the discrete time Markov chain ( DTMC) model of CMIMO-SM-ARQ protocol with 3L + 1 states and gave the state space. Based on the outage probability of WSN and the one-step state transition probability matrix, it derived the analytical expressions of throughput, energy efficiency and delay of CMIMO-SM-ARQ protocol. Numerical simulation results show that the outage probability and energy efficiency of the proposed protocol are better than the single input single output automatic repeat request ( SISO-ARQ) protocol, and the CMIMO-SM-ARQ protocol has a higher throughput and lower delay when transmitting information at medium and long distances( over 67 m). [ABSTRACT FROM AUTHOR]

Considering that the contacts between travelers promote the epidemic spreading, this study constructed a spreading model with non-Markovian travel process and used computer simulation technology to simulate the epidemic spreading, where the time delay travel process and the infection and recovery during travel were considered on the metapopulation network. Based on the microscopic Markovian chain approach（MMCA）, this paper developed a theoretical framework to predict the epidemic threshold. Simulation results indicate that the travel infection promotes the infection in travel but inhibits the infection within the subpopulations, and the travel time and the travel contact rate may change the time evolution of prevalence. These results help to understand the influence of travel infection on epidemic spreading. [ABSTRACT FROM AUTHOR]

This paper analyzed the security of an image encryption algorithm based on compound chaotic sequence, the proposed algorithm adopted three-level encryption structure of permutation-forward diffusion-reverse diffusion. Due to the forward diffusion and the reverse diffusion used the same one-dimensional diffusion sequence, therefore, this paper simplified the two level encryption structure of the forward diffusion and reverse diffusion to one-level diffusion encryption structure, further, simplified the three-level encryption structure of permutation-forward diffusion-reverse diffusion to two-level encryption structure of permutation and diffusion. Moreover, the chaotic sequences generated by the encryption algorithm were independent of the plaintext images or ciphertext images, consequently, it could crack the corresponding equivalent diffusion keys and equivalent permutation keys by chosen-plaintext attack. Theoretical analysis and numerical simulation experiment results verify the effectiveness of the analytical method. Finally, this paper proposed some improved suggestions for the original encryption algorithm to promote the security. [ABSTRACT FROM AUTHOR]

This paper proposed an event-triggered mechanism based on cooperative control algorithm for the stability of autonomous vehicle platoon system,which could deal with the disturbance in the communication process and reduce the information redundancy and resource waste in the platoon control.Firstly,this paper designed a vehicle platoon algorithm for the directed topology on the basis of event-triggered mechanism.Even if there was disturbance,the follower autonomous vehicles could be consistent with the speed of leader autonomous vehicle,and each two consecutive autonomous vehicles could keep the desired safe distance.In addition,it constructed a Lyapunov function and gave the analysis of Zeno behavior to testify the validity and security of the proposed algorithm.Finally,the numerical simulation proves the correctness of the control algorithm. [ABSTRACT FROM AUTHOR]

To improve the delay and throughput performance of wireless sensor network ( WSN), this paper proposed a dualhop, multi-source and multi-relay cooperative automatic repeat request ( DH-MSMR-CARQ) protocol. The paper established the Markov chain models of DH-MSMR-CARQ protocol with two different relay selections under maximum ratio combining ( MRC) and gave the state spaces respectively. Based on truncation, this paper derived analytical expressions of average transmission delay and throughput according to their respective average packet error rate and state transition probability matrix. The numerical simulation results show that the number of source nodes, packet length and the packet error rate from the best relay node to destination node are the key factors affecting the average transmission delay, and the first relay selection method has higher throughput. In addition, the DH-MSMR-CARQ protocol has higher throughput than the direct SSSR-CARQ, MSSRCARQ and MSSR-CARQ protocols in non-extreme channel environment ( the packet error rates between source nodes and relay nodes are less than 0. 8). [ABSTRACT FROM AUTHOR]

This paper proposed two containment control algorithms for first-order/second-order multi-agent systems for discrete-time flocking motion problems. By using modern control theory, algebraic graph theory and linear matrix inequalities to analyze the proposed control algorithm, this paper obtained convergence conditions in a finite time for flocking motion of multiagent systems with interference under discrete-time conditions. Finally, by using the LMI toolbox in numerical simulation, it determined the range of positive definite matrices. The simulations illustrate the correctness of the conclusion. [ABSTRACT FROM AUTHOR]

Aiming at the shortcomings of aquila optimization algorithm（AO）, this paper proposed an aquila optimization algorithm using hybrid search strategy. Firstly, the algorithm introduced dynamic adjustment function to balance global exploration and local exploitation; Secondly, it introduced chaotic adaptive weights to enhance the global search capability of the algorithm and accelerate the convergence speed of the algorithm; Thirdly, it introduced a new individual mutation probability coefficient and an improved differential mutation strategy, and used individuals with better fitness values to lead other individuals in the population to carry out search activities, which maintained the diversity of the population and enhanced the ability of the algorithm to jump out of the local optimum. Through the numerical experiment simulation of 8 benchmark test functions, 10 CEC2019 test functions and 1 engineering application problem, The experimental results show that the algorithm has a significant improvement in global convergence speed and optimization accuracy, and has a better ability to jump out of the local optimum. [ABSTRACT FROM AUTHOR]

Due to the increasing demand for rich multimedia services, Internet of vehicles needs to provide massive equipment connections to meet the needs of high spectrum efficiency and low delay. Software Defined Network (SDN), caching and Non-Orthogonal Multiple Access (NOMA) technologies are considered as potential solutions to effectively solve these key challenges. Therefore, this paper proposed a cache aided NOMA power allocation scheme for software defined vehicular network. Firstly, according to the characteristics of vehicles always moving at high speed in Internet of vehicles, the scheme proposed a new cluster head selection algorithm. The arriving road traffic will be predicted with the help of SDN to realize adaptive vehicle clustering. Secondly, the scheme introduced a cache aided NOMA strategy. Each vehicle uses NOMA principle to cache and request files in the file cache stage. Thirdly, for the two cluster head vehicle communication scenarios under the condition of double Nakagami-m fading, the scheme proposed an optimal power allocation strategy. The optimization problem is formulated as finding the optimal power curve of each vehicle, so as to maximize the probability of successfully decoding the target file on each vehicle. Finally, numerical simulation and theoretical analysis show that the performance of the proposed cache aided NOMA power allocation scheme is significantly better than the conventional NOMA and cache aided Orthogonal Multiple Access（OMA). [ABSTRACT FROM AUTHOR]

Aiming at the shortcomings of crow search algorithm ( CSA), this paper proposed a crow search algorithm using multi-mode flight ( MFCSA) . Based on the strength of foraging ability, the algorithm divided the population into two groups: strong and weak foraging ability. Those with strong foraging ability adopted the strategy of trailing and tracking the optimal target of the current group, and flied to the vicinity of the current optimal position of the group under the guidance of the group information to carry out search activities, which enhanced the local exploitation ability of the algorithm. Those with weaker foraging ability adopted the two strategies of observing and learning the foraging methods of the strong, and flying away quickly when encountering danger, the former could improve the global exploration ability of the algorithm, and the latter could maintain the diversity of the population. Through the numerical experiment simulation of 15 benchmark test functions and 2 engineering application problems, the results show that the MFCSA has better performance in optimization accuracy, convergence speed, etc., enhances the ability to avoid falling into the local optimum, and has better stability. [ABSTRACT FROM AUTHOR]

This paper developed an opportunistic maintenance strategy model of multi-component equipment based on disassembly sequence for the problem that disassembly is not considered in the maintenance of multi-component equipment. Firstly, it represented the disassembly sequence by the disassembly mixture diagram, and then obtained the disassembly time and cost of each component. It described the failure characteristics of each component by combining the mixed failure rate of decreasing service age factor and increasing failure rate factor according to the decline process of each component. Secondly, on this basis, it solved the optimal preventive maintenance plan with the equipment opportunity window as the decision variable and the lowest maintenance cost as the goal under the condition that the equipment met certain availability. Finally, through numerical simulation analysis, it verified the effectiveness of the proposed multi-component opportunistic maintenance strategy. [ABSTRACT FROM AUTHOR]

Focused on the problems that low-precision and easily to fall into local optimum result in the high-dimensional space by the longhorn search algorithm,this paper proposed a new optimization algorithm of the short-lived beetles-the shortlived search algorithm based on quadratic interpolation which was called QIBAS.The algorithm took tentacle’s left and right tentacles as interpolation coordinate points after the beetle moved.And it generated new solution with a second interpolation,then compared to the current optimal solution and the global optimal solution with the fitness of interpolation solution.At the same time to update the global optimal solution,it performed numerical simulation tests on multiple unimodal and multimodal functions,and their dimensions took as 100,500,1 000,5 000 and 10 000.The simulation results show that the introduction of quadratic interpolation effectively improves the ability of the BAS algorithm to jump out of the local optimum.When QIBAS solves the optimal value,its solution accuracy is greatly improved,and the convergence speed is also significantly improved.The effectiveness of the improved algorithm is verified. [ABSTRACT FROM AUTHOR]

For the detection blind zone problem of interference suppression method based on block matrix, this paper proposed a post-processing method of interference suppression based on local transform processing. Firstly, the method used linear trans-- form synthesize a set data on the interference suppression azimuth. Secondly, it obtained the corresponding spatial spectrum of each spatial azimuth by spatial spectrum synthesis method. Then, it extracted the base change value of spatial spectral by local transformation. Finally, it equalized the spatial spectrum by the base change value of spatial spectrum and reduced the detection blind wne. The numerical simulation and data processing results show that, this method reduces the change value of spatial spectrum base through local nonlinear equalization of spatial spectrum after interference suppression, reduces detection blind zone within 3°, and improves interference suppression method based on block matrix. [ABSTRACT FROM AUTHOR]

In view of the characteristics of the small-scale unmanned helicopter system which is highly nonlinear, strongly coupled and susceptible to internal and external disturbance, this paper proposed a control strategy combining nonlinear block back-stepping control with generalized proportional integral observer. In this method, at first, it used a generalized proportional integral observer to construct a multi-order observation loop and to estimate the system state variables, disturbances and the multi-order derivatives of disturbances, and then it added the estimated value of disturbance into the helicopter system model and adapted back-steeping method to obtain the tracking flight controller of the helicopter. Numerical simulation results of step signal and complex trajectory tracking show that, the designed controller has an ideal dynamic response performance, tracking capability and disturbance attenuation ability under the influence of various internal and external disturbances. Compared with the nonlinear disturbance observer, the generalized proportional integral observer has a higher estimation accuracy for high order and fast time-varying disturbances and achieves better disturbance suppression effects. [ABSTRACT FROM AUTHOR]

The ultrasound tongue imaging in pronunciation is an effective way to analyze the tongue movement. However, the processing analysis for ultrasound tongue imaging sequence can provide valuable information for various application fields, such as linguistics, phonetics, speech processing, speech engineering, tongue modeling, etc. Based on the existing research findings at home and abroad, this paper concluded the tracking and extraction techniques of tongue contour, analyzed quantitative comparison method of different tongue contour and pointed out the measuring method for tongue movement. It was expected that which could provide technical methods for the related researchers in the study of pronunciation physiology and language study, and the new algorithm and new model in computer fields could be applied in pronunciation physiological tongue study through the related technique improvement, improving the scientific and accurate description of the phenomenon of phonetic phenomena. [ABSTRACT FROM AUTHOR]

Traditional attack-defense models on WSN usually include only one kind of attack. However, in real cases, malicious nodes often take various attacks and adjust their strategies to improve the attacking success rate. In view of this situation, this paper proposed three attack-defense game models for WSN under different attacks, and studied the attack-defense game processes of WSN under external attacking, internal attacking and mixed attacking, respectively. By analyzing and solving game models, it got the optimal strategies of both players of the games, and verified the theoretical results by numerical simulation. This work is of practical guiding significance to design the intrusion detection system in WSN. [ABSTRACT FROM AUTHOR]

In order to solve the problem that communication and computing resources are consumed in the first order multiagent system circle formation with communication delay, this paper introduced an event-driven control mechanism, and designed the control law for arbitrary circle formation, which was coupling with state dependent and state independent event-driven conditions. Event-triggered function was based on state error, made the information transmission between two neighbor agents and the controller updates driven by properly defined events. It proved the convergence of the control law strictly and theoretically, and the numerical simulation validated the effectiveness of control algorithm. The simulation results also s how that the updating frequency of the controller and the resource consumption of the agent are reduced with the desired system performance. [ABSTRACT FROM AUTHOR]

In the big data environment, the problem of high time complexity of multi-label K-nearest neighbor( ML-KNN ) is particularly prominent. In addition, ML-KNN does not consider the effect of K nearest neighbors on the final classification results. This paper first clustered the training set, and then found a nearest cluster as new training set for test dataset. Then it calculated nearest neighbor distance weight, by which the effect of k neighbors was described. Finally, an unseen sample could be classified by this new method. Numerical simulation results in different datasets show that the proposed algorithm obtained a better classification result and improved the time complexity of the algorithm. [ABSTRACT FROM AUTHOR]

Since static PPI network are difficult to truly reflect the dynamic character of cells, the convergence speed is slow, cluster precision and recall is low in mining protein complex based on ant colony clustering, this paper proposed an ant colony clustering algorithm based on fuzzy granular and closeness degree to mine protein complexes in dynamic weighted PPI network, named FGCDACC-DPC (joint fuzzy granular and closeness degree ant colony cluste ring-DPC). First, based on the topological and biological characteristics of the PPI network, it designed a comprehensive weight metric (CWM) to accurately describe the interaction between proteins. Second, this method constructed a series of dense and highly co-expressed complex core based on the basic characteristic of the complexes, then it employed the picking and dropping operations, which based on fuzzy granular and closeness degree, to cluster the nodes in PPI network, in order to reduce effectively the computational complexity and rand omness, speed up the clustering speed. Finally, this algorithm designed a local and global strategy founded on function trans mission and timing functional relevance theory for weight's update, which achieved the function transmission between different gene rations of ant colonies and networks at different times to effectively improve clustering accuracy. FGCDACC-DPC algorithm was used to mine protein complexes on DIP data. Experimental results demonstrate that this algorithm has better performance on precision and recall, which is more reasonable to identify protein complexes. [ABSTRACT FROM AUTHOR]

Since static PPI network are difficult to truly reflect the dynamic character of cells, the convergence speed is slow, cluster precision and recall is low in mining protein complex based on ant colony clustering, this paper proposed an ant colony clustering algorithm based on fuzzy granular and closeness degree to mine protein complexes in dynamic weighted PPI network, named FGCDACC-DPC (joint fuzzy granular and closeness degree ant colony clustering-DPC). First, based on the topological and biological characteristics of the PPI network, it designed a comprehensive weight metric (CWM) to accurately describe the interaction between proteins. Second, this method constructed a series of dense and highly co-expressed complex core based on the basic characteristic of the complexes, then it employed the picking and dropping operations, which based on fuzzy granular and closeness degree, to cluster the nodes in PPI network, in order to reduce effectively the computational complexity and rand omness, speed up the clustering speed. Finally, this algorithm designed a local and global strategy founded on function trans mission and timing functional relevance theory for weight's update, which achieved the function transmission between different gene rations of ant colonies and networks at different times to effectively improve clustering accuracy. FGCDACC-DPC algorithm was used to mine protein complexes on DIP data. Experimental results demonstrate that this algorithm has better performance on precision and recall, which is more reasonable to ide ntify protein complexes. [ABSTRACT FROM AUTHOR]

Basing on good performance of sliding-mode controlling, the paper investigated finite-time synchronization of fractal-order chaotic system by Terminal sliding-mode control strategy, and realized synchronization of drive-response chaotic Sprott-C system (with the fractal order α : 0 < a < 1 ) with unknown parameters and disturbance by designing property slidingmode surface and fractal-order controller. Moreover, one estimated the unknown parameters and upper bound of the unknown systematic parameters and disturbance successfully by some appropriate adaptive update laws combining with fractal-order differential equations theory and finite-time stability theory. Finally, by choosing proper parameters, numerical simulations provide illustration to show the effectiveness and feasibility of the theoretical results. [ABSTRACT FROM AUTHOR]

To make research results more realistic, this paper studied the consensus of multi-agent systems with uncertainties and randomly occurring nonlinearities and time delay via impulsive control with topology switching. In the traditional protocol, it was usually assumed that the communication delay between adjacent individuals was the same as the communication delay between individual and leader, but this was conservative. In the new protocol, the value of delay above could be different. Compared with traditional research methods, the approach that deals with the delay in complex network synchronization research is introduced into the research of consensus of multi-agent systems. Using a generalized Ilaianay inequality, two sufficient conditions which were not related to the delay were given to meet the leader-following consensus of systems with topology switching, in other words, the delay did not affect the final consensus of system when the relevant parameters satisfied the theorem’s conditions. Compared with the decision conditions with delay on other methods, the results of this study are less conservative. The numerical simulation verifies the feasibility of the new protocol. [ABSTRACT FROM AUTHOR]

There are some problems on multi-user downlink power allocation and beamforming in a cognitive radio network (CRN) which works in the underlay mode. They are the high complexity of the conventional SDR algorithm. the limited applicability and ignoring the interferences of the primary network (PN) to the secondary user(SU) , etc. Aiming at these problems, this paper firstly added the term of interference of the PN to the SU to the CRN model and formulated the optimization problem. Then based on the duality of uplink-downlink, it obtained the simple and fast iterative algorithm by introducing virtual power, transforming the optimization problem into the problem of uplink power allocation and beamforming. And it analyzed the convergence of the algorithm to obtain the convergent conditions. It also reckoned the algorithm complexity. The result demonstrates that iterative algorithm is superior to the SDR algorithm. Numerical simulation results show that the algorithm conveiges faster, and that the variation of transmitting power of the primary base station (PBS) could affect the feasibility region. They also show that the increasing of transmitting power of the PBS could lead to the downlink power increasing. The influences are notable. [ABSTRACT FROM AUTHOR]

In order to reduce the effects of communication delay, this paper investigated the leader-following consensus of the second-order nonlinear multi-agent systems with active leader. It presented a new concept called approximate random impulsive delay, and designed a new control protocol to make the system achieve the leader-following consensus. Compared with the traditional protocol, when the impulsive input delay was so small, each agent in the new protocol predicted their current state of time based on the delay state and sent the prediction state to each neighbor agents, which compensated for its own feedback channel delay meanwhile. Based on the Lyapunov stability theory, using the nature of a kind of generalized Halanay inequality obtained two sufficient conditions which could guarantee the reaching of leader-following consensus of systems. Finally, the numerical simulation verifies the superiority of new protocol. [ABSTRACT FROM AUTHOR]

This paper researched the energy efficiency optimization of simultaneous wireless information and power transfer( SWIPT) in heterogeneous small cellular networks. In order to maximize the energy efficiency of the downlink cellular system, it jointly optimized the splitting ratio of transmit beamforming vector and receive power under both small cellular users’ communication quality and the collected energy, and the transmission power of the small cell base station constraints. The problem belonged to the nonconvex optimization problem, which transformed the equivalent problem by the variable substitution, and then used the subgradient iteration algorithm based on the Lagrange multiplier to solve the problem. The results of computer simulation show that the joint optimization algorithm is simple and effective. [ABSTRACT FROM AUTHOR]

To overcome the effects of the intense jam for the FD systems in the extreme spectrum environment, this paper proposed a novel DSIC method that adapted to the frequency agility FD systems. The error compensation model of the full working band was calculated offline and could generate the SI channel coefficients real-timely to reconstruct the SI signal and accomplish the DSIC. The numerical simulation results indicate that the level of the residual SI signal after the DSIC is below the noise floor level in the full band, which also demonstrate the consistency and convergence of this method at different frequency points. [ABSTRACT FROM AUTHOR]

To understand die dynamic evolution of economic crisis and reveal its mechanism based on macroeconomic system, this paper used international trade data provided from World Trade Organization to build an international trading of weighted and directed network by complex network theory. It used a simple model of cascading crisis to simulate numerically an economic crisis,the results revealed that the OOP and tradevolumn might both have significant influent on the avalanche size of the spreading, but not strong positive correlation. Then, it utilized target selection strategies to remove edges in ITN, the data showed that the economic interdependence between countries could significantly affect the convergence behavior of spreading on ITN. Furthermore, statistical analysis showed that the spatial features had identified within dynamic evolution, which suggested those countries from specially regions were vulnerable to crisis spreading. The findings in this study are helpful to deeply understand the evolution of crisis spreading and against to the emergence of cascading failures in economic system. [ABSTRACT FROM AUTHOR]

Aiming at the high complexity of codebook design of sparse code multiple access( SCMA),this paper proposed a design scheme for SCMA codebook in AWGN channels. Firstly,it designed the constellations for each resource block of all users. Secondly,it generated the corresponding constellations for each user by using the subset segmentation method of trellis coded modulation( TCM). Then,the generated constellations composed constellation matrix with the low density spreading sequence. Finally,constellation matrix was converted to users’ codebook. The proposed scheme could maximize the minimum Euclidean distance of constellation points not only between the users,but also within one user. Simulation results demonstrate that the designed codebook based on the proposed method can improve the BER performance of system. The system also performs well even if under high overload. [ABSTRACT FROM AUTHOR]

Compressive sensing is a new sampling theory which makes use of the sparsity of signals to recover the high-dimension signal from very few measurements. Unfortunately,most of the existing measurement matrices have high correlation between elements,which can not guarantee exact recovery and has greatly restricted their application prospects. Based on this,this paper proposed a novel Chebyshev chaotic measurement sensing matrix based on sampling columnization( SC3M). The sampling columnization and normalization guaranteed the low correlation in column of SC3 M,which optimized the recovery effect. Moreover,it proved that the proposed SC3 M sensing matrix satisfies the RIP with overwhelming probability from the Johnson-Lindenstrauss lemma. Numerical simulations show that the SC3 M is sufficient to guarantee exact recovery,which shows better effect compared to other popular measurement matrixes such as the fully random matrix,Bernoulli matrix and Gaussian sensing matrix. [ABSTRACT FROM AUTHOR]

In reality,individuals are affected by all the neighbors in different social networks with the spreading of information. This paper introduced the concept of hypernetwork to depict complex social relations among individuals. Based on infectious disease model,it performed the simulations of public opinion propagation. In the simulations,it compared the public opinion propagation in hypernework and complex network. When the structure parameters of hypernetwork were setting to special values,the model could degenerate into a complex network model. Furthermore,it also discussed the effects of structure parameters of hypernetwork,transmission rate,recovery rate and the initial infectious nodes. The public opinion propagation time and extent could reveal the overall trend of the spreading of public opinion. [ABSTRACT FROM AUTHOR]

The identification of the most influential nodes in complex networks is of great significance to the network diffusion dynamics,such as the acceleration of information diffusion or the suppression of the spread of rumors. On the basis of the existing methods of identifying the most influential nodes,this paper proposed a recognition method of influential nodes based on community structure and k-shell decomposition analysis. The method used ks values of the neighbor nodes in different communities to determine the influence of nodes( called Nc value),identified the different influence of the nodes with the same ks value. And through the SIR model of single infection source transmission simulation,it is found that the node with the higher Nc value not only obtains the greater impact,but also spreads faster than other nodes. [ABSTRACT FROM AUTHOR]

Based on random waypoint and random direction model, this paper proposed a novel earthquake relief mobility model through analyzing the demand characteristics of earthquake relief within prime time. Then, through analyzing victims self-rescue and rescue from relief teams these two phases respectively, it proposed the routing strategy for earthquake rescue. This mobility model and routing policy are validated correct by simulation experiments with the opportunistic network environment simulator. [ABSTRACT FROM AUTHOR]

To tackle the network congestion issue caused by redundant traffic by users' repeated access to the same network resources, this paper proposed a weighted bipartite network (WBN) model which evolved with time. Through the analysis of users' network behavior and redundant traffic' formation and evolution mechanism, WBN model adopted ways of preferential connection and topology growth to complete network evolution. Simulation experiment results show that strength of user nodes has experienced from the exponential distribution to power-law distribution and then random distribution. It effectively simulates the evolution of real network redundant traffic. Simulation results are also consistent with theoretical analysis and show that WBN model is accurate and practical. [ABSTRACT FROM AUTHOR]

In order to decrease energy consumption caused by competition for cluster head of each node during the cluster head replacement phase, this paper proposed a cluster head selection strategy based on scheduling in wireless sensor networks. The strategy divided all nodes into cluster head node, member node and scheduling node three types. In operation phase, the scheduling node makes real-time monitoring for the energy consumption of the cluster head node and the member node. In cluster head replacement phase, the scheduling node specified the corresponding node as cluster head according to the result of monitoring, which thereby reduced the energy consumption caused by competition for cluster head of each node. Finally, the simulation experiment results show that the improved algorithm can effectively improve network performance and prolong the network life cycle. [ABSTRACT FROM AUTHOR]

To meet the watermarking requirement in encrypted domain, this paper proposed a novel reversible watermarking algorithm in histogram difference domain for encrypted image by utilizing a combination of histogram shifting and homomorphic encryption. It could embeded a watermark into the encrypted image directly to realize the process of plain image-encrypted image-watermark embedding, which simplified the traditional redundant process of plain image-encrypted image-decryption--watermark embedding-encryption again. Simulation experimental results demonstrate that the proposed algorithm can provide greater payload capacity and higher image fidelity. After it extracts the watermark completely, it can recover the original image reversibly. It outperforms other related algorithms. [ABSTRACT FROM AUTHOR]

To solve the problem of decision discontinuity and the problem of authorization inflexibility exist in the attribute based access control model under the cloud environment, this paper proposed a kind of improved attribute based access control model. What was more, it introduced the concepts of obligation and condition in usage control and the concept of meta state into the model. The improved model realized flexible and continuous authorization through the monitoring of obligation set which could complete the state transition and then trigger the authorization. The research studied the improved model from two aspects of formal definition and security analysis. Its corresponding advantages were also analyzed. Compared with the traditional model, the model has higher security and a more flexible way of authorization. It is more suitable for the cloud environment. [ABSTRACT FROM AUTHOR]

In current clustering processing algorithms of histogram publishing based on differential privacy preserving, there was not algorithm which differentiate between histogram counts with smaller variance and histogram counts with larger variance. And it caused the waste of algorithm complexity when dealing with histogram with smaller variance. This paper proposed a segmentation algorithm based on the D-value of adjacent bins. It determined the segmentation boundary through calculating the D-value of adjacent unit bins and then determined the feasibility of each division based on the sum value of reconstruction error and the amount of noise. It verified the effectiveness of the proposed algorithm through the experimental simulation and theoretical analysis. This algorithm ensures the accuracy of data released. What's more important is that it greatly improves the efficiency of the algorithm. [ABSTRACT FROM AUTHOR]

To determinate that whether the deadmarkings affect the safety of the system and the correctness of the model or not in the state space report which obtained by using CPN Tools to simulate a CPN model, this paper proposed an algorithm which based on the ASK-CTL and model checking theories by using the non-standard state space query to verify the rationality of the deadmarkings in a CPN model. This algorithm was based on the theory of model checking and non-standard state space query which applied ML language to edit the functional functions would be obtained for a further study of the deadmarking in order to ensure the safety of the system or the correctness of the CPN model. Finally, it took an elevator door system as an example to verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

For many large scale graph reachability query problems in reality, this paper proposed a new algorithm based on RDD which decomposed a graph into a series of spanning trees and a residue graph. In this way, it transformed any reachability query into these two queries to reduce the cost. Compared with the traditional algorithms, like interval labeling, chain de composition, 2-hop labeling, and path-trees etc, this algorithm could lead to smaller space overhead, and lesser time complexity. The simulation illustrates that the algorithm has a smaller storage and more effectively to deal with the large scale groph reachability query problem. [ABSTRACT FROM AUTHOR]

In order to achieve path planning among obstacles environment for mobile robot, this paper proposed an improved shuffled frog leaping algorithm(SFLA). Te improved algorithm added crossover operation based on the original algorithm, and applied learning mechanism in the original SFLA update strategy, also proposed a method to generate a new individual with a control parameter instead of the original random update operations. It firstly transformed the problem of robot path planning into a minimization one, and then defined the fitness of a frog based on the position of target and obstacles in the environment, sleeted the position of the globally best frog in each iterative, and reached by the robot in sequence, thus realized the optimal path planning. In the mobile robot's simulation experiment, compared with the basic leap frog algorithm and other intelligent algorithms, the improved algorithm has greatly improvements in the planning time and number of successes. Te simulation result demonstrates the effectiveness of the improved algorithm. [ABSTRACT FROM AUTHOR]

The road is unstable under emergency conditions (like earthquakes, landslides, floods, etc ), accident waiting to happen. To solve problem of logistics distribution under emergency conditions, based on the study of traditional ant colony algorithm in solving VRP (vehicle routing problem), this paper tried to improve VRP mathematical model by adding a dynamic road factor. It gave a mathematical mode of ant colony algorithm to solve improved vehicle routing problem, and used the actual latitude and longitude of 21 cities in Shaanxi Province as an emergency analog cargo demanding places and warehouse locations to make a system simulation. It analyzed the parameters which had impact on improved algorithm convergence. Theoretical studies and MATLAB simulation proves that the improved algorithm can effectively solve the actual situation of emergency logistics distribution. [ABSTRACT FROM AUTHOR]

As an important research direction in text mining, this paper widely studied unsupervised and weak supervised generative models in text sentiment classification. It described the definition, classification and development of the generative model in text sentiment classification, focused on the relationship between the different generative sentiment models, with introduced the most representative models. Furthermore, it summarized the trends of the generative model and development in the future. [ABSTRACT FROM AUTHOR]

Local binary fitting model based on area only considers image statistical information. But the noise in image changes image intensity distribution, so this model cannot efficiently segment images with heavy noise. In order to improve the robustness to the noise, this paper proposed a novel local active contour model driven by image gray and gradient. This model that combined the image gradient information is on the basis of the image intensity statistics. The energy function of this model was then constructed with two parts: the local binary gray fitting energy and the local binary gradient fitting energy. Finally, the contour could be driven to the objective boundaries by minimizing the energy functional. Experimental results show that the proposed model can overcome the impact of the weak edges and heavy noise in the image to get satisfied segmentations, and outperforms state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

In order to overcome the problem of low solution precision of traditional nonlinear constraint algorithms, this paper-proposed a new optimization algorithm based on particle filter. It used this algorithm to solve nonlinear constraint problem, and combined the model and mechanism of particle filters. It established the optimization algorithm based on particle filter algorithm, and gave the procedures of which as well. Then it converted the nonlinear constraint optimization problems to function optimization problems, and established mathematical models of particle filter optimization algorithm for the nonlinear constraint optimization problems. Simulation results verify the validity of the new algorithm, and show that the optimization method based on particle filter has higher efficiency and rate than the traditional optimization algorithm when solving nonlinear optimization problems. Meanwhile, the proposed algorithm has its feasibility to future research on nonlinear constraint optimization problems. [ABSTRACT FROM AUTHOR]

In order to provide decision analysis tool for network optimization, this paper established the mathematical model of network survivability based on the influences and realized the simulation and analysis platform for network failure. By simulating the optical network link or node failure to analyze the effect on different levels of network business, then generated scientific and effective contingency plan on the basis of business protection principles. Through the optimization of the plans, it reduced the influence of fault on the business to largest extent in the actual network operation. Studies show that this platform could accurately and effectively simulate network fault and analyze survivability, which provides scientific basis for business protection and network optimization in fiber communication network. [ABSTRACT FROM AUTHOR]

To solve the problem of inflexibility in the allocation and revocation of attributes, which existed in the attribute based access control model under the cloud environment, this paper put forward a method based on the meta value. The research was done from two aspects of formal definition and performance simulation experiment to study the improved model. With the introduction of concept of meta value, it proposed a method of allocation and revocation of attribute based on the meta value, which solved the problem of fine-grained attribute revocation in the model. Compared with the traditional repeat authorization method, the method conforms to the principle of least privilege. What is more, it has higher security and higher efficiency. [ABSTRACT FROM AUTHOR]