Estimation of the anisotropy of hydraulic conductivity through 3D fracture networks using the directional geological entropy

With an extension of the geological entropy concept in porous media,the approach called directional entrogram is applied to link hydraulic behavior to the anisotropy of the 3D fracture networks.A metric called directional entropic scale is used to measure the anisotropy of spatial order in different directions.Compared with the traditional connectivity indexes based on the statistics of fracture geometry,the directional entropic scale is capable to quantify the anisotropy of connectivity and hydraulic conductivity in heterogeneous 3D fracture networks.According to the numerical analysis of directional entrogram and fluid flow in a number of the 3D fracture networks,the hydraulic conductivities and entropic scales in different directions both increase with spatial order(i.e.,trace length decreasing and spacing increasing)and are independent of the dip angle.As a result,the nonlinear correlation between the hydraulic conductivities and entropic scales from different directions can be unified as quadratic polynomial function,which can shed light on the anisotropic effect of spatial order and global entropy on the heterogeneous hydraulic behaviors.

Spontaneous Recovery in Directed Dynamical Networks

Complex networked systems,which range from biological systems in the natural world to infrastructure systems in the human-made world,can exhibit spontaneous recovery after a failure;for example,a brain may spontaneously return to normal after a seizure,and traffic flow can become smooth again after a jam.Previous studies on the spontaneous recovery of dynamical networks have been limited to undirected networks.However,most real-world networks are directed.To fill this gap,we build a model in which nodes may alternately fail and recover,and we develop a theoretical tool to analyze the recovery properties of directed dynamical networks.We find that the tool can accurately predict the final fraction of active nodes,and the prediction accuracy decreases as the fraction of bidirectional links in the network increases,which emphasizes the importance of directionality in network dynamics.Due to different initial states,directed dynamical networks may show alternative stable states under the same control parameter,exhibiting hysteresis behavior.In addition,for networks with finite sizes,the fraction of active nodes may jump back and forth between high and low states,mimicking repetitive failure-recovery processes.These findings could help clarify the system recovery mechanism and enable better design of networked systems with high resilience.

Bee Colony Optimization Algorithm for Routing and Wavelength Assignment Based on Directional Guidance in Satellite Optical Networks

With the development of satellite communication,in order to solve the problems of shortage of on-board resources and refinement of delay requirements to improve the communication performance of satellite optical networks,this paper proposes a bee colony optimization algorithm for routing and wavelength assignment based on directional guidance(DBCO-RWA)in satellite optical networks.In D-BCORWA,directional guidance based on relative position and link load is defined,and then the link cost function in the path search stage is established based on the directional guidance factor.Finally,feasible solutions are expanded in the global optimization stage.The wavelength utilization,communication success probability,blocking rate,communication hops and convergence characteristic are simulated.The results show that the performance of the proposed algorithm is improved compared with existing algorithms.

Bidirectional Quantum Secure Direct Communication Network Protocol with Hyperentanglement

We propose a bidirectional quantum secure direct communication(QSDC) network protocol with the hyperentanglment in both the spatial-mode ad the polarization degrees of freedom of photon pairs which can in principle be produced with a beta barium borate crystal.The secret message can be encoded on the photon pairs with unitary operations in these two degrees of freedom independently.Compared with other QSDC network protocols,our QSDC network protocol has a higher capacity as each photon pair can carry 4 bits of information.Also,we discuss the security of our QSDC network protocol and its feasibility with current techniques.

Voronoi-Based Coverage Optimization for Directional Sensor Networks

Sensing coverage is a fundamental problem in sensors networks. Different from traditional isotropic sensors with sensing disk, directional sensors may have a limited angle of sensing range due to special applications. In this paper, we study the coverage problem in directional sensor networks (DSNs) with the rotatable orientation for each sensor. We propose the optimal coverage in directional sensor networks (OCDSN) problem to cover maximal area while activating as few sensors as possible. Then we prove the OCDSN to be NP-complete and propose the Voronoi-based centralized approximation (VCA) algorithm and the Voronoi-based distributed approximation (VDA) algorithm of the solution to the OCDSN problem. Finally, extensive simulation is executed to demonstrate the performance of the proposed algorithms.

Controllability and Directionality in Complex Networks

We investigate how to assign link directions in a given complex network to enhance its controllability.Based on the node residual degree,a method of assigning link direction is proposed.Numerical simulation demonstrates that the method outperforms the random direction assignment method in enhancing the controllability of the network.Furthermore,robustness of control is also improved.

FIXED/PREASSIGNED-TIME SYNCHRONIZATION OF QUATERNION-VALUED NEURAL NETWORKS INVOLVING DELAYS AND DISCONTINUOUS ACTIVATIONS: A DIRECT APPROACH

The fixed-time synchronization and preassigned-time synchronization are investigated for a class of quaternion-valued neural networks with time-varying delays and discontinuous activation functions. Unlike previous efforts that employed separation analysis and the real-valued control design, based on the quaternion-valued signum function and several related properties, a direct analytical method is proposed here and the quaternion-valued controllers are designed in order to discuss the fixed-time synchronization for the relevant quaternion-valued neural networks. In addition, the preassigned-time synchronization is investigated based on a quaternion-valued control design, where the synchronization time is preassigned and the control gains are finite. Compared with existing results, the direct method without separation developed in this article is beneficial in terms of simplifying theoretical analysis, and the proposed quaternion-valued control schemes are simpler and more effective than the traditional design, which adds four real-valued controllers. Finally, two numerical examples are given in order to support the theoretical results.

Percolation transitions in edge-coupled interdependent networks with directed dependency links

We propose a model of edge-coupled interdependent networks with directed dependency links(EINDDLs)and develop the theoretical analysis framework of this model based on the self-consistent probabilities method.The phase transition behaviors and parameter thresholds of this model under random attacks are analyzed theoretically on both random regular(RR)networks and Erd¨os-Renyi(ER)networks,and computer simulations are performed to verify the results.In this EINDDL model,a fractionβof connectivity links within network B depends on network A and a fraction(1-β)of connectivity links within network A depends on network B.It is found that randomly removing a fraction(1-p)of connectivity links in network A at the initial state,network A exhibits different types of phase transitions(first order,second order and hybrid).Network B is rarely affected by cascading failure whenβis small,and network B will gradually converge from the first-order to the second-order phase transition asβincreases.We present the critical values ofβfor the phase change process of networks A and B,and give the critical values of p andβfor network B at the critical point of collapse.Furthermore,a cascading prevention strategy is proposed.The findings are of great significance for understanding the robustness of EINDDLs.

Forming Conditions and Neural Network Control of Continuously Directional Microstructurein Directional Solidification Continuous Casting Process

Directional solidification continuous casting (DSCC) process is a new manufacturing technology for metallic materials which combines advantages of both directional solidification technology and continuous casting technology. Unlimited long shaped metal with directionally solidifying microstructure can be produced by this process. It is experimentally shown that controlling condition of stable and continuous growth of single crystal structure means the precise control of the location of the S/L interface, which is affected and determined by seven process parameters. Moreover, these parameters are also interacted each other, so the disturbance of any parameters may cause the failure of controlling of S/L interface. In this paper, on the basis of analyzing the forming conditions of continuously directional microstructures in DSCC process, the control model of DSCC procedure by neural network control (NNC) method was proposed and discussed. Combining with the experiments, we first used the computer to simulate the effects of the solidification parameters on destination control variable (S/L interface) and the interactions among these parameters during DSCC procedure. Secondly many training samples necessary for neural network calculation can be obtained through the simulation. Moreover, these samples are inputted into neural network software (NNs) and trained, then the control model can be built up.

Directional neighbor discovery in mmWave wireless networks

The directional neighbor discovery problem,i.e,spatial rendezvous,is a fundamental problem in millimeter wave(mmWave)wireless networks,where directional transmissions are used to overcome the high attenuation.The challenge is how to let the transmitter and the receiver beams meet in space under deafness caused by directional transmission and reception,where no control channel,prior information,and coordination are available.In this paper,we present a Hunting based Directional Neighbor Discovery(HDND)scheme for ad hoc mmWave networks,where a node follows a unique sequence to determine its transmission or reception mode,and continuously r0-tates its directional beam to scan the neighborhood for other mmWave nodes.Through a rigorous analysis,we derive the conditions for ensured neighbor discovery,as well as a bound for the worst-case discovery time and the impact of sidelobes.We validate the analysis with extensive simulations and demonstrate the superior perfor-mance of the proposed scheme over several baseline schemes.

Research on the longitudinal protection of a through-type cophase traction direct power supply system based on the empirical wavelet transform

This paper proposes a longitudinal protection scheme utilizing empirical wavelet transform(EWT)for a through-type cophase traction direct power supply system,where both sides of a traction network line exhibit a distinctive boundary structure.This approach capitalizes on the boundary’s capacity to attenuate the high-frequency component of fault signals,resulting in a variation in the high-frequency transient energy ratio when faults occur inside or outside the line.During internal line faults,the high-frequency transient energy at the checkpoints located at both ends surpasses that of its neighboring lines.Conversely,for faults external to the line,the energy is lower compared to adjacent lines.EWT is employed to decompose the collected fault current signals,allowing access to the high-frequency transient energy.The longitudinal protection for the traction network line is established based on disparities between both ends of the traction network line and the high-frequency transient energy on either side of the boundary.Moreover,simulation verification through experimental results demonstrates the effectiveness of the proposed protection scheme across various initial fault angles,distances to faults,and fault transition resistances.

IMPROVED MODE-MATCHING AND NETWORK ANALYSIS OF E-PLANE WAVEGUIDE BRANCH DIRECTIONAL COUPLERS

The E-plane waveguide branch directional couplers are analyzed by a method which combines the multimode network theory with rigorous mode-matching approach. The electromagnetic field components are expanded by the superposition of LSEx modes rather than TE and TM modes in the mode-matching procedure. Meanwhile, the electromagnetic problem is transferred into the network problem through the mode-matching treatment. It is shown that the present method has the advantages of simplicity and less computation without affecting the accuracy of the calculation.

Capacity analysis of inhomogeneous hybrid wireless networks using directional antennas

Most of studies on network capacity are based on the assumption that all the nodes are uniformly distributed, which means that the networks are characterized by homogeneity. However, many realistic networks exhibit inhomogeneity due to natural and man-made reasons. In this work, the capacity of inhomogeneous hybrid networks with directional antennas for the first time is studied. By setting different node distribution probabilities, the whole network can be devided into dense cells and sparse cells. On this basis, an inhomogeneous hybrid network model is proposed. The network can exhibit significant inhomogeneity due to the coexistence of two types of cells. Then, we derive the network capacity and maximize the capacity under different channel allocation schemes. Finally, how the network parameters influence the network capacity is analyzed. It is found that if there are plenty of base stations, the per-node throughput can achieve constant order, and if the beamwidth of directional antenna is small enough, the network capacity can scale.

Directional Routing Algorithm for Deep Space Optical Network

With the development of science, economy and society, the needs for research and exploration of deep space have entered a rapid and stable development stage. Deep Space Optical Network(DSON) is expected to become an important foundation and inevitable development trend of future deepspace communication. In this paper, we design a deep space node model which is capable of combining the space division multiplexing with frequency division multiplexing. Furthermore, we propose the directional flooding routing algorithm(DFRA) for DSON based on our node model. This scheme selectively forwards the data packets in the routing, so that the energy consumption can be reduced effectively because only a portion of nodes will participate the flooding routing. Simulation results show that, compared with traditional flooding routing algorithm(TFRA), the DFRA can avoid the non-directional and blind transmission. Therefore, the energy consumption in message routing will be reduced and the lifespan of DSON can also be prolonged effectively. Although the complexity of routing implementation is slightly increased compared with TFRA, the energy of nodes can be saved and the transmission rate is obviously improved in DFRA. Thus the overall performance of DSON can be significantly improved.

Simulation &Performance Evaluation of QoS Routing Protocol for Adhoc Networks Using Directional Communication

A wireless ad-hoc network is a self-organized wireless network without fixed or backbone infrastructure. All nodes have routing capability and use peer-to-peer packet transmission or forward packets to other node using multi hop communication. Now days mobile ad-hoc networks are being used for different applications and traffics, so it require quality of service (QoS) support in routing protocol. In this paper, a modified QoS routing protocol using directional antenna has been proposed. High and normal priority can be assigned based on type of traffic. All the nodes in the path used by high priority flow are reserved as high priority flow for that flow and normal priority flow will avoid the paths used by high priority flows. If no disjoint paths are available, there may be two possibilities: Normal priority flows are blocked and other is, normal priority flows are allow using the coupled path with high priority flow. Blocking the normal priority flow, QoS routing protocol improves the performance of high priority flow. This concept may be use in emergency communication. Simulation results show that by assigning the priorities to flows, performance of high priority flows are improved and it will further improved by blocking the normal priority flow.

Coverage Analyses on Directional Transmissions Ultra-Dense Networks with Imperfect Beam Alignment

Blockage and imperfect beam alignment are two principal difficulties in high-frequency bands directional transmissions.In this paper,the coverage performance of downlink directional transmissions in ultra-dense networks is analyzed,with the consideration of beam alignment error and link blockage through stochastic geometry.Numerical experiments demonstrate that narrower beam leads to higher coverage probability with perfect beam alignment,but it is not the case with imperfect beam alignment.Therefore,the optimal beamwidth that maximize the coverage probability is characterized and a closed-form approximation of the optimal beamwidth is derived under imperfect beam alignment,accordingly.Furthermore,the optimal beamwidth is a monotonically increasing function of the standard deviation of the beam alignment error,and a monotonically decreasing function of the beamwidth of correspondent communication end,indicating that the beamwidth of the communication pairs ought to be jointly designed.

Collision Classification MAC Protocol for Underwater Acoustic Communication Networks Using Directional Antennas

Traditional underwater acoustic communication networks(UACNs)generally use omnidirectional transmission technology that causes a large number of data-packet collisions,thus resulting in low network throughput and high end-to-end delays.Compared with omnidirectional transmission technology,directional technology only sends and receives data packets in a specified direction.This can significantly reduce the probability of collisions and improve network performance.However,it also causes a deafness problem,which occurs when the sending node sends a data packet to the receiving node but the receiving node is unable to reply to the sender,because its antenna beam is closed.To resolve this issue,this study proposes a collision classification media access control(CC-MAC)protocol for UACNs.With this protocol,the underwater acoustic channel is divided into two subchannels,and the nodes transmit corresponding data types on them.The sending node can estimate the current status of the receiving node(i.e.,no collision,normal collision,deafness)according to the type of the data packet received and the sub-channel it arrived on,and it can choose correct options to improve network efficiency.Finally,we verify the performance of CC-MAC via simulations,showing that the protocol achieved higher network throughput and lower end-toend delays.

Fully Distributed Learning for Deep Random Vector Functional-Link Networks

In the contemporary era, the proliferation of information technology has led to an unprecedented surge in data generation, with this data being dispersed across a multitude of mobile devices. Facing these situations and the training of deep learning model that needs great computing power support, the distributed algorithm that can carry out multi-party joint modeling has attracted everyone’s attention. The distributed training mode relieves the huge pressure of centralized model on computer computing power and communication. However, most distributed algorithms currently work in a master-slave mode, often including a central server for coordination, which to some extent will cause communication pressure, data leakage, privacy violations and other issues. To solve these problems, a decentralized fully distributed algorithm based on deep random weight neural network is proposed. The algorithm decomposes the original objective function into several sub-problems under consistency constraints, combines the decentralized average consensus (DAC) and alternating direction method of multipliers (ADMM), and achieves the goal of joint modeling and training through local calculation and communication of each node. Finally, we compare the proposed decentralized algorithm with several centralized deep neural networks with random weights, and experimental results demonstrate the effectiveness of the proposed algorithm.

NEW PRINCIPLE FOR DIRECTIONAL COMPARISON CARRIER PROTECTION OF EHV TRANSMISSION LINES

The increasing scale and complexity of power systems require high performance and high reliability of power system protection.Protective relaying based on directional comparison with power line carrier or microwave channels is the most suitable protection scheme for long distance EHV transmission lines and is widely used in power systems.The key element of such protection is a directional relay used to discriminate the fault direction.In order to overcome the disadvantages of conventional directional relays,the authors of this paper put forward the directional comparison carrier protection based on the artificial neural network(ANN).The protection is extensively tested using electromagnetic transient program (EMTP) under various electric power system operating and fault conditions.It is proved that the directional comparison carrier protection based on ANN,which can recognize various fault patterns of the protected transmission line(such as fault direction,fault phases etc.)correctly in any kind of operating and fault conditions and the whole process,is satisfactory for EHV transmission line protection.

Economical quantum secure direct communication network with single photons

In this paper a scheme for quantum secure direct communication （QSDC） network is proposed with a sequence of polarized single photons. The single photons are prepared originally in the same state （0） by the servers on the network, which will reduce the difficulty for the legitimate users to check eavesdropping largely. The users code the information on the single photons with two unitary operations which do not change their measuring bases. Some decoy photons, which are produced by operating the sample photons with a Hadamard, are used for preventing a potentially dishonest server from eavesdropping the quantum lines freely. This scheme is an economical one as it is the easiest way for QSDC network communication securely.