Optimization of Charging/Battery-Swap Station Location of Electric Vehicles with an Improved Genetic Algorithm-Based Model

The joint location planning of charging/battery-swap facilities for electric vehicles is a complex problem.Considering the differences between these two modes of power replenishment,we constructed a joint location-planning model to minimize construction and operation costs,user costs,and user satisfaction-related penalty costs.We designed an improved genetic algorithm that changes the crossover rate using the fitness value,memorizes,and transfers excellent genes.In addition,the present model addresses the problem of“premature convergence”in conventional genetic algorithms.A simulated example revealed that our proposed model could provide a basis for optimized location planning of charging/battery-swapping facilities at different levels under different charging modes with an improved computing efficiency.The example also proved that meeting more demand for power supply of electric vehicles does not necessarily mean increasing the sites of charging/battery-swap stations.Instead,optimizing the level and location planning of charging/battery-swap stations can maximize the investment profit.The proposed model can provide a reference for the government and enterprises to better plan the location of charging/battery-swap facilities.Hence,it is of both theoretical and practical value.

Joint UAV 3D deployment and sensor power allocation for energy-efficient and secure data collection

Unmanned aerial vehicles(UAVs) are advantageous for data collection in wireless sensor networks(WSNs) due to its low cost of use,flexible deployment,controllable mobility,etc. However,how to cope with the inherent issues of energy limitation and data security in the WSNs is challenging in such an application paradigm. To this end,based on the framework of physical layer security,an optimization problem for maximizing secrecy energy efficiency(EE) of data collection is formulated,which focuses on optimizing the UAV’s positions and the sensors’ transmit power. To overcome the difficulties in solving the optimization problem,the methods of fractional programming and successive convex approximation are then adopted to gradually transform the original problem into a series of tractable subproblems which are solved in an iterative manner. As shown in simulation results,by the joint designs in the spatial domain of UAV and the power domain of sensors,the proposed algorithm achieves a significant improvement of secrecy EE and rate.

Uncertainty entropy-based exploratory evaluation method and its applications on missile effectiveness evaluation

Some attributes are uncertain for evaluation work because of incomplete or limited information and knowledge.It leads to uncertainty in evaluation results.To that end,an evaluation method,uncertainty entropy-based exploratory evaluation(UEEE),is proposed to guide the evaluation activities,which can iteratively and gradually reduce uncertainty in evaluation results.Uncertainty entropy(UE)is proposed to measure the extent of uncertainty.First,the belief degree distributions are assumed to characterize the uncertainty in attributes.Then the belief degree distribution of the evaluation result can be calculated by using uncertainty theory.The obtained result is then checked based on UE to see if it could meet the requirements of decision-making.If its uncertainty level is high,more information needs to be introduced to reduce uncertainty.An algorithm based on the UE is proposed to find which attribute can mostly affect the uncertainty in results.Thus,efforts can be invested in key attribute(s),and the evaluation results can be updated accordingly.This update should be repeated until the evaluation result meets the requirements.Finally,as a case study,the effectiveness of ballistic missiles with uncertain attributes is evaluated by UEEE.The evaluation results show that the target is believed to be destroyed.

Engineering Knill–Laflamme–Milburn Entanglement via Dissipation and Coherent Population Trapping in Rydberg Atoms

We present a scheme for dissipatively preparing bipartite Knill–Laflamme–Milburn(KLM)entangled state in a neutral atom system,where the spontaneous emission of excited Rydberg states,combined with the coherent population trapping,is actively exploited to engineer a steady KLM state from an arbitrary initial state.Instead of commonly used antiblockade dynamics of two Rydberg atoms,we particularly utilize the Rydberg–Rydberg interaction as the pumping source to drive the undesired states so that it is unnecessary to satisfy a certain relation with laser detuning.The numerical simulation of the master equation signifies that both the fidelity and the purity above 98%is available with the current feasible parameters,and the corresponding steady-state fidelity is robust to the variations of the dynamical parameters.

Multi-Antenna Jammer Assisted Covert Communications in Data Collected IoT with NOMA

In this paper,we investigate covert communications in data collected IoT with NOMA,where the paired sensor nodes S_(m) and S_(n) transmit covert messages to a legitimate receiver(Bob)in the presence of a Warden(Willie).To confuse the detection at Willie,an extra multi-antenna friendly jammer(Jammer)has been employed to transmit artificial noise(AN)with random power.Based on the CSI of Willie is available or not at Jammer,three AN transmission schemes,including null-space artificial noise(NAN),transmit antenna selection(TAS),and zeroforcing beamforming(ZFB),are proposed.Furthermore,the closed-form expressions of expected minimum detection error probability(EMDEP)and joint connection outage probability(JCOP)are derived to measure covertness and reliability,respectively.Finally,the maximum effective covert rate(ECR)is obtained with a given covertness constraint.The numerical results show that ZFB scheme has the best maximum ECR in the case of the number of antennas satisfies N>2,and the same maximum ECR can be achieved in ZFB and NAN schemes with N=2.Moreover,TAS scheme also can improve the maximum ECR compared with the benchmark scheme(i.e.,signal-antenna jammer).In addition,a proper NOMA node pairing can further improve the maximum ECR.

Concise and efficient direct-view generation of arbitrary cylindrical vector beams by a vortex half-wave plate

A concise, efficient, and practical direct-view scheme is presented to generate arbitrary cylindrical vector(CV)beams, including CV beams, vortex beams, and cylindrical vector vortex(CVV) beams, by a vortex half-wave plate(VHP). Six kinds of first-order and other high-order CV beams, such as azimuthally polarized(AP) beams, antivortex radial polarization mode beams, and three-order AP beams, are formed by simply rotating a half-wave plate. The Stokes parameters and double-slit interference of multitype CV beams are investigated in detail.The polarization parameters, including degree of polarization, polarization azimuth, and ellipticity, are obtained,which demonstrates the efficient generation of CV beams. In addition, the double-slit interference experiment is introduced in the setup, and fringe misplacement and tilt appear for CVV beams, in which the misplacement number M is 2P+1 for P ≤ 2 and 2P-1 for P ≥ 3, where P is the polarization order number, and the fringe tilt offset is positively related to the topological charge number l of CVV beams. In addition, new types of VHPs can be formed by cascading two or more VHPs when the types of available VHPs are limited, assisting in more flexible generation of multitype CV beams. It is experimentally demonstrated that arbitrary CV beams with high quality are effectively achieved by the proposed setup, and the double-slit interference method can be utilized to determine and analyze CV beams rapidly and concisely by practical performance, which shows the potential to be implemented as a commercial device.

针对异质群体的高质量轨迹规划方法（英文）

基于具有最大速度和最大加速度约束的轨迹规划方法,针对人群仿真中的异质群体,提出一种新颖的高质量轨迹规划方法。该方法能够保证个体的运动路径是平滑的,个体的速度是连续的。考虑到真实人具有最大速度和最大加速度的生理学约束,本文首先推导出一种时间最优的轨迹和可行域来解决kinodynamic规划问题。随后,通过计算具有恰当速度多样性的轨迹设计出一种高质量的轨迹规划方法。仿真结果表明提出的轨迹规划方法具有更高的真实性,能够为人群仿真中的虚拟人提供高质量的运动轨迹。

Measurement-driven Gauss-Hermite particle filter with soft spatiotemporal constraints for multi-optical theodolites target tracking

Multi-Optical Theodolite Tracking systems(MOTTs)can stealthily extract the target’s status information from bearings only through non-contact measurement.The constrained MOTTs are partially compatible,yet many existing research works and results are based on the known model,ignoring its discrimination with the target maneuvering behavior pattern.To compensate for these mismatches,this paper develops a Measurement-driven Gauss-Hermite Particle Filter(MGHPF),which elegantly fuses the spatiotemporal constraints and its soft form to perform MOTT missions.Specifically,the target dynamic model and tracking algorithm are based on the target behavior pattern with the adaptive turn rate,fully exploiting the spatial epipolar geometry characteristics for each intersection measurement by a minimax strategy.Then,the center of the feasible area is approximated via the analytic coordinate transformation,and the latent samples are updated via the deterministic Gauss-Hermite integral method with the target’s predictive turn rate.Simultaneously,the effects of truncation correction and compensation feedback from the current measurement and historical estimation data are adaptively incorporated into the PF’s importance distribution to cover the mixture likelihood.Besides,an effective causality-invariant updating rule is provided to estimate the parameters of these soft spatiotemporal constrained MOTTs with convergence guarantees.Simulated and measured results show good agreement;compared with the stateof-the-art Multi-Model Rao-Blackwell Particle Filter(MMRBPF),the proposed MGHPF improves the filtering accuracy by 7.4%-34.7%and significantly reduces the computational load.

Mission-oriented cooperative 3D path planning for modular solar-powered aircraft with energy optimization

Modular Solar-Powered Aircraft(M-SPA)is a kind of High-Altitude Long-Endurance(HALE)aircraft which exploits the mission advantage of swarm UAV and the HALE advantage of large aspect-ratio SPA.M-SPA’s separated mode and combined mode give it the potential to maximize the mission efficiency with limited solar energy.In this paper,firstly,oriented by the mission of maximizing the cruise area,the overall design of the M-SPA is modeled,including the energy model,the aerodynamic model and the flight environment settings.Secondly,by analyzing the energy consumption of the flight modes,we design a multi-phase flight mission strategy.Then,a 24-hour three-dimensional(3D)flight profile of the M-SPA is optimized,including the sub-SPA cooperative path planning in the separation mode.Finally,inspired by the Traveling Salesman Problem(TSP),an improved Ant Colony Algorithm(ACA)is exploited to find the optimal path for each sub-SPA,which is further developed into a dynamic separation and combination scheme for the M-SPA.The simulation results show that the mission performance of the M-SPA outperforms that of the conventional SPA,and explicitly,the mission coverage of the M-SPA is slightly less than a linear increase under comparable simulation conditions.

Future Changes in the Impact of North Pacific Midlatitude Oceanic Frontal Intensity on the Wintertime Storm Track in CMIP5 Models

The storm track and oceanic front play an important role in the midlatitude air–sea interaction.In this study,future changes in the impact of the North Pacific midlatitude oceanic frontal intensity on the wintertime storm track are projected based on climate model outputs from the Coupled Model Intercomparison Project Phase 5(CMIP5).The performance of 13 CMIP5 models is evaluated,and it is found that a majority of these models are capable of reproducing the northward intensification of the storm track in response to the strengthened oceanic front.The ensemble means of outputs from six best models under three Representative Concentration Pathway(RCP)scenarios(RCP2.6,RCP4.5,and RCP8.5)are compared with the results of the historical simulation,and future changes are projected.It is found that the impact of the oceanic frontal intensity on the storm track tends to get stronger and extends further westward in a warming climate,and the largest increase appears in the RCP8.5 run.Further analysis reveals that the stronger impact of the oceanic front on the storm track in the future may be partially attributed to the greater oceanic frontal impact on the near-surface baroclinicity,which is mainly related to the intensified oceanic frontal impact on the meridional potential temperature gradient under the climate change scenario.However,this process can hardly explain the increasing impact of the oceanic front on the upstream of the storm track.

Energy-Efficient and Secure Power Allocation and Trajectory Optimization for UAV-Enabled Data Collection in Wireless Sensor Networks

Using unmanned aerial vehicles(UAVs)to collect data in wireless sensor networks(WSNs)has advantages of controllable mobility and flexible deployment.However,there are potential challenges of energy limitation and data security which may limit such applications.To cope with these challenges,a complicated and intractable optimization problem is formulated,which maximizes the performance metric of secrecy energy efficiency(EE)subject to the constraints of secrecy rate,maximum power,and trajectory.Then,an energy-efficient and secure solution is developed to improve the secrecy EE of the UAV-enabled data collection in the WSNs by joint optimizing the UAV’s trajectory and velocity along with the sensors’power.The proposed solution is an iterative algorithm based on the optimization approaches of alternating optimization,successive convex approximation,and fractional programming.Simulation results demonstrate that the proposed solution scheme is effective for improving the secrecy EE while guaranteeing the data security.

Recent Progress in Fiber-Optic Hydrophones

Fiber-optic hydrophone (FOH) is a significant type of acoustic sensor, which can be used in both military and civilian fields such as underwater target detection, oil and natural gas prospecting, and earthquake inspection. The recent progress of FOH is introduced from five aspects, including large-scale FOH array, very-low-frequency detection, fiber-optic vector hydrophone (FOVH), towed linear array, and deep-sea and long-haul transmission. The above five aspects indicate the future development trends in the FOH research field, and they also provide a guideline for the practical applications of FOH as well as its array.