Actor-Critic-Based UAV-Assisted Data Collection in the Wireless Sensor Network

Wireless Sensor Network(WSN)is widely utilized in large-scale distributed unmanned detection scenarios due to its low cost and flexible installation.However,WSN data collection encounters challenges in scenarios lacking communication infrastructure.Unmanned aerial vehicle(UAV)offers a novel solution for WSN data collection,leveraging their high mobility.In this paper,we present an efficient UAV-assisted data collection algorithm aimed at minimizing the overall power consumption of the WSN.Firstly,a two-layer UAV-assisted data collection model is introduced,including the ground and aerial layers.The ground layer senses the environmental data by the cluster members(CMs),and the CMs transmit the data to the cluster heads(CHs),which forward the collected data to the UAVs.The aerial network layer consists of multiple UAVs that collect,store,and forward data from the CHs to the data center for analysis.Secondly,an improved clustering algorithm based on K-Means++is proposed to optimize the number and locations of CHs.Moreover,an Actor-Critic based algorithm is introduced to optimize the UAV deployment and the association with CHs.Finally,simulation results verify the effectiveness of the proposed algorithms.

New Rural Community Construction or Retention Development:A Comparative Analysis of Rural Settlement Transition Mechanism in Plain Agriculture Area of China Based on Actor Network Theory

It is an important way to realize rural revitalization and sustainable development to guide rural settlement transition(RST)in an appropriate way.This paper uses actor network theory(ANT)to construct a theoretical framework for the study of RST.Taking two typical villages with different transition paths in rural areas of North China Plain as examples,this paper reveals the mechanism of RST and makes a comparative analysis.The results show that:1)after identifying problems and obligatory passage point,key actors recruit heterogeneous actors into the actor network by entrusting them with common interests,and realize RST under the system operation.2)Rural settlements under different transition paths have similarities in the problems to be solved,collective actions and policy factors,but there are differences in the transition process,mechanism and effect.The actor network and mechanism of RST through the path of new rural community construction are more complex and the transition effect is more thorough.In contrast,the degree of RST of retention development path is limited if there is no resource and location advantage.3)Based on the applicable conditions of different paths,this paper designs a logical framework of‘Situation-Structure-Behavior-Result’to scientifically guide the identification of RST paths under the background of rural revitalization.

Actor-critic框架下的二次指派问题求解方法

二次指派问题(QAP)属于NP-hard组合优化问题,在现实生活中有着广泛应用。目前相对成熟的启发式算法通常以问题为导向来设计定制化算法,缺乏迁移泛化能力。为提供一个统一的QAP求解策略,将QAP问题的流量矩阵及距离矩阵抽象成两个无向完全图并构造相应的关联图,从而将设施和地点的指派任务转化为关联图上的节点选择任务,基于actor-critic框架,提出一种全新的求解算法ACQAP。首先,利用多头注意力机制构造策略网络,处理来自图卷积神经网络的节点表征向量;然后,通过actor-critic算法预测每个节点被作为最优节点输出的概率;最后,依据该概率在可行时间内输出满足目标奖励函数的动作决策序列。该算法摆脱人工设计,且适用于不同规模的输入,更加灵活可靠。实验结果表明,在QAPLIB实例上,本算法在精度媲美传统启发式算法的前提下,迁移泛化能力更强;同时相对于NGM等基于学习的算法,求解的指派费用与最优解之间的偏差最小,且在大部分实例中,偏差均小于20%。

Assessment of challenges and strategies for driving energy transitions in emerging markets:A socio-technological systems perspective

The pursuit of improved quality of life standards has significantly influenced the contemporary mining model in the 21st century.This era is witnessing an unprecedented transformation driven by pressing concerns related to sustainability,climate change,the just energy transition,dynamic operating environments,and complex social challenges.Such transitions present both opportunities and obstacles.The aim of this study is to provide an extensive literature review on energy transition to identify the challenges and strategies associated with navigating transformations in energy systems.Understanding these transformations is particularly critical in the face of the severe consequences of global warming,where an accelerated energy transition is viewed as a universal remedy.Adopting a socio-technological systems perspective,specifically through the application of Actor Network Theory(ANT),this research provides a theoretical foundation while categorising challenges into five distinct domains and outlining strategies across these different dimensions.These insights are specifically tailored for emerging market countries to effectively navigate energy transition while fostering the development of resilient societies.Furthermore,our findings highlight that energy transition encompasses more than a mere technological shift;it entails fundamental changes in various systemic socio-economic imperatives.Through focusing on the role of social structures in transitions,this study makes a significant and innovative contribution to ANT,which has historically been criticised for its limited acknowledgement of social structures.Consequently,we propose an emerging market energy transition framework,which not only addresses technological aspects,but also integrates social considerations.This framework paves the way for future research and exploration of energy transition dynamics.The outcomes of this study offer valuable insights to policymakers,researchers,and practitioners engaged in the mining industry,enabling them to comprehend the multifaceted challenges involved and providing practical strategies for effective resolution.Through incorporating the social dimension into the analysis,we enhance the understanding of the complex nature of energy system transformations,facilitating a more holistic approach towards achieving sustainable and resilient energy transitions in emerging markets and beyond.

Multifunctional Landscape Actor-Network Construction from the Perspective of Rural Tourism Experiences

During the construction of multifunctional landscape(MFL) actor-network, economic, social, and ecological functions presented significant differences, which resulted from the different roles and effects of various heterogeneous actors according to the tourism experience. In Hekou Village at the border area between China and North Korea, the roles and effects of heterogeneous actors during the MFL actor-network construction were analyzed by means of the analytic network process(ANP), which verified the Groundings-Entrepreneurship-Markets(GEM) theoretical framework of the MFL actor-network that assumed tourism experiences were core actors, and economic, social, and ecological landscape actors acted as support. Research results showed that in the MFL actornetwork construction, social and economic functions of landscapes were strong, while ecological and tourism experience functions were weak and that folk customs and land utilization were key actors of the MFL actor-network construction. In the MFL actor-network construction, actors played different roles and had different effects on the network. Intelligence facilities and rurality were critical to drive the MFL actor network translation process and pass through "obligatory passage point". By changing the interaction mode and intensity of the actors, the MFL actor-network could be promoted.

基于CDKF-RBFPID的激光器恒流源控制器

激光器的稳定工作需要一个输出电流精度高和稳定的恒流源控制系统。针对激光器恒流源系统在噪声环境下输出精度差且使用PID算法参数难整定的问题,提出一种基于中心差分卡尔曼滤波(Center Differential Kalman Filter,CDKF)与改进的径向基函数(Radial Basis Function,RBF)神经网络自适应PID控制相结合的算法CDKF-RBFPID。通过CDKF更新恒流源系统的状态、协方差,从而滤除系统中的状态噪声和测量噪声。利用强化学习Actor-Critic框架调整RBF-PID参数,实现自适应参数调整。对恒流源系统输出电流和激光器输出功率进行对比实验,结果表明:CDKF RBFPID算法能够有效降低噪声对系统的影响,恒流源输出电流精度以及激光器输出功率稳定性进一步提升,其中响应时间缩短了58.3%,稳态误差降低了71.4%,输出电流控制精度达到1%。

Enhancing real-time performance via controlled actor relocation in wireless sensor and actor networks

Actors'relocation is utilized during the network initialization to enhance real-time performance of wireless sensor and actor networks(WSANs)which is an important issue of WSANs.The actor deployment problem in WSANs is proved NP-Hard whether the amount of actors is redundant or not,but to the best of our knowledge,no effective distributed algorithms in previous research can solve the problem.Thus two actor deployment strategies which need not the boundary control compared with present deployment strategies are proposed to solve this problem approximately based on the Voronoi diagram.Through simulation experiment,the results show that our distributed strategies are more effective than the present deployment strategies in terms of real-time performance,convergence time and energy consumption.

Cyber Resilience through Real-Time Threat Analysis in Information Security

This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].

一种自适应模糊Actor-Critic学习

提出一种基于模糊RBF网络的自适应模糊A ctor-C ritic学习.采用一个模糊RBF神经网络同时逼近A ctor的动作函数和C ritic的值函数,解决状态空间泛化中易出现的“维数灾”问题.模糊RBF网络能够根据环境状态和被控对象特性的变化进行网络结构和参数的自适应学习,使得网络结构更加紧凑,整个模糊A ctor-C ritic学习具有泛化性能好、控制结构简单和学习效率高的特点.M oun ta in C ar的仿真结果验证了所提方法的有效性.

乡村农旅产业行动者社交网络结构特征研究--以珠三角A市H镇乡村为例

乡村振兴重点是产业振兴,在资金、政策等投入下,投资有效性无法保证。乡村产业规模小,个体行动者在产业中影响大,引入行动者网络和社交网络分析,解读村域尺度下各类行动者如何影响乡村产业成败。首先,用行动者网络绘制分析图谱;其次,用社交网络分析主导能力、稳定性、关联性,分析网络模型的结构特征;最后,运用个体质性分析。结果:一,行动者的投入空间聚集明显,网络呈现线性与复杂性;二,成功产业网络具有结构紧密、整体关联性强且较为稳定的特征;三,行动者支持程度与投入个人(团体)的协调能力对成败影响最大。

基于多智能体柔性演员-评论家学习的服务功能链部署算法

针对网络功能虚拟化(NFV)架构下业务请求动态变化引起的服务功能链(SFC)部署优化问题,该文提出一种基于多智能体柔性演员-评论家(MASAC)学习的SFC部署优化算法。首先,建立资源负载惩罚、SFC部署成本和时延成本最小化的模型,同时受限于SFC端到端时延和网络资源预留阈值约束。其次,将随机优化问题转化为马尔可夫决策过程(MDP),实现SFC动态部署和资源的均衡调度,还进一步提出基于业务分工的多决策者编排方案。最后,在分布式多智能体系统中采用柔性演员-评论家(SAC)算法以增强探索能力,并引入了中央注意力机制和优势函数,能够动态和有选择性地关注获取更大部署回报的信息。仿真结果表明,所提算法可以实现负载惩罚、时延和部署成本的优化,并随业务请求量的增加能更好地扩展。

Dynamic Coverage with Wireless Sensor and Actor Networks in Underwater Environment

This paper studies the problem of dynamic coverage with wireless sensor and actor networks (WSANs) in underwater environment. Different from most existing works, the WSANs consist of two kinds of nodes, i.e., sensor nodes (SNs) which cannot move autonomously and actor nodes (ANs) which can move autonomously according to the performance requirement. The problem of how to coordinate two kinds of nodes to facilitate dynamic coverage in underwater environment is challenging due to their heterogeneous capabilities. To reduce redundancy of communication links and improve connectivity between ANs and SNs in underwater WSANs, a min-weighted rigid graph based topology optimization scheme is first developed, such that the underwater communication energy consumption can be saved. With the optimized topology, a dynamic coverage strategy is proposed to improve the coverage among SNs and ANs for underwater WSAN where underwater fluid motions are considered. Furthermore, it is proved that the network coverage area is connected by using the min-weighted rigid graph. Finally, simulation results are presented to show the effectiveness of the main results. © 2014 Chinese Association of Automation.

The ZigBee Based Wireless Sensor and Actor Network in Intelligent Space Oriented to Home Service Robot

In the study of intelligent space oriented to home service robot, an important technology is how to construct an communication network which has the characters of high reliability and easy building. In this paper, based on the characteristics of ZigBee protocol, ZigBee technology is used to construct a wireless sensor and actor network. Several intelligent services based on ZigBee wireless sensor and actor network are shown to certify the reliability of this communication network. ZigBee wireless sensor and actor network builds an information bridge for the components in the intelligent space, the spatially distributed devices are connected together seamlessly. With this network, robot can share the mass information in the intelligent space and improve its performance with 'light-packs', devices in intelligent space, such as lamp, curtain can be controlled autonomously.

基于替代迹的蜂窝网信道分配Actor-Critic算法

针对D2D混合蜂窝网络在进行信道分配时难以在较高信噪比条件下进行自动信道分配的问题,提出了一种基于替代迹的蜂窝网络信道分配Actor-Critic算法。首先定义了信道分配问题的MDP模型,然后定义了基于替代迹的Actor-Critic算法。Actor采用模拟退火探索策略自适应控制状态空间的搜索,将critic部分求解的值函数的时间差分误差用于更新该策略的优先级,再依优先级对策略进行更新;critic部分采用基于替代迹的值函数更新方式,并计算值函数的时间差分误差,以指导actor改进策略。实验结果表明其具有系统吞吐量大和信噪比高的优点。

Monitoring subsidence rates along road network by persistent scatterer SAR interferometry with high-resolution TerraSAR-X imagery

Ground subsidence is one of the key factors damaging transportation facilities, e.g., road networks consisting of highways and railways. In this paper, we propose to apply the persistent scatterer synthetic aperture radar interferometry （PS-InSAR） approach that uses high- resolution TerraSAR-X （TSX） imagery to extract the regional scale subsidence rates （i.e., average annual sub- sidence in mm/year） along road networks. The primary procedures involve interferometric pair selection, interfer- ogram generation, persistent scatterer （PS） detection, PS networking, phase parameterization, and subsidence rate estimation. The Xiqing District in southwest Tianjin （China） is selected as the study area. This district contains one railway line and several highway lines. A total of 15 TSX images covering this area between April 2009 and June 2010 are utilized to obtain the subsidence rates by using the PS-InSAR （PSI） approach. The subsidence rates derived from PSI range from -68.7 to -1.3 mm/year. These findings show a significantly uneven subsidence pattern along the road network. Comparison between the PSI-derived subsidence rates and the leveling data obtained along the highways shows that the mean and standard deviation （SD） of the discrepancies between the two types of subsidence rates are 0.1 and 4-3.2 mm/year, respectively. The results indicate that the high-resolution TSX PSI is capable of providing comprehensive and detailed subsidence information regarding road networks with millimeter-level accuracy. Further inspections under geo- logical conditions and land-use categories in the study area indicate that the observed subsidence is highly related to aquifer compression due to groundwater pumping. Therefore, measures should be taken to mitigate groundwater extraction for the study area.

社交媒体虚假信息的动态成因与治理启示--基于行动者网络理论视角的分析

将行动者网络理论引入社交媒体虚假信息的动态生成原因分析,遵循该理论框架,通过对不同行动者及互动关系的分层阐述,挖掘虚假信息的生成条件与状态,并据此提出相应的治理启示与思路,实践目标在于从源头上减少并遏制虚假信息的生成。

Prediction of flow stress of Ti-15-3 alloy with artificial neural network

Hot compression experiments were conducted on Ti 15 3 alloy specimens using Gleeble 1500 Thermal Simulator.These tests were focused to obtain the flow stress data under various conditions of strain,strain rate and temperature. On the basis of these data, the predicting model for the nonlinear relation between flow stress and deformation strain,strain rate and temperature for Ti 15 3 alloy was developed with a back propagation artificial neural network method. Results show that the neural network can reproduce the flow stress in the sampled data and predict the nonsampled data well. Thus the neural network method has been verified to be used to tackle hot deformation problems of Ti 15 3 alloy. [

Cognitive amplify-and-forward dual-hop relay networks over α-μ fading channels

This paper provides an analytic performance evaluation of dual-hop cognitive amplify-and-forward (AF) relaying networks over independent nonidentically distributed (i.n.i.d.) fading channels. Two different transmit power constraint strategies at the secondary network are proposed to investigate the performance of the secondary network. In the case of combined power constraint,the maximum tolerable interference power on the primary network and the maximum transmit power at the secondary network are considered. Closed-form lower bound and its asymptotic expression for the outage probability (OP) are achieved. Utilizing the above results,average symbol error probability (ABEP) at high signal-to-noise ratios (SNRs) are also derived. In order to further study the performance of dual-hop cognitive AF relaying networks,the Closed-form lower bounds and asymptotic expressions for OP with single power constraint of the tolerable interference on the primary network is also obtained. Both analytical and simulation are employed to validate the accuracy of the theoretical analysis. The results show that the secondary network obtains a better performance when higher power constraint is employed.

A new algorithm for wireless sensor network based on NS-2

Considering wireless sensor network characteristics,this paper uses network simulator,version2(NS-2)algorithm to improve Ad hoc on-demand distance vector(AODV)routing algorithm,so that it can be applied to wireless sensor networks.After studying AODV routing protocol,a new algorithm called Must is brought up.This paper introduces the background and algorithm theory of Must,and discusses the details about how to implement Must algorithm.At last,using network simulator(NS-2),the performance of Must is evaluated and compared with that of AODV.Simulation results show that the network using Must algorithm has perfect performance.