An Optimization Approach of IoD Deployment for Optimal Coverage Based on Radio Frequency Model

Recently,Internet of Drones(IoD)has garnered significant attention due to its widespread applications.However,deploying IoD for area coverage poses numerous limitations and challenges.These include interference between neighboring drones,the need for directional antennas,and altitude restrictions for drones.These challenges necessitate the development of efficient solutions.This research paper presents a cooperative decision-making approach for an efficient IoDdeployment to address these challenges effectively.The primary objective of this study is to achieve an efficient IoDdeployment strategy thatmaximizes the coverage regionwhile minimizing interference between neighboring drones.In deployment problem,the interference increases as the number of deployed drones increases,resulting in bad quality of communication.On the other hand,deploying a few drones cannot satisfy the coverage demand.To accomplish this,an enhanced version of a concise population-based meta-heuristic algorithm,namely Improved Particle SwarmOptimization(IPSO),is applied.The objective function of IPSO is defined based on the coverage probability,which is primarily influenced by the characteristics of the antennas and drone altitude.A radio frequency(RF)model is derived to evaluate the coverage quality,considering both Line of Sight(LOS)and Non-Line of Sight(NLOS)down-link coverage probabilities for ground communication.It is assumed that each drone is equipped with a directional antenna to optimize coverage in a given region.Extensive simulations are conducted to assess the effectiveness of the proposed approach.Results demonstrate that the proposed method achieves maximum coverage with minimum transmission power.Furthermore,a comparison is made against Collaborative Visual Area Coverage Approach(CVACA),and a game-based approach in terms of coverage quality and convergence speed.The simulation results reveal that our approach outperforms both CVACA and the gamebased schemes in terms of coverage and convergence speed.Comparisons validate the superiority of our approach over existing methods.To assess the robustness of the proposed RFmodel,we have considered two distinct ranges of noise:range1 spanning from−120 to−90 dBm,and range2 spanning from−90 to−70 dBmfor different numbers of UAVs.In summary,this research presents a cooperative decision-making approach for efficient IoD deployment to address the challenges associatedwith area coverage and achieves an optimal coveragewithminimal interference.

Mathematical Modeling and Design of RIS Deployment in a RIS-Assisted Metal Cuboid for WAIC Systems

Wireless avionics intra-communications(WAIC)is an emergent research topic,since it can improve fuel efficiency and enhance aircraft safety significantly.However,there are numerous baffles in an aircraft,e.g.,seats and cabin bulkheads,resulting in serious blockage and even destroying wireless communications.Thus,this paper focuses on the reconfigurable intelligent surface(RIS)deployment issue of RIS-assisted WAIC systems,to solve the blockage problem caused by baffles.We first propose the mirror-symmetric imaging principle for mathematically analyzing electromagnetic(EM)wave propagation in a metal cuboid,which is a typical structure of WAIC systems.Based on the mirror-symmetric imaging principle,the mathematical channel model in a metal cuboid is deduced in detail.In addition,we develop an objective function of RIS's location and deduce the optimal RIS deployment location based on the geometric center optimization lemma.A two-dimensional gravity center search algorithm is then presented.Simulation results show that the designed RIS deployment can greatly increase the received power and efficiently solve the blockage problem in the aircraft.

Dynamic modeling of spacecraft solar panels deployment with Lie group variational integrator

The spacecraft with multistage solar panels have nonlinear coupling between attitudes of central body and solar panels, especially the rotation of central body is considered in space. The dynamics model is based for dynamics analysis and control, and the multistage solar panels means the dynamics modeling will be very complex. In this research, the Lie group variational integrator method is introduced, and the dynamics model of spacecraft with solar panels that connects together by flexible joints is built. The most obvious character of this method is that the attitudes of central body and solar panels are all described by three-dimensional attitude matrix. The dynamics models of spacecraft with one and three solar panels are established and simulated. The study shows Lie group variational integrator method avoids parameters coupling and effectively reduces difficulty of modeling. The obtained continuous dynamics model based on Lie group is a set of ordinary differential equations and equivalent with traditional dynamics model that offers a basis for the geometry control.

Optimization and Deployment of Memory-Intensive Operations in Deep Learning Model on Edge

As a large amount of data is increasingly generated from edge devices,such as smart homes,mobile phones,and wearable devices,it becomes crucial for many applications to deploy machine learning modes across edge devices.The execution speed of the deployed model is a key element to ensure service quality.Considering a highly heterogeneous edge deployment scenario,deep learning compiling is a novel approach that aims to solve this problem.It defines models using certain DSLs and generates efficient code implementations on different hardware devices.However,there are still two aspects that are not yet thoroughly investigated yet.The first is the optimization of memory-intensive operations,and the second problem is the heterogeneity of the deployment target.To that end,in this work,we propose a system solution that optimizes memory-intensive operation,optimizes the subgraph distribution,and enables the compiling and deployment of DNN models on multiple targets.The evaluation results show the performance of our proposed system.

Formal Approach to Workow Application Fragmentations Over Cloud Deployment Models

Workow management technologies have been dramatically improving their deployment architectures and systems along with the evolution and proliferation of cloud distributed computing environments.Especially,such cloud computing environments ought to be providing a suitable distributed computing paradigm to deploy very large-scale workow processes and applications with scalable on-demand services.In this paper,we focus on the distribution paradigm and its deployment formalism for such very large-scale workow applications being deployed and enacted across the multiple and heterogeneous cloud computing environments.We propose a formal approach to vertically as well as horizontally fragment very large-scale workow processes and their applications and to deploy the workow process and application fragments over three types of cloud deployment models and architectures.To concretize the formal approach,we rstly devise a series of operational situations fragmenting into cloud workow process and application components and deploying onto three different types of cloud deployment models and architectures.These concrete approaches are called the deployment-driven fragmentation mechanism to be applied to such very large-scale workow process and applications as an implementing component for cloud workow management systems.Finally,we strongly believe that our approach with the fragmentation formalisms becomes a theoretical basis of designing and implementing very large-scale and maximally distributed workow processes and applications to be deployed on cloud deployment models and architectural computing environments as well.

Hybrid Power Bank Deployment Model for Energy Supply Coverage Optimization in Industrial Wireless Sensor Network

Energy supply is one of the most critical challenges of wireless sensor networks(WSNs)and industrial wireless sensor networks(IWSNs).While research on coverage optimization problem(COP)centers on the network’s monitoring coverage,this research focuses on the power banks’energy supply coverage.The study of 2-D and 3-D spaces is typical in IWSN,with the realistic environment being more complex with obstacles(i.e.,machines).A 3-D surface is the field of interest(FOI)in this work with the established hybrid power bank deployment model for the energy supply COP optimization of IWSN.The hybrid power bank deployment model is highly adaptive and flexible for new or existing plants already using the IWSN system.The model improves the power supply to a more considerable extent with the least number of power bank deployments.The main innovation in this work is the utilization of a more practical surface model with obstacles and training while improving the convergence speed and quality of the heuristic algorithm.An overall probabilistic coverage rate analysis of every point on the FOI is provided,not limiting the scope to target points or areas.Bresenham’s algorithm is extended from 2-D to 3-D surface to enhance the probabilistic covering model for coverage measurement.A dynamic search strategy(DSS)is proposed to modify the artificial bee colony(ABC)and balance the exploration and exploitation ability for better convergence toward eliminating NP-hard deployment problems.Further,the cellular automata(CA)is utilized to enhance the convergence speed.The case study based on two typical FOI in the IWSN shows that the CA scheme effectively speeds up the optimization process.Comparative experiments are conducted on four benchmark functions to validate the effectiveness of the proposed method.The experimental results show that the proposed algorithm outperforms the ABC and gbest-guided ABC(GABC)algorithms.The results show that the proposed energy coverage optimization method based on the hybrid power bank deployment model generates more accurate results than the results obtained by similar algorithms(i.e.,ABC,GABC).The proposed model is,therefore,effective and efficient for optimization in the IWSN.

Dynamics and rebound behavior analysis of flexible tethered satellite system in deployment and station-keeping phases

The tether deployment of a tethered satellite system involves the consideration of complex dynamic properties of the tether,such as large deformation,slack,and even rebound,and therefore,the dynamic modelling of the tether is necessary for performing a dynamic analysis of the system.For a variablelength tether element,the absolute nodal coordinate formulation(ANCF)in the framework of the arbitrary Lagrange-Euler(ALE)description was used to develop a precise dynamic model of a tethered satellite.The model considered the gravitational gradient force and Coriolis force in the orbital coordinate frame,and it was validated through numerical simulation.In the presence of dynamic constraints,a deployment velocity of the tether was obtained by an optimal procedure.In the simulation,rebound behavior of the tethered satellite system was observed when the ANCF-ALE model was employed.Notably,the rebound behavior cannot be predicted by the traditional dumbbell model.Furthermore,an improved optimal deployment velocity was developed.Simulation results indicated that the rebound phenomenon was eliminated,and smooth deployment as well as a stable state of the station-keeping process were achieved.Additionally,the swing amplitude in the station-keeping phase decreased when a deployment strategy based on the improved optimal deployment velocity was used.

Modular Extremely Large-Scale Array Communication:Near-Field Modelling and Performance Analysis

This paper investigates the wireless communication with a novel architecture of antenna arrays,termed modular extremely large-scale array(XLarray),where array elements of an extremely large number/size are regularly mounted on a shared platform with both horizontally and vertically interlaced modules.Each module consists of a moderate/flexible number of array elements with the inter-element distance typically in the order of the signal wavelength,while different modules are separated by the relatively large inter-module distance for convenience of practical deployment.By accurately modelling the signal amplitudes and phases,as well as projected apertures across all modular elements,we analyse the near-field signal-to-noise ratio(SNR)performance for modular XL-array communications.Based on the non-uniform spherical wave(NUSW)modelling,the closed-form SNR expression is derived in terms of key system parameters,such as the overall modular array size,distances of adjacent modules along all dimensions,and the user's three-dimensional(3D)location.In addition,with the number of modules in different dimensions increasing infinitely,the asymptotic SNR scaling laws are revealed.Furthermore,we show that our proposed near-field modelling and performance analysis include the results for existing array architectures/modelling as special cases,e.g.,the collocated XL-array architecture,the uniform plane wave(UPW)based far-field modelling,and the modular extremely large-scale uniform linear array(XL-ULA)of onedimension.Extensive simulation results are presented to validate our findings.

Dynamic analysis and nonlinear identification of space deployable structure

The dynamic equivalent continuum modeling method of the mast which is based on energy equivalency principle was investigated. And three kinds of mast dynamic model were established, which were equivalent continuum model, finite element model and simulation model, respectively. The mast frequencies and mode shapes were calculated by these models and compared with each other. The error between the equivalent continuum model and the finite element model is less than 5% when the mast length is longer. Dynamic responses of the mast with different lengths are tested, the mode frequencies and mode shapes are compared with finite element model. The mode shapes match well with each other, while the frequencies tested by experiments are lower than the results of the finite element model, which reflects the joints lower the mast stiffness. The nonlinear dynamic characteristics are presented in the dynamic responses of the mast under different excitation force levels. The joint nonlinearities in the deployable mast are identified as nonlinear hysteresis contributed by the coulomb friction which soften the mast stiffness and lower the mast frequencies.

Analytical and computational modelling for wave energy systems：the example of oscillating wave surge converters

The development of new wave energy converters has shed light on a number of unanswered questions in fluid mechanics, but has also identified a number of new issues of importance for their future deployment. The main concerns relevant to the practical use of wave energy converters are sustainability, survivability, and maintainability. Of course,it is also necessary to maximize the capture per unit area of the structure as well as to minimize the cost. In this review, we consider some of the questions related to the topics of sustainability, survivability, and maintenance access, with respect to sea conditions, for generic wave energy converters with an emphasis on the oscillating wave surge converter. New analytical models that have been developed are a topic of particular discussion. It is also shown how existing numerical models have been pushed to their limits to provide answers to open questions relating to the operation and characteristics of wave energy converters.

Dynamic Characteristics of Planar Deployable Structure Based on ScissorLike Element Using Influence Coefficient Method

In order to execute geometric analysis for planar deployable mechanism of scissors unit,the dynamic analysis model of scissor planar deployable structure is created based on the Cartesian coordinate system,the influence coefficient is acquired by means of the coordinate transformation,combining the D 'Alembert 's principle with Dynamic-Static method,the dynamic characteristic analysis is completed finally. Moreover,specific calculating examples are adopted to verify the effectiveness of proposed method,and the result shows that the movement of each component of scissors unit mechanism is more smooth during initial deployment stage,however,when the configuration angle θ of unit mechanism is approaching π,some comparative large variations would appear on movement parameters and hinge constraint force.

Joint On-Demand Pruning and Online Distillation in Automatic Speech Recognition Language Model Optimization

Automatic speech recognition(ASR)systems have emerged as indispensable tools across a wide spectrum of applications,ranging from transcription services to voice-activated assistants.To enhance the performance of these systems,it is important to deploy efficient models capable of adapting to diverse deployment conditions.In recent years,on-demand pruning methods have obtained significant attention within the ASR domain due to their adaptability in various deployment scenarios.However,these methods often confront substantial trade-offs,particularly in terms of unstable accuracy when reducing the model size.To address challenges,this study introduces two crucial empirical findings.Firstly,it proposes the incorporation of an online distillation mechanism during on-demand pruning training,which holds the promise of maintaining more consistent accuracy levels.Secondly,it proposes the utilization of the Mogrifier long short-term memory(LSTM)language model(LM),an advanced iteration of the conventional LSTM LM,as an effective alternative for pruning targets within the ASR framework.Through rigorous experimentation on the ASR system,employing the Mogrifier LSTM LM and training it using the suggested joint on-demand pruning and online distillation method,this study provides compelling evidence.The results exhibit that the proposed methods significantly outperform a benchmark model trained solely with on-demand pruning methods.Impressively,the proposed strategic configuration successfully reduces the parameter count by approximately 39%,all the while minimizing trade-offs.

新疆煤层气大规模高效勘探开发关键技术领域研究进展与突破方向

新疆煤层气资源量7.5万亿m^(3)(2000 m以浅),已施工煤层气井450口,年产气量达到0.8亿m^(3),新疆维吾尔自治区提出了2025年实现煤层气产量25亿m^(3)的目标,煤层气大规模高效开发成为紧迫的重大需求。从煤层气富集模式与选区技术、“甜点”预测探测技术、加速滚动开发与快速增储上产策略、地质适配性开发技术、煤层气与煤炭、油气协同开发技术5个关键技术领域,系统梳理了新疆煤层气勘探开发已取得的主要研究进展,分析提出了可能突破方向。研究表明:新疆煤储层具有多-厚煤层普遍、低阶煤发育、急倾斜煤层多见、煤体变形与构造控制显著、水文条件和露头条件复杂,和三“低”(含气量低、甲烷体积分数低、含气饱和度低)五“高”(高含气强度、高孔隙度、高地应力变化、高储层压力变化、高渗透率变化)的含气性及物性等煤层气地质独特性;煤层气成因与富集模式具有多样性,包括生物成因气、热成因气或生物-热复合成因及其相应富集模式,生物成因气藏或生物成因气贡献普遍;煤层气分布赋存规律呈现前陆盆地、山间盆地显著差异性;创新形成基于“两”分开(浅部与深部,低阶煤与中高阶煤)“两”结合(地质评价与工程评价,多元数据)的科学评价与基于“机器学习+三维地质建模”的精准选区技术是第1个突破方向。深部煤层气/煤系气“甜点”发育区域主要为盆内坳陷的凸起、盆内隆起的凹陷、盆缘斜坡,高产井位多为构造高点,发育层位为割理裂隙发育的原生结构煤层或孔裂隙发育的煤系砂砾岩储层;基于“地球物理+岩石物理+岩石力学地层新方法”和“地质甜点+工程甜点新理念”的深部煤层气/煤系气“甜点”预测探测技术是第2个突破方向。低风险、短周期、高效率、多批次工程部署是加速滚动开发的基本原则;中浅部煤层气快速增储上产技术策略是在优选新区块布井建井、对老区块煤层气井进行增产改造;深部煤层气快速增储上产技术策略是在大型盆地缓坡深部和盆内凸起“甜点”区优先部署开发;科学加速滚动开发与高效快速增储上产的工程部署方法与技术策略是第3个突破方向。在井网井型差异性优化部署、低储层伤害钻井固井、高可靠性录井测井试井、多井型高效分段压裂、低套压-控压排采管控等工程技术取得重要进展;发展构建新疆煤层气大规模高效勘探开发地质适配性技术体系是第4个突破方向。开展先采气后采煤、煤层气与煤共采、煤层气与原位富油煤共采,推动中浅部煤层气与煤炭协同勘探开发;开展煤系叠合型气藏开发、煤层气与煤系气共探共采、煤系全油气系统勘探开发,推动深部煤层气与油气协同勘探开发,已有关注和探索;煤层气与煤、油气共探共采是第5个突破方向。成果试图为新疆煤层气大规模高效勘探开发提供技术支持和工程决策参考。

环形桁架式空间薄膜展开机构运动精度可靠性建模与分析

空间薄膜展开机构的姿态和位置精度会对薄膜索网的工作形态产生影响。文章首先构建环形桁架式空间薄膜展开机构运动精度可靠性理论模型,然后基于ADAMS建立考虑展开机构杆长误差的参数化仿真模型,并采用蒙特卡罗法对展开机构进行运动精度可靠性仿真分析,求解运动精度可靠度。结果表明,以机构展开到位时折展杆支撑点所拟合的空间圆心坐标位置误差及半径误差作为其运动精度可靠性量化评价指标是正确的。该研究可为空间薄膜展开机构的可靠性设计提供参考。

场景理论视域下地铁列车旅客界面需求研究

目的 为了提高乘客在地铁车厢内的乘车体验,优化地铁列车旅客界面的合理性与便捷性。方法 以场景理论为基础,采用问卷调查和用户访谈等方法,收集现有地铁乘客的用户需求,提炼客观场景。运用Kano模型明确地铁旅客界面设计的用户需求权重,基于对用户需求权重的考量及QFD质量屋展开,功能需求被转化为产品特征,用以分析用户需求与产品特征之间的关系。结果 归纳了典型地铁乘车场景,构建地铁列车乘客界面的用户需求与产品特征之间的关联矩阵,并以此为基础分别从车厢布局、信号灯提示、扶握系统和导视系统四个方面,提出了地铁列车旅客界面的配置策略。结论 从场景分析的角度结合多重定量、定性分析方法,验证场景理论对挖掘地铁乘车需求具有一定指导作用,并提出地铁列车旅客界面在提升旅客乘车体验方面的初步建议。

面向边缘智能的神经网络模型生成与部署研究

随着移动计算、第五代移动通信技术(5G)以及物联网(IoT)技术的不断演进,各类终端设备的数量呈现指数级增长。这种激增的终端设备连接到网络产生了巨大的数据流,对于需要实时处理和快速响应用户任务的需求提出了新的挑战。尤其是在这些海量数据中,半结构化和非结构化数据所占比例较大,这使得神经网络因其独特的优势而得到了广泛应用。为了提高数据处理能力和推理精度,神经网络模型会被设计得非常复杂,其存储和运行均需要消耗大量的计算资源。然而,边缘设备通常只配置有限的计算资源,无法满足存储和运行复杂神经网络模型的需求,需要借助云计算中心来完成这些任务。这种云协同会引发响应延时和增加网络带宽消耗,并带来用户隐私数据泄露等潜在风险。为了解决这些问题,提出一种面向边缘智能的神经网络模型快速生成与自动化部署(NGD)方法,根据边缘设备的硬件配置和承载的具体计算任务需求,生成与其匹配的神经网络模型,并将其快速部署在目标设备上,实现设备本地推理。在3种典型的硬件平台上的神经网络模型生成与部署实验结果表明,NGD方法能够高效地为资源受限的边缘设备生成匹配的神经网络模型,并快速地将其部署在设备上进行推理任务。

绳驱桁架结构伸展臂的主动振动控制

伸展臂由于受到空间温度变化和卫星机动动作的影响,不可避免地会产生振动。在阻尼较低的空间环境中,这种振动衰减较慢,影响伸展臂的正常工作。因此,合适的振动控制方法对于伸展臂的正常工作至关重要。本文采用拉绳作为作动器的空间桁架结构伸展臂,研究其作动绳上铰链串联顺序的优化和模型预测控制律的设计,这两部分内容均考虑了作动绳的单边约束和饱和约束。首先,通过ANSYS软件获取结构的模态信息;然后结合系统可控性原理和遗传算法计算出作动绳上铰链串联最优顺序;最后,在数值仿真中,通过设计的控制率对一个由四个单元组成的桁架结构伸展臂的振动控制过程进行仿真分析。结果表明,提出的作动绳串联铰链的方式能够有效抑制伸展臂的振动。

复杂多方向威胁下的导弹预警雷达优化部署方法

针对现有导弹预警雷达部署相对独立、协同困难,难以满足大规模对抗场景的现状,从远程预警雷达、跟踪识别雷达、机动式预警雷达不同的任务特点出发,建立应对复杂多方向威胁的多型导弹预警雷达优化部署模型,在满足最优覆盖、协同交接、目标识别等任务约束下,解决雷达协同部署问题。针对所提模型设计了一种基于云自适应的分区优化离散粒子群(CPBPSO)算法,通过设计分区编码策略缩减算法求解空间、加入云自适应变异算子提高算法全局寻优和局部跳出能力,使算法更适用于导弹预警雷达部署问题的处理。实例验证了所提模型在求解单方向、多方向威胁场景部署问题的可行性,对比分析了CPBPSO算法的有效性,基本满足导弹预警雷达最优化协同部署的需求。

6G网络中面向AI大模型的联邦学习与协同部署技术综述

随着6G网络的逐步推进和AI技术的迅猛发展,AI模型在无线网络中的应用日益广泛。综述了6G网络中面向AI大模型的无线联邦学习与协同部署技术发展现状与挑战。首先,对比了AI大模型与基础模型的区别,并介绍了不同的联邦学习范式。接着,概述了AI大模型在无线网络中的几种高效联邦微调方案,包括低秩自适应、模型分割、用户分簇和跨组织协作微调等。然后,阐述了AI大模型在无线网络中的多种部署方案,包括基于模型压缩的轻量化部署、分布式横向协同模型部署、云边端纵向协同模型部署等。最后,讨论了在6G网络中应用AI大模型面临的挑战与机遇。

基于FSRce模型的机电产品绿色概念设计方案生成方法

针对部分机电产品在概念设计阶段未综合考虑客户和环境的需求,进而影响产品详细设计的问题,提出了一种基于功能—结构—客户和环境需求(function‒structure‒requirements of customer and environment,FSRce)模型的机电产品绿色概念设计方案生成方法。首先,从案例库中选择合适的功能和结构对现有产品设计树中的节点进行扩展和关联;同时通过数据挖掘、专家打分等方法获得产品的客户和环境需求重要度,以构建基于FSRce模型的产品概念设计空间。然后,先利用加权区间粗糙数法对客户和环境需求重要度进行分析,得到需求相对重要度,再运用模糊质量功能展开(fuzzy quality function deployment,FQFD)将需求相对重要度转化为产品的工程特性权重。最后,利用物元理论构建基于工程特性的产品物元域和各结构物元集,并结合工程特性权重得到各结构的满意度分值,通过比较满意度优选得到满足客户和环境需求的产品概念设计方案。以某小型工业吹风机为例,基于上述方法对其概念设计方案进行优化。相比于原始方案,优化后的吹风机在能源消耗上降低了15.38%,在碳排放上降低了15.32%,且客户满意度提高了44.66%,由此验证了所提出方法的可行性与有效性。所提出的方法为机电产品概念设计方案的生成提供了一种新思路,能更好地辅助设计人员实现对机电产品的绿色设计。