Machine learning for predicting the outcome of terminal ballistics events

Machine learning(ML) is well suited for the prediction of high-complexity,high-dimensional problems such as those encountered in terminal ballistics.We evaluate the performance of four popular ML-based regression models,extreme gradient boosting(XGBoost),artificial neural network(ANN),support vector regression(SVR),and Gaussian process regression(GP),on two common terminal ballistics’ problems:(a)predicting the V50ballistic limit of monolithic metallic armour impacted by small and medium calibre projectiles and fragments,and(b) predicting the depth to which a projectile will penetrate a target of semi-infinite thickness.To achieve this we utilise two datasets,each consisting of approximately 1000samples,collated from public release sources.We demonstrate that all four model types provide similarly excellent agreement when interpolating within the training data and diverge when extrapolating outside this range.Although extrapolation is not advisable for ML-based regression models,for applications such as lethality/survivability analysis,such capability is required.To circumvent this,we implement expert knowledge and physics-based models via enforced monotonicity,as a Gaussian prior mean,and through a modified loss function.The physics-informed models demonstrate improved performance over both classical physics-based models and the basic ML regression models,providing an ability to accurately fit experimental data when it is available and then revert to the physics-based model when not.The resulting models demonstrate high levels of predictive accuracy over a very wide range of projectile types,target materials and thicknesses,and impact conditions significantly more diverse than that achievable from any existing analytical approach.Compared with numerical analysis tools such as finite element solvers the ML models run orders of magnitude faster.We provide some general guidelines throughout for the development,application,and reporting of ML models in terminal ballistics problems.

Controlling chaos based on a novel intelligent integral terminal sliding mode control in a rod-type plasma torch

An integral terminal sliding mode controller is proposed in order to control chaos in a rod-type plasma torch system.In this method, a new sliding surface is defined based on a combination of the conventional sliding surface in terminal sliding mode control and a nonlinear function of the integral of the system states. It is assumed that the dynamics of a chaotic system are unknown and also the system is exposed to disturbance and unstructured uncertainty. To achieve a chattering-free and high-speed response for such an unknown system, an adaptive neuro-fuzzy inference system is utilized in the next step to approximate the unknown part of the nonlinear dynamics. Then, the proposed integral terminal sliding mode controller stabilizes the approximated system based on Lyapunov＇s stability theory. In addition, a Bee algorithm is used to select the coefficients of integral terminal sliding mode controller to improve the performance of the proposed method. Simulation results demonstrate the improvement in the response speed, chattering rejection, transient response,and robustness against uncertainties.

The Intelligent Terminal Design for Integrated Substation Auxiliary System

The integrated substation auxiliary system is a project composed by software and hardware to help operators of a substation carry daily maintain works. The intelligent terminal is the key part of the system and it provides important UI and communication functions for the user. Smart phones can achieve higher bandwidth data communication, and at the same time can carry Bluetooth communication, video call, multimedia display and other functions. Smart phone is a potential common platform, suitable for the deployment of substation integrated auxiliary system terminal. Based on the Android Smart phone platform, this paper develops intelligent client-side software for the integrated substation auxiliary system and it can realize the operation ticket control, the video call, the substation map display and other functions. This client-side software has been applied in practice, and has gained good effects.

Real- Time Color Enhancement Method Used for Intelligent Mobile Terminals

In certain environments and under some conditions, the video images taken by the intelligent mobile video phones seem dark, and the colors are not bright or saturated enough.This paper presents an adaptive method to enhance the video image brightness visualization and the color performance depending on the certain hardware property and function parameters. The experimental results prove that this method can enhance the colors and the contrast of the video images, based on the estimated quality feature values of each frame, without using the extra Digital Signal Processor (DSP).

Impact of NGN Architecture by Intelligent Terminals

This paper discusses the impacts on the existing NGN network architecture by the intelligent terminals or NGN terminals. An economical and simple network with multitudes of services can be realized if terminal intelligence is utilized for functions traditionally performed by the network. The existing terminals without required intelligence can also be supported via terminal emulation at the edge of the network. Communication is established between the interested parties by the combined efforts of the NGN terminals and the network. A possible network architecture where the NGN terminals and NGN network co-operation is suggested. The benefits for such network, such as increased network robustness, interoperability and scalability, are explored in this paper.

A Discussion on the Practical Teaching Reform of Intelligent Mobile Terminal Technology Course

In this intelligent era,there is a high market demand for professional engineering talents in the computer industry.Based on engineering education accreditation,this paper briefly discusses the practical teaching reform of the intelligent mobile terminal technology course,which involves integrating theory with practical,taking students as the center,focusing on practical teaching,strengthening students’practical skills and computer application development skills,as well as promoting the construction and development of engineering accreditation.

Design and Implementation of Mobile Intelligent Hidden Danger Inspection System

With the increasing development of Internet technology,computer Internet,intelligent terminal,cloud computing and other new technologies continue to emerge.All kinds of app based on mobile intelligent terminal are widely used because of its convenience and intelligence.However,for the safety of the coal industry,how to use these technologies based on mobile intelligent terminal to establish a set of efficient long-term mechanism of safety inspection and risk control is a necessary method to upgrade the safety management mode.Therefore,in order to meet the requirements of hidden danger investigation and management,this paper designs an intelligent hidden danger investigation and management system.Based on Ionic,the system constructs a cross platform mixed mode mobile app development framework.The paper shows that the system can realize the basic hidden danger investigation requirements.

基于BIM和物联网技术的智慧工地平台在LNG码头施工中的应用

针对LNG(液化天然气)码头工程施工中存在的安全风险系数大、人员管控要求高、安装难度高、工期进度紧等问题,开展基于BIM和物联网技术在智慧工地平台的研究与应用。通过采用建立BIM技术与物联网技术融合的智慧工地管理方法,深化创建施工BIM模型,结合相应的智能化设备,实现模型与现场数据接入和集成的应用,解决了施工过程管控难、数据信息源集成多、劳务人员现场管理难等典型LNG码头工程施工问题。通过将BIM技术与智慧工地平台在施工阶段融合应用,有效提升了LNG码头工程建设项目的施工质量和技术管理水平。研究旨在为LNG码头领域的工程建设提供有益的经验和借鉴,推动智慧工地平台在该领域的应用和发展。

数字孪生在制造业中实现的关键技术及典型应用综述

数字孪生技术是实现智能制造和工业数字化转型的关键技术,受到学术界和产业界的广泛关注和研究。近十年来,随着数据采集技术、计算机性能和相关智能算法的迅速发展,数字孪生技术的研究及应用取得了巨大进展。针对数字孪生技术应用领域的多样性和对象层级的复杂性,本文回顾了数字孪生基本概念和模型的发展历程,综述了数字孪生技术在制造业应用的关键技术及其发展成果。在此基础上,阐述了数字孪生技术在制造业三个层级的应用现状以及数字孪生赋能智能制造的新范式。最后,展望了制造业数字孪生技术未来发展趋势,为后续研究提供参考。

基于DID模型的医护智能终端无纸化办公系统应用效果评估

目的采用双重差分法(DID)模型评估智能终端无纸化办公系统对医护工作效率及工作满意度的影响。方法将某院2023年1月-2月的80名医生和160名护士作为研究对象,分为干预组和对照组。干预组采用智能终端无纸化办公App,对照组采用传统的医护工作站模式。记录不同时间点病历书写时间、护理项目完成时间、护理质量评分、医护工作满意度得分,并通过建立DID模型比较两组各项指标的差异。结果随着干预时间延长,在第7天、14天、28天时,干预组病历书写平均时间、护理项目完成平均时间均短于对照组,护理质量均分、医护工作满意度均分均高于对照组,差异均具有统计学意义(P<0.05)。DID模型显示,干预组病历书写平均时间、护理项目完成平均时间呈递减趋势(t=-2.170、-6.590,P<0.05),护理质量评分、医护工作满意度呈递增趋势(t=5.180、3.240,P<0.05)。结论智能终端无纸化办公系统能够有效提高医护人员工作效率和工作满意度。

基于D3QN-PER的集装箱码头IGV任务动态分配研究

针对自动化集装箱码头智能导引车(IGV)作业环境动态、作业过程受电池电量约束等问题,研究不确定环境下考虑充电的IGV任务动态分配方法。分析不同载重下IGV充放电过程,提出基于电量区间自主决策的充电策略。为规避动态环境下IGV作业时间不确定对装卸效率的影响,以IGV和集装箱任务信息为状态空间,以集装箱分配规则为备选动作,综合装卸等待成本、IGV搬运成本和充电成本设计即时奖励,基于深度强化学习构建面向IGV任务分配的马尔可夫模型。为克服传统深度Q网络(DQN)过估计、收敛困难和训练不稳定问题,设计集成优先级经验回放(PER)机制和决斗双重深度Q网络(D3QN)结构的D3QN-PER算法。实验结果表明:D3QN-PER算法比单一规则决策和随机决策的IGV搬运任务总完工时间平均分别改进4.60%和12.05%,具有更好的收敛性能和训练稳定性。

基于NFC的乡村智慧医疗系统设计

随着乡村振兴战略的实施,数字乡村建设如火如荼地进行着,乡村医疗系统的数字化改革是大势所趋。传统的乡村医疗系统存在“看病难、看病烦”的缺点,迫切需要一种全新的,更加智慧、便捷的智慧医疗系统。文章充分利用近场通信(Near Field Communication,NFC)技术的特点,将其应用于智慧医疗系统,提出了一种全新的智慧医疗系统架构,智能终端代替传统的病历,自主支付。该系统能够为大众提供快捷的医疗信息分享与查询、准确的诊断治疗以及全天候的信息服务。经过验证,该系统是可行的。

一种可重构雷达智能终端设计

针对雷达系统对于显控终端的功能重构需求,提出了基于SNMP协议的交换机在线配置方法、数据源在线选择方法,实现了显控终端的功能自动重构,显著降低了显控终端功能调整的复杂度,提高了系统的使用灵活性和可靠性。通过增加自然人机交互手段、采用智能化工具、基于人因工程的造型和布局设计等实现显控终端的智能人机交互,大幅提高显控终端的人机交互效率。以大数据为驱动,通过辅助决策系统进行智能判别、信息推送,降低了操作员决策的难度,提高了精准度。

云边端架构下边缘智能计算关键问题综述:计算优化与计算卸载

近年来,随着入网设备数量与数据体量的急剧增加,以云计算为代表的中心式计算模式的缺点越来越显露出来。边缘计算,即让计算尽量靠近数据源,以减少数据传输时间和网络延迟,作为云计算的补充,已经成为学术界和工业界关注的焦点。该文面向边缘计算中应用较广的实例架构—云边端架构,以及边缘计算的典型应用—边缘智能计算,讨论云边端架构下边缘智能计算的两大关键问题:计算优化和计算卸载。首先分析和梳理了云边端架构下边缘智能计算优化的应用与研究现状。然后讨论了云边端架构下计算卸载的研究思路和现状。最后,总结提出了目前云边端架构下边缘智能计算业务所面临的挑战和未来研究趋势。

基于可穿戴设备医用防护服微环境监测系统的研究

随着全球气温不断升高,生态环境不断变化,重大传染病疫情时有发生。个体防护装备是医护人员避免生物污染危害的直接防护屏障,但长期穿戴专业的医用防护服装备会导致体表温度升高、大量出汗、虚脱等状况。为此,基于一次性医用防护服设计一种监测系统,以实时监测一次性防护服内的温湿度、二氧化碳含量及穿着人员的心率和血氧饱和度等数据。针对穿戴者长时间在污染区域作业,与外界通信受限的问题,搭建物联网云平台并采用无线传输技术实现作业人员与后方控制人员的信息交互,提高了一次性防护服的安全性和控制能力。针对微环境的温湿度、二氧化碳浓度及人体的心率和血氧饱和度等设定不同的阈值,随着工作的进行,通过微环境参数的改变来触发报警系统。所设计的监测系统满足设备向小型化发展的要求,方便医护人员穿戴,且获取监测数据后能及时通过物联网上传。

基于灰色模型的局部放电智能感知终端评估方法研究

随着电网运维部门对在线监测和智能化运检的重视,各种监测功能的智能终端逐步普及,针对投入使用的智能传感器,迫切需要一个成熟的平台和评估方法对智能终端的各项核心的性能指标进行校核和评估。以局部放电智能感知终端灵敏度、线性度、数据稳定性、可靠性(环境适应性和EMC(electro magnetic compatibility))和电池功耗寿命5项核心的指标为研究对象,提出每个指标的评估方法。最后结合熵值法与灰色理论对局部放电智能感知终端评估建立量化评价体系,给出案例分析。通过8个智能终端的案例,利用熵值法赋权,通过灰色关联分析法计算各个指标的关联系数,最终计算得8个智能终端综合得分,其中最高评价得分为77.1%,最低得分为44.8%,分数差异明显。基于灰色模型的定量评分可以有效的进行局部放电智能感知终端评估。文中的研究结果为局部放电智能感知终端设备的参数和性能指标量化评价提供了指导。

安卓智能终端自动化测试技术综述

随着新一代移动通信技术和芯片的发展,智能移动终端用户规模不断增加。为了快速抢占市场,开发商缩短了智能终端的开发周期,这对应用系统的可靠性、稳定性等提出了更高的要求,而自动化测试技术是保障这些智能终端高可靠、强稳定运行的重要手段。结合目前主流智能终端的架构特点和组件特征,分别探讨了安卓系统的黑盒测试技术和白盒测试技术。在黑盒测试方面,比较分析了最新的用户界面测试和模糊测试技术以及工具使用情况,评价了它们在保证应用系统可靠性和稳定性方面的效果。在白盒测试方面,总结了自动生成测试用例技术、动静态的污点分析技术、第三方库检测技术和权限检测技术。随着人工智能大模型等新兴技术不断涌现,越来越多的智能终端设备开始搭载各种深度学习模型,这些模型的不透明性使得内部决策过程难以解释和理解,从而黑盒测试在评估模型可靠性和稳定性过程中越发重要。自动化测试正在面临从传统规则基础下的测试向更加智能的机器学习驱动的测试转变。未来将人工智能大模型等新兴技术引入到现有的智能终端测试实践中,成为解决这一问题的必然趋势。

基于边缘计算的台区短期负荷预测方法

配变台区是配电物联网与用户交互的重要纽带,台区短期负荷预测对实现配电物联网的精益化管理具有重要意义。为缓解全部台区上传负荷数据所带来的通信压力,提出一种基于边缘计算的台区短期负荷预测方法,将台区智能配变终端存储30天的历史负荷数据作为样本数据,通过核平滑法对样本数据进行清洗,因样本数据较少考虑将样本归一化后,拆分为标幺曲线与基值分别计算提高预测结果精度。然后通过相关系数法构建历史负荷数据的相关系数矩阵,用相关系数矩阵替换仿射传播相似度矩阵后聚类求得相似日的标幺曲线,再通过加权求和求得待测日的标幺曲线。同时,按照相似日原理预测待测日基值,最终通过待测日标幺曲线和基值反归一化后得到待测日负荷曲线完成预测工作。通过山东某配变30天的历史负荷数据计算验证,表明所提方法可以实现台区负荷量级小、样本少、波动大情形下的合理预测,占用主站计算资源较少,对配网精益化运维具有积极意义。

基于移动智能终端交互行为的持续身份认证技术综述

随着移动智能终端的发展和普及,更多用户在智能手机、平板等移动终端上进行支付、转账、存储个人信息等活动。为了提高用户使用移动智能终端的安全性和便利性,目前移动智能终端身份认证的发展趋向于持续认证。首先,回顾了现有基于移动智能终端的身份认证工作;其次,整理了目前主流的性能评估指标和产业界应用;最后,对持续身份认证在移动智能终端中亟待解决的问题以及发展趋势进行了总结和探讨。

数智时代多个快递企业末端协同仓共配:机遇与挑战

基于实物互联网(Physical Internet,PI)理论和物流友好设计(Design for Logistics,DFL)理论,文章分析了能均衡环境成本、运营成本及改善交付效率的“多个快递企业末端协同仓共配”这一创新模式未来发展面临的机遇与挑战、相应的路径选择与应对策略,结论认为:以绿色低碳与合作协同为内核的“多个快递企业末端协同仓共配”模式不仅可持续,而且市场价值和社会价值巨大;单业务操作层面上来看,多企面单异质问题是其市场主体实现高效率自动化分拣的最大障碍因素之一,建议行业层面共同努力并且立即行动。