Modified DS np Chart Using Generalized Multiple Dependent State Sampling under Time Truncated Life Test

This study presents the design of a modified attributed control chart based on a double sampling(DS)np chart applied in combination with generalized multiple dependent state(GMDS)sampling to monitor the mean life of the product based on the time truncated life test employing theWeibull distribution.The control chart developed supports the examination of the mean lifespan variation for a particular product in the process of manufacturing.Three control limit levels are used:the warning control limit,inner control limit,and outer control limit.Together,they enhance the capability for variation detection.A genetic algorithm can be used for optimization during the in-control process,whereby the optimal parameters can be established for the proposed control chart.The control chart performance is assessed using the average run length,while the influence of the model parameters upon the control chart solution is assessed via sensitivity analysis based on an orthogonal experimental design withmultiple linear regression.A comparative study was conducted based on the out-of-control average run length,in which the developed control chart offered greater sensitivity in the detection of process shifts while making use of smaller samples on average than is the case for existing control charts.Finally,to exhibit the utility of the developed control chart,this paper presents its application using simulated data with parameters drawn from the real set of data.

Time’s Running Out

OIL-RICH Libya faces an array of daunting challenges in dealing with the legacies of Muammar Gaddafl＇s 42 years in power, not least the dysfunctional labor sector he left behind. Add to this the damage done to the country＇s economic infrastructure during the revolution that ousted Gaddafi in 2011, and the impact of the civil war that has raged for nearly a year. and the prognosis looks very grim,

The Physical Significance of the Synthetic Running Correlation Coefficient and Its Applications in Oceanic and Atmospheric Studies

In order to study the temporal variations of correlations between two time series,a running correlation coefficient(RCC)could be used.An RCC is calculated for a given time window,and the window is then moved sequentially through time.The current calculation method for RCCs is based on the general definition of the Pearson product-moment correlation coefficient,calculated with the data within the time window,which we call the local running correlation coefficient(LRCC).The LRCC is calculated via the two anomalies corresponding to the two local means,meanwhile,the local means also vary.It is cleared up that the LRCC reflects only the correlation between the two anomalies within the time window but fails to exhibit the contributions of the two varying means.To address this problem,two unchanged means obtained from all available data are adopted to calculate an RCC,which is called the synthetic running correlation coefficient(SRCC).When the anomaly variations are dominant,the two RCCs are similar.However,when the variations of the means are dominant,the difference between the two RCCs becomes obvious.The SRCC reflects the correlations of both the anomaly variations and the variations of the means.Therefore,the SRCCs from different time points are intercomparable.A criterion for the superiority of the RCC algorithm is that the average value of the RCC should be close to the global correlation coefficient calculated using all data.The SRCC always meets this criterion,while the LRCC sometimes fails.Therefore,the SRCC is better than the LRCC for running correlations.We suggest using the SRCC to calculate the RCCs.

Mathematical Proof of the Synthetic Running Correlation Coefficient and Its Ability to Reflect Temporal Variations in Correlation

The running correlation coefficient(RCC)is useful for capturing temporal variations in correlations between two time series.The local running correlation coefficient(LRCC)is a widely used algorithm that directly applies the Pearson correlation to a time window.A new algorithm called synthetic running correlation coefficient(SRCC)was proposed in 2018 and proven to be rea-sonable and usable;however,this algorithm lacks a theoretical demonstration.In this paper,SRCC is proven theoretically.RCC is only meaningful when its values at different times can be compared.First,the global means are proven to be the unique standard quantities for comparison.SRCC is the only RCC that satisfies the comparability criterion.The relationship between LRCC and SRCC is derived using statistical methods,and SRCC is obtained by adding a constraint condition to the LRCC algorithm.Dividing the temporal fluctuations into high-and low-frequency signals reveals that LRCC only reflects the correlation of high-frequency signals;by contrast,SRCC reflects the correlations of high-and low-frequency signals simultaneously.Therefore,SRCC is the ap-propriate method for calculating RCCs.

Run by Run Control of Time-pressure Dispensing for Electronics Encapsulation

To alleviate the influence of gas compressibility on the process performance of time-pressure dispensing for electronics encapsulation,a predictive model is developed based on power-law fluid to estimate the encapsulant amount dispensed.Based on the simple and effective model,a run by run (RbR) supervisory control scheme is delivered to compensate the variation resulting from gas volume change in the syringe.Both simulation and experiment have shown that the dispensing consistency has been greatly improved with the model-based RbR control strategy developed in this paper.

A Comparison of 3D Methods for Identifying the Stance Phase in Treadmill Running for Both Rearfoot and Forefoot Runners

We compared six 3D methods, OptoGait, and Myotest Run for the determination of contact time for runners with different foot strike patterns. Twenty male participants were divided into two groups： the heel group, who attack the ground with the heel （n = 12）, and the toe group, who attack the ground with the middle/front of the foot （n = 8）. They performed trials at speeds of 8 km/h then 16 km/h. To detect foot strike, the use of peak velocity of 3D markers located on the heel, the fifth metatarsal, and the great toe provided the best results for both groups. To detect the toe off, the minimum vertical position of a 3D marker placed in line with the great toe gave the most satisfactory results for both groups. In this way, the values of contact time measured with the 3D methods are consistent. Values measured with OptoGait appear consistent too, while those of the Myotest Run underestimate the contact time for both speeds. 3D analysis provides interesting opportunities for calculation of contact time for both rearfoot and forefoot runners, using specific peak velocities to determine foot strike and marker displacement to determine toe off.

运行时间周期化工业机器人模型迭代寻优NURBS轨迹插补

为满足工业机器人高精度复杂曲线运动的需求,本文提出运行时间周期化工业机器人模型迭代寻优NURBS轨迹插补算法.首先,根据轨迹最大轮廓误差和机器人动力学特性对曲线分段.随后,提出优化回溯算法,使各子曲线段均可用S曲线加减速规划.之后,为保证机器人在进给速度极小值处不超速,将各加减速阶段运行时间调整为插补周期的整数倍,并对子曲线段衔接处速度平滑处理.最后,提出模型迭代寻优曲线插补,大大降低了速度波动率.仿真试验表明,该方法插补轨迹的各项指标均满足要求且最大速度波动率仅为0.000099%.真机试验也验证了该方法可有效减小轨迹误差.

汽车零部件Milk-run车辆调度优化模型和算法

为了寻求汽车零部件采用循环取货时车辆的最优路径,提出将每个供应商零部件循环、分批提取使车辆尽可能满载的建模思路,建立具有车辆容积、车辆到达时间窗、供应商供货动态时间窗、车辆最大行程约束的车辆调度优化模型,设计了用于求解该模型的改进启发式节约算法。最后通过算例验证了多重约束模型及算法的有效性。

非参数自适应EWMA SR控制图及其变采样间隔设计

本文基于Wilcoxon符号秩(Signed Rank, SR)检验统计量,提出了一种非参数自适应指数加权移动平均(Adaptive Exponentially Weighted Moving Average, AEWMA)控制图。所提出的AEWMA SR控制图结合了非参数统计量的稳健受控性能以及自适应控制图良好的整体偏移检测特性。同时,为了提高固定采样间隔下的非参数AEWMA SR静态控制图对异常偏移的检测效率,本文进一步研究了可变采样间隔(Variable Sampling Intervals, VSI)下的非参数AEWMA SR动态控制图设计问题。使用了Markov链方法计算控制图的精确平均运行链长(Average Run Length, ARL)和平均报警时间(Average Time to Signal, ATS)等性能指标。通过仿真分析比较了VSI AEWMA SR控制图、FSI AEWMA SR控制图和VSI EWMA SR控制图的统计性能。结果表明,所提出的VSI AEWMA SR控制图能兼顾对于不同大小偏移的敏感性,且变采样间隔的动态策略能显著提高控制图的检测效率。

基于运行时检测的Java反序列化漏洞防御技术

反序列化漏洞自被发现以来,便受到安全研究者的广泛关注,越来越多的漏洞被爆出,给企业的网络安全带来严重挑战。Java语言多态、反射等特性,导致其反序列化漏洞利用链更加多变和复杂,带来了更大的防御和检测难度。因此,研究如何防御Java反序列化漏洞攻击,成为网络防御的重要环节。通过对公开的众多Java反序列化漏洞进行研究,提出了基于运行时检测的Java反序列化漏洞防御技术方案。根据反序列化数据类型,将反序列化漏洞分为Java原生反序列化漏洞、JSON反序列化漏洞、XML反序列化漏洞、YAML反序列化漏洞4种类型,并针对每种类型的反序列化漏洞、归纳其漏洞利用过程中的反序列化入口函数;通过Java的运行时保护技术,对Java底层的敏感行为如命令执行进行监控,获取系统当前的运行时上下文信息;通过在上下文信息中匹配漏洞利用中的反序列化入口函数,来判断当前行为是否为反序列化漏洞的利用行为。在多个Java应用(如WebLogic、JBoss、Jenkins等)的测试结果表明,该方案能有效地对Java反序列化漏洞攻击行为进行防御,且不会对目标系统性能产生较大的影响。同时,在与其他主流防护方案的比较中,该方法显示出更好防护效果。

考虑蓄电池Run-time等效模型的船舶直流应急电网短路电流计算

为计算直流应急电网不同故障类型下的短路电流,便于直流应急电网开关器件的型号以及相应的保护措施的选择,提出了一种考虑蓄电池Run-time等效模型的船舶直流应急电网短路电流计算方法。与传统蓄电池的Thevenin等效模型和PNGV(the partnership for a new generation of vehicles)等效模型相比,所提方法考虑了蓄电池容量衰减、温度、循环次数、存储时长、电流倍率、自身产热等多因素的影响,对蓄电池的故障等值电路进行了精确模拟。最后,利用实际的直流应急电网短路电流仿真和实验验证了所提方法的准确性,与Thevenin等效模型和PNGV等效模型相比,不同故障下蓄电池Run-time等效模型短路电流的计算误差更小。

基于梯度提升决策树的材料计算时间预测模型

材料计算运行时间预测对提升作业调度效率和新材料研发有着至关重要的作用,传统集群作业运行时间预测模型的精度较差,在领域的可用性较低。为此,提出一种基于梯度提升决策树的作业预测模型,结合领域知识和相关文献对VASP作业日志数据进行清洗,对选择的特征进行重要性评估,然后在不同数据量、不同样本分布数据条件下进行实验,将该模型与使用传统机器学习方法的模型进行比较。实验表明,所提方法的平均绝对百分比误差在不同条件下均低于传统机器学习方法,且综合作业运行时间的预测误差为4.28%,优于RunningNet方法的10.3%,证明了所提模型对材料计算运行时间预测精度更高,对提升作业调度效率和加快新材料研发作用更大。

基于改进蜣螂优化算法的机械臂轨迹规划方法研究

本文以ABB-IRB 120为研究对象,建立了机械臂连杆坐标系以及DH参数表,并在给定运动学基础上,将改进蜣螂优化算法应用于4-3-4分段多项式轨迹优化中;最后将改进蜣螂优化算法和粒子群优化算法进行对比,得到了机械臂关节适应度变化曲线。仿真实验结果表明,相较粒子群算法,改进蜣螂算法能有效提高解的寻优精度和收敛速度,大幅度缩短机械臂运行时间,降低了机械臂在运行过程中的冲击与振动。

24h全日集中空气源热泵热水系统贮热水箱容积的分析探讨

在空气源热泵热水系统设计中,贮热水箱容积的计算至关重要。介绍并分析了现行标准规程贮热水箱容积的计算公式,指出了公式运用时可能存在的问题。针对空气源热泵定时运行、24 h全日集中热水供应系统,根据热泵运行时间与用水高峰持续时段的覆盖关系,分情况分析并推导了贮热水箱容积的计算公式。在设计取值范围内,对上述推导公式计算的贮热水箱容积进行了分析。提出了贮热水箱容积在方案阶段的估算建议值。

Web端关键帧动画运行时的构建及实例

为解决HTML5 Canvas缺少完备的动画运行环境的问题,本文构建了一种基于面向对象编程思想的关键帧动画运行时。该运行时以JavaScript编程语言为载体,利用JavaScript语言特性,对关键帧动画运行逻辑进行高度抽象。实例运行结果表明,该运行时不仅能为创造高性能、高灵活度的关键帧动画提供可能,还能为创建低耦合、低代码量的拓展类提供基础。

RR-SC:边缘设备中基于随机计算神经网络的运行时可重配置框架

随着人工智能民主化的发展,深度神经网络已经被广泛地应用于移动嵌入式设备上,例如智能手机和自动驾驶领域等.随机计算作为一种新兴的、有前途的技术在执行机器学习任务时使用简单的逻辑门而不是复杂的二进制算术电路.它具有在资源(如能源、计算单元和存储单元等)受限的边缘设备上执行深度神经网络低能耗、低开销的优势.然而,之前的关于随机计算的工作都仅仅设计一组模型配置并在固定的硬件配置上实现,忽略了实际应用场景中硬件资源(如电池电量)的动态改变,这导致了低硬件效率和短电池使用时间.为了节省电池供电的边缘设备的能源,动态电压和频率调节技术被广泛用于硬件重配置以延长电池的使用时间.针对基于随机计算的深度神经网络,创新性地提出了一个运行时可重配置框架,即RR-SC,这个框架首次尝试将硬件和软件的重配置相结合以满足任务的时间约束并最大限度节省能源.RR-SC利用强化学习技术可以一次性生成多组模型配置,同时满足不同硬件配置(即不同的电压/频率等级)下的准确率要求.RR-SC得到的解具有最好的准确率和硬件效率权衡.同时,多个模型配置运行时在同一个主干网络上进行切换,从而实现轻量级的软件重配置.实验结果表明,RRSC可以在110 ms内进行模型配置的轻量级切换,以保证在不同硬件级别上所需的实时约束.同时,它最高可以实现7.6倍的模型推理次数提升,仅造成1%的准确率损失.

机车实时走行公里应用系统设计及应用

为满足机车分级整备、跨铁路局集团公司(简称:局)段整备和精准检修的管理需求,设计了集采集、传输、应用等功能为一体的机车实时走行公里应用系统。利用车载装置实时采集列车运行监控装置(LKJ)走行公里数据;依托3G/4G移动网络和机辆信息管理平台内/外网传输通道,实现在线走行公里数据的传输和落地;通过机车走行公里地面应用,实现实时数据查询和多维度统计分析,以及机车整备预测、修程预测等功能。在试点局段的试用结果表明,该系统为机车整备、检修提供了量化依据,减少人工维护数据工作量,杜绝机车失修和超整备周期使用的发生,减轻运输安全风险,整体提升机车运营维护水平和效率。

基于最优子抽样的大数据泊松回归系数估计

为了快速且准确地求解泊松回归估计量,提出建立在最优子抽样算法基础上的泊松回归模型。通过证明子样本估计量的渐近性质,提出了两步最优子抽样算法,并根据A-最优性思想和L-最优性准则设计了两种抽样概率下的抽样方法。性能对比试验显示,本文提出的最优子抽样算法的均方误差显著低于其他方法;运行时间对比显示,L-最优性准则对应抽样概率的抽样方法比A-最优性思想对应抽样算法在估计回归系数上运行时间更少;超大样本和维度下,最优子抽样算法在两种维度中的运行时间平均比杠杆子抽样算法分别减少了61.84%、70.64%。以上结果表明,所提出的最优子抽样算法基础上的泊松回归可有效逼近全部数据下的最大似然估计,在估计回归系数上更具有优越性。

基于飞行时间的自动扶梯速度及制停距离测量装置开发

针对自动扶梯运行速度及制停距离测量问题,提出了一种基于飞行时间的无接触测量方法,并开发了相应的装置。运行速度测量时,将激光测距模块置于自动扶梯中段的上方,测量梯级的垂直方向上高度变化和上升速度,通过计算得出垂直方向上升速度,再根据扶梯倾斜角度计算得到扶梯运行速度;制停距离测量时,将电流感应模块至于动力回路的线路处,通过检测动力回路电流的通断触发激光测距模块进入制停距离测量模式,测量断电后梯级垂直上升的距离,再通过计算得出扶梯制停距离。开发基于μC/OS-III实时操作系统的手持设备,用于控制激光测距模块的开关及采集/显示自动扶梯速度和制停距离。激光测距模块、电流感应模块及手持模块采用Zigbee无线网络连接。试验结果表明,该装置可有效测得自动扶梯运行速度、制停距离,且安装方便,可重复性高,能提高检验效率及精度。

双喉道Ludwieg管风洞启动过程及其有效运行时间延长

Ludwieg管风洞是开展高超声速空气动力学实验基础研究的重要平台。但是,快开阀启动式高超声速Ludwieg管风洞长期受快开阀影响,产生不同类型的来流扰动模态。双喉道气动布局可有效消除快开阀启动式高超声速Ludwieg管风洞上游部件的扰动来源,但是会导致风洞有效运行时间大幅缩短。针对该问题,通过非定常数值模拟对双喉道气动布局高超声速Ludwieg管风洞的启动特性进行研究,然后对第1喷管扩张段与稳定段进行了融合设计,研究了不同扩张角与稳定段组合对风洞启动时间以及流场品质的影响。结果表明,采用减小扩张角组合设计能够使双喉道气动布局高超声速Ludwieg管风洞的有效运行时间提升近20%,并且对下游实验段内的静态流场品质几乎无影响,有效提高了风洞的实验能力。同时,相较于较大的扩张角组合,较小的扩张角设计能够减少约10%的总压损失。