Digital CEOs in Digital Enterprises:Automating,Augmenting,and Parallel in Metaverse/CPSS/TAOs

BIG models or foundation models are rapidly emerging as a key force in advancing intelligent societies[1]–[3]Their significance stems not only from their exceptional ability to process complex data and simulate advanced cognitive functions,but also from their potential to drive innovation across various industries.

Adaptive Reclosing Scheme Based on Traveling Wave Injection For Multi-Terminal dc Grids

The hybrid dc circuit breaker(HCB)has the advantages of fast action speed and low operating loss,which is an idealmethod for fault isolation ofmulti-terminal dc grids.Formulti-terminal dc grids that transmit power through overhead lines,HCBs are required to have reclosing capability due to the high fault probability and the fact that most of the faults are temporary faults.To avoid the secondary fault strike and equipment damage that may be caused by the reclosing of the HCB when the permanent fault occurs,an adaptive reclosing scheme based on traveling wave injection is proposed in this paper.The scheme injects traveling wave signal into the fault dc line through the additionally configured auxiliary discharge branch in the HCB,and then uses the reflection characteristic of the traveling wave signal on the dc line to identify temporary and permanent faults,to be able to realize fast reclosing when the temporary fault occurs and reliably avoid reclosing after the permanent fault occurs.The test results in the simulation model of the four-terminal dc grid show that the proposed adaptive reclosing scheme can quickly and reliably identify temporary and permanent faults,greatly shorten the power outage time of temporary faults.In addition,it has the advantages of easiness to implement,high reliability,robustness to high-resistance fault and no dead zone,etc.

Auto CAD二次开发在幕墙设计中的应用

随着建筑幕墙行业的快速发展,幕墙设计工作也越来越复杂.幕墙设计不仅在招投标阶段发挥重要作用,更在工程施工过程中给予大量的技术支持,导致幕墙设计人员肩上的担子越来越重.本文通过研究Auto CAD二次开发来解决复杂幕墙设计问题,减少重复机械操作,提高幕墙设计人员的工作效率.

基于Auto CAD的通风管道系统的优化

当前通风管道系统的尺寸优化主要由人工完成,效率较低,针对该问题,分析了通风管道系统的结构特性,选用了B树作为基本数据结构,根据通风管道中线图及其连通特性建立管路构建方法。依据通风管道中风速、风量与截面积的关系,计算出各个管道的理论截面积,确定了管道截面尺寸优化策略。最后使用上述方法针对某通风管道进行了优化设计。

基于AUTO Civil 3D的水利工程勘察设计

本文通过无人机技术和数字高程模型,采集水库工程的地形和地貌数据;将原始工程资料、采集的地貌数据以及地形数据,输入至AUTO Civil 3D软件中,生成水库工程地形曲面模型和地质三维实体模型,完成模型颜色渲染,进行水库工程勘察设计。这种基于AUTO Civil 3D的水利工程勘察方法测试结果表明,该方法能够有效完成水利工程地质模型的生成,呈现地质信息的实体结果;模型的构建精度较高,可有效完成航道疏浚时河底清淤勘察设计。

Injuries Associated with Auto-Tricycle Crashes in an African City: Incidence and Pattern

Purpose: The aim of this study was to determine the incidence and pattern of injuries resulting from auto-tricycle crashes among patients in a tertiary referral centre in Ghana. Methods: Data were retrospectively extracted from hospital records of patients who got involved in auto-tricycle crashes and presented to the Accident and Emergency Centre of the Komfo Anokye Teaching Hospital (KATH), over a one-year period using a structured questionnaire. The gathered data were then entered into an electronic database and then analysed with SPSS version 20.0. Results: The incidence of injury following auto-tricycle crashes over the one-year period was 5.9% (95% CI: 4.9% - 7.0%) with a case fatality rate (FR) of 3.8% (95% CI: 1.3% - 8.7%). All the mortalities resulted from head and neck injuries and none of the patients involved wore a crash helmet. Only 5% of those studied wore crash helmets and were all drivers. Closed fractures accounted for 58% of the injuries, followed by open fractures, 28%. The most commonly fractured bones were the tibia/fibula, followed by the femur and then radius/ulna. The most common mechanism of injury was auto-tricycle toppling over (29%). Passengers were the most injured (48%), followed by drivers (37%) and pedestrians (15%). Most (72%) injuries among participants involved a single body part. On the injury severity scale, most (61%) of patients had minor trauma and 38% had major trauma. Conclusion: Auto-tricycle crashes account for 5.9% of injuries at the study site with a case fatality rate of 3.8%. Passengers had a higher injury rate (48%) than drivers (37%). Fractures of the tibia/fibula were most commonly associated with auto-tricycle crashes. Injuries to the head and neck were responsible for the deaths in the study participants and non-use of a crash helmet was associated with mortalities.

基于Auto bank的某水库大坝渗流安全评价

以富水水库为例,依托达西定律和渗流理论基础,并结合Auto bank有限元软件分析了水库在正常高水位、设计洪水位、校核洪水位下坝体及坝基的渗流状况,计算结果表明水库日渗漏量远小于允许日渗漏量,水库渗漏量满足规范要求。大坝各工况最大渗透坡降均小于规范允许值,渗透变形满足规范要求。左坝肩存绕渗现象,建议加强监测。

Auto CAD在陶瓷产品设计三视图中的应用研究

Auto CAD制图的应用为陶瓷产品设计提供了有力帮助,能显著提升陶瓷产品的观赏性、艺术性,同时使陶瓷产品保持其应有的实用性。对此,本文针对Auto CAD在陶瓷产品设计三视图中的应用价值展开探讨,对于Auto CAD的应用原理进行研究,而后对Auto CAD在陶瓷产品设计三视图中的具体应用进行分析,对于如何推动这一制图软件的深度应用提出一些建议,希望能为相关从业者在Auto CAD的应用方面提供一些借鉴。

一种基于AutoLISP的地形图斜坡类要素处理程序的设计与实现

在大比例尺地形图编辑中存在大量的依比例斜坡类符号要素,包括依比例斜坡、干堤、加固岸、路堤、路堑等,该类符号是一种复合性符号,由坡顶线和坡面两部分组成,坡顶线由坡顶母线和长短齿符号组成,其中长齿长度和坡面宽度一致且垂直于坡顶母线,该符号表示复杂,编辑工作较为费时费力。利用AutoLISP语言开发斜坡类符号要素处理程序,实现符号长齿自动延伸,可大大提高该类符号编辑工作效率,提升制图表达效果。

Relevant Factors to a Statistical Analysis of Overvoltages - Application to Three-Phase Reclosing of Compensated Transmission Lines

This paper describes the statistical study of important factors that influences transient over voltages resulting from three-phase reclosing of shunt compensated transmission lines. These factors include the model used for transmission line representation and the influence of line transposition. Additionally, the over voltages reduction to proper levels depending on the type of control technique are illustrated and analyzed in statistical terms. The evaluation covers three shunt compensation degrees. The digital simulations were performed using the PSCAD/EMTDC software.

Auto CAD图解法在缓和曲线计算中的应用

本文以缓和曲线直角坐标计算公式及切线角计算公式为基础,先用Excel分段计算出缓和曲线坐标,用较短长度直线连接成一条多段线来拟合缓和曲线;然后利用Auto CAD中自定义坐标系、旋转和平移等命令,实现在直线段和圆曲线之间插入缓和曲线的图解坐标计算方法。

Optimum line reclosing time for the enhancement of interconnected power system stability

Automatic line reclosing schemes used in an extra-high-voltage power system is an economical and effective means to maintain transient stability. A novel method is proposed in the paper to adaptively optimize the automatic line reclosing time after a transient fault for enhancement of interconnected power system transient stability. Both the study on the transient energy over network and the structure-preserving multi-machines power system model illustrate that the excessive convergence of potential energy on the lines with a certain cutset deteriorate power system stability, and therefore, an optimum line reclosing strategy can be established by minimizing the change in transient potential energy distribution across a cutset lines in the vicinity of the faulty line as an optimization target, and the optimal reclosure time is set to the time of minimum line phase angle difference. Without any pre-determined knowledge, the method is adaptive to various power system operation modes and fault conditions, and easy to implement because only a limited number of data measured at one location on a tie-line linking sub-networks are required. Simulations have been performed with the OMIB(One Machine and Infinite Bus System) and a real inter-connected power system to verify the applicability of the method proposed.

基于Auto Lisp的滴灌系统辅助设计程序开发

滴灌系统管道繁多,在设计过程中存在大量重复性工作。以Auto CAD软件为开发平台,应用Auto Lisp语言开发出一种滴灌系统辅助设计程序,实现了干管标注、分干管标注等多个功能的自动化设计,有效地提高了工作效率。

Feature Enhanced Stacked Auto Encoder for Diseases Detection in Brain MRI

The detection of brain disease is an essential issue in medical and research areas.Deep learning techniques have shown promising results in detecting and diagnosing brain diseases using magnetic resonance imaging(MRI)images.These techniques involve training neural networks on large datasets of MRI images,allowing the networks to learn patterns and features indicative of different brain diseases.However,several challenges and limitations still need to be addressed further to improve the accuracy and effectiveness of these techniques.This paper implements a Feature Enhanced Stacked Auto Encoder(FESAE)model to detect brain diseases.The standard stack auto encoder’s results are trivial and not robust enough to boost the system’s accuracy.Therefore,the standard Stack Auto Encoder(SAE)is replaced with a Stacked Feature Enhanced Auto Encoder with a feature enhancement function to efficiently and effectively get non-trivial features with less activation energy froman image.The proposed model consists of four stages.First,pre-processing is performed to remove noise,and the greyscale image is converted to Red,Green,and Blue(RGB)to enhance feature details for discriminative feature extraction.Second,feature Extraction is performed to extract significant features for classification using DiscreteWavelet Transform(DWT)and Channelization.Third,classification is performed to classify MRI images into four major classes:Normal,Tumor,Brain Stroke,and Alzheimer’s.Finally,the FESAE model outperforms the state-of-theart,machine learning,and deep learning methods such as Artificial Neural Network(ANN),SAE,Random Forest(RF),and Logistic Regression(LR)by achieving a high accuracy of 98.61% on a dataset of 2000 MRI images.The proposed model has significant potential for assisting radiologists in diagnosing brain diseases more accurately and improving patient outcomes.

有无Auto flash优化时摆位误差对乳腺癌容积旋转调强放疗计划剂量学的影响

目的:探讨有无Auto flash参与优化时,不同方向的摆位误差对乳腺癌VMAT计划的剂量学影响。方法:选取20例行VMAT技术照射的右侧乳腺癌根治术后患者。Monaco治疗计划系统在优化时可以选择是否对靶区采用Auto flash虚拟外放多叶光栅边界进行优化,对治疗时Auto flash参与优化的计划,制定一个无Auto flash的计划,对于治疗时无Auto flash参与优化的计划,制定一个有Auto flash的计划。2个计划的优化函数和条件均保持一样。对制定好的计划在头脚、上下、左右6个方向上分别引入3 mm和5 mm的摆位误差,重新计算剂量分布,以PTV的V100,D98,D2,Dmean,患侧肺的V20、V5,健侧肺的V5,脊髓的Dmax以及心脏的Dmean的变化幅度评价治疗计划对摆位误差的敏感性。结果:对3 mm的摆位误差,有Auto flash优化的VMAT计划在任一方向上PTV的剂量偏差均小于5%,无Auto flash优化的VMAT计划在下方向上的PTV剂量偏差大于5%,其余均小于5%。对5 mm的摆位误差,有Auto flash优化的VMAT计划在左和下方向的PTV剂量偏差大于5%,其余均小于5%,无Auto flash优化的VMAT计划在左和下方向的PTV剂量偏差大于5%,其余均小于5%。但就偏差的幅度而言,有Auto flash的计划小于无Auto flash的计划。结论:有Auto flash的计划,在有摆位误差时剂量学差异小于无Auto flash的计划,在制定乳腺癌计划时应该采用Auto flash参与优化。两种计划均在内、上、前这三个方向上剂量学偏差最小,外、下、后三个方向上剂量学偏差最大,在摆位时更应该刻意关注。

Classification Model for IDS Using Auto Cryptographic Denoising Technique

Intrusion detection systems(IDS)are one of the most promising ways for securing data and networks;In recent decades,IDS has used a variety of categorization algorithms.These classifiers,on the other hand,do not work effectively unless they are combined with additional algorithms that can alter the classifier’s parameters or select the optimal sub-set of features for the problem.Optimizers are used in tandem with classifiers to increase the stability and with efficiency of the classifiers in detecting invasion.These algorithms,on the other hand,have a number of limitations,particularly when used to detect new types of threats.In this paper,the NSL KDD dataset and KDD Cup 99 is used to find the performance of the proposed classifier model and compared;These two IDS dataset is preprocessed,then Auto Cryptographic Denoising(ACD)adopted to remove noise in the feature of the IDS dataset;the classifier algorithms,K-Means and Neural network classifies the dataset with adam optimizer.IDS classifier is evaluated by measuring performance measures like f-measure,recall,precision,detection rate and accuracy.The neural network obtained the highest classifying accuracy as 91.12%with drop-out function that shows the efficiency of the classifier model with drop-out function for KDD Cup99 dataset.Explaining their power and limitations in the proposed methodology that could be used in future works in the IDS area.

考虑倒箱的Auto Store仓储拣选系统提箱作业优化

为减少Auto Store仓储拣选系统的倒箱作业时间,提高其提箱作业效率,在已知料箱存储状态及订单商品信息的条件下,研究了Auto Store仓储拣选系统提箱作业优化的问题。以提箱作业时间来衡量Auto Store仓储拣选系统作业效率,建立以最短提箱作业时间为目标的整数规划模型,设计启发式算法对模型进行求解,提出问题下界的约束条件及求解方法,同时,通过算例比较启发式算法与理论下界的差异,表明倒箱作业规则对Auto Store仓储拣选系统提箱作业效率影响较大,优化倒箱作业规则,可提高其提箱作业效率,为Auto Store的倒箱作业优化提供了理论支持。

基于Auto lisp的地籍测量程序设计

地籍测量是为了获取和表达地籍信息所进行的测绘工作。其内业处理方面,业已步入数字化,国内主流软件是南方CASS,该软件是以Auto CAD为平台开发的,本文通过对Auto CAD的二次开发语言Auto Lisp的阐述,旨在研究Auto CAD的二次开发语言Auto Lisp在地籍数据处理中的应用,并通过实例进行分析得出,经过二次开发语言Auto Lisp应用在地籍测量中,提高了数据处理的效率与绘图质量。

Auto CPAP治疗对精神分裂症伴发睡眠呼吸暂停综合征患者的睡眠结构、焦虑情绪的影响

目的 探究Auto CPAP治疗对伴发失眠及睡眠呼吸暂停综合征的精神分裂症患者睡眠结构、焦虑情绪的影响。方法 选取2022年1月至2023年1月绍兴市第七人民医院收治的伴发失眠及睡眠呼吸暂停综合征的精神分裂症患者88例,按随机数字表法分为对照组(n=44)和观察组(n=44)。对照组进行常规治疗,观察组是在对照组的基础上行Auto CPAP治疗。采用多导睡眠检测系统监测患者治疗前后的睡眠时间结构:睡眠总时间(TST)、睡眠效率(SE)、睡眠潜伏期时间(SOL)、觉醒时间(WASO)、快速动眼睡眠期时间(REM)占比、非快速动眼睡眠期1(NREM1)占比、NREM2占比、NREM3占比;采用Hamilton抑郁量表(HAMD)对所有患者治疗前后的焦虑抑郁情绪进行评分。结果 治疗后,两组TST、SE、REM、NREM3显著升高,SOL、WASO、NREM1、NREM2均显著降低(均P<0.05);与对照组相比观察组的TST、SE、REM、NREM3均高,SOL、WASO、NREM1、NREM2均低(均P<0.05)。治疗后,两组HAMD评分均显著降低(P<0.05);与对照组相比,观察组的HAMD评分均低(P <0.05)。结论 Auto CPAP治疗可以明显改善精神分裂症伴发睡眠呼吸暂停综合征患者的睡眠结构,缓解患者的焦虑情绪。

中职机械制图与Auto CAD融合教学探索

机械制图与 Auto CAD是中职机电专业的一门主干课程,本课程的特点是学生在学习机械制图中,既要掌握理论知识,又要运用计算机进行绘图,这给教师在教学中提出了很大的挑战。在实际教学中,可以采取将《机械制图》与《Auto CAD》进行有机融合的做法,充分发挥 Auto CAD软件强大的绘图功能和三维造型功能,从三维实体建模到二维工程图绘制,从二维工程图到三维实体模型。通过“3D建模—编辑—修改—表达”这样一个螺旋上升的过程来完成课程教学任务。将二者融合教学是解决这一难题的有效途径。本文就如何将机械制图与 Auto CAD融合教学进行探讨,并以两个典型案例进行了分析和说明,以期对专业课程的教学有所裨益。