Cluster DetectionMethod of Endogenous Security Abnormal Attack Behavior in Air Traffic Control Network

In order to enhance the accuracy of Air Traffic Control(ATC)cybersecurity attack detection,in this paper,a new clustering detection method is designed for air traffic control network security attacks.The feature set for ATC cybersecurity attacks is constructed by setting the feature states,adding recursive features,and determining the feature criticality.The expected information gain and entropy of the feature data are computed to determine the information gain of the feature data and reduce the interference of similar feature data.An autoencoder is introduced into the AI(artificial intelligence)algorithm to encode and decode the characteristics of ATC network security attack behavior to reduce the dimensionality of the ATC network security attack behavior data.Based on the above processing,an unsupervised learning algorithm for clustering detection of ATC network security attacks is designed.First,determine the distance between the clustering clusters of ATC network security attack behavior characteristics,calculate the clustering threshold,and construct the initial clustering center.Then,the new average value of all feature objects in each cluster is recalculated as the new cluster center.Second,it traverses all objects in a cluster of ATC network security attack behavior feature data.Finally,the cluster detection of ATC network security attack behavior is completed by the computation of objective functions.The experiment took three groups of experimental attack behavior data sets as the test object,and took the detection rate,false detection rate and recall rate as the test indicators,and selected three similar methods for comparative test.The experimental results show that the detection rate of this method is about 98%,the false positive rate is below 1%,and the recall rate is above 97%.Research shows that this method can improve the detection performance of security attacks in air traffic control network.

Threshold decision for instrument control system and its application in nuclear power plant

Threshold decision is an important function of nuclear instrument control system based on physical parameters threshold decision. Because the conventional decision methods lack correlation with time and conditions, by analyzing the existing methods, some optimized methods are adopted. Considering safety, those methods are improved in data processing algorithms, floating threshold with multiple values, association with specific working condition, etc. These measures im- prove the nuclear instrument control system in fault tolerance and fault diagnosis, especially, the shutdown number of nucle- ar power plant decreases.

Genuine (k,m)-Threshold Controlled Teleportation and Multipartite Entanglement

We propose genuine （k, m）-threshold controlling schemes for controlled teleportation via multi-particle entangled states, where the teleportation of a quantum state from a sender （Alice） to a receiver （Bob） is under the control of m supervisors such that k （k≤ m） or more of these supervisors can help Bob recover the transferred state. By construction, anyone of our quantum channels is a genuine multipartite entangled state of which any two parts are inseparable. Their properties are compared and contrasted with those of the well-known GHZ, W, and linear cluster states, and also several other genuine multipartite entangled states recently introduced in the literature.

Threshold Multiparty Controlled Teleportation of Arbitrary m-Qubit Quantum Information

We present a （t, .n） threshold multiparty controlled quantum teleportation protocol of an arbitrary m-qubit quantum state between two remote parties. The unknown m-qubit quantum state can be recovered by the receiver under control of a subset of the n controllers if the number of the subset is larger than or equal to a threshold, say, t, but not for any t - 1 or fewer controllers. Our scheme seems to be more practical and more flexible than other existing protocols. The quantum resource required is just m Einstein-Podolsky-Rosen （EPR） pairs plus some single photons. The techniques required are only Bell state measurement, single-qubit unitary operation and yon Neumann measurement. So our scheme is also feasible with present-day technique.

Dynamic Threshold-Based Approach to Detect Low-Rate DDoS Attacks on Software-Defined Networking Controller

The emergence of a new network architecture,known as Software Defined Networking(SDN),in the last two decades has overcome some drawbacks of traditional networks in terms of performance,scalability,reliability,security,and network management.However,the SDN is vulnerable to security threats that target its controller,such as low-rate Distributed Denial of Service(DDoS)attacks,The low-rate DDoS attack is one of the most prevalent attacks that poses a severe threat to SDN network security because the controller is a vital architecture component.Therefore,there is an urgent need to propose a detection approach for this type of attack with a high detection rate and low false-positive rates.Thus,this paper proposes an approach to detect low-rate DDoS attacks on the SDN controller by adapting a dynamic threshold.The proposed approach has been evaluated using four simulation scenarios covering a combination of low-rate DDoS attacks against the SDN controller involving(i)a single host attack targeting a single victim;(ii)a single host attack targeting multiple victims;(iii)multiple hosts attack targeting a single victim;and(iv)multiple hosts attack targeting multiple victims.The proposed approach’s average detection rates are 96.65%,91.83%,96.17%,and 95.33%for the above scenarios,respectively;and its average false-positive rates are 3.33%,8.17%,3.83%,and 4.67%for similar scenarios,respectively.The comparison between the proposed approach and two existing approaches showed that it outperformed them in both categories.

A Computer System for Forecasting the Threshold Period for Crop Weed Control

In this article, a model of a weed control threshold forecast system has been established, with related model solving, data checking, database setting up, and system engineering illustration. Moreover, it is tested by a software with data from a sugar cane planting experimental field in Yunnan, China. The methodology behind the detailed system analysis, design, and engineering has been discussed. The issue of how to create a dynamic data-dependent forecast model of a threshold forecast system, whose threshold changes according to the change of planting environment has been solved. Hence an effective solution has been initiated for further development on an agricultural expert system.

Application of Statistical Process Control for Setting Action Thresholds as Quality Assurance of Dose Verifications in External Beam Radiotherapy

Purpose: To test the concept of Statistical Process Control (SPC) as a Quality Assurance (QA) procedure for dose verifications in external beam radiation therapy in conventional and 3D Conformal Radiotherapy (3D-CRT) treatment of cervical cancer. Materials and Methods: A study of QA verification of target doses of 198 cervical cancer patients undergoing External Beam Radiotherapy (EBRT) treatments at two different cancer treatment centers in Kenya was conducted. The target doses were determined from measured entrance doses by the diode in vivo dosimetry. Process Behavior Charts (PBC) developed by SPC were applied for setting Action Thresholds (AT) on the target doses. The AT set was then proposed as QA limits for acceptance or rejection of verified target doses overtime of the EBRT process. Result and Discussion: Target doses for the 198 patients were calculated and SPC applied to test whether the action limits set by the Process Behavior Charts could be applied as QA for verified doses in EBRT. Results for the two sub-groups of n = 3 and n = 4 that were tested produced action thresholds which are within clinical dose specifications for both conventional AP/PA and 3D-CRT EBRT treatment techniques for cervical cancer. Conclusion: Action thresholds set by SPC were within the clinical dose specification of ±5% uncertainty for both conventional AP/PA and 3D-CRT EBRT treatment techniques for cervical cancer. So the concept of SPC could be applied in setting QA action limits for dose verifications in EBRT.

基于POW的区块链共识机制的改进

基于工作量证明(Proof of Work,POW)的共识机制在寻找随机数(Nonce)过程中算力主导记账,浪费计算资源及内存,存在51%算力的危险。针对此缺陷,提出一种改进的基于POW的区块链共识机制IPOW(Improve Proof of Work),引入控制权重、激励阈值、有效时间和奖励因子,给出相关算法,通过控制权重等得出最终记账权R。实验结果表明,与POW相比,IPOW共识机制削弱了算力对于节点获得记账权的主导地位,控制权重越大,越容易获得记账权;降低节点作恶的概率,减少富人愈富现象的发生。

爆破振动效应研究若干进展

爆破振动效应是由爆破振动引起的周边环境的动力响应及其作用后果。当今,爆破技术在我国交通、水电、城建等领域工程建设中的应用越来越广泛、爆破环境也越来越复杂,爆破振动控制成为制约工程爆破安全高效施工的工程难题。在综述爆破振动相关研究现状的基础上,从爆破振动特征、作用机理与动力响应、预测及控制技术3个方面,系统归纳和阐述了爆破振动效应研究的科学技术体系,并结合近年来一些典型的工程建设背景,介绍了作者团队在爆破振动效应研究相关方面的若干进展。

机力通风冷却塔风机自寻优群控方法研究

机力通风冷却塔以占地面积小的显著优点,在中小型基建工程中得到广泛应用。为提升中小型基建工程外冷系统的节能性和可靠性、改进传统多风机控制方法,创新性地提出了一种基于累计运行时间的机力通风冷却塔风机自寻优群控方法。将多风机整体化控制改进为顺序化联动控制,可有效降低风机启动门槛出力、消除整体化控制固有缺陷,满足非线性、时变性、大滞后系统控制的节能、可靠需求。经工程验证:该方法是一种契合纯变频电机配置冷却塔系统的多风机控制方法。该方法风机出力柔和、控制线性度好、系统易镇定、稳态偏差小;能够通过累计运行时间参数比对,实现风机自动交互运行,运行可靠性高。该方法的提出与实际应用可对配置机力通风冷却塔的中小型基建工程的安全节能运行提供借鉴。

高铁列车荷载作用下桩-土复合地基及近接地铁隧道的动力响应模拟研究

[目的]作为典型的振动荷载,高铁列车运行引起的振动荷载会诱发桩-土地基及附近结构产生动力响应,有必要对桩-土复合地基及近接隧道的动力响应特性进行研究。[方法]基于西安地铁14号线下穿大西高速铁路特大桥工程,采用模型试验和数值模拟相结合的方法,以峰值振动加速度、峰值振动速度和峰值振动位移作为动力响应评价指标,研究了列车移动荷载作用下桩-土复合地基及近接隧道的动力响应特性。[结果及结论]研究结果表明,当施加列车荷载时,地基内部的动力响应指标均随着埋深的增加而衰减,但存在近接隧道时,动力响应指标值显著增加,且在隧道埋深处衰减明显。随着距桩基中心距离的增加,隧道埋深处的桩-隧之间地基的各动力响应指标从“波浪形”分布变为单调递减分布。根据峰值振动速度的控制阈值,近接隧道埋深处距桩基础中心水平3.6 m范围内的地基处于危险影响区,必须采用减振措施;3.6~11.4 m范围内的地基处于强影响区,建议采取减振措施;11.4 m以外的地基处于弱影响区,视结构的重要性决定是否需要采取减振措施。

债务融资对终极股东行为影响的实证分析——基于内部控制质量的门限效应和调节效应

集中股权结构的上市公司中,终极股东对其他中小股东有一定的利益侵害动机,债务融资作为公司治理的一个重要环节,研究其对终极股东行为的影响是一个值得探究的问题。以我国523家非金融类上市公司2007-2022年的面板数据为样本,考虑内部控制质量的门限效应与调节效应,实证检验了债务融资对终极股东掏空行为的促进或抑制效应。研究发现:(1)银行债务、商业信用和长期债务对终极股东掏空行为具有显著的促进效应;当内部控制质量分别大于门限值860.160、873.700、873.700时,此类效应减弱;(2)短期债务对终极股东掏空行为具有显著的抑制效应;当内部控制质量大于门限值873.700时,此效应得到加强;(3)商业信用、长期债务、银行债务对于国有企业中终极股东掏空行为的促进效应,受到内部控制质量的反向调节。研究结论为上市公司制定健全的内部治理环境策略以及为债权人制定合理的借贷策略从而促进上市公司高质量发展提供了参考依据。

改进的量子彩色图像中值滤波算法

图像处理任务中广泛应用中值滤波器来平滑图像和消除幅度极大或极小的噪声,并且可以保持图像的边缘特性,不会使图像产生明显模糊。提出一种改进的空间域量子彩色图像中值滤波算法,并且在IBM Q(international business machines quantum)平台上进行仿真。该算法将量子彩色图像进行存储,利用量子比较器模块、量子控制交换器模块、中值计算模块和阈值模块设计量子彩色图像中值滤波的量子线路。相较于已有的量子彩色图像中值滤波算法,在进行中值滤波之前加入了阈值进行噪声判断,该算法滤波效果更好,同时时间复杂度也更低。

基于阈值控制策略的Filippov Chay神经元动力学及其耦合同步

细胞内外带电离子的连续泵送和传递产生的电磁感应效应对神经元的电活动及模态转换会产生一定的影响,促使其展现出更加丰富的放电特性.文章基于电磁感应影响下的Chay神经元模型,引入了一种以膜电压为阈值的不连续控制策略,建立了相应的Filippov Chay神经元模型,探究了在阈值控制策略影响下的神经元放电节律转迁及相应的边界运动.首先,对系统的边界动力学及滑膜动力学进行了理论分析.其次,利用单双参数分岔图探究了系统多样的放电模式.再次,结合Matcont仿真及稳定性理论详细分析了系统的平衡点及其稳定性,并且利用快慢动力学分析法进一步研究了在阈值影响下所产生的滑膜动力学及各种边界运动的切换.最后,通过电突触耦合,对不同阈值条件下耦合神经元的同步问题进行了讨论.数值仿真结果表明,在阈值的调控下Filippov Chay系统会产生滑膜放电活动及相应的穿越运动和擦边运动,同时其放电周期数也会随着阈值呈现出不同的变化规律,且对于不同阈值下的电耦合情况而言,在系统实现完全同步后都会稳定在周期数较低的放电态.以上所得结果有助于更好地理解神经元滑膜的相关控制,对进一步探究生物神经系统中复杂放电活动和信息处理的动力学行为提供了一定的帮助.

双闭环PID应用下投篮机器人路径跟踪控制研究

投篮机器人路径图像噪声会影响机器人路径跟踪控制效果,导致投篮机器人偏离正常轨迹,为此提出双闭环PID应用下投篮机器人路径跟踪控制方法。分析投篮机器人架构,利用OpenMv视觉识别方法采集投篮机器人路径图像,结合小波阈值算法对采集到的图像实施去噪处理,从而获取清晰的投篮机器人路径图像。根据图像去噪处理结果,将曲线拟合法与特征点检测法相结合,实现投篮机器人路径识别。根据投篮机器人路径识别结果确定路径实际偏移量,结合推动器实现位置、移动速度建立的双闭环PID控制器,从而实现投篮机器人路径跟踪控制。实验结果表明,该方法的投篮机器人路径图像去噪熊效果好、跟踪控制效果好,充分验证了该方法的有效性。

基于行驶舒适性的路桥过渡段差异沉降控制阈值

为解决传统路面结构路桥过渡段差异沉降过大和二次跳车问题,结合路桥工程实践,通过将桥头搭板放置一定深度和设置两级枕梁,并将桥头搭板与枕梁现浇在一起的方式,提出一种刚柔连续过渡的桥头搭板结构,用以改善桥头路基的应力分布及变形;同时为研究不同等级公路的路桥过渡段差异沉降控制阈值,给出量化指标,通过分析桥头跳车作用机理,根据车辆振动系统输入激励与输出响应的关系,建立二维五自由度车辆振动模型,并根据不同等级公路的路桥过渡段处治情况,建立相应的计算模型,编写程序求解人体加权加速度均方根值,根据人体舒适程度分级情况确定不同等级公路的路桥过渡段差异沉降控制阈值。结果表明:高速公路一级公路、二级公路和三级公路的路桥过渡段差异沉降控制阈值为将容许搭板纵坡变化值控制在0.30%~0.40%、0.40%~0.55%、0.50%~0.75%和0.95%~1.35%,四级公路的路桥过渡段差异沉降控制阈值为台阶高度控制在0.05m以内。

氨氮胁迫对厌氧处理高浓度有机氮废水的影响

以实际制膜废水为例,探究了氨胁迫下高浓度有机氮废水甲烷化及微生物群落的动态响应,明确了氨抑制阈值,抑制形态,抑制机制和应对策略.结果表明,氨对AD处理高浓度有机氮废水的主要氨抑制形态为游离氨(FA),抑制阈值为(145±10)mg/L,半抑制浓度为(244±10)mg/L.在AD处理高浓度有机氮废水时,乙酸营养型产甲烷菌Methanosaeta,甲基营养型产甲烷菌Methanomassiliicoccus和Methanomethylovorans是主要产甲烷微生物.Methanosaeta和Methanomethylovorans分别在氨氮高于300mg/L和900mg/L时活性下降,同时产氢产二氧化碳相关功能微生物在FA高于140mg/L时受到抑制,使含碳数大于1的小分子有机物在系统内累积,最终导致高FA条件下化学需氧量去除率降低和氨氮释放不完全.在受到高氨抑制后,可通过调控pH值的方式实现系统的恢复,但无法通过微生物驯化的方式缓解.

改进小波阈值降噪方法在振动-高动态离心复合试验控制系统中的应用

目的 针对振动-高动态离心复合试验控制系统中控制信号受噪声干扰导致控制效果不佳的情况,进行降噪处理,以提升试验控制能力。方法 利用改进的小波阈值降噪方法,对振动-高动态离心复合试验控制系统中控制信号进行降噪处理,通过分析信号特性,结合小波阈值降噪方法原理,提出阈值准则随分解尺度自适应动态变化的改进方法。结果 通过本文改进方法和其他小波阈值降噪方法的对比分析表明,本文所提方法对于振动-高动态离心系统所存在的中高频噪声干扰起到了明显抑制作用,可有效保留控制信号特征,获得了更佳的综合降噪效果,信噪比提升近10 dB,满足试验控制所需的降噪要求。结论 采用自适应动态变化的阈值准则的小波阈值降噪方法对振动-高动态离心复合试验系统的控制信号进行降噪处理有效且可靠,可对后续相关试验技术研究方向提供一种可行思路。

双波长LD泵浦Nd^(3+)∶YAG免温控被动调Q激光器的研究

传统的固体激光器体积、重量大,功耗高,限制了其在空间受限设备中的应用。被动调Q的LD泵浦免温控固体激光器省去了复杂的温度控制装置,调Q机构简单,能够满足复杂温度环境的特殊应用场景的小型化、低功耗要求。提出了基于双波长LD泵浦实现宽温度范围免温控阈值自适应的1.06μm激光脉冲输出方法。基于Nd∶YAG晶体设计了角锥棱镜谐振腔,仿真分析了LD泵浦源到激光棒的面心距对热负载的影响,并确定4 mm的最佳面心距。数值分析了相同泵浦功率下-40~60℃温度范围内激光静态能量输出变化,以及不同初始透过率的可饱和吸收体对激光阈值脉宽的影响。计算结果表明在-37℃~60℃范围内,阈值脉宽都在200μs以下,阈值脉宽最低点达到了29.4μs。构建主波实时探测的阈值自适应调节装置并搭建实验系统,实验结果表明,在温度范围为-35~60℃时,阈值脉宽变化范围为40~180μs。采用激光腔体一体加工成型,应用轻量化的铝合金材料,实现工程化应用,体积83.5 mm×44 mm×29.5 mm,重量约为230 g。在23.8%初始透过率的饱和吸收体条件下实现单脉冲输出能量42 mJ,脉冲宽度5.2 ns。

基于庞特里亚金极小值原理的柴电混合动力船舶能量管理策略

提升混合动力船舶的能源利用率,制定合适的能量管理策略以实现功率合理分配、减小船舶燃油消耗、节约成本,是混合动力船舶的亟需解决的关键技术问题。本文基于Matlab/Simulink仿真建模软件,建立对象船舶的动力系统仿真模型,研究不同功率需求下对柴油发电机和超级电容的控制要求。考虑动力源特性和船舶功率需求,本文提出了一种基于庞特里亚金极小值的能量管理策略对目标船舶进行合理的功率分配。仿真结果表明:基于庞特里亚金极小值原理的能量管理策略能够优化船舶柴油机组原动机的工作状态,使其在比油耗较低的点工作。在该策略的控制下,航行工况内的柴油发电机组原动机平均比油耗为207.2 g/(kW·h),总燃油消耗量为204.1 kg。本文方法不仅对船舶减小燃油消耗具有积极的作用,同时对提高船舶运行经济性具有重要意义。