Robust zero-watermarking algorithm based on discrete wavelet transform and daisy descriptors for encrypted medical image

In the intricate network environment,the secure transmission of medical images faces challenges such as information leakage and malicious tampering,significantly impacting the accuracy of disease diagnoses by medical professionals.To address this problem,the authors propose a robust feature watermarking algorithm for encrypted medical images based on multi-stage discrete wavelet transform(DWT),Daisy descriptor,and discrete cosine transform(DCT).The algorithm initially encrypts the original medical image through DWT-DCT and Logistic mapping.Subsequently,a 3-stage DWT transformation is applied to the encrypted medical image,with the centre point of the LL3 sub-band within its low-frequency component serving as the sampling point.The Daisy descriptor matrix for this point is then computed.Finally,a DCT transformation is performed on the Daisy descriptor matrix,and the low-frequency portion is processed using the perceptual hashing algorithm to generate a 32-bit binary feature vector for the medical image.This scheme utilises cryptographic knowledge and zero-watermarking technique to embed watermarks without modifying medical images and can extract the watermark from test images without the original image,which meets the basic re-quirements of medical image watermarking.The embedding and extraction of water-marks are accomplished in a mere 0.160 and 0.411s,respectively,with minimal computational overhead.Simulation results demonstrate the robustness of the algorithm against both conventional attacks and geometric attacks,with a notable performance in resisting rotation attacks.

Performance enhancement of a viscoelastic bistable energy harvester using time-delayed feedback control

This paper focuses on the stochastic analysis of a viscoelastic bistable energy harvesting system under colored noise and harmonic excitation, and adopts the time-delayed feedback control to improve its harvesting efficiency. Firstly, to obtain the dimensionless governing equation of the system, the original bistable system is approximated as a system without viscoelastic term by using the stochastic averaging method of energy envelope, and then is further decoupled to derive an equivalent system. The credibility of the proposed method is validated by contrasting the consistency between the numerical and the analytical results of the equivalent system under different noise conditions. The influence of system parameters on average output power is analyzed, and the control effect of the time-delayed feedback control on system performance is compared. The output performance of the system is improved with the occurrence of stochastic resonance(SR). Therefore, the signal-to-noise ratio expression for measuring SR is derived, and the dependence of its SR behavior on different parameters is explored.

Building Facade Point Clouds Segmentation Based on Optimal Dual-Scale Feature Descriptors

To address the current issues of inaccurate segmentation and the limited applicability of segmentation methods for building facades in point clouds, we propose a facade segmentation algorithm based on optimal dual-scale feature descriptors. First, we select the optimal dual-scale descriptors from a range of feature descriptors. Next, we segment the facade according to the threshold value of the chosen optimal dual-scale descriptors. Finally, we use RANSAC (Random Sample Consensus) to fit the segmented surface and optimize the fitting result. Experimental results show that, compared to commonly used facade segmentation algorithms, the proposed method yields more accurate segmentation results, providing a robust data foundation for subsequent 3D model reconstruction of buildings.

Non-fragile observer-based passive control for descriptor systems with time-delay

This paper investigates the problem of non-fragile observer-based passive control for descriptor systems with time-delay. The perturbations in both the control gain and observer gain of the observer-based controller are considered. For the cases of the additive perturbations and multiplicative perturbations, sufficient conditions are given such that the closed-loop systems are admissible and passive with dissipation η. The observer-based controller gains could be obtained from the solutions of linear matrix inequalities （LMIs）. Moreover, the maximum dissipation of the system is provided. Simulation examples are given to show the effectiveness of the deign methods.

Observer-based passive control for descriptor systems with time-delay

This article is concerned with the problem of observer-based passive control for descriptor systems with time delay. Sufficient conditions are first presented for the closed loop systems to be admissible and passive with dissipation η in the case of that the time delay is known, and two kinds of methods are given to design the expected observer. Then, the case of that the time delay is unknown or uncertain is discussed. The observer-based control gains could be obtained from the solutions of linear matrix inequalities （LMIs）. Simulation examples are given to show the effectiveness of the designed methods.

Effects of time-delayed vibration absorber on bandwidth of beam for low broadband vibration suppression

The effects of time-delayed vibration absorber(TDVA) on the dynamic characteristics of a flexible beam are investigated. First, the vibration suppression effect of a single TDVA on a continuous beam is studied. The first optimization criterion is given,and the results show that the introduction of time-delayed feedback control(TDFC) is beneficial to improving the vibration suppression at the anti-resonance band. When a single TDVA is used, the anti-resonance is located at a specific frequency by the optimum design of TDFC parameters. Then, in order to obtain low-frequency and broad bands for vibration suppression, multiple TDVAs are uniformly distributed on a continuous beam,and the relationship between the dynamic responses and the TDFC parameters is investigated. The obtained relationship shows that the TDVA has a significant regulatory effect on the vibration behavior of the continuous beam. The effects of the number of TDVAs and the nonlinearity on the bandgap variation are discussed. As the multiple TDVAs are applied, according to the different requirements on the location and bandwidth of the effective vibration suppression band, the optimization criteria for the TDFC parameters are given, which provides guidance for the applications of TDVAs in practical projects such as bridge and aerospace.

Design and analysis of active disturbance rejection control for time-delay systems using frequency-sweeping

For the typical first-order systems with time-delay,this paper explors the control capability of linear active disturbance rejection control(LADRC).Firstly,the critical time-delay of LADRC is analyzed using the frequency-sweeping method and the Routh criterion,and the stable time-delay interval starting from zero is accurately obtained,which reveals the limitations of general LADRC on large time-delay.Then in view of the large time-delay,an LADRC controller is developed and verified to be effective,along with the robustness analysis.Finally,numerical simulations show the accuracy of critical time-delay,and demonstrate the effectiveness and robustness of the proposed controller compared with other modified LADRCs.

Degree-Based Entropy Descriptors of Graphenylene Using Topological Indices

Graph theory plays a significant role in the applications of chemistry,pharmacy,communication,maps,and aeronautical fields.The molecules of chemical compounds are modelled as a graph to study the properties of the compounds.The geometric structure of the compound relates to a few physical properties such as boiling point,enthalpy,π-electron energy,andmolecular weight.The article aims to determine the practical application of graph theory by solving one of the interdisciplinary problems describing the structures of benzenoid hydrocarbons and graphenylene.The topological index is an invariant of a molecular graph associated with the chemical structure,which shows the correlation of chemical structures using many physical,chemical properties and biological activities.This study aims to introduce some novel degree-based entropy descriptors such as ENTSO,ENTGH,ENTHG,ENTSS,ENTNSO,ENTNReZ1,ENTNReZ2 and ENTNSS using the respective topological indices.Also,the above-mentioned entropy measures and physico-chemical properties of benzenoid hydrocarbons are fitted using linear regression models and calculated for graphenylene structure.

Combining descriptor-based analyses and mean-field modeling of the electrochemical interface to comprehend trends of catalytic processes at the solid/liquid interface

Electrocatalysis is undergoing a renaissance due to its central importance for a sustainable energy economy,relying on green(electro-)chemical processes to harvest,convert,and store energy.Theoretical considerations by electronic structure methods are key to identify potential material motifs for electrocatalytic processes at the solid/liquid interface.Most commonly,heuristic concepts in the realm of materials screening by the compilation of volcano plots are used,which rely on a plethora of simplifications and approximations of the complex electrochemical interface.While the investigation of the catalytic processes at the solid/liquid interface mainly relies on descriptor-based approaches,in the present future article it is discussed that the inclusion of the liquid part of the interface by mean-field models is crucial to elevate screening approaches to the next level.

Design of novel transition-metal-doped C_(4)N_(4) as highly effective electrocatalysts for nitrogen fixation with a new intrinsic descriptor

Electrocatalytic nitrogen reduction reaction(NRR) is an efficient and green way to produce ammonia,which offers an alternative option to the conventional Haber-Bosch process.Unfortunately,the large-scale industrial application of NRR processes is still hindered by poor Faraday efficiency and high overpotential,which need to be overcome urgently.Herein,combined with density functional theory and particle swarm optimization algorithm for the nitrogen carbide monolayer structural search(C_mN_(8-m),m=1-7),the surprising discovery is that single transition metal-atom-doped C_(4)N_(4) monolayers(TM@C_(4)N_(4)) could effectively accelerate nitrogen reduction reaction.TM@C_(4)N_(4)(TM=29 transition metals) as single-atom catalysts are evaluated via traditional multi-step screening method,and their structures,NRR activity,selectivity and solvation effect are investigated to evaluate their NRR performance,Through the screening steps,W@C_(4)N_(4) possesses the highest activity for NRR with a very low limiting potential of-0.29 V.Moreover,an intrinsic descriptor φ is proposed with machine learning,which shortens the screening process and provides a new idea for finding efficient SACs.This work not only offers promising catalysts W@C_(4)N_(4) for NRR process but also offers a new intrinsic and universal descriptor φ.

Group Hybrid Coordination Control of Multi-Agent Systems With Time-Delays and Additive Noises

A new kind of group coordination control problemgroup hybrid coordination control is investigated in this paper.The group hybrid coordination control means that in a whole multi-agent system(MAS)that consists of two subgroups with communications between them,agents in the two subgroups achieve consensus and containment,respectively.For MASs with both time-delays and additive noises,two group control protocols are proposed to solve this problem for the containment-oriented case and consensus-oriented case,respectively.By developing a new analysis idea,some sufficient conditions and necessary conditions related to the communication intensity betw een the two subgroups are obtained for the following two types of group hybrid coordination behavior:1)Agents in one subgroup and in another subgroup achieve weak consensus and containment,respectively;2)Agents in one subgroup and in another subgroup achieve strong consensus and containment,respectively.It is revealed that the decay of the communication impact betw een the two subgroups is necessary for the consensus-oriented case.Finally,the validity of the group control results is verified by several simulation examples.

Effects of Physical Parameters and Time-Delay Coefficients on the Amplitude and Frequency Bandwidth of Saturation Controller for a Beam Vibration

In this paper, the influence of physical parameters on the width of saturated control frequency band and the influence of time delay parameters on the stability of saturated control system are studied. The analytical solution of the motion equation of the system when the main resonance and the 1:2 internal resonance occur simultaneously is obtained by multiple scale method, experimentally measured natural frequencies of nonlinear beams. The effects of excitation amplitude, delay feedback coefficients and nonlinear coefficients on saturation control are investigated. The results of the study show that the bandwidth of the saturation control can be increased by increasing the value of the external excitation, the nonlinear coefficients enhance the nonlinear phenomena of the system.

基于直线段检测和LT描述符的矿井图像线特征匹配算法

图像匹配是同步定位与地图构建(SLAM)技术中极为重要的一环,用于根据图像之间的变换关系确定相机位姿。基于线特征的图像匹配方法具有较强的鲁棒性和抗噪能力,更加适用于井下图像匹配,基于深度学习的线描述符对线段遮挡等场景具有较高的鲁棒性,性能优于传统描述符,但卷积神经网络架构的描述符将可变长度线段抽象为固定维进行描述,不利于线段长度及视差变化较大图像的匹配。针对上述问题,提出一种基于直线段检测和线描述符的矿井图像线特征匹配算法。在频域利用单参数同态滤波降低图像的照射分量,并增强反射分量,提升亮度及对比度;在YUV空间利用对比度受限的自适应直方图均衡化(CLAHE)算法对亮度分量进行均衡,使亮度分布更加均匀;变换至RGB空间提取直线段检测(LSD)线,引入一种基于Transformer架构的LT描述符构建LSD线的特征向量,最后完成线特征匹配。实验结果表明:该算法结合了同态滤波和CLAHE算法的优点,增强后图像的亮度适中,对比度良好,灰度分布均匀,增强效果优于单参数同态滤波算法、EnlightenGAN算法;该算法提取的线特征数较原图平均提升了32.92%,在不同相似纹理占比、不同程度旋转与平移变化的井下图像匹配中鲁棒性好,平均正确匹配数为61.75对,平均精度为86.83%,优于线二进制描述符(LBD)算法、LBD_NNDR算法、LT算法,能够满足矿井图像稳健匹配的需求。

基于非线性各向异性滤波的图像特征匹配算法

图像特征匹配是增强现实系统中的关键技术,匹配精度是提升特征匹配性能的关键。提出了一种多尺度特征匹配加强算法(I-AKAZE),通过对非线性各向异性滤波过程中传导函数的改进,减缓图像梯度值大的区域非线性扩散速度,极大程度地保留了匹配图像的边缘特征;同时,结合改进的非线性量化加速稳健特征描述符(NLG-SURF),提高了描述符的识别率。实验结果表明I-AKAZE算法在Mikolajczyk数据集上的可重复性得分相比目前先进的AKAZE算法有着大幅度提升,对应的特征描述符的平均识别率提升8.4%,并且运行速度比经典的SIFT算法快约19%,算法整体在检测和描述阶段上的性能都有提升。

ML-QSPR方法预测煤基液体的燃料性能

煤基液体混合物如煤焦油、煤直接液化油的分子结构描述和性质预测是开发煤基液体产品高值化工艺和技术的重要基础。由于煤基液体主要由C、H、O、N、S元素构成数量庞杂、芳环结构各异的混合物,因此,使用Python中的RDKit工具包,利用简化分子线性输入规范(Simplified Molecular Input Line Entry System,SMILES)语言构建煤基液体中物质分子描述符,描述符包含样品元素信息、环数与环结构信息、原子数及分子量信息等共计115个分子描述符。对比人工信息提取方法,将所构建的分子描述符能够体现煤基液体分子结构碎片、分子量及原子个数信息等作为机器学习的特征输入变量,用于建立预测煤基液体的燃料性能的分子机器学习-定量结构性质关系方法 (ML-QSPR),实现对燃料低位热值(LHV)、液体密度(ρ)、闪点(FP)、十六烷值(CN)4个关键燃料性能参数的快速预测。模型验证分析表明LHV、ρ、FP模型的R^(2)分别为0.996、0.988、0.987;CN预测中加入混合物数据进行预测,R^(2)=0.959。与已公开报道的预测LHV、ρ、FP、CN性质方法对比,笔者提出ML-QSPR方法在预测4个关键燃料性能参数准确度方面有提升,在获取结果速度方面有显著优势。利用ML-QSPR模型预测得到的煤基液体制特种燃料性能参数数据库中的信息,分析增加不同族组分物质的碳原子数量时4个燃料性能参数的演变趋势,发现LHV、ρ、FP、CN四个燃料性能参数均受碳数(n)影响显著。由于LHV主要由n决定,不同族组分物质的LHV差距小;而不同族组分物质的ρ、FP和CN性质差距明显。此外,本研究训练好的模型可用于预测新的分子,为新型燃料分子设计提供参考;ML-QSPR方法作为迁移学习模型可在今后用于煤基液体其他场景相关理化性质的分析。

基于形状描述符的滞回曲线相似性指标的形成

为了形成全面的相似度指标以评价滞回曲线的拟合程度,引入了已广泛用于图像特征提取的形状描述符,并提出了基于这些描述符形成计算数值模拟曲线相对于实验曲线的相似度指标的具体流程.根据该流程,形成了一个基于形状上下文的相似度指标.先计算两曲线滞回圈之间的相似度,再对这些相似度进行加权组合,形成整个滞回环的相似度.为了验证该指标,采用Bouc-Wen模型进行数值模拟研究.改变Bouc-Wen模型的5个参数,并形成51条数值模拟曲线,计算这些曲线相对于中值曲线的相似度与力峰值点、耗能、刚度误差.结果表明,相似度与误差之间的斯皮尔曼相关系数绝对值均大于0.78,有强烈的相关性,从而验证了该指标的可行性和指标形成流程的有效性.

一种基于点云语义图描述符的回环检测方法研究

随着计算机水平和机器人传感器技术的不断进步,移动机器人已逐渐向智能化发展。其中,定位与建图(SLAM)是其定位的关键技术,回环检测是SLAM系统的重要模块。为解决传统回环检测耗时长和效率低等问题,本文提出一种基于点云语义图描述符的回环检测方法,在KITTI里程计数据集00和05序列中进行回环检测性能测试,并与Scan Context、LEGO-LOAM和VFH三种算法进行对比。结果表明:该方法在100%准确率下的召回率和50%召回率下的准确率最高,回环检测性能最好。

基于傅里叶描述子的手势识别方法

手势识别是计算机视觉人机交互应用领域关键技术,手势轮廓携带有手势重要特征,准确捕获手势轮廓对提高手势识别具有重要意义。针对手掌轮廓特征提取困难和手势识别率低问题,提出了基于傅里叶描述子的手势识别方法,按照候选窗口最大轮廓傅里叶描述子匹配度和置信度分割出手掌区域;跟踪手掌轮廓计算其傅里叶描述子得到手势轮廓特征值;将16个手势轮廓特征值作为BP人工神经网络的输入,利用BP人工神经网络识别手势。实验表明,该方法能有效捕获手势轮廓和识别19种手势,具有识别率高、性能优良和鲁棒性好等优点。

酱香型白酒感官品质描述形成、发展与趋势

酱香型白酒因其深厚文化底蕴、传统固态酿造工艺、独特风味与感官体验,深受广大消费者的喜爱。文章于中国知网、全国标准信息公共服务平台及食品伙伴网数据库检索“酱香”“酱酒”相关文献121篇、标准96项,得到酱香型白酒感官描述词537个,通过对文献材料梳理分析,简述酱香型白酒感官品质描述形成、发展、趋势及其标准化历程,总结酱香型白酒风味物质与气味特征关系,分析现有描述词相关问题,并提出构建酱香型白酒感官品质描述体系及结合现代感官评价技术表征酱香型白酒感官品质的相关思路与建议。