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.

A novel multi-channel porous structure facilitating mass transport towards highly efficient alkaline water electrolysis

An advantageous porous architecture of electrodes is pivotal in significantly enhancing alkaline water electrolysis(AWE)efficiency by optimizing the mass transport mechanisms.This effect becomes even more pronounced when aiming to achieve elevated current densities.Herein,we employed a rapid and scalable laser texturing process to craft novel multi-channel porous electrodes.Particularly,the obtained electrodes exhibit the lowest Tafel slope of 79 mV dec^(-1)(HER)and 49 mV dec^(-1)(OER).As anticipated,the alkaline electrolyzer(AEL)cell incorporating multi-channel porous electrodes(NP-LT30)exhibited a remarkable improvement in cell efficiency,with voltage drops(from 2.28 to 1.97 V)exceeding 300 mV under 1 A cm^(-1),compared to conventional perforated Ni plate electrodes.This enhancement mainly stemmed from the employed multi-channel porous structure,facilitating mass transport and bubble dynamics through an innovative convection mode,surpassing the traditional convection mode.Furthermore,the NP-LT30-based AEL cell demonstrated exceptional durability for 300 h under 1.0 A cm^(-2).This study underscores the capability of the novel multi-channel porous electrodes to expedite mass transport in practical AWE applications.

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.

Design of Cold-Junction Compensation and Disconnection Detection Circuits of Various Thermocouples and Implementation of Multi-Channel Interfaces Using Them-A Secondary Publication

Cold-junction compensation(CJC)and disconnection detection circuit design of various thermocouples(TC)and multi-channel TC interface circuits were designed.The CJC and disconnection detection circuit consists of a CJC semiconductor device,an instrumentation amplifier(IA),two resistors,and a diode for disconnection detection.Based on the basic circuit,a multi-channel interface circuit was also implemented.The CJC was implemented using compensation semiconductor and IA,and disconnection detection was detected by using two resistors and a diode so that IA input voltage became-0.42 V.As a result of the experiment using R-type TC,the error of the designed circuit was reduced from 0.14 mV to 3μV after CJC in the temperature range of 0°C to 1400°C.In addition,it was confirmed that the output voltage of IA was saturated from 88 mV to-14.2 V when TC was disconnected from normal.The output voltage of the designed circuit was 0 V to 10 V in the temperature range of 0°C to 1400°C.The results of the 4-channel interface experiment using R-type TC were almost identical to the CJC and disconnection detection results for each channel.The implemented multi-channel interface has a feature that can be applied equally to E,J,K,T,R,and S-type TCs by changing the terminals of CJC semiconductor devices and adjusting the IA gain.

Multi-channel terahertz focused beam generator based on shared-aperture metasurface

Most of existing metasurfaces usually have limited channel behavior,which seriouslyhinders their development and application.In this paper,we propose a multi-channel terahertz focused beam generator based on shared-aperture metasurface,and the generator consists of a top square metal strip,a middle layer of silica and a metal bottom plate.By changing the position and size of the shared-aperture array,the designed metasurface can generate any number of multi-channel focusing beams at different predicted positions.In addition,the energy intensity of focusing beams can be controlled.The full-wave simulation results show that the metasurface achieves four-channel vortex focused beam generation with different topological charges,and five-,six-,eight-channel focused beam generation with different energy intensities at a frequency of 1 THz,which are in good agreement with the theoretically calculated predictions.This work can provide a new idea for designing the terahertz multichannel devices.

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.

Fast pre-stack multi-channel inversion constrained by seismic reflection features

Classical multi-channel technology can significantly reduce the pre-stack seismic inversion uncertainty, especially for complex geology such as high dipping structures. However, due to the consideration of complex structure or reflection features, the existing multi-channel inversion methods have to adopt the highly time-consuming strategy of arranging seismic data trace-by-trace, limiting its wide application in pre-stack inversion. A fast pre-stack multi-channel inversion constrained by seismic reflection features has been proposed to address this issue. The key to our method is to re-characterize the reflection features to directly constrain the pre-stack inversion through a Hadamard product operator without rearranging the seismic data. The seismic reflection features can reflect the distribution of the stratum reflection interface, and we obtained them from the post-stack profile by searching the shortest local Euclidean distance between adjacent seismic traces. Instead of directly constructing a large-size reflection features constraint operator advocated by the conventional methods, through decomposing the reflection features along the vertical and horizontal direction at a particular sampling point, we have constructed a computationally well-behaved constraint operator represented by the vertical and horizontal partial derivatives. Based on the Alternating Direction Method of Multipliers (ADMM) optimization, we have derived a fast algorithm for solving the objective function, including Hadamard product operators. Compared with the conventional reflection features constrained inversion, the proposed method is more efficient and accurate, proved on the Overthrust model and a field data set.

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.

Opportunistic Routing with Multi-Channel Cooperative Neighbour Discovery

Due to the scattered nature of the network,data transmission in a dis-tributed Mobile Ad-hoc Network(MANET)consumes more energy resources(ER)than in a centralized network,resulting in a shorter network lifespan(NL).As a result,we build an Enhanced Opportunistic Routing(EORP)protocol architecture in order to address the issues raised before.This proposed routing protocol goal is to manage the routing cost by employing power,load,and delay to manage the routing energy consumption based on theflooding of control pack-ets from the target node.According to the goal of the proposed protocol techni-que,it is possible to manage the routing cost by applying power,load,and delay.The proposed technique also manage the routing energy consumption based on theflooding of control packets from the destination node in order to reduce the routing cost.Control packet exchange between the target and all the nodes,on the other hand,is capable of having an influence on the overall efficiency of the system.The EORP protocol and the Multi-channel Cooperative Neighbour Discovery(MCCND)protocol have been designed to detect the cooperative adja-cent nodes for each node in the routing route as part of the routing path discovery process,which occurs during control packet transmission.While control packet transmission is taking place during the routing path discovery process,the EORP protocol and the Multi-channel Cooperative Neighbour Discovery(MCCND)protocol have been designed to detect the cooperative adjacent nodes for each node in the routing.Also included is a simulation of these protocols in order to evaluate their performance across a wide range of packet speeds using Constant Bit Rate(CBR).When the packet rate of the CBR is 20 packets per second,the results reveal that the EORP-MCCND is 0.6 s quicker than the state-of-the-art protocols,according to thefindings.Assuming that the CBR packet rate is 20 packets per second,the EORP-MCCND achieves 0.6 s of End 2 End Delay,0.05 s of Routing Overhead Delay,120 s of Network Lifetime,and 20 J of Energy Consumption efficiency,which is much better than that of the state-of-the-art protocols.

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。

W-系统矩和Fourier变换下Volume Descriptors不变特征的三维模型检索

针对V-系统矩难以构造快速算法的不足,提出一种W-系统矩及其快速算法,并融合volume descriptors不变特征应用于三维模型检索.首先对模型体素化;其次计算体素模型的W-系统矩和物体运动不变量,得到特征向量;最后进行特征融合及匹配.实验结果表明,该算法的检索效率和性能均优于三维球面调和函数方法和三维Legendre矩方法.

钙质砂特征形状分析及不排水剪切强度研究

钙质砂的形状是影响其宏观力学性质的重要因素。人工挑选出不同特征形状(块状、片状、条状)的钙质砂,通过显微图像采集与处理技术,定义并构建了一个形状参数(偏离度α),对钙质砂的特征形状进行三维定量描述,配制3种不同形状掺量的钙质砂试样进行三轴固结不排水剪切试验,研究钙质砂的特征形状对其剪切特性的影响。研究结果表明:(1)偏离度α能够较好地对钙质砂的形状进行描述及区分,可作为一种量化钙质砂形状的有效手段;(2)钙质砂的不排水剪切强度与偏离度α有较好的相关性:若增加片状钙质砂的含量(α增加),则试样的不排水剪切强度降低,若增加条状钙质砂的含量(α减小),不排水剪切强度增大。研究成果不但加深了对钙质砂特征形状的理解,还为准确评估钙质砂的抗剪强度提供了新思路。

阳光玫瑰葡萄感官特征解析与感官轮建立

为了明确阳光玫瑰葡萄的感官特征并构建其科学完善的感官轮,本研究通过建立感官品评小组,对不同产区的阳光玫瑰葡萄以及在不同温度下贮藏的阳光玫瑰葡萄进行系统感官评价。研究明确了能够表征阳光玫瑰葡萄感官特点的10个外观轮廓描述语,包括饱满、颗粒紧凑、大小均匀、翠绿、黄绿、着色均匀、果皮光滑、果面有光泽感、水滴型、圆球状;11个质地轮廓描述语,包括皮薄、肉厚、硬、脆、嫩、紧实、细腻、有弹性、水分大、无籽、润滑;7个口感轮廓描述语,包括甘甜、清脆、爽口、鲜嫩、水润、清新、回味香甜;和4个香气轮廓描述语,包括玫瑰香、果香、甜香和草本植物香气,并进而构建了阳光玫瑰葡萄感官轮和其在不同贮藏方式下的感官轮。本研究首次解析阳光玫瑰葡萄感官特征并构建感官轮,为生产者和消费者之间的感官沟通提供基础,也为阳光玫瑰葡萄贮藏、品质改进和开发研究提供指导意义。