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.

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.

SEDS技术制备水飞蓟素纳米颗粒

采用超临界流体增强溶液分散技术(SEDS)从丙酮溶液中沉淀制备水飞蓟素纳米颗粒,用扫描电镜考察了工艺参数温度(25℃,32℃,40℃,50℃)、压力(9.5 MPa,12 MPa,15 MPa,20 MPa)、溶液浓度(40 mg·mL-1,60 mg·mL-1,80mg·mL-1,100 mg·mL-1,120 mg·mL-1)对颗粒形貌、粒径尺寸及粒径尺寸分布的影响.结果表明,所得颗粒均为实心微球;温度和溶液浓度是影响粒径尺寸的主要因素,降低温度和浓度能够显著减小粒径尺寸;温度也对粒径尺寸分布影响显著,在40℃时,粒径尺寸分布较窄,当温度高于或低于40℃时,粒径尺寸分布明显变宽.通过优化工艺参数,在9.5 MPa,40℃,60 mg·mL-1的条件下,制备出粒径尺寸介于100～300nm的水飞蓟素纳米颗粒.

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.

郫县豆瓣感官轮及定量描述剖面建立

为探究中国地理标志产品郫县豆瓣的感官特性,通过感官评价小组构建郫县豆瓣的感官轮及定量描述剖面。采用中心点剖面法结合几何平均值对市面上21款豆瓣产品进行感官描述词开发,构建包括外观、基本味、香气、风味和质地5个维度共计53个感官描述词。进一步结合多元统计方法复选出23个感官描述词并建立相应的强度参比样,开展不同种类和等级郫县豆瓣感官品质的定量描述评价。结果表明,郫县传统豆瓣酱香、辣香更强、质地偏黏,可见性(蚕豆瓣)、硬度更大。相比传统豆瓣,郫县红油豆瓣颜色偏红褐色,具有更强的油香、香料香、湿润性和油味等特性。随等级增加,郫县豆瓣的酱香、豆豉味等特征更突出,滋味更加醇厚。本研究可为郫县豆瓣的感官品质评价、产品质量控制及改进提供基础数据和评价方法参考。

不同溶剂条件下利用SEDS法制备乙基纤维素微粒的实验研究

分别利用二氯甲烷、丙酮和乙醇作为溶剂采用超临界流体增强溶液分散法(SEDS)制备了乙基纤维素微粒,考察了不同压力、温度和溶剂条件下所制备微粒的粒径大小及形态。实验表明:在体系亚临界和超临界状态下制备的微粒粒径及形态完全不同;聚合物的玻璃化温度的降低对微粒的形态影响比较大;溶剂对微粒粒径及形态也有较大影响,特别是对可制备微粒的压力及温度的范围的影响。

SEDS在星载综合电子系统中的应用设计

针对目前如何实现星载软件快速集成和测试的需求,对空间数据系统咨询委员会CCSDS标准SIOS领域中SEDS的概念、应用背景以及国外最先展开应用的现状进行了分析;对星载综合电子系统的分层体系结构以及各层的功能、业务、构件、协议等进行了研究说明;基于该体系结构,给出了SEDS在星载综合电子系统研制过程中的顶层应用设计、以卫星遥测功能为例给出了SEDS的设计实例以及SEDS后续的扩展应用方法;在软件开发阶段、调试测试阶段、单元测试、组装测试以及确认测试阶段以SEDS为输入进行了设计验证,验证结果表明通过部分代码自动生成以及各阶段数据复用,SEDS的应用有助于实现星载接口的标准化并促进星载综合电子系统乃至整个航天器研制周期的缩短。

SEDS技术制备亚微米RDX的喷嘴结构设计

为了制备粒度分布窄的亚微米黑索今（RDX）球形颗粒，设计出一种适用于超临界流体增强溶液扩散（SEDS）技术的喷嘴。该喷嘴利用气流雾化原理，在结构上采用环缝、微孔湍流区等技术，使CO2流体在喷嘴内高速流动，解决了常规内部混合喷嘴易堵、制备粒度大等问题。经实验验证，在相同工艺条件（温度35℃、压力10MPa、CO2流量15kg·h-1、RDX溶液流量2mL·min-1）下，采用法国SFP2超临界萃取仪原装内混式喷嘴制备出分布区间3—15μm的微米级RDX球形颗粒，制备过程易堵；采用新结构喷嘴（中心孔内径及其壁厚值均为0．1mm、环缝宽度为0．1mm、湍流区长径比为10：1、压力差为1MPa）制备出的RDX粒度分布区0．1～2μm、平均粒度660nm、粒度形貌好、无团聚的亚微米RDX球形颗粒，制备过程顺畅，解决了易堵问题。

Fourier Descriptors with Different Shape Signatures:a Comparative Study for Shape Based Retrieval of Kinematic Constraints

Fourier Descriptors（FD） has been widely used in image analysis and computer vision for shape recognition as they can be made independent of translation,rotation,as well as scaling.They have also been used for developing methods for the analysis and synthesis of four-bar linkages for path generation.This paper focuses on a comparative study of Fourier descriptors derived from various shape signatures of planar closed curves.This includes representations based on Cartesian coordinates,centroid distance,cumulative angle,and curvature.The comparison is conducted not only using commonly used criteria for shape representation and identification but also in the context of shape based retrieval of kinematic constraints for task centered mechanism design.Examples are provided to seek to extract geometric constraints such as circle,circular arc,ellipse and line-segment from a given motion.

Chemical Reactivity Theory (CRT) Study of the Melanoidin M8: Local Conceptual Density Functional Theory Descriptors

This study evaluated a fixed long-range corrected range-separated hybrid (RSH) density functional associated with the Def2TZVP basis set alongside the Solvation Model based on Density (SMD) for the computation of the structure, molecular properties and chemical reactivity of the M8 intermediate melanoidin pigment. The preference of the active sites pertinent to radical, nucleophilic and electrophilic attacks is made through linking them with the electrophilic and nucleophilic Parr functions, Fukui function indices, and condensed Dual Descriptor. This study showed that the MN12SX density functional is the most suitable one for predicting the chemical reactivity of this system.

A Revisited Definition of the Three Solute Descriptors Related to the Van der Waals Forces in Solutions

It is currently admitted that the intermolecular forces implicated in Gas Liquid Chromatography (GLC) can be expressed as a product of parameters (or descriptors) of solutes and of parameters of solvents. The present study is limited to those of solutes, and among them the three ones are involved in the Van der Waals forces, whereas the two ones involved in the hydrogen bonding are left aside at this stage. These three studied parameters, which we call δ, ω and ε, respectively reflect the three types of Van der Waals forces: dispersion, orientation or polarity strictly speaking, and induction-polarizability. These parameters have been experimentally obtained in previous studies for 121 Volatile Organic Compounds (VOC) via an original Multiplicative Matrix Analysis (MMA) applied to a superabundant and accurate GLC data set. Then, also in previous studies, attempts have been made to predict these parameters via a Simplified Molecular Topology procedure (SMT). Because these last published results have been somewhat disappointing, a promising new strategy of prediction is developed and detailed in the present article.

A stochastic reconstruction strategy based on a stratified library of structural descriptors and its application in the molecular reconstruction of naphtha

Molecular reconstruction is a rapid and reliable way to provide molecular detail of petroleum fractions,which is required in the kinetic modeling of petroleum conversation processes at the molecular level.In the typical stochastic reconstruction method,the estimation of properties of pseudo molecules that are generated by Monte Carlo sampling depends on the building of predefined molecular libraries,which is expensive and inaccessible for certain petroleum fractions.In this paper,a novel stochastic reconstruction strategy is proposed,which is based on a stratified library of structural descriptors.Properties of pseudo molecules generated in the novel strategy can be directly estimated by group contribution method in the condition of lacking predefined molecular libraries.In this strategy,the molecular building diagram comprises two steps.First,the ring structure is configured by determining the number of rings.Different from the length of chain adopted in the traditional stochastic reconstruction method,in the second step,number of structural descriptors(SDs)for binding site and chain were determined sequentially for the configuration of binding site and saturated acyclic hydrocarbon chain.These structural descriptors for binding site and chain were selected from group contribution methods.To count the number of partial overlapping sections between structural descriptors for chain,two supplementary structural descriptors were created.All possible saturated structures of hydrocarbon chains can be represented by structural descriptors at the scale of property estimation.This strategy separates the building of a predefined molecule library from the stochastic reconstruction process.The exact structures of pseudo molecules represented by structural descriptors in this work can be determined with sufficient chemical knowledge.Fifty naphtha samples are tested independently to demonstrate the performance of the proposed strategy and the results show that the estimated properties were close enough to the experimental values.This strategy will benefit the molecular management of petrochemical industries and therefore improve economic and environmental efficiencies.

Adsorption Properties and Quantum Molecular Descriptors of the Folic Acid Drug Adsorbed onto Zigzag and Armchair Single Walled Carbon Nanotubes:DFT Simulations

The adsorption behavior of folic acid onto（5,0） zigzag and（5,5） armchair carbon nanotube（SWCNT） has been investigated using B3 LYP density functional at the 6-31G＊ level. The adsorption energies,molecular orbital analysis and structural changes at the adsorption site are indicative of covalent adsorption on the zigzag SWCNT surface,while the adsorption is physical on the armchair SWCNT surface. The density of states（DOS） Plot and the quantum molecular descriptors（QMD） are witness to the significant changes in the electronic properties of SWCNT systems after the attachment of adsorbed species to the tube surface. According to the calculated results,the single-walled carbon nanotubes are expected to be a potential efficient adsorbent for the adsorption of folic acid drug and also can be used as a suitable drug delivery vehicle within biological systems.

Geometric structures,electronic characteristics,stabilities,catalytic activities,and descriptors of graphene-based single-atom catalysts

Single-atom catalysts(SACs)have been a research hotspot due to their high catalytic activity,selectivity,and atomic utilization rates.However,the theoretical research of SACs is relatively fragmented,which restricts further understanding of SAC stability and activity.To address this issue,we report our analysis of the geometric structures,electronic characteristics,stabilities,catalytic activities,and descriptors of 132 graphene-based singleatom catalysts(M/GS)obtained from density functional theory calculations.Based on the calculated formation and binding energies,a stability map of M/GS was established to guide catalyst synthesis.The effects of metal atoms and support on the charge of metal atoms are discussed.The catalytic activities of M/GS in both nitrogen and oxygen reduction reactions are predicted based on the calculated magnetic moment and the adsorption energy.Combined with the electronegativity and d-band center,a two-dimensional descriptor is proposed to predict the O adsorption energy on M/GS.More importantly,this theoretical study provides predictive guidance for the preparation and rational design of highly stable and active single-atom catalysts using nitrogen doping on graphene.

Shape matching and retrieval based on multiple feature descriptors

A lot of 3D shape descriptors for 3D shape retrieval have been presented so far. This paper proposes a new mechanism, which employs several existing global and local 3D shape descriptors as input. With the sparse theory, some descriptors which play the most important role in measuring similarity between query model and the model in the dataset are selected automatically and an affinity matrix is constructed. Spectral clustering method can be implemented to this affinity matrix. Spectral embedding of this affinity matrix can be applied to retrieval, which integrating almost all the advantages of selected descriptors. In order to verify the performance of our approach, we perform experimental comparisons on Princeton Shape Benchmark database. Test results show that our method is a pose-oblivious, efficient and robustness method for either complete or incomplete models.

SEDS在船舶电力推进系统设计中的应用

电站是船舶电力推进系统中最重要的环节之一,借助SEDS平台,分析了不同电站配置方案对船舶电力系统的影响,为数字仿真应用于船舶电力系统设计提供了思路。

Recognition of 3-D Aircrafts by Fourier Descriptors with Fast and Efficient Library Search

Fourier descriptors are used as features for 3-D aircraft classification and pose determination from a 2-D image recorded at an arbitrary viewing angle. By the feature ranking of Fourier descriptors, a classification procedure based on the fast nearest neighbour rule is proposed to save the matching time of an unknown aircraft with a partial library search. The testing results of some typical examples indicate this method is generally applicable and efficient in 3-D aircraft recognition.

Prediction of liquid chromatography retention factors for α-branched phenylsulfonyl acetates using quantum chemical descriptors

The logarithms of retention factors normalized to a hypothetical pure water eluent(log k w) were determined on a reversed phase high performance liquid chromatography(RP HPLC) column (Li Chrosorb RP 18 column) for 20 new α\|branched phenylsulfonyl acetates. The atomic charge method was applied to develop quantitative structure retention relationships(QSRRs). Among the available geometric and electronic descriptors, surface area (S), ovality (O), and the charge of carboxyl group(Q OC ) are significant. In the model, the contribution of surface area (S) is the greatest. The molecular mechanism of retention was demonstrated through the model. With the correlation coefficient ( r 2 adj , adjusted for degrees of freedom) of 0.964, the standard error of 0.164 and the F value of 170.39, the model has good predictive capacity.

DFT-Based Prediction of Bioconcentration Factors of Polychlorinated Biphenyls in Fish Species Using Molecular Descriptors

Experimental determination of BCFs is expensive and demanding if performed correctly. Because of this, measuring the BCFs of many thousands of chemical substances that are potential regulatory interest is simply not possible. Hence, prediction of BCFs of the PCBs based on QSAR were made time to time to increase the probability of success and reduce the time and cost in exploring the toxicological and ecological characteristics of molecules. DFT methods are, in general, capable of generating a variety of isolated molecular descriptors as well as local reactivity descriptors quite accurately. In this work, prediction of BCFs of the fifty seven PCBs based on quantum chemical descriptors derived from DFT method using the B88-PW91 GGA energy function with the DZVP basis set have been made. The study concluded that dipole moment and ionization potential are reliable descriptors for correlation of bioconcentration factors of polychlorinated biphenyls with their electronic structures. The resulted QSAR model (r2 = 0.9139, ?= 0.8986, k = 2, SE = 0.2668) can be useful for predicting the BCFs of compounds prior to their synthesis.

Genetic Divergence in Mango and Obtaining Minimum Efficient Descriptors

Mangifera indica (mango) is a typically tropical fruit with considerable economic value. Brazil features a wide variety of cultivars of this fruit, most of which are known under several different names. Indeed, the nomenclature of mango varieties is still quite confusing. Up to now there has been no well-defined scientific principle to differentiate them. The objective of the present work is to compare the different clustering methods in assessing genetic divergence among mango accessions, as well as identify the minimum efficient descriptors for that crop. A total of 20 mango accessions in Cáceres, Mato Grosso state, Brazil were evaluated. When building dissimilarity matrices, the descriptors were divided according to the following groups: leaf, flower/inflorescence, fruit, seed and growth habit/ripening period. With these divisions, combinations were performed among the groups of descriptors. The similarity index was used to obtain the dissimilarity matrices. Later, the accessions were clustered using the methods of Tocher, Ward and UPGMA. The study observed that it was possible to reduce the number of descriptors from 64 to 35, and that the clustering methods were compatible with the study of the genetic diversity of mango.