Synthesis of Three-Dimensional Hierarchical Flower-Like Mg–Al Layered Double Hydroxides with Excellent Adsorption Performance for Organic Anionic Dyes

In this work,a facile and effective strategy to prepare three-dimensional(3D)hierarchical flower-like Mg–Al layered double hydroxides(3D-LDH)was developed via a one-step double-drop coprecipitation method usingγ-Al 2O 3particles as a template.The characterization and experimental results showed that the calcined product,3D-LDO,features a large specific surface area of 204.2 m^(2)/g,abundant active sites,and excellent adsorption performance for Congo red(CR),methyl orange(MO),and methyl blue(MB).The maximum adsorption capacities of 3D-LDO for CR,MO,and MB were 1428.6,476.2,and 1666.7 mg/g,respectively;such performance is superior to that of most reported adsorbents.The adsorption mechanism of organic anionic dyes by 3D-LDO was extensively investigated and attributed to surface adsorption,the memory effect of 3D-LDO,and the unique 3D hierarchical flower-like structure of the adsorbent.Recycling performance tests revealed that3D-LDO has satisfactory reusability for the three organic anionic dyes.

Asymmetric image encryption algorithm based on a new three-dimensional improved logistic chaotic map

Based on some analyses of existing chaotic image encryption frameworks and a new designed three-dimensional improved logistic chaotic map(3D-ILM),an asymmetric image encryption algorithm using public-key Rivest–Shamir–Adleman(RSA)is presented in this paper.In the first stage,a new 3D-ILM is proposed to enhance the chaotic behavior considering analysis of time sequence,Lyapunov exponent,and Shannon entropy.In the second stage,combined with the public key RSA algorithm,a new key acquisition mathematical model(MKA)is constructed to obtain the initial keys for the 3D-ILM.Consequently,the key stream can be produced depending on the plain image for a higher security.Moreover,a novel process model(NPM)for the input of the 3D-ILM is built,which is built to improve the distribution uniformity of the chaotic sequence.In the third stage,to encrypt the plain image,a pre-process by exclusive OR(XOR)operation with a random matrix is applied.Then,the pre-processed image is performed by a permutation for rows,a downward modulo function for adjacent pixels,a permutation for columns,a forward direction XOR addition-modulo diffusion,and a backward direction XOR addition-modulo diffusion to achieve the final cipher image.Moreover,experiments show that the the proposed algorithm has a better performance.Especially,the number of pixels change rate(NPCR)is close to ideal case 99.6094%,with the unified average changing intensity(UACI)close to 33.4634%,and the information entropy(IE)close to 8.

Using"Three-dimensional Space Resources"for Fenlong Technology to Improve Grain Econoloy and Expand Human Living Spaces

Fenlong Technology has been applied to increase yield by 20%-50%,improve quality by 5%,and retain water by 100%in 40 kinds of crop cultivated land and saline-alkali land in 26 provinces of China.This paper clarified for the first time the scientific theory system of Fenlong Technology using three-dimensional space resources"Fenlong Agricultural Nature Theory"and the development of the relative"limits"of agricultural growth,which provides a huge power support and natural force for expanding human living spaces.Through inventing and creating a scientific and technological system of farming tools,farming machinery,farming modes,and magic weapons for cultivation,Fenlong Technology can increase grain,promote ecological development,and greatly expand the living spaces of the Chinese nation and achieve sustainable development.Using Fenlong Technology,China has expanded from the current single"cultivated land agriculture"to the"big pattern agriculture"of Fenlong"cultivated land+saline land+degraded grassland+marginal land+desertified land+river water",flexibly used 147 million ha of"three-dimensional space resources"of land,and the newly increased food,meat,and fish can feed 300 million to 400 million people,increased the water storage by 100 billion m^(3),and reduced the collection of groundwater by 20 million to 60 billion m^(3).

A Method for Hierarchical Subband HDTV Splitting

In this paper, an investigation is made on compatibility of the video formats TV (625/50/2:1/4:3), EDTV (625/50/1:1/16:9), HDTVint (1250/50/2:1/16:9) and HDTVpro(1250/50/2:1/16:9) in three-dimensional subband coding. A hierarchical method is proposed leading to a more reasonable joint solution for the issues of digital transmission evolution and interlace-to-progressive scanning conversion ill the frame work of bit rate compression. Conventional HDTVint with the diamond shaped spectrum is proposed to be replaced by a kind of 'switching'HDTVin signal which consists of three components and motion detection bits (MDB). The first component and the MDB represent TV. The first plus the second component and the MDB represent EDTV.HDTVpro is splitted into switching HDTVint and extra component. The switching threshold and the length of temporal filter banks are discussed. Rearranging the pixels in subbands is recommended. Based on the proposed method, the transmission system can evolve through four steps: TV, EDTV, HDTVint and HDTVpro Results of bit rate compression are also presented. TV, EDTV, HDTVint and HDTVpro are compressed to approximately 40, 80, 128 and 256 Mbit/s respectively. Interlace scanning has drawbacks such as line flicker and line crawling as the eye follows the line structure in the picture. Progressive version switching TV and HDTVint can be reconstructed using one frame memory without the problems of handling temporal-vertical diamond shaped spectra of conventional TV and HDTVint based on a one-frame memory algorithm in the receiver.

Incremental Linear Discriminant Analysis Dimensionality Reduction and 3D Dynamic Hierarchical Clustering WSNs

Optimizing the sensor energy is one of the most important concern in Three-Dimensional(3D)Wireless Sensor Networks(WSNs).An improved dynamic hierarchical clustering has been used in previous works that computes optimum clusters count and thus,the total consumption of energy is optimal.However,the computational complexity will be increased due to data dimension,and this leads to increase in delay in network data transmission and reception.For solving the above-mentioned issues,an efficient dimensionality reduction model based on Incremental Linear Discriminant Analysis(ILDA)is proposed for 3D hierarchical clustering WSNs.The major objective of the proposed work is to design an efficient dimensionality reduction and energy efficient clustering algorithm in 3D hierarchical clustering WSNs.This ILDA approach consists of four major steps such as data dimension reduction,distance similarity index introduction,double cluster head technique and node dormancy approach.This protocol differs from normal hierarchical routing protocols in formulating the Cluster Head(CH)selection technique.According to node’s position and residual energy,optimal cluster-head function is generated,and every CH is elected by this formulation.For a 3D spherical structure,under the same network condition,the performance of the proposed ILDA with Improved Dynamic Hierarchical Clustering(IDHC)is compared with Distributed Energy-Efficient Clustering(DEEC),Hybrid Energy Efficient Distributed(HEED)and Stable Election Protocol(SEP)techniques.It is observed that the proposed ILDA based IDHC approach provides better results with respect to Throughput,network residual energy,network lifetime and first node death round.

基于改进FAHP-TOPSIS的船舶产业链韧性测度研究

针对船舶产业链韧性测度的规范性研究较少,文章基于船舶产业链的特点,结合其他领域的相关研究,从恢复力、适应力、反应力以及创新力四个维度构建了船舶产业链韧性指标体系,运用模糊层次分析法确定各指标的权重以及改进的TOPSIS相结合的创新性方法对船舶产业链韧性进行测度分析,研究表明重点可从恢复力角度改进产业链结构,同时可以提升产业创新力和适应力,调整和优化产业链策略,研究可为船舶产业链的安全发展提供参考。

突发公共卫生事件下救援物资配送方案研究

在突发公共卫生事件封控情况下,大规模应急救援物资的配送需要兼顾效率、成本及安全性,在有限的救援投入下获取最大化资源利用和最小化配送成本,同时避免人员的交叉感染。为此,提出了基于两层配送网络的应急物资配送方案,并提出改进粒子群优化算法(Improved Particle Swarm Optimization Algorithm,IPSOA)对配送路径进行优化。首先,根据行政区划分以及物资需求点的空间分布、各需求点的居民人数和需求量,采用层次聚类算法建立由“物资储备中心-物资集散中心”和“物资集散中心-物资需求点”构成的两层配送网络,每层配送网络都由多配送中心和多需求点组成,该物资配送属于多配送车辆的多中心车辆路径规划问题(Multi-Depot Vehicle Routing Problem,MDVRP)。其次,为了获取合理高效的配送路径,以配送成本最小为目标,构建基于多约束的物资配送优化模型,并提出基于人工鱼群算法(Artificial Fish Swarm Algorithm,AFSA)的粒子群优化(AFSA-PSO)算法对两层配送网络进行求解。最后,以某市9个行政区在疫情封控期间的数据为例验证两层配送网络和AFSA-PSO算法的有效性。结果表明:构建的两层配送网络和AFSA-PSO算法能够对多车辆MDVRP问题进行有效求解,科学规划配送路径;算法对比发现,AFSA-PSO能够避免模型过早收敛,且能够获取比遗传算法和粒子群优化算法更少的车辆数和更短的配送路径,有效地降低配送成本,提高经济效益。

IHMP:an improved hierarchical motion planner for mobile manipulator in static environment

Mobile manipulators are used in a variety of fields because of their flexibility and maneuverability.The path planning capability of the mobile manipulator is one of the important indicators to evaluate the performance of the manipulator,but it is greatly challenged in the face of maps with narrow channel.To address the problem,an improved hierarchical motion planner(IHMP)is proposed,which consists of a two-dimensional(2D)path planner for the mobile base,and a three-dimensional(3D)trajectory planner for the on-board manipulator.Firstly,a hybrid sampling strategy is proposed,which can reduce invalid nodes of the generated probabilistic roadmap.Bridge test is used to locate the narrow channel areas,and a Gaussian sampler is deployed in these areas and the boundaries.Meanwhile,a random sampler is deployed in the rest areas.Trajectory planner for on-board manipulator is to generate a collision-free and safe trajectory in the narrow channel with collaboration of the 2D path planner.The experimental results show that IHMP is effective for mobile manipulator motion planning in complex static environments,especially in narrow channel.

改进下垂控制下的中压直流配电系统双时间尺度分层调控方法

针对中压直流配电系统,在负荷激增、可再生能源出力突变等特殊工况下,传统优化调度方案与协调控制策略存在系统运行经济性有待提升、直流母线电压易越限的问题。为此,提出一种基于改进下垂控制的中压直流配电系统双时间尺度分层调控方法。首先,构建一种具备直流故障穿越能力的3端混合型模块化多电平换流器(modular multilevel converter,MMC)环状±10 kV中压直流配电系统,该系统含电动汽车充电站、储能系统、分布式光伏与风电等灵活性资源。其次,制定各单元协调控制策略,并采用tan函数改进传统下垂控制,以提高系统应对大幅功率波动的能力。然后,基于改进控制策略提出一种双时间尺度分层优化调控方法:在长时间尺度的系统调度层,以运行总成本最小为优化目标,确定各换流器参考功率;在短时间尺度的换流器间协调控制层,改进下垂曲线,并优化控制系数,以兼顾系统运行经济性与电能质量。最后,以典型算例验证该文所提优化调度方案及协调控制策略的有效性:通过灵活调度多种柔性资源,系统运行总成本可降低约11%;在某数据中心负荷激增100%的工况下,各直流母线电压波动仍能维持在±3%UN(额定电压)的允许范围内。

基于RRT*算法和DWA算法的分层结构路径规划策略

为优化复杂动态环境下路径规划问题,提高路径搜索效率,缩短路径规划时间,提出一种基于改进RRT*算法和DWA算法的分层结构路径规划策略;该路径规划分层结构由全局路径规划层和局部路径规划层组成,全局路径规划层根据已知静态障碍物信息利用改进RRT*算法进行全局路径规划;当路径中出现未知动态障碍物时,根据规划策略将启用局部路径规划层,基于获取的动态障碍物信息,利用DWA算法进行局部路径规划;最终通过全局与局部路径规划策略相结合得到最终的可行路径;仿真实验结果表明:文章提出的分层结构路径规划策略在复杂动态环境中可以高效地完成路径规划任务。

基于改进模糊层次分析法的高速列车轮轨等效锥度优化方案评价研究

【目的】针对当前缺乏高速列车轮轨等效锥度优化方案综合评价体系的问题,提出基于改进模糊层次分析法的综合评价方法。【方法】结合影响等效锥度选取的主要动力学因素,选取了14个评价指标构建指标分解模型,采用改进的三标度层次分析法确定权重。在动力学软件Simpack中建立3种等效锥度的模型,计算底层指标值并进行无量纲化处理,确定模糊评价隶属度矩阵,并构建模糊理论系统评价模型,得出3种方案的综合评价结果。【结果】3种等效锥度方案的得分分别为:方案M1为26.2%,方案M2为17.9%,方案M3为16.2%,方案M1为最优选择。通过对两组具有显著差异的等效锥度方案进行动力学仿真计算,发现结果与综合评价体系的结论相一致,验证了评价方法的可靠性。【结论】可有效评价高速列车轮轨等效锥度方案,能够为高速列车的等效锥度方案优选提供科学依据。

基于改进层次斜率熵(IHSloE)的信号低频和高频故障特征提取方法

采用传统的基于粗粒化处理的多尺度特征提取方法,无法提取故障信号中的高频部分的故障信息,导致其提取到的故障特征难以准确地表征滚动轴承的故障状态和动态特性,无法保证故障诊断的可靠性和准确性。针对该缺陷,提出了一种基于改进层次斜率熵(IHSloE)和随机森林(RF)的滚动轴承故障诊断方法。首先,利用改进层次化处理代替粗粒化处理,实现了信号的多尺度分析目的,基于斜率熵,提出了改进层次斜率熵的非线性动力学指标;随后,利用IHSloE方法提取了滚动轴承振动信号的故障特征,建立了表征滚动轴承故障特性的故障特征;最后,基于RF模型建立了多故障分类器,并将故障特征输入至RF分类器进行了训练和测试,以实现滚动轴承的故障识别目的;利用滚动轴承数据集进行了实验,并将其与其他的故障特征提取指标进行了对比。研究结果表明:IHSloE方法采用改进的层次化处理,能够快速有效地提取出振动信号中的高频故障特征,诊断准确率达到了99%,而特征提取时间仅为149.35 s;相较于采用粗粒化处理和层次处理的特征提取方法,其准确率至少提高了2%和1%,证明该方法适用于滚动轴承的故障诊断。

基于改进可拓云模型的装配式建筑施工安全风险评价方法

为保障装配式建筑施工安全,考虑到施工安全指标因素的模糊性与随机性,运用组合赋权-改进可拓云模型对施工安全风险进行评价。首先,从“三度空间”视角下,在物理、社会、信息三个层面构建了评价指标体系;其次,运用改进的层次分析法(AHP)和熵权法(EW)确定主客观权重,基于距离函数确定综合权重,根据云理论和可拓学理论提出一种云熵确定方法,对传统可拓云模型进行改进后构建评价模型;最后,将该模型运用到工程实例中,与其他模型进行对比。结果表明:该施工项目评价等级为很安全,且具有很高的可信度;验证了该模型的可靠性和可行性,为装配式建筑施工安全风险评价提供了一种更加科学、准确的评价方法。

基于改进的层次分析法的工程质量风险评估模型研究

为了探索改进的层次分析法在工程质量风险评估中的应用,提出了一种基于模糊数学和灰色关联分析的量化和排序方法,克服了传统方法的主观性和不确定性。以高速公路工程为例,建立了一个包含四个准则层和四个方案层的评估层次结构,综合考虑了设计、施工、材料和环境等多个影响因素。通过与传统的层次分析法进行对比分析,验证了改进的层次分析法的有效性,发现两种方法的评估结果存在一定的差异,说明改进的层次分析法能够更好地反映工程质量风险的实际情况。

基于改进共识算法的虚拟电厂主从多链交易匹配机制

在未来新型电力系统中,虚拟电厂(virtual power plant,VPP)内部多主体的可信交易和信息安全将更加复杂和具有挑战性。而区块链技术的信息安全、分布决策、智能合约及防篡改等特征,为VPP多元主体可信交易提供新思路。文中聚焦VPP内部多聚合商形成的利益最大化及可信交易匹配效率问题,首先,依据交易主体需求差异,建立区块链技术与多智能体系统融合的一主多从分层互动控制架构;其次,设计一种面向多聚合商对等交易需求下的可信交易匹配机制,引入非合作博弈模型,保证了多聚合商主体的利益;然后,基于区块链的分布式粒子群优化算法提出了改进的委托权威证明机制(delegated proof-of-authority,DPoA)共识算法,提高交易的安全性;最后,通过算例分析验证文中所提策略的合理性和可行性,该策略能有效增强多主体交易的匹配效率和安全性。

基于改进差异算子和Gabor_ELM的SAR图像变化检测算法

针对差异图构造单一、抗噪性差及纹理特征不足等问题,提出一种基于改进差异算子和Gabor_ELM的SAR图像变化检测算法。该方法结合改进对数比的高效性和邻域比的鲁棒性,提出一种改进差异算子,再通过对差异图提取Gabor纹理信息结合层次模糊聚类和极限学习机(ELM)来实现Gabor_ELM变化检测算法。实验表明,与FLICM、MRFFCM、ELM及PCANet算法相比,提出的算法能较好地保留变化细节信息且具有较高检测精度。实验数据正确率达到98%以上,Ottawa数据的Kappa系数达到0.94。

基于k-sums分段聚类的动态组合学习光伏短期功率预测

目前单一模型预测精度存在难以随着功率波动保持最优的问题,为提高并网系统运行的稳定性和电网的节能调度,文中提出了一种基于k-sums分层聚类的动态学习组合光伏短期功率预测方法。利用k-sums算法经过分段聚类,将天气类型分为晴天A 1、多云A 2、阴雨天B。通过TCN(Temporal Convolutional Network)提取数据的时序特征,并结合GRU(Gate Recurrent Unit)建立融合提取时序特征模块的改进GRU结构,以达到对时序特征敏感的效果。将改进GRU结构与SVM(Support Vector Machine)动态组合,使用Elastic Net算法输出最佳权重值叠加得到最终预测值。文中采用江苏某地区的光伏发电功率数据及对应的气象数据对所提方法进行验证,结果表明动态组合学习模型的MAE(Mean Absolute Error)为1.888,RMSE(Root Mean Squared Error)为2.403。

考虑不同约束区间的风电场布局分级优化

为了提高风电场布局优化中尾流模型预测精度,以便能够较好预测风机安装台数和最大限度降低度电成本,本文基于改进三维尾流模型,考虑风力机处于不同约束区间,采用分级优化策略对2 km×2 km风电场进行精确布局优化。首先,利用网格法对风电场进行第一阶优化;其次,考虑不同约束区间,采用坐标法对第一级优化结果进行第二阶优化。研究表明:与Jensen尾流模型相比,改进后的三维尾流模型可以更合理地优化风电场布局;考虑收敛速度及度电成本,当约束区域为l_(imit)=150、200 m时,第二阶算法迭代速度较快,优化后其度电成本为0.8498/W,相比第一阶优化结果,降低了3.33%。

Solid-conversion synthesis of three-dimensionally ordered mesoporous ZSM-5 catalysts for the methanol-to-propylene reaction

A facile synthesis of hierarchical ZSM-5 with the three-dimensionally ordered mesoporosity(3DOm ZSM-5)was achieved by solid conversion(SC)of SiO_(2)colloidal crystals to high-crystalline ZSM-5.The products of 3DZ5_S/C and 3DZ5_S,which were severally transformed from the carbon-padded SiO_(2)colloidal crystals and the initial SiO_(2)colloidal crystals,exhibited not only a similar ordered structure and acidity but also higher crystallinity and more balanced meso-/micropore combination in comparison with 3DZ5_C obtained by the conventional confined space crystallization approach.All three synthesized 3DZ5 catalysts showed improved methanol-to-propylene performance than the commercially microporous ZSM-5(CZ5),embodied in five times longer lifetime,higher propylene selectivity and S_(propylene)/S_(ethylene) ratio(P/E),and superior coke toleration with lower formation rate of coke(R_(coke)).Moreover,the 3DZ5_S catalyst in situ converted from SiO_(2)colloidal crystals presented the highest selectivities of propylene(42.51%)and light olefins(74.6%)among all three 3DZ5 catalysts.The high efficiency in synthesis and in situ utilization of SiO_(2)colloidal crystals demonstrate the proposed SC strategy to be more efficiently and eco-friendly for the high-yield production of not only 3DOm ZSM-5 but also other types of hierarchical zeolites.

改良早期预警评分系统联合层级链式护理对重症肺炎患儿的影响

目的 探讨基于改良早期预警评分(MEWS)系统的层级链式护理对重症肺炎患儿临床症状改善、肺功能、并发症的影响。方法 选择医院2021年1月—2022年12月收治的重症肺炎患儿128例为研究对象,按照组间基本特征具有可比性的原则分为对照组和观察组,各64例。对照组采用常规护理干预模式,观察组在常规护理基础上采用基于MEWS系统的层级链式护理干预。比较两组患儿的临床症状改善情况、肺功能指标[呼吸频率(RR)、用力肺活量(FVC)、达峰容积比(vPTEF/vE)]、并发症发生率、依从率、家属焦虑情绪[汉密尔顿焦虑量表(HAMA)、Zung焦虑自评量表(SAS)]评分。结果 护理干预后,观察组患儿发热、咳嗽、气促、肺啰音消失时间均短于对照组,差异有统计学意义(P<0.05)。护理干预1周后,观察组患儿RR低于对照组,FVC、vPTEF/vE高于对照组,差异均有统计学意义(P<0.05);观察组患儿并发症发生率低于对照组,差异有统计学意义(P<0.05);观察组患儿依从性高于对照组,差异有统计学意义(P<0.05);观察组患儿家属HAMA、SAS评分低于对照组,差异有统计学意义(P<0.05)。结论 基于MEWS系统的层级链式护理可有效改善重症肺炎患儿的临床症状和肺功能,降低并发症的发生率,提高患儿的依从率,减轻患儿家属的焦虑情绪,有助于促进患儿康复。