一类分数阶微积分的中值定理及应用

Riemann-Liouville分数阶微积分算子是一类带有一个函数的分数阶微积分算子的特殊情形，以Riemann-Liouville分数阶微积分算子的积分中值定理和微分中值定理为基础，我们得到了一类带有一个函数的分数阶微积分算子的积分中值定理和微分中值定理，并给出其在计算方面的一些应用。     

基于双时间点检测的毫米波雷达人流量监测方法

针对现有基于视频监控的人流量统计方案成本高、算法复杂且不利于个人隐私保护的局限性，利用毫米波雷达体积小、成本低、分辨率高的特点，提出了一种基于双时间点检测的人流量监测方法。该方法先获取人体目标散射点位置和多普勒频移信息来构成点云数据，然后根据多普勒频移正负来判断人体的运动方向，并筛选具有高多普勒频移值的点云数据以降低干扰点对聚类结果的影响；在双时间点对特定区域内人员数量进行统计，并根据双时间点之间所获取的点云数据聚类结果对所统计人员数据进行修正。实验结果表明，该方法能够用匿名的方式以较高的正确率统计人员进出。     

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).     

Nanofiber structured oxygen defective CoFe2O4-x catalyst for the water-gas shift reaction in waste-to-hydrogen processes

Waste-to-hydrogen processes are a way to produce hydrogen from waste and reduce the amount of landfill/incineration of wastes simultaneously through the gasification of waste. The water-gas shift (WGS) reaction is a key step in this waste-to-hydrogen process by removing the CO and producing additional H₂. A nanofiber-structured CoFe₂O₄ catalyst was synthesized by the electrospinning method, and the catalytic performance in WGS using waste-derived synthesis gas was compared with that of catalysts prepared by sol-gel, hydrothermal, and co-precipitation methods. The CoFe₂O₄ catalyst synthesized by the electrospinning method showed a clear nanofiber structure and revealed a superior redox property. This superior redox property, which has a large relation with the high oxygen storage capacity of the catalyst, induced the formation of an active phase (Co⁰ and Fe₃O₄) in CoFe₂O₄. As a result, the nanofiber structured oxygen defective CoFe₂O_4-x prepared by the electrospinning method showed the best catalytic activity in this study.     

Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing,reinforcement learning and improved QRNN

The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems.     

Research on phase shift characteristics of electromagnetic wave in plasma

The phase shift characteristics reflect the state change of electromagnetic wave in plasma sheath and can be used to reveal deeply the action mechanism between electromagnetic wave and plasma sheath. In this paper, the phase shift characteristics of electromagnetic wave propagation in plasma were investigated. Firstly, the impact factors of phase shift including electron density,collision frequency and incident frequency were discussed. Then, the plasma with different electron density distribution profiles were employed to investigate the influence on the phase shift characteristics. In a real case, the plasma sheath around the hypersonic vehicle will affect and even break down the communication. Based on the hypersonic vehicle model, we studied the electromagnetic wave phase shift under different flight altitude, speed, and attack angle. The results indicate that the phase shift is inversely proportional to the flight altitude and positively proportional to the flight speed and attack angle. Our work provides a theoretical guidance for the further research of phase shift characteristics and parameters inversion in plasma.     

Weighted power means of q-rung orthopair fuzzy information and their applications in multiattribute decision making

Weighted power means with weights and exponents serving as their parameters are generalizations of arithmetic means. Taking into account decision makers' flexibility in decision making, each attribute value is usually expressed by a $q$-rung orthopair fuzzy value ($q$-ROFV, $q\ge 1$), where the former indicates the support for membership, the latter support against membership, and the sum of their $q$th powers is bounded by one. In this paper, we propose the weighted power means of $q$-rung orthopair fuzzy values to enrich and flourish aggregations on $q$-ROFVs. First, the $q$-rung orthopair fuzzy weighted power mean operator is presented, and its boundedness is precisely characterized in terms of the power exponent. Then, the $q$-rung orthopair fuzzy ordered weighted power mean operator is introduced, and some of its fundamental properties are investigated in detail. Finally, a novel multiattribute decision making method is explored based on developed operators under the $q$-rung orthopair fuzzy environment. A numerical example is given to illustrate the feasibility and validity of the proposed approach, and it is shown that the power exponent is an index suggesting the degree of the optimism of decision makers.     

Cu/Fe3O4 catalyst for water gas shift reaction: Insight into the effect of Fe2+ and Fe3+ distribution in Fe3O4

Two precursors, namely, p-CFO-T (tetragonal) and p-CFO-C (cubic), were fabricated by a sol-gel method via citric acid and poly(vinyl alcohol) complexation, respectively. After H₂-reduction, the two were converted to Cu/Fe₃O₄ catalysts of different complexions, which are named as CFO-CA and CFO-PVA, respectively. The distribution of Fe²⁺ and Fe³⁺ in the Cu/Fe₃O₄ catalysts was studied by Raman and XPS techniques. It was disclosed that the distribution of Fe²⁺ and Fe³⁺ in Fe₃O₄ has an effect on Cu–Fe₃O₄ interaction and catalyst surface basicity. Compared to CFO-PVA, CFO-CA has a larger amount of Fe³⁺, which mostly sits at the octahedral sites, leading to stronger Cu–Fe₃O₄ interaction, and a larger amount of catalyst surface sites that are of weak basicity. As a result, the critical elementary steps of WGS reaction, viz. water dissociation, –COOH decomposition and CO₂ desorption are promoted as reflected in the lower E_a and higher catalytic activity of CFO-CA.     

考虑行走弹性影响下的车辆换挡过程分析

为研究行走弹性对工程车辆行走换挡过程的影响，建立了考虑驱动轮轮胎变形引起的车辆行走弹性影响的整车行走动力学模型，该模型适用于换挡过程分析。计算与分析了典型装载机动力换挡过程，将考虑或不考虑行走弹性时计算得到的整车加速度和瞬时冲击度的变化过程分别进行了对比，利用实车试验对单一换挡过程进行了验证；并将考虑行走弹性时升挡过程中变速箱输入输出转速变化过程、离合器滑摩功率特性的计算结果与不考虑行走弹性时换挡过程的计算结果进行了对比。研究结果表明：与不考虑行走弹性的情况相比，行走弹性变形使得换挡过程中整车加速度的变化更加平缓；换入挡离合器有两次滑摩过程，冲击度更小，换挡时间更长；离合器接合时的冲击度与其接入时间有关；滑摩功更小。     

基于EVSEWT的下击暴流时变平均风提取

下击暴流等极端风具有强烈的非平稳特性，给风场特性分析、结构响应计算带来挑战。根据经验将非平稳风分为时变平均风和零均值脉动风分别进行分析，是处理非平稳风速信号的有效方法。分析了几种常见时变均值提取方法的优缺点，在此基础上提出一种基于能量波谷寻找的经验小波变换方法，用于下击暴流时变平均风速提取，并将提取的时变平均风和脉动风用于分析某幢高层建筑顶部位移响应。对2组下击暴流的分析结果得出：与经验模态分解和离散小波变换方法相比，基于能量波谷寻找的经验小波变换方法模型提取的时变平均风更符合预期，对应的结构响应偏于安全。