A 6-DOF humanoid wall-climbing robot with flexible adsorption feet based on negative pressure suction

A wide range of dangerous and special tasks have witnessed the applications of wall-climbing robots, but they still cannot adapt well torough or sloping walls. This paper proposes a 6-DOF (degree of freedom) humanoid wall-climbing robot (HWCR) based on the principle of negative pressure suction. HWCR has the advantages of flexible adsorption feet, strong adaptability, strong anti-subversion performance, and high friction to the wall. We deduce mechanics formulas and carry out a parametric design of the foot structure so that it can meet the requirement of robot wall climbing. We use Fluent to analyze the flow field of the adsorption foot and determine the motor speed that can provide a reliable adsorption force. Using the D-H matrix to plan gait, we also design a compound cycloid-based foot trajectory to reduce the impact between the HWCR and the wall. Experiments on the uneven wall and sloping wall show that the vehicle can walk with an ideal gait, and the resistance value of the servo on each joint is much lower than the critical value, which ensures the smooth movement of the HWCR.     

基于改进灰狼优化算法的服务功能链映射算法

随着工业互联网、车联网、元宇宙等新型互联网应用的兴起，网络的低时延、可靠性、安全性、确定性等方面的需求正面临严峻挑战。采用网络功能虚拟化技术在虚拟网络部署过程中，存在服务功能链映射效率低与部署资源开销大等问题，联合考虑节点激活成本、实例化开销，以最小化平均部署网络成本为优化目标建立了整数线性规划模型，提出基于改进灰狼优化算法的服务功能链映射（improved grey wolf optimization based service function chain mapping，IMGWO-SFCM）算法。该算法在标准灰狼优化算法基础上添加了基于无环K最短路径（K shortest path，KSP）问题算法的映射方案搜索、映射方案编码以及基于反向学习与非线性收敛改进三大策略，较好地平衡了其全局搜索及局部搜索能力，实现服务功能链映射方案的快速确定。仿真结果显示，该算法在保证更高的服务功能链请求接受率下，相较于对比算法降低了11.86%的平均部署网络成本。     

An optimal configuration for hybrid SOFC,gas turbine,and Proton Exchange Membrane Electrolyzer using a developed Aquila Optimizer

In this research, a technical, economic and environmental analysis has been proposed to a Hybrid Solid Oxide Fuel Cell (SOFC) system-based hybrid system including biomass, gas turbine, and Proton Exchange Membrane Electrolyzer. A multi-objective optimization technique has been utilized to improve the overall product cost and the exergy effectiveness based on a developed version of Aquila Optimizer (DAO). The main idea of using the developed version is to improve the accuracy and the precision of the original Aquila optimizer. The system is then authenticated in terms of energy/exergy effectiveness, and energy-economic efficiency. The achievements indicate that employing the optimization algorithm for different configurations provided satisfying results for the system.     

Frequency response data-based peak filter design applied to MIMO large-scale high-precision scan stage

A large-scale high-precision scan stage is important equipment in the industrial productions of micro-fabrication such as flat panel display (FPD) lithography systems. Designing controllers for multi-input multi-output (MIMO) systems is time-consuming and needs experience because of the interaction between each axis and many controller tuning parameters. The aim of this study is to develop a peak filter design method based on frequency response data to reduce repetitive disturbance. This data-based approach does not use the model and only uses the frequency response data of the controlled system and the disturbance spectrum calculated from the scanning error data (Contribution 1). The peak filter is designed by convex optimization and satisfies robust stability conditions for six-degree-of-freedom systems (Contribution 2). The control performance of the designed peak filter is experimentally demonstrated with an industrial MIMO large-scale high-precision scan stage in reducing the scanning error of the main stroke of the translation along the $x$-axis (Contribution 3).     

Automated prediction system of household energy consumption in cities using web crawler and optimized artificial intelligence

The supply of electrical energy is critical to convenient and comfortable living. However, people consume a large amount of energy, contributing to an energy crisis and global warming, and damaging some ecological cycles. Residential electricity consumption has greater elasticity than industrial and business consumption; it therefore has high energy-saving potential. This work establishes an automated platform, which provides information about residential electricity consumption in each city in Taiwan. Machine learning was used to forecast future residential electricity demand. A nature-inspired optimization method was applied to enhance the accuracy of the best machine learner, yielding an even better hybrid ensemble model. Performance measures indicate that the resulting model is accurate and provides effective information for reference. An automatic web-based system based on the model was combined with a web crawler and scheduled to run automatically to provide information on monthly residential electricity consumption in each county and city. By providing energy consumption information across the country, power providers and government can discuss policy and set different goals for energy use. The results of this study can facilitate the early implementation of energy-saving and carbon emission-reducing in cities and aid utility companies in establishing energy conservation guidelines.     

红心火龙果发酵液喷雾干燥工艺优化及红心火龙果籽油的研究

以红心火龙果发酵液作为研究对象,通过优化喷雾干燥工艺制备粉剂,最佳工艺条件为:20%麦芽糊精,进液量:10mL/min,进口温度为120℃,出口温度为65℃;得到的粉剂为紫红色粉末,益生菌含量达到108cfu/g以上,口感酸甜。将发酵后的火龙果籽进行提取,得到的火龙果籽油含有丰富的十六酸、亚油酸和油酸。     

具有保护肠上皮细胞HT-29免受大肠杆菌和H2O2损伤潜力的植物乳杆菌的筛选

益生菌可在肠道定植从而发挥抗炎或抗氧化活性，有利于宿主肠道健康。本实验研究了从新疆传统发酵乳制品中分离得到的8?株植物乳杆菌对大肠杆菌侵袭和过氧化氢刺激肠上皮细胞HT-29的保护作用。结果表明：在8?株植物乳杆菌中，植物乳杆菌35具有最高的黏附能力。植物乳杆菌35可通过取代、竞争、排阻的方式抑制大肠杆菌对HT-29细胞的黏附，抑制率分别为42.60%、59.17%、60.19%。植物乳杆菌35及其多糖可抑制大肠杆菌刺激HT-29细胞产生白细胞介素-8；同时保护HT-29细胞免受过氧化氢的损伤，增加超氧化物歧化酶、谷胱甘肽过氧化物酶活力水平并降低丙二醛含量。结论：植物乳杆菌35及其粗胞外多糖具有抑制大肠杆菌O157诱导的炎症性肠病的潜力。     

Optimal design and operation of integrated microgrids under intermittent renewable energy sources coupled with green hydrogen and demand scenarios

Renewable energy integration into existing or new energy hubs together with Green technologies such as Power to Gas and Green Hydrogen has become essential because of the aim of keeping the average global temperature rise within 2 ^°C with regard to the Paris Agreement. Hence, all energy markets are expected to face substantial transitions worldwide. On the other hand, investigation of renewable energy systems integrated with green chemical conversion, and in particular combination of green hydrogen and synthetic methanation, is still a scarce subject in the literature in terms of optimal and simultaneous design and operation for integrated energy grids under weather intermittency and demand uncertainty. In fact, the integration of such promising new technologies has been studied mainly in the operational phase, without considering design and management simultaneously. Thus, in this work, a multi-period mixed-integer linear programming (MILP) model is formulated to deal with the aforementioned challenges. Under current carbon dioxide limitations dictated by the Paris Agreement, this model computes the best configuration of the renewable and non-renewable-based generators, their optimal rated powers, capacities and scheduling sequences from a large candidate pool containing thirty-nine different equipment simultaneously. Moreover, the effect of the intermittent nature of renewable resources is analyzed comprehensively under three different scenarios for a specific location. Accordingly, a practical scenario generation method is proposed in this work. It is observed that photovoltaic, oil co-generator, reciprocating ICE, micro turbine, and bio-gasifier are the equipment that is commonly chosen under the three different scenarios. Results also show that concepts such as green hydrogen and power-to-gas are currently not preferable for the investigated location. On the other hand, analysis shows that if the emission limits are getting tightened, it is expected that constructing renewable resource-based grids will be economically more feasible.     

基于重要度排序的配电自动化终端优化布局方法

针对配电自动化终端优化布局问题，提出了一种基于重要度排序的终端优化布局方法。首先以等年值综合费用为目标函数，供电可靠性和投入产出比为双重约束建立了配电自动化终端优化布局模型。然后通过分析配电自动化终端对供电可靠性提升的影响，给出各个节点的“二遥”及“三遥”终端安装重要度定义及计算公式。最后采用枚举法确定最优终端安装数量，基于节点终端安装重要度排序确定终端的最优安装位置。该方法考虑了已布局节点对剩余节点终端安装重要度的影响，能够在降低计算量的同时兼顾布局合理性。运用所提方法RBTS-BUS2系统及扩充模型进行终端优化布局并与智能优化算法的布局结果进行对比，验证了本文方法的有效性及优越性。