公共卫生事件下公安机关网络舆论引导问题探析——基于SWOT分析法的运用

新冠肺炎疫情是新媒体大数据时代遇到的第一次重大公共卫生事件,其衍生出来的网络舆论影响着政治、经济、民生多方面的发展。公安机关作为一支维护社会稳定的队伍,在突发事件舆情传播与引导方面起到重要作用。公共卫生事件下的网络舆论具有持续性、大规模性以及多类型舆论并发等特点,本文基于SWOT分析法,找出公安机关网络舆论引导的内外部优劣势和外部机遇与威胁,提出增强意识、提升运用新媒体能力以及引导舆论从“人”入手等对策,从而为提高公安机关在网络舆论引导上的工作效率提出建议。     

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。     

Neural Style Transfer for image within images and conditional GANs for destylization

In this paper, the feature representation of an image by CNN is used to hide the secret image into the cover image. The style of the cover image hides the content of the secret image and produce a stego image using Neural Style Transfer (NST) algorithm, which resembles the cover image and also contains the semantic content of secret image. The main technical contributions are to hide the content of the secret image in the in-between hidden layered style features of the cover image, which is the first of its kind in the present state-of-art-technique. Also, to recover the secret image from the stego image, destylization is done with the help of conditional generative adversarial networks (GANs) using Residual in Residual Dense Blocks (RRDBs). Further, stego images from different layer combinations of content and style features are obtained and evaluated. Evaluation is based on the visual similarity and quality loss between the cover-stego pair and the secret-reconstructed secret pair of images. From the experiments, it has been observed that the proposed algorithm has 43.95 dB Peak Signal-to-Noise Ratio (PSNR)), .995 Structural Similarity Index (SSIM), and .993 Visual Information Fidelity (VIF) for the ImageNet dataset. The proposed algorithm is found to be more robust against StegExpose than the traditional methods.     

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.     

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。     

使能未来工厂的5G能力综述

5G系统将移动通信服务从移动电话、移动宽带和大规模机器通信扩展到新的应用领域，即所谓对通信服务有特殊要求的垂直领域。对使能未来工厂的5G能力进行了全面的分析总结，包括弹性网络架构、灵活频谱、超可靠低时延通信、时间敏感网络、安全和定位，而弹性网络架构又包括对网络切片、非公共网络、5G局域网和边缘计算的支持。希望从广度到深度，对相关的理论及技术应用做透彻、全面的梳理，对其挑战做清晰的总结，从而为相关研究和工程技术人员提供借鉴。     

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。     

农村综合能源系统多层协同优化运行方法

农村综合能源系统通过多种能源的协同互补,在满足农村用户多元化用能需求的同时,能有效提升能源利用效率和用能经济性。首先,在考虑适应农村典型场景的基础上,提出了一种三层协同自律的农村综合能源分层协同运行优化框架。然后,基于农村综合能源系统典型设备,建立了三层农村综合能源系统源-储-荷联合优化调度模型以及相应的优化调度流程。调度模型中冬季通过对沼气发电机组的余热回收与空气源热泵协同对用户供热;夏季对沼气发电机组余热进行回收,并通过溴化锂制冷机与空气源热泵联合对农村用户供冷。最后,对农村综合能源系统多层协同优化方法进行了算例分析,结果表明该优化方法提高了农村居民用能的经济性,验证了所提方法的有效性。