Study on the Promotion Strategy of College Students’ Reading and Writing Ability Under the Micro Network Environment

Network media has become more and more involved in our daily life. It has become a part of modern life that cannot be stopped or rejected. Then, how to correctly face the changes in the Internet era is placed in front of everyone. Students need to “learn how to use the media to get their all-round development, effectively prevent the foreign information pollution, and actively guide students to a truly rational attitude for WeChat, blog and micro-blog”. It is a kind of media literacy being confronted with the network’s ability to consciously resist the harmful information, but also to benefit their own development and firmly grasp the information, so as to make full use of the convenience of network self promotion. “Screen reading” network plays an important role in college students’ life, and the fragmentation, the text features of the writing ability of college students also have a strong impact; this paper focuses on the influence of college students in the network reading and writing patterns on their writing ability and influence. From the perspective of media literacy education for college students, writing ability and reading ability provide a feasible way.

用于Mini/Micro-LED芯片缺陷检测的全局特征压缩卷积神经网络

微型发光二极管(Mini/Micro-LED)是下一代显示技术。随着Mini/Micro-LED芯片物理尺寸的微小化,制造良品率下降、集成度激增,Mini/Micro LED芯片的快速、精确检测成为工业生产的关键。然而由于芯片尺寸小、分布密集,单个目标的特征信息占比不足,且工业检测要求检测算法速度快、易部署,Mini/Micro-LED芯片缺陷检测仍面临巨大挑战。针对这些问题,设计了一种压缩注意力细节-语义互补卷积神经网络(CADSC-CNN)。在特征融合网络加入基于自注意力机制的编码器结构,更容易获取全局信息,对小目标的特征信息进行补充;同时对自注意力进行压缩操作减少模型的参数量,提高检测速率。此外,通过工业相机采集的Mini/Micro-LED数据集验证该方法的有效性。实验表明,该方法的平均精度均值(mAP)达到了95.6%,速度为100.6 fps。

Characterizing the influence of stress-induced microcracks on the laboratory strength and fracture development in brittle rocks using a finite-discrete element method-micro discrete fracture network FDEM-μDFN approach

Heterogeneity is an inherent component of rock and may be present in different forms including mineralheterogeneity, geometrical heterogeneity, weak grain boundaries and micro-defects. Microcracks areusually observed in crystalline rocks in two forms： natural and stress-induced; the amount of stressinducedmicrocracking increases with depth and in-situ stress. Laboratory results indicate that thephysical properties of rocks such as strength, deformability, P-wave velocity and permeability areinfluenced by increase in microcrack intensity. In this study, the finite-discrete element method （FDEM）is used to model microcrack heterogeneity by introducing into a model sample sets of microcracks usingthe proposed micro discrete fracture network （mDFN） approach. The characteristics of the microcracksrequired to create mDFN models are obtained through image analyses of thin sections of Lac du Bonnetgranite adopted from published literature. A suite of two-dimensional laboratory tests including uniaxial,triaxial compression and Brazilian tests is simulated and the results are compared with laboratory data.The FDEM-mDFN models indicate that micro-heterogeneity has a profound influence on both the mechanicalbehavior and resultant fracture pattern. An increase in the microcrack intensity leads to areduction in the strength of the sample and changes the character of the rock strength envelope. Spallingand axial splitting dominate the failure mode at low confinement while shear failure is the dominantfailure mode at high confinement. Numerical results from simulated compression tests show thatmicrocracking reduces the cohesive component of strength alone, and the frictional strength componentremains unaffected. Results from simulated Brazilian tests show that the tensile strength is influenced bythe presence of microcracks, with a reduction in tensile strength as microcrack intensity increases. Theimportance of microcrack heterogeneity in reproducing a bi-linear or S-shape failure envelope and itseffects on the mechanisms leading to spalling damage near an underground opening are also discussed.

Planning and design of a micro energy network for seawater desalination and regional energy interconnection

With the rapid developme nt of the economy, the continu ously in creasing populati on, and ongoing climate change, the shortage of freshwater resources has become an increasingly important global problem. Seawater desalination tech no logy can effectively alleviate the pressure on freshwater supplies and has bee n in vestigated in many countries. However, the majority of existing projects focus on the research and development of desalination equipment and the use of new tech no logies and pay less atte ntion to the operation optimizati on of the desalinati on process. The micro energy n etwork (MEN) designed in this study is an efficient distributed energy supply system that can be used to simultaneously supply electricity, cooling, heating, and freshwater as photovoltaic power, wind power, combined heat and power (CHP), electric cooling and heating, and a seawater desalinati on device are in teg rated into the MEN. In this study, a model for operati on optimization of a MEN for seawater desalination was developed and the influences of the electric cooling and heating ratios and the operation optimization of the seawater desalination device were studied with the aim of minimizing the life cycle cost. Based on the results of this study, MENs can reduce the operation cost of desalination devices and improve the efficiency of renewable energy sources.

The Simulation of Rumor’S Spreading and Controlling in Micro-Blog Users’ Network

In this work, a rumor’s spreading and controlling in a directed Micro-blog user network being consisted with 580 000 nodes are simulated. By defining some authority nodes that release anti-rumor information as the prevention strategy, the effect of the nodes’ role in network on rumor’s suppression is studied. The findings show that rumor will be spread out fast and reach a stable level within limited steps. The suppression of rumor is more predominated by the intervening opportunity, the earlier the intervention strategy was implemented, the better the rumor’s controlling could be achieved. The controlling effect is less relevant with the role of the authority nodes in network.

A Micro-Payment Based Isolation ofMisbehavior Secure Routing for Sensor Network

In this paper, we present a Micro-payment based Isolation of Misbehavior(MIM) secure routing protocol. The protocol contains three parts: micro-payment scheme, routingdiscovery and malicious nodes detection The micro-payment scheme proposed in MIM is the firstvirtual currency system that can be suit lor sensor network environment, Based on the micro-paymentscheme, we device an energy aware routing protocol, which forwards packets by auction. Furthermore,the base station can detect and isolate misbehave or non-cooptrare nodes according to the routinginformation.

考虑需求响应和共享储能的微网联盟两阶段优化调度

随着共享储能的推广,能源信息的流动与共享得到进一步发展,为促进能源管理和提升利用效率,提出一种基于共享储能和需求响应的微网联盟两阶段优化调度策略。首先,建立多微网联盟-共享储能系统运行框架,并基于综合贡献度对微网利益分配过程进行建模;其次,建立两阶段优化调度模型,第一阶段以多微网联盟-共享储能系统净收益最大为目标,第二阶段考虑用户的需求响应,求解耗能用户的最低购能费用;再次,利用求解器对两阶段模型分别进行求解,得到多微网系统的分时能源价格、各微网设备的运行状态、需求响应后负荷和各微网利益;最后,设置4个方案作为算例,验证所提优化策略在提高各微网收益和激励用户需求响应的有效性。

Active Vibration Isolation of Micro-Manufacturing Platform Based on Neural Network

The micromation and precision of the Micro-Electromechanical System demand that its manufacturing, measuring and assembling must work in a micro-manufacturing platform with good ability to isolate vibrations. This paper develops a vibration isolation system of micro-manufacturing platform. The brains of many kinds of birds can isolate vibrations well, such as woodpecker’s brain. When a woodpecker pecks the wood at the speed as 1.6 times as the velocity of sound, its brain will tolerate the wallop 1 500 times of the weight of itself without any damage. The isolation mechanics and organic texture of woodpecker’s brain that has good isolation characteristics were studied. A structure model of vibration isolation system for the micro-manufacturing platform is established based on the bionics of the bird’s brain vibration isolation mechanism. In order to isolate effectively the high frequency vibrations from the ground, a rubber layer is used to isolate vibrations passively between the micro-manufacturing platform’s pedestal and the ground. This layer corresponds to the cartilage and muscles in the outer meninges of the bird’s brain. The active vibration isolation technique is adopted to isolate vibrations between the micro-manufacturing platform and the pedestal. Air springs are used as elastic components, which correspond to the interspaces between the outer meninges and the encephala of the bird’s brain. Actuators are made of giant magnetostrictive material, and it corresponds to the nerves and neural muscles linking the meninges and the encephala. The actuators and air springs are arranged vertically in parallel to make use of the giant magnetostrictive actuators effectively. The air springs support almost all weight of the micro-manufacturing platform and the giant magnetostrictive actuators support almost no weight. In order to realize high performance to isolate complex micro-vibration, the control method using a three-layer neural network is presented. This vibration control system takes into account the floor disturbance and the direct disturbance acting on the micro-manufacturing platform. The absolute acceleration of the micro-manufacturing platform is used as the performance index of vibration control. The performance of the control system is tested by numerical simulation. Simulation results show that the active vibration isolation system has good isolation performance against the floor disturbance and the direct disturbance acting on the micro-manufacturing platform in all the frequency range.

A novel strategy of smart manipulation by micro-scale oscillatory networks of the reactionary zones for enhanced extreme thrust control of the next-generation solid propulsion systems

The main aim of this research is to get a better knowledge and understanding of the micro-scale oscillatory networks behavior in the solid propellants reactionary zones. Fundamental understanding of the micro-and nano-scale combustion mechanisms is essential to the development and further improvement of the next-generation technologies for extreme control of the solid propellant thrust. Both experiments and theory confirm that the micro-and nano-scale oscillatory networks excitation in the solid propellants reactionary zones is a rather universal phenomenon. In accordance with our concept,the micro-and nano-scale structures form both the fractal and self-organized wave patterns in the solid propellants reactionary zones. Control by the shape, the sizes and spacial orientation of the wave patterns allows manipulate by the energy exchange and release in the reactionary zones. A novel strategy for enhanced extreme thrust control in solid propulsion systems are based on manipulation by selforganization of the micro-and nano-scale oscillatory networks and self-organized patterns formation in the reactionary zones with use of the system of acoustic waves and electro-magnetic fields, generated by special kind of ring-shaped electric discharges along with resonance laser radiation. Application of special kind of the ring-shaped electric discharges demands the minimum expenses of energy and opens prospects for almost inertia-free control by combustion processes. Nano-sized additives will enhance self-organizing and self-synchronization of the micro-and nano-scale oscillatory networks on the nanometer scale. Suggested novel strategy opens the door for completely new ways for enhanced extreme thrust control of the solid propulsion systems.

Optimal Partitioning of Distribution Networks for Micro-Grid Operation

A great concern for the modern distribution grid is how well it can withstand and respond to adverse conditions. One way that utilities are addressing this issue is by adding redundancy to their systems. Likewise, distributed generation (DG) is becoming an increasingly popular asset at the distribution level and the idea of microgrids operating as standalone systems apart from the bulk electric grid is quickly becoming a reality. This allows for greater flexibility as systems can now take on exponentially more configurations than the radial, one-way distribution systems of the past. These added capabilities, however, make the system reconfiguration with a much more complex problem causing utilities to question if they are operating their distribution systems optimally. In addition, tools like Supervisory Control and Data Acquisition (SCADA) and Distribution Automation (DA) allow for systems to be reconfigured faster than humans can make decisions on how to reconfigure them. As a result, this paper seeks to develop an automated partitioning scheme for distribution systems that can respond to varying system conditions while ensuring a variety of operational constraints on the final configuration. It uses linear programming and graph theory. Power flow is calculated externally to the LP and a feedback loop is used to recalculate the solution if a violation is found. Application to test systems shows that it can reconfigure systems containing any number of loops resulting in a radial configuration. It can connect multiple sources to a single microgrid if more capacity is needed to supply the microgrid’s load.

YASA轴向磁通永磁电机定子槽漏感计算

定子槽漏感是定子无轭模块化(yokeless and segmented,YASA)轴向磁通永磁电机电感的主要分量,会降低电机的功率因数和最大输出转矩。该文提出定子槽内微小单元磁场能量法计算YASA电机的定子槽漏感,通过建立计及铁心饱和影响的二维等效磁网络模型准确计算槽内微小单元储存的磁场能量,进而计算定子槽漏感。基于所提出的方法,进一步研究定子结构参数以及极槽配合对YASA电机定子槽漏感的影响规律。有限元仿真和实验结果表明,该文所提出的YASA电机定子槽漏感计算方法的可行性和准确性。

微观地块服务设施可达性评价及路网优化影响分析

针对现有的服务设施可达性评价方法分析尺度大、数据精度低且无法依赖网络地图应用程序编程接口(Application Programming Interface,API)评价路网规划方案等问题,提出一种可用于规划方案评价的微观地块综合服务设施可达性评价方法.依据土地利用性质将研究区域划分为565个微观地块,利用实际居住建筑物空间分布测算各地块的人口分布;基于实际路网构建地铁-公交加权复合网络模型和小汽车网络模型,并设计通行时间的计算方法;利用改进潜力模型精确地计算各地块的医疗、教育、就业、商业和文化休闲5类设施的可达性,加权得到综合可达性.此外,考虑路网规划方案对交通网络的更新,以评价规划方案对可达性的具体影响.研究结果表明:可达性与服务设施及交通网络的空间分布呈现强相关性,公共交通网络的合理布局可有效缓解由服务设施和路网差异引起可达性分布差异;优化路网能有效提高可达性水平,但这种改善效果在不同区域间存在差异,设施密度较高的区域提高幅度较大.此评价方法可以为城市各类公共服务设施的合理配置、交通网络的规划与优化,以及社会公平性的增强提供新的视角和工具.

基于改进卷积神经网络的心理状态预警技术

针对传统问卷法难以真实反映被调查者心理状态的问题,基于光流法和卷积神经网络提出了一种微表情判断方法,并将其作为心理状态预警技术的核心模块。对于数据集中人脸数据离散的问题,该方法采用人眼权重法对图像进行预处理,且通过金字塔光流算法提取预处理图像序列的光流特征,再利用三维卷积神经网络对该特征加以训练。与传统算法相比,所提方法在减少模型训练参数与运算时间的同时还具有更优的学习能力。实验测试结果表明,该算法在CASME数据集上的微表情识别准确率为89.2%,F1值为0.6751,均优于其他对比方法。由此证明,该算法可实现对人脸微表情的准确识别,进而为学生心理状态预警提供客观的数据支撑。

考虑产消者响应与不确定性的微能网双层混合博弈优化

随着分布式能源的发展,传统用户具备发电能力而成为产消者(production and consumption users,PCU)的趋势愈演愈烈,该文主要研究了同一微能网下大量产消者的协同运行问题。电价不确定性和产消者响应给微能网协同不同利益主体的PCU之间的调度带来困难。在此背景下提出考虑产消者响应与电价不确定性的微能网与产消者混合博弈优化策略。首先,构建产消者响应模型和电价不确定性模型,引入效用函数来描述PCU的满意程度,采用鲁棒优化和机会约束方法描述电价的不确定性与新能源出力的不确定性。其次,构建混合博弈模型,即上层微能网运营商(integrated energy operator,IEO)与下层PCU之间的主从博弈模型和下层PCU联盟之间的合作博弈模型。上层IEO作为主从博弈的领导者以运行成本最小化为目标,通过为产消者制定电价、热价引导产消者的用能需求;下层产消者作为跟随者,以效益最大为目标通过合作方式对IEO的决策进行产消者响应。PCU之间的合作博弈以纳什议价的方式进行,将PCU模型等效为联盟收益最大化和合作分配两个子问题。基于KKT条件利用Big-M法和Mc Cormick包络法将双层问题转换为单层混合整数线性规划问题求解主从博弈,结合交替方向乘子法(alternating direction multiplier method,ADMM)求解下层合作博弈。结果表明,该文所提策略有效协调了微能网与PCU的调度并保证了PCU合作联盟的公平性。

多站融合的微能源系统站 网协同布局

为了促进资源的共享,提高能源利用率,建立了双层站网优化布局模型,对多站融合的微能源系统的融合站数量、位置、设备容量配置,以及管线分布进行了协同规划。上层模型采用最小生成树和谱聚类求解,解决了融合站数量、位置和管线分布问题;下层模型采用提出的改进的粒子群优化算法,解决了设备容量配置问题。通过对规划区域进行算例仿真,得出了系统站网协同布局的优化结果,验证了所提模型和算法的可行性与合理性。

基于微服务和物联网的配电网智能计量架构

为实现电力系统向智能电网模式的演进,依赖于配电网(DN)的自动化,需要新的基础设施、技术和应用。提出一种基于微服务和物联网(IoT)的配电网自动化的智能计量设施,支持各种有助于实现配电网自动化和管理的服务。首先,在测量基础设施中对特定硬件、设备和底层协议进行抽线;然后,利用消息队列遥测传输(MQTT)作为以事件为导向的发布/订阅协议来实现,同时支持发布/订阅和请求/响应机制来实现;最后,使用以大数据为导向的可群集软件模块来实现可扩展性。分布式状态估计(SE)和网络拓扑重构算法验证了智能计量设施支持交互和协同操作。

云边环境下微服务通信网络入侵行为识别方法

通信网络入侵行为具有多样性,难以保障入侵行为的识别效果,因此提出一种云边环境下微服务通信网络入侵行为识别方法。引入非线性变换函数,对微服务通信网络入侵行为的特征进行半监督学习,通过将原始入侵行为映射到高维空间,获取正常运行状态下特征向量的参数。在构建以改进降噪自编码网络为基础的网络入侵行为识别模型的过程中,引入注意力机制,根据网络状态数据的重构误差与所设定的网络入侵行为特征阈值之间的差异,判断具体的入侵行为。根据测试结果,该方法能够准确识别出不同类型的入侵攻击。

基于氢储能的偏远地区零碳微能网构建及运行策略研究

针对绿色能源富集的偏远地区外部供能代价大、内部绿色微电源可靠性低、柴油发电机作为后备电源成本较高等问题,文章提出了离网型储氢供能场景下基于氢储能的微能网设计。根据可再生能源富集偏远地区能源时空分布特性,提出了基于氢储能的零碳微能网构建框架,构建了绿色能源富集区建设氢能零碳微能网的资源禀赋约束及微能网运行约束,制定了能源富裕及短缺期微能网运行策略,并对云南省某村镇案例进行仿真。结果表明,文章构建的微能网运行策略能有效消除区域绿色微电源出力不稳定以及季节性短缺对供电系统可靠性的影响,减轻区域热负荷负担。研究成果可为偏远地区、海岛等绿色能源富集区域的用能改善及降碳提供参考。

基于微多普勒角点特征与Non-Local机制的穿墙雷达人体步态异常终止行为辨识技术

穿墙雷达能够穿透建筑物墙体,实现室内人体目标探测。利用深度学习提取不同肢节点的微多普勒特征,可以有效辨识障碍物后的人体行为。但是,当生成训练、验证集与生成测试集的受试者不同时,基于深度学习的行为识别方法测试准确率相对验证准确率往往较低,泛化能力较差。因此,该文提出一种基于微多普勒角点特征与Non-Local机制的穿墙雷达人体步态异常终止行为辨识技术。该方法利用Harris与Moravec检测器提取雷达图像上的角点特征,建立角点特征数据集;利用多链路并行卷积和Non-Local机制构建全局上下文信息提取网络,学习图像像素的全局分布特征;将全局上下文信息提取网络重复堆叠4次得到角点语义特征图,经多层感知机输出行为预测概率。仿真和实测结果表明,所提方法可以有效识别室内人体步行过程中存在的坐卧、跌倒等突发步态异常终止行为,在提升识别准确率、鲁棒性的前提下,有效控制泛化精度误差不超过6.4%。