Polymer electrets and their applications

Polymer electrets have revealed great potential application in electromechanical devices because of the low weight, large quasi-piezoelectric sensitivity, and excellent flexibility. For an electret, a permanent and macroscopic electric field exists on the surface, principally led by a macroscopic electrostatic charge on the surface or a net orientation of polar groups inside the object. Here, progress in the development of polymer electrets is reviewed. After a brief retrospect of the research courses and those typical polymer electrets that are classified into fluorine polymer and nonfluorine polymer, we present a survey on the charging methods, including corona, soft X-ray, contact, thermal and monoenergetic particle beams. The latest representative applications (i.e., power harvesting, sensors, field effect transistors, and biomedicine) based on polymer electrets are also summarized. Finally, we complete this review with a discussion on perspectives and challenges in this field.     

基于形态特征提取的急性下壁心肌梗死BiLSTM网络辅助诊断算法

急性下壁心肌梗死是一种病发急、进展快、致死率高的心脏疾病,该文提出一种新颖的基于形态特征提取的BiLSTM神经网络分类的急性下壁心肌梗死辅助诊断算法,可大幅度提高医生对急性下壁心肌梗死疾病的诊断效率并有助于及时确诊.算法包括:对胸痛中心数据库心拍信号进行降噪及心拍分割;根据临床心内科医学诊断指南提取了12导联波形距离特征和分导联波形幅值特征;依据提取的特征搭建LSTM与BiLSTM神经网络进行心拍的分类识别;使用PTB公开数据库和胸痛中心数据库多临床中心进行交叉验证.实验结果表明,加入胸痛中心真实临床数据后,基于形态特征提取BiLSTM神经网络的急性下壁心肌梗死辅助诊断算法准确率达到99.72％,精度达到99.53％,灵敏度达到100.00％,同时F1-Score达到99.76.该算法比其他现有算法准确率提高至少1％,该项研究具有非常重要的临床应用价值.     

基于VMD和BSA-KELM的高陡边坡位移预测模型研究

边坡位移的时间序列曲线存在复杂的非线性特性,传统的预测模型精度不足以满足预测要求。为此提出了基于变分模态分解的鸟群优化-核极限学习机的预测模型,并用于河北省某水泥厂的边坡位移预测。该方法首先采用VMD把边坡位移序列分解为一系列的有限带宽的子序列,再对各子序列分别采用相空间重构并用核极限学习机预测,采用鸟群算法优化相空间重构的嵌入维度和KELM中惩罚系数和核参数三个数值,以取得最优预测模型。最后将各个子序列预测值叠加,得到边坡位移的最终预测值。结果表明：和KELM、BSA-KELM、EEMD-BSA-KELM模型相比,基于VMD的BSA-KELM预测精度更高,为边坡位移的预测提供一种有效的方法。     

Fabrication of crescent-shaped ceramic microparticles based on single emulsion microfluidics

Ceramic microparticles have great potentials in various fields such as materials engineering, biotechnology, microelectromechanical systems, etc. Morphology of the microparticle performs an important role on their application. To date, it remains difficult to find an effective and controllable way for fabricating nonspherical ceramic microparticles with 3D features. This work demonstrates a method that combines UV light lithography and single emulsion opaque-droplet-templated microfluidic molding to prepare the crescent-shaped ceramic microparticles. By tailoring the intensity of UV light and flow rate of fluid, the shapes of microparticles are accordingly tuned. Therefore, varieties of crescent-shaped microparticles and their variations have been fabricated. After sintering, the crescent-shaped alumina ceramic microparticles were obtained. Benefitting from the light absorption and scattering behavior of most ceramic nanoparticles, this system can serve as a general platform to produce crescent-shaped microparticles made from different materials, and hold great potentials for applications in microrobotics, structural materials in MEMS, and biotechnology.     

北斗星历解析及实时卫星位置解算实现

利用 C 语言编程进行北斗卫星星历数据的实时读取，更新结构体的卫星轨道参数， 从而实现北斗卫星位置的解算，并与武汉大学数据中心提供的北斗精密星历作比较，对解算的卫星位置结果进行评估，最大误差不超过 3.5 米，满足实际应用需要。     

盾构隧道施工物料无人运输发展现状及关键技术

盾构隧道施工物料无人运输有助于提升运输效率、降低运输成本、减少运输安全事故率。与公路汽车无人驾驶、港口车辆无人驾驶、轨道交通无人驾驶等逐步成熟的无人驾驶技术不同，在隧道场景下实施施工物料无人运输存在运输物料种类繁多、运输调度困难、地下定位信号拒止、狭窄车道频繁会车、行车路面工况复杂、地上地下联动响应慢等诸多挑战。从实现盾构隧道施工物料无人运输的关键问题分析入手，综述当前盾构隧道施工物料运输方式、运输需求、无人运输发展现状及存在的挑战，提出盾构隧道施工物料无人运输的五大关键技术：多种类物料智能货控能效管理技术，无人化垂直装卸门机控制技术，多传感器融合同步定位与地图构建技术，隧道复杂环境路径规划与自主避障技术，隧-地一体化联动响应的高可靠性无线通信技术。     

25%小偏置碰撞策略及测试评估研究

随着汽车事故的增加,且小重叠碰撞事故死亡率居高不下,小偏置碰撞试验逐渐成为焦点。基于IIHS公布的最新车辆碰撞试验结果,统计超过100余款不同类型的25%小偏置碰撞车辆,建立碰撞转角与碰撞区域的数学模型,将25%小偏置碰撞归结为三种不同的碰撞策略,分别是吸能策略、掠过策略和掠过与吸能策略;并进行试验验证,对三种策略的优缺点进行分析。结果表明,小偏置碰撞试验可运用合理的碰撞策略达到法规要求,对25%小偏置碰撞试验具有一定的参考价值。     

“电工学”国家级一流课程建设与实践

根据新时代新工科人才需求特点和电工学课程特点,分析非电专业学生的电类实践需求,提出构建电工学课程为核心的电工电子实践创新能力培养新体系。通过优化教学内容、开展教学模式和考核模式改革、构建教学资源体系和进行教师队伍建设,使我校电工学课程教学质量提升、学生工程实践和创新能力提高、学生满意度增加、一流课程建设成效显著。