5G核心网业务模型的智能化预测研究

摘 要：核心网业务模型的建立是5G网络容量规划和网络建设的基础，通过现有方法得到的理论业务模型是静态不可变的且与实际网络存在偏离。为了克服现有5G核心网业务模型与现网模型适配性较差以及规划设备无法满足用户实际业务需求的问题，提出了一种长短期记忆（long short-term memory，LSTM）网络与卷积LSTM （convolution LSTM，ConvLSTM）网络双通道融合的 5G 核心网业务模型预测方法。该方法基于人工智能（artificial intelligence，AI）技术以实现高质量的核心网业务模型的智能预测，形成数据反馈闭环，实现网络自优化调整，助力网络智能化建设。     

基于误差估值累加开环校正的诱导式欺骗检测方法

诱导式卫星欺骗干扰可诱导航空器逐渐偏离预定航迹，难以被发现，因此及时有效地检测干扰是飞行安全的保障。在现有紧组合导航体制基础上，设计了一种基于误差估值累加开环校正的紧组合导航结构，并证明了其性能与传统闭环校正紧组合导航性能等效。在此结构中，将紧组合导航系统与自适应序贯概率比检测方法结合，提出了一种基于误差估值累加开环校正的诱导式欺骗检测方法，融合紧组合导航信息与其他不受欺骗影响的导航信息，构建欺骗检测统计量进行诱导式欺骗检测。仿真结果表明，开环校正结构可避免随时间累加的惯性导航系统误差所导致的组合导航滤波器发散问题，同时欺骗检测方法可进一步提高算法对“最坏”情形下微小诱导式欺骗的检测效果。     

有机-无机压电材料TMCM-MnCl3的研究

有机-无机压电材料是一种分子铁电体，具有柔性、结构灵活、易成膜、全液相合成及环保节能等优点，可满足新一代薄膜器件及可穿戴设备的需求。该文以三甲基卤代甲基铵(TMXM, X=F, Cl, Br)为有机部分，MnCl₂为无机部分，通过溶液蒸发法制备了具有钙钛矿分子结构的有机-无机压电材料三甲基氯三氯化锰(TMCM-MnCl₃)，并对其分子结构组成、压电、热学、声学及铁电性进行表征。结果表明，TMCM-MnCl₃的压电常数为106 pC/N，居里温度为130 ℃，声阻抗值约为16.5 MRayl，低于压电陶瓷PZT-4(大于33 MRayl)，具有广阔的应用前景。     

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。     

矢量语音传感器微阵列

人工智能的普及促进了语音交互技术的发展,语音传感器阵列作为智能语音交互的硬件前端,成为语音交互领域的前沿研究方向.矢量语音传声器自有的偶极子指向性、零点深度以及阵列体积小便于集成的特点特别符合语音交互技术对硬件设备的要求.基于此,通过采用两组矢量敏感单元"共点正交"形成矢量微阵列实现声源空间锐化波束指向,其不受瑞利限与空间采样率限制,与传统空间离散分布的声压麦克风阵列有着本质区别,是矢量微阵列的核心优势所在.矢量微阵列传声器弥补了现有双麦阵列的不足,具有更为广阔的应用前景,作为智能语音交互的硬件前端,对推动智能语音交互领域的发展具有重要意义.     

Electrowetting-Assisted Generation of Ultrastable High Charge Densities in Composite Silicon Oxide–Fluoropolymer Electret Samples for Electric Nanogenerators

Electric nanogenerators that directly convert the energy of moving drops into electrical signals require hydrophobic substrates with a high density of static electric charge that is stable in “harsh environments” created by continued exposure to potentially saline water. The recently proposed charge-trapping electric generators (CTEGs) that rely on stacked inorganic oxide–fluoropolymer (FP) composite electrets charged by homogeneous electrowetting-assisted charge injection (h-EWCI) seem to solve both problems, yet the reasons for this success have remained elusive. Here, systematic measurements at variable oxide and FP thickness, charging voltage, and charging time and thermal annealing up to 230 °C are reported, leading to a consistent model of the charging process. It is found to be controlled by an energy barrier at the water-FP interface, followed by trapping at the FP-oxide interface. Protection by the FP layer prevents charge densities up to −1.7 mC m⁻² from degrading and the dielectric strength of SiO₂ enables charge decay times up to 48 h at 230 °C, suggesting lifetimes against thermally activated discharging of thousands of years at room temperature. Combining high dielectric strength oxides and weaker FP top coatings with electrically controlled charging provides a new paradigm for developing ultrastable electrets for applications in energy harvesting and beyond.     

数字签名技术在医院电子病历中的设计与应用

为推进病历数字化发展,并确保其信息的安全性,将以HIS电子病历系统为基础,采用安信数字签名技术和PKI或PMI系统搭建相信并加以任用的授权服务,经过针对实际的PKC和CA的确认、委托与管控构建整体的数字签名平台,完成电子病历数字签名功能设计,以加强电子文件的完整性、真实性和不可抵赖性。最后以某医院的XML结构化的电子病历系统为基础进行项目实施,完成了医护人员通过HIS的快速身份认证,和准确地数字签名。     

基于ERNIE-BiGRU模型的摘要语步自动识别研究

学术文献的摘要是对文献主要内容的浓缩,摘要不同部分的语步具有不同的信息,语步的自动识别和抽取对于学术摘要的后续研究有着重要的应用价值,而目前语步识别的研究相对较少,并且相关算法的效果还需要提高。针对上述问题,该文提出了一种基于ERNIE-BiGRU模型的语步识别算法。该算法首先结合中文句法分析理论提出基于句法依存关系的多语步结构拆分法,对学术文献摘要多语步结构进行自动拆分,获得多个单语步结构;然后构建用于训练的单语步结构语料库,并利用知识增强语义表示预训练模型,训练出句子级词向量;最后将训练出的单语步结构词向量信息输入双向门限循环单元(BiGRU)进行摘要语步自动化识别,取得了良好的效果。实验结果表明,该算法具有较好的鲁棒性和较高的识别精度,在结构化和非结构化摘要上的识别准确率分别达到了96.57%和93.75%。     

伊拉克米桑油田水平井钻井关键技术

针对伊拉克米桑油田盐膏层巨厚、钻井液密度窗口窄、存在高压盐水层,储层段漏塌同层导致复杂时效高等问题,通过对比分析国内外盐膏层和窄压力窗口地层钻井技术,总结了米桑油田钻井面临的主要技术难点,从井身结构优化、钻井提速和复杂预防等方面入手,研究形成了适合米桑油田的钻井关键技术,并进行了现场试验应用,取得了显著的效果.伊拉克米桑油田钻井关键技术对该地区钻井技术方案设计和钻井提速提效具有较强的借鉴和指导作用.     

Colossal dielectric response and relaxation behavior in novel system of Zr4+ and Nb5+ co-substituted CaCu3Ti4O12 ceramics

In this work, we developed a novel system of isovalent Zr⁴⁺ and donor Nb⁵⁺ co-doped CaCu₃Ti₄O₁₂ (CCTO) ceramics to enhance dielectric response. The influences of Zr⁴⁺ and Nb⁵⁺ co-substituting on the colossal dielectric response and relaxation behavior of the CCTO ceramics fabricated by a conventional solid-phase synthesis method were investigated methodically. Co-doping of Zr⁴⁺ and Nb⁵⁺ ions leads to a significant reduction in grain size for the CCTO ceramics sintered at 1060 °C for 10 h. XRD and Raman results of the CaCu₃Ti_3.8-xZr_xNb_0.2O₁₂ (CCTZNO) ceramics show a cubic perovskite structure with space group Im-3. The first principle calculation result exhibits a better thermodynamic stability of the CCTO structure co-doped with Zr⁴⁺ and Nb⁵⁺ ions than that of single-doped with Zr⁴⁺ or Nb⁵⁺ ion. Interestingly, the CCTZNO ceramics exhibit greatly improved dielectric constant (~10⁵) at a frequency range of 10²–10⁵ Hz and at a temperature range of 20–210 °C, indicating a giant dielectric response within broader frequency and temperature ranges. The dielectric properties of CCTZNO ceramics were analyzed from the viewpoints of defect-dipole effect and internal barrier layer capacitance (IBLC) model. Accordingly, the immensely enhanced dielectric response is primarily ascribed to the complex defect dipoles associated with oxygen vacancies by co-doping Zr⁴⁺ and Nb⁵⁺ ions into CCTO structure. In addition, the obvious dielectric relaxation behavior has been found in CCTZNO ceramics, and the relaxation process in middle frequency regions is attributed to the grain boundary response confirmed by complex impedance spectroscopy and electric modulus.