产教融合背景下高职特色专业群“平台+模块”课程体系建设研究

In view of the problems in the construction of characteristic professional groups in higher vocational colleges, the professional group of "intelligent manufacturing" is taken as the research object, and the "platform + module" suitable for the development of the industry will be constructed according to the content of the vocational ability planning courses of the post group. The curriculum system establishes the framework of professional groups, and explores and forms a strategic study to optimize and integrate professional group resources.     

5G网络在智能交通中的应用发展趋势分析

Along with the advent of 5G era, China's transportation industry for intelligent development enters into the fast lane. Based on the integration of communication technology, Internet of things technology, big data technology, cloud computing technology, ar- tificial intelligence technology and so on, the whole process and all-round intelligent control are carried out in traffic construction, traffic management, road transportation, traffic service and so on, so as to ensure smooth and safe travel and to provide good servic- es to road, railway, civil aviation, water transportation and other transportation networks. It is the important feature of intelligent transportation in the 5G era. This paper analyses the trend of application and development of 5G network in intelligent transporta- tion, which is the research basis of perfecting transportation service and the scientific basis of promoting the intelligent and modern development of transportation in China.     

Zone model predictive control for pressure management of water distribution network

In the water distribution network (WDN), although the water demand of the node is changing constantly, the water quantity and water pressure of the node need to be met at each moment. To realize energy saving and consumption reduction, it is proposed to control the nodal water head of WDN in an appropriate narrow range. The frequent large fluctuation of the water demand, which may lead the water pressure exceed the expected range, increases the difficulty of the zone control. To realize optimized WND control, a novel zone predictive control is proposed, where two switching cases are considered. The switching condition is whether there are feasible solutions to keep the pressure within the expected region over the prediction horizon. When the condition is satisfied, the controller minimizes the variation of inputs with constraints of pressure range for ensuring the tank level staying within the expected zone and obtaining optimal economic cost. When the current pressure is out of the expected region or the condition is not satisfied due to the large variation of water demand, a reference trajectory of outputs is introduced, which is combined with the inputs as an optimization variable, and the constraints of expected zone are moved from the output to the introduced reference trajectory. Through minimizing the distance between reference trajectory and output, the controller will keep the tank level from deviating too far from the expected zone and will drive the tank level rapidly into the expected zone once the tank level exceeds the expected range. An application of the proposed zone MPC to WDN in Shinan District of Shanghai is given to illustrate its effectiveness.     

视频侦查中人像智能分析应用及算法优化

人像智能分析指的是对视频或录像中的人像进行结构化和可视化分析,对目标人物进行性别、年龄、发型等特征的智能识别,这项技术在视频侦查中有极高的应用价值。人像识别早期的算法是通过人工提取特征,通过学习低级视觉特征来针对不同属性进行分类学习,这种基于传统方法的模型表现常常不尽如人意。在计算机视觉领域,通过海量图像数据学习的神经网络比传统方法有更丰富的信息量和特征可以被提取。文章尝试通过深度学习技术训练神经网络模型对行人进行检测和识别,对于衣着不同的行人进行智能识别,具有更好的鲁棒性,提升了视频人像识别的准确率,拓展了人工智能技术在身份识别领域的应用。     

Analyzing dissipation effects on the non-classicality witnessing by a qubit via the entangled state representation

ABSTRACT

In this paper, we study detection of the state non-classicality for a quantum harmonic oscillator by a qubit in the presence of dissipation effects. We show that dissipation can enhance the effectiveness of the method in case of using the corrected form of the related nonclassicality witness. Such an improvement is attributed to the fact that dissipation leads to probing a surface, instead of a curve, of the complex plane for non-classicality condition on normally-ordered characteristic function.     

基于模拟退火优化BP神经网络的变形监测数据预测方法

针对BP神经网络模型用于变形监测数据处理时容易陷入局部极小值并且收敛速度慢的问题，提出一种基于模拟退火(Simulated Annealing,SA)算法优化BP神经网络的建筑物变形预测方法，利用SA的全局寻优能力对BP神经网络的模型参数进行优化，使参数迭代过程始终保持较高的“温度”和“能量”，从而确保BP神经网络能够得到全局最优解的同时具备较高的预测精度和收敛速度。采用实际算例对所提SA-BP方法在低信噪比和小样本条件下的预测精度进行验证，结果表明所提方法相对于传统BP神经网络法和小波方法能够获得更高的预测精度，并且在小样本和低信噪比条件下优势更加明显。     

皮带输送机运行过程中常见问题及处理对策

皮带输送机是煤矿井下重要的煤炭运输设备,其稳定运行关系着煤矿生产的高产高效。由于煤矿井下生产环境恶劣,皮带输送机很容易发生各种问题。因此,对皮带输送机运行过程中出现的问题进行准确分析并进行处理显得十分重要。对皮带输送机运行过程中出现的一些常见问题进行了分析,并给出了一些相应的处理对策,有助于实现煤矿生产的高产高效。     

基于气动性能与刚度特性的风力机翼型优化设计

结合翼型泛函集成理论与叶片截面刚度矩阵数学计算模型,提出了风力机中等厚度翼型气动性能与结构刚度特性的一体化设计方法,实现了翼型气动性能与叶片截面刚度特性的同时提高。对考虑叶片截面铺层参数变化设计的WQ-B300翼型与DU97-W-300翼型进行了气动性能与结构刚度特性对比分析,结果表明:相比于DU97-W-300翼型,WQ-B300翼型的气动性能与叶片截面刚度性能均有显著提高,其挥舞刚度和摆振刚度分别提高了6.2%和8.4%,验证了该设计方法的可行性,给风力机中等厚度及大厚度翼型设计提供了一种思路。     

全局力平衡PDC钻头布齿优化设计

针对聚晶金刚石复合片(PDC)钻头在钻井破岩过程中因受力不平衡，导致钻井倾斜、井径扩大、钻头产生横向振动和涡动，造成钻头早期失效的问题，基于已有PDC钻头切削力学知识，构建了PDC钻头弯曲力矩及全局力平衡布齿优化设计模型，并提出模型求解方法。布齿设计实例结果表明，采用全局力平衡布齿设计方法得到的布齿结构可使PDC钻头在不同进尺条件下均能保持全局力平衡状态，尤其低进尺（小于1 mm）时的力平衡状态得到极大改善，提高了PDC钻头的钻井稳定性，对于改善钻头受力、提升钻头使用寿命、提高钻井质量与效率具有重要意义。