浅析汽车博物馆建筑设计理念

汽车博物馆是汽车历史的浓缩,是汽车工业的承载体.通过对国内外典型汽车博物馆建筑实例进行剖析,分析汽车博物馆建筑设计理念,探讨汽车博物馆建筑设计的方法.     

A time-optimal aircraft-following model based on Pontryagin’s minimum principle

A time-optimal aircraft-following model is introduced to address air traffic flow interference by velocity reduction. The objective function is set up as minimizing the recovery time during which the separation minima are not infringed and the separation of the air traffic flow returns to the initial separation at the terminal time. Pontryagin’s minimum principle is used to solve the optimum aircraft-following velocity control law. An analytical minimum safe following separation is also provided under the time-optimal control law. The simulation results show that the precision first-order tracking accuracy is achieved without losing the separation.

     

自适应梯度重建分水岭分割算法

目的 针对灰度分水岭算法存在过分割且难以直接应用到彩色图像分割的问题,提出一种自适应梯度重建分水岭分割算法。方法 该方法首先利用PCA技术对彩色图像降维,然后计算降维后的梯度图像,并采用自适应重建算法修正梯度图像,最后对优化后的梯度图像应用分水岭变换实现对彩色图像的正确分割。结果 采用融合了颜色距离、均方差和区域信息的性能指标和分割区域数对分割效果进行评估,对不同类型的彩色图像进行分割实验,本文算法在正确分割图像的同时获得了较高的性能指标。与现有的分水岭分割算法相比,提出的方法能有效剔除图像中的伪极小值,减少图像中的极小值数目,从而解决了过分割问题,有效提升了分割效果。结论 本文算法具有较好的适用性和较高的鲁棒性。     

基于3G传输网络的道路气象预警系统

利用传感技术为监测手段开发一套基于3G传输网络的道路气象预警系统,使道路管理部门精确掌握气象资料和天气预报,并根据各路段的地形及气候特点,结合路段交通状况,制定各自的应急预案,以保证道路的行车安全和顺畅。此系统对道路沿线气象状况进行监测、分析并采取有效的应急预案,对保障道路过往车辆和人身财产安全有着积极作用。     

通信公司能耗管理系统和采集系统改造工程解析

能耗的持续增长是当前电信企业面临的重大问题,能耗监测体系和能耗管理系统的不健全,导致电信相关企业对能耗的实际情况不能全面的掌握,以至于节能改造项目的实施也存在诸多问题。根据要求,某通信集团公司将集中建设能耗管理平台,对电能进行集中管理。目前某省通信公司已有的能耗管理平台存在耗电量统计不准确,人性化设计较弱,采集信息显示不完整,无法提供全网能耗分析需求的信息等问题。本系统的改造建设以现有能耗管理平台为基础,通过网管中心虚拟化方式,构建全面的能耗管理平台,对电能实现集中管理,并为之后的节能减排项目提供技术支撑。本文所涉及的实践知识和技术资料可为之后相关领域的能耗管控相关工程提供参考和指导。     

尼龙和聚醋短纤维填充胶料的流变性能

研究了尼龙和聚酯短纤维填充胶料的流变性能，探讨了预处理、温度、短纤维用量等因素对流变性能的影响，分析了短纤维自身性与胶料流变性能之间的依赖关系。     

A tensor decomposition based collaborative filtering algorithm for time-aware POI recommendation in LBSN

Point of interest (POI) recommendation problem in location based social network (LBSN) is of great importance and the challenge lies in the data sparsity, implicit user feedback and personalized preference. To improve the precision of recommendation, a tensor decomposition based collaborative filtering (TDCF) algorithm is proposed for POI recommendation. Tensor decomposition algorithm is utilized to fill the missing values in tensor (user-category-time). Specifically, locations are replaced by location categories to reduce dimension in the first phase, which effectively solves the problem of data sparsity. In the second phase, we get the preference rating of users to POIs based on time and user similarity computation and hypertext induced topic search (HITS) algorithm with spatial constraints, respectively. Finally the user’s preference score of locations are determined by two items with different weights, and the Top-N locations are the recommendation results for a user to visit at a given time. Experimental results on two LBSN datasets demonstrate that the proposed model gets much higher precision and recall value than the other three recommendation methods.

     

基于朴素贝叶斯算法的中文评论分类

针对中文评论分类问题,采用朴素贝叶斯算法进行深入研究.首先,根据中文评论分类的需求设计了朴素贝叶斯分类器;然后,使用WEKA以不同特征提取方式对其功能性进行了对比分析.通过一系列的实验数据的横向对比表明,在朴素贝叶斯分类器下采用集成特征选取时文本分类的准确率最佳,准确率达97.65％,验证了朴素贝叶斯分类器在处理中文评论分类问题的可应用性.     

Visible light localization algorithm based on multi-measurements constraints

In the indoor visible light transmission environment with complex noise, traditional received signal strength indication(RSSI)localization algorithm and imaging localization algorithm are unable to accurately determine the reason of the inaccurate localization model and inadequate constraints of position coordinates. In order to solve the problems, a visible light localization algorithm based on multi-measurements constraints is presented in the paper. The algorithm first constructs a joint localization state space model based on RSSI localization and the imaging localization algorithm. Then, states, measurements and their equations are constructed based on the space model. Finally, the equations are resolved using the unscented Kalman filter(UKF). Compared with RSSI localization and imaging localization, simulation results show that the RMSE of the proposed algorithm could be closer to the Cramer Rao bound. Besides, the localization probability of the proposed algorithm is higher than that of RSSI localization and imaging localization algorithm.     

Load identification in one dimensional structure based on hybrid finite element method

The new hybrid elements are proposed by combing modified Hermitian wavelet elements with ANASYS elements. Then hybrid elements are substituted into finite element formulations to solve the load identification. Transfer matrix can be constructed by using the inverse Newmark algorithm and hybrid finite element method. Loads can obtain through the responses and the transfer matrix. Load identification law was studied under different excitation cases in rod and Timoshenko beam. Regularization method is adopted to solve ill-posed inverse problem of load identification. Compared with ANSYS results, hybrid elements and HCSWI elements can accurately identify the applied load. Numerical results show that the algorithm of hybrid elements is effective. The accuracy of hybrid elements and HCSWI elements can be verified by comparing the load identification result of ANASYS elements with the experiment data. Hermitian wavelet finite element methods have high accuracy advantage but it is difficult to apply the engineering practice. In practical engineering, complex structure can be analyzed by using the hybrid finite element methods which can be obtained the high accuracy in the crucial component.