Dynamic Matching-Based Spectrum Detection in Cognitive Radio Networks

Cognitive Radio Network provides an opportunity to reduce the spectrum resource crisis by allowing secondary users to access the idle spectrum allocated to primary users. The precondition of spectrum sharing is to obtain the Spectrum Availability Information(SAI). Energy detection is a typical technology to get SAI. With the mobility of primary users, the energy received by secondary users varies greatly with the distance from the target primary users. Most of the existing energy detection algorithms that use fixed thresholds are not suitable. We propose a Dynamic Matching-Based Spectrum Detection(DMBSD) scheme which can detect sensing data, reduce the impact of malicious data and make final sensing results more accurate with dynamic threshold setting and data matching. Simulation results show that the proposed scheme can detect tempered data, and increase detection probability by decreasing false alarm probability and missed detection probability.

Geo-Social Profile Matching Algorithm for Dynamic Interests in Ad-Hoc Social Network

Among mobile users, ad-hoc social network (ASN) is becoming a popular platform to connect and share their interests anytime anywhere. Many researchers and computer scientists investigated ASN architecture, implementation, user experience, and different profile matching algorithms to provide better user experience in ad-hoc social network. We emphasize that strength of an ad-hoc social network depends on a good profile-matching algorithm that provides meaningful friend suggestions in proximity. Keeping browsing history is a good way to determine user’s interest, however, interests change with location. This paper presents a novel profile-matching algorithm for automatically building a user profile based on dynamic GPS (Global Positing System) location and browsing history of users. Building user profile based on GPS location of a user provides benefits to ASN users as this profile represents user’s dynamic interests that keep changing with location e.g. office, home, or some other location. Proposed profile-matching algorithm maintains multiple local profiles based on location of mobile device.

Inertia Matching During Dynamic Simulation of Vehicle Drive System on Test Bench

Framework and basic parameters of a test bench for motor drive system of electric vehicle (EV) are illuminated. Two kinds of electric drive models, one was for the electric vehicle drived on real road, the other was for that on test bench, are put forward. Then, dynamic analysis of these models is made in detail. Inertia matching method of the test bench is researched and some useful formulas and graphs are brought forward. The experiment of an electric bus is introduced in order to explain the usage of this inertia matching method.

Hierarchical adaptive stereo matching algorithm for obstacle detection with dynamic programming

An adaptive weighted stereo matching algorithm with multilevel and bidirectional dynamic programming based on ground control points (GCPs) is presented. To decrease time complexity without losing matching precision, using a multilevel search scheme, the coarse matching is processed in typical disparity space image, while the fine matching is processed in disparity-offset space image. In the upper level, GCPs are obtained by enhanced volumetric iterative algorithm enforcing the mutual constraint and the threshold constraint. Under the supervision of the highly reliable GCPs, bidirectional dynamic programming framework is employed to solve the inconsistency in the optimization path. In the lower level, to reduce running time, disparity-offset space is proposed to efficiently achieve the dense disparity image. In addition, an adaptive dual support-weight strategy is presented to aggregate matching cost, which considers photometric and geometric information. Further, post-processing algorithm can ameliorate disparity results in areas with depth discontinuities and related by occlusions using dual threshold algorithm, where missing stereo information is substituted from surrounding regions. To demonstrate the effectiveness of the algorithm, we present the two groups of experimental results for four widely used standard stereo data sets, including discussion on performance and comparison with other methods, which show that the algorithm has not only a fast speed, but also significantly improves the efficiency of holistic optimization.

An Incremental Graph Pattern Matching Based Dynamic Cold-Start Recommendation Method

In order to give accurate recommendations for cold-start user, researchers use social network to find similar users. These efforts assume that cold-start user’s social relationships are static. However social relationships of cold-start user may change as time pass by. In order to give accurate and timely in manner recommendations for cold-start user, it is need to update social relationship continuously. In this paper, we proposed an incremental graph pattern matching based dynamic cold-start recommendation method (IGPMDCR), which updates similar users for cold-start user based on topology of social network, and gives recommendations based on the latest similar users’ records. The experimental results show that, IGPMDCR could give accurate and timely in manner recommendations for cold-start user.

Improved HardNet and Stricter Outlier Filtering to Guide Reliable Matching

As the fundamental problem in the computer vision area,image matching has wide applications in pose estimation,3D reconstruction,image retrieval,etc.Suffering from the influence of external factors,the process of image matching using classical local detectors,e.g.,scale-invariant feature transform(SIFT),and the outlier filtering approaches,e.g.,Random sample consensus(RANSAC),show high computation speed and pool robustness under changing illumination and viewpoints conditions,while image matching approaches with deep learning strategy(such as HardNet,OANet)display reliable achievements in large-scale datasets with challenging scenes.However,the past learning-based approaches are limited to the distinction and quality of the dataset and the training strategy in the image-matching approaches.As an extension of the previous conference paper,this paper proposes an accurate and robust image matching approach using fewer training data in an end-to-end manner,which could be used to estimate the pose error This research first proposes a novel dataset cleaning and construction strategy to eliminate the noise and improve the training efficiency;Secondly,a novel loss named quadratic hinge triplet loss(QHT)is proposed to gather more effective and stable feature matching;Thirdly,in the outlier filtering process,the stricter OANet and bundle adjustment are applied for judging samples by adding the epipolar distance constraint and triangulation constraint to generate more outstanding matches;Finally,to recall the matching pairs,dynamic guided matching is used and then submit the inliers after the PyRANSAC process.Multiple evaluation metrics are used and reported in the 1st place in the Track1 of CVPR Image-Matching Challenge Workshop.The results show that the proposed method has advanced performance in large-scale and challenging Phototourism benchmark.

加权3D-Matching的改进算法

Matching问题构成了一类重要的NP难问题.此类问题在诸多领域中有着重要的应用,如调度、代码优化等领域.对于加权3D-matching问题,通过深入分析问题的结构特性,可以转化成加权3D-matching augmentation问题进行求解,即从一个最大加权的k-matching着手构造权值最大的(k+1)-matching.从问题的特殊结构特性出发,给出了加权3D-matching augmentation问题特有的性质:k-matching中存在2列使得该2列至少有2k/3元素被包含在(k+1)-matching中所对应的2列中.基于给出的性质,通过运用color-coding和动态规划技术,给出了一个时间复杂度为O*(4.823k)的参数算法,最终求解加权3D-matching问题.该算法较目前文献中的最好结果O*(5.473k)有了极大的改进.

Adaptive key SURF feature extraction and application in unmanned vehicle dynamic object recognition

A new method based on adaptive Hessian matrix threshold of finding key SRUF( speeded up robust features) features is proposed and is applied to an unmanned vehicle for its dynamic object recognition and guided navigation. First,the object recognition algorithm based on SURF feature matching for unmanned vehicle guided navigation is introduced. Then,the standard local invariant feature extraction algorithm SRUF is analyzed,the Hessian Metrix is especially discussed,and a method of adaptive Hessian threshold is proposed which is based on correct matching point pairs threshold feedback under a close loop frame. At last,different dynamic object recognition experiments under different weather light conditions are discussed. The experimental result shows that the key SURF feature abstract algorithm and the dynamic object recognition method can be used for unmanned vehicle systems.

Transport properties of warm and hot dense iron from orbital free and corrected Yukawa potential molecular dynamics

The equation of states,diffusions,and viscosities of strongly coupled Fe at 80 and 240 eV with densities from 1.6 to 40 g/cm^(3) are studied by orbital-free molecular dynamics,classical molecular dynamics with a corrected Yukawa potential and compared with the results from average atom model.A new local pseudopotential is generated for orbital free calculations.For low densities,the Yukawa model captures the correct ionic interaction behavior around the first peak of the radial distribution function(RDF),thus it gives correct RDFs and transport coefficients.For higher densities,the scaled transformation of the Yukawa potential or adding a short range repulsion part to the Yukawa potential can give correct RDFs and transport coefficients.The corrected potentials are further validated by the force matching method.

CALCULATION AND IMPROVEMENT OF DYNAMIC CHARACTERISTICS OF CENTRIFUGE

The modeling of the rotor support system of a typical centrifuge is discussed. The impedance matching method, cooperating with Riccati transfer matrix method and modal analysis method are adopted to calculate its dynamic characteristics. The influences of the main parts to the critical speeds are analyzed. Based on the analysis, a critical speed in the operating speed range is tuned successfully, and thus the dynamic characteristics of the centrifuge are much improved.

Application of signal sparse decomposition in dynamic test

In dynamic test,sampling rate is high and noise is strong,so a signal sparse decomposition method based on Gabor dictionary is put forward.This method iteratively decomposes the signal with the matching pursuit(MP)algorithm and takes the coherence ratio of the threshold as a condition of iteration termination.Standard MP algorithm is time-consuming,thus an adaptive genetic algorithm is introduced to MP method,which makes computation speed accelerate effectively.Experimental results indicate that this method not only can effectively remove high-frequency noise but also can compress the signal greatly.

Research on Pattern Matching Method of Multivariate Hydrological Time Series

The existing pattern matching methods of multivariate time series can hardly measure the similarity of multivariate hydrological time series accurately and efficiently.Considering the characteristics of multivariate hydrological time series,the continuity and global features of variables,we proposed a pattern matching method,PP-DTW,which is based on dynamic time warping.In this method,the multivariate time series is firstly segmented,and the average of each segment is used as the feature.Then,PCA is operated on the feature sequence.Finally,the weighted DTW distance is used as the measure of similarity in sequences.Carrying out experiments on the hydrological data of Chu River,we conclude that the pattern matching method can effectively describe the overall characteristics of the multivariate time series,which has a good matching effect on the multivariate hydrological time series.

DYNAMIC ANALYSIS OF UNDERGROUND COMPOSITE STRUCTURES UNDER EXPLOSION LOADING

In selecting rational types of underground structures resisting explosion,in order to improve stress states of the structural section and make full use of material strength of each part of the section,the research method of composite structures is presented. Adopting the analysis method of micro-section free body,equilibrium equations,constraint equations and deformation coordination equations are given. Making use of the concept of generalized work and directly introducing Lagrange multiplier specific in physical meaning,the validity of the constructed generalized functional is proved by using variation method. The rational rigidity matching relationship of composite structure section is presented through example calculations.

利用局部特征匹配的运动小目标光流估计

基于深度光流估计的动态背景运动小目标检测,为了保证小目标的检测性能,一般采用较少的下采样次数以维持较高的分辨率,但由此带来了较大的计算耗时。特征匹配是深度光流估计的一个核心处理环节,其耗时在光流估计整体耗时中的占比较大,且对下采样次数非常敏感。据此,提出一种基于局部特征匹配的快速光流估计算法:引入目标运动信息,缩小特征匹配的空间范围,减少待处理的数据量;设计分块局部匹配策略,引入批处理机制,避免出现逐点局部匹配策略数据处理耗时过大问题,实现算法加速。在此基础上,在光流估计获取的光流场上,采用CenterNet网络检测运动目标对应的光流异常区域。从光流估计耗时、检测精度等方面开展了实验验证,结果表明:针对运动小目标检测,分块特征匹配光流估计比全局特征匹配光流估计耗时减少约25%,目标检测性能相当。

基于策略的动态角色分配模型及应用

访问控制是应用系统中的重要问题之一。传统的基于角色的访问控制(RBAC)方案需要预先定义和同步用户-角色赋值关系,这会带来管理成本和同步开销,并且限制了应用系统的灵活性和动态性。文章提出一种基于策略的动态角色分配模型(Policy-based Dynamic Role Assignment Model——PDRA),它无需同步用户就可以自定义角色,并通过策略匹配的方式实现动态分配。模型完全兼容RBAC,可以成为RBAC良好的扩展机制。文章给出了模型的定义和算法,评估了模型的性能,并在华东师范大学的数据治理平台中进行了应用,验证了该方案的可行性和有效性。

弹光调制器动态参数测量与高效驱动匹配研究

为了提高弹光调制器(photoelastic modulator,PEM)的驱动效率,提出了一种基于PEM动态参数测量的阻抗匹配参数计算方法。理论分析了PEM调制幅度与驱动电压大小的关系,建立了PEM及其谐振匹配网络的等效电路模型,在此基础上推导了PEM谐振驱动电压与各个参数的关系,并设计了针对PEM动态测试的测量系统与验证方法。对谐振频率为44.822 kHz的PEM进行各项特性曲线的理论仿真与试验比较,验证了动态测量系统的可靠性,并通过数值仿真得到PEM最优匹配参数。在最优匹配参数附近选取不同匹配参数,测量实际谐振驱动电压,测量结果与仿真曲线相关性达0.996 4,变化趋势在10μF前基本吻合,且在理论最优匹配参数下,实际谐振驱动电压峰值达510 V,优于其他驱动匹配方法,接近理论最大值,相对误差小于1.16%。通过PEM等效动态参数推算的最优匹配参数,可使PEM达到最大驱动效率。

电力物联网用户侧负荷数据动态R-树匹配方法

电力物联网用户侧负荷数据维度较大,导致数据匹配延时时间过长,为了解决上述问题,基于动态R-树实现电力物联网用户侧负荷数据动态匹配。建立负荷计算模型,分析负荷历史运行信息,实现数据检测。通过归一化函数完成归一化处理,提取动态特征,构建动态R-树,确定匹配机制,根据矩阵计算函数完成压缩处理,利用动态匹配算法更新集对R-树内部结构进一步加以修改,在清除矩形之前,利用叶结点的Hash索引得到R-树匹配矩阵,使用Hash搜索准确地找到目标矩形,增强分布与交互仿真中的实时性,实现用户侧负荷数据动态匹配。实验结果表明,研究的动态R-树匹配方法在数据插入、数据匹配、数据维护过程中的延时时间低于48ms,实时性较好。

运营期普速铁路曲线区段异常晃车影响因素研究

为分析某运营期普速铁路160 km/h速度等级曲线区段的异常晃车问题,对晃车区段的轮轨廓形进行测量,分析了晃车区段的实测车体加速度与轨道几何不平顺数据的时频特征,进一步建立了车辆-有砟轨道耦合动力学仿真模型,采用试验研究和仿真计算相结合的方式研究了轮轨匹配特性和欠过超高状态对曲线区段车辆横向稳定性的影响。结果表明:异常晃车曲线区段车体横向加速度较大,存在明显周期性振动,车体横向加速度振动空间频率为0.024 m^(-1),对应波长为42 m;晃车曲线区段内外股钢轨廓形对称性差,外股钢轨轨顶面和轨距角处磨耗更严重,与实测车轮廓形匹配时轮轨接触点在轨顶面上更为集中;与采用LM&CHN60廓形相比,采用实测轮轨廓形通过曲线时的轮对横移量更大,轮对和转向架周期性振动更明显,周期性振动空间频率为0.024 m^(-1),与异常晃车频率相同;运行速度为60 km/h时的轮轴横向力显著增加,运行速度为160 km/h时的脱轨系数和轮重减载率显著增加;在曲线半径为5000 m,超高为25 mm条件下,车辆以60 km/h和160 km/h的运行速度通过曲线时分别属于严重过超高和欠超高状态,车体横向加速度振动频率与转向架蛇行运动和车轮蛇行运动频率接近,显著影响了车辆通过曲线时的动力响应;运行速度为120 km/h时曲线区段车辆动力响应整体较小,由此可见适当的欠超高有助于提升车辆曲线通过能力;由于曲线参数的限制,建议优先采用降速通过的方式减小车辆通过该段曲线时的车辆动力响应,同时通过改善轮轨匹配关系进一步提升车辆曲线通过能力。

一种面向移动端应用的实时目标检测算法

针对目标检测算法部署在移动端存在内存消耗大、精度低等问题,在NanoDet模型的基础上提出一种引入改进注意力机制的轻量级目标检测网络。首先,设计通道双池化及空间双向拆分的注意力模块,在尽可能不增加计算消耗的同时加强网络对感兴趣区域的关注能力;其次,引入空洞卷积及Mish函数增加网络的感受野及特征判别能力,并缩减冗余的降采样单元结构以加快网络的实时性;最后,在MS COCO2017数据集及安卓设备上的实验验证可知,本文算法在少量模型参数下提高了检测准确率,并保证30帧/秒的移动端检测速度,效果优于YOLO系列等轻量级网络。实验结果表明,本文算法参数量较YOLO系列模型参数量更低,更适合移动端和嵌入式设备的实时目标检测场景。

基于GIS的自然资源确权登记数据平台建设与应用

自然资源确权登记是完善自然资源资产产权制度的必要手段,信息化平台的建设能够确保数据的统一登记和精准管理,文章结合GIS技术和空间数据库技术研发了自然资源确权登记数据平台,基于组件式模式开发了数据建库、数据操作、数据应用以及数据质检等功能,可为用于自然资源管理的地理信息系统应用提供一定的技术支撑。