Construction and Enumeration of a Class of Primitive σ-LFSR Sequences

有限域GF(2k)上本原σ-LFSR序列的分量序列均是二元域上具有相同极小多项式的m-序列,已知一条GF(2k)上本原σ-LFSR序列的距离向量,就可以用二元域上的m-序列构造它.研究了一类本原σ-LFSR序列——Z本原σ-LFSR序列距离向量的计算问题.给出了一种GF(2k)上n级Z本原σ-LFSR序列距离向量的计算方法,其主要思想是,利用GF(2k)上1级Z本原σ-LFSR序列的距离向量来计算n级Z本原σ-LFSR序列的距离向量.与其他现有方法相比,该方法的效率更高.更有价值的是,该方法也适用于GF(2k)上n级m-序列距离向量的计算.最后给出了GF(2k)上n级Z本原σ-LFSR序列的计数公式,说明其个数比GF(2k)上n级m-序列更多.     

一类本原σ-LFSR 序列的构造与计数

有限域GF(2k)上本原σ-LFSR序列的分量序列均是二元域上具有相同极小多项式的m-序列,已知一条GF(2k)上本原σ-LFSR序列的距离向量,就可以用二元域上的m-序列构造它.研究了一类本原σ-LFSR序列——Z本原σ-LFSR序列距离向量的计算问题.给出了一种GF(2k)上n级Z本原σ-LFSR序列距离向量的计算方法,其主要思想是,利用GF(2k)上1级Z本原σ-LFSR序列的距离向量来计算n级Z本原σ-LFSR序列的距离向量.与其他现有方法相比,该方法的效率更高.更有价值的是,该方法也适用于GF(2k)上n级m-序列距离向量的计算.最后给出了GF(2k)上n级Z本原σ-LFSR序列的计数公式,说明其个数比GF(2k)上n级m-序列更多.     

本原σ-LFSR序列的若干性质

σ-LFSR是一种基于字的LFSR模型,能充分利用现代CPU的特点,可很好地应用于设计适合快速软件实现的序列密码算法中.但从伪随机特性和资源利用率的角度看,实际应用的σ-LFSR序列必定是本原的.对本原σ-LFSR序列的性质作了较深入的分析,得到了其分位序列之间是线性无关的,并指出分位序列的极小多项式实际是状态转移矩阵的特征多项式;通过引入块Hankel矩阵,给出了一个求本原σ-LFSR序列极小多项式的算法;最后给出了σ-LFSR序列为本原的充要条件.     

本原σ-LFSR的计数研究

针对s-LFSR能够充分利用现代通用CPU且具有结构简单、适合软件快速实现的特点,利用本原s-LFSR的距离向量和基判别定理,将本原s-LFSR的计数问题转化为线性空间上基的问题,以此为基础,利用F2上次数小于n的互素多项式的对数解决F4上本原s-LFSR的计数问题.     

基于SIMD技术的σ-LFSR

σ-线性反馈移位寄存器(σ-LFSR)是一类适合软件快速实现的新型反馈移位寄存器。结合第二代单指令多数据流扩展指令集SSE2,设计了一类基于SIMD技术的σ-LFSR。这类σ-LFSR充分利用SSE2提供的128bit整数数据结构及其操作,获得了非常高的软件实现效率,同时其输出序列达到了最大周期并具有良好的随机性。所得结论表明这类基于SIMD技术的σ-LFSR可以作为适合软件实现的高速序列密码驱动部分。     

本原?-LFSR序列距离向量性质研究

根据不同类距离向量的分量大小关系,对本原?-LFSR的距离向量进行分类,每一个距离向量有n!个等价类。通过研究距离向量的基本性质,得到一类Z本原?-LFSR的距离向量的期望为(0, T/2, T/2,…, T/2),在此基础上给出2种Z本原?-LFSR的构造方法。对距离向量和线性复杂度之间的关系进行讨论,得出距离向量到线性复杂度是一个满射的结论。     

A trinomial type of σ-LFSR oriented toward software implementation

In this paper, we introduce a new type of feedback shift register based on words, called σ-linear feedback shift register (σ-LFSR) which can make full use of the instructions of modern CPUs so that we can find good σ-LFSR with simple structure and fast software implementation. After analysis, we find a class of simple σ-LFSR with maximal period and give an algorithm of searching for those σ-LFSRs. As a result, we provide a new optional fast component in the design of modern word-based stream ciphers.     

面向大数据的图模式挖掘概率算法

在当今大数据时代,MapReduce等大数据处理框架处理数据能力有限,其在处理有关图的数据时常常显得缓慢低效,典型如3-clique计数问题,故需要探究一种高效的算法处理这类clique计数问题。由于在前人文献中对3-clique计数问题已有深入探讨,故针对该问题的扩展版本—4-clique计数问题进行探究。在一个启发式的想法下提出了基于邻边采样的概率采样算法,利用切诺夫不等式证明该算法在近似条件下只需要一定数量的采样器作为相对误差的性能保证。通过实验评估对比发现,相对于传统精确算法,概率采样算法虽然在结果上损失了少量的精度,但在算法运行时间和空间占用上具有巨大的优势。最后得出其在实际应用中具有巨大实践价值的结论。     

环Z/(pe)上最高权位序列模整数的保熵性

本文对环 上本原序列导出的最高权位序列模 的保熵性进行了研究,这里 为任意奇素数, 为任意正整数且 。利用环 上次数为 的本原多项式导出的本原序列元素分布的性质,对上述最高权位序列保熵性成立的充分条件进行了构造。同时当本原多项式的次数 足够大时,其本原多项式构造的本原序列导出最高权位序列的保熵性是严格成立的。结果表明,这类最高权位序列与环 上本原序列一样具有模 的保熵性。因此,使用此类序列构造出的算法能够有效抵抗面向比特的攻击,特别在抵抗代数攻击和快速相关攻击上有极其重要的作用。     

甲基定位效应的密度泛函理论研究

以苯、甲苯及甲苯氯化反应所形成的σ络合物(中间体)为研究对象,运用密度泛函理论的B3LYP法,在6-311GDK21**水平上优化计算,并寻找σ络合物相互转化的过渡态.算出苯和甲苯的电荷分布、σ络合物的能量与电荷分布,以及σ络合物之间相互转化的过渡态的结构参数和能量.从电荷密度、σ络合物的稳定性及其相互转化机理3个方面,解释甲基的邻、对位的定位效应.为进一步研究取代基的定位效应,提供一些理论依据.     

Faster CNN-based vehicle detection and counting strategy for fixed camera scenes

Automatic detection and counting of vehicles in a video is a challenging task and has become a key application area of traffic monitoring and management. In this paper, an efficient real-time approach for the detection and counting of moving vehicles is presented based on YOLOv2 and features point motion analysis. The work is based on synchronous vehicle features detection and tracking to achieve accurate counting results. The proposed strategy works in two phases; the first one is vehicle detection and the second is the counting of moving vehicles. Different convolutional neural networks including pixel by pixel classification networks and regression networks are investigated to improve the detection and counting decisions. For initial object detection, we have utilized state-of-the-art faster deep learning object detection algorithm YOLOv2 before refining them using K-means clustering and KLT tracker. Then an efficient approach is introduced using temporal information of the detection and tracking feature points between the framesets to assign each vehicle label with their corresponding trajectories and truly counted it. Experimental results on twelve challenging videos have shown that the proposed scheme generally outperforms state-of-the-art strategies. Moreover, the proposed approach using YOLOv2 increases the average time performance for the twelve tested sequences by 93.4% and 98.9% from 1.24 frames per second achieved using Faster Region-based Convolutional Neural Network (F R-CNN ) and 0.19 frames per second achieved using the background subtraction based CNN approach (BS-CNN ), respectively to 18.7 frames per second.

     

教室电铃的PLC自动控制装置

本文介绍了采用Ｆ１系列ＰＬＣ控制教室电铃的装置，实践证明，性能可靠，计时准确，使用方便，有推广应用价值。     

An efficient online citrus counting system for large-scale unstructured orchards based on the unmanned aerial vehicle

The accurate detection and counting of fruits in natural environments are key steps for the early yield estimation of orchards and the realization of smart orchard production management. However, existing citrus counting algorithms have two primary limitations: the performance of counting algorithms needs to be improved, and their system operation efficiency is low in practical applications. Therefore, in this paper, we propose a novel end-to-end orchard fruit counting pipeline that can be used by multiple unmanned aerial vehicles (UAVs) in parallel to help overcome the above problems. First, to obtain on-board camera images online, an innovative UAV live broadcast platform was developed for the orchard scene. Second, for this challenging specific scene, a detection network named Citrus-YOLO was designed to detect fruits in the video stream in real-time. Then, the DeepSort algorithm was used to assign a specific ID to each citrus fruit in the online UAV scene and track the fruits across video frames. Finally, a nonuniform distributed counter was proposed to correct the fruit count during the tracking process, and this can significantly reduce the counting errors caused by tracking failure. This is the first work to realize online and end-to-end counting in a field orchard environment. The experimental results show that the F1 score and mean absolute percentage error of the method are 89.07% and 12.75%, respectively, indicating that the system can quickly and accurately achieve fruit counting in large-scale unstructured citrus orchards. Although our work is discussed in the context of fruit counting, it can be extended to the detection, tracking and counting of a variety of other objects of interest in UAV application scenarios     

Finite element MAC scheme in general curvilinear coordinates

A combined study of F.D. and F.E. methods for 2-D incompressible Navier-Stokes flows is undertaken. In primitive variable formulation, major difficulties are connected to spurious numerical oscillations which may arise from the enforcement of the incompressibility constraint. With regard to this problem, various F.D. schemes differ essentially according to the variable location on the mesh points, while F.E. schemes are analogously differentiated by the interpolation functions adopted for the different variables. In the present paper, we propose an F.E. analog of MAC scheme, which can be accomplished by different interpolation functions for the two velocity components. This new F.E. scheme-although based on low order approximations-eliminates all spurious oscillations. The extension to curvilinear quadrilateral elements—which is needed in order to achieve geometrical versatility—requires the problem to be formulated in general curvilinear coordinates and the contravariant velocity components to be assumed as variables. Some numerical results are presented and discussed, in order to assess the capabilities of the proposed model.     

USB接口的多功能容栅传感器测量系统

根据容栅传感器的原理与带USB模块的C8051F321单片机,设计了一套基于USB接口的测量系统。该系统能实现最大数跟踪、最小数跟踪、示值保持和清零等功能,通过USB接口与上位机交换数据。系统中采用LM393芯片将传感器信号电平转换为CMOS电平,采用光耦隔离技术等增强系统的抗干扰能力。     

基于谷歌眼镜传感器的曲线拟合计步算法

当前独立的计步器普遍要考虑行人佩戴的部位,如基于手机的计步方法可靠性受限于手机放置位置。根据谷歌眼镜的位置固定特性设计了一种新的计步算法,有效地解决了平地、斜坡、上下楼梯等场景下的计步问题。该算法综合运用谷歌眼镜采集的加速度传感器信号和旋转矢量传感器信号,对这些信号进行快速傅里叶变换滤波处理,用二次曲线拟合信号序列,根据曲线参数阈值进行计步判断。实验结果表明：该算法在平地、斜坡、上下楼梯等场景具有96%以上的准确率。     

基于MSP430的输液滴速监视仪设计

介绍一种基于光电开关、MSP430F149单片机、LCM12864Z5液晶屏和键盘的输液滴速监视仪;利用MSP430F149单片机外部中断将光电开关转换出的输液液滴矩形脉冲进行数据处理,计算出输液速度和输液量,同时预算出输液的剩余时间,并将结果显示在液晶屏上,使输液治疗变得更加方便和安全;对系统的硬件组成、工作原理和软件设计进行了描述;实验测试结果表明,系统检测精度高,输液速度调节响应快,运行可靠,且功耗少,成本低,操作方便.     

Local Limit Properties for Pattern Statistics and Rational Models

Motivated by problems of pattern statistics, we study the limit distribution of the random variable counting the number of occurrences of the symbol a in a word of length n chosen at random in {a,b}^*, according to a probability distribution defined via a rational formal series s with positive real coefficients. Our main result is a local limit theorem of Gaussian type for these statistics under the hypothesis that s is a power of a primitive series. This result is obtained by showing a general criterion for (Gaussian) local limit laws of sequences of integer random variables. To prove our result we also introduce and analyse a notion of symbol-periodicity for irreducible matrices, whose entries are polynomials over positive semirings; the properties we prove on this topic extend the classical Perron--Frobenius theory of non-negative real matrices. As a further application we obtain some asymptotic evaluations of the maximum coefficient of monomials of given size for rational series in two commutative variables.     

Inception single shot multi-box detector with affinity propagation clustering and their application in multi-class vehicle counting

Multi-class vehicle detection and counting in video-based traffic surveillance systems with real-time performance and acceptable precision are challenging. This paper proposes a modified single shot multi-box convolutional neural network named Inception-SSD (ISSD) for vehicle detection and a centroid matching algorithm for vehicle counting. An Inception-like block is introduced to replace the extra feature layers in the original SSD to deal with the multi-scale vehicle detection to enhance smaller vehicles’ detection. Non-Maximum Suppression (NMS) is replaced with Affinity Propagation Clustering (APC) to improve the detection of nearby occluded vehicles. For a 300 × 300 input image, on PASCAL VOC 2007 test data set, the proposed ISSD achieved 79.3 mean Average Precision (mAP) and ran on an NVIDIA RTX2080Ti; the network attains a speed of 52.3 frames per second. ISSD with APC generates 2.7% improvement in mAP over original SSD300 while almost retaining its time efficiency. By centroid matching algorithm, the vehicles are counted class-wise with a weighted F1 of 98.5%, which is quite superior to the other recent existing research works.