数据流中基于最近数据的动态维护Generator表示法

数据流中频繁的数据更新使得重新挖掘整个数据集显得比较困难。该文提出了在数据流中,基于最近数据的动态维护Generator表示方法。通过界定边界项集,使得由数据更新可能引起的项集变化能在边界集中被检测到,而无须保存所有频繁集,使处理限定在仅与更新相关的项集范围之内,取得了较好效果。

Fault Attack on the Balanced Shrinking Generator

Fault analysis, belonging to indirect attack, is a cryptanalysis technique for the physical implementation of cryptosystem. In this paper, we propose a fault attack on the Balanced Shrinking Generator. The results show that the attacker can obtain the secret key by analyzing faulty output sequences which is produced by changing control clock of one of Linear Feedback Shift Registers （LFSR）. Therefore, the balanced shrinking generator has a trouble in hardware implementation.

PROBABILITY MODEL OF GUNTHER GENERATOR

This paper constructs the probability model of Gunther generator at first, and the finite dimension union distribution of the output sequence is presented. The result shows that the output sequence is an independent and uniformly distributed 0,1 random variable sequence. It gives the theoretical foundation about why Gunther generator can avoid the statistic weakness of the output sequence of stop-and-go generator, and analyzes the coincidence between output sequence and input sequences of Gunther generator. The conclusions of this paper would offer theoretical references for designers and analyzers of clock-controlled generators.

Weak generalized self-shrinking generators

The security of certain classes of the generalized self-shrinking sequence （GSS） generators is analyzed. Firstly, it is shown that the security of these GSS generators is equivalent to the security of the GSS generators of the class-1, after which two effective key recovery attacks on the GSS generators of the class-1 are developed to evaluate their security.

STUDY ON STREAM CIPHERS USING GENERATING FUNCTIONS

Several kinds of stream ciphers—complementary sequences of period sequences,partial sum of period sequences,inverse order sequences and finitely generated sequences,arestudied by using techniques of generating functions.Their minimal polynomials,periods,as wellas generating functions are given.As to finitely generated sequences,the change of their linearcomplexity profiles as well as the relationship between the two generated sequences usder thecase in which the degree of connected polynomials are fixed,are discussed.

Stability Enhancement of Small-Scale Power Grid with Renewable Power Sources by Variable Speed Diesel Power Plant

This paper proposes a power control method to improve a stability of a small-scale power grid with renewable energy sources. In an isolated small- scale power grid such as an island, diesel power plant is main power source which has an environmental burden and expensive running cost due to high priced fossil fuel. Thus, expanding installation of the renewable energy sources such as a wind power is strongly desirable. Such fluctuating energy sources, however, harm power quality of the small-scale power grid, and in addition, conventional power plant in the small-scale power grid cannot, in general, stabilize the grid system with such fluctuating power sources. In this study, Variable Speed Doubly-Fed Induction Generator (VS-DFIG) is proposed to be in-stalled at a diesel power plant instead of a conventional Fixed Speed Synchronous Generator (FS-SG), because quick control of a power balance in the small-scale power grid can be achieved by using the inertial energy of VS-DFIG. In addition, utilization of a Battery Energy Storage System (BESS) is also considered to assist cooperatively the VS-DFIG control. As a result of the simulation analysis by using the proposed method, it is verified that frequency fluctuations due to renewable energy source can be effectively reduced by quick power control of the VS-DFIG compared to the conventional FS-SG, and further control ability can be obtained by utilizing BESS. Moreover, the transient stability of a small-scale power grid during a grid fault can also be enhanced.

SELECTION OF THE LINEAR COMBINING VECTOR G OF THE GENERALIZED SELF-SHRINKING GENERATORS

Given an m-sequence, the main factor influencing the least period of the Generalized Self-Shrinking (GSS) sequence is the selection of the linear combining vector G. Based on the calculation of the minimal polynomial of L GSS sequences and the comparison of their degrees, an algorithm for selecting the linear com-bining vector G is presented, which is simple to understand, to implement and to prove. By using this method, much more than 2L?1 linear combining vectors G of the desired properties will be resulted. Thus in the practical application the linear combining vector G can be chosen with great arbitrariness. Additionally, this algorithm can be extended to any finite field easily.

基于GPU的北斗B1宽带复合信号实时发生器设计

为了实现北斗B1C+B1I信号的联合生成,提出一种基于软件无线电和图形处理器(graphics processing unit,GPU)加速的北斗B1宽带复合信号的实时生成方法,该方法针对单边带复数二进制偏移载波(single-sideband complex binary offset carrier,SCBOC)调制方式的信号体制进行设计,系统根据用户配置的接收机运动轨迹和星历文件,生成中频信号并通过射频端发射。为了进一步提升GPU并行运算速度,从优化设备内存结构、设计并行线程架构和统一计算设备架构流(compute unified device architecture stream,CUDA)加速3个方面,设计了基于异步运算的加速采样点数据计算的CUDA优化实现方案。测试结果证明,优化后的算法可以基于SCBOC调制实时生成北斗B1I+B1C信号,基于GTX3060的GPU平台,信号90 M采样率下能实现8颗卫星复合信号的实时生成。

公平与认同:普职分流政策民众阻抗的舆情分析与教育治理改进

职业教育是培养高素质技术技能人才与促进经济社会高质量发展的基础性工程,在教育系统中具有独特价值。然而,当前职业教育社会认同度并不理想。在新《中华人民共和国职业教育法》出台后,“取消初中毕业后普职分流”的政策误读迅速引爆了各大媒体的热搜。本研究借助NVivo12.0对广大民众网络评论进行深入分析后发现,职业教育在入口公平、过程公平、结果公平上存在较大的社会争论。普职分流争议的根源在于职业教育存在社会偏见严重、体系不够完善、质量参差不齐、结果公平欠佳等问题。因此,提升职业教育社会认同度需要树立科学观念,完善职业教育体系,加强内涵建设,优化职教高考制度,改善评价环境。

Linear complexity of Ding generalized cyclotomic sequences

Minimal polynomials and linear complexity of binary Ding generalized cyclotomic sequences of order 2 with the two-prime residue ring Zpq are obtained by Bai in 2005. In this paper, we obtain linear complexity and minimal polynomials of all Ding generalized cyclotomic sequences. Our result shows that linear complexity of these sequences takes on the values pq and pq-1 on our necessary and sufficient condition with probability 1/4 and the lower bound （pq - 1）/2 with probability 1/8. This shows that most of these sequences are good. We also obtained that linear complexity and minimal polynomials of these sequences are independent of their orders. This makes it no more difficult in choosing proper p and q.

Incremental Learning Framework for Mining Big Data Stream

At this current time,data stream classification plays a key role in big data analytics due to its enormous growth.Most of the existing classification methods used ensemble learning,which is trustworthy but these methods are not effective to face the issues of learning from imbalanced big data,it also supposes that all data are pre-classified.Another weakness of current methods is that it takes a long evaluation time when the target data stream contains a high number of features.The main objective of this research is to develop a new method for incremental learning based on the proposed ant lion fuzzy-generative adversarial network model.The proposed model is implemented in spark architecture.For each data stream,the class output is computed at slave nodes by training a generative adversarial network with the back propagation error based on fuzzy bound computation.This method overcomes the limitations of existing methods as it can classify data streams that are slightly or completely unlabeled data and providing high scalability and efficiency.The results show that the proposed model outperforms stateof-the-art performance in terms of accuracy(0.861)precision(0.9328)and minimal MSE(0.0416).

The Application of the Generalized Differential Formulation of the First Law of Thermodynamics for Evidence of the Tidal Mechanism of Maintenance of the Energy and Viscous-Thermal Dissipative Turbulent Structure of the Mesoscale Oceanic Eddies

The practical significance of the established generalized differential formula-tion of the first law of thermodynamics (formulated for the rotational coor-dinate system) is evaluated (for the first time and for the mesoscale oceanic eddies) by deriving the general (viscous-compressible-thermal) and partial (incompressible, viscous-thermal) local conditions of the tidal maintenance of the quasi-stationary energy and dissipative turbulent structure of the mesoscale eddy located inside of the individual fluid region of the ther-mally heterogeneous viscous (compressible and incompressible, respective-ly) heat-conducting stratified fluid over the two-dimensional bottom topog-raphy characterized by the horizontal coordinate x along a horizon-tal axis X. Based on the derived partial (incompressible) local condition (of the tidal maintenance of the quasi-stationary energy and viscous-thermal dis-sipative turbulent structure of the mesoscale eddy) and using the calculated vertical distributions of the mean viscous dissipation rate per unit mass and the mean thermal dissipation rate per unit mass in four regions near the observed mesoscale (periodically topographically trapped by nearly two-dimensional bottom topography h(x) eddy located near the northern region of the Yamato Rise in the Japan Sea, the combined analysis of the energy structure of the eddy and the viscous-thermal dissipative structure of turbulence is presented. The convincing evidence is presented of the tidal mechanism of maintenance of the eddy energy and viscous-thermal dissipa-tive structure of turbulence (produced by the breaking internal gravity waves generated by the eddy) in three regions near the Yamato Rise subjected to the observed mesoscale eddy near the northern region of the Yamato Rise of the Japan Sea.

Candidate members of the Pal 5, GD-1, Cetus Polar and Orphan tidal stellar halo streams from SDSS DR9, LAMOST DR3 and APOGEE catalogs

We present candidate members of the Pal 5, GD-1, Cetus Polar and Orphan tidal stellar streams found in LAMOST DR3, SDSS DR9 and APOGEE catalogs. In LAMOST DR3, we find 20, 4 and 24 high confidence candidates of tidal streams GD-1, Cetus Polar and Orphan respectively. We also list 59, 118 and 10 high confidence candidates of tidal streams Cetus Polar, Orphan and Pal 5, respectively from the SDSS DR9 spectroscopic catalog. Furthermore, we find seven high confidence candidates of the Pal 5 tidal stream in the APOGEE data. Compared with SDSS, the new candidates from LAMOST DR3 are brighter, so that together, more of the color-magnitude diagram, including the giant branch, can be explored. Analysis of the SDSS data shows that there are three metallicity peaks associated with the Orphan stream which also exhibit some spatial separation. The LAMOST data confirm multiple metallicities in this stream. The metallicity, given by the higher resolution APOGEE instrument, of the Pal 5 tidal stream is [Fe/H] ,- -1.2, higher than that given earlier by SDSS spectra. Many previously unidentified stream members are tabulated here for the first time, along with existing members, allowing future researchers to further constrain the orbits of these objects as they move within the Galaxy＇s dark matter potential.

Single-particle 3D reconstruction on specialized stream architecture and comparison with GPGPUs

The wide acceptance and data deluge in medical imaging processing require faster and more efficient systems to be built.Due to the advances in heterogeneous architectures recently,there has been a resurgence in the first research aimed at FPGA-based as well as GPGPU-based accelerator design.This paper quantitatively analyzes the workload,computational intensity and memory performance of a single-particle 3D reconstruction application,called EMAN,and parallelizes it on CUDA GPGPU architectures and decouples the memory operations from the computing flow and orchestrates the thread-data mapping to reduce the overhead of off-chip memory operations.Then it exploits the trend towards FPGA-based accelerator design,which is achieved by offloading computingintensive kernels to dedicated hardware modules.Furthermore,a customized memory subsystem is also designed to facilitate the decoupling and optimization of computing dominated data access patterns.This paper evaluates the proposed accelerator design strategies by comparing it with a parallelized program on a 4-cores CPU.The CUDA version on a GTX480 shows a speedup of about 6 times.The performance of the stream architecture implemented on a Xilinx Virtex LX330 FPGA is justified by the reported speedup of 2.54 times.Meanwhile,measured in terms of power efficiency,the FPGA-based accelerator outperforms a 4-cores CPU and a GTX480 by 7.3 times and 3.4 times,respectively.

生成对抗网络协同角度异构中心三元组损失的跨模态行人重识别

基于红外与可见光域之间的跨模态行人重识别对于夜间场景监控极为重要,但由于红外图像和可见光图像的数据分布存在较大差异,使得模型很难提取到同一行人在不同模态下的模态不变特征.本文针对现有跨模态行人重识别算法中存在的数据集样本数量较少问题以及不同模态图像之间存在较大跨模态差异问题,提出了一种新颖的生成对抗网络来生成与原始图像相似的匹配图像,在对跨模态行人数据集进行增广的同时减少跨模态差异;为减少跨模态差异和模态内差异,本文采用了双流网络来提取更具鉴别性特征,并提出了角度异构中心三元组损失对正负样本在特征空间中夹角进行约束,提升其在特征空间中的聚类效果.本文在SYSU-MM01和RegDB数据集上进行实验验证,结果表明本文所提出的生成匹配图像方法能够有效降低不同模态图像之间的跨模态差异,同时角度异构中心三元组损失使得特征空间中的嵌入特征具有角度辨别性,从而提升模型的分类能力.在SYSU-MM01数据集中,本文方法相较于最新算法在Rank-1和mAP分别提升了5.71%和8.18%,证实了文中方法的有效性.

试飞遥测实时监控分析报告自动生成系统设计

为提高试飞遥测实时监控系统数据分析综合能力,优化实时监控服务质量,面向遥测数据量大、高实时计算的遥测实时监控场景,设计一种实时监控分析报告自动生成系统。系统基于Hadoop的大数据分布式框架设计,以SpringBoot敏捷开发框架搭建,采用流式计算引擎Storm用于实时数据计算、离线计算引擎Spark用于数据统计分析,具备数据实时采集、数据实时计算、数据统计分析、数据分类存储以及监控报告管理核心功能。目前,系统已经在国产某大型客机飞行试验过程中使用,满足在飞行结束后3 min内自动生成本架次全历程监控分析报告,可作为快速评价试飞过程的辅助决策手段,对于缩短试飞周期、提高试飞效率具有重要意义。

FRTDS的仿真脚本优化和指令流生成策略

为提高FRTDS的仿真规模,本文提出一种仿真脚本优化方案及指令流生成策略。在仿真脚本生成过程中,以子网络的预计算方法、框架网络的求解方法为优化对象,以仿真脚本的执行时间最短为优化目标,采用遗传算法对仿真脚本进行了综合优化。在指令流生成过程中,采用兼顾最晚执行时间和通信距离的多批次策略选择待执行任务及其运算核,按照通信资源消耗量确定待执行任务的数据源及其传输通道,减轻通信资源匮乏对仿真脚本执行时间的影响。对含106电平双端PFB-MMC交直交电力系统进行了实时仿真,验证了所提方法的有效性。

基于多源数据的产业区域协同发展评价体系研究——以珠三角新一代电子信息产业集群为例

采用企业大数据、手机信令等多源数据,从城际间产业集群的潜在关联、实际关联2个维度,构建产业集群区域协同发展评价体系,以珠三角城市群新一代电子信息产业集群为例,研究发现:1)珠三角城市群以深圳、东莞、广州为核心,形成较为完善的新一代电子信息产业链网络,从潜在关联看:同质化水平较高且围绕着各都市圈表现出专业化分工趋势;从实际关联看:核心城市资金交往紧密、各都市圈内出行关联密切。2)珠三角新一代电子信息产业集群协同发展显著的是深圳与东莞、深圳与广州、珠海与中山、中山与江门,其中深圳与东莞表现为差异化强合作;珠三角核心城市间协同关系较好,但边缘城市有所不足,总体协同水平不高。该评价体系可用于测量城际产业集群的协同发展,有助于城市规划和政策制定,促进地区经济的可持续增长,并为其他城市群的产业协同发展提供参考和借鉴。