Research on the High Robustness JavaEE Enterprise Development Mode based on Hadoop and Cloud Servers

In this paper, we conduct research on the high robustness JavaEE enterprise development mode based on Hadoop and cloud servers. The current virtual machine real-time migration can only achieve manual migration, and cannot achieve full-automatic migration. In other words, when the server overload requires the administrator to artificially select a low-load host, and then hit migration command to implement the migration. In recent years, the Hadoop is becoming popular, and the read performance of the data is measured in terms of the time overhead for reading the required data. The key to reducing read time is to optimize that Hadoop cloud data read time and the RDBMS data query time. This paper integrates the mentioned techniques to construct the novel JavaEE enterprise development pattern that will promote the further development of the related techniques.

Boundary states for entanglement robustness under dephasing and bit flip channels

We investigate the robustness of entanglement for a multiqubit system under dephasing and bit flip channels. We exhibit the difference between the entanglement evolution of the two forms of special states, which are locally unitarily equivalent to each other and therefore possess precisely the same entanglement properties, and demonstrate that the difference increases with the number of qubits n. Moreover, those two forms of states are either the most robust genuine entangled states or the most fragile ones, which confirm that local unitary(LU) operations can greatly enhance the entanglement robustness of n-qubit states.

A robust triaxial localization method of AE source using refraction path

Acoustic emission(AE)localization algorithms based on homogeneous media or single-velocity are less accurate when applied to the triaxial localization experiments.To the end,a robust triaxial localization method of AE source using refraction path is proposed.Firstly,the control equation of the refraction path is established according to the sensor coordinates and arrival times.Secondly,considering the influence of time-difference-of-arrival(TDOA)errors,the residual of the governing equation is calculated to estimate the equation weight.Thirdly,the refraction points in different directions are solved using Snell’s law and orthogonal constraints.Finally,the source coordinates are iteratively solved by weighted correction terms.The feasibility and accuracy of the proposed method are verified by pencil-lead breaking experiments.The simulation results show that the new method is almost unaffected by the refraction ratio,and always holds more stable and accurate positioning performance than the traditional method under different ratios and scales of TDOA outliers.

基于SQL Server的LAN办公系统的开发应用

分析了一个具体的局域网办公系统的的设计和应用,包括系统的需求、工作流程、数据库设计及开发工具和应用环境;提出了一种从工作流程到数据库设计的新思路,对一般的数据库应用系统的设计具有较好的借鉴和指导意义。系统能够满足一般企事业单位和学校的办公要求,具有及时、可靠、安全和可扩展性等特点。

Windows 2000 Server的网络安全机制

文章分析了Windows 2000 Server的安全问题以及适用策略,为Windows 2000 Server局域网络的安全提供参考。

管理信息系统网络的新结构──Client／Server

总结目前在管理信息系统中计算机局域网络和数据库的作用，介绍了新的网络体系结构──客户／服务器（Ｃｌｉｅｎｔ／Ｓｅｒｖｅｒ）的基本概念和特点，并以实例形式说明了建立一个Ｃｌｉｅｎｔ／Ｓｅｒｖｅｒ结构系统时应注意的三个问题。

以SQL Server为平台搭建C/S模式的局域网

以SQL Server为平台,通过Windows身份验证方式注册SQL Server服务器、搭建C/S模式局域网,是一种比通过SQL Server身份验证方式注册SQL Server服务器,搭建的C/S模式的局域网更为复杂但更安全的方式.该过程以配置服务器并提升为域控制器;在域控制器的Active Directory中新建域用户帐户并授权,SQL Server企业管理器中新建域用户登录帐号;非域控制器主机加入域控制器指定域并以域用户身份登录Windows系统、登录指定域,以Windows身份验证方式访问域控制器上的SQL Server数据库这些步骤进行.

High speed robust image registration and localization using optimized algorithm and its performances evaluation

Local invariant algorithm applied in downward-looking image registration,usually computes the camera＇s pose relative to visual landmarks.Generally,there are three requirements in the process of image registration when using these approaches.First,the algorithm is apt to be influenced by illumination.Second,algorithm should have less computational complexity.Third,the depth information of images needs to be estimated without other sensors.This paper investigates a famous local invariant feature named speeded up robust feature（SURF）,and proposes a highspeed and robust image registration and localization algorithm based on it.With supports from feature tracking and pose estimation methods,the proposed algorithm can compute camera poses under different conditions of scale,viewpoint and rotation so as to precisely localize object＇s position.At last,the study makes registration experiment by scale invariant feature transform（SIFT）,SURF and the proposed algorithm,and designs a method to evaluate their performances.Furthermore,this study makes object retrieval test on remote sensing video.For there is big deformation on remote sensing frames,the registration algorithm absorbs the Kanade-Lucas-Tomasi（KLT） 3-D coplanar calibration feature tracker methods,which can localize interesting targets precisely and efficiently.The experimental results prove that the proposed method has a higher localization speed and lower localization error rate than traditional visual simultaneous localization and mapping（vSLAM） in a period of time.

Anonymous crowdsourcing-based WLAN indoor localization

In order to solve the problem of location privacy under big data and improve the user positioning experience,a new concept of anonymous crowdsourcing-based WLAN indoor localization is proposed by employing the Micro-Electro-Mechanical System(MEMS)motion sensors as well as WLAN module in off-the-shelf smartphones.First of all,the crowdsourced motion traces with similar Received Signal Strength(RSS)sequences are assembled into a motion graph.Second,the mobility map is constructed according to traces segmentation and clustering.Third,the pixel template matching is adopted to physically label the pre-constructed mobility map.Finally,the robust Extended Kalman Filter(EKF)is designed to perform localization by matching the newly-collected RSS measurements against the mobility map.The extensive experimental results show that the proposed approach is capable of constructing a physically-labeled mobility map from the sporadically-collected crowdsourced motion traces as well as achieving satisfactory localization accuracy in a cost-efficient manner.

利用PCI局部总线实现Blade Server的数据交换

通过对刀片服务器基本概念、主要组成以及内部架构的分析和研究,针对刀片与主板之间的高速通信需求,采用PCI总线作为系统的数据通信协议,给出了PCI局部总线的详细分析和设计流程,以及系统所采用的"PCI+FPGA+FLASH"方案的具体实现方法和步骤,最后给出了实际的测试验证结果,相关结论,对设计PCI通信系统具有较强的借鉴意义。

Robust Source Localization in Shallow Water Based on Vector Optimization

Owing to the multipath effect, the source localization in shallow water has been an area of active interest. However, most methods for source localization in shallow water are sensitive to the assumed model of the underwater environment and have poor robustness against the underwater channel uncertainty, which limit their further application in practical engineering. In this paper, a new method of source localization in shallow water, based on vector optimization concept, is described, which is highly robust against environmental factors affecting the localization, such as the channel depth, the bottom reflection coefficients, and so on. Through constructing the uncertainty set of the source vector errors and extracting the multi-path sound rays from the sea surface and bottom, the proposed method can accurately localize one or more sources in shallow water dominated by multipath propagation. It turns out that the natural formulation of our approach involves minimization of two quadratic functions subject to infinitely many nonconvex quadratic constraints. It shows that this problem （originally intractable） can be reformulated in a convex form as the so-called second-order cone program （SOCP） and solved efficiently by using the well-established interior point method, such as the sottware tool, SeDuMi. Computer simulations show better performance of the proposed method as compared with existing algorithms and establish a theoretical foundation for the practical engineering application.

Exchange Server 2007本土化应用探讨

分析Exchange Server 2007在国内面临的问题,进而结合本单位实际,探讨Exchange Server 2007在四个方面所作的本土化应用,最后小结本土化应用所取得的成果,并展望Exchange Server 2007在国内的应用前景。

Block-based logical hierarchical cluster for distributed multimedia architecture on demand server

A structure of logical hierarchical cluster for the distributed multimedia on demand server is proposed. The architecture is mainly composed of the network topology and the resource management of all server nodes. Instead of the physical network hierarchy or the independent management hierarchy, the nodes are organized into a logically hieraxchical cluster according to the multimedia block they caches in the midderware layer. The process of a member joining/leaving or the structure adjustment cooperatively implemented by all members is concerned with decentralized maintenance of the logical cluster hierarchy. As the root of each logically hierarchical cluster is randomly mapped into the system, the logical structure of a multimedia block is dynamically expanded across some regions by the two replication policies in different load state respectively. The local load diversion is applied to fine-tune the load of nodes within a local region but belongs to different logical hierarchies. Guaranteed by the dynamic expansion of a logical structure and the load diversion of a local region, the users always select a closest idle node from the logical hierarchy under the condition of topology integration with resource management.

Robust Local Weighted Regression for Magnetic Map-Based Localization on Smartphone Platform

The magnetic information measured on the smartphone platform has a large fluctuation and the research of indoor localization algorithm based on smart-phone platform is less. Indoor localization algorithm on smartphone platform based on particle filter is studied. Robust local weighted regression is used to smooth the original magnetic data in the process of constructing magnetic map. Use moving average filtering model to filter the online magnetic observation data in positioning process. Compare processed online magnetic data with processed magnetic map collected by smartphone platform and the average matching error is 0.3941uT. Average positioning error is 0.229 meter when using processed online and map data.

An object tracking and global localization method using the cylindrical projection of omnidirectional image

We present an omnidirectional vision system we have implemented to provide our mobile robot with a fast tracking and robust localization capability. An algorithm is proposed to do reconstruction of the environment from the omnidirectional image and global localization of the robot in the context of the Middle Size League RoboCup field. This is accomplished by learning a set of visual landmarks such as the goals and the corner posts. Due to the dynamic changing environment and the partially observable landmarks, four localization cases are discussed in order to get robust localization performance. Localization is performed using a method that matches the observed landmarks, i.e. color blobs, which are extracted from the environment. The advantages of the cylindrical projection are discussed giving special consideration to the characteristics of the visual landmark and the meaning of the blob extraction. The analysis is established based on real time experiments with our omnidirectional vision system and the actual mobile robot. The comparative studies are presented and the feasibility of the method is shown.

基于深度学习的指纹室内定位对抗样本攻击研究

基于深度学习的指纹室内定位系统因其能够有效抽取接收信号强度(RSS)指纹数据的深层特征而大幅提高了室内定位性能,但该类方法需要大量多样化的RSS指纹数据训练模型,并且目前对其安全漏洞也缺乏充分的研究,这些安全漏洞源于无线Wi-Fi媒体的开放性和分类器的固有缺陷(如易遭受对抗性攻击等)。为此,对基于深度学习的RSS指纹室内定位系统的对抗性攻击进行研究,提出一种基于Wi-Fi指纹室内定位的对抗样本攻击框架,并利用该框架研究对抗攻击对基于深度学习的RSS指纹室内定位模型性能的影响。该框架包含离线训练和在线定位两个阶段。在离线训练阶段,设计适用于增广Wi-Fi RSS指纹数据的条件生成对抗网络(CGAN)来生成大量多样化的RSS指纹数据训练高鲁棒的室内定位深度学习模型;在线定位阶段,构造最强的一阶攻击策略来生成针对Wi-Fi RSS指纹室内定位系统的有效RSS对抗样本,研究对抗攻击对不同室内定位深度学习模型性能的影响。实验结果显示:在公开UJIIndoorLoc数据集上,由所提框架生成的RSS指纹对抗样本对卷积神经网络(CNN)、深度神经网络(DNN)、多层感知机(MLP)、pixeldp_CNN指纹室内定位模型的攻击成功率分别达到94.1%、63.75%、43.45%、72.5%;对由CGAN增广数据训练的上述4种指纹室内定位模型的攻击成功率分别达到84.95%、44.8%、15.7%、11.5%。由此表明,现有的基于深度学习的指纹室内定位模型易遭受对抗样本攻击的影响,由真实数据和增广数据混合训练的室内定位模型在面临对抗样本攻击时具有更好的鲁棒性。

面向强后处理场景的图像篡改定位模型

针对微信、微博等社交平台对图像进行的压缩、尺度拉伸等有损操作带来的篡改痕迹模糊或被破坏的挑战,提出了一种对抗强后处理的图像篡改定位模型。该模型选用了基于Transformer的金字塔视觉转换器作为编码器,用于提取图像的篡改特征。同时,设计了一个类UNet结构的端到端编码器-解码器架构。金字塔视觉转换器的金字塔结构和注意力机制可以灵活关注图像的各个区块,结合类UNet结构能够多尺度地提取图像上下文间的关联信息,对强后处理的图像有着较好的鲁棒性。实验结果表明,所提模型在对抗JPEG压缩、高斯模糊等常见的后处理操作以及在不同社交媒体传播场景的数据集上的定位性能上明显优于目前主流的篡改定位模型,展现出了优异的鲁棒性。

基于RLLE算法的脑力负荷分类

近年来,随着人工智能领域技术的不断发展,脑机接口(brain-computer interface,BCI)吸引了更多学者的关注。实时监测高强度脑力工作者的脑力负荷水平并根据其任务做出动态调整是保护国家财产和操作人员安全的重要手段。研究表明由脑电图(electroencephalogram,EEG)提取的特征功率谱密度对于脑力负荷的变化比较敏感,但由于其维数过高,容易造成数据灾难。传统的主成分分析降维(principal component analysis,PCA)算法会损失数据的部分非线性特征。局部线性嵌入(locally linear embedding,LLE)是常用的非线性降维算法,但该算法对噪声的敏感性高,降维结果受参数影响较大。稳健局部线性嵌入算法RLLE(robust locally linear embedding),在LLE优化权重矩阵时添加了正则项优化,不仅增强了模型的抗噪能力,也解决了解模型过程中可能会出现的矩阵病态和奇异性问题。实验结果表明,经过RLLE降维后的数据使用支持向量机(support vector machine,SVM)分类精度普遍高于经过PCA和LLE的降维方式,具有更强的抗干扰能力。

基于CERLMDAN-PE-NLMS的MEMS陀螺信号去噪方法

随着武器技术的不断发展,常规弹药的制导化改造已成为一种必然趋势。通过应用精确制导技术,可以显著提高弹药的打击精度和效率。而在实现弹药制导化改造的过程中,精准测量角速度是一项关键核心技术。微机电系统(Micro-Electro Mechanical System,MEMS)陀螺仪存在输出信号噪声大、精度低的问题,针对上述问题,提出了一种自适应噪声完备集合鲁棒局部均值分解(CERLMDAN)和归一化LMS算法(Normalized Least Mean Square,NLMS)结合的滤波模型。该模型通过在鲁棒局部均值分解(Robust Local Mean Decomposition,RLMD)过程中添加白噪声将原始数据分解为多个乘积函数(Product Functions,PF),并根据排列熵(Permutation Entropy,PE)将PF分为混合PF和有用PF;其次对混合PF使用NLMS去噪;最后,把处理后的PF和有用PF进行重构,得到去噪后的信号。试验表明,本文提出的去噪模型对信号均值与方差有显著提升,信号均值由0.5891提升至0.5396,信号方差由44.473提升至5.2692。

四川省极端气温事件与城镇化发展的关联影响

在当前全球变暖背景下,近年来城镇化进程加速,研究四川省极端气温事件与城镇化发展的关联,对于降低四川极端温度事件的灾害风险和未来城市规划布局具有重要参考价值。利用四川省36个气象站点1980—2020年气温日值数据、夜间灯光和土地利用遥感数据、经济和人口空间分布网格数据,通过计算世界气象组织推荐的16个极端温度指数,并采用K-means与层次聚类相结合的方法,将气象站点划分为城市、城郊和乡村3类,分析四川省城镇化进程中极端温度事件的时间变化趋势及其与城镇化的关联影响,并探讨1980—2010年、1980—2015年、1980—2020年3个不同时段极端温度事件的区域变化趋势和不同类别气象站点的变化差异。结果表明,四川省1980―2020年极端高温事件呈增加趋势,极端低温事件呈减少趋势;城市站点的最高气温极大值、暖昼日数、月平均日较差增加趋势最明显,乡村站点的霜冻日数、冷夜日数、冷昼日数减少趋势最明显,城郊站点的夏季日数和暖夜日数增加趋势最明显;极端气温事件的增暖趋势在3个时段都较为显著,且乡村站点的增暖趋势相比城市和城郊站点更为明显;3个时段内,城市和城郊站点的夏季日数均多于乡村站点,而乡村站点的霜冻日数多于城市站点,城市和城郊站点的冷事件减少幅度均小于乡村。研究结果揭示了城镇化对极端气温事件影响的共性和区域差异性,对影响机理的深入研究还有待后续进一步分析和讨论。