Correlation between Transport and Occurrence of Dengue Cases in Bahia

Dengue is a public health problem that presents complexity in its dissemination. The physical means of spreading and the dynamics of the spread between the municipalities need to be analyzed to guide effective public policies to combat this problem. This study shows a correlation between the exponent of criticality present in SOC （self-organized criticality） and the number of buses per week, identifying municipalities that exert important roles in the spread of dengue in Bahia, confirming transport as a physical means for the diffusion of dengue.     

Remote charge scattering： a full Coulomb interaction approach and its impact on silicon nMOS FinFETs with HfO2 gate dielectric

Remote charge scattering(RCS)has become a serious obstacle inhabiting the performance of ultrathin gate oxide MOSFETs.In this paper,we evaluate the impact of RCS by treating the real-space full Coulomb interaction between remote charges and inversion carriers.A new approach that can be simply incorporated in ensemble Monte Carlo(EMC)based simulations without any variation of the standard EMC simulator is developed.The charge-carrier(c-c)interaction model is based on a particle-mesh(PM)calculation method which resolves both the long-range and short-range Coulomb interactions by solving Poisson’s equation on a refined mesh.The validity of our approach is verified by three-dimensional(3-D)resistor simulations,from which the obtained doping dependence of the low-field mobility agrees well with experimental results.The proposed approach is then used to study the impact of RCS on the drive current and carrier transport properties in the channel of a 20 nm silicon(Si)nMOS FinFET with HfO2gate stack.We find that the influence of RCS is strongly localized in the vicinity of the remote charges and exhibits a granular nature,indicating the necessity to consider the full Coulomb interaction in RCS.     

基于SSL/TLS的安全文件传输系统

为了保证Internet上数据的安全传输,加密传输得到越来越多的应用。主要阐述了如何通过JSSE实现基于SSL/TLS协议的安全文件传输系统,给出了使用JSSE创建安全套接字连接的具体方法。系统具有跨平台、传输性能高效等特点。在此基础上分析了基于SSL/TLS协议的文件传输系统的安全性。由于数据加密往往是很耗时的,会在一定程度上影响传输效率,所以还通过将本系统与一般的文件传输系统相比较,分析了基于SSL/TLS安全文件传输系统的传输效率。     

基于Web服务的广域网文件I/O研究

广域网异构性不断加剧，分布式存储系统间的互操作、资源整合、可扩展性等问题日益突出，形成了许多信息孤岛。该文提出了一个基于Web服务的广域网文件I/O，改进广域网存储系统存在的上述问题。给出了WSIO的架构和实现，对其性能作了研究，并在实验基础上进行了性能优化。     

协议测试仪的EPP接口设计

WPT-2000是自主研制成功的国产广域网协议测试仪。它采用分体式系统结构，由一台便携式PC和包捕获控制器组成。为了实现两者之间高效而廉价的通信，采用了EPP接口方案。EPP是IEEE1284标准中定义的PC机上的增强并行接口协议，它支持高速半双工双向数据传送。结果证明，所设计的EPP接口方案可以完整可靠地将最高速率达2Mbps的广域网络数据包传送到PC。文中介绍了EPP接口协议、包捕获控制器的EPP接口电路设计和PC机上的EPP实现程序。     

Data Utilization-Based Adaptive Data Management Method for Distributed Storage System in WAN Environment

Recently, research on a distributed storage system that efficiently manages a large amount of data has been actively conducted following data production and demand increase. Physical expansion limits exist for traditional standalone storage systems, such as I/O and file system capacity. However, the existing distributed storage system does not consider where data is consumed and is more focused on data dissemination and optimizing the lookup cost of data location. And this leads to system performance degradation due to low locality occurring in a Wide Area Network (WAN) environment with high network latency. This problem hinders deploying distributed storage systems to multiple data centers over WAN. It lowers the scalability of distributed storage systems to accommodate data storage needs. This paper proposes a method for distributing data in a WAN environment considering network latency and data locality to solve this problem and increase overall system performance. The proposed distributed storage method monitors data utilization and locality to classify data temperature as hot, warm, and cold. With assigned data temperature, the proposed algorithm adaptively selects the appropriate data center and places data accordingly to overcome the excess latency from the WAN environment, leading to overall system performance degradation. This paper also conducts simulations to evaluate the proposed and existing distributed storage methods. The result shows that our proposed method reduced latency by 38% compared to the existing method. Therefore, the proposed method in this paper can be used in large-scale distributed storage systems over a WAN environment to improve latency and performance compared to existing methods, such as consistent hashing.     

非定常Monte Carlo输运问题的并行算法

文中给出了非定常MonteCarlo(下文简写为MC)输运问题的并行算法 ,对并行程序的加载运行模式进行了讨论和优化设计 .针对MC并行计算设计了一种理想情况下无通信的并行随机数发生器算法 .动态MC输运问题有大量的I/O操作 ,特别是读取剩余粒子数据文件需要大量的I/O时间 ,文中针对I/O问题 ,提出了三种并行I/O算法 .最后给出了并行算法的性能测试结果 ,对比串行计算时间 ,使用 6 4台处理机时的并行计算时间缩短了 30倍     

Metadata Feedback and Utilization for Data Deduplication Across WAN

Data deduplication for file communication across wide area network (WAN) in the applications such as file synchronization and mirroring of cloud environments usually achieves significant bandwidth saving at the cost of significant time overheads of data deduplication. The time overheads include the time required for data deduplication at two geographi-cally distributed nodes (e.g., disk access bottleneck) and the duplication query/answer operations between the sender and the receiver, since each query or answer introduces at least one round-trip time (RTT) of latency. In this paper, we present a data deduplication system across WAN with metadata feedback and metadata utilization (MFMU), in order to harness the data deduplication related time overheads. In the proposed MFMU system, selective metadata feedbacks from the receiver to the sender are introduced to reduce the number of duplication query/answer operations. In addition, to harness the metadata related disk I/O operations at the receiver, as well as the bandwidth overhead introduced by the metadata feedbacks, a hysteresis hash re-chunking mechanism based metadata utilization component is introduced. Our experimental results demonstrated that MFMU achieved an average of 20%～40% deduplication acceleration with the bandwidth saving ratio not reduced by the metadata feedbacks, as compared with the “baseline” content defined chunking (CDC) used in LBFS (Low-bandwith Network File system) and exiting state-of-the-art Bimodal chunking algorithms based data deduplication solutions.     

Issues in Symbian S60 platform forensics

This paper aims at presenting the real and complete structure of the Symhian S60 v3 （third edition） platform file system, which is considered one of the most secure and armored systems issued by Symbian Ltd. in the last two years. By analyzing the unique features of security, which have been applied at the file system level, it will become clear how to develop applications for digital forensic purposes. Moreover, the limitations and main issues related to accessing the observable portion of the file system will be pointed out, and possible solutions will be presented.     

基于VC++类库的CAD/CAPP集成系统的研究与实践

文章采用特征拼装及特征单元的参数化设计方法，在以VisualC++类库（MicrosoftFoundationClassMFC类）为数据存储、交换与管理的基础上，成功地实现了CAD／CAPP集成数据的传递与共享。通过DXF接。方式与VisualC++的连接，可在AutoCAD14下自动生成零件图，在集成环境下自动生成工艺文件。     

Network and data location aware approach for simultaneous job scheduling and data replication in large-scale data grid environments

Data Grid integrates graphically distributed resources for solving data intensive scientific applications. Effective scheduling in Grid can reduce the amount of data transferred among nodes by submitting a job to a node, where most of the requested data files are available. Scheduling is a traditional problem in parallel and distributed system. However, due to special issues and goals of Grid, traditional approach is not effective in this environment any more. Therefore, it is necessary to propose methods specialized for this kind of parallel and distributed system. Another solution is to use a data replication strategy to create multiple copies of files and store them in convenient locations to shorten file access times. To utilize the above two concepts, in this paper we develop a job scheduling policy, called hierarchical job scheduling strategy （HJSS）, and a dynamic data replication strategy, called advanced dynamic hierarchical replication strategy （ADHRS）, to improve the data access efficiencies in a hierarchical Data Grid. HJSS uses hierarchical scheduling to reduce the search time for an appropriate computing node. It considers network characteristics, number of jobs waiting in queue, file locations, and disk read speed of storage drive at data sources. Moreover, due to the limited storage capacity, a good replica replacement algorithm is needed. We present a novel replacement strategy which deletes files in two steps when free space is not enough for the new replica： first, it deletes those files with minimum time for transferring. Second, if space is still insufficient then it considers the last time the replica was requested, number of access, size of replica and file transfer time. The simulation results show that our proposed algorithm has better performance in comparison with other algorithms in terms of job execution time, number of intercommunications, number of replications, hit ratio, computing resource usage and storage usage.     

分布式站点间的跨域文件系统

高能物理科学研究大多依托固定站点大科学装置,拥有海量实验数据。因此数据计算往往基于异地站点的海量实验数据。针对这些海量的分布式实验数据,传统的高能物理计算模式中采用了网格的方式进行跨域数据共享,但资源利用率低、响应时间长以及部署维护困难等问题,限制了网格技术在中小型站点间的数据共享。针对高能物理计算环境中,中小型站点间的数据共享问题,以Streaming & Cache为核心思想,设计一种远程文件系统,提出远程数据访问本地化,提供高实时性数据访问模式,实现基于HTTP协议的按需数据传输与管理,拥有数据块散列存储和文件统一化视图管理。与高能物理计算中常用分布式文件系统EOS、Lustre、GlusterFS相比,具有广域网可用性、网络时延不敏感性和高性能数据访问模式。     

Feature selection on probabilistic symbolic objects

In data analysis tasks, we are often confronted to very high dimensional data. Based on the purpose of a data analysis study, feature selection will find and select the relevant subset of features from the original features. Many feature selection algorithms have been proposed in classical data analysis, but very few in symbolic data analysis （SDA） which is an extension of the classical data analysis, since it uses rich objects instead to simple matrices. A symbolic object, compared to the data used in classical data analysis can describe not only individuals, but also most of the time a cluster of individuals. In this paper we present an unsupervised feature selection algorithm on probabilistic symbolic objects （PSOs）, with the purpose of discrimination. A PSO is a symbolic object that describes a cluster of individuals by modal variables using relative frequency distribution associated with each value. This paper presents new dissimilarity measures between PSOs, which are used as feature selection criteria, and explains how to reduce the complexity of the algorithm by using the discrimination matrix.     

Spatial Data Mining to Support Environmental Management and Decision Making--A Case Study in Brazil

The growth of geo-technologies and the development of methods for spatial data collection have resulted in large spatial data repositories that require techniques for spatial information extraction, in order to transform raw data into useful previously unknown information. However, due to the high complexity of spatial data mining, the need for spatial relationship comprehension and its characteristics, efforts have been directed towards improving algorithms in order to provide an increase of performance and quality of results. Likewise, several issues have been addressed to spatial data mining, including environmental management, which is the focus of this paper. The main original contribution of this work is the demonstration of spatial data mining using a novel algorithm with a multi-relational approach that was applied to a database related to water resource from a certain region of S~o Paulo State, Brazil, and the discussion about obtained results. Some characteristics involving the location of water resources and the profile of who is administering the water exploration were discovered and discussed.     

Continuous Outlier Monitoring on Uncertain Data Streams

Outlier detection on data streams is an important task in data mining. The challenges become even larger when considering uncertain data. This paper studies the problem of outlier detection on uncertain data streams. We propose Continuous Uncertain Outlier Detection （CUOD）, which can quickly determine the nature of the uncertain elements by pruning to improve the efficiency. Furthermore, we propose a pruning approach -- Probability Pruning for Continuous Uncertain Outlier Detection （PCUOD） to reduce the detection cost. It is an estimated outlier probability method which can effectively reduce the amount of calculations. The cost of PCUOD incremental algorithm can satisfy the demand of uncertain data streams. Finally, a new method for parameter variable queries to CUOD is proposed, enabling the concurrent execution of different queries. To the best of our knowledge, this paper is the first work to perform outlier detection on uncertain data streams which can handle parameter variable queries simultaneously. Our methods are verified using both real data and synthetic data. The results show that they are able to reduce the required storage and running time.     

基于Hadoop的广域网分布式主题爬虫系统框架

广域网分布式爬虫与局域网爬虫相比有诸多的优势,而现有基于Hadoop分布式爬虫的设计主要是面向局域网环境的。为解决Hadoop分布式计算平台不适合部署于广域网的问题,设计了一个基于Hadoop的广域网分布式爬虫系统框架。爬虫系统利用消息中间件实现分布式可靠通信,数据存储采用可伸缩的Hadoop分布式文件系统HDFS,网页解析利用MapReduce并行处理,并基于模板匹配实现框架可定制。系统的性能仿真显示该框架具有支撑大规模爬虫并发工作的能力。     

Research of Graduation Project Management System Based on B/S Mode

Graduation project management system is designed and developed on B/S mode with C# language. The main flow of the system is students＇ selecting projects. System is designed on teachers, students and administrators, students. Focus on the project application, the project audit, the select projects and the results generated summary ect. It enables instructors to assign projects and students to select them online quickly and conveniently, and instructors can track and manage the graduation design in the whole course through the system. This system provides a good interactive platform of graduation design for teachers and students, which improves the efficiency and quality of the project selection of graduation design.     

Cropping and Noise Resilient Steganography Algorithm Using Secret Image Sharing

This paper proposes an image steganography scheme, in which a secret image is hidden into a cover image using a SIS （secret image sharing） scheme. Taking advantage of the fault tolerance property of the （k, n）-threshold SIS, where using any k of n shares （k ≤ n）, the secret data can be recovered without any ambiguity. In order to increase the security of the secret information to digital attacks, the proposed steganography algorithm becomes resilient to cropping and impulsive noise contamination using SIS scheme. Among many SIS schemes proposed until now, the Lin and Chan＇s scheme is selected as the SIS, due to its lossless recovery capability of a large amount of secret data. Stego-image quality and hiding capacity depend on the prim number used in polynomial. The proposed scheme is evaluated from several points of view, such as imperceptibility of the stego-image respect to its original cover image using the PSNR, quality of the extracted secret image, robustness of hidden data to cropping operation, impulsive noise contamination and the combination of both attacks. The evaluation results show a high quality of the extracted secret image from the stego-image when it suffered more than 20% cropping and/or high density noise contamination.     

Proposal for an Optimal Job Allocation Method Based on Multiple Costs Balancing in Hybrid Cloud

Due to the explosive increase in the amount of information in computer systems, we need a system that can process large amounts of data efficiently. Cloud computing system is an effective means to achieve this capacity and has spread throughout the world. In our research, we focus on hybrid cloud environments, and we propose a method for efficiently processing large amounts of data while responding flexibly to needs related to performance and costs. We have developed this method as middleware. For data-intensive jobs using this system, we have created a benchmark that can determine the saturation of the system resources deterministically. Using this benchmark, we can determine the parameters in this middleware. This middleware can provide Pareto optimal cost load balancing based on the needs of the user. The results of the evaluation indicate the success of the system.