异构数据转化与信息发布系统的实现

提出了一种异构数据转化为同一DBMS管理下的数据的方法,并在此基础上阐述了Web发布异构数据信息的框架和方法,并给出了一个实例。     

Adaptive per-user per-object cache consistency management for mobile data access in wireless mesh networks

We propose and analyze an adaptive per-user per-object cache consistency management (APPCCM) scheme for mobile data access in wireless mesh networks. APPCCM supports strong data consistency semantics through integrated cache consistency and mobility management. The objective of APPCCM is to minimize the overall network cost incurred due to data query/update processing, cache consistency management, and mobility management. In APPCCM, data objects can be adaptively cached at the mesh clients directly or at mesh routers dynamically selected by APPCCM. APPCCM is adaptive, per-user and per-object as the decision regarding where to cache a data object accessed by a mesh client is made dynamically, depending on the mesh client’s mobility and data query/update characteristics, and the network’s conditions. We develop analytical models for evaluating the performance of APPCCM and devise a computational procedure for dynamically calculating the overall network cost incurred. We demonstrate via both model-based analysis and simulation validation that APPCCM outperforms non-adaptive cache consistency management schemes that always cache data objects at the mesh client, or at the mesh client’s current serving mesh router for mobile data access in wireless mesh networks.     

位置相关信息服务中的一种数据预取方法

位置相关信息服务中访问数据涉及到复杂的空间计算,导致访问数据的延迟时间较长,而数据预取能够显著提高数据的访问速度,缩短访问数据的时间。基于LDD的预取策略如DDP考虑了数据距离,但是没有考虑数据的访问概率和更新频率及数据大小。针对以上问题提出基于价值的数据预取（CDP）策略,一些重要的数据预取因素如访问概率、更新频率、数据项大小、数据距离和有效范围等都包含在价值函数里,根据价值函数值的大小来选择被预取的数据。通过实验对比,CDP比DDP策略能更有效的提高缓存命中率。     

数据仓库在信息管理中的现实应用

在当今激烈的竞争中,信息对于医院及学校的生存与发展起着至关重要的作用。在信息分析研究中,采用数据仓库技术能大大提高方便性、准确性和及时性,可支持单位的行政管理及主管部门的决策。该文介绍了数据仓库的产生、发展,数据仓库与传统数据库相比所具有的优点以及如何建立数据仓库,在信息管理系统中,数据仓库如何应用及体现。     

The role of congestion in probabilistic broadcasting for ubiquitous wireless multi-hop networks through mediation analysis

Broadcast schemes play an important role in the performance of mobile ad hoc networks, which are a clear example of ubiquitous wireless multi-hop networks where nodes collaborate in a distributed way. They are widely used as a dissemination mechanism and as a part of the discovery phase of routing protocols. The simple flooding algorithm is the usual mechanism employed in mobile ad hoc networks, but its inefficiency has been demonstrated in congested scenarios due to the high number of collisions and contentions. However, these problems can be partially alleviated by using a probabilistic broadcast approach in which every node forwards the incoming packets according to a certain forwarding probability. In this paper, we use a simple probabilistic broadcast protocol to evaluate the effects of congestion on the performance of broadcasting in ad hoc networks through a mediation analysis. We hypothesize that the congestion mediates in the relationship between the forwarding probability (independent variable) and the output metric (dependent variable). We consider several output metrics according to the application of the broadcasting protocol such as reachability, broadcasting delay, packet delivery fraction and end to end delay. The simulation results show the existence of the mediating effects and how such effects may be counterbalanced depending on the target use of the probabilistic broadcast scheme.     

Minimizing center key storage in hybrid one-way function based group key management with communication constraints

We study the problem of designing a storage efficient secure multicast key management scheme based on one-way function trees (OFT) for a prespecified key update communication overhead. Canetti, Malkin and Nissim presented a hybrid model that divides a group of N members into clusters of M members and assigns each cluster to one leaf node of a key tree. Using the model, we formulate a constrained optimization problem to minimize the center storage in terms of the cluster size M. Due to the monotonicity of the center storage with respect to M, we convert the constrained optimization into a fixed point equation and derive the optimal M^* explicitly. We show that the asymptotic value of the optimal M^*, given as with μ=O(logN) and a being the degree of a key tree, leads to the minimal storage as , when the update communication constraint is given as O(logN). We present an explicit design algorithm that achieves minimal center storage for a given update communication constraint.     

数据挖掘在医院信息化建设中的应用研究

本文的研究工作主要围绕在医院信息系统(HIS)中使用数据挖掘技术展开。将数据挖掘理论应用于实际的医院信息系统(HIS)系统中,实现医院信息系统(HIS)系统与数据挖掘技术的结合。本文对数据挖掘的概念及国内外应用现状,以及数据挖掘在医院信息系统中的应用和展望进行了阐述。     

信息管理中数据库技术实践应用分析

信息管理中,数据库管理是其中最为重要的环节。如何解决好信息管理中数据库技术问题是各种软件设计、系统开发需要考虑的首要问题,本文就其话题进行了论述,首先从数据库技术发展的概述进行分析,其次从数据库技术在信息管理中的特征着手,最后提出了数据库技术在信息管理中的应用对策,主要有加强数据库系统的完整性、提高数据库技术的安全性、促进数据库与信息管理一体化三个方面,为数据库技术的发展具有重要的现实意义。     

Spatio-temporal effects of multimedia objects storage and delivery for video-on-demand systems

As the number of video streams to be supported by a digital video delivery system (DVDS) increases, an improved understanding of the necessity for reliable and cost-efficient support for a considerable number of video streams (in the magnitude of tens of thousands), and the dependency largely on software capabilities emerges. Even in the presence of an optimal hardware configuration, or model, and associated costs, using software to exploit the underlying hardware capabilities is of paramount importance. Although a number of DVDSs have become operational, their ability to deliver the required services mainly depends on the small number of streams supported and the hardware trade-offs. It is imperative that current software developments account for the eventual scalability of the number of video streams without commensurate increase in hardware. In this paper, we present strategies for the management of video streams in order to maintain and satisfy their space and time requirements. We use a DVDS architectural model with functionally dichotomized nodes: a single-node partition is responsible for data retrieval, while the remaining partition of nodes accepts user requests, determines object locations, and routes requests through the network that connects both partitions. We present a detailed analysis of the issues related to queuing I/O requests and data buffering. The discussion includes the requirements for arranging and scheduling I/O requests and data buffers, with the objective of guaranteeing the required data availability rates for continuous media display.     

关于高校实验室网络信息化管理平台的研究

从分析目前高校实验室管理的内容和存在的主要问题出发,提出了实验室网络信息化管理平台的设计方案,方案采用前台应用层、中间业务层、后台数据层三层架构,基于B/S和C/S相结合的开发模式和模块化设计的体系结构.     

Standard clock simulation and ordinal optimization applied to admission control in integrated communication networks

In this paper we apply the ideas of ordinal optimization and the technique of Standard Clock (SC) simulation to the voice-call admission-control problem in integrated voice/data multihop radio networks. This is an important problem in networking that is not amenable to exact analysis by means of the usual network modeling techniques. We first describe the use of the SC approach on sequential machines, and quantify the speedup in simulation time that is achieved by its use in a number of queueing examples. We then develop an efficient simulation model for wireless integrated networks based on the use of the SC approach, which permits the parallel simulation of a large number of admission-control policies, thereby reducing computation time significantly. This model is an extension of the basic SC approach in that it incorporates fixed-length data packets, whereas SC simulation is normally limited to systems with exponentially distributed interevent times. Using this model, we demonstrate the effectiveness of ordinal-optimization techniques, which provide a remarkably good ranking of admission-control policies after relatively short simulation runs, thereby facilitating the rapid determination of good policies. Moreover, we demonstrate that the use of crude, inaccurate analytical and simulation models can provide highly accurate policy rankings that can be used in conjunction with ordinal-optimization methods, provided that they incorporate the key aspects of system operation.     

政府机构人事工资信息管理系统的开发

本文论述了政府机关人事工资信息管理系统的设计目标以及系统的功能结构，结合实际项目的背景，提出了人事工资管理系统的解决方案，并以分模块的形式探讨了系统的功能，介绍了系统的特点。     

Bridging the gap between product lifecycle management and sustainability in manufacturing through ontology building

Green manufacturing has been a major concern in recent years. As product lifecycle management strategies embrace sustainability within its spectrum of multi-disciplinary efforts, it has become crucial that manufacturing companies have the ability to exchange product and process related data with emphasis on sustainability not only amongst its internal information systems like CAD, CAPP and ERP, but also throughout their supply chain and other stakeholders. Industry demands solutions for interoperability between heterogeneous systems that can account for the necessary semantics in order to establish seamless, unambiguous information sharing of data from a product's cradle to its grave. One of the most promising approaches to overcome these issues is the use of ontologies that serve as interlingua, for translating between local data structures. The present research proposes an ontology that relates sustainability terms to product and process data entities through semantic ties.     

数据采集系统在中间试验工厂的开发与应用

基于中间试验工厂设备多而杂的特点,为了提升中间试验工厂的管理能力和设备利用率,对中间试验工厂的设备功能进行了研究,提出了基于Framework的分布式系统方案。在方案实施中,对与Framework系统不兼容的设备进行了改造升级,成功实现了各种不同接口设备生产数据的采集。并在此基础上开发出了专用的数据采集系统,为中间试验工厂的设备运行、科研调度提供了有力的技术支撑,同时也为其他钢厂设备的引进和数据采集系统的建立提供了可以借鉴的经验。     

虚拟制造专用网中产品信息安全性的研究与实现

提出了利用VPN（虚拟专用网）构建网上制造系统的理论框架。通过PDM（产品数据管理）对异地制造资源进行远程管理和控制,建立面向产品的WMN(虚拟制造专用网),实现产品异地设计与制造的协同工作;并着重研究了虚拟制造专用网中产品数据传输的安全性问题。     

Non-parametric and parametric methods using satellite images for estimating growing stock volume in alpine and Mediterranean forest ecosystems

This paper describes applications of non-parametric and parametric methods for estimating forest growing stock volume using Landsat images on the basis of data measured in the field, integrated with ancillary information. Several k-Nearest Neighbors (k-NN) algorithm configurations were tested in two study areas in Italy belonging to Mediterranean and Alpine ecosystems. Field data were acquired by the regional forest inventory and forest management plans, and satellite images are from Landsat 5 TM and Landsat 7 ETM+. The paper describes the data used, the methodologies adopted and the results achieved in terms of pixel level accuracy of forest growing stock volume estimates. The results show that several factors affect estimation accuracy when using the k-NN method. For the two test areas a total of 3500 different configurations of the k-NN algorithm were systematically tested by changing the number and type of spectral and ancillary input variables, type of multidimensional distance measures, number of nearest neighbors and methods for spectral feature extraction using the leave-one-out (LOO) procedure. The best k-NN configurations were then used for pixel level estimation; the accuracy was estimated with a bootstrapping procedure; and the results were compared to estimates obtained using parametric regression methods implemented on the same data set.

The best k-NN growing stock volume pixel level estimates in the Alpine area have a Root Mean Square Error (RMSE) ranging between 74 and 96 m³ ha^− 1 (respectively, 22% and 28% of the mean measured value) and between 106 and 135 m³ ha^− 1 (respectively, 44% and 63% of the mean measured value) in the Mediterranean area. On the whole, the results cast a promising light on the use of non-parametric techniques for forest attribute estimation and mapping with accuracy high enough to support forest planning activities in such complex landscapes. The results of the LOO analyses also highlight the importance of a local empirical optimization phase of the k-NN procedure before defining the best algorithm configuration. In the tests performed the pixel level accuracy increased, depending on the k-NN configuration, as much as 100%.     

Living in a big data world: Predicting mobile commerce activity through privacy concerns

As advertisers increasingly rely on mobile-based data, consumer perceptions regarding the collection and use of such data becomes of great interest to scholars and practitioners. Recent industry data suggests advertisers seeking to leverage personal data offered via mobile devices would be wise to acknowledge and address the privacy concerns held by mobile users. Utilizing the theoretical foundation of communication privacy management (CPM), the current study investigates commonly understood privacy concerns such as collection, control, awareness, unauthorized secondary use, improper access and a newly adapted dimension of location tracking, trust in mobile advertisers, and attitudes toward mobile commerce, to predict mobile commerce engagement. Data from this study indicate that control, unauthorized access, trust in mobile advertisers, and attitude toward mobile commerce significantly predicted 43% of the variance in mobile commerce activity.