集中药包土中爆炸成腔的三维数值模拟

运用数值模拟的方法对土中封闭爆炸成腔进行了仿真研究。介绍了用LS -DYNA3D求解运算的基本过程 ,并运用该程序对集中装药条件下土中爆炸成腔进行了三维模拟。结果表明 :该程序可以用来模拟土中爆炸成腔 ,得到的空腔与药包半径之比与实验基本吻合。     

On the long-term retention of geometry-centric digital engineering artifacts

This paper discusses the challenges of long-term preservation of digital geometric models and the engineering processes associated with them. For engineering, design, manufacturing, and physics-based simulation data this requires formats that are accessible potentially indefinitely into the future. One of the fundamental challenges is the development of digital geometry-centric engineering representations that are self describing and assured to be interpretable over the long lifespans required by archival applications. Additionally, future users may have needs that require other information, going beyond geometry, be also accessible to fully interpret the model. These problems are highly interdisciplinary and not exclusively algorithmic or technical. To provide context, the paper introduces a case study illustrating an overall portrait of the problem. Based on observations from this case study, we present a framework for enhancing the preservation of geometry-centric engineering knowledge. This framework is currently being used on a number of projects in engineering education.     

TPS3: A privacy preserving data collection protocol for smart grids

Smart grid (SG) allows for two-way communication between the utility and its consumers and hence they are considered as an inevitable future of the traditional grid. Since consumers are the key component of SGs, providing security and privacy to their personal data is a critical problem. In this paper, a security protocol, namely TPS3, is based on Temporal Perturbation and Shamir’s Secret Sharing (SSS) schemes that are proposed to ensure the privacy of SG consumer’s data. Temporal perturbation is employed to provide temporal privacy, while the SSS scheme is used to ensure data confidentiality. Temporal perturbation adds random delays to the data collected by smart meters, whereas the SSS scheme fragments these data before transmitting them to the data collection server. Joint employment of both schemes makes it hard for attackers to obtain consumer data collected in the SG. The proposed protocol TPS3 is evaluated in terms of privacy, reliability, and communication cost using two different SG topologies. The performance evaluation results clearly show that the TPS3 protocol ensures the privacy and reliability of consumer data in SGs. The results also show that the tradeoff between the communication cost and security of TPS3 is negligible.     

Reversible privacy preserving data mining: a combination of difference expansion and privacy preserving

Privacy Preserving Data Mining (PPDM) can prevent private data from disclosure in data mining. However, the current PPDM methods damaged the values of original data where knowledge from the mined data cannot be verified from the original data. In this paper, we combine the concept and technique based on the reversible data hiding to propose the reversible privacy preserving data mining scheme in order to solve the irrecoverable problem of PPDM. In the proposed privacy difference expansion (PDE) method, the original data is perturbed and embedded with a fragile watermark to accomplish privacy preserving and data integrity of mined data and to also recover the original data. Experimental tests are performed on classification accuracy, probabilistic information loss, and privacy disclosure risk used to evaluate the efficiency of PDE for privacy preserving and knowledge verification.     

Application of high efficiency data compression and 2-D digital filtering techniques to remote sensing data processing

Abstract.

Remote sensing data, as received from earth resource satellites or obtained through digitization of aircraft photos, are to be processed by means of high efficiency techniques to improve the quality of the data and to obtain final useful results. Two data processing techniques of appreciable interest, namely, data compression and 2-D digital filtering are considered. By means of data compression the amount of data can be reduced solving storage and handling problems, while through 2-D digital filtering correction, enhancement and pattern recognition operations can be performed improving the quality of the data and extracting useful results. Efficient 2-D digital filters of FIR type using the Cappellini window and of IIR type using rotation and stabilization procedures are presented. Data compression techniques using local space operators and 2-D transformations with thresholds and variable length encoding are described. Practical software packages ready for the application of the above techniques are shown. Results obtained by processing through the described techniques satellite data and digitized aircraft photos are presented.     

An activity-based costing model for long-term preservation and dissemination of digital research data: the case of DANS

Financial sustainability is an important attribute of a trusted, reliable digital repository. The authors of this paper use the case study approach to develop an activity-based costing (ABC) model. This is used for estimating the costs of preserving digital research data and identifying options for improving and sustaining relevant activities. The model is designed in the environment of the Data Archiving and Networked Services (DANS) institute, a well-known trusted repository. The DANS–ABC model has been tested on empirical cost data from activities performed by 51 employees in frames of over 40 different national and international projects. Costs of resources are being assigned to cost objects through activities and cost drivers. The ‘euros per dataset’ unit of costs measurement is introduced to analyse the outputs of the model. Funders, managers and other decision-making stakeholders are being provided with understandable information connected to the strategic goals of the organisation. The latter is being achieved by linking the DANS–ABC model to another widely used managerial tool—the Balanced Scorecard (BSC). The DANS–ABC model supports costing of services provided by a data archive, while the combination of the DANS–ABC with a BSC identifies areas in the digital preservation process where efficiency improvements are possible.     

RDF存储策略的研究与实现

在介绍RDF数据模型的基础上,对目前RDF的几种存储方式进行了研究,并分析了各自的优劣性;然后提出了一种基于关系数据库的RDF存储策略,并设计出对应的关系模型;最后采用Jena对一个RDF数据段实例进行了解析,从而实现了RDF在关系数据库中的存储.     

A novel anonymization algorithm: Privacy protection and knowledge preservation

In data mining and knowledge discovery, there are two conflicting goals: privacy protection and knowledge preservation. On the one hand, we anonymize data to protect privacy; on the other hand, we allow miners to discover useful knowledge from anonymized data. In this paper, we present an anonymization method which provides both privacy protection and knowledge preservation. Unlike most anonymization methods, where data are generalized or permuted, our method anonymizes data by randomly breaking links among attribute values in records. By data randomization, our method maintains statistical relations among data to preserve knowledge, whereas in most anonymization methods, knowledge is lost. Thus the data anonymized by our method maintains useful knowledge for statistical study. Furthermore, we propose an enhanced algorithm for extra privacy protection to tackle the situation where the user’s prior knowledge of original data may cause privacy leakage. The privacy levels and the accuracy of knowledge preservation of our method, along with their relations to the parameters in the method are analyzed. Experiment results demonstrate that our method is effective on both privacy protection and knowledge preservation comparing with existing methods.     

Positivity preservation, stencil selection and applications of LSKUM to 3-D inviscid flows

Meshless methods do not require a mesh but only need a distribution of points in the computational domain. At any point, the approximation of spatial derivatives appearing in the partial differential equations is performed using a local cloud of points called the connectivity (or stencil). While point generation is easier than mesh generation, the selection of a good stencil becomes critical to the success of meshless methods. In this work we develop some criteria for quantifying the quality of stencils for meshless methods and apply them to LSKUM using points obtained from a complex grid system called FAME. We also show that LSKUM is positivity preserving under a CFL condition which lends further evidence to its robustness.     

Beyond usability: the OoBE dynamics of mobile data services markets

With processors imbedded in appliances, cars, books, and other retail products, modern society has entered the world of pervasive computing. Yet few consumers are able to set up new digital devices and integrate them into everyday life. From this perspective, the data-enabled mobile phone leads the way. In many markets, mobile phones have a product life cycle of 12 months or less. Some subscribers are able to put their new phones to immediate and full use. For others, the learning curve is so steep that they move on to a replacement without having learned to exploit the functionality available in the first one. This work applies earlier findings by IMARC researchers in segmenting mobile data services (MDS) markets, interprets recent survey data, and synthesizes a model to guide design of the Out-of-the-Box Experience (OoBE) for mobile data subscribers. This integrative model can be applied across cultures to help service developers, facilitators and operators design, distribute and communicate new MDS to fulfill the demand side requirements of potential adopters, and to guide packaging design to improve user experiences during the early stages of use.     

Recoverability preservation: a measure of last resort

Recoverability preservation is the property of a system to maintain recoverability even when it does not maintain correctness; recoverability, in turn, is the property of a system to avoid failure, even when system states have errors. In this paper, we argue that fault tolerance techniques could be more streamlined, less intrusive, and more effective if they focused on the criterion of recoverability preservation instead of the traditional criterion of correctness preservation. To this effect, we briefly introduce, motivate, illustrate, and analyze the concept of recoverability preservation, then we explore some of its applications.     

某型投物伞系统三维动态仿真的设计与实现

随着科技的发展,仿真的效果逐渐增强,仿真在各个领域的应用也日趋广泛.越来越多的军用和民用部门都希望用仿真技术来替代真实的训练或效果测试,以求最大限度地降低成本.文中主要利用OpenGL和VC技术设计并实现了某型投物伞系统在模拟环境中投放情况的仿真.首先介绍了OpenGL技术,接着重点探讨了通过几何建模、行为建模来建立三维图形、实现仿真的方法,并介绍了投放环境的绘制.最后给出了仿真效果视图,基本能显示出降落伞的投放完成情况.     

3-D analysis of functional instabilities of the ankle using digital still cameras

A technique to analyze the functional instability of an ankle is proposed. The technique is based on measurements using two digital still cameras. We carried out several experiments using this technique. Subjects are requested to stand on an experimental table whose angle of inclination is adjusted. By comparing the postures of both feet, we could tell that the subjects had experienced an ankle sprain and had functional instabilities in their ankles.This work was presented in part at the 8th International Symposium on Artificial Life and Robotics, Oita, Japan, January 24–26, 2003     

基于人工神经网络的压力传感器三维数据融合

针对压力传感器对温度变化和电流波动的交叉灵敏度问题,采用径向基函数(RBF)人工神经网络法对其进行数据融合处理,详细讨论了网络的训练过程和数据融合过程,消除温度和电流对压力传感器的影响。仿真结果表明:当温度变化48.5℃,电流波动3%时,经RBF神经网络数据融合后,压力波动为0.544%,大大降低了交叉干扰,提高传感器的稳定性及其精度,满足在线融合的需要。     

对三维激光扫描系统的研究和改进

介绍了三维激光扫描技术、三维激光扫描系统分类以及系统的工作流程,并针对当前工作中的技术难点--提高数据采集性能,进行了深入的研究和实践.从系统标定、光刀中心提取、三维定位3个方面进行了探讨,提出了一种改进的激光线中心提取算法,并利用双CCD像机的二维坐标进行图像融合,提高了数据采集的性能.实验结果表明了该算法的可行性以及对系统改进的有效性,能够满足实际应用的需要.     

Models and algorithms for efficient multiresolution topology estimation of measured 3-D range data

In this paper, we propose a new efficient topology estimation algorithm to construct a multiresolution polygonal mesh from measured three-dimensional (3-D) range data. The topology estimation problem is defined under the constraints of cognition, compactness, and regularity, and the algorithm is designed to be applied to either a cloud of points or a dense mesh. The proposed algorithm initially segments the range data into a finite number of Voronoi patches using the K-means clustering algorithm. Each patch is then approximated by an appropriate polygonal and eventually a triangular mesh model. In order to improve the equiangularity of the mesh, we employ a dynamic mesh model, in which the mesh finds its equilibrium state adaptively, according to the equiangularity constraint. Experimental results demonstrate that satisfactory equiangular triangular mesh models can be constructed rapidly at various resolutions, while yielding tolerable modeling error.     

The Florida Digital Archive and DAITSS: a working preservation repository based on format migration

The Florida Digital Archive is a long-term digital preservation repository for the use of the libraries of the public universities of Florida. It is managed by the Florida Center for Library Automation (FCLA) and based on Dark Archive in the Sunshine State (DAITSS), repository software developed by FCLA with the aid of grant funding from the Institute of Museum and Library Services (IMLS). DAITSS is designed to implement active preservation strategies based on format transformations including forward migration, normalization, and localization. As a case study, the Florida Digital Archive and DAITSS show that active preservation strategies can be incorporated into repository applications from the start, and that doing so affects all aspects of application design. The Florida Digital Archive has been in production since November 2005. The DAITSS application is nearing completion and will be released as open source software in 2006.     

Information ecology: open system environment for data, memories, and knowing

An information ecology provides a conceptual framework to consider data, the creation of knowledge, and the flow of information within a multidimensional context. This paper, reporting on a 1 year project to study the heterogeneity of information and its management within the Long Term Ecological Research (LTER) community, presents some manifestations of traditionally unreported ‘invisible work’ and associated elements of informal knowledge and unarticulated information. We draw from a range of ethnographic materials to understand ways in which data-information-knowledge are viewed within the community and consider some of the non-linear aspects of data-knowledge-information that relate to the development of a sustained, robust, persistent infrastructure for data collection in environmental science research. Taking data as the unit of study, the notion of long-term research and data holdings leads to consideration of types of memory and of knowledge important for design of cyberinfrastructures. Complexity, ambiguity, and nonlinearity are part of an information ecology and addressed today by exploring multiple types of knowledge, developing information system vocabularies, and recognizing the need for intermediation.     

Connectivity preservation of second-order nonlinear multiagent systems with hybrid event-driven and time-driven control

In practice, the capability of communication between each pair of agents is within a finite range. This paper investigates how to preserve connectivity for nonlinear multiagent systems while reaching consensus under event-driven control technique. By introducing an appropriate potential function based on the distance of two agents, we can demonstrate that all the agents will not lose connectivity if the initial undirected graph is connected. Furthermore, due to the existence of friction and time delay, we utilise the Young's inequality and a Lyapunov–Krasovskii functional to eliminate the negative effects of time delay. The use of impulse functions is considered which can avoid the singularity in the control input. Moreover, the hybrid event-driven and time-driven control technique is utilised to reduce the requirements of communication resources. Finally, numerical simulations are conducted to demonstrate the effectiveness of our methodology.     

Dynamic disparity adjustment and histogram-based filtering of range data for fast 3-D hand tracking

Range data is very important in human-computer interaction applications. Although less costly, range acquisition and processing still presents a speed vs data reliability tradeoff. This paper proposes a method that, given noisy and generally unreliable range data, can filter out erroneous information using range histograms for regions of interest selected in registered color data. Then, using the resulting consistent data that has passed filters, this method limits the depth search space dynamically using motion history and its current state. Experimental results demonstrate the success of the proposed algorithm. Using filtered range data, the algorithm correctly identified the hand involved in manipulation 99.85% of the time. Dynamic disparity adjustment produced a speedup of 60.17% over a static disparity range selection. An application to virtual reality navigation is also presented.