Media Constructions of Aboriginality: implications for engagement with coal seam gas development in Australia

Recent neo-liberal policy frameworks in Australia advocate economic development opportunities for Aboriginal Australians as a viable strategy to redress the marginalisation and social disadvantage that appear to characterise many Aboriginal communities. In New South Wales (NSW), Aboriginal peoples are currently negotiating with industry for the chance to participate in coal seam gas (CSG) development opportunities. Based upon research focusing on CSG development in the Northern NSW region, this paper argues that certain constructions of Aboriginality inhibit successful Aboriginal engagement with the economic opportunities provided by CSG. This paper illuminates the role of the media in facilitating dominant discourse about Aboriginality and the implications of those constructions for Aboriginal engagement with the mainstream economy. Findings demonstrate that the media are complicit in constructing Aboriginal peoples in a way that could prejudice their attempts to engage in economic opportunities that do not align with the dominant constructions of Aboriginality.     

面向云计算的网络体系结构下数据传输机制

分析目前云计算架构下的传输机制,针对网络传输机制中缺少对链路上的任务需求的耦合相关性,提出未来面向云计算的网络体系结构下数据传输机制,分别从网络传输延迟、传输可靠性和云节点存储安全性进行研究,并针对每个瓶颈提出相应的修改方法,从而构建了一个支持不同服务质量需求的云架构,该架构支持现有的网络异构融合,满足可控可管可扩展等需求,适用于新型网络通信信息基础设施.     

全球位置信息叠加协议与位置服务网技术研究进展与展望

随着信息技术的快速发展,当今世界步入信息爆发性增长的时代,互联网、物联网和传感网中的海量人类社会相关信息为解决城市治理和社会管理问题提供了新视角,如何将信息进行快速有效地整合和共享,是进一步提高城市智慧化管理能力面临的巨大挑战。近年来,在社会信息的位置泛在属性基础上提出的全球位置信息叠加协议与位置服务网技术,将位置作为信息横向关联的结点,为打通各领域系统间的壁垒,实现跨网、跨平台、跨系统、跨位置语言的海量异构信息自动汇集、融合计算与智能服务,提升社会化信息共享水平和效率,推动智慧地球和智能社会建设提供了支持。本文着重介绍了目前国内外关于全球位置信息叠加协议与位置服务网技术在立体剖分与位置编码、位置编码映射、地理实体编码、泛在位置信息叠加协议、高精度位置时空框架与位置感知的信息融合技术等各项关键技术的前沿进展。并进一步总结了全球位置服务网在行业中的示范应用,最后对全球位置服务网在技术和应用上的未来研究方向进行了讨论,以期望为未来全球位置服务网的发展提供参考。     

基于区域经济发展水平的耕地社会责任价值补偿

以省为单元量化其耕地保护社会责任价值,以此检验不同省份所承担的耕地保护社会责任价值与国家赋予的应承担价值偏差,从而确定其在该方面履行责任的程度。本文选取人均GDP等五个主要经济发展水平作参照,进行相关性分析,建立经济发展水平指标与单位面积耕地社会责任价值之间的回归模型。研究结果表明：粮食主产区所承担的责任远高于发达地区...     

MODELLING HEAT AND MOISTURE TRANSFER IN UNSATURATED SOIL USING A FINITE DIFFERENCE SELF-IMPLICIT METHOD ON PARALLEL COMPUTERS

A parallel numerical finite difference model, employing the self-implicit method, for coupled heat and moisture transfer in unsaturated soil is presented. The model is programmed in Occam and executed on a parallel computing network of transputers. An assessment of the model was achieved via the simulation of a laboratory experiment. A very good correlation between experimental and numerical results was obtained. Comparison of results with those obtained from a parallel explicit method is also illustrated showing no significant difference. The computational time employing the new method was, however, found to be half of that obtained using the explicit method. The computational efficiency of the approach was also found to be very high. © 1997 John Wiley & Sons, Ltd.     

State-of-the-art review of soft computing applications in underground excavations

Soft computing techniques are becoming even more popular and particularly amenable to model the complex behaviors of most geotechnical engineering systems since they have demonstrated superior predictive capacity,compared to the traditional methods.This paper presents an overview of some soft computing techniques as well as their applications in underground excavations.A case study is adopted to compare the predictive performances of soft computing techniques including eXtreme Gradient Boosting(XGBoost),Multivariate Adaptive Regression Splines(MARS),Artificial Neural Networks(ANN),and Support Vector Machine(SVM) in estimating the maximum lateral wall deflection induced by braced excavation.This study also discusses the merits and the limitations of some soft computing techniques,compared with the conventional approaches available.     

An efficient framework for ensemble of natural disaster simulations as a service

Calculations of risk from natural disasters may require ensembles of hundreds of thousands of simulations to accurately quantify the complex relationships between the outcome of a disaster and its contributing factors. Such large ensembles cannot typically be run on a single computer due to the limited computational resources available. Cloud Computing offers an attractive alternative, with an almost unlimited capacity for computation, storage, and network bandwidth. However, there are no clear mechanisms that define how to implement these complex natural disaster ensembles on the Cloud with minimal time and resources. As such, this paper proposes a system framework with two phases of cost optimization to run the ensembles as a service over Cloud. The cost is minimized through efficient distribution of the simulations among the cost-efficient instances and intelligent choice of the instances based on pricing models. We validate the proposed framework using real Cloud environment with real wildfire ensemble scenarios under different user requirements. The experimental results give an edge to the proposed system over the bag-of-task type execution on the Clouds with less cost and better flexibility.     

基于GPGPU的并行影像匹配算法

提出一种基于GPGPU的CUDA架构快速影像匹配并行算法,它能够在SIMT模式下完成高性能并行计算。并行算法根据GPU的并行结构和硬件特点,采用执行配置技术、高速存储技术和全局存储技术三种加速技术,优化数据存储结构,提高数据访问效率。实验结果表明,并行算法充分利用GPU的并行处理能力,在处理1280×1024分辨率的8位灰度图像时可达到最高多处理器warp占有率,速度是基于CPU实现的7倍。CUDA在高运算强度数据处理中呈现出的实时处理能力和计算能力,为进一步加速影像匹配性能和GPU通用计算提供了新的方法和思路。     

卫星重力资料分析的同解法研究及其仿真

对同解法的基本思想和流程进行归纳,研制相应的软件系统.利用模拟的GPS和星间测距数据进行同时确定重力场模型和卫星精密轨道的仿真模拟,验证本文设计思路的可行性和软件系统的可靠性.