高职Linux项目化课程教学评价体系的研究

高职院校培养一专多能的复合型应用型人才成为当前高职教育的首要任务。因此对高职Linux教学评价体系改革进行了实证研究,提出高职Linux教学评价应该结合高职培养目标的特点,依据真实性评价的理念,构建基于能力本位的高职Linux教学评价体系,从而促进高职学生Linux综合应用能力和综合素质的提高。     

引黄入晋北干线倒虹吸输水工程的水击压力控制

山西省万家寨引黄工程分成南干线和北干线.北干线倒虹吸输水工程全长113 km左右,采用内径2～2.2 m的PCCP管有压输水.研究了北干线倒虹吸输水工程的水击压力控制、调流阀安装位置对管道压力等级设计的影响及调流阀、泄压阀、检修阀的联合工作方式,以及设计了新型的多喷孔套筒调流阀以适应水击压力的控制要求.同时,也研究了该线路设计调压井或者溢流井的必要性及其参数.通过研究,不仅找出现有设计存在的安全隐患,提出了控制水击压力的工程措施,而且大大减少了工程投资.     

Performance evaluation of GAIA supercomputer using NPB multi-zone benchmarks

GAIA is a recently developed IBM POWER6 supercomputer consisting of 24 SMP compute nodes with 64-way processors each, and it is currently ranked 393 on the Top500 supercomputer list published in November 2009. In this paper, we present the performance characteristics of GAIA evaluated by interconnecting the 24 computing nodes with low-latency InfiniBand network. We evaluate the performance of the new dual-core Power 595 system in terms of increased problem size using the multi-zone versions of the NAS Parallel Benchmarks.     

Positive approximation and converse approximation in interval-valued fuzzy rough sets

Methods of fuzzy rule extraction based on rough set theory are rarely reported in incomplete interval-valued fuzzy information systems. Thus, this paper deals with such systems. Instead of obtaining rules by attribute reduction, which may have a negative effect on inducting good rules, the objective of this paper is to extract rules without computing attribute reducts. The data completeness of missing attribute values is first presented. Positive and converse approximations in interval-valued fuzzy rough sets are then defined, and their important properties are discussed. Two algorithms based on positive and converse approximations, namely, mine rules based on the positive approximation (MRBPA) and mine rules based on the converse approximation (MRBCA), are proposed for rule extraction. The two algorithms are evaluated by several data sets from the UC Irvine Machine Learning Repository. The experimental results show that MRBPA and MRBCA achieve better classification performances than the method based on attribute reduction.     

Optimization for limited angle tomography in medical image processing

This paper aims to reduce the problems of incomplete data in computed tomography, which happens frequently in medical image process and analysis, e.g., when the high-density region of objects can only be penetrated by X-rays at a limited angular range. As the projection data are available only in an angular range, the incomplete data problem can be attributed to the limited angle problem, which is an ill-posed inverse problem. Image reconstruction based on total variation (TV) reduces the problem and gives better performance on edge-preserving reconstruction; however, the artificial parameter can only be determined through considerable experimentation. In this paper, an effective TV objective function is proposed to reduce the inverse problem in the limited angle tomography. This novel objective function provides a robust and effective reconstruction without any artificial parameter in the iterative processes, using the TV as a multiplicative constraint. The results demonstrate that this reconstruction strategy outperforms some previous ones.     

Pricing strategies for tied digital contents and devices

Media companies are increasingly offering digital content to consumers. Many of these companies are tying digital content with their proprietary digital devices. In this study, we develop a consumer demand model for digital device and digital content based on a constant elasticity demand function. In modeling consumer valuation of the digital device, we take consumer surplus on digital content into account. We further derive equilibrium prices for digital devices based on an oligopoly competition model with horizontal product differentiation. We analyze the equilibrium prices and how prices affect firm profits. We find product differentiation and the level of product substitutability affect prices. We also find that content price plays a significant role in affecting the price of the digital device. Content price can either increase or decrease the tied digital device price depending on the profit margin and demand elasticity of the digital content. We further analyze how content and device prices affect their respective profits and the overall profit of the firm. We extend our model to vertical product differentiation and find vertical product differentiation and the level of product quality affect prices.     

User-centric query refinement and processing using granularity-based strategies

Under the context of large-scale scientific literatures, this paper provides a user-centric approach for refining and processing incomplete or vague query based on cognitive- and granularity-based strategies. From the viewpoints of user interests retention and granular information processing, we examine various strategies for user-centric unification of search and reasoning. Inspired by the basic level for human problem-solving in cognitive science, we refine a query based on retained user interests. We bring the multi-level, multi-perspective strategies from human problem-solving to large-scale search and reasoning. The power/exponential law-based interests retention modeling, network statistics–based data selection, and ontology-supervised hierarchical reasoning are developed to implement these strategies. As an illustration, we investigate some case studies based on a large-scale scientific literature dataset, DBLP. The experimental results show that the proposed strategies are potentially effective.     

干扰约束下的认知无线电传输链路自适应算法

针对干扰约束下的认知无线电传输链路自适应算法开展研究,基于OFDM的认知用户与主用户共存,认知用户在保证对主用户干扰容限的前提下执行子载波与功率分配,以树形分支贪婪算法为基础,引入功率余量因子和干扰余量因子并通过比较余量因子相对大小来选择子载波,通过减小分支数以降低算法复杂度.仿真结果表明,改进的树形分支贪婪算法获得的...     

移动分布感知的车载自组网络数据分发

提出了一种面向发布/订阅系统基于车辆移动分布感知的事件分发策略MDA(mobile distribution-aware data dissemination).基于车流的自组织性及自稳性的特点,建立VANET(vehicular ad hoc network)下的发布/订阅模型,通过计算车辆与移动订阅者的相遇概率,预测订阅者的移动分布,并以此为依据实时部署和调度广播令牌在网络中的转发,从而有效地控制事件代理的分布,保证了数据传递的有效性.与已有相关研究相比,MDA采用的启发式算法,能够使事件代理的分布更好地适应网络环境的动态变化.此外,MDA采用了一种基于概率预测密度的令牌控制算法,通过实时地调整令牌的数量,进而控制事件代理的数量,降低了整个网络的负载.模拟实验结果表明,与现有的几种消息分发算法相比,MDA能以较低的网络负载和传输延迟获得较高的数据传输成功率.