大岗山水电站工程边坡稳定性分析

采用SLOPE/W模块对大岗山水电站工程边坡稳定性进行了计算分析。该水电站右岸工程边坡高达420m,卸荷裂隙控制右岸边坡的整体稳定性,构成确定性的2个潜在不稳定块体。分析结果表明,天然状态下右岸边坡整体稳定,地震对边坡稳定性影响较大,开挖对边坡稳定性有一定影响。     

Fast computation of minimal elementary decompositions of metabolic flux vectors

The concept of elementary flux vector is valuable in a number of applications of metabolic engineering. For instance, in metabolic flux analysis, each admissible flux vector can be expressed as a non-negative linear combination of a small number of elementary flux vectors. However a critical issue concerns the total number of elementary flux vectors which may be huge because it combinatorially increases with the size of the metabolic network. In this paper we present a fast algorithm that randomly computes a decomposition of admissible flux vectors in a minimal number of elementary flux vectors without explicitly enumerating all of them.     

Selection of third party software in Off-The-Shelf-based software development—An interview study with industrial practitioners

The success of software development using third party components highly depends on the ability to select a suitable component for the intended application. The evidence shows that there is limited knowledge about current industrial OTS selection practices. As a result, there is often a gap between theory and practice, and the proposed methods for supporting selection are rarely adopted in the industrial practice. This paper's goal is to investigate the actual industrial practice of component selection in order to provide an initial empirical basis that allows the reconciliation of research and industrial endeavors. The study consisted of semi-structured interviews with 23 employees from 20 different software-intensive companies that mostly develop web information system applications. It provides qualitative information that help to further understand these practices, and emphasize some aspects that have been overlooked by researchers. For instance, although the literature claims that component repositories are important for locating reusable components; these are hardly used in industrial practice. Instead, other resources that have not received considerable attention are used with this aim. Practices and potential market niches for software-intensive companies have been also identified. The results are valuable from both the research and the industrial perspectives as they provide a basis for formulating well-substantiated hypotheses and more effective improvement strategies.     

Flash memory efficient LTL model checking

As the capacity and speed of flash memories in form of solid state disks grow, they are becoming a practical alternative for standard magnetic drives. Currently, most solid-state disks are based on NAND technology and much faster than magnetic disks in random reads, while in random writes they are generally not.So far, large-scale LTL model checking algorithms have been designed to employ external memory optimized for magnetic disks. We propose algorithms optimized for flash memory access. In contrast to approaches relying on the delayed detection of duplicate states, in this work, we design and exploit appropriate hash functions to re-invent immediate duplicate detection.For flash memory efficient on-the-fly LTL model checking, which aims at finding any counter-example to the specified LTL property, we study hash functions adapted to the two-level hierarchy of RAM and flash memory. For flash memory efficient off-line LTL model checking, which aims at generating a minimal counterexample and scans the entire state space at least once, we analyze the effect of outsourcing a memory-based perfect hash function from RAM to flash memory.Since the characteristics of flash memories are different to magnetic hard disks, the existing I/O complexity model is no longer sufficient. Therefore, we provide an extended model for the computation of the I/O complexity adapted to flash memories that has a better fit to the observed behavior of our algorithms.     

Hybrid assessment method for software engineering decisions

During software development, many decisions need to be made to guarantee the satisfaction of the stakeholders' requirements and goals. The full satisfaction of all of these requirements and goals may not be possible, requiring decisions over conflicting human interests as well as technological alternatives, with an impact on the quality and cost of the final solution. This work aims at assessing the suitability of multi-criteria decision making (MCDM) methods to support software engineers' decisions. To fulfil this aim, a HAM (Hybrid Assessment Method) is proposed, which gives its user the ability to perceive the influence different decisions may have on the final result. HAM is a simple and efficient method that combines one single pairwise comparison decision matrix (to determine the weights of criteria) with one classical weighted decision matrix (to prioritize the alternatives). To avoid consistency problems regarding the scale and the prioritization method, HAM uses a geometric scale for assessing the criteria and the geometric mean for determining the alternative ratings.     

An algorithmic framework for network reconstruction

Models of biological systems and phenomena are of high scientific interest and practical relevance, but not always easy to obtain due to their inherent complexity. To gain the required insight, experimental data are provided and need to be interpreted in terms of models that explain the observed phenomena. In systems biology the framework of Petri nets is often used to describe models for the regulatory mechanisms of biological systems. The aim of this paper is to provide, based on results in Marwan et al. (2008) [1] and Durzinsky et al. (2008) [2], an algorithmic framework for the challenging task of generating all possible Petri nets fitting the given experimental data.     

基于VBA技术的因次分析自动化方法

对于化工过程或相关的工程实验等工程实际问题,数学上直接应用基本方程求解极为困难,有赖于实验研究来解决。因次分析方法将工程实际问题中实验条件下物理量之间的关联视为无因次量之间的关联,大大降低变量数目,成数量级地减少实验工作量,使相关物理量较多的化工过程通过实验获得物理量之间的关联成为可能。对于复杂的化工过程等实际问题,经典的因次分析方法涉及化工过程建模、若干个方程组的求解及大量重复而以烦琐的数学计算,才能找出这些无因次量之间关联。采用ActiveX技术与VBA混合编程进行因次分析,自动选择核心物理量、求出核心物理量待定幂次,自动对数群的4项核心物理量幂次与数群物理量组合表对照、确定无因次数群。利用VBA混合编程自动实现工程实验的因次分析,获得实验模型与原型结构之间的相似准则,建立并简化了实验关联公式,并通过示例,阐述了因次分析的自动化方法及其实现过程。因次分析自动化方法应用于学生毕业论文的工程实验设计中,分析化工过程的相似关系,为指导毕业论文的工程实验提供可靠依据,使用方便,收效良好。     

基于红外线光电开关的测速系统设计与应用

随着现代科技的不断进步,各个领域对测速系统的应用越来越多,同时也对测速精度的要求日益苛刻。文中提出一种基于红外线光电开关的测速系统,采用NI6251高速数据采集卡以及LabVIEW软件设计代替了传统的基于单片机或FPGA等自行设计的硬件电路所组成的数据采集分析系统,提高了测速系统的可靠性和测量精度。文中介绍了整个测速系统的工作原理、结构设计和软件设计,并进行了系统的误差分析。现场试验结果证明,该方法能够将高速直线运动物体的测试误差保证在0.0015%以内。     

基于语义的领域虚拟数据中心研究与实现

油井工程领域涉及的数据具有分布、异构和自治性强等特点,并且存在复杂的语义关联,无法为全局决策提供有效的数据支持。利用本体和虚拟视图集成技术,提出了油井工程虚拟数据中心解决方案,通过构造领域全局本体并利用本体抽取、本体映射和查询转换实现领域数据语义集成,提供了统一和基于语义的数据查询与共享服务。实际应用表明,虚拟数据中心能够为油井生产决策提供全面和实时的数据支持。     

逼近点云的三角形网格的边缘误差减小研究

基于SOFM神经网络构建的三角形网格模型可以实现测量点云压缩后的Delaunay三角逼近剖分,但该模型存在边缘误差。为减小三角形网格的边缘误差,改进了三角形网格模型的训练模式,提出了3步训练模式。第1步采用整个测量点云,对三角形网格模型中的所有神经元进行整体训练;第2步采用测量点云中的边界点集,对三角形网格模型中的网格边界神经元进行训练;第3步采用边界点集中的角点点集,对与边界角点匹配最佳的网格边界神经元进行训练。算例表明,应用该训练模式,可以有效减小三角形网格的边缘误差,三角形网格逼近散乱点云的逼近精度得到提高并覆盖散乱点云整体分布范围。