基于优化目标可调控的免疫网络算法的分析与应用

针对目前几种免疫网络模型在数据聚类方面应用的一些不足,在aiNet免疫算法的基础上结合函数优化的思想提出一种基于目标可调控的免疫模型。并在算法中给出目标控制函数,和细胞记忆库的概念。本算法提高了免疫学习质量并从整体上对免疫网络进行优化。     

面向构件接口变异的模型检验技术研究

随着构件技术在软件开发中的广泛应用,人们对构件化软件系统质量的要求也在不断提高。该文运用模型检验技术进行接口变异测试的相关研究工作。该文首先详细介绍了基于模型检验技术的变异测试的基本原理,随后通过对构件集成时接口之间的交互关系进行分析后,提出了通过构造接口函数调用关系模型进行基于模型检验的接口变异测试方法。最后,通过实例进行了对JavaBean构件的接口测试用例的自动生成。     

Robust Feature-Preserving Mesh Denoising Based on Consistent Subneighborhoods

In this paper, we introduce a feature-preserving denoising algorithm. It is built on the premise that the underlying surface of a noisy mesh is piecewise smooth, and a sharp feature lies on the intersection of multiple smooth surface regions. A vertex close to a sharp feature is likely to have a neighborhood that includes distinct smooth segments. By defining the consistent subneighborhood as the segment whose geometry and normal orientation most consistent with those of the vertex, we can completely remove the influence from neighbors lying on other segments during denoising. Our method identifies piecewise smooth subneighborhoods using a robust density-based clustering algorithm based on shared nearest neighbors. In our method, we obtain an initial estimate of vertex normals and curvature tensors by robustly fitting a local quadric model. An anisotropic filter based on optimal estimation theory is further applied to smooth the normal field and the curvature tensor field. This is followed by second-order bilateral filtering, which better preserves curvature details and alleviates volume shrinkage during denoising. The support of these filters is defined by the consistent subneighborhood of a vertex. We have applied this algorithm to both generic and CAD models, and sharp features, such as edges and corners, are very well preserved.     

Skew detection in document images based on rectangular active contour

The digitalization processes of documents produce frequently images with small rotation angles. The skew angles in document images degrade the performance of optical character recognition (OCR) tools. Therefore, skew detection of document images plays an important role in automatic document analysis systems. In this paper, we propose a Rectangular Active Contour Model (RAC Model) for content region detection and skew angle calculation by imposing a rectangular shape constraint on the zero-level set in Chan–Vese Model (C-V Model) according to the rectangular feature of content regions in document images. Our algorithm differs from other skew detection methods in that it does not rely on local image features. Instead, it uses global image features and shape constraint to obtain a strong robustness in detecting skew angles of document images. We experimented on different types of document images. Comparing the results with other skew detection algorithms, our algorithm is more accurate in detecting the skews of the complex document images with different fonts, tables, illustrations, and layouts. We do not need to pre-process the original image, even if it is noisy, and at the same time the rectangular content region of a document image is also detected.     

A collaborative platform for complex product design with an extended HLA integration architecture

How to integrate the heterogeneous, autonomous models in a distributed environment, running on Internet, integration based on multilayer federation architecture and simulation resources dynamic reuse are the major difficulties for complex product collaborative design and simulation. An extended HLA-based collaborative simulation platform for multidisciplinary collaborative design is proposed. The architecture of platform is first given. The idea and realization of four key technologies, the dynamic creation of simulation federation based on resource management federation (RMF), HLA enabled template, collaborative simulation algorithm based on stage-data synchronization and TH_RTI, an extensible HLA runtime infrastructure (RTI), which is a web enabled RTI and can be used at Internet, are emphasized. Finally, an industry case is given. The demonstration of these prototype systems shows that extended HLA integration architecture is effective infrastructure for multidisciplinary collaborative modeling and simulation (M&S).     

Multistage System Planning for Hydrogen Production and Distribution

Hydrogen is an energy carrier that has the potential to improve the sustainability of transportation fuels and reduce oil dependence. This paper presents a stochastic dynamic programming model for sequentially building a hydrogen production and distribution system. The decision variables are the sequence and locations of the central production sites and the corresponding distribution systems from supply to demand sites. A case study based on the geographic setting of Northern California is included, in which the hydrogen is produced via coal gasification and transported from plant to city gates (demand sites) by cryogenic liquid hydrogen trucks. Future demands for hydrogen are modeled as uncertain parameters, with an assumption that hydrogen fuel cell vehicle (HFCV) market penetration rate increases from 1% to 25% over a 20-year period. This model provides multistage decision support for long term transportation energy planning at national and regional levels.     

Solving Stochastic Transportation Network Protection Problems Using the Progressive Hedging-based Method

This research focuses on pre-disaster transportation network protection against uncertain future disasters. Given limited resources, the goal of the central planner is to choose the best set of network components to protect while allowing the network users to follow their own best-perceived routes in any resultant network configuration. This problem is formulated as a two-stage stochastic programming problem with equilibrium constraints, where the objective is to minimize the total expected physical and social losses caused by potential disasters. Developing efficient solution methods for such a problem can be challenging. In this work, we will demonstrate the applicability of progressive hedging-based method for solving large scale stochastic network optimization problems with equilibrium constraints. In the proposed solution procedure, we solve each modified scenario sub-problem as a mathematical program with complementary constraints and then gradually aggregate scenario-dependent solutions to the final optimal solution.     

基于双核处理器的机敏结构振动主动控制器设计

针对分布植入式压电机敏结构振动主动控制技术需求,提出一种新型基于嵌入式架构的多通道振动响应控制器;该系统以嵌入式处理器(ARM)和数字信号处理器(DSP)为双处理器核心,ARM处理器上运行实时操作系统μC/OS-II,并提供人机接口单元和通信等功能,DSP处理器主要负责数据采集、算法运算和处理结果输出,整个系统充分结合了ARM处理器强大的中断处理能力和DSP处理器高效快速的数据处理能力;详细阐述系统总体设计思想、系统软硬件设计方案、系统构成与核心部件、功能指标和开发过程,以及实验测试设置与结果验证;设计开发与测试分析表明,该控制器性能良好且功能丰富,能够满足实际研究工作的需要。     

研究生人工智能系列课程教学改革

从人工智能系列课程的实际特点出发,结合中南大学智能所教师授课方面的经验,总结并提出几点教学改革建议。这些教学经验在博士研究生教学改革中收到良好效果,对其他系列课程的研究性教学也有重要的指导作用。     

一种卫星遥测数据相关性分析方法

卫星遥测数据反映了卫星各系统的实时工作情况,是对卫星各系统工作状态进行分析判断的依据,其数据处理结果及质量直接影响卫星在轨性能的分析和状态的评定.运用ID3算法对卫星太阳帆板遥测数据进行分析,挖掘隐藏在数据中的知识和规则,得到数据之间的关联性,为卫星在轨性能分析提供依据.