基于DLL的工控组态软件内存数据库系统的设计

介绍基于动态链接库DLL的内存数据库系统的设计思想和实现方法。提出在DLL中利用内存映像文件来实现多进程共享内存数据库的方法，同时给出了内存数据库接口。建立的内存数据库系统具有很好的开放性。     

DCS组态软件实时数据库系统的设计

实时数据库系统是DCS组态软件体系结构的关键部分。通过分析实时数据库的特点和DCS系统的使用要求，提出了采取传统数据库系统、文件系统和内存数据库系统兼用的多种存储介质来构建的实时数据库系统，并利用DLL来建立动态实时数据库，从而实现代码和资源共享，进而实现任务间的快速通信。最后给出了实时数据库及相关数据模型的实现方法实例。     

组态软件实时数据库系统研究及设计

利用Windows的DLL(动态连接库)和全局共享内存技术来建立系统实时数据库的设计思想,采取传统数据库系统、文件系统和内存数据库系统兼用,利用多种存储介质来构造系统的实时数据库系统,并通过给用户提供一套接口标准——实时数据库系统接口,来实现I/O驱动程序与用户程序和实时数据库系统间的高速数据传递。     

用于内存数据库的Hash索引的设计与实现

电信领域已成为数据密集型行业,需要高性能的数据库系统作为支撑系统,基于磁盘的数据库系统不能满足“实时”、“近实时”访问数据库的需求,将数据库核心数据驻留在内存中,可以使用内存数据库来满足需求。Hash索引是数据库系统中广泛使用的索引技术之一,它能够快速地访问数据,易于设计和实现。该文根据内存数据库的特点,为电信网管系统的内存数据库设计并实现了Hash索引。     

基于Win CE系统的内存数据库SQL解析器的分析与设计

本文在厦门大学研发的基于WinCE系统内存数据库xMMDB的基础上,利用xMMDB提供的内存数据库API,设计并实现了SQL解析器,使该内存数据库系统能够支持SQL语言。本文阐述了使用yacc工具设计SQL操作的语法树及完成内存数据库系统语法分析的过程,提出了一种SQL解析器的实现方法,通过C语言编写的词法分析程序,向语法分析程序提供单词,并设计了一个结构体存储词法分析中的关键字属性,以便在调用内存数据库API的时候使用。     

一种主动实时数据库的系统内存管理方法

通过对一个主动实时数据库(ARTs—DB)的研究，借鉴操作系统的内存管理机制，提出了一种具有现代应用特征的数据库系统内存管理模式。文中从ARTs—DB的系统内存管理定义出发，探讨了主动实时数据库系统内存管理的目标及实现策略，并详细介绍了一种实现方法。     

内存数据库组织分区法的评析

实时数据库系统(RTDBS)的高性能要求以内存数据库(MMDB)作底层支持。内存数据库分区方法是将数据库逻辑对象存储在内存中的组织管理方法。该文提出了比较不同的数据库组织分区方法的模型和方法,试图找出适合于内存数据库的分区方法。     

主动实时内存数据库系统的数据交换策略及实现

实时数据库系统的高性能要求以内存数据库(MMDB)做底层支持。内存数据库事务在运行过程中没有内外存I/O,这就要求在对事务进行预处理(知识提取)的基础上合理地进行内外存交换。该文针对一个自主开发的主动实时内存数据库系统(ART-Ⅱ),介绍了其内外存数据交换的策略及实现。     

内存数据库相关技术的研究与分析

所谓内存数据库,简单地说就是任何时刻任意一个活动事务所操作的数据集都要存放在内存中,换句话说,内存数据库系统就是数据库的“工作版本“常驻内存的数据库系统.显然.它要求较大的内存量,至少应能存储当前处理的数据,但并不要求在任何时刻整个数据库都存放在内存.内存数据库是支持高性能信息处理的有力工具,是实现诸如实时数据库、智能数据库等的基础,其核心问题是数据库的存储结构及存取方法,以提高空间利用率.为此,首先讨论了内存数据库的定义,接着分析了并发控制、MMDB的逻辑优化规则、动态降低锁粒度和动态提高锁粒度,最后做了总结.     

基于Hash+链表索引的专用型内存数据库系统的设计与实现

文章研究了内存数据库管理系统的原理和关键技术,根据移动短信监控系统中内存数据库的特点,设计和实现了一个基于Hash+链表索引的专用型内存数据库系统,用于解决垃圾短信分析系统中海量短信的存取问题.     

基于船载太阳光度计的中国海域MODIS卫星反演气溶胶光学参数验证

利用2006~2007年中国海洋大学东方红2号科考船在中国黄海和东海海域的POM-01MK2太阳光度计气溶胶光学参数的观测资料,与MODIS反演结果进行比较,给出了光学厚度、| ngstrm指数和粒子有效半径的对比结果。结果表明：两种观测方法得到的气溶胶光学厚度的一致性较好,相关系数（标准差）达0.97（0.08）,73%的对比结果在期望误差（Δτ=±0.03±0.05τ）之内;季节分类对比结果,秋季和春季相关系数（标准差）均为0.97（0.08）;海域分类对比结果,黄海北部海域和黄海南部海域相关系数（标准差）分别为0.98（0.08）和0.76（0.10）。MODIS反演得到的| ngstrm指数偏低,相关系数（标准差）为0.67（0.23）;按季节分类得到,秋季和春季相关系数（标准差）分别为0.71（0.27）和0.62（0.19）;按海域分类得到,黄海北部海域和黄海南部海域相关系数（标准差）分别为0.87（0.07）和0.70（0.30）。粒子有效半径的对比结果偏差和离散度较大,相关系数（标准差）仅为0.31（0.10）。造成这种现象的原因可能是该海域沙尘气溶胶和人类源二次气溶胶浓度较高导致海上气溶胶光学性质同MODIS反演中使用的光学参量有较大差别。     

Hiding secret data in images via predictive coding

This paper presents a prediction-based image-hiding scheme that embeds secret data into compression codes during image compression. This scheme employs a two-stage structure: a prediction stage and an entropy coding stage. The secret data is embedded into the difference values of a given image after the prediction stage is performed.According to the experimental results, the image quality is better than Jpeg-Jsteg and its improved scheme (Inform. Sci. 141 (1-2) (2002) 123). The average image quality of the stego-images in the proposed scheme is greater than 50 dB when the hiding capacity is 1 bit per pixel, whereas those values in Jpeg-Jsteg and scheme in Chang et al. (Inform. Sci. 141 (1-2) (2002) 123) are 37.04 and 33.73 dB, respectively. The hiding capacity of the proposed scheme is 65,536 bits when the hiding capacity is 1 bit per pixel, whereas it is 53,248 bits in scheme (Inform. Sci. 141 (1-2) (2002) 123) and less than 3000 bits in Jpeg-Jsteg.     

Cooperative path planning with priority target assignment and collision avoidance guidance for rescue unmanned surface vehicles in a complex ocean environment

In this paper, a novel cooperative path planning scheme of unmanned surface vehicles (USVs) for rescuing targets in a complex ocean environment is proposed. The primary objective of the rescue USVs is to bring all targets back safely on the premise of first rescuing priority targets, while optimizing the path length, the navigation time and the angular energy. The main contributions of this paper are as follows: (1) The proposed K-means-division (KMD) algorithm is able to identify a complex ocean environment with collision-free zone and static-obstacles zone; (2) The proposed path planning method with fast-marching-method-based ellipse guidance range (E-FMM) is able to optimize the angular energy while ensuring safety; (3) The proposed cooperative management system (including priority-target-assignment (PTA) with reward-mechanism genetic-optimization (RM-GO) and collision-avoidance (CA) guidance law with Tangent-based surge-varying wave-disturbances-observer (Tangent-SV-WDO)) can accomplish the mission of the rescue USVs. Comparative studies with the state-of-the-art methods demonstrate that the proposed cooperative path planning scheme is superior in terms of priority-target-assignment (PTA) and collision-avoidance (CA) of the actual rescue work.     

Adaptive filtering of EEG/ERP through Bounded Range Artificial Bee Colony (BR-ABC) algorithm

In this paper, the Artificial Bee Colony (ABC) algorithm is applied to construct Adaptive Noise Canceller (ANC) for electroencephalogram (EEG)/Event Related Potential (ERP) filtering with modified range selection, described as Bounded Range ABC (BR-ABC). ERP generated due to hand movement is filtered through Adaptive Noise Canceller (ANC) from the EEG signals. ANCs are also implemented with Least Mean Square (LMS) and Recursive Least Square (RLS) algorithm. Performance of the algorithms is evaluated in terms of Signal-to-Noise Ratio (SNR) in dB, correlation between resultant and template ERP, and mean value difference. Testing of their noise attenuation capability is done on contaminated ERP with white noise at different SNR levels. A comparative study of the performance of conventional gradient based methods like LMS, RLS, and ABC algorithm is also made which reveals that ABC algorithm gives better performance in highly noisy environment.     

Design and implementation of a realtime co-processor for denoising Fiber Optic Gyroscope signal

The amount of noise present in the Fiber Optic Gyroscope (FOG) signal limits its applications and has a negative impact on navigation system. Existing algorithms such as Discrete Wavelet Transform (DWT), Kalman Filter (KF) denoise the FOG signal under static environment, however denoising fails in dynamic environment. Therefore in this paper an Adaptive Moving Average Dual Mode Kalman Filter (AMADMKF) is developed for denoising the FOG signal under both the static and dynamic environments. Performance of the proposed algorithm is compared with DWT and KF techniques. Further, a hardware Intellectual Property (IP) of the algorithm is developed for System on Chip (SoC) implementation using Xilinx Virtex-5 Field Programmable Gate Array (Virtex-5FX70T-1136). The developed IP is interfaced as a Co-processor/ Auxiliary Processing Unit (APU) with the PowerPC (PPC440) embedded processor of the FPGA. It is proved that the proposed system is an efficient solution for denoising the FOG signal in real-time environment. Hardware acceleration of developed Co-processor is 65× with respect to its equivalent software implementation of AMADMKF algorithm in the PPC440 embedded processor.     

Structural analysis based sensor measurement fault diagnosis in cement industries

This investigation presents a fault diagnosis methodology for detecting sensor faults in cement industries pyro processing section. It works in three steps: (a) modelling, (b) analysis, and (c) validation. In the modelling, the actual data from the cement pyro processing is used to do a correlation analysis between output and input variables. The structural model is obtained from the correlation tests. During the analysis phase the Structural analysis Tool (SaTool) is used to detect the detectability and isolability of the faults. The results of the structural analysis are validated in a cement industry using residual analysis performed using structural sensor model and real-time measurements. The main advantages of this fault diagnosis technique are: (a) it requires only correlation analysis to obtain the structural model without a detailed physical model as in other methods, (b) conclusions regarding detectability and isolability can be easily drawn during the analysis stage itself, and (c) the method is simple compared to the model-based, and data-history based methods. The effectiveness of the proposed method is illustrated using data from cement pyro processing plant and its performance is compared with model based approaches for four different types of sensor faults: (1) bias, (2) drift, (3) stuck, and (4) measurement failures. Our results demonstrate that the structural method is able to detect the sensor faults even in the presence of noisy information, and its performance is comparable with that of model based approaches without employing a physical model.     

Multi-model predictive control with local constraints based on model switching

Because model switching system is a typical form of Takagi-Sugeno(T-S) model which is an univer sal approximator of continuous nonlinear systems,we describe the model switching system as mixed logical dynamical (MLD) system and use it in model predictive control (MPC) in this paper.Considering t hat each local model is only valid in each l ocal region,we add local constraints to local models.The stability of proposed multi-model predictiv e control (MMPC) algorithm is analyzed, and the p erformance of MMPC is also demonstrated on an in ulti-multi-output(MIMO) simulated pH neutralization process.     

A bi-layer optimization approach for a hybrid flow shop scheduling problem involving controllable processing times in the steelmaking industry

A steelmaking-continuous casting (SCC) scheduling problem is an example of complex hybrid flow shop scheduling problem (HFSSP) with a strong industrial background. This paper investigates the SCC scheduling problem that involves controllable processing times (CPT) with multiple objectives concerning the total waiting time, earliness/tardiness and adjusting cost. The SCC scheduling problem with CPT is seldom discussed in the existing literature. This study is motivated by the practical situation of a large integrated steel company in which the just-in-time (JIT) and cost-cutting production strategy have become a significant concern. To address this complex HFSSP, the scheduling problem is decomposed into two subproblems: a parallel machine scheduling problem (PMSP) in the last stage and an HFSSP in the upstream stages. First, a hybrid differential evolution (HDE) algorithm combined with a variable neighborhood decomposition search (VNDS) is proposed for the former subproblem. Second, an iterative backward list scheduling (IBLS) algorithm is presented to solve the latter subproblem. The effectiveness of this bi-layer optimization approach is verified by computational experiments on well-designed and real-world scheduling instances. This study provides a new perspective on modeling and solving practical SCC scheduling problems.     

粗集理论中连续属性的广义离散化

提出一种处理区间属性值离散化问题的新方法,其特点是在离散化过程中强调类别可分离性,首先拓展已有的基于断点划分的离散化定义,给出基于类别可分离性的广义离散化定义;然后描述了广义离散化算法并进行时间复杂性分析;最后利用辐射源信号进行了仿真实验．结果表明,该方法能有效离散区问属性决策系统,简化分类器的设计和提高识别率,从而拓展了粗集理论的应用范围．