基于ASP.NET的ADO与ADO.NET分析与研究

探讨基于ASP．NET框架ADO和ADO．NET的两种数据库访问技术，并给出一个在ASP．NET下使用ADO．NET组件对数据库访问的实例。然后，对这两种技术在缓存中的数据集存储形式、脱机与连机关系、标准化程度、传输性能方面进行了比较分析，突出了ADO．NET的优点。     

Sql存储过程在ASP.NET中的应用

在使用ASP．NET的过程中，数据库访问是一个很重要的部分，特别是在B／S系统的构建过程中，数据库操作几乎成为了一个必不可少的操作。调用存储过程实现数据库操作是很多程序员使用的方法。本文将向大家介绍存储过程度ASP，NET数据库应用程序中存储过程的应用．以此提高ASP．NET数据库应用程序的总体性能。     

基于ASP．NET数据分页技术的研究

数据分页是Web项目中经常使用的一种技术,尤其应用在对海量数据库中的访问,它是提高用户数据访问速度的主要手段。本文结合ASP．NET和存储过程的优点,详细分析了ASP．NET中各种数据分页技术,尤其是利用存储过程来进行分页的技术．通过测试分析结果比较了各种数据分页技术的性能。     

基于.NET的数据访问策略

为了实现基于.NET构架的高效数据库访问，文中介绍了基于.NET构架的四种数据访问策略，并解释这些策略对连接数据源的条件限制以及数据库读取方式的内部运行机制。然后给出具体实例，说明如何实现其中的两种策略，并附上机运行结果。最后，比较这些数据访问策略的特点，分析总结出各种策略适用环境。     

基于.NET的数据访问策略

为了实现基于.NET构架的高效数据库访问,文中介绍了基于.NET构架的四种数据访问策略,并解释这些策略对连接数据源的条件限制以及数据库读取方式的内部运行机制.然后给出具体实例,说明如何实现其中的两种策略,并附上机运行结果.最后,比较这些数据访问策略的特点,分析总结出各种策略适用环境.     

ADO．NET数据库访问技术

ADO．NET是．NET应用程序与数据库通信的桥梁,其使用XML来进行数据交换并加入了许多新的程序接口,使得数据库访问更加简单？通过C#程序说明ADO．NET数据库访问过程。     

开发高性能ADO.NET应用程序的探讨

本文通过对ADO．NET数据库访问技术的分析，阐述了如何提高ADO．NET性的方法，包括选择合适的敷据提供程序、如何打开和关闭数据库连接、SQL指令的使用、存储过程的编写、DataReader和DataSet的选择以厦选择合适的事务等多方面的解决方案。     

ASP．NET下Web数据库访问技术研究

AD0．NET是ASP．NET下操作数捌库的核心组件,是一种全新的数据席访问机制。利用ADO．NET,开发者可以方便地访问种种基于Web的数据库,AD0．NET捉供的两种数据库访问方式：有连接方式和无连接方式,有连接方式它始终保持应用程序与数据库的连接状态;无连接方式使用DataAdapter对象查询到数据并填充到DataSet后就可以断开与数据库的连接。     

．NET数据库应用程序快速开发的方法与实现（下）

介绍．NET Framework中的源代码模型库CodeDOM,并讲解如何使用相关技术自动生成．NET数据库应用程序代码,包括存储过程、业务对象类、数据访问对象类,以及用户界面。这种开发方法不仅能够减少数据库应用开发中的大量重复操作,也有助于规范程序结构和代码风格。     

.NET平台下调用存储过程的方法

.NET采用了一种新的数据访问技术ADO.NET,在ADO.NET中可以通过动态SQL语句或者存储过程进行数据访问.然而,在真实环境中,存储过程具有确保数据访问操作一致性、安全、高效率等优点.因此结合合理的n层应用程序使用存储过程代替SQL语句进行数据访问,可以出于任何使用SQL语句的目的来使用存储过程.     

An automatic procedure for identifying alternative automobile ingress movements in young and elderly populations with or without prostheses

This paper presents an automatic numerical procedure for classifying the automobile ingress movements in young and elderly populations with or without prostheses. This procedure proceeds in two stages. The first stage works to identify the main movement strategies by classifying the subjects according to new indices, called 3BJCV (3 Bases Joint Contribution Vector). These indices make it possible to take the complexity of the automobile ingress movement into account. They quantify the contribution of the lower limbs chains angles' and those of the chain gathering the trunk and head in the final positioning of the midpoint between the two hips (MPH). The second stage specifies the main movement strategies obtained in stage 1 by classifying the subjects according to the relevant articular variables of the ingress movement.This two-stage procedure was applied to the ingress movements extracted from the national HANDIMAN (RNTS, 2004) project, measured in experiments carried out with a small vehicle and a large vehicle (i.e., a minivan). The two main ingress movement strategies were identified: a one-foot ingress strategy and a two-foot ingress strategy. In all, 6 ingress sub-strategies were highlighted automatically, without requiring any special expertise. Five of these sub-strategies had already been observed, based on the same experiments, in the past. The 6th sub-strategy was used by subjects who were divided into 2 other sub-strategy groups while of the observation.

Relevance to industry

The procedure proposed in this study can help ergonomists and car manufacturers to quantify and classify the automobile ingress movements without requiring any a priori expertise on the movement. It also helps to improve any given numerical simulation by providing numerical data characterizing the different ingress movement profiles.     

Evolutionary algorithms and gradient search: similarities anddifferences

Classical gradient methods and evolutionary algorithms represent two very different classes of optimization techniques that seem to have very different properties. This paper discusses some aspects of some “obvious” differences and explores to what extent a hybrid method, the evolutionary-gradient-search procedure, can be used beneficially in the field of continuous parameter optimization. Simulation experiments show that on some test functions, the hybrid method yields faster convergence than pure evolution strategies, but that on other test functions, the procedure exhibits the same deficiencies as steepest-descent methods     

蒙特卡罗与准蒙特卡罗相互融合的整体光照计算

蒙特卡罗方法具备普适性、鲁棒性以及与问题复杂度无关性等优点，非常适于十分难解的整体光照计算问题，但缺点是生成图像随机噪声大．准蒙特卡罗方法计算连续被积函数低维积分的收敛速度快于蒙特卡罗方法，但不适于直接求解复杂的整体光照计算问题．文中研究蒙特卡罗整体光照计算最根本环节，即随机游动的抽样模式，提出融合蒙特卡罗与准蒙特卡罗的两种通用的新型整体光照计算策略．两种新型策略可以应用于所有基于蒙特卡罗的整体光照算法，不仅能够降低生成图像的随机噪声，而且实现简单、不增加计算和存储开销．     

Multimode-oriented polynomial transformation-based defuzzificationstrategy and parameter learning procedure

In an earlier paper (1996), we proposed a set of generalized defuzzification strategies which can be characterized as single-mode-oriented strategies. A single-mode-oriented defuzzification strategy, although useful in many research projects and real world applications, cannot be applied to a multimode situation where two or more distinct possibility peaks exist in its membership function distribution. In this paper, for multimode-oriented generalized defuzzification applications, a multimode-oriented polynomial transformation based defuzzification strategy (M-PTD) is introduced. The new M-PTD strategy, which uses the Kalman filter in parameter learning procedure, offers a constraint-free and self-renewal defuzzification solution.     

Alternate strategies for solving bottleneck assignment problems —analysis and computational results

We analyse two strategies for solving the bottleneck assignment problem — the threshold method and the shortest augmenting path concept —, show their theoretical equivalence and computational behaviour. We develop a new rather efficient labeling technique to be used in the shortest augmenting path method and a hybrid procedure combining the advantages of both concepts. Extensive computational results are reported.     

Generalized defuzzification strategies and their parameter learningprocedures

Defuzzification is a procedure of crucial importance for fuzzy systems because a final crisp output (control) action is required in many theoretical and practical applications. The choice of defuzzification strategy, therefore, can directly affect the success of such applications. Among the existing strategies, neither the center of area (COA) nor the mean of maximum (MOM) emerges as the better defuzzification strategy. A compromise strategy that combines the two methods may offer a synergetic solution. In this paper, the authors introduce two new objective defuzzification strategies, Gaussian distribution transformation-based defuzzification (GTD) and polynomial transformation-based defuzzification (PTD), which are based on a discrete universe of discourse. Both strategies can perform better than the existing strategies and the PTD strategy offers a generalized defuzzification tool for a wide class of practical problems. Both strategies include the COA and MOM strategies as special cases, and both are based on parameter learning processes using the extended Kalman filter as their iterative improvement algorithms on sample database containing fuzzy sets and the associate defuzzified values. The proposed parameter learning procedures are capable of either off-line or on-line processing     

Robust ANalysis Of VAriance: An approach based on the Forward Search

A simple robust method for the detection of atypical observations and the analysis of their effect in the ANOVA framework is presented. It is proposed to use a forward search procedure that orders the observations by their closeness to the hypothesized model. The procedure can be applied following two different strategies: one that adds units maintaining the relative group dimension and the other that adds only one new unit at each step of the search. The assessment of the goodness of the method is carried out through a simulation study. The method is then applied to real data. Results are presented through easy to interpret plots which are powerful in revealing the structure of the data.     

A stochastic local search algorithm for constrained continuous global optimization

This paper presents a new stochastic local search algorithm known as feasible–infeasible search procedure (FISP) for constrained continuous global optimization. The proposed procedure uses metaheuristic strategies for combinatorial optimization as well as combined strategies for exploring continuous spaces, which are applied to an efficient process in increasingly refined neighborhoods of current points. We show effectiveness and efficiency of the proposed procedure on a standard set of 13 well‐known test problems. Furthermore, we compare the performance of FISP with SNOPT (sparse nonlinear optimizer) and with few successful existing stochastic algorithms on the same set of test problems.     

The Combination of Two Control Strategies for Series Hybrid Electric Vehicles

With most countries paying attention to the environment protection, hybrid electric vehicles have become a focus of automobile research and development due to the characteristics of energy saving and low emission. Power follower control strategy (PFCS) and DC-link voltage control strategy are two sorts of control strategies for series hybrid electric vehicles (HEVs). Combining those two control strategies is a new idea for control strategy of series hybrid electric vehicles. By tuning essential parameters which are the defined constants under DC-link voltage control and under PFCS, the points of minimum mass of equivalent fuel consumption (EFC) corresponding to a series of variables are marked for worldwide harmonized light vehicles test procedure (WLTP). The fuel economy of series HEVs with the combination control schemes performs better compared with individual control scheme. The results show the effects of the combination control schemes for series HEVs driving in an urban environment.      

UIO design for singular delayed LPV systems with application to actuator fault detection and isolation

In this paper, the unknown input observer (UIO) design for singular delayed linear parameter varying (LPV) systems is considered regarding its application to actuator fault detection and isolation. The design procedure assumes that the LPV system is represented in the polytopic framework. Existence and convergence conditions for the UIO are established. The design procedure is formulated by means of linear matrix inequalities (LMIs). Actuator fault detection and isolation is based on using the UIO approach for designing a residual generator that is completely decoupled from unknown inputs and exclusively sensitive to faults. Fault isolation is addressed considering two different strategies: dedicated and generalised bank of observers’ schemes. The applicability of these two schemes for the fault isolation is discussed. An open flow canal system is considered as a case study to illustrate the performance and usefulness of the proposed fault detection and isolation method in different fault scenarios.