机器翻译系统融合技术综述

该文对机器翻译研究中的系统融合方法进行了全面综述和分析。根据在多系统输出结果的基础上进行融合的层次差异,我们将系统融合方法分为三类 句子级系统融合、短语级系统融合和词汇级系统融合。然后,针对这三种融合方法,该文分别介绍了它们各自具有代表性的研究工作,包括实现方法、置信度估计和解码算法等,并着重阐述了近年来使用广泛的词汇级系统融合方法中用于构造混淆网络的词对齐技术。最后,该文对这三类系统融合方法进行了比较、总结和展望。     

降落伞投放实验仿真系统的研究与实现

该文介绍了某型降落伞投放实验仿真系统的组成、功能、设计思想和实现的方法。首先讨论了仿真系统的建模,提出了系统的功能并给出了整个系统的数据流图。接着介绍了伞系统的建模方法,重点讨论了主伞衣的模型和降落过程的实现。然后介绍了投放环境的仿真方法,讨论了天空、地形以及飞机的建模方法。最后给出了一个利用Open GL实现该系统的方法,并显示了系统的运行情况。该系统能真实反映降落伞的整个投放过程。     

微型嵌入式系统故障诊断方法综述

随着物联网和大数据的高速发展,微型嵌入式系统已经广泛应用于外卖、共享单车、运输、快递和智能家居等行业之中,现有的故障诊断研究主要集中在传统嵌入式系统上,因此针对微型嵌入式系统故障诊断文献相对较少。针对上述问题和结合该系统的特点(有限计算能力和存储空间的),提出了一类适合微型嵌入式系统故障诊断方法分类方法,将其分为两大类,即本地故障诊断方法和远程故障诊断方法。接着讲述了微型嵌入式系统故障诊断方法核心思想,总结出了各方法在微型嵌入式系统上运用的优缺点和应该注意的问题,最后讨论了微型嵌入式系统故障诊断亟待解决的问题。     

基于SystemC和POOSL的语音识别系统的系统级建模与性能分析的对比*

根据复杂嵌入式系统的系统级建模的需要,提出了一套复杂嵌入式系统的系统级设计流程和建模方法。该方法主要包括了层次化建模方法、TopDown建模方法、面向对象建模技术和YChart建模方法,并采用提出的系统级建模方法,分别使用SystemC语言和POOSL语言成功地对语音识别系统进行了建模;通过模型的仿真进行了性能分析,并对分别得到的性能分析结果进行了对比,两种语言的系统延迟时间与CPU占用率的性能分析结果基本一致,为建模人员进行复杂嵌入式系统的系统级建模和性能分析提供了指导与参考。     

基于云理论的多功能电子战系统作战效能评估方法

多功能电子战系统是一个动态、多变量、开放的复杂大系统,系统影响因素众多,逻辑关系复杂。因此,对多功能电子战进行效能评估非常困难。对于复杂的大系统,唯一有效处理开放的复杂大系统的方法就是定性和定量相结合的综合集成方法。文章采用定性和定量相结合的评估方法,即云理论方法建立了多功能电子战系统作战效能评估模型,并给出算例说明评估步骤。     

《数字信号处理》中系统的因果性、稳定性判断

数字信号处理中主要讨论线性移不变、因果、稳定系统,因此需要掌握如何判断一个系统的因果和稳定性。本文采用多种方法来判断系统的因果和稳定性,介绍了每种判断方法所适用的情况,并对容易发生错误的判断方法进行了分析。通过这些方法,我们可以快速而准确的判断系统的因果和稳定性。     

8031单片机数据采集系统

本文介绍了以8031单片机为控制核心的数据采集系统。该系统以对温度的采集、处理、显示和打印为例,具体介绍了系统硬件线路的配置原理、数据采集和处理的方法,并给出了控制程序,最后阐述了系统的调试方法和步骤。实践证明,该系统实用可靠。     

基于CBR的智能答疑系统范例库的研究与实现

CBR方法是近年来人工智能领域先进和实用的方法,范例库作为智能答疑系统的核心部分,为进一步提高答疑系统的智能性,将CBR引入范例库,研究了基于CBR的智能答疑系统范例库的构建方法,对聚类方法和遗传算法在CBR范例库的检索、维护中的应用进行了分析、测试。通过CBR范例库的建立、检索和维护有效地提高了智能答疑系统的性能、进一步提高了智能答疑系统的智能性。     

社会经济系统模型及建模方法述评(下)

为了系统的介绍社会经济系统建模与仿真方法,计划从"社会经济系统模型及建模方法述评"、"官产学合作创新系统建模及仿真方法研究"和"基于SWARM平台的社会经济系统仿真实证研究"等三个方面来进行阐述,本篇是该系列文章的首篇。在本篇中,作者依据系统理论与系统科学方法,采用"系统是社会存在的基本方式"和"系统模型将真实和深刻地反映复杂的社会经济系统实际状态"的观点,对作用于社会经济系统中的"双螺旋与三螺旋模型"、"复杂适应系统模型"和"系统动力学模型"等三类典型社会经济模型,进行了深入的解析和述评。     

导弹武器系统仿真可信度评估方法研究

飞航导弹武器系统是一个复杂大系统,复杂的仿真系统的可信度评估是一项关键技术,必须采取有效的手段和方法对整个仿真系统的可信度进行综合评估。关于仿真系统可信度评估的方法有很多如：相似度方法、层次分析方法、模糊综合评判法、CLIMB法和评价树方法等等,该文在综合分析各种方法的基础上,明确仿真可信度的基本概念和可信性评估的一般步骤,给出一个客观的、实用的、量化的、具有可操作性的导弹武器系统可信度评估方法。     

基于RMI网上教学数据实时处理模型研究与实现

随着Internet应用的普及,网上教学已成为重要的教学手段,而采用何种技术来实现网上教学数据的的实现处理与广播式传送则是系统成功与否的关键。本文详细叙述了利用RMI分布式对象技术设计实现的网上教学数据实时处理模型,并给出了该模型的详细实现过程,文中提出的模型,通过采用callback处理方式,既简化了数据处理过程,又达到了数据实时处理的目的,这一模型已被应用于我们开发的网上实时教学系统中。     

Robust tuning for machine-directional predictive control of MIMO paper-making processes

This paper solves the controller tuning problem of machine-directional predictive control for multiple-input–multiple-output (MIMO) paper-making processes represented as superposition of first-order-plus-dead-time (FOPDT) components with uncertain model parameters. A user-friendly multi-variable tuning problem is formulated based on user-specified time domain specifications and then simplified based on the structure of the closed-loop system. Based on the simplified tuning problem and a proposed performance evaluation technique, a fast multi-variable tuning technique is developed by ignoring the constraints of the MPC. In addition, a technique to predict the computation time of the tuning algorithm is proposed. The efficiency of the proposed method is verified through Honeywell real time simulator platform with a MIMO paper-making process obtained from real data from an industrial site.     

粗糙集数据挖掘技术在丙酮精制中的应用研究

将基于粗糙集理论的数据挖掘方法应用于丙酮精制过程产品质量的预报。针对流程工业数据高维、构成复杂、连续性强等特点，改进了基本的粗糙集数据挖掘算法，并与模糊聚类等技术相结合，提出了一种适用于流程工业数据的粗糙集数据挖掘方法。在采用实际丙酮精制生产数据作为样本的实验中应用效果良好，表明该方法具有一定的实用价值。     

The data warehouse virtualization framework for operational business intelligence

In order to explore the most current information and react faster to changing business conditions, organizations consider real‐time data warehousing a powerful technique to achieve operational business intelligence (BI). We propose in this paper a novel real‐time data warehouse (RTDW) framework based on the virtualization concept. Our approach introduces a conceptual modelling technique, known as ring modelling, for real‐time data management and multidimensional analysis. This technique produces a flexible semi‐structured data model that accommodates unknown business process data and relationships as they evolve, handles schema changes and aggregate‐management efficiently, and scales well with the large size of increasing data volumes. With the help of a telecommunication business example, We evaluated our proposed approach in an extensive experimental study where we compared our approach Ring Model with existing structured multidimensional conceptual models (MCMs), i.e. relational OLAP and multidimensional OLAP, and with semi‐structured MCM, i.e. XML Cubes, in terms of scalability, data storage estimations, data updates loading time, and query response times. Our performance results show that encouraging speedups are achieved.     

长江中游短时天气预警系统

海量高频度的天气雷达资料获取、处理及快速显示分析是短时天气预报中非常重要的环节。该文从系统需求、设计和实现等方面描述开发一个完整的短时预警报服务系统的方法。介绍通信系统设计、图像工作站的开发和数据压缩技术等的应用。通过自主开发的GIS系统,解决了图像动画和对准问题,运用多线程调度满足海量资料的实时分析要求。实际应用表明,系统具有很强的实时性,可以满足业务上的需求。     

Predictive on-line monitoring of continuous processes

For safety and product quality, it is important to monitor process performance in real time. Since traditional analytical instruments are usually expensive to install, a process model can be used instead to monitor process behavior. In this paper, a monitoring approach using a multivariate statistical modeling technique, namely multi-way principal component analysis (MPCA), is studied. The method overcomes the assumption that the system is at steady state and it provides a real time monitoring approach for continuous processes. The monitoring approach using MPCA models can detect faults in advance of other monitoring approaches. Several issues which are important for the proposed approach, such as the model input structure, data pretreatment, and the length of the predictive horizon are discussed. A multi-block extension of the basic methodology is also treated and this extension is shown to facilitate fault isolation. The Tennessee Eastman process is used for demonstrating the power of the new monitoring approach.     

基于规范变量分析的化工单元多变量统计监控

化工生产过程往往含有大量的过程变量,且过程多处于闭环控制作用下,产生的测量数据常常存在互相关和自相关。规范变量分析(CVA)通过最大化两个变量集间的相关度,实现对高维数据的降维,并得到一组最大限度地解释变量集中信息的规范变量,很好地解决了上述问题。本文介绍一种基于CVA的过程监控方法,并将此方法应用于一实际化工单元的过程监控,利用控制图,及时准确地检测到过程故障,表明了基于CVA的监控方法的有效性。     

A real time process management system using RFID data mining

Recently, there have been numerous efforts to fuse the latest Radio Frequency Identification (RFID) technology with the Enterprise Information System (EIS). However, in most cases these attempts are centered mainly on the simultaneous multiple reading capability of RFID technology, and thus neglect the management of massive data generated from the RFID reader. As a result, it is difficult to obtain flow information for RFID data mining related to real time process control. In this paper, we propose an advanced process management method, called ‘Procedure Tree’ (PT), for RFID data mining. Using the suggested PT, we are able to manage massive RFID data effectively, and perform real time process management efficiently. Then we evaluate the efficiency of the proposed method, after applying it to a real time process control system connected to the RFID-based EIS. For the verification of the suggested system, we collect an enormous amount of data in the Enterprise Resource Planning (ERP) database, analyze characteristics of the collected data, and then compute the elapsed time on each stage in process control. The suggested system was able to perform what the traditional RFID-based process control systems failed to do, such as predicting and tracking of real time process and inventory control.     

Merging event logs for process mining: A rule based merging method and rule suggestion algorithm

In an inter-organizational setting the manual construction of process models is challenging because the different people involved have to put together their partial knowledge about the overall process. Process mining, an automated technique to discover and analyze process models, can facilitate the construction of inter-organizational process models. This paper presents a technique to merge the input data of the different partners of an inter-organizational process in order to serve as input for process mining algorithms. The technique consists of a method for configuring and executing the merge and an algorithm that searches for links between the data of the different partners and that suggests rules to the user on how to merge the data. Tool support is provided in the open source process mining framework ProM. The method and the algorithm are tested using two artificial and three real life datasets that confirm their effectiveness and efficiency.     

基于WWW的实时在线系统监测技术

简要介绍了ASP技术,分析和讨论了利用ASP技术实现在Internet/Intranet上进行实时在线监测系统的设计方案。该系统采用ASP技术处理实时数据,在实际的Web应用中结合ActiveX控件动态地显示数据,为电厂的管理及运行人员提供了正确的信息支持。