有线无线一体化通信系统在煤矿的应用

介绍了矿用行政通信系统、调度通信系统、无线通信系统,提出了煤矿有线无线一体化通信系统解决方案,并介绍了该系统的组成、主要设备及功能特点。应用结果表明,该系统实现了矿井有线无线通信系统的有效融合,达到了统一调度指挥的目的。     

基于内容的Pub/Sub系统中分发器网络自重构的研究*

提出了提高基于内容的Pub/Sub系统健壮性和交互效率的系统自重构方法。该方法包括系统的恢复策略和系统的自组织策略。系统的恢复策略,预防了节点的意外崩溃造成的系统瘫痪;系统自组织策略, 有效地降低了系统的事件交互成本,提高了基于内容的Pub/Sub系统的效率。自重构方法在基于内容的Pub/Sub系统SOES中得到了体现。     

计算机网络课程e-Learning系统的技术特色与功能特点

给出了一种基于 Web的实时交互式计算机网络课程 e Learning系统。分析了系统的组成、系统的技术特色和系统各模块的功能特点以及系统的工作方式。包括点播服务及多点广播服务的系统工作模式 ,最后介绍了系统中存在的问题以及系统的应用前景     

电工实验辅助测评系统的设计与实现

介绍了设计电工实验辅助测评系统的过程．分析了系统需求。给出了系统的数据流图：结合系统需求．设计出系统的软件结构图．提出了一种试卷分配策略。给出了系统的部分算法描述。     

基于Web和工作流技术的办公自动化系统

针对如何建立企业的Internet信息平台系统,提出了基于Web和工作流技术的办公自动化系统设计方案.介绍了办公自动化系统的优点,讨论了系统的整体设计目标和在设计时要注意的问题,阐述了系统的整体结构和工作流平台系统的构成.     

计算机多媒体辅助教学网站的开发

该文分析了基于ASP的Web远程考试系统的发展要求。分析了Web下考试系统的基本原理,结合系统需求,给出了系统架构。对于系统的数据库设计给出了详细的表,最后对关键代码进行了分析。     

关于发电厂直流及UPS系统维护的探讨

在大容量火力发电厂中,直流系统和交流不停电系统（UPS）是两个不可缺少的电源系统。简要介绍了某电厂直流系统和UPS系统电源的基本构成、主要特点和运行方式,并对直流系统和UPS系统在大型发电厂中的应用和重要性进行了阐述,进而探讨了直流系统和UPS系统的运行和维护。     

分布式计算机实时监控系统

针对目前实时监控系统的不足,设计了分布式的计算机实时监控系统.系统的设计充分体现了分布式数据库的特点,信息共享性好;同时系统采用红外检测技术,提高了系统的实时性.实验证明,系统达到了预期效果.     

基于LINUX的嵌入式Email系统的设计与实现

嵌入式Email系统是类PC嵌入式系统,是嵌入式操作系统及其应用软件的一个重要组成部分,但是现有PC上的嵌入式Email系统都不能适应类PC嵌入式系统的硬件环境要求。文中采用了一种新的构建嵌入式Email系统的方法,设计与实现了清华嵌入式Email系统,可根据各种类PC嵌入式系统的不同要求进行定制。首先,论述了类PC嵌入式系统的硬件平台对嵌入式Email系统的苛刻要求,其次,描述了清华嵌入式Email系统的体系结构,接着,讨论了清华嵌入式Email系统的实现机制与原理,以及系统模型,最后,给出了嵌入式Email系统的特点。由于采用了现在流行的一种开放源码的组件,使得整个系统功能完善,并能够完全符合类PC嵌入式系统的要求。嵌入式Email系统已经在自主研制的掌上电脑HPC和交互式网络电视上成功地运行。     

过程控制训练仿真评估方法研究

评估系统是过程控制型仿真系统的重要组成部分,随着过程控制型仿真系统复杂性增大,其评估系统构建也日趋复杂.该文从一般性的角度对过程控制型仿真系统评估方法进行了探讨,对训练仿真系统中的过程事件进行了分类.针对训练目的,提出了过程控制训练仿真系统的评估标准.结合训练仿真系统的特点,提出了评估的假设前提和事件类型判定方法.以此基础改进了分步评估法并构建了训练仿真系统的评估模型.最后,以海上补给训练仿真系统实际项目为背景,实现了海上补给训练仿真系统评估系统.     

基于传感器最优配置的等价空间故障检测方法

提出一种基于传感器最优配置的等价空间故障检测方法．针对线性时不变动态系统，给出了传感器最优配置问题的描述，以及基于传感器最优配置的故障检测多目标优化问题的描述．在系统可供测量的N个变量中，选择能获得关于系统故障尽可能多信息的m个变量作为测量变量，在满足对故障具有尽可能高的灵敏度，同时对扰动等未知信号具有尽可能强的鲁棒性的条件下，使整个系统测量成本达到最低．仿真算例说明了所提出设计方法及算法的有效性．     

浅析目前动漫教学中存在的误区

动漫教学在当今高校教育中所占比例越来越重,然而,由于诸多方面原因,当前动漫教学过程存在一些误区。本文从动漫基础教学、动漫教学的本土原创性和动漫教学培养目标几方面入手,旨在找出造成动漫教学重借鉴轻原创、重西方轻中国、重技术轻艺术的根本原因,以提高教学水平。     

A structured marketplace for arbitrary services

Creating simple marketplaces with common rules, that enable the dynamic selection and consumption of functionality, is the missing link to allow small businesses to enter the cloud, not only as consumers, but also as vendors. In this paper, we present the concepts behind a hybrid service and process repository that can act as the foundation for such a marketplace, as well as a prototype that allowed us to test various real-world scenarios. The advantage of a hybrid service and process repository is that, it not only holds a flat list of services, but also exposes a generic set of use cases, that it obtains information on how specific services can be used to implement the use cases as well as information to select services at run-time according to customer’s goal functions.     

Parallel programming in computational science: an introductory practical training course for computer science undergraduates at Aachen University

Parallel programming of high-performance computers has emerged as a key technology for the numerical solution of large-scale problems arising in computational science and engineering (CSE). The authors believe that principles and techniques of parallel programming are among the essential ingredients of any CSE as well as computer science curriculum. Today, opinions on the role and importance of parallel programming are diverse. Rather than seeing it as a marginal beneficial skill optionally taught at the graduate level, we understand parallel programming as crucial basic skill that should be taught as an integral part of the undergraduate computer science curriculum. A practical training course developed for computer science undergraduates at Aachen University is described. Its goal is to introduce young computer science students to different parallel programming paradigms for shared and distributed memory computers as well as to give a first exposition to the field of computational science by simple, yet carefully chosen sample problems.     

基于Asterisk的PBX设计与实现

随着计算机处理能力的不断增强,人们开始尝试将计算机应用于企业电话交换的处理中。这样在降低成本的同时,增加了许多由计算机处理带来的附加功能。Asterisk就是这样一个可应用于企业自有电话系统的开源软件,它将一台普通的PC机变身成为一台可用于企业电话交换的机器,用较小的成本完成了通常需要昂贵的交换机才能完成的任务,同时也拥有非常多的特色功能,如互动式语音应答、语音邮件、电话详情记录、呼叫中心等等。文中叙述了Asterisk的背景技术、功能模块的设计与实现的过程,并用实例说明了功能如何被达成。     

Customized Share Level Monitoring System for Users in OSN-Third Party Applications

Preserving privacy of the user is a very critical requirement to be met with all the international laws like GDPR, California privacy protection act and many other bills in place. On the other hand, Online Social Networks (OSN) has a wide spread recognition among the users, as a means of virtual communication. OSN may also acts as an identity provider for both internal and external applications. While it provides a simplified identification and authentication function to users across multiple applications, it also opens the users to a new spectrum of privacy threats. The privacy breaches costs to the users as well as to the OSN. Despite paying millions of dollars as fine every year, the OSN has not done any significant changes, as data is the fuel and what it loses as fine is far less compared to the money OSN makes out of the shared data. In this work, we have discussed a wide range of possible privacy threats and solutions prevailing in OSN-Third Party Application (TPA) data sharing scenario. Our solution models the behavior of the user, as well as TPA and pinpoints the avenues of over sharing to the users, thereby limiting the privacy loss of the user.     

融入Universum学习的度量学习算法

度量学习通过更真实的刻画样本之间的距离,来提高分类和聚类的精度。GMML（Geometric Mean Metric Learning）在学习度量矩阵[A]时,使得在该度量下同类点之间的距离尽可能小,不同类点之间的距离尽可能大。GMML用来学习的训练样本均为目标类数据,而对于现实存在的为数众多的同领域非目标类数据,即Universum数据并未加以利用,不免造成信息的浪费,针对此,提出一种新的度量学习算法--融入Universum学习的GMML（U-GMML）。U-GMML期望得到一个新的度量矩阵[A],使得同类点之间的距离尽可能小,不同类点之间的距离尽可能大,且Universum数据与目标类数据的距离尽可能大,从而使得所学习的度量矩阵[A]更有利于分类。真实数据集上的实验结果验证了该算法的有效性。     

Intra-molecular electron communication,spectroscopic and conformational stability of the newly developed urethane modified polyetheramide coatings: Computational methods

There have been constant research efforts towards the development of new and thermally stable resins, containing properties to outdoor usage, such as high quality of adhesion, as well as resistance to water and acid, amongst others. In this computational study, the spectroscopic properties were calculated, also the intramolecular electronic communication, susceptibility, as well as conformational changes in two monomers of potential resins, namely Albiziabenth oil polyetheramide (ABOPEtA) and urethanated Albiziabenth oil polyetheramide (UABOPEtA), as well as their precursor, namely hydroxylethyl albiziabenth oil amide (HEABOA). Many of these computed properties clearly show that the urethane linkage group in UABOPEtA acts as a strong electron withdrawing group, consequently causing the rest of the molecule to be more nucleophilic. This leads to an increase in the stability of UABOPEtA, as compared the rest of the molecules, as evidenced by an increase in the intramolecular energy of interaction, as well as negative values of the polarizability exaltation index (Γ). Further UABOPEtA is also associated with higher non-linear optical properties, in terms of the hyperpolarizabilities (β) and increased aromaticity, than for molecules ABOPEtA and HEABOA. The conformational folding of molecule UABOPEtA is characterized by larger values of the bisphenol-A linkage bond angle C⋯C⋯C, contrary to the angle observed in molecule ABOPEtA. This is a direct effect of hiding the urethane unit in the cleft of the folded UABOPEtA, which clearly leads to an increase in the hydrophobicity of UABOPEtA.     

Selective Branch Inversion: Confidence Estimation for Branch Predictors

This paper describes a family of branch predictors that use confidence estimation to improve the performance of an underlying branch predictor. This method, referred to as Selective Branch Inversion (SBI), uses a confidence estimator to determine when the branch direction prediction is likely to be incorrect; branch decisions for these low-confidence branches are inverted. SBI with an underlying Gshare branch predictor outperforms other equal sized predictors such as the best history length Gshare predictor, as well as equally complex McFarling and Bi-Mode predictors. Our analysis shows that SBI achieves its performance through conflict detection and correction, rather than through conflict avoidance as some of the previously proposed predictors such as Bi-Mode and Agree. We also show that SBI is applicable to other underlying predictors, such as the McFarling Combined predictor. Finally we show that Dynamic Inversion Monitoring (DIM) can be used as a safeguard to turn off SBI in cases where it degrades the overall performance.     

A hierarchical attention-based neural network architecture, based on human brain guidance, for perception, conceptualisation, action and reasoning

We present a neural network software architecture, guided by that of the human and more generally primate brain, for the construction of an autonomous cognitive system (which we have named GNOSYS). GNOSYS is created so as to be able to attend to stimuli, to conceptualise them, to learn their predicted reward value and reason about them so as to attain those stimuli in the environment with greatest predicted value. We apply this software system to an embodied version in a robot, and describe the activities in the various component modules of GNOSYS, as well as the overall results. We briefly compare our system with some others proposed to have cognitive powers, and finish by discussion of future developments we propose for our system, as well as expanding on the arguments for and against our approach to creating such a software system.