Hierarchical Stochastic Neighbor Embedding

In recent years, dimensionality‐reduction techniques have been developed and are widely used for hypothesis generation in Exploratory Data Analysis. However, these techniques are confronted with overcoming the trade‐off between computation time and the quality of the provided dimensionality reduction. In this work, we address this limitation, by introducing Hierarchical Stochastic Neighbor Embedding (Hierarchical‐SNE). Using a hierarchical representation of the data, we incorporate the well‐known mantra of Overview‐First, Details‐On‐Demand in non‐linear dimensionality reduction. First, the analysis shows an embedding, that reveals only the dominant structures in the data (Overview). Then, by selecting structures that are visible in the overview, the user can filter the data and drill down in the hierarchy. While the user descends into the hierarchy, detailed visualizations of the high‐dimensional structures will lead to new insights. In this paper, we explain how Hierarchical‐SNE scales to the analysis of big datasets. In addition, we show its application potential in the visualization of Deep‐Learning architectures and the analysis of hyperspectral images.     

AltaRica 3.0模型到Promela模型转换与验证方法研究

AltaRica语言用于安全关键系统的建模,其拥有一套完整的建模分析工具,但随着AltaRica3.0的更新,ARC等传统的AltaRica建模分析工具已不再支持,而SPIN作为一个穷尽式模型验证工具被广泛应用。介绍了AltaRica3.0相对于之前版本在表达能力方面的改进,以及其底层模型GTS的基本结构。以AltaRica3.0扁平化为GTS模型的思想为基础,提出了一种AltaRica3.0模型向Promela模型的转换规则。以民用飞机中机轮刹车系统WBS为例,建立了AltaRica3.0模型,并且通过转换规则转为Promela模型。最后根据民用航空标准SAE ARP 4761中对机轮刹车系统的安全性要求,利用SPIN工具对机轮刹车系统的安全属性进行了验证。     

Collective knowledge systems: Where the Social Web meets the Semantic Web

What can happen if we combine the best ideas from the Social Web and Semantic Web? The Social Web is an ecosystem of participation, where value is created by the aggregation of many individual user contributions. The Semantic Web is an ecosystem of data, where value is created by the integration of structured data from many sources. What applications can best synthesize the strengths of these two approaches, to create a new level of value that is both rich with human participation and powered by well-structured information? This paper proposes a class of applications called collective knowledge systems, which unlock the “collective intelligence” of the Social Web with knowledge representation and reasoning techniques of the Semantic Web.     

异构多核上支持OpenMP3.0的自适应任务粒度策略

任务粒度是决定任务并行程序性能的关键因素,鉴于不同应用其最优的任务粒度可能不同,提出一种异构多核Cell处理器上支持OpenMP3.0的自适应任务粒度策略.该策略首先广度生成任务,直到所有的线程达到饱和,之后若某个线程执行完自身任务而处于空闲状态时,通过回溯到忙碌线程的任务树中最早可以派生任务的结点处生成新任务,以供空闲线程窃取执行.该策略不仅保证生成的任务粒度最大化,并且有效地解决了负载不均衡问题.实验在一个Cell处理器上进行,结果表明与顺序执行速度相比,自适应任务粒度策略达到了4.1到7.2的加速比,并且该策略优于现有的Tascell和AdaptiveTC方案,同时对于绝大部分应用表现出了良好的可扩展行.     

Exploring inattention and distraction in the SafetyNet Accident Causation Database

Distraction and inattention are considered to be very important and prevalent factors in the causation of road accidents. There have been many recent research studies which have attempted to understand the circumstances under which a driver becomes distracted or inattentive and how distraction/inattention can be prevented. Both factors are thought to have become more important in recent times partly due to the evolution of in-vehicle information and communication technology. This study describes a methodology that was developed to understand when factors such as distraction and inattention may have been contributors to crashes and also describes some of the consequences of distraction and inattention in terms of subsequent driver actions.     

运载火箭时序仿真测试系统设计

检测运载火箭地面测试设备的方法种类繁多,方法复杂,测试周期较长。设计一种运载火箭时序仿真测试系统,采用FPGA芯片的SOPC(可编程片上系统)技术,基于全双工USB 3.0控制芯片( CYUSB3014)完成上位机通信,单板模拟运载火箭飞行过程中64路时序系统发出的时序信号和时串信号,对不同测试需求的地面测试设备进行功能检测和故障诊断。具有方法简单,通用性好、精度等级高、通道数多的优点,能有效提高地面测试设备在测试任务中的测试效率。     

基于EJB3.0的煤矿分布式空间数据同步系统设计与实现

 本文基于EJB3.0技术设计实现了煤矿分布式空间数据库同步系统,并结合LRGIS 3.0以地测部门的采掘工程平面图为例加以阐述,保障了煤矿空间数据的一致性、时效性,结合LRGIS 3.0实现了矿山信息化管理。     

助燃空气对乙烯裂解炉NOx排放的影响

乙烯裂解炉内复杂物理化学过程耦合模拟与优化能够满足乙烯装置对高效率、低污染和低成本的设计和操作要求,对提高乙烯工业的竞争力具有重要意义。针对简单燃烧机理难以准确预测炉膛燃烧生成NO_x浓度分布的弊端,提出了在裂解炉使用更准确的简化GRI-Mesh 3.0机理结合涡耗散概念(EDC)模型的方法,并对Sandia Flame D的燃烧过程进行计算流体力学(CFD)模拟,验证了此耦合模型的可靠性。在已建立的燃烧模型的基础上,研究了助燃空气对降低裂解炉NO排放的影响,结果表明：在满足裂解炉热效率的情况下,空气预热温度为300~600 K、过量空气系数为1.1时降低NO的效果最佳。     

DNP3.0在济钢EMCC系统中的实现

主要介绍DNP3.0的基本结构和功能，结合济钢能源管控中心的实例，给出了DNP协议在MOX中的具体实现方法，通过该协议系统实现了“四遥”功能。现场运行结果显示，DNP3.0协议具有较高的通信效率和通信可靠性。     

基于线性约束LSCMA在TS101上的实现

本文探讨了ADSPTigerSHARC101S的在基于线性约束最小二乘恒模算法(LSCMA)中的应用。首先介绍了最小二乘恒模算法基本原理和权值迭代公式,并对其进行线性约束然后介绍了ADSPTigerSHARC101S芯片的基本结构特征和它强大的功能并简单描述了其相应开发软件VisualDSP 3.0的功能及使用方法。给出了最小二乘恒模算法实现波束合成的具体流程图,在经过Matlab软件成功进行仿真模拟之后用VisualDSP 3.0设计了DSP程序,用C语言嵌套部分汇编语言的形式实现了用ADSPTigerSHARC101S进行迭代求权向量的过程。