Alcohol consumption detection through behavioural analysis using intelligent systems

We describe in this paper a new methodology for blood alcohol content (BAC) estimation of a subject. Rather than using external devices to determine the BAC value of a subject, we perform a behaviour analysis of this subject using intelligent systems. We monitor the user’s actions in an ordinary task and label those data to various measured BAC values. The obtained data-set is then used to train learning systems to detect alcoholic consumption and perform BAC estimation. We obtain good results on a mono-user base, and lower results with multiple users. We improve the results by combining multiple classifiers and regression algorithms.     

基于日志挖掘的移动应用用户访问模型建模技术研究

提出了一种基于监控日志挖掘的移动应用用户访问模型自动构造方法,该方法包括监控代码注入和界面访问模型构造两部分。首先,提出了一种监控代码自动注入方法,即通过对移动应用代码的静态分析,自动地在相应位置插入监控代码以支持在运行时动态地监控用户的访问行为。其次,提出了一种基于状态机的移动应用用户访问模型构造方法。访问模型中状态机的节点和节点间跳转上的附加属性描述了UI界面之间的跳转行为和界面内控件的使用情况。对移动应用进行的实验表明,这种基于监控日志挖掘的移动应用用户访问模型自动构造方法能够成功地自动注入移动应用的监控代码,并能够有效获得移动应用用户界面访问行为。     

Optimisation of specimen temperature and pulse fraction in atom probe microscopy experiments on a microalloyed steel

This paper details the effects of systematic changes to the experimental parameters for atom probe microscopy of microalloyed steels. We have used assessments of the signal-to-noise ratio (SNR), compositional measurements and field desorption images to establish the optimal instrumental parameters. These corresponded to probing at the lowest possible temperature (down to 20 K) with the highest possible pulse fraction (up to 30%). A steel containing a fine dispersion of solute atom clusters was used as an archetype to demonstrate the importance of running the atom probe at optimum conditions.     

Performance analysis challenges and framework for high-performance reconfigurable computing

Reconfigurable computing (RC) applications employing both microprocessors and FPGAs have potential for large speedup when compared with traditional (software) parallel applications. However, this potential is marred by the additional complexity of these dual-paradigm systems, making it difficult to identify performance bottlenecks and achieve desired performance. Performance analysis concepts and tools are well researched and widely available for traditional parallel applications but are lacking in RC, despite being of great importance due to the applications’ increased complexity. In this paper, we explore challenges and present new techniques in automated instrumentation, runtime measurement, and visualization of RC application behavior. We also present ideas for integration with conventional performance analysis tools to create a unified tool for RC applications as well as our initial framework for FPGA instrumentation and measurement. Results from a case study are provided using a prototype of this new tool.     

基于Zigbee的无线动态应变测量

ZigBee是一种低速率、低成本、低功耗的短程无线网络协议。利用最新的Zigbee无线传感器网络技术和零漂移数字可设增益应变放大器对传统的应变测量在技术上进行改进,使得应变测量更方便、灵活和准确。作者给出其测量方案的精密激励电源、仪表放大电路、DAC调零和射频硬件电路以及Zigbee无线网络协议软件设计。所设计的应变测量模块具有体积小、精度高、功耗低、配置灵活的特点。实际应用表明,该设计满足技术方案的要求并已成功地应用于桥梁和机械应变测试系统中。     

焦炉煤气热值仪预处理系统的改进

焦炉煤气含有较多难以净化的杂质,对分析焦炉煤气的在线分析仪预处理系统的净化能力要求较高.分析了CM6G热值仪检测系统在韶钢焦炉煤气热值检测中取样及预处理系统存在的问题,并探讨了预处理系统部件的改进措施.经实验表明,改进后的预处理系统净化效果大大加强,满足仪表在线连续检测的要求.     

基于FPGA的逻辑分析仪连续触发模块设计

该文介绍一种逻辑分析仪数据捕获模式的设计原理与实现方法。该模式主要用于嵌入式软件的测试分析,它不再采用采样的方式来采集数据,而是利用软件插桩与硬件设置触发字相结合的方法来监视系统总线。当程序运行到插桩点时,硬件将产生触发,此时才会主动地到总线上将相应数据与对应的具体时问捕获回来,从而实现有效数据的精确捕获。此外,在FPGA内部采用双RAM交替读写的方式来暂存数据,在不中断程序运行的情况下,实现有效数据的长时间实时存取与分析,提高嵌入式软件性能分析的范围和质量。采用FPGA作为构成硬件架构的基本功能器件,提高了工作速度,使整个设计具具有集成度高、性能稳定、调试方便等特点。该模块在实际应用中得到了验证,并取得了良好的效果。     

A capacitance based axial position sensor for cryocoolers

The recent development of a Stirling cryocooler designed to operate with a body temperature of less than 220 K required an axial motor position sensor which could operate over this temperature range. Although linear variable differential transformers (LVDTs), have traditionally been used, these are temperature dependent and would have required development due to integrated electronics, which could not be used at these low temperatures. A sensor was therefore developed based on the principle of measuring the capacitance between static and moving concentric rings. The design is presented along with the signal conditioning circuit. Experimental results show that the sensor had suitable bandwidth with a temperature independent gain between room temperature and 220 K. Future developments are described including a similar sensor to measure the radial motion of a motor during operation.     

虚拟仪器软件体系结构（VISA）

本文介绍了ＶＩＳＡ的开发目的，内部结构特点，分布式系统支持原理，从ＶＩＳＡ的内部属性，软件兼容性和增强功能，硬件支持能力等几方面分析了ＶＩＳＡ的特性，阐述了ＶＩＳＡ作为Ｉ／Ｏ软件标准，为软件工具化提供了一多厂家基础的可行性和科学性。     

Baseline Models for Bridge Performance Monitoring

A baseline model is essential for long-term structural performance monitoring and evaluation. This study represents the first effort in applying a neural network-based system identification technique to establish and update a baseline finite element model of an instrumented highway bridge based on the measurement of its traffic-induced vibrations. The neural network approach is particularly effective in dealing with measurement of a large-scale structure by a limited number of sensors. In this study, sensor systems were installed on two highway bridges and extensive vibration data were collected, based on which modal parameters including natural frequencies and mode shapes of the bridges were extracted using the frequency domain decomposition method as well as the conventional peak picking method. Then an innovative neural network is designed with the input being the modal parameters and the output being the structural parameters of a three-dimensional finite element model of the bridge such as the mass and stiffness elements. After extensively training and testing through finite element analysis, the neural network became capable to identify, with a high level of accuracy, the structural parameter values based on the measured modal parameters, and thus the finite element model of the bridge was successfully updated to a baseline. The neural network developed in this study can be used for future baseline updates as the bridge being monitored periodically over its lifetime.