Al–Si cast alloys under isothermal and thermomechanical fatigue conditions

This work presents a survey of the isothermal and anisothermal fatigue behavior of aluminum casting alloys obtained from different processes. Experimental results have shown that porosity, especially large and irregular pores, provides the main factor in decreasing fatigue properties of the tested alloys. In materials with similar porosity levels, other microstructural factors became relevant such as, matrix morphology and the amount of alloying elements. Fractographic analyses showed that fatigue cracks preferentially start to propagate in microcracks or interdendritic shrinkage usually located next to the surface. In most cases, propagation takes place in the eutectic phase, although in the thixoformed material, a transition from transgranular to intergranular mode was observed in the crack propagation mode.     

Machine-learning paradigms for selecting ecologically significant input variables

Harmful algal blooms, which are considered a serious environmental problem nowadays, occur in coastal waters in many parts of the world. They cause acute ecological damage and ensuing economic losses, due to fish kills and shellfish poisoning as well as public health threats posed by toxic blooms. Recently, data-driven models including machine-learning (ML) techniques have been employed to mimic dynamics of algal blooms. One of the most important steps in the application of a ML technique is the selection of significant model input variables. In the present paper, we use two extensively used ML techniques, artificial neural networks (ANN) and genetic programming (GP) for selecting the significant input variables. The efficacy of these techniques is first demonstrated on a test problem with known dependence and then they are applied to a real-world case study of water quality data from Tolo Harbour, Hong Kong. These ML techniques overcome some of the limitations of the currently used techniques for input variable selection, a review of which is also presented. The interpretation of the weights of the trained ANN and the GP evolved equations demonstrate their ability to identify the ecologically significant variables precisely. The significant variables suggested by the ML techniques also indicate chlorophyll-a (Chl-a) itself to be the most significant input in predicting the algal blooms, suggesting an auto-regressive nature or persistence in the algal bloom dynamics, which may be related to the long flushing time in the semi-enclosed coastal waters. The study also confirms the previous understanding that the algal blooms in coastal waters of Hong Kong often occur with a life cycle of the order of 1–2 weeks.     

考虑电动汽车电量及充电站位置的最优路径查找

在环境保护和节约能源要求下,发展电动汽车已经成为重要的产业方向,但现有电动汽车发展还不够成熟,存在续航里程不足的缺点,充换电服务网络也还不够普及,因此对汽车行驶线路耗电量少的路径搜索就尤为重要。基于Dijkstra算法和Floyd算法提出了一种查找电动汽车在不同道路工况下行驶时耗电量最少的路径模型,得到了电动汽车行驶的最优路径,模型并使用Matlab软件自带语言编程并仿真,得到直观的路线信息、距离。     

Actuator and Sensor Fault Detection and Isolation for Uncertain Switched Nonlinear System Based on Sliding Mode Observers

International Journal of Control, Automation and Systems - In this paper, we discuss actuator fault and sensor fault detection and isolation (FDI) problems for a class of switched nonlinear systems...     

基于云存储的离线下载系统

数据获取是现代网络应用中的重要组成部分,是几乎所有网络操作的前提。下载工具能够帮助用户更加便捷地获取网络资源。该文提出一个基于云存储的离线下载系统,系统保持离线下载原有特色与优点,并引入云存储解决系统存储空间不足和"秒杀"下载率不高的的问题,利用基于文件存储价值的存储更新策略提高云存储系统的存储效率。双机热备技术的引入,有效提高系统整体可靠性。     

医院住院信息管理系统的设计与实现

随着网络技术和IT技术的发展和进步,计算机应用已经涉及到人们生活的各个方面。医院住院信息管理系统是实现一个Web形式的B/S架构的数据信息收集、处理和查询的完整的信息处理方案。该系统集合了患者管理,床位管理,医生管理以及病房管理的综合性信息医院管理系统软件。运用软件工程的设计思想对网站进行了需求分析和逐步设计。