Water Bloom Precursor Analysis Based on Two Direction S-Rough Set

In the field of water quality management, it is vital to determine the main precursory anomalies from the precursor of intricate water bloom in the context of a given area. In this paper, a water bloom precursor analysis method, based on two direction singular rough set, was proposed. This approach was produced on the basis of the different sections and pre-water bloom of water bloom precursor anomalies and characteristic of elements transferred in singular rough set. For testing the validity of two direction singular rough set application in water bloom precursor analysis, Xiangxi River, which is one of the typical tributaries of Three Gorges Reservoir in China, was selected as study area. The result showed that compared with other indexes, pH and dissolved oxygen (DO) are the most valuable indicators of water bloom in the precursory anomalies. Furthermore, regarding with water bloom precursory anomalies in Xiangxi River, most of the nutrient loading and biological community are the key indicators. Hence, this method can determine the main precursory anomaly for water bloom in the study area, which provides powerful knowledge support to water quality specialists for them to comprehensively analyze precursory anomaly so as to find out its relationship with occurrence law of water bloom.     

Potential thread-level-parallelism exploration with superblock reordering

The growing number of processing cores in a single CPU is demanding more parallelism from sequential programs. But in the past decades few work has succeeded in automatically exploiting enough parallelism, which casts a shadow over the many-core architecture and the automatic parallelization research. However, actually few work was tried to understand the nature, or amount, of the potentially available parallelism in programs. In this paper we will analyze at runtime the dynamic data dependencies among superblocks of sequential programs. We designed a meta re-arrange buffer to measure and exploit the available parallelism, with which the superblocks are dynamically analyzed, reordered and dispatched to run in parallel on an ideal many-core processor, while the data dependencies and program correctness are still maintained. In our experiments, we observed that with the superblock reordering, the potential speedup ranged from 1.08 to 89.60. The results showed that the potential parallelism of normal programs was still far from fully exploited by existing technologies. This observation makes the automatic parallelization a promising research direction for many-core architectures.     

Industrial TiO2 based nacreous pigments as functional building materials: Photocatalytic removal of NO

In this paper, the photocatalytic activity of industrial titanium dioxide (TiO₂) based nacreous pigments was researched as functional building materials for photocatalytic NO remove. Three industrial TiO₂ based nacreous pigments were selected to estimate the photocatalytic activity for NO remove. This study is a good proof that pearlescent pigments can eliminate NO, and its performance is positively correlated with its titanium dioxide content. And this research will widen the application of nacreous pigments in functional building materials, and provide a new way to eliminate in door nitric oxide pollution.     

硅压阻式气压高度计的设计与实现

采用硅压阻式压力传感器,以ATmega88PA为控制器设计了气压高度计。内嵌全温度范围的曲面拟合算法进行温度补偿及线性化处理,解决了压力传感器的温漂和非线性问题,并用海拔高度与气压的关系计算高度。测量结果通过RS-485接口发送给上位机。测试结果表明,该气压高度计压力测量误差优于0.50‰,分辨率为0.01 h Pa,线性度为0.999 9;标准大气环境下高度测量误差为0.16 m,线性度为0.999 8。该气压高度计具有质量小、功耗低、精度高、工作可靠等优点。     

计算思维影响下的应用型本科计算机基础教学改革探索

当前以计算思维能力培养为切入点的大学计算机课程改革工作已进入一个新的阶段,如何改革计算机基础教学以适应当前形势的发展,是计算机基础教学面临的挑战。以计算思维为导向,对应用型本科院校大学计算机基础课程的目标定位、教学内容、教学过程等教学环节作改革式探索。     

防止过拟合的属性约简

近年来,机器学习的过拟合问题备受关注,尤其在属性约简中。为解决这一难题,提出一种融合集成策略和去除操作的算法。首先将训练模型数据平分为◢M份;然后将其中M◣-1份采用集成策略进行潜在约简计算;最后将剩余的一份进行提前测试,一旦发生过拟合则将刚加入的属性从潜在约简集中去除。利用提前测试潜在属性约简的方法来防止过拟合现象的发生,几组UCI数据的实验结果说明了新算法的有效性,同时为丰富和发展属性约简提供了一种新的方向。     

Coordinating efficiency and equity in disaster relief logistics via information updates

This paper addresses a multi-supplier, multi-affected area, multi-relief, and multi-vehicle relief allocation problem in disaster relief logistics. A multi-objective optimisation model based on disaster scenario information updates is proposed in an attempt to coordinate efficiency and equity through timely and appropriate decisions regarding issues such as vehicle routing and relief allocation. An optimal stopping rule is also proposed to determine the optimum period of delay before responding to disaster, because decision making requires accurate disaster information. The main contribution of this paper is solving relief allocation problem in a novel way by correlating operational research with statistical decision making and Bayesian sequential analysis. Finally, a case is presented based on the post-disaster rescue in Eastern China after supertyphoon Saomai to test the applicability and show the potential advantages of the proposed model.     

A schema aware ETL workflow generator

Extract, Transform and Load (ETL) processes organized as workflows play an important role in data warehousing. As ETL workflows are usually complex, various ETL facilities have been developed to address their control-flow process modeling and execution control. To evaluate the quality of ETL facilities, Synthetic ETL workflow test cases, consisting of control-flow and data-flow aspects are needed to check ETL facility functionalities at construction time and to validate the correctness and performance of ETL facilities at run time. Although there are some synthetic workflow and data set test case generation approaches existed in literatures, little work is done to consider both aspects at the same time specifically for ETL workflow generators. To address this issue, this paper proposes a schema aware ETL workflow generator with which users can characterize their ETL workflows by various parameters and get ETL workflow test cases with control-flow of ETL activities, complied schemas and associated recordsets. Our generator consists of three steps. First, with type and ratio of individual activities and their connection characteristic parameter specification, the generator will produce ETL activities and form ETL skeleton which determine how generated activities are cooperated with each other. Second, with schema transformation characteristic parameter specification, e.g. ranges of numbers of attributes, the generator will resolve attribute dependencies and refine input/output schemas with complied attributes and their data types. In the last step, recordsets are generated following cardinality specifications. ETL workflows in specific patterns are produced in the experiment in order to show the ability of our generator. Also experiments to generate thousands of ETL workflow test cases in seconds have been done to verify the usability of the generator.     

医疗大数据特征挖掘及重大突发疾病早期预警

通过运用新兴的尖端云计算技术,设计研发了健康云平台。采用分布式云存储技术存储大规模的异构多模态生理信号数据,将数据挖掘模型（L1-逻辑斯蒂）整合至MapReduce框架中,快速挖掘用户的健康信息以及重大疾病高风险因子,让用户能实时地了解自己的身体状况,同时对用户的异常状况给出预警信息,并通知其前往医院就医,实现了对重大突发疾病的早期预警。     

稀疏表示分类中遮挡字典构造方法的改进

针对稀疏表示分类算法中遮挡字典维数高且无冗余的问题,提出一种遮挡字典构造方法.首先通过图像分块得到各级的遮挡基图像;然后将所有互不相同的遮挡基图像按字典顺序转化为向量,并用这些向量作为遮挡字典的列,从而构造出维数相对较低且具有一定冗余度的遮挡字典.实验结果表明,该方法不仅明显提高了稀疏表示分类算法对遮挡人脸的识别率,而且还能通过减少图像的分块级数降低稀疏分解的耗时量,提高运算效率.