我国矿井水资源化利用现状及前景展望

针对现阶段我国在矿井水资源化政策制定、科学研究、人才培养及宣传等方面存在的问题,在总结全国53处煤矿矿井水利用率、利用方式、利用价格等现状的基础上,分析了矿井水资源化利用的制约因素,提出了出台落地性政策、加强创新人才建设培养、分质分类利用、加大宣传和发挥行业协会作用等政策方面的建议,指出高质量矿井水的开发、矿井水资源热能利用、产业化和规模化经营、废弃矿矿井水资源化利用等是矿井水热能利用的方向。     

江阴市"十四五"水利高质量发展规划的思考

总结江阴市"十三五"水利发展规划在水安全、水资源、水生态、农村水利、水管理服务及水利发展保障等方面的完成情况.分析江阴市水利发展存在的主要短板、问题.围绕建设高质量的水安全保障体系、水资源配置体系、水生态治理体系、水利管理体系、水利服务体系,系统提出江阴市"十四五"水利高质量发展规划思路.     

An online multiple object tracker based on structure keeper net

We propose a novel online multiple object tracker taking structure information into account. State-of-the-art multi-object tracking (MOT) approaches commonly focus on discriminative appearance features, while neglect in different levels structure information and the core of data association. Addressing this, we design a new tracker fully exploiting structure information and encoding such information into the cost function of the graph matching model. Firstly, a new measurement is proposed to compare the structure similarity of two graphs whose nodes are equal. With this measurement, we define a complete matching which performs association in high efficiency. Secondly, for incomplete matching scenarios, a structure keeper net (SKnet) is designed to adaptively establish the graph for matching. Finally, we conduct extensive experiments on benchmarks including MOT2015 and MOT17. The results demonstrate the competitiveness and practicability of our tracker.

     

石油石化系统言息安全态势评估指标体系研究

文章阐述了石油石化系统信息安全态势评估指标体系的研究意义,提出了指标体系的研究思路,分析了指标体系的基本构成,说明了指标体系的总体框架,并对指标体系的数据获取和应用前景作了介绍。对于丰富和完善国家信息安全态势评估指标体系,是一个有意义的探索。     

基于双缓冲机制的多尺度导航电子地图显示设计

为了提高电子地图数据的精度和画面显示的速率,对地图数据格式加以改进,新增isvl参数准确标识出被描绘数据情报的尺度,对检索的数据缓存做了优化性能管理,依据地图数据的格式提出了坐标变换、数据解析和描画范围定位的准确算法,采用双缓冲机制绘制地图;经实验证明,使用该套方案实验的结果,具有以下特性:1)高精度,多尺度;2)画面合理的表达了空间关系;3)支持实时动态快速显示;可应用到电子地图的研发中。     

视觉测量中多光学靶点亮度自适应控制

提出了一种面向大视场高精度视觉测量的多红外目标靶点（红外LED）亮度自适应控制方法。以微控制器PIC16F873A和LED驱动芯片MAX6964作为核心器件,设计了可满足大空间范围内靶点亮度控制需求的多目标靶点控制驱动器。为了使LED在近距测量时的调节精度和远近距离测量时的发光亮度都能满足要求,根据MAX6964输出特点设计了PWM信号输出电路,并采用推挽电路驱动LED。实验证明,目标靶点在CCD相机上成像光斑稳定一致。     

Weighted principal component extraction with genetic algorithms

Pattern recognition techniques have been widely used in a variety of scientific disciplines including computer vision, artificial intelligence, biology, and so forth. Although many methods present satisfactory performances, they still have several weak points, thus leaving a lot of space for further improvements. In this paper, we propose two performance-driven subspace learning methods by extending the principal component analysis (PCA) and the kernel PCA (KPCA). Both methods adopt a common structure where genetic algorithms are employed to pursue optimal subspaces. Because the proposed feature extractors aim at achieving high classification accuracy, enhanced generalization ability can be expected. Extensive experiments are designed to evaluate the effectiveness of the proposed algorithms in real-world problems including object recognition and a number of machine learning tasks. Comparative studies with other state-of-the-art techniques show that the methods in this paper are capable of enhancing generalization ability for pattern recognition systems.     

降膜蒸发过程的数值模拟和传热传质分析

利用CFD软件对逆流降膜蒸发过程进行了实验模拟研究,研究了速度边界层、热边界层和浓度边界层的变化对降膜蒸发传热传质特性的影响规律;通过建立一维逆流降膜蒸发的数学方程编程求解出了对流传热传质的Nu数和Sh数,利用Fluent软件模拟出的实验结果采用回归分析得出了气液流量比Raw、流道的长宽比αL、空气进口无量纲温度θai以及空气进口Re数与Nu数、Sh数之间的无量纲关系式,可为降膜蒸发换热器的设计提供参考。