智能变电站设备管控大数据分析系统研究

结合数据挖掘、大数据技术在电力系统中的应用现状，分析和设计了一种智能变电站设备管控大数据分析系统。对变电站设备运行状态的大数据特征及基本框架进行了分析，并重点阐述了变电站设备运行状态大数据分析系统的数据集成与预处理、数据存储与处理、设备状态评估模型以及数据可视化展示。实验结果表明，所设计的大数据分析系统能够大幅度提升变电站设备数据分析智能化水平，为变电站管控稳定运行提供更加有效和实用性的技术支撑。     

A small-scale silica gel-water adsorption system for domestic air conditioning and water heating by the recovery of solar energy

A small-scale silica gel-water adsorption system with modular adsorber, which utilizes solar energy to achieve the cogeneration of domestic air conditioning and water heating effect, is proposed and investigated in this paper. A heat recovery process between two adsorbers and a mass recovery process between two evaporators are adopted to improve the overall cooling and heating performance. First, the adsorption system is tested under different modes (different mass recovery, heat recovery, and cogeneration time) to determine the optimal operating conditions. Then, the cogeneration performance of domestic cooling and water heating effect is studied at different heat transfer fluid temperatures. The results show that the optimal time for cogeneration, mass recovery, and heat recovery are 600 s, 40 s, and 40 s, respectively. When the inlet temperature of hot water is around 85°C, the largest cooling power and heating power are 8.25 kW and 21.94 kW, respectively. Under the condition of cooling water temperature of 35°C, the obtained maximum COP_c, COP_h, and SCP of the system are 0.59, 1.39, and 184.5 W/kg, respectively.     

LTE室分高倒流小区解决方案的研究

LTE室分高倒流直接影响室内4G用户的感知，同时较大程度拉低LTE网络驻留率指标。由于室内无线环境的封闭性，室分小区之间的覆盖独立性，仅仅通过参数调整的手段达到降低高倒流的效果非常不明显，因此本文针对目前影响室内用户感知的高倒流问题，从高倒流小区的标准出发，对室分高倒流小区的发现手段，产生原因及解决方案进行详尽地阐述，并针对各类型的高倒流情形提出解决方法，最终提供读者发现、分析及解决室分高倒流小区的有效方案，从而作为研究方法提供给LTE室内小区高倒流问题解决的指导意见     

Learning Association Rules and Tracking the Changing Concepts on Webpages: An Effective Pornographic Websites Filtering Approach

We applied the decision tree algorithm to learn association rules between webpage’s category (pornographic or normal) and the critical features. Based on these rules, we proposed an efficient method of filtering pornographic webpages with the following major advantages: 1) a weighted window-based technique was proposed to estimate for the condition of concept drift for the keywords found recently in pornographic webpages; 2) checking only contexts of webpages without scanning pictures; 3) an incremental learning mechanism was designed to incrementally update the pornographic keyword database.     

基于大数据挖掘的用电行为分析

得益于智能电网的发展,电力大数据的价值与作用逐渐被挖掘。通过对电力大数据的深入挖掘与研究,可促进电网企业管理水平的进一步提升,为我国智能电网的发展提供助力。而依托于大数据挖掘的用户用电行为分析,可实现当前企业电网调控与需求侧的充分融合,为电力系统的稳定性运行提供保障。基于此,文章针对大数据挖掘的用电行为分析进行深入探析,以期为智能电网发展提供帮助。     

极端耗水层带精准识别和调堵新技术

油田注水开发后期,部分油层存在极端耗水层带,存在耗水量大,注水驱油效率低,水循环成本高的开发问题,精准认识并有效封堵极端耗水层带,可提高注水利用率。目前国外出现了应用磁性纳米粒子的精细表征新技术及超顺磁性纳米颗粒封堵新技术,抑制极端耗水,实现低成本、高强度、深度堵调。     

浅谈煤与瓦斯突出矿井"U"型通风系统采煤工作面上隅角瓦斯管理

屯兰煤矿是煤与瓦斯突出矿井,瓦斯涌出量大,上隅角瓦斯治理困难。为解决这一通风难题,该矿采取沿空留巷抽采措施进行作业。实践证明,该技术解决了上隅角瓦斯积聚隐患,保障了矿井高产高效。     

Applied data science in patient-centric healthcare: Adaptive analytic systems for empowering physicians and patients

We define the emerging research field of applied data science as the knowledge discovery process in which analytic systems are designed and evaluated to improve the daily practices of domain experts. We investigate adaptive analytic systems as a novel research perspective of the three intertwining aspects within the knowledge discovery process in healthcare: domain and data understanding for physician- and patient-centric healthcare, data preprocessing and modelling using natural language processing and (big) data analytic techniques, and model evaluation and knowledge deployment through information infrastructures. We align these knowledge discovery aspects with the design science research steps of problem investigation, treatment design, and treatment validation, respectively. We note that the adaptive component in healthcare system prototypes may translate to data-driven personalisation aspects including personalised medicine. We explore how applied data science for patient-centric healthcare can thus empower physicians and patients to more effectively and efficiently improve healthcare. We propose meta-algorithmic modelling as a solution-oriented design science research framework in alignment with the knowledge discovery process to address the three key dilemmas in the emerging “post-algorithmic era” of data science: depth versus breadth, selection versus configuration, and accuracy versus transparency.     

基于大数据的C语言程序设计

C语言作为一种程序设计语言,在大数据组成的物联网和云计算中应用广泛,具有强大的适应性和兼容性,是大数据时代下,在IT行业中起到关键作用的程序设计语言。文章分析了基于大数据的C语言程序设计的必然性和应用策略,为C语言在大数据上的应用方向提供了参考依据。以汉字的应用为例,提出了解决C语言应用问题的思路。