煤矿5G分布式MIMO组网技术研究（增刊）

根据煤矿井下的安全防爆要求，天线的射频发射功率受到严格限制，导致煤矿5G的基站部署密度显著高于地面场景。为了解决由此引发的交叉覆盖问题，本文提出了煤矿5G分布式MIMO组网技术，利用分布在不同位置的天线实现对用户数据的联合并行发送，不仅避免了由交叉覆盖导致的乒乓切换等负面效应，还提升了边缘区域的信号覆盖效果。在乌兰木伦煤矿的300米采煤工作面内，利用分布式MIMO组网技术实现了5G信号的无边界覆盖，上行速率不低于500Mbps，保障了煤机数据的实时有效传输。     

切顶卸压技术在双鸭山矿区沿空留巷中的应用

为了使双鸭山矿区煤炭资源最大程度地被采掘,减少资源浪费,提高矿井效益,延长矿井服务年限及促进矿井安全生产,以双鸭山矿区3个缓倾斜中厚煤层综采工作面为工程背景,对切顶卸压无煤柱开采技术进行深入探索,经过实际的检验证明,在双鸭山矿区缓倾斜中厚煤层中,采用切顶卸压技术进行沿空留巷,技术可行,经济合理,工艺简单,成巷率高。     

基于多媒体技术的思想政治教育课程资源整合系统

为解决资源种类划分结果异常,设计基于多媒体技术的思想政治教育课程资源整合系统。选用CYUSB3014芯片作为此次设计系统的主控芯片,并设定信息处理芯片以及外围电路。在此基础上,对思政课程信息进行分类,建立了课程资源库。优化资源整合模块,设定多媒体资源整合流程,并添加DataSet与.NET Framework数据处理程序,实现对多媒体数据的高效处理。构建系统测试环节显示,此系统资源种类划分结果较为合理且系统承载率较高。由此可知,此系统在应用中具有较高的综合性能。     

A hybrid optimization technique for proficient energy management in smart grid environment

Electrical energy is one of the key components for the development and sustainability of any nation. India is a developing country and blessed with a huge amount of renewable energy resources still there are various remote areas where the grid supply is rarely available. As electrical energy is the basic requirement, therefore it must be taken up on priority to exploit the available renewable energy resources integrated with storage devices like fuel cells and batteries for power generation and help the planners in providing the energy-efficient and alternative solution. This solution will not only meet electricity demand but also helps reduce greenhouse gas emissions as a result the efficient, sustainable and eco-friendly solution can be achieved which would contribute a lot to the smart grid environment. In this paper, a modified grey wolf optimizer approach is utilized to develop a hybrid microgrid based on available renewable energy resources considering modern power grid interactions. The proposed approach would be able to provide a robust and efficient microgrid that utilizes solar photovoltaic technology and wind energy conversion system. This approach integrates renewable resources with the meta-heuristic optimization algorithm for optimal dispatch of energy in grid-connected hybrid microgrid system. The proposed approach is mainly aimed to provide the optimal sizing of renewable energy-based microgrids based on the load profile according to time of use. To validate the proposed approach, a comparative study is also conducted through a case study and shows a significant savings of 30.88% and 49.99% of the rolling cost in comparison with fuzzy logic and mixed integer linear programming-based energy management system respectively.     

Distributed two‐stage state estimation with event‐triggered strategy for multirate sensor networks

This paper investigates the state estimation issue for a class of wireless sensor networks (WSNs) with the consideration of limited energy resources. First, a multirate estimation model is established, and then, a new event‐triggered two‐stage information fusion algorithm is developed based on the optimal fusion criterion weighted by matrices. Compared with the existing methods, the presented fusion algorithm can significantly reduce the communication cost in WSNs and save energy resources of sensors efficiently. Furthermore, by presetting a desired containment probability over the interval [0,1] with the developed event‐triggered mechanism, one can obtain a suitable compromise between the communication cost and the estimation accuracy. Finally, a numerical simulation for the WSN tracking system is given to demonstrate the effectiveness of the proposed method.     

Scalable Yielding of Highly Stable Polyelectrolyte-Coated Copper Sulfide Nanoparticles by Flash Nanoprecipitation for Photothermal-Chemotherapeutics

Photothermal-chemotherapeutic nanoparticles (NPs) are attracting increasing attention and becoming more widely used for cancer therapy in the clinic due to their noninvasiveness, notable tissue penetration abilities, and low systemic adverse effects. However, functional ligands are conventionally modified onto photothermal NPs to well stabilize the inorganic particles suffering from complex chemical modifications, low productivity, and batch-to-batch inconsistencies, and thus significantly restricting their clinical applications. Herein, flash nanoprecipitation (FNP) is taken advantage of to afford rapid and uniform mixing for generating local supersaturated CuS clusters for small and highly stable CuS NPs effectively stabilized by polyacrylic acid through a continuous strategy. It greatly reduces the complexity for CuS NPs synthesis and functionalization in a facile intensified mixing process. These as-synthesized particles are high-drug loading, scalable, and most importantly, it is easy to control their sizes and charges through external conditions. Toxicity and tumor inhibition experiments confirm the high cell toxicity and good suppression of tumor growth under near-infrared irradiation indicating a promising prospect of FNP in the large-scale and continuous yielding of highly stable and high-performing photothermal-chemotherapeutic NPs for cancer therapy.     

Enhancement of a global lake and reservoir database to aid climate studies and resource monitoring utilizing satellite radar altimetry

Here, we describe the expansion and enhancement of a large (surface area ≥100 km²) lake and reservoir database (1.GREALD). These efforts have also resulted in the spin-off of two additional databases, one containing lakes and reservoirs (2.GREALD, area 10–99 km²), and the other containing ephemeral lakes (3.GELD, area ≥100 km²). These databases are unique sources for projects that utilize satellite radar altimeter data to monitor surface water levels. While 1.GREALD aims to be a complete catalog, 2.GREALD focuses on reservoirs in response to applied sciences programs that monitor water and energy resources. The creation of 3.GELD has climate change objectives as well as water resources and ecosystem conservation applications. The recording of information pertaining to the potential overpasses (waterbody crossings) of the current and archive satellite altimeters is a primary objective as is the need to highlight any form of controlled water level variation. The permanent water databases now contain 6282 entries, half experience some form of anthropogenic influence and ～430 have been identified as potential climatically sensitive terminal lakes. The revised integral surface area distribution is a power law with exponent ?1.016. Statistics reveal that with altimetric repeat visit times of 10-day to monthly, at least 80% of the permanent water bodies (≥10 km²) have been overflown at some period since the 1990s. Current information on water use and reservoir formation date show that the primary use of the reservoir class is hydroelectric power, and that China, Brazil, India, Turkey, and Vietnam dominate the dam building in recent decades.     

Cryptographic Lightweight Encryption Algorithm with Dimensionality Reduction in Edge Computing

Edge Computing is one of the radically evolving systems through generations as it is able to effectively meet the data saving standards of consumers, providers and the workers. Requisition for Edge Computing based items have been increasing tremendously. Apart from the advantages it holds, there remain lots of objections and restrictions, which hinders it from accomplishing the need of consumers all around the world. Some of the limitations are constraints on computing and hardware, functions and accessibility, remote administration and connectivity. There is also a backlog in security due to its inability to create a trust between devices involved in encryption and decryption. This is because security of data greatly depends upon faster encryption and decryption in order to transfer it. In addition, its devices are considerably exposed to side channel attacks, including Power Analysis attacks that are capable of overturning the process. Constrained space and the ability of it is one of the most challenging tasks. To prevail over from this issue we are proposing a Cryptographic Lightweight Encryption Algorithm with Dimensionality Reduction in Edge Computing. The t-Distributed Stochastic Neighbor Embedding is one of the efficient dimensionality reduction technique that greatly decreases the size of the non-linear data. The three dimensional image data obtained from the system, which are connected with it, are dimensionally reduced, and then lightweight encryption algorithm is employed. Hence, the security backlog can be solved effectively using this method.     

可控中子及X射线源测井技术发展现状及趋势

随着核仪器技术的进步以及安全健康的工业发展需求，具有人工可控性的中子源及X射线源逐步在测井领域得到推广应用，为油气等矿产资源的勘探开发提供了关键技术手段。可控中子及X射线源测井技术是以中子发生器或X射线管产生的中子或X射线与地层物质作用，通过探测中子、伽马或X射线从而进行地层孔隙度、密度、油气饱和度和元素含量的测井技术。本文概述了可控中子及X射线源测井技术，回顾了其发展历程；介绍了可控中子及X射线测井技术在数值模拟、仪器研制及数据处理方法方面的研究现状及应用，并展望了可控中子及X射线源测井技术的发展前景，认为未来可控中子及X射线源测井技术可从以下三个方面开展研究：分析不同射线在能量、时间及空间的分布规律，开展探测理论基础研究；联合不同学科优势，开展多类型多模式的新型仪器研制；增强谱数据校正及解析方法研究，开展谱信息综合分析及应用。