使能未来工厂的5G能力综述

5G系统将移动通信服务从移动电话、移动宽带和大规模机器通信扩展到新的应用领域，即所谓对通信服务有特殊要求的垂直领域。对使能未来工厂的5G能力进行了全面的分析总结，包括弹性网络架构、灵活频谱、超可靠低时延通信、时间敏感网络、安全和定位，而弹性网络架构又包括对网络切片、非公共网络、5G局域网和边缘计算的支持。希望从广度到深度，对相关的理论及技术应用做透彻、全面的梳理，对其挑战做清晰的总结，从而为相关研究和工程技术人员提供借鉴。     

Effect of phosphogypsum on saline-alkalinity and aggregate stability of bauxite residue

A column experiment was conducted to investigate the effect of phosphogypsum (PG) on the saline- alkalinity, and aggregate stability of bauxite residue. Results showed that: with increasing leaching time, the concentrations of saline-alkali ions decreased while the concentration increased in bauxite residue leachate; compared with CK (control group) treatment, pH, electric conductivity (EC), exchangeable sodium percentage (ESP), sodium absorption ratio (SAR), and exchangeable Na⁺ content of bauxite residue were reduced following PG treatment; average particle sizes in aggregates following CK and PG treatments were determined to be 155 and 193 nm, respectively. SR-μCT test results also confirmed that bauxite residue following PG treatment acquired larger aggregates and larger pore diameter. These results indicate that the PG treatment could significantly modulate the saline-alkalinity, and simultaneously enhance aggregate stability of bauxite residue, which provides a facile approach to reclaim bauxite residue disposal areas.     

大规模多状态计算系统的容错性能分析

针对异构计算节点组成的大规模多状态计算系统的容错性能分析问题，提出了一种计算系统容错性能的评估方法。该方法采用自定义的两级容错性能形式化描述框架进行系统描述，通过构造多值决策图（Multi-value Decision Diagram，MDD）模型对系统进行容错性能建模，并基于构造的模型高效地计算出部件故障的条件下计算系统在特定性能水平上运行的概率，减少了计算的冗余性。实验结果表明，该方法在模型的大小和构建时间上均优于传统方法。该方法的提出将对系统操作员或程序设计者具有重要意义，使其确保系统适合预期应用。     

A survey on fog computing for the Internet of Things

Fog computing has emerged to support the requirements of IoT applications that could not be met by today’s solutions. Different initiatives have been presented to drive the development of fog, and much work has been done to improve certain aspects. However, an in-depth analysis of the different solutions, detailing how they can be integrated and applied to meet specific requirements, is still required. In this work, we present a unified architectural model and a new taxonomy, by comparing a large number of solutions. Finally, we draw some conclusions and guidelines for the development of IoT applications based on fog.     

全尾砂和废石联合胶结充填体最佳配比及应用

针对红岭铅锌矿分级充填骨料来源不足、地表废石堆积污染环境的情况,提出将该矿选厂产生的全尾砂和地表废石作为充填骨料的联合胶结充填方案。分别测试了全尾砂和地表废石的物理化学性质,验证了碎石和全尾砂作为联合充填骨料的可行性。通过充填配比试验,分析了不同配比全尾砂废石充填体强度特性,得出了最佳充填配比。结果表明,充填试块的强度随灰砂比减小而减小,随养护龄期增加呈增大趋势,随充填料浆质量浓度增大而增大,最佳配比为: 胶结充填灰砂比1∶8、普通充填灰砂比1∶12,全尾砂∶废石配比4∶6,质量浓度78%。根据研究结果,在红岭铅锌矿进行了全尾砂废石充填技术工业应用,证实该技术可行。     

An overview on fault diagnosis and nature-inspired optimal control of industrial process applications

Fault detection, isolation and optimal control have long been applied to industry. These techniques have proven various successful theoretical results and industrial applications. Fault diagnosis is considered as the merge of fault detection (that indicates if there is a fault) and fault isolation (that determines where the fault is), and it has important effects on the operation of complex dynamical systems specific to modern industry applications such as industrial electronics, business management systems, energy, and public sectors. Since the resources are always limited in real-world industrial applications, the solutions to optimally use them under various constraints are of high actuality. In this context, the optimal tuning of linear and nonlinear controllers is a systematic way to meet the performance specifications expressed as optimization problems that target the minimization of integral- or sum-type objective functions, where the tuning parameters of the controllers are the vector variables of the objective functions. The nature-inspired optimization algorithms give efficient solutions to such optimization problems. This paper presents an overview on recent developments in machine learning, data mining and evolving soft computing techniques for fault diagnosis and on nature-inspired optimal control. The generic theory is discussed along with illustrative industrial process applications that include a real liquid level control application, wind turbines and a nonlinear servo system. New research challenges with strong industrial impact are highlighted.     

移动边缘计算环境下的动态资源分配策略

在通讯设备爆炸式增长的时代,移动边缘计算作为5G通讯技术的核心技术之一,对其进行合理的资源分配显得尤为重要。移动边缘计算的思想是把云计算中心下沉到基站部署(边缘云),使云计算中心更加靠近用户,以快速解决计算资源分配问题。但是,相对于大型的云计算中心,边缘云的计算资源有限,传统的虚拟机分配方式不足以灵活应对边缘云的计算资源分配问题。为解决此问题,提出一种根据用户综合需求变化的动态计算资源和频谱分配算法(DRFAA),采用"分治"策略,并将资源模拟成"流体"资源进行分配,以寻求较大的吞吐量和较低的传输时延。实验仿真结果显示,动态计算资源和频谱分配算法可以有效地降低用户与边缘云之间的传输时延,也可以提高边缘云的吞吐量。     

Usability of a cloud-based collaborative learning framework to improve learners’ experience

Computer-Supported Collaborative Learning (CSCL) is concerned with how Information and Communication Technology (ICT) might facilitate learning in groups which can be co-located or distributed over a network of computers such as Internet. CSCL supports effective learning by means of communication of ideas and information among learners, collaborative access of essential documents, and feedback from instructors and peers on learning activities. As the cloud technologies are increasingly becoming popular and collaborative learning is evolving, new directions for development of collaborative learning tools deployed on cloud are proposed. Development of such learning tools requires access to substantial data stored in the cloud. Ensuring efficient access to such data is hindered by the high latencies of wide-area networks underlying the cloud infrastructures. To improve learners’ experience by accelerating data access, important files can be replicated so a group of learners can access data from nearby locations. Since a cloud environment is highly dynamic, resource availability, network latency, and learner requests may change. In this paper, we present the advantages of collaborative learning and focus on the importance of data replication in the design of such a dynamic cloud-based system that a collaborative learning portal uses. To this end, we introduce a highly distributed replication technique that determines optimal data locations to improve access performance by minimizing replication overhead (access and update). The problem is formulated using dynamic programming. Experimental results demonstrate the usefulness of the proposed collaborative learning system used by institutions in geographically distributed locations.     

A Mobile Cloud-Based eHealth Scheme

Mobile cloud computing is an emerging field that is gaining popularity across borders at a rapid pace. Similarly, the field of health informatics is also considered as an extremely important field. This work observes the collaboration between these two fields to solve the traditional problem of extracting Electrocardiogram signals from trace reports and then performing analysis. The developed system has two front ends, the first dedicated for the user to perform the photographing of the trace report. Once the photographing is complete, mobile computing is used to extract the signal. Once the signal is extracted, it is uploaded into the server and further analysis is performed on the signal in the cloud. Once this is done, the second interface, intended for the use of the physician, can download and view the trace from the cloud. The data is securely held using a password-based authentication method. The system presented here is one of the first attempts at delivering the total solution, and after further upgrades, it will be possible to deploy the system in a commercial setting.     

人工砂混凝土性能试验研究

采用正交试验方法配制了不同人工砂取代率、石粉含量、粉煤灰含量的混凝土, 对比了每组混凝土的坍落度, 研究了3 d、28 d龄期混凝土的抗压性能。结果表明: 最优配比的人工砂取代率、石粉含量和粉煤灰含量分别为10%、3%和5%, 此时28 d抗压强度为40.1 MPa, 满足30 MPa的混凝土设计强度。