基于CiteSpace的资源型产业研究知识图谱分析

资源型产业发展为推进国家经济增长和工业化进程提供了重要保障。为深入了解资源型产业的研究情况，以CNKI数据库为数据源，搜集2000—2020年关于资源型产业的核心及以上期刊论文，利用CiteSpace软件从发文作者与研究机构分布、关键词共现网络和时区图谱等方面，绘制知识图谱，进行可视化分析。研究发现：资源型产业领域的研究成果愈加丰富，但研究群体间联系合作较少，且现有的合作研究主要集中在所处地域资源富集和具有学科优势的研究机构及学者；资源型产业领域的研究热点可概括为产业发展、资源型城市、产业集群、产业结构、产业链和产业集聚等方面；针对资源型产业领域未来可从资源型产业相关理论研究、创新发展模式和可持续发展等方面深入展开。     

Design of frameworks for self-adaptive service-oriented applications: A systematic analysis

Self-adaptive service-oriented Applications (Self-Apps) must be able to understand themselves or the environment in which they are executed, and propose solutions to meet changing conditions. The development of these applications is not a trivial task, since it encompasses issues from different research areas. Despite the importance of frameworks for Self-Apps, there is a lack of comprehensive analysis of how the design of such applications is performed, and regarding the standardization of concepts and coverage of minimum requirements for Self-Apps. The main contribution of this article is to present this comprehensive analysis, providing the state of the art for this subject. This analysis was built through a Systematic Mapping Study, based on a total of 65 studies, from which we identify the main attributes for Quality of Service (QoS), search strategies, and service management strategies employed in the design of frameworks for Self-Apps. The main aspects of requirements involved in the design of Self-Apps were pointed out to stakeholders. For example, these applications must implement a method for evaluation of QoS based on metrics. We also put forward the S-Frame, a modular solution that brings together the main features for the design of Self-Apps, and describe the main challenges concerning these applications.     

Investigation of metallic color perception using real‐world materials

Metallic colors have a unique appearance of glossiness with features such as highlights, contrast, and reflections on their surface, and therefore, metallic objects are very attractive to humans. Especially, gold, silver, and copper colors are familiar metals used as decorative materials, coins, and other furnishings. However, the mechanism and condition of metallic perception have not been fully investigated. There are a few studies for investigating metallic perception using rendered patches or images, but there is no study using real‐world objects. In our previous study, we developed a simple representation technique that made real objects appear to be made of gold by projecting a solid color onto a target nonmetallic object. By using the representation technique, in this study, we have further investigated the perception of metallic appearance such as gold, silver, and copper using real‐world materials, and analyzed the difference between these metallic perceptions. Our results indicate that the perception of the metallic object is different for gold, silver, and copper. Our new findings are as follows: the glitter required for the perception of gold and silver becomes an obstacle to the perception of copper; the metallic perception reveals that learning experience might be strongly affecting; and luminance adjustment is sensitive to the perception of metallic objects.     

Estimating underground mine ventilation friction factors from low density 3D data acquired by a moving LiDAR

Ventilation system analysis for underground mines has remained mostly unchanged since the Atkinson method was made popular by Mc Elroy in 1935. Data available to ventilation technicians and engineers is typically limited to the quantity of air moving through any given heading. Because computer-aided modelling, simulation, and ventilation system design tools have improved, it is now important to ensure that developed models have the most accurate information possible. This paper presents a new technique for estimating underground drift friction factors that works by processing 3 D point cloud data obtained by using a mobile Li DAR. Presented are field results that compare the proposed approach with previously published algorithms, as well as with manually acquired measurements.     

基于VR技术的智能变电站运行仿真培训系统

为了更加真实、直观地呈现智能变电站的运行整体结构,构建基于VR技术的智能变电站运行仿真培训系统。该系统通过5个模块协同完成智能变电站运行仿真培训,结合实际变电站的设备情况,采用二维纹理映射方法完成变电站设备仿真建模;系统利用虚拟现实交互模块呈现培训场景,参与培训人员能够通过人机交互设备,实现场景漫游和相关培训内容操作。测试结果表明:该系统能够较好地模拟出智能变电站的实际运行情况,参与培训的人员可以身临其境地完成整个变电站的巡视,更真实、直观地呈现智能变电站的整体状态。     

Adaptive neural network command filtered backstepping control of pure‐feedback systems in presence of full state constraints

An adaptive neural network (NN) command filtered backstepping control is proposed for the pure‐feedback system subjected to time‐varying output/stated constraints. By introducing a one‐to‐one nonlinear mapping, the obstacle caused by full stated constraints is conquered. The adaptive control law is constructed by command filtered backstepping technology and radial basis function NNs, where only one learning parameter needs to be updated online. The stability analysis via nonlinear small‐gain theorem shows that all the signals in closed‐loop system are semiglobal uniformly ultimately bounded. The simulation examples demonstrate the effectiveness of the proposed control scheme.     

Scientific mapping to identify competencies required by industry 4.0

The objective of this study was to identify what competencies are identified in the literature as necessary for Industry 4.0 by conducting a survey of the literature and a scientific mapping of the evolution of the issues related to the qualification of professionals for Industry 4.0 and possible paths for research and education. A search was conducted on the Scopus, Web of Science and Science Direct databases for the interval from 2010 to 2018. This systematic review revealed topics and authors currently specialized in the field and allowed mapping the field of study. The identification of journals and keywords useful in future studies was also an object of this study. SciMAT software was used for the systematic literature review. The results are highlighted by the set of competencies (knowledge and skills) that must be developed in professional education to accompany the new industrial revolution, as well as the importance of integrating efforts by companies, governments and universities. These efforts should focus on creating “learning factories”, which are understood to be environments that provide practical experiences to these professionals, preparing them in the best way possible for the requirements of Industry 4.0. This conceptual map showed that the main competencies needed include skills: (leadership, strategic vision of knowledge, self-organization, giving and receiving feedback, pro-activity, creativity, problem solving, interdisciplinarity, teamwork, collaborative work, initiative, communication, innovation, adaptability, flexibility and self-management) and knowledge of contemporary fields (information and communication technology, algorithms, automation, software development and security, data analysis, general systems theory and sustainable development theory).     

Revealing Nanomechanical Domains and Their Transient Behavior in Mixed-Halide Perovskite Films

Halide perovskites are a versatile class of semiconductors employed for high performance emerging optoelectronic devices, including flexoelectric systems, yet the influence of their ionic nature on their mechanical behavior is still to be understood. Here, a combination of atomic-force, optical, and compositional X-ray microscopy techniques is employed to shed light on the mechanical properties of halide perovskite films at the nanoscale. Mechanical domains within and between morphological grains, enclosed by mechanical boundaries of higher Young's Modulus (YM) than the bulk parent material, are revealed. These mechanical boundaries are associated with the presence of bromide-rich clusters as visualized by nano-X-ray fluorescence mapping. Stiffer regions are specifically selectively modified upon light soaking the sample, resulting in an overall homogenization of the mechanical properties toward the bulk YM. This behavior is attributed to light-induced ion migration processes that homogenize the local chemical distribution, which is accompanied by photobrightening of the photoluminescence within the same region. This work highlights critical links between mechanical, chemical, and optoelectronic characteristics in this family of perovskites, and demonstrates the potential of combinational imaging studies to understand and design halide perovskite films for emerging applications such as photoflexoelectricity.     

电子探针面分析法测定钢的脱碳层深度

提出钢表层脱碳层深度测定的一种新方法,即电子探针面分析法。对热轧态高碳工具钢75Cr1、淬火齿轮钢20CrMnTi、冷轧退火低碳车厢板SH1100钢3个典型钢种完成脱碳层深度的测定试验,结果表明:对于珠光体-铁素体型中高碳钢的脱碳层深度测定,金相法测定值是电子探针面分析法测定值的77%左右;对于淬回火钢的脱碳层深度测定,电子探针面分析法的测量精度在10 μm以下,约是显微硬度法测量精度的十分之一;对于脱碳层深度不易准确测定的低碳钢,电子探针面分析法通过较大区域范围的平均碳含量变化曲线来测定脱碳层深度,测量结果准确。电子探针面分析法在脱碳层深度测定方面具有钢种组织状态不限、试样形状不限、数据统计性好、测量精度高、易操作等优势,可在业内大力推广。     

Fine resolution mapping of population age-structures for health and development applications

The age-group composition of populations varies considerably across the world, and obtaining accurate, spatially detailed estimates of numbers of children under 5 years is important in designing vaccination strategies, educational planning or maternal healthcare delivery. Traditionally, such estimates are derived from population censuses, but these can often be unreliable, outdated and of coarse resolution for resource-poor settings. Focusing on Nigeria, we use nationally representative household surveys and their cluster locations to predict the proportion of the under-five population in 1 × 1 km using a Bayesian hierarchical spatio-temporal model. Results showed that land cover, travel time to major settlements, night-time lights and vegetation index were good predictors and that accounting for fine-scale variation, rather than assuming a uniform proportion of under 5 year olds can result in significant differences in health metrics. The largest gaps in estimated bednet and vaccination coverage were in Kano, Katsina and Jigawa. Geolocated household surveys are a valuable resource for providing detailed, contemporary and regularly updated population age-structure data in the absence of recent census data. By combining these with covariate layers, age-structure maps of unprecedented detail can be produced to guide the targeting of interventions in resource-poor settings.