固废制备微晶泡沫玻璃的研究进展

为实现固体废弃物的高值化利用，从微晶泡沫玻璃的制备机理、工艺流程及温度制度等方面分析了工业固体废弃物制备微晶泡沫玻璃的可行性，重点论述了金属矿尾矿、赤泥、高炉矿渣、煤矸石、粉煤灰等固体废弃物制备微晶泡沫玻璃的国内外研究进展，并对微晶泡沫玻璃的研究和发展趋势进行了展望。     

浅谈压延铜箔光面色差的成因

针对压延铜箔在表面处理过程中光面易出现色差的问题,从设备、工艺、人员操作等方面进行成因探讨,并给出了应对措施。     

中国无机盐工业发展现状及展望

建国70 a以来中国无机盐工业发展迅猛,取得了巨大成就,中国已成为世界上最大的无机盐生产、出口和消费国。分析了中国无机盐工业生产现状和进出口情况,指出行业存在大宗产品产能过剩、产品精细化率偏低、产业集中度和资源配置率偏低、矿产资源保障能力不足、节能减排任务重、自主创新能力弱等问题,并提出未来发展建议及发展方向。新能源用无机材料、无机粉体功能材料、5G通迅用无机材料、电子化学品和电镀化学品等专用化学品将是未来无机盐工业发展的热点。随着产业链现代化水平的不断提升,将会逐渐实现行业规模化、绿色发展与安全生产。     

A Student's t-based density peaks clustering with superpixel segmentation (tDPCSS) method for image color clustering

Image color clustering is a basic technique in image processing and computer vision, which is often applied in image segmentation, color transfer, contrast enhancement, object detection, skin color capture, and so forth. Various clustering algorithms have been employed for image color clustering in recent years. However, most of the algorithms require a large amount of memory or a predetermined number of clusters. In addition, some of the existing algorithms are sensitive to the parameter configurations. In order to tackle the above problems, we propose an image color clustering method named Student's t-based density peaks clustering with superpixel segmentation (tDPCSS), which can automatically obtain clustering results, without requiring a large amount of memory, and is not dependent on the parameters of the algorithm or the number of clusters. In tDPCSS, superpixels are obtained based on automatic and constrained simple non-iterative clustering, to automatically decrease the image data volume. A Student's t kernel function and a cluster center selection method are adopted to eliminate the dependence of the density peak clustering on parameters and the number of clusters, respectively. The experiments undertaken in this study confirmed that the proposed approach outperforms k-means, fuzzy c-means, mean-shift clustering, and density peak clustering with superpixel segmentation in the accuracy of the cluster centers and the validity of the clustering results.     

服役后20号钢在低温下的力学性能研究

分析了20号无缝钢管的室温和低温力学性能,结合显微组织观察、晶粒度统计和断口分析,发现低温低应力工况下服役后20号无缝钢管的力学性能完全符合冷库用液氨管道的使用要求。     

共享交通的时空轨迹检索与群体发现

为解决共享交通下的共乘用户群体发现效率低、准确率不高问题，依据R-树原理建立GeoOD-Tree索引，并在此基础上提出以最大化共乘率为目标的群体发现策略。首先，对原始时空轨迹数据进行特征提取与标定处理，挖掘有效出行起讫点（OD）轨迹；其次，针对用户起讫点轨迹的特征，建立GeoOD-Tree索引进行有效的存储管理；最后，给出以最大化共乘行程为目标的群体发现模型，并运用K最近邻（KNN）查询对搜索空间剪枝压缩，提高群体发现效率。采用西安市近12000辆出租车营运轨迹数据，选取动态时间规整（DTW）等典型算法与所提算法在查询效率与准确率上进行性能对比分析。与DTW算法相比，所提算法的准确率提高了10.12%，查询效率提高了约15倍。实验结果表明提出的群体发现策略能有效提高共乘用户群体发现的准确率和效率，可有效提升共乘出行方式的出行率。     

Precise Extraction of Charge Carrier Mobility for Organic Transistors

Unreliable mobility values, and particularly greatly overestimated values and severely distorted temperature dependences, have recently hampered the development of the organic transistor field. Given that organic field‐effect transistors (OFETs) have been routinely used to evaluate mobility, precise parameter extraction using the electrical properties of OFETs is thus of primary importance. This review examines the origins of the various mobilities that must be determined for OFET applications, the relevant extraction methods, and the data selection limitations, which help in avoiding conceptual errors during mobility extraction. For increased precision, the review also discusses device fabrication considerations, calibration of both the specific gate‐dielectric capacitance and the threshold voltage, the contact effects, and the bias and temperature dependences, which must actually be handled with great care but have mostly been overlooked to date. This review serves as a systematic overview of the OFET mobility extraction process to ensure high precision and will also aid in improving future research.