Directed collaboration patterns in funded teams: A perspective of knowledge flow     

《Information processing & management》2023,60(2):103237

Collaborations in funded teams are essential for understanding funded research and funding policies, although of high interest, are still not fully understood. This study aims to investigate directed collaboration patterns from the perspective of the knowledge flow, which is measured based on the academic age. To this end, we proposed a project-based team identification approach, which gives particular attention to funded teams. The method is applicable to other funding systems. Based on identified scientific teams, we detected recurring and significant subgraph patterns, known as network motifs, and under-represented patterns, known as anti-motifs. We found commonly occurred motifs and anti-motifs are remarkably characterized by different structures matching certain functions in knowledge exchanges. Collaboration patterns represented by motifs favor hierarchical structures, supporting intensive interactions across academic generations. Anti-motifs are more likely to show chain-like structures, hindering potentially various knowledge activities, and are thus seldom found in real collaboration networks. These findings provide new insights into the understanding of funded collaborations and also the funding system. Meanwhile, our findings are helpful for researchers, the public and policymakers to gain knowledge on research(ers) evolution, particularly in terms of primordial collaboration patterns.  相似文献   

A novel personality detection method based on high-dimensional psycholinguistic features and improved distributed Gray Wolf Optimizer for feature selection     

《Information processing & management》2023,60(2):103217

Existing personality detection methods based on user-generated text have two major limitations. First, they rely too much on pre-trained language models to ignore the sentiment information in psycholinguistic features. Secondly, they have no consensus on the psycholinguistic feature selection, resulting in the insufficient analysis of sentiment information. To tackle these issues, we propose a novel personality detection method based on high-dimensional psycholinguistic features and improved distributed Gray Wolf Optimizer (GWO) for feature selection (IDGWOFS). Specifically, we introduced the Gaussian Chaos Map-based initialization and neighbor search strategy into the original GWO to improve the performance of feature selection. To eliminate the bias generated when using mutual information to select features, we adopt symmetric uncertainty (SU) instead of mutual information as the evaluation for correlation and redundancy to construct the fitness function, which can balance the correlation between features–labels and the redundancy between features–features. Finally, we improve the common Spark-based parallelization design of GWO by parallelizing only the fitness computation steps to improve the efficiency of IDGWOFS. The experiments indicate that our proposed method obtains average accuracy improvements of 3.81% and 2.19%, and average F1 improvements of 5.17% and 5.8% on Essays and Kaggle MBTI dataset, respectively. Furthermore, IDGWOFS has good convergence and scalability.  相似文献   

基于负样本多通道优化SSD网络的钢铁厂提取     

卢凯旋  李国清  陈正超  昝露洋  李柏鹏  高建威 《中国科学院大学学报》2020,37(3):352-359

准确提取钢铁厂对去产能监测和环境保护具有重要意义。传统的人工目视解译方法效率低、成本高，无法满足开展大区域钢铁厂监测的需求。以深度学习目标检测网络SSD为基础，构建面向遥感影像钢铁厂提取的深度学习目标检测网络，提出maxout模块，将负样本通路优化为多分支结构，突出难分负样本特征并提升网络对无用特征的抵制效果。利用国产GF-1数据对京津冀地区的钢铁厂进行快速自动提取实验。与人工解译的钢铁厂点位数据的对比表明，该目标检测方法的提取精度达到80%以上。  相似文献   

一种在轨海上多运动舰船目标检测和跟踪方法     

矫腾章  胡玉新  吕鹏  张凯  台宪青 《中国科学院大学学报》2020,37(3):368-378

传统遥感卫星图像处理采用在地面进行目标检测和跟踪处理的模式，卫星将拍摄到的图像数据下传至地面数据处理中心，由地面数据处理系统对接收到的遥感图像数据进行目标检测和跟踪。然而，随着遥感图像分辨率的不断提高，需要下传的数据量增大，导致星地数据传输的时间大大增加，最终造成目标检测和跟踪的时效性降低。针对上述问题，提出一种基于多特征量判别的Canny边缘检测和联合概率数据关联的在轨海上多运动舰船目标检测和跟踪方法。将该方法利用中国科学院微小卫星创新研究院的高分微纳卫星实测数据在模拟星载的嵌入式开发平台上进行验证，结果表明该方法能够在轨对海上多运动舰船目标进行快速、准确的检测和跟踪。  相似文献   

基于深度学习的SSD模型尾矿库自动提取     

闫凯  沈汀  陈正超  闫弘轩 《中国科学院大学学报》2020,37(3):360-367

针对华北地区尾矿库自动提取问题，将基于深度学习的SSD目标检测模型应用于遥感图像尾矿库提取。首先标记华北地区2 000个样本，随机挑选1 500个作为训练样本，剩余样本作为测试样本，验证模型的检测精度。分析卷积层对应感受野与图像中尾矿库尺寸关系，发现原始SSD模型漏检误检大型尾矿库。改进SSD模型结构，提出增加额外卷积层的策略，提高对大型尾矿库目标的检测精度。实验表明，在置信度阈值为0.3时，改进的SSD模型相比原始模型，检测精确率提高10.0%，召回率提高14.4%，提高了大型尾矿库检测精度。验证了基于深度学习的SSD目标检测模型自动提取尾矿库的可行性以及改进算法的有效性。  相似文献   

基于无人机激光点云的树障检测与砍伐树木数量估算     

张苏  齐立忠  韩文军  朱笑笑  习晓环  王成  王濮  聂胜 《中国科学院大学学报》2020,37(6):760-766

电力走廊的树木生长会对输电线路的安全运营造成巨大影响，精确检测出影响线路安全的树木并将其砍伐至关重要。因此，提出一种基于无人机激光点云的树障检测与砍伐树木数量估算方法。首先，对激光点云进行快速自动化处理，先后精确提取地面点、电力线点与植被点；其次，基于电力线点进行分段，并分析电力线与植被点的安全距离，进而确定树障区域的位置和范围；最后，对树障区域植被点云进行单木分割，并统计单木数量，最终实现砍伐树木数量的精准估算。研究结果表明，无人机激光点云可以实现输电通道树障的有效检测与砍伐树木数量的精确估算，总体树木砍伐数量估算精度可达92.3%，可为输电线路安全运营提供遥感技术支撑，也可为电网运维单位制订树木砍伐计划提供可靠依据。  相似文献   

面向需求的应用本体不一致诊断方法研究     

宋丹辉 《现代情报》2016,36(3):27-37

为计算复杂应用本体中非合法蕴含式集合的根本性冲突原因, 首先对现有不一致诊断方法进行系统的梳理, 然后结合应用本体及其需求特点, 分析存在问题与不足, 探讨将原本相互孤立的、分别应用在不同诊断工具中的反模式探测法、根辨解法、简洁辨解法之核心算法进行组合、优化的思路与方法。在此基础上, 提出一个综合性的启发式简洁根辨解诊断法, 阐述其基本思路与具体步骤, 并以相关论文中经常使用的实验本体为例, 验证方法的有效性。  相似文献   

荧光标记法检测活细胞内游离钙离子浓度的改进   总被引：5，自引：0，他引：5  

许鑫华  傅英松  韩波  何淑兰  王遵  陈强 《科技通报》2003,19(4):282-284

改进了活细胞内游离钙离子浓度的测定方法，即用惰性基体纳米微球包埋荧光染料，将荧光纳米微球转运进细胞，用于细胞内游离钙离子浓度的实时测定。该方法与传统方法相比，染料不易泄漏，不会出现分室现象，不易光漂白，是一种非常有实用价值的测量活细胞内游离钙离子浓度的方法。  相似文献   

误用检测攻击模式表示技术研究     

吴伯桥  刘雪飞 《中国科技信息》2006,(13):101-102,104

误用检测技术由于其检测效率高、误报警率低，是目前实际IDS系统主要采用的技术，该技术是采用适当的方法描述已知攻击模式，与已知攻击模式匹配的事件认为是入侵，因此，攻击模式的表达是误用检测的主要研究问题。本文主要总结攻击模式的表示方法，并对各种方法进行分析。  相似文献   

网络入侵检测技术研究   总被引：2，自引：0，他引：2  

莫林利  王长征 《科技广场》2005,(2):35-36

入侵检测是保护网络信息安全的重要途径。本文介绍了网络入侵检测的概念和入侵检测技术的分类，重点阐述了网络入侵检测系统的工怍原理、信息收集及其分析方法。  相似文献