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1.
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   
2.
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   
3.
随着深度学习技术的兴起,目标检测算法正在经历着变革式的发展。作为深度学习目标检测研究领域中最新的一个研究方向,基于关键点的目标检测算法正在得到越来越多的关注,已成为目标检测的一个重要研究方向。本文在对基于深度学习的目标检测技术进行简要回顾的基础上,着重分析了基于关键点的目标检测方法所涉及的核心技术,并从所采用的骨干网络、特征点、COCO数据库中的检测表现等几个角度对相关方法进行汇总,论述了各类方法的检测性能。最后通过对各类方法进行对比总结出当前关键点目标检测方法存在的问题,并对未来的研究方向进行了展望。  相似文献   
4.
BackgroundAthletes tend to have better visuo-motor performance than do sedentary individuals. However, several basic visual-function and perceptual parameters remain unexplored to date. In this study, we investigated whether differences exist in visual function, performance, and processing between basketball players and individuals without a sport-involvement background.MethodsA total of 33 healthy men with no visual impairment or pathology were divided into 2 groups, depending on the involvement in sport (semi-professional basketball players and sedentary individuals). We tested their baseline heart-rate variability in the resting position apart from subjective questionnaires to determine their physical fitness level, and we checked their visual function, performance, and processing through an extended battery of optometric tests.ResultsThe 2 groups differed in resting heart-rate variability parameters (p < 0.001), confirming their dissimilarities in regular time practising sports per week. The basketball players showed a closer breakpoint and recovery nearpoint of convergence, a higher fusional-vergence rate, better discriminability halos, and better eye–hand coordination (all p values < 0.05).ConclusionThese results show evidence that athletes, basketball players in this case, exhibit better performance in several visual abilities in comparison to a group of individuals without sporting backgrounds, suggesting an improvement due to the systematic involvement of those skills during basketball practice.  相似文献   
5.
BackgroundHealth-related fitness knowledge (HRFK) has been an essential concept for many health and physical education programs. There has been limited understanding and longitudinal investigation on HRFK growth. This longitudinal study examined HRFK growth and its individual- and school-level correlates in middle school years under 1 curriculum condition: Five for Life.MethodsParticipants were 12,044 students from 47 middle schools. Data were collected at both individual/participant and school/institution levels. Individual-level variables included gender, grade, and HRFK test scores. School-level variables included percentage of students receiving free and reduced meals (FARM), student-to-faculty ratio for physical education, and school academic performance (SAP). We used hierarchical linear modeling to examine HRFK 3-year growth in relation to individual- and school-level correlates.ResultsThe average HRFK score at 6th grade for females was 42.81% ± 1.32%. The predicted HRFK growth was 17.06% ± 1.02% per year, holding other factors constant. A 1-standard deviation increase in FARM correlated with a 14.68%-point decrease in predicted test score (p = 0.02). A 1-standard deviation increase in SAP was associated with an 11.90%-point increase in HRFK score. Males had a significantly lower growth rate than females during the middle school years (0.78%/year, p = 0.02).ConclusionThe result showed that both individual- and school-level variables such as gender, FARM, and SAP influenced HRFK growth. Educators should heed gender differences in growth curves and recognize the correlates of school-level variables.  相似文献   
6.
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   
7.
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   
8.
创新驱动高质量发展是高等教育发展的未来,也是“双一流”建设质量发展指标研究的关键。在筛选和找出“双一流”建设质量的关键绩效指标(KPI)的基础上,提出了三个步骤的技术路线:一是分析影响因素,且按其重要性进行排列;二是按重要程度不同而精选出关键影响要素和绩效指标;三是更加重视整体研究和相关性研究,促进“以评促建”功能的实现。最后,对其中几个关键绩效指标(KPI)进行较为详细的诠释,包括高等教育毛入学率、生师比、学术声誉调查等。  相似文献   
9.
在传统免疫细胞分离检测实验教学的基础上,利用高性能正置荧光显微镜和流式细胞仪以不同技术检测鉴定免疫细胞,对实验教学内容和教学方法进行了改革和实践。将教学与临床科研相结合,利用大型贵重仪器以及合理安排实验时间开发综合实验。结果表明,学生不仅可以更有效消化医学免疫学课程基础知识,了解学科新技术的发展,而且可以培养学生的科研创新能力和综合分析能力。  相似文献   
10.
针对传统光纤端面尺寸检测几何尺寸误差大、效率低的弊端,采用一种基于Halcon的光纤端面尺寸检测方法,利用数字图像处理算法,采用中值滤波的方法对图像进行预处理,消除图像噪声,并对图像进行二值化及形态学处理,选用Canny算子作为边缘检测算子确定像素级边缘,该方法边缘检测性能较好,且具有较强的抗噪声能力|再从选取的边缘中选出类圆度高的部分边缘进行共圆轮廓合并、拟合,通过拟合的椭圆和圆得到光纤半径、不圆度、同心度等几何参数。实验结果表明,纤芯和包层半径可以精确到万分之一,不圆度和同心度可以精确到小数点后8位,测量精度较高且不受操作水平影响。  相似文献   
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