Predicting the early growth of word and nonword reading fluency in a consistent syllabic orthography     

Tomohiro Inoue  George K. Georgiou  Naoko Muroya  Miyuki Hosokawa  Hisao Maekawa  Rauno Parrila 《Journal of Research in Reading》2020,43(3):364-381

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肌筋膜疼痛综合征诱因及外治手段研究进展     

林键杰  张翔 《体育科技文献通报》2020,(4):28-31

不良生活习惯和伤后康复不佳导致的肌筋膜疼痛综合征已经成为当前影响人们生活质量的因素之一。本文运用文献资料法,梳理肌筋膜疼痛综合征的诱因及外治(非内服药物治疗)手段,探究其干预手段的疗效,由病因入手,研究最佳干预方法。综合研究表明:(1)肌筋膜疼痛综合征病因包括:骨骼肌及筋膜外伤、风寒入侵机体、慢性劳损、局部肌筋膜慢性炎症损伤等;(2)目前对肌筋膜疼痛综合征康复的方法主要以针刺和温和灸为主,本文纳入针刺治疗和温和灸治疗有效率高达89.5%和100%;(3)其发病的常见部位为腰背部及肩颈部,不同部位、不同病因的肌筋膜疼痛综合征应采取不同的治疗方式,复合治疗方法比单一手段干预效果更佳。  相似文献   

基于AIS数据的船舶排放估测模型与实船验证     

王直欢  王维勋  施欣 《上海海事大学学报》2019,40(4):12-16

为提升船舶能耗和排放估测的准确性和灵活性,提出面向船舶自动识别系统(automatic identification system, AIS)大数据的完全自下而上的船舶能耗和排放估测新方法。该方法视船舶为一种基于船舶航迹的线排放源,在构建船舶网格化轨迹模型的基础上,考虑每个网格航段的持续时间和发动机负载,实现船舶能耗和排放的精细化建模,统一船舶排放总量和空间分布计算。实船应用表明,该方法可提供更加准确的船舶能耗估计,并可灵活计算各种航行状态、船队规模和时空尺度的能耗和排放清单。  相似文献   

一种基于图割的机载LiDAR单木识别方法     

王濮  邢艳秋  王成  习晓环 《中国科学院大学学报》2019,36(3):385-391

针对现有机载激光雷达（light detection and ranging，lidar）数据单木分割算法在密集林区中探测精度较低的问题，结合林木冠层空间结构分层的特点，提出一种从机载点云数据直接分离单木的方法。首先，对原始点云数据进行去噪、滤波、高程归一化；然后基于冠层高度模型（canopy height model，chm）计算局部最大值以确定冠层表面的明显树顶，以此作为单木位置的先验知识，继而采用归一化割（normalized cut，Ncut）方法实现冠层的初始分割；最后，以全局最大值代替局部最大值，并将冠层形状、冠层最小点数作为约束条件，再次利用Ncut方法完成对漏检单木的探测，进而实现单木的精确探测。实验结果表明，针对密集林区的单木分割，本方法有效地减少了漏识单木，整体精度达90%以上，将有助于单木三维结构定量描述及参数反演。  相似文献   

基于极化特征和纹理特征的PolSAR影像建筑物提取方法     

马肖肖  程博  刘岳明  崔师爱  梁琛彬 《中国科学院大学学报》2019,36(5):682-693

极化合成孔径雷达（PolSAR）以其多参数、多通道、多极化、信息记录更加完整等特点，在城市地物提取领域中发挥着重要作用，并已成为遥感影像研究领域的热点。选择覆盖苏州市的Radarsat2影像，利用极化非相干分解法和灰度共生矩阵法分别提取19种极化特征和8种纹理特征，通过分析建筑物、植被和水体的极化特征和纹理特征进行特征组合，结合主成分分析法（PCA）和支持向量机法（SVM）对城市建筑物进行提取，并定量评估精度。结果表明：基于极化特征的建筑物提取精度最高为92.4%；基于纹理特征的提取精度最高为88.9%；极化特征与纹理特征相结合可以提高精度，最高精度为93.7%；PCA特征融合算法具有较高的运算效率，同时提高了精度。  相似文献   

Digital Module 16: Longitudinal Data Analysis     

Jeffrey R. Harring  Tessa L. Johnson 《Educational Measurement》2020,39(3):137-138

In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module begins with a nontechnical overview of longitudinal data analyses drawing distinctions with cross-sectional analyses in terms of research questions to be addressed. Nuances of longitudinal designs, timing of measurements, and the real possibility of missing data are then discussed. The three interconnected components of the LME model—(1) a model for individual and mean response profiles, (2) a model to characterize the covariation among the time-specific residuals, and (3) a set of models that summarize the extent that individual coefficients vary—are discussed in the context of the set of activities comprising an analysis. Finally, they demonstrate how to estimate the linear mixed effects model within an open-source environment (R). The digital module contains sample R code, diagnostic quiz questions, hands-on activities in R, curated resources, and a glossary.  相似文献   

Ancient Mural Classification Method Based on Improved AlexNet Network     

Jianfang Cao  Hongyan Cui  Qi Zhang  Zibang Zhang 《文物保护研究》2020,65(7):411-423

ABSTRACT

As an important part of art and culture, ancient murals depict a variety of different artistic images, and these individual images have important research value. For research purposes, it is often important to first determine the type of objects represented in a painting. However, the mural painting environment makes datasets difficult to collect, and long-term exposure leads to underlying features that are not distinct, which makes this task challenging. This study proposes a convolutional neural network model based on the classic AlexNet network model and combines it with feature fusion to automatically classify ancient mural images. Due to the lack of large-scale mural datasets, the model first expands the dataset by applying image enhancement algorithms such as scaling, brightness conversion, noise addition, and flipping; then, it extracts the underlying features (such as fresco edges) shared by the first stage of a dual channel structure. Subsequently, a second-stage deep abstraction is conducted on the features extracted by the first stage using a two-channel network, each of which has a different structure. The obtained characteristics from both channels are merged, and a loss function is constructed to obtain the classification result. This approach improves the model's robustness and feature expression ability. The model achieves an accuracy of 84.24%, a recall rate of 84.15%, and an F1-measure of 84.13% when applied to a constructed mural image dataset. Compared with the AlexNet model and other improved convolutional neural network models, the proposed model improves each evaluation index by approximately 5%, verifying the rationality and effectiveness of the model for automatic mural image classification. The mural classification model proposed in this paper comprehensively considers the influences of network width and depth and can extract rich details from mural images from multiple local channels. An effective classification method could help researchers manage and protect mural images in an orderly fashion and quickly and effectively search for target images in a digital mural library based on a specified image category, aiding mural condition monitoring and restoration efforts as well as archaeological and art historical research.  相似文献   

基于DE-SVM的船舶航迹预测模型     

刘娇  史国友  杨学钱  朱凯歌 《上海海事大学学报》2020,41(1):34-39

为提高船舶航迹预测精度,解决准确建模难度大和神经网络易陷入局部最优的问题,考虑实时获取目标船AIS数据较少的特点,提出一种基于支持向量机(support vector machine,SVM)的航迹预测模型。选择AIS数据中的航速、航向和船舶经纬度作为样本特征变量;采用小波阈值去噪的方法处理训练数据;采用差分进化(differential evolution,DE)算法对模型内部参数寻优以提高模型收敛速度和预测精度。选取天津港实船某段航迹的AIS数据,比较基于DE-SVM与基于BP神经网络的航迹预测模型的仿真结果。结果表明,基于DE-SVM的航迹预测模型具有更高的预测精度,简单、可行、高效,且耗时少。  相似文献   

动态接力点模式下双自动化轨道吊协调调度     

邱亚  梁承姬  张悦 《上海海事大学学报》2020,41(3):53-59

为提高自动化集装箱码头堆场中自动化轨道吊(automated stacking crane,ASC)的作业效率,研究箱区动态接力点对双ASC作业效率的影响。考虑双ASC作业过程中的安全距离、相互冲突等因素,建立以最小化双ASC最长完工时间为目标的混合整数规划模型,利用遗传算法对该模型进行求解。与固定贝位接力模式进行对比,结果表明,相较于固定贝位接力模式,动态接力点模式下双ASC的作业效率更高。在不同规模算例背景下,将遗传算法与CPLEX的计算结果进行对比,验证了遗传算法的有效性。  相似文献   

基于隐马尔科夫模型的VLCC目的港预测     

杨春  王一丹  徐晖  胡勤友  潘亚兰 《上海海事大学学报》2020,41(4):42-49

超大型油船(very large crude carrier，VLCC)目的港预测对海运原油流向预测以及货源地未来运力估计具有重要作用。针对VLCC的AIS目的港信息存在缺失、更新不及时、不准确等现象，提出一种基于隐马尔科夫模型的VLCC目的港预测方法。分析船舶AIS轨迹数据，得到油船历史停靠港口序列；根据VLCC轨迹提取习惯航路，以航路中的交叉点为依据设置观测线；利用船舶航行轨迹数据判断船舶是否经过观测线以及经过观测线的方向，对不同方向分别计算船舶在挂靠港间的转移概率矩阵和船舶挂靠港与观测线间的输出概率矩阵，建立VLCC目的港预测模型并进行预测。研究结果表明：在大多数情况下VLCC目的港预测的准确率可以达到70%以上；航线越固定、运行越规律的船舶，预测准确率越高；船舶越靠近目的港，预测越准确；重载状态下的船舶目的港预测更准确。  相似文献