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1.
Masahiro Horiuchi Yoko Handa-Kirihara Daijiro Abe Yoshiyuki Fukuoka 《Journal of sports sciences》2019,37(14):1638-1647
We investigated combined effects of ambient temperature (23°C or 13°C) and fraction of inspired oxygen (21%O2 or 13%O2) on energy cost of walking (Cw: J·kg?1·km?1) and economical speed (ES). Eighteen healthy young adults (11 males, seven females) walked at seven speeds from 0.67 to 1.67 m s?1 (four min per stage). Environmental conditions were set; thermoneutral (N: 23°C) with normoxia (N: 21%O2) = NN; 23°C (N) with hypoxia (H: 13%O2) = NH; cool (C: 13°C) with 21%O2 (N) = CN, and 13°C (C) with 13%O2 (H) = CH. Muscle deoxygenation (HHb) and tissue O2 saturation (StO2) were measured at tibialis anterior. We found a significantly slower ES in NH (1.289 ± 0.091 m s?1) and CH (1.275 ± 0.099 m s?1) than in NN (1.334 ± 0.112 m s?1) and CN (1.332 ± 0.104 m s?1). Changes in HHb and StO2 were related to the ES. These results suggested that the combined effects (exposure to hypoxia and cool) is nearly equal to exposure to hypoxia and cool individually. Specifically, acute moderate hypoxia slowed the ES by approx. 4%, but acute cool environment did not affect the ES. Further, HHb and StO2 may partly account for an individual ES. 相似文献
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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
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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
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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
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Five hundred million tweets are posted daily, making Twitter a major social media platform from which topical information on events can be extracted. These events are represented by three main dimensions: time, location and entity-related information. The focus of this paper is location, which is an essential dimension for geo-spatial applications, either when helping rescue operations during a disaster or when used for contextual recommendations. While the first type of application needs high recall, the second is more precision-oriented. This paper studies the recall/precision trade-off, combining different methods to extract locations. In the context of short posts, applying tools that have been developed for natural language is not sufficient given the nature of tweets which are generally too short to be linguistically correct. Also bearing in mind the high number of posts that need to be handled, we hypothesize that predicting whether a post contains a location or not could make the location extractors more focused and thus more effective. We introduce a model to predict whether a tweet contains a location or not and show that location prediction is a useful pre-processing step for location extraction. We define a number of new tweet features and we conduct an intensive evaluation. Our findings are that (1) combining existing location extraction tools is effective for precision-oriented or recall-oriented results, (2) enriching tweet representation is effective for predicting whether a tweet contains a location or not, (3) words appearing in a geography gazetteer and the occurrence of a preposition just before a proper noun are the two most important features for predicting the occurrence of a location in tweets, and (4) the accuracy of location extraction improves when it is possible to predict that there is a location in a tweet. 相似文献
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冯文贺 《河南科技学院学报》2014,(9):47-50
提出一个以大规模语料库为资源提取材料,以词汇集为语义成分表达方式的动态词群建构方法,其维度特征值的提取不但具有客观性,而且操作简易。维度特征值用词汇集的方式表示特征取值范围,可以避免传统的义素概括性过强、词汇个性表现不足的缺陷。这种方法有利于面向应用的大规模动态词群的建构。 相似文献
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本文以我国家用电器产品为例,通过采用Logistic模型来描述在产品成长期各产品的市场扩展特征,比较各产品的参数差异,发现其中的规律性,为企业相关产品的市场扩展研究提供科学依据。 相似文献