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Research in Higher Education - Given the significant need to increase and diversify graduate enrollments within computing fields, it is vital to understand what shapes students’ pathways to...  相似文献   
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ABSTRACT

The aims of this study were to identify profiles of sedentary behaviour (SB) patterns, based on leisure-time self-reported SB modalities (screen, educative, social, and relaxing) and to evaluate changes in these profiles over 2 years among Spanish youth aged 8–18 years. Latent profile analysis (LPA), a data-driven analytic approach, was used to identify groups of boys and girls (n = 1553; 48% girls; mean±SD age: 12.56 ± 2.49 y) with distinct SB profiles using the SB modalities (time/d) as input variables. Latent transition analysis, an extension of LPA that uses longitudinal data, was used to analyse 2-year changes in these profiles. At baseline, four and three SB profiles were found among boys (labelled: screen, educative, social, and relaxing) and girls (labelled: screen/social, educative, and relaxing), respectively. Overall, more girls (range: 48%-67%) had the same profile over time, than boys (40%-52%). Participants with a screen or relaxing SB profile at baseline were more likely to have an educative profile after 2 years. Youth with a social and an educative SB profile at baseline were more likely to transition to profiles characterized by higher screen and social SB, respectively. Using a novel and person-centered approach, this study identified gender-specific SB profiles that were moderately stable over time.  相似文献   
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基于深度学习的中文专利自动分类方法研究   总被引:2,自引:0,他引:2  
[目的/意义] 面向当前国内专利审查和专利情报分析工作中对于海量专利分类的客观需求,设计了7种基于深度学习的专利自动分类方法,对比各种方法的分类效果,从而助力专利分类效率和效果的提升。[方法/过程] 针对传统机器学习方法存在的缺陷,基于Word2Vec、CNN、RNN、Attention机制等深度学习技术,考虑专利文本语序特征、上下文特征以及分类关键特征,设计Word2Vec+TextCNN、Word2Vec+GRU、Word2Vec+BiGRU、Word2Vec+BiGRU+TextCNN等7种深度学习模型,以中国专利为例,选取IPC主分类号的"部"作为分类依据,对比这7种模型与3种传统分类模型在中文专利分类任务中的效果。[结果/结论] 实证研究效果显示,采用考虑语序特征、上下文特征及强化关键特征的深度学习方法进行中文专利分类具有更优的分类效果。  相似文献   
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[目的/意义] 通过构建二模复杂网络模型,揭示隐藏在海量文献中的隐性知识。[方法/过程] 通过NetworkX复杂网络工具包,依据任意两个节点的共现关系构建二模复杂网络模型;对网络模型中节点的共现关系进行加权,计算网络的拓扑信息并进行AP聚类,提取节点间的直接关系;采用AUC方法对AA、JC、加权改进的wAA和wJC等4种链路预测算法进行评价,遴选出最合适的预测算法,并对复杂网络的隐性关系进行预测分析。[结果/结论] 以潜在药物靶点挖掘为例进行的实证研究结果表明,wAA链路预测算法为最优的链路预测算法;二模复杂网络模型、指标和方法体系在美国化学文摘社数据库中的药物靶点挖掘中具有一定的有效性。下一步计划在其他数据库中或其他研究领域中进行尝试,以进一步验证该模型的通用性和有效性。  相似文献   
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Cultural Studies of Science Education - The retention of underrepresented students remains a significant challenge in the STEM (Science, Technology, Engineering and Math) disciplines. A broad range...  相似文献   
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This study investigated the validity and reliability of the GymAware PowerTool (GPT). Thirteen resistance trained participants completed three visits, consisting of three repetitions of free-weight back squat, bench press, deadlift (80% one repetition maximum), and countermovement jump. Bar displacement, peak and mean velocity, peak and mean force, and jump height were calculated using the GPT, a three-dimensional motion capture system (Motion Analysis Corporation; 150 Hz), and a force plate (Kistler; 1500 Hz). Least products regression were used to compare agreeability between devices. A within-trial one-way ANOVA, typical error (TE; %), and smallest worthwhile change (SWC) were used to assess reliability. Regression analysis resulted in R2 values of >0.85 for all variables excluding deadlift mean velocity (R2 = 0.54–0.69). Significant differences were observed between visits 3-2 for bench press bar displacement (0.395 ± 0.055 m; 0.383 ± 0.053 m), and deadlift bar displacement (0.557 ± 0.034 m; 0.568 ± 0.034 m). No other significant differences were found. Low to moderate TE (0.6–8.8%) were found for all variables, with SWC ranging 1.7–7.4%. The data provides evidence that the GPT can be used to measure kinetic and kinematic outputs, however, care should be taken when monitoring deadlift performance.  相似文献   
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A significant number of archaeological finds of the 13th–16th century from the Tuscan sites of Germagnana and Gambassi in Valdelsa—FI, was studied by different physico-chemical investigations (SEM–EDS, ICP, Mössbauer spectroscopy, XRD, XRF, TG-DTA) in order to contribute to clarify the production methodology and the pre-industrial glass manufacture technology. The studied samples are mainly non-vitreous finds as production waste, refractory materials, crucibles and raw materials; also vitreous finds as frits, skims, glasses (glass masses, glass working waste and finished products) have been taken into consideration. The obtained petrographic and physico-chemical data strongly suggest that both Gambassi and Germagnana glass manufactures were strictly connected with the sources of vitrifiable materials, situated in Tuscan sand quarries. In particular a comparison between sands from the neighbouring quarries and appropriate finds of the two archaeological sites evidences that the employed vitrifiable materials possibly belong to La Casina La Cava resort. The archaeological classification, based on macroscopic observation and stratigraphic position, was compared and verified with the scientific classification of the examined finds of Germagnana and Gambassi sites based on their composition, morphology and physico-chemical properties.  相似文献   
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