Semantic word shifts in a scientific domain

Understanding semantic word shifts in scientific domains is essential for facilitating interdisciplinary communication. Using a data set of published papers in the field of information retrieval (IR), this paper studies the semantic shifts of words in IR based on mining per-word topic distribution over time. We propose that semantic word shifts not only occur over time, but also over topics. The shifts are examined from two perspectives, the topic-level and the context-level. According to the over-time word-topic distribution, stable words and unstable words are recognized. The diverging and converging trends in the unstable type reveal characteristics of the topic evolution process. The context-level shifts are further detected by similarities between word vectors. Our work associates semantic word shifts with the evolving of topics, which facilitates a better understanding of semantic word shifts from both topics and contexts.     

Do funded papers attract more usage?

Research funding has been seen as one of the most important resource in the reward system of science. And usage of publications denotes an interesting perspective of user behavior in scientific communication. This study aims to address the relationship between funding and Usage Count, which is a new metrics item established on the platform of Web of Science. Full records of 300,010 articles published in 2013 were downloaded in October 2015, and divided into six disciplines, including information science library science, education educational research, economics, computer science, materials science, and chemistry. Seven indicators were proposed to measure the impact, including Funding rate, Citation per paper, Usage rate, Usage per paper, Citation difference, Usage difference, and Conversion rate. It concluded funding has impact on usage and citation, and funded papers attract more usage, but varying in different disciplines. Usage Count can be used in the extension of citation metrics but with limits. This study originally engages with usage metrics and detected that there is positive correlation between usage and funding.     

Microwave dielectric properties of SrLa[Ga1−x(Mg0.5Ti0.5)x]O4 and SrLa[Ga1−x(Zn0.5Ti0.5)x]O4 (x = 0.2-0.8) ceramics

SrLa[Ga_1−x(R_0.5Ti_0.5)_x]O₄ (R = Mg, Zn) ceramics were prepared by a standard solid state sintering method. The single-phase ceramics with K₂NiF₄-type layered perovskite structure and I4/mmm space group were obtained, indicating that SrLa(R_0.5Ti_0.5) and SrLaGaO₄ can form the unlimited solid solutions. With increasing x for R = Mg and Zn, ε_r increases monotonously, the Qf value first increases and then decreases, while τ_f increases from a negative to a positive value. The optimized microwave dielectric properties were obtained as following: ε_r = 23.3, Qf = 89 400 GHz, τ_f = −0.8 ppm/°C for SrLa[Ga_0.6(Mg_0.5Ti_0.5)_0.4]O₄ and ε_r = 23.3, Qf = 76 200 GHz, τ_f = 0.2 ppm/°C for SrLa[Ga_0.7(Zn_0.5Ti_0.5)_0.3]O₄, indicating that the present solid solution ceramics are the promising candidates as microwave resonator materials for the telecommunication applications.     

分子筛脱水吸附塔的结构应力与疲劳分析

综合考虑分子筛脱水吸附塔的结构、疲劳状况及管口载荷等因素,利用ANSYS对吸附塔进行结构应力与疲劳分析。计算结果表明:所建立的吸附塔整体模型合理;该结构在确保可靠性的基础上可降低制造成本;该设备能满足疲劳寿命的要求。     

A multi-criteria context-sensitive approach for social image collection summarization

Recent increase in the number of digital photos in the content sharing and social networking websites has created an endless demand for techniques to analyze, navigate, and summarize these images. In this paper, we focus on image collection summarization. Earlier methods in image collection summarization consider representativeness and diversity criteria while recent ones also consider other criteria such as image quality, aesthetic or appeal. In this paper, we propose a multi-criteria context-sensitive approach for social image collection summarization. In the proposed method, two different sets of features are combined while each one looks at different criteria for image collection summarization: social attractiveness features and semantic features. The first feature set considers different aspects that make an image appealing such as image quality, aesthetic, and emotion to create attractiveness score for input images while the second one covers semantic content of images and assigns semantic score to them. We use social network infrastructure to identify attractiveness features and domain ontology for extracting ontology features. The final summarization is provided by integrating the attractiveness and semantic features of input images. The experimental results on a collection of human generated summaries on a set of Flickr images demonstrate the effectiveness of the proposed image collection summarization approach.     

高密度聚乙烯/铅硼复合材料屏蔽性能和力学性能研究

研究了高密度聚乙烯/铅硼复合材料的屏蔽性能和力学性能，通过屏蔽仿真比较了密度及碳化硼（B4C）含量对屏蔽性能的影响，通过试验比较了B4C含量对屏蔽性能、弯曲强度及冲击强度的影响。仿真结果表明,随聚乙烯/铅硼复合材料密度升高，快中子屏蔽性能下降，热中子屏蔽性能和γ屏蔽性能提高；保持聚乙烯/铅硼复合材料密度不变，随B4C含量的提高，中子屏蔽性能提高而γ屏蔽性能下降;实验数据表明,随B4C含量的升高，高密度聚乙烯/铅硼材料的快中子屏蔽性能、热中子屏蔽性能升高，γ屏蔽系数下降，冲击强度和弯曲强度下降明显，屏蔽性能测试结果和仿真结果规律性相符；综合仿真结果和实验数据表明，含B4C 2 %左右的高密度聚乙烯/铅硼复合材料同时具有较好的屏蔽性能和力学性能。