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.     

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.     

Deformation of a surface layer and coating application using a flexible tool

The microstructure and properties of the functional coatings formed by impact friction processing of product surfaces with a flexible tool are studied. It is established that the processing produces a hard nanostructured surface layer with fragments up to 0.13 µm in size, as it is achieved by severe plastic deformation.     

Alloy optimisation of bainitic steel for large plastic mould

Based on the phase transformation theories, especially the T₀ concept of bainite transformation, alloy optimisation of bainitic steel with carbides has been carried out aiming at the produce of plastic mould with large cross-section. The effect of manganese and silicon on proeutectoid ferrite and bainite transformation is explored by dilatometric analysis, XRD and different microscopy techniques. The results show that after the alloy optimisation, the transformation of proeutectoid ferrite is suppressed and when the cooling rate is lower than 0·1°C?s^??1, the new lower bainite transformation appears by decreasing carbon capacity of austenite and promoting carbide precipitation. Industrial production proves that the optimised alloy SDP1 can meet the demand for the plastic mould with the thickness of 1050?mm.     

Determination of the Life Cycle of Heat-Exchange Tubes of Vapor Condensers on the Basis of Statistical Analysis of Local Pitting Corrosion According to Data of Eddy Current Testing

Protection of Metals and Physical Chemistry of Surfaces - The possibility is shown of creating a chart of local corrosion damage in the walls of heat-exchange tubes on the basis of the data of...