National Science Library,Chinese Academy of Sciences
Not a member yet
10241 research outputs found
Sort by
The Research on Disruptive Technology Identification Based on Scientific and Technological Information Mining and Expert Consultation: A Case Study on the Energy Field
No full text
Context and auto-interaction are all you need: Towards context embedding based QoS prediction via automatic feature interaction for high quality cloud API delivery
No full textCloud application programming interface (API) is a software intermediary that enables data exchange, business logic or functionality delivery between applications, infrastructures and IoT devices for supporting service oriented architecture. Currently, the number of cloud API in the Web is increasing and the number of cloud API with similar functionality is very large. Since quality of service (QoS) can well differentiate the performance of similar cloud API, QoS prediction has become the critical base for fast, personalized and high-quality cloud API selection and recommendation. However, contexts are used indirectly through context aware neighbors in most existing researches and the combined feature interactions are treated equally in previous factorization machine based methods, which together hinder the accurate QoS prediction. To address the above concerns, we first conduct data analysis on real-world QoS datasets and provide conclusive evidence to verify the necessity of incorporating contextual information and differentiating feature interaction. Then, we propose a context-aware QoS prediction approach via automatic feature interaction named CAFI. Contextual information of both user and cloud API sides are directly fed into CAFI through feature embedding. Moreover, the importance weights of feature interactions are learned by a generalized regularized dual averaging optimizer, so as to reward effective feature interaction and penalize noise feature interaction automatically. Lastly, final QoS prediction is obtained in an ensemble way by balancing the results of linear regression, automatic feature interaction and non-linear interaction. Extensive experiments on two public real-world QoS datasets demonstrate that CAFI can significantly improve QoS prediction accuracy. And the proposed CAFI approach is promising to encourage service providers provide high quality APIs and enable developer get desired cloud APIs quickly, thereby promoting the development of API economy.</p
Dominant drivers of the increasing environmental footprint of changing diets in China
No full textShifting diets potentially contribute significantly, both directly and indirectly, to arable land depletion, water resource shortages, and climate change. They also play a key role in the sustainable development of resources and the environment in China. However, the economic and social demographic factors driving the environmental footprints of diet are not yet well understood and quantified, which hinders an effective assessment of the potential of clean food consumption in reducing environmental stress due to resource shortages and global warming. We based this study on Chinese statistical data and considered residents in China, who account for about 20% of the world's population, as the research object to demonstrate that the environmental footprints of the residents' diets at different levels are primarily driven by Engel's coefficient and the children dependency ratio, and secondarily by the proportion of the illiterate population in the total population over six years old, and these factors have completely different mechanisms of influencing the environmental footprint of urban and rural residents. These findings provide unique evidence supporting the regulation of the diet by influencing factors that can provide a reference for policy makers globally, especially in developing countries such as China with scarce arable land and freshwater resources, to address the diet-resource environment dilemma and promote the sustainable development of humans, resources, and the environment.</p
