Image retrieval based on AND/OR-construction models

With the rapid development of the Internet, finding desired images from numerous images has become an important research topic. In this paper, we propose an image retrieval system facilitating retrieval time and accuracy. Since the performance of image retrieval is deeply influenced by image features and retrieval methods. Five different types of features and five different methods are used to find the best combination for an image retrieval system. First, we segment out the main object in an image and then extract its features. Next, relevant features are selected from the original feature set for facilitating image retrieval, using the SAHS algorithm. Then, five methods based on AND/OR-construction are proposed to build the image retrieval model, using the relevant features. Finally, the experimental results not only show that our methods are more effective than the other state-of-the-art methods but also present some observations never explored by the previous research.

     

Evolution of collaboration and optimization of impact: self-organization in multinational research

Scientometrics - The expanding presence of multinational research teams highlights the importance of characterizing the outcomes of international collaboration. Herein, we characterize the...     

Mechanistic Insights and Photodegradation of Heterostructure Graphene Oxide/Titanium Dioxide

Topics in Catalysis - In this study, the electrospinning method was used to prepare graphene oxide/titanium dioxide (GO/TiO2) nanofibers with different contents of GO as photocatalysts used to...     

From utility disconnection to universal access

By some estimates, 31% of Americans face some sort of ‘energy insecurity,’ but the full extent of the issue and the magnitude of its effect are often difficult to quantify. This case study examines disconnection policies primarily in Minnesota and attempts to extrapolate lessons learned for other states and the nation as a whole. The case study concludes with a discussion about the relevance of U.S. universal access to the utility shut-off challenge.     

Th17 Cells as Potential Probiotic Therapeutic Targets in Inflammatory Bowel Diseases

Inflammatory bowel diseases (IBD) are characterized by wasting and chronic intestinal inflammation triggered by various cytokine-mediated pathways. In recent years, it was shown that T helper 17 (Th17) cells are involved in the pathogenesis of IBD, which makes them an attractive therapeutic target. Th17 cells preferentially produce interleukin (IL)-17A–F as signature cytokines. The role of the interplay between host genetics and intestinal microbiota in the pathogenesis of IBD was demonstrated. Probiotics are live microorganisms that when orally ingested in adequate amounts, confer a health benefit to the host by modulating the enteric flora or by stimulating the local immune system. Several studies indicated the effectiveness of probiotics in preventing and treating IBD (ulcerative colitis, and Crohn’s disease). Furthermore, there is mounting evidence of probiotics selectively targeting the Th17 lineage in the prevention and management of inflammatory and autoimmune diseases such as IBD. This review highlights critical roles of Th17 cells in the pathogenesis of IBD and the rationale for using probiotics as a novel therapeutic approach for IBD through manipulation of Th17 cells. The potential molecular mechanisms by which probiotics modulate Th17 cells differentiation and production are also discussed.     

Aerial face recognition and absolute distance estimation using drone and deep learning

The Journal of Supercomputing - Because of the rise of deep learning and neural networks, algorithms based on deep learning have also been developed and subtly applied in daily life. This paper...