Integration Of Multiple Databases Research Articles

Robust CNN-based flow pattern identification for horizontal gas-liquid pipe flow using flow-induced vibration

Determination of flow patterns is crucial for the prediction of unsteady flow parameters, which is important for multiphase flow pipeline integrity management. Thus far, various methods have been put forward, however, their robustness has yet to be thoroughly tested across varying environments. Despite recent progress in flow-induced vibration (FIV) of multiphase flows, variability due to measurement approach and pipeline conditions remains an under-investigated area. This paper proposes a non-intrusive, robust convolutional neural network (CNN) flow pattern identification method based on FIV analysis. FIV for horizontal gas–liquid pipe flow under various flow patterns is investigated experimentally by simultaneously analyzing acquired FIV signals and high-speed video. A range of pipeline scenarios is thoroughly studied, encompassing variations in flow conditions, measurement axes, pipe material, and installation conditions. Both Hilbert-Huang Transform (HHT) and Short Time Fourier Transform (STFT) are used to investigate the characteristics of FIV. The results show distinct flow patterns with the FIV signal varying with measurement axes and pipe conditions. Three processes are applied to increase identification robustness: HHT images to eliminate variability due to structure signatures and flow conditions; Ostu’s threshold to eliminate image magnitude difference; and data augmentation, applied to both time signals and images, to increase database diversity. From these, the morphological features associated with flow patterns are extracted. Pattern identification results using a neural network architecture trained by GoogLeNet show over 95% accuracy. To test the generalizability of the proposed flow pattern identification method, the trained method is employed to make predictions in various pipeline scenarios. The results show that the trained model attains an accuracy of over 90% when predicting the flow pattern using data from different axes, and an accuracy above 80% when predicting with different pipe material and installation conditions. During the model training phase, the integration of multiple databases or the implementation of transfer learning can result in a substantial improvement in accuracy, reaching a respectable level of at least 90%.

Mechanisms of traditional Chinese medicines in the treatment of allergic rhinitis using a network biology approach

Abstract Objective To systematically explore the effect and mechanism of traditional Chinese herbs in the treatment of allergic rhinitis. Methods Magnolia flower, xanthium fruit, astragalus root, paniculate cynanchum, scutellaria root, cicada molting, stephania root, small centipeda herb, and licorice root as traditional Chinese herbs are widely used to treat allergic rhinitis. With multiple database integration and entity grammar systems, a molecular interaction network of traditional Chinese herbs for treating allergic rhinitis was established. Bioinformatics approaches were adopted to integrate relevant data and biological information by multiple databases. Molecular interaction network of Chinese herbs for treating allergic rhinitis was constructed based on entity grammar systems model. The network was then used for elucidating the anti-allergic rhinitis mechanism of the Chinese herbs on the molecular level. The subnetworks were also extracted to explicitly display the pathway and targets where effective components acted on. Results Traditional Chinese herbs could influence various pathological aspects in allergic rhinitis including the production of pro-inflammatory substances, such as histamine and cytokine IL-4, IL-13, lowering IgE level or blocking antigen binding, altering the biological processes of IgE, modulating the balance of Th or other cells by cell proliferation and differentiation, mediating cell–cell signaling and second-messenger-mediated signaling, stabilizing the cell membrane, and affecting regulation of cellular defense response. Conclusion The research theoretically confirms the mechanism of anti-allergic rhinitis by traditional Chinese herbs, provides important fundamental research information for treatment of allergic rhinitis, and may serve as a reference for new drug development and effective ingredients of compatibility.

Implementation of data bases in advertising

Taking into account the modern tendencies in advertising, generation and use of databases is imposed as critical for achieving desired effects, reaching target audiences and their incitement to purchasing actions. Databases in this case include all data that advertisers or marketing agencies can collect on the target groups, which are related to their geographic and socio-demographic profiles, as well as behavioral patterns, especially when it comes to the consumption of certain products and media content. Such bases are essential for determining the appropriate media and advertising strategies in relation to members of target markets that appear to be in various stages of purchasing process. As all necessary data rarely can be collected from a single source, the integration of multiple databases by using appropriate techniques should be implemented in practice, in order to obtain more complex profiles of target groups.