Domain Adaptive Person Search via GAN-based Scene Synthesis for Cross-scene Videos

Person search has recently been a challenging task in the computer vision domain, which aims to search specific pedestrians from real cameras.Nevertheless, most surveillance videos comprise only a handful of images of each pedestrian, which often feature identical backgrounds and clothing. Hence, it is difficult to learn more discriminative features for person search in real scenes. To tackle this challenge, we draw on Generative Adversarial Networks (GAN) to synthesize data from surveillance videos. GAN has thrived in computer vision problems because it produces high-quality images efficiently. We merely alter the popular Fast R-CNN model, which is capable of processing videos and yielding accurate detection outcomes. In order to appropriately relieve the pressure brought by the two-stage model, we design an Assisted-Identity Query Module (AIDQ) to provide positive images for the behind part. Besides, the proposed novel GAN-based Scene Synthesis model that can synthesize high-quality cross-id person images for person search tasks. In order to facilitate the feature learning of the GAN-based Scene Synthesis model, we adopt an online learning strategy that collaboratively learns the synthesized images and original images. Extensive experiments on two widely used person search benchmarks, CUHK-SYSU and PRW, have shown that our method has achieved great performance, and the extensive ablation study further justifies our GAN-synthetic data can effectively increase the variability of the datasets and be more realistic

Synchronization Reliability Evaluation Method for Mechanisms with Different Time Distribution

Synchronization reliability problems are common in the mechanical field; motion asynchrony will affect the performance or even lead to failure. As action time of mechanisms does not share the identical distribution, the existing synchronization reliability evaluation method has great limitations. Aimed at the problem, a novel synchronization reliability evaluation method is proposed. Starting from two mechanisms, the synchronization reliability of N mechanisms can be obtained with recursive algorithm, where synchronization reliability of the mechanisms is expressed as a multiple integral, through dividing the integral domain into several independent domains, the uncertain integral limits are translated into certain integral limits, and then multiple integral can be solved. The numerical examples show that errors between the proposed methods and the MC simulation are very small, which proved that the methods are correct. Finally, synchronization reliability of folding wings is evaluated. The proposed methods make up for the limitations of the existing method and have good versatility

A hybrid prediction approach for enhancing heat transfer efficiency of coal-fired power plant boiler

Predicting future fouling status is a crucial but tough topic in the applications of energy conservation and pollution reduction at coal-fired power plants because of the significant influence that ash slag has on the heat transfer efficiency of boilers in coal-fired power plants. For the prediction of gray areas in heated areas, a hybrid system based on complementary ensemble empirical modal decomposition, gray models, and long short-term memory networks is presented. This is because the time series of ash pollution degrees is not linear and not smooth. Initially, using a complementary ensemble empirical modal decomposition, the original sequence after wavelet threshold denoising is divided into a number of subseries components. The projected values for the cleanliness factor were then generated by superimposing the predictions from the IMF and residual components. The experimental findings support the model’s precision and dependability and demonstrate that the CEEMD-GM-LSTM model does, in fact, perform very well in forecasting the ash situation in the heated zone

Decreased Intracellular pH Induced by Cariporide Differentially Contributes to Human Umbilical Cord-Derived Mesenchymal Stem Cells Differentiation

Background/Aims: Na+/H+ exchanger 1 (NHE1) is an important regulator of intracellular pH (pHi). High pHi is required for cell proliferation and differentiation. Our previous study has proven that the pHi of mesenchymal stem cells is higher than that of normal differentiated cells and similar to tumor cells. NHE1 is highly expressed in both mesenchymal stem cells and tumor cells. Targeted inhibition of NHE1 could induce differentiation of K562 leukemia cells. In the present paper we explored whether inhibition of NHE1 could induce differentiation of mesenchymal stem cells. Methods: MSCs were obtained from human umbilical cord and both the surface phenotype and functional characteristics were analyzed. Selective NHE1 inhibitor cariporide was used to treat human umbilical cord-derived mesenchymal stem cells (hUC-MSCs). The pHi and the differentiation of hUC-MSCs were compared upon cariporide treatment. The putative signaling pathway involved was also explored. Results: The pHi of hUC-MSCs was decreased upon cariporide treatment. Cariporide up-regulated the osteogenic differentiation of hUC-MSCs while the adipogenic differentiation was not affected. For osteogenic differentiation, β-catenin expression was up-regulated upon cariporide treatment. Conclusion: Decreased pHi induced by cariporide differentially contributes to hUC-MSCs differentiation