Research on Key Quality Characteristics of Electromechanical Product Based on Meta-Action Unit

Electromechanical products have many quality characteristics, representing their quality. In addition, there are long-existed quality problems of electromechanical products, such as poor accuracy, short precision life, large fluctuations in performance, frequently failing, and so on. Based on meta-action unit (MU) for electromechanical products, this book chapter proposes a key quality characteristic control method, which provides theoretical and technical support for essentially guaranteeing the complete machine’s quality. The formation mechanisms of MU’s four key quality characteristics (precision, precision life, performance stability, and reliability) are studied. Moreover, we introduce an overview of key quality characteristic control methods based on MU. The complex large system research method of “decomposition-analysis-synthesis” is adopted to study these key science problems

Clinical efficacy of combination of oxaliplatin and vascular intervention in treatment of advanced cervical cancer and related prognostic factors

Purpose: To investigate the therapeutic effect of combination of oxaliplatin and vascular intervention in patients with advanced cervical cancer (ACC), and its influence on the prognosis of patients.Methods: One hundred ACC patients were selected and equally assigned to control (oxaliplatin) and combination or study (oxaliplatin plus vascular intervention) groups. The patients in control group received oxaliplatin, while those in study group were treated with oxaliplatin combined with vascular intervention. Clinical efficacy, levels of vascular endothelial growth factor (VEGF), vascular endothelial growth factor receptor-2 (VEGFR-2), fibroblast growth factor-2 (FGF-2), BFGF and platelet-derived growth factor (PDGF) before and after therapy, and survival rate at 3, 6, 12 and 18 months after therapy were determined compared between the two groups. The prognostic factors were analyzed with logistic factor analysis.Results: The clinical efficacy and survival rate at 3, 6, 12 and 18 months after therapy in the combination group were higher when compared with those of the control group (p < 0.05). After therapy, the levels of VEGF, VEGFR-2, FGF-2, BFGF and PDGF were lower in the combination group than in control group. Age, short-term efficacy and basic diseases were identified as the influencing factors for the prognosis of patients with advanced cervical cancer (p < 0.05).Conclusion: The combination of oxaliplatin and vascular intervention significantly improved clinical treatment efficacy and survival rate in ACC patients. Age, short-term efficacy and basic diseases affected the prognosis of patients

Overviews of Investigation on Submersible Pressure Hulls

With the exploration of natural resources and the research on oceanography in the deep sea obtained more and more attention, in the recent years, the pressure hull of the submersibles has been widely studied and used in many states. In order to the continuing design and assessment on it effectively, the paper summarizes the design method, the structural feature and the material selection of this object

Diverse Knowledge Distillation for End-to-End Person Search

Person search aims to localize and identify a specific person from a gallery of images. Recent methods can be categorized into two groups, i.e., two-step and end-to-end approaches. The former views person search as two independent tasks and achieves dominant results using separately trained person detection and re-identification (Re-ID) models. The latter performs person search in an end-to-end fashion. Although the end-to-end approaches yield higher inference efficiency, they largely lag behind those two-step counterparts in terms of accuracy. In this paper, we argue that the gap between the two kinds of methods is mainly caused by the Re-ID sub-networks of end-to-end methods. To this end, we propose a simple yet strong end-to-end network with diverse knowledge distillation to break the bottleneck. We also design a spatial-invariant augmentation to assist model to be invariant to inaccurate detection results. Experimental results on the CUHK-SYSU and PRW datasets demonstrate the superiority of our method against existing approaches -- it achieves on par accuracy with state-of-the-art two-step methods while maintaining high efficiency due to the single joint model. Code is available at: https://git.io/DKD-PersonSearch.Comment: Accepted to AAAI, 2021. Code is available at: https://git.io/DKD-PersonSearc

A magnetic γ-Fe\u3csub\u3e2\u3c/sub\u3eO\u3csub\u3e3\u3c/sub\u3e@PANI@TiO\u3csub\u3e2\u3c/sub\u3e core–shell nanocomposite for arsenic removal \u3ci\u3evia\u3c/i\u3e a coupled visible-light-induced photocatalytic oxidation– adsorption process†

Arsenic polluted groundwater impairs human health and poses severe threats to drinking water supplies and ecosystems. Hence, an efficient method of simultaneous oxidation of As(III) to As(V), and removal of As(V) from water has triggered increasing attention. In this study, a magnetic γ-Fe2O3 core–shell heterojunction nanocomposite was synthesized by means of hydrothermal crystallization of TiO2 on the surface of the magnetic core–shell loaded with polyaniline (γ-Fe2O3@PANI@TiO2). As an efficient photocatalyst coupled with adsorption, γ-Fe2O3@PANI@TiO2 has a high light utilization and good adsorption capacity. Notably, the nanocomposite has excellent stability at various initial pH values with good reusability. Among the co-existing ions investigated, PO43- has the greatest competitive reaction. The photocatalytic oxidation of As(III) on γ-Fe2O3@PANI@TiO2 is dominated by the synergy of several active substances, with superoxide free radicals and photogenerated holes being the major players

Demonstration of three‐dimensional indoor visible light positioning with multiple photodiodes and reinforcement learning

To provide high‐quality location‐based services in the era of the Internet of Things, visible light positioning (VLP) is considered a promising technology for indoor positioning. In this paper, we study a multi‐photodiodes (multi‐PDs) three‐dimensional (3D) indoor VLP system enhanced by reinforcement learning (RL), which can realize accurate positioning in the 3D space without any off-line training. The basic 3D positioning model is introduced, where without height information of the receiver, the initial height value is first estimated by exploring its relationship with the received signal strength (RSS), and then, the coordinates of the other two dimensions (i.e., X and Y in the horizontal plane) are calculated via trilateration based on the RSS. Two different RL processes, namely RL1 and RL2, are devised to form two methods that further improve horizontal and vertical positioning accuracy, respectively. A combination of RL1 and RL2 as the third proposed method enhances the overall 3D positioning accuracy. The positioning performance of the four presented 3D positioning methods, including the basic model without RL (i.e., Benchmark) and three RL based methods that run on top of the basic model, is evaluated experimentally. Experimental results verify that obviously higher 3D positioning accuracy is achieved by implementing any proposed RL based methods compared with the benchmark. The best performance is obtained when using the third RL based method that runs RL2 and RL1 sequentially. For the testbed that emulates a typical office environment with a height difference between the receiver and the transmitter ranging from 140 cm to 200 cm, an average 3D positioning error of 2.6 cm is reached by the best RL method, demonstrating at least 20% improvement compared to the basic model without performing RL

Conditional Positional Encodings for Vision Transformers

We propose a conditional positional encoding (CPE) scheme for vision Transformers. Unlike previous fixed or learnable positional encodings, which are pre-defined and independent of input tokens, CPE is dynamically generated and conditioned on the local neighborhood of the input tokens. As a result, CPE can easily generalize to the input sequences that are longer than what the model has ever seen during training. Besides, CPE can keep the desired translation-invariance in the image classification task, resulting in improved classification accuracy. CPE can be effortlessly implemented with a simple Position Encoding Generator (PEG), and it can be seamlessly incorporated into the current Transformer framework. Built on PEG, we present Conditional Position encoding Vision Transformer (CPVT). We demonstrate that CPVT has visually similar attention maps compared to those with learned positional encodings. Benefit from the conditional positional encoding scheme, we obtain state-of-the-art results on the ImageNet classification task compared with vision Transformers to date. Our code will be made available at https://github.com/Meituan-AutoML/CPVT .Comment: A general purpose conditional position encoding for vision transformer