In-process monitoring and prediction of droplet quality in droplet-on-demand liquid metal jetting additive manufacturing using machine learning

Journal of Intelligent Manufacturing - In droplet-on-demand liquid metal jetting (DoD-LMJ) additive manufacturing, complex physical interactions govern the droplet characteristics, such as size,...     

Applying deep learning in football ankle injury for value of high-power magnetic resonance bioimaging evaluation

The Journal of Supercomputing - This study was to evaluate the performance of magnetic resonance imaging (MRI) reconstruction algorithm based on convolutional neural network (CNN) in the diagnosis...     

卫星USB测控副载波同步算法研究

吉林一号卫星测控采用USB测控体制,遥控接收采用FFT+DPLL1+DPLL2的架构,FFT主要实现对载波的粗捕,DPLL1在FFT的基础上实现对载波相位的精跟踪,DPLL2实现副载波的跟踪。对遥控副载波跟踪所用到的数字PLL技术进行了研究,首先给出了载波多普勒折算到副载波上的方法,然后对模拟PLL数字化进行了详细的论述,并设计了遥控副载波同步用的PLL2,对其稳定性、快捕带及快捕时间、捕获带和捕获时间、同步速率等进行了分析和仿真。结果表明,该方法具有捕获时间短、跟踪精度高、稳定性好等特点,易于数字化实现,已成功在吉林一号系列卫星中得到应用。     

Analysis of Critical Factors in Manufacturing by Adopting a Cloud Computing Service

The advantages of a cloud computing service are cost advantages, availability, scalability, flexibility, reduced time to market, and dynamic access to computing resources. Enterprises can improve the successful adoption rate of cloud computing services if they understand the critical factors. To find critical factors, this study first reviewed the literature and established a three-layer hierarchical factor table for adopting a cloud computing service based on the Technology-Organization-Environment framework. Then, a hybrid method that combines two multi-criteria decision-making tools—called the Fuzzy Analytic Network Process method and the concept of VlseKriterijumska Optimizacija I Kompromisno Resenje acceptable advantage—was used to objectively identify critical factors for the adoption of a cloud computing service, replacing the subjective decision of the authors. The results of this study determined five critical factors, namely data access security, information transmission security, senior management support, fallback cloud management, and employee acceptance. Finally, the paper presents the findings and implications of the study.     

三模混合集成小型化滤波器设计

提出了一种基于LC串联单元的三模混合集成小型化滤波器电路拓扑。该电路拓扑具有对称性,主体由4个LC串联单元所构成的“星型”结构组成,能够通过对其并联于地的LC串联单元中元件参数的调节实现对滤波器双零点的自由调节。基于奇偶模分析方法,给出了所提出滤波器拓扑的综合设计方法,并采用基于商业化硅基表贴电容的低成本混合集成技术研制一款具有明显小型化特性的三模多零点带通滤波器。所研制的滤波器仿真与测试结果吻合良好,其中心频率为2.6 GHz,3 dB带宽为1.34 GHz,插入损耗典型值为1.6 dB,能够在4～12 GHz的频带范围内实现30 dB的抑制能力,其面积尺寸为3.2 mm×1.9 mm(0.03λ0×0.02λ0)。     

A Survey on Long-Tailed Visual Recognition

The heavy reliance on data is one of the major reasons that currently limit the development of deep learning. Data quality directly dominates the effect of deep learning models, and the long-tailed distribution is one of the factors affecting data quality. The long-tailed phenomenon is prevalent due to the prevalence of power law in nature. In this case, the performance of deep learning models is often dominated by the head classes while the learning of the tail classes is severely underdeveloped. In order to learn adequately for all classes, many researchers have studied and preliminarily addressed the long-tailed problem. In this survey, we focus on the problems caused by long-tailed data distribution, sort out the representative long-tailed visual recognition datasets and summarize some mainstream long-tailed studies. Specifically, we summarize these studies into ten categories from the perspective of representation learning, and outline the highlights and limitations of each category. Besides, we have studied four quantitative metrics for evaluating the imbalance, and suggest using the Gini coefficient to evaluate the long-tailedness of a dataset. Based on the Gini coefficient, we quantitatively study 20 widely-used and large-scale visual datasets proposed in the last decade, and find that the long-tailed phenomenon is widespread and has not been fully studied. Finally, we provide several future directions for the development of long-tailed learning to provide more ideas for readers.

     

Global contextual guided residual attention network for salient object detection

High-level semantic features and low-level detail features matter for salient object detection in fully convolutional neural networks (FCNs). Further integration of low-level and high-level features increases the ability to map salient object features. In addition, different channels in the same feature are not of equal importance to saliency detection. In this paper, we propose a residual attention learning strategy and a multistage refinement mechanism to gradually refine the coarse prediction in a scale-by-scale manner. First, a global information complementary (GIC) module is designed by integrating low-level detailed features and high-level semantic features. Second, to extract multiscale features of the same layer, a multiscale parallel convolutional (MPC) module is employed. Afterwards, we present a residual attention mechanism module (RAM) to receive the feature maps of adjacent stages, which are from the hybrid feature cascaded aggregation (HFCA) module. The HFCA aims to enhance feature maps, which reduce the loss of spatial details and the impact of varying the shape, scale and position of the object. Finally, we adopt multiscale cross-entropy loss to guide network learning salient features. Experimental results on six benchmark datasets demonstrate that the proposed method significantly outperforms 15 state-of-the-art methods under various evaluation metrics.

     

Fast medical concept normalization for biomedical literature based on stack and index optimized self-attention

Neural Computing and Applications - Medical concept normalization aims to construct a semantic mapping between mentions and concepts and to uniformly represent mentions that belong to the same...     

立体停车位液压系统控制策略及节能控制技术研究

针对目前立体停车位均采用阀控液压动力系统,存在系统效率低、能耗大等问题,将伺服电机直驱定量泵的节能技术应用于立体停车位的液压系统中.采用滑模变结构算法与模糊控制算法相结合的模糊滑模控制算法作为立体停车位各个工况切换的控制策略,相比于工业中常用的模糊PID控制算法,模糊滑模变结构控制能够对系统设定流量需求进行快速响应,在多个工况切换时,波动小、稳定速度快.同时对使用节能技术的立体停车位运行时的功率、能耗及系统效率进行测试,结果表明使用伺服电机直驱定量泵的液压节能系统与使用传统阀控液压系统相比,能耗降低了31.2%,系统效率提高了33.2%,具有较好的节能效果.     

Additional bending moment analysis of the trigeminal universal joint installed by single or twin radial bearing北大核心CSCD

To find out the causes of vibration and noise of the trigeminal universal joint which appeared in the installation and use process, the additional moment distribution with the varies of the input shaft angular and the deflection angle was analyzed. Kinematics diagrams of the trigeminal universal joint when the output shaft installed by single radial bearing or twin radial bearing were established. The system coordinates were established under the two installation ways, and the motion equations were established by the direction cosine matrix tools. It indicated that the trigeminal universal joint installed by the single radial bearing was an approximately isometric speed transmission, and was a constant velocity transmission with twin radial bearing installed. Furthermore, the additional moment component on the input shaft and the output shaft was analyzed under the two installation ways. According to the virtual displacement principle, the additional moment on the tripod universal joint when the output shaft installed by twin radial bearing and single radial bearing were determined. When installed by single radial bearing, the deflection moment exists and the vibration frequency of additional moment was three times of the input shaft as a sine curve. The variation trend of the additional moment was straight up with the increase of deflection angle. When installed by twin radial bearing, the deflection moment was zero and the additional moment increased gradually with the increase of deflection angle but did not fluctuate. The analysis revealed that additional moment existed in the trigeminal universal joint system under both installation ways would produce bending vibration. This study is of great significance to study the causes of vibration and determine the nonlinear dynamics of the system.