Sequential alignment attention model for scene text recognition

Scene text recognition has been a hot research topic in computer vision due to its various applications. The state-of-the-art solutions usually depend on the attention-based encoder-decoder framework that learns the mapping between input images and output sequences in a purely data-driven way. Unfortunately, there often exists severe misalignment between feature areas and text labels in real-world scenarios. To address this problem, this paper proposes a sequential alignment attention model to enhance the alignment between input images and output character sequences. In this model, an attention gated recurrent unit (AGRU) is first devised to distinguish the text and background regions, and further extract the localized features focusing on sequential text regions. Furthermore, CTC guided decoding strategy is integrated into the popular attention-based decoder, which not only helps to boost the convergence of the training but also enhances the well-aligned sequence recognition. Extensive experiments on various benchmarks, including the IIIT5k, SVT, and ICDAR datasets, show that our method substantially outperforms the state-of-the-art methods.     

Digital twin-based analysis of volumetric error mapping procedures

The evaluation of the volumetric accuracy of a machine tool is an open challenge in the industry, and a wide variety of technical solutions are available in the market and at research level. All solutions have advantages and disadvantages concerning which errors can be measured, the achievable uncertainty, the ease of implementation, possibility of machine integration and automation, the equipment cost and the machine occupation time, and it is not always straightforward which option to choose for each application. The need to ensure accuracy during the whole lifetime of the machine and the availability of monitoring systems developed following the Industry 4.0 trend are pushing the development of measurement systems that can be integrated in the machine to perform semi-automatic verification procedures that can be performed frequently by the machine user to monitor the condition of the machine. Calibrated artefact based calibration and verification solutions have an advantage in this field over laser based solutions in terms of cost and feasibility of machine integration, but they need to be optimized for each machine and customer requirements to achieve the required calibration uncertainty and minimize machine occupation time.This paper introduces a digital twin-based methodology to simulate all relevant effects in an artefact-based machine tool calibration procedure, from the machine itself with its expected error ranges, to the artefact geometry and uncertainty, artefact positions in the workspace, probe uncertainty, compensation model, etc. By parameterizing all relevant variables in the design of the calibration procedure, this simulation methodology can be used to analyse the effect of each design variable on the error mapping uncertainty, which is of great help in adapting the procedure to each specific machine and user requirements. The simulation methodology and the analysis possibilities are illustrated by applying it on a 3-axis milling machine tool.     

Differences between oculomotor and perceptual artifacts for temporally limited head mounted displays

We used perceptual and oculomotor measures to understand the negative impacts of low (phantom array) and high (motion blur) duty cycles with a high‐speed, AR‐likehead‐mounted display prototype. We observed large intersubject variability for the detection of phantom array artifacts but a highly consistent and systematic effect on saccadic eye movement targeting during low duty cycle presentations. This adverse effect on saccade endpoints was also related to an increased error rate in a perceptual discrimination task, showing a direct effect of display duty cycle on the perceptual quality. For high duty cycles, the probability of detecting motion blur increased during head movements, and this effect was elevated at lower refresh rates. We did not find an impact of the temporal display characteristics on compensatory eye movements during head motion (e.g., VOR). Together, our results allow us to quantify the tradeoff of different negative spatiotemporal impacts of user movements and make subsequent recommendations for optimized temporal HMD parameters.     

甘肃省陇东地区极端降水的时空特征

为阐明甘肃省陇东地区极端降水的变化规律,利用该地区13个气象台站1961~2015年的逐日降水资料,应用超门限峰值法、反距离加权法、线性倾向估计法、滑动平均法、Mann-Kendall突变分析法、复值Morlet小波分析法研究极端降水的时空变化特征。结果表明,陇东地区各站第95百分位极端降水阈值在27.8mm附近变化,即可以大雨事件作为极端降水事件进行监测;极端降水指数主要表现为从南向北递减的趋势,极端降水事件对环县和崆峒的影响较小;极端降水事件虽然在总量、强度上表现为减小趋势,但其发生频次及对总降水的贡献率逐渐增强;极端降水总量和极端降水强度周期变化均在21年左右能量最强,而极端降水频次和极端降水贡献率周期变化分别在28、5年左右能量最强。     

基于高分一号遥感卫星的渤海湾悬浮泥沙时空分布反演

悬浮泥沙是评价II类水体水质的重要参数之一,近海岸水域悬浮泥沙对重金属、营养盐等具有一定的吸附作用,悬浮泥沙的分布特征在一定程度上反映着污染物的迁移和循环,因此研究悬浮泥沙对渤海湾建设和环境保护具有重要意义。为探究渤海湾水域悬浮泥沙浓度 和分布的变化特征,利用高分一号多光谱卫星影像,通过采用波段组合的方式对悬浮泥沙含量指数反演提取,反演得到2019年9个月的渤海湾悬浮泥沙指数,分析发现渤海湾悬浮泥沙含量在冬季受季风影响较高,春季和夏季的时候渤海湾高浓度悬浮泥沙向近岸收缩,秋季 悬浮泥沙分布格局有正在向冬季过渡的趋势,本文研究可为渤海湾的生态环境保护和工业开发提供重要的科学依据和参考价值。     

ATSP:时态网络可视化的自适应时间片划分方法

现有的时态网络可视化方法大多采用等量时间片来可视化网络的演变，不利于时态模式的快速挖掘和发现。为此，根据时态网络固有的特征提出自适应时间片划分方法（Adaptive Time Slice Partition method，ATSP）。在时态网络的两种表示方式（基于事件的表示方式和基于快照的表示方式）的基础上，构建了ATSP的基础模型，同时提出了一种改进模型用来描述事件间隔时间服从长尾分布的时态网络。为了实现时间片的不等量划分，针对探索任务的不同提出了基于时态模式的ATSP规则和基于中心节点的ATSP规则，并提出了实现算法--层次划分算法（Hierarchical Partition algorithm，HP）和增量划分算法（Incremental Partition algorithm，IP）。实验结果表明，ATSP方法比传统的时间片划分方法更能准确地表示网络的时态特征，且该方法应用于可视化时，能有效归纳并展示网络的特征，明显提高了视觉分析的效率。     

云南镇源难处理金精矿工艺矿物学研究

利用X射线衍射、X射线荧光光谱（XRF）、X射线能谱分析（EDX）和矿物解离分析（MLA）等检测手段对云南镇源难处理金精矿的化学组成、矿物组成、硫化物特征以及金的分布情况进行了详细的工艺矿物学研究。结果显示：该金矿以硫化矿、碳酸盐和硅酸盐类矿物为主，含有3.18%的有机碳和2.37%的无机碳。通过金的诊断浸出发现96.16%的金被硫化物包裹，少量金以单体形式存在。通过对主要载金矿物黄铁矿、辉锑矿和毒砂的粒度、包裹及裸露情况进行分析，得出大部分硫化矿以解离单体的形式存在，少部分与其他矿物共生。根据MLA测试及金的诊断浸出，认为大部分金被硫化矿完全包裹，处理该矿石时应先进行硫化物包裹层的氧化处理，再进行金矿的浸出。     

Study of spatial and temporal evolution of Ar and F atoms in SF6/Ar microsecond pulsed discharge by optical emission spectroscopy

The study of sulfur hexafluoride (SF₆) discharge is vital for its application in gas-insulated equipment. Direct current partial discharge (PD) may cause SF₆ decomposition, and the decomposed products of SF₆, such as F atoms, play a dominant role in the breakdown of insulation systems. In this study, the PD caused by metal protrusion defects is simulated by a needle-plate electrode using pulsed high voltage in SF₆/Ar mixtures. The spatial and temporal characteristics of SF6/Ar plasma are analyzed by measuring the emission spectra of F and Ar atoms, which are important for understanding the characteristics of PD. The spatial resolved results show that both F and Ar atom spectral intensities increase first from the plate anode to the needle and then decrease under the conditions of a background pressure of 400 Pa, peak voltage of −1000 V, frequency of 2 kHz, pulse width of 60 μs, and electrode gap of 5–9 mm. However, the distribution characteristics of F and Ar are significantly different. The temporal distribution results show that the spectral intensity of Ar decreases first and then increases slowly, while the spectral intensity of F increases slowly for the duration of the pulsed discharge at the electrode gap of 5 mm and the pulse width of 40–80 μs.     

Flight control of a hexa-rotor airship: Uncertainty quantification for a range of temperature and pressure conditions

The present paper is concerned with the dynamic modeling and design of control laws for a small non-rigid multi-rotor airship constituted of an oblate-spheroid helium balloon coupled with an electric-powered hexa-rotor airframe. The vehicle is assumed to operate in windless and low-speed conditions. A six-degree-of-freedom nonlinear dynamic model is derived for it using the Newton–Euler approach and considering, among other efforts, a restoring torque due to the displacement of the balloon’s center of buoyancy above the vehicle’s center of mass and the added-mass effect resulting from the air–structure interaction. Using the derived model and assuming a time-scale separation between the translational and rotational dynamics, the attitude and position control laws are designed separately from each other. Both laws are formulated using feedback linearization combined with control input saturation within appropriate parallelepipedal sets, which are carefully chosen to respect pre-defined bounds on the control torque, control force and maximum inclination angle. The effect of temperature and pressure fluctuations is taken into account through a parametric probabilistic approach, where Maximum Entropy Principle is used to construct a physically consistent stochastic model and Monte Carlo method is used as the stochastic solver to propagate the uncertainties through the system. Extensive simulation results show the effectiveness of the proposed control system and quantify the uncertainty of its performance over a wide range of local temperature and pressure.