Presentation attack detection based on two-stream vision transformers with self-attention fusion

Aiming at the performance degradation of the existing presentation attack detection methods due to the illumination variation, a two-stream vision transformers framework (TSViT) based on transfer learning in two complementary spaces is proposed in this paper. The face images of RGB color space and multi-scale retinex with color restoration (MSRCR) space are fed to TSViT to learn the distinguishing features of presentation attack detection. To effectively fuse features from two sources (RGB color space images and MSRCR images), a feature fusion method based on self-attention is built, which can effectively capture the complementarity of two features. Experiments and analysis on Oulu-NPU, CASIA-MFSD, and Replay-Attack databases show that it outperforms most existing methods in intra-database testing and achieves good generalization performance in cross-database testing.     

A customized low-rank prior model for structured cartoon–texture image decomposition

The mathematical characterization of the texture component plays an instrumental role in image decomposition. In this paper, we are concerned with a low-rank texture prior based cartoon–texture image decomposition model, which utilizes a total variation norm and a global nuclear norm to characterize the cartoon and texture components, respectively. It is promising that our decomposition model is not only extremely simple, but also works perfectly for globally well-patterned images in the sense that the model can recover cleaner texture (or details) than the other novel models. Moreover, such a model can be easily reformulated as a separable convex optimization problem, thereby enjoying a splitting nature so that we can employ a partially parallel splitting method (PPSM) to solve it efficiently. A series of numerical experiments on image restoration demonstrate that PPSM can recover slightly higher quality images than some existing algorithms in terms of taking less iterations or computing time in many cases.     

酸性尾矿废弃地生态修复技术进展

酸性尾矿废弃地废石含有硫化物，在雨水的淋溶作用下会产出硫酸，加剧废弃地的酸化，增加企业环保成本，而生态修复工作就是从源头上控制废弃地的酸化。根据尾矿废弃地酸化机理，结合国内外最新研究进展，分析了生态修复技术现状；概述了隔离覆盖、改良剂改良、植物修复、微生物法等多种处理方法在实践中的适应性及优缺点，并分别介绍了隔离覆盖-植物修复技术、原位改良-植物修复技术在Reden煤矿、永平铜矿的成功应用案例。针对酸性尾矿废弃地的特点，单一处理方法具有较大的局限性，需要采用联合工艺进行治理，隔离覆盖-植物修复技术、原位改良-植物修复技术因见效快、效果好、操作简单，势必成为将来研究的主要方向。     

Application of fuzzy image restoration in criminal investigation

The advancement of science and technology has a positive effect on the development of law disciplines. The development of algorithms and artificial intelligence also has a certain impact on judicial practice. Image restoration is a significant technique in image processing. It aims to objectively restore the content or quality of the original image from the degraded image. Image degradation is always generated in image transmission, such as distortion, blur. In modern video surveillance system, image restoration is significant for criminal investigation. However, image restoration based on conventional filter algorithms cannot achieve satisfactory performance. Thus, we first introduce the image restoration algorithms based on different degradation model. Then, we propose some applications of fuzzy image restoration in criminal investigation. We conduct experiments on both degraded images and videos and experimental results have shown the effectiveness of fuzzy image restoration applying to the criminal investigation.     

自适应融合层级特征的混合退化图像复原算法

多种退化类型混合的图像比单一类型的退化图像降质更严重,很难建立精确模型对其复原,研究端到端的神经网络算法是复原的关键.现有的基于操作选择注意力网络的算法(operation-wiseattentionnetwork,OWAN)虽然有一定的性能提升,但是其网络过于复杂,运行较慢,复原图像缺乏高频细节,整体效果也有提升的空间.针对这些问题,提出一种基于层级特征融合的自适应复原算法.该算法直接融合不同感受野分支的特征,增强复原图像的结构;用注意力机制对不同层级的特征进行动态融合,增加模型的自适应性,降低了模型冗余;另外,结合L1损失和感知损失,增强了复原图像的视觉感知效果.在DIV2K,BSD500等数据集上的实验结果表明,该算法无论是在峰值信噪比和结构相似性上的定量分析,还是在主观视觉质量方面,均优于OWAN算法,充分证明了该算法的有效性.     

新时代背景下铀矿绿色勘查技术体系研究*

实施铀矿绿色勘查是新时代生态文明战略背景下全新的勘查模式，也是保障国家安全和能源安全的必然要求。将绿色理念引入铀矿资源勘查中，对铀矿地质勘查的目的、原则、理念、技术手段和工作流程进行了创新，以最少的环境付出和经济成本获取更好的勘查成果和地质信息。在完善铀矿勘查理论体系的基础上，引入“创新、协调、绿色、开放、共享”的发展理念，参照现行的勘查标准选择合适的工程技术，形成了由成矿理论、勘查技术、勘查标准、环境恢复和勘查评价等5个方面构成的铀矿绿色勘查技术体系。     

Transmission system restoration with co-optimization of repairs,load pickups,and generation dispatch

This paper studies the restoration of a transmission system after a significant disruption such as a natural disaster. It considers the co-optimization of repairs, load pickups, and generation dispatch to produce a sequencing of the repairs that minimizes the size of the blackout over time. The core of this process is a Restoration Ordering Problem (ROP), a non-convex mixed-integer nonlinear program that is outside the capabilities of existing solver technologies. To address this computational barrier, the paper examines two approximations of the power flow equations: The DC model and the recently proposed LPAC model. Systematic, large-scale testing indicates that the DC model is not sufficiently accurate for solving the ROP. In contrast, the LPAC power flow model, which captures line losses, reactive power, and voltage magnitudes, is sufficiently accurate to obtain restoration plans that can be converted into AC-feasible power flows. An experimental study also suggests that the LPAC model provides a robust and appealing tradeoff between accuracy and computational performance for solving the ROP.     

城市河流系统治理策略在鹅颈水生态修复中的应用

在简要介绍城市河流系统治理策略的基础上，详细论述其在鹅颈水生态修复中的应用。鹅颈水治理以流域为空间单位，准确把握河流主要问题，综合考量水资源、水安全、水环境、水生态、水文化，坚持工程和非工程措施并重，分阶段逐步实现洪水风险管理、外源污染控制、河流水质修复、河流生态系统恢复的目标。结果表明，鹅颈水目前已基本消除黑臭，水质逐渐提升至国家地表水Ⅳ类水标准。提出进一步加强河流生态系统恢复、优化管理制度、逐步建立全过程和全指标生态监测评估体系、实施弹性管理等鹅颈水系统治理措施。     

Group decision support system for backbone-network reconfiguration

Modern power system is unprecedentedly vulnerable and the society is exposed to higher blackout risks. Therefore restoration is a key issue to power systems. Reasonable backbone-network reconfiguration is necessary for re-establishing the network and restoring loads quickly. In order to speed up network reconfiguration under security constraints, a group decision support system (GDSS) is developed. A unified data platform based on data warehouse is constructed to resolve inconsistencies of data, information and models. A three-stage restoration strategy and a two-layer restoration path searching method are proposed to establish restoration schemes. Multiple attribute decision-making is implemented to evaluate alternatives and consider various attributes about restoration speed and system security comprehensively. Group decision-making provides an aggregated cardinal ranking of candidate restoration schemes. The GDSS uses expert rules for qualitative analysis and numerical computation programs for quantitative analysis, and it can resolve the semi-structured decision problem of network reconfiguration efficiently. Restoration plan of Shandong power grid is developed with the proposed method and it has been adopted by State Grid Shandong Electric Power Company. Performance results of Shandong power grid of China demonstrate the feasibility and flexibility of the method.