流场动态可视化平台关键技术与应用

流场模拟是计算机仿真模拟的热点和难点,是展现水流动态变化过程、辅助寻求水流运动变化规律的重要手段。流场可视化技术的应用可以有效提高水流信息表达的直观性与综合性。本文以北江航道水流可视化为例,开发了浏览器/服务器结构的航道水流可视化平台,重点研究了平台中基于图像的流场可视化技术,采用渲染到纹理技术和通用图形处理器计算中的乒乓技术实现了流场可视化的融合,采用基于视点动态渲染的方式有效解决了水流细节层次的表现问题。在北江航道水流可视化应用中流场动态显示效果流畅,运行帧率达60帧左右。该流场可视化实现方法可以为网页端流场可视化实现与应用提供参考。     

Interfacial Proton Supply/Filtration Regulates the Dynamics of Electrocatalytic Nitrogen Reduction Reaction: A Perspective

As a promising energy carrier, ammonia synthesis by electrocatalytic nitrogen reduction reaction (eNRR) is a promising green and low-carbon ammonia synthesis strategy that can replace the traditional Haber–Bosch process. However, the development of eNRR processes is mainly severely constrained by competitive hydrogen evolution reaction (HER), and the corresponding strategies to inhibit this adverse side reaction to obtain high eNRR selectivity are still limited. In addition, for this complex reaction involving gas–liquid–solid three-phase interface and proton/electron transfer, it is great significance to analyze and summarize the existing inhibition HER strategies from the viewpoint of dynamics. In view of this, this work reviews proton supply/filtration regulation strategy in catalytic system, allowing a systematic survey of the literature focusing on interface membrane regulation (inorganic membrane and organic membrane), electrolyte regulation (metal-mediated strategy and electrolyte ion regulation strategy) and system device design (electrode structure design and electrolytic cell device design). Constructive catalytic system design guidance is also suggested to inhibit hydrogen evolution and improve NH₃ selectivity, aiming for scalable and economically feasible applications.     

Semantic Plane-Structure based motion detection with a nonstationary camera

This paper presents a novel method to accurately detect moving objects from a video sequence captured using a nonstationary camera. Although common methods provide effective motion detection for static backgrounds or through only planar-perspective transformation, many detection errors occur when the background contains complex dynamic interferences or the camera undergoes unknown motions. To solve this problem, this study proposed a motion detection method that incorporates temporal motion and spatial structure. In the proposed method, first, spatial semantic planes are segmented, and image registration based on stable background planes is applied to overcome the interferences of the foreground and dynamic background. Thus, the estimated dense temporal motion ensures that small moving objects are not missed. Second, motion pixels are mapped on semantic planes, and then, the spatial distribution constraints of motion pixels, regional shapes and plane semantics, which are integrated into a planar structure, are used to minimise false positives. Finally, based on the dense temporal motion and spatial structure, moving objects are accurately detected. The experimental results on CDnet dataset, Pbi dataset, Aeroscapes dataset, and other challenging self-captured videos under difficult conditions, such as fast camera movement, large zoom variation, video jitters, and dynamic background, revealed that the proposed method can remove background movements, dynamic interferences, and marginal noises and can effectively obtain complete moving objects.© 2017 ElsevierInc.Allrightsreserved.     

Improvisation of Node Mobility Using Cluster Routing-based Group Adaptive in MANET

In today's Internet routing infrastructure, designers have addressed scaling concerns in routing constrained multiobjective optimization problems examining latency and mobility concerns as a secondary constrain. In tactical Mobile Ad-hoc Network (MANET), hubs can function based on the work plan in various social affairs and the internally connected hubs are almost having the related moving standards where the topology between one and the other are tightly coupled in steady support by considering the touchstone of hubs such as a self-sorted out, self-mending and self-administration. Clustering in the routing process is one of the key aspects to increase MANET performance by coordinating the pathways using multiple criteria and analytics. We present a Group Adaptive Hybrid Routing Algorithm (GAHRA) for gathering portability, which pursues table-driven directing methodology in stable accumulations and on-request steering strategy for versatile situations. Based on this aspect, the research demonstrates an adjustable framework for commuting between the table-driven approach and the on-request approach, with the objectives of enhancing the output of MANET routing computation in each hub. Simulation analysis and replication results reveal that the proposed method is promising than a single well-known existing routing approach and is well-suited for sensitive MANET applications.     

Na3Zr2Si2PO12固态电解质研究进展

钠离子电池具有资源丰富、能量密度高等优点,使用固态电解质的固态钠电池兼具高安全性成为研究热点。固态电解质是超离子导体,是固态电池关键材料。Na₃Zr₂Si₂PO₁₂是钠超离子导体（NASICON）中最具代表性的固态电解质材料。总结了Na₃Zr₂Si₂PO₁₂材料的结构、离子传输机制及其相互关系,旨在从机理上理解Na₃Zr₂Si₂PO₁₂固态电解质中钠离子传输性能;总结了主要制备方法,指出了不同方法的优缺点;在提升离子电导率方面,对合成工艺、掺杂、界面因素进行了总结,力求归纳和探索合成高性能钠离子固态电解质的途径。     

APPCorp: a corpus for Android privacy policy document structure analysis

With the increasing popularity of mobile devices and the wide adoption of mobile Apps, an increasing concern of privacy issues is raised. Privacy policy is identified as a proper medium to indicate the legal terms, such as the general data protection regulation (GDPR), and to bind legal agreement between service providers and users. However, privacy policies are usually long and vague for end users to read and understand. It is thus important to be able to automatically analyze the document structures of privacy policies to assist user understanding. In this work we create a manually labelled corpus containing 231 privacy policies (of more than 566,000 words and 7,748 annotated paragraphs). We benchmark our data corpus with 3 document classification models and achieve more than 82% on F1-score.     

Few-shot node classification via local adaptive discriminant structure learning

Node classification has a wide range of application scenarios such as citation analysis and social network analysis. In many real-world attributed networks, a large portion of classes only contain limited labeled nodes. Most of the existing node classification methods cannot be used for few-shot node classification. To train the model effectively and improve the robustness and reliability of the model with scarce labeled samples, in this paper, we propose a local adaptive discriminant structure learning (LADSL) method for few-shot node classification. LADSL aims to properly represent the nodes in the attributed graphs and learn a metric space with a strong discriminating power by reducing the intra-class variations and enlarging inter-class differences. Extensive experiments conducted on various attributed networks datasets demonstrate that LADSL is superior to the other methods on few-shot node classification task.     

Tariff reduction as a tool to increase the efficiency of electricity distributors: A case study in southern Brazil

The article aims to evaluate the consumer response to a reduction in the electricity tariffs as a hourly economic signal for the case of an electric utility in the state of Rio Grande do Sul, southern Brazil. Using Differences-in-differences method, the results were robust in showing that the change in the economic signal increased up to 81.01% the consumption at the time influenced by the change, improving the way in which the company's assets are used, in addition to reducing fuel oil consumption by users.     

北京冬奥会五环标志塔——延庆“海陀塔”设计

第24届冬奥会在北京成功举办,北京延庆“海陀塔”作为北京冬奥会标志性景观,已成为本届冬奥会的重要文化遗产被永久保留。“海陀塔”的设计为造型与照明一体化设计,使得设计可以综合考虑造型、材料和照明之间的整体关系,并通过技术和工程手段使三个方面得以高度契合、相互辅佐,更好地实现节能理念,塑造设计意象。     

基于复杂结构信息的图神经网络序列推荐算法

图结构因其在序列推荐场景中的自然适应性而备受关注,而现有的基于图神经网络的会话序列推荐算法虽然能够利用图结构信息达到较好的推荐效果,但是没有考虑用户在会话序列中的重复点击行为和项目之间的复杂转换,且未很好地利用图中复杂的结构信息,导致推荐的效果受到一定程度的限制。提出有向与无向信息同注意力相融合的图神经网络序列推荐算法,并基于推荐算法给出项目隐含向量建模算法,结合会话序列图中的有向结构信息与无向结构信息,通过考虑用户的重复点击行为和引入注意力机制建立会话中点击项目的复杂转换模型。图节点在特征传播的过程中平衡邻居节点信息与自身信息的比例,以更准确地预测推荐过程中生成的会话向量。在Diginetica、Yoochoose 1/64、Yoochoose 1/4 3个数据集上的实验结果表明,与SR-GNN、TAGNN算法相比,该算法精度最高提升4.34%,能够更好地预测用户在会话中的下一次点击精度。