Auto-registration of medium and high spatial resolution satellite images by integrating improved SIFT and spatial consistency constraints

Feature-based methods have been developed in the past decades for the registration of optical satellite images. However, it is still a challenging problem to handle well the registration between medium and high spatial resolution images due to the large difference of the spatial structural features and local details for the same objects. In this study, an automated co-registration technique is proposed that integrates an improved SIFT (I-SIFT) and a novel matching strategy called spatial consistency constraints (SCC) to cope with the large difference in spatial resolutions between the image pair. Three constraints on angle, distance, and ratio are introduced to re the initial matching features obtained by I-SIFT. Three groups of experiments were conducted to validate the effectiveness of the proposed method. The experiments used high resolution multispectral and panoramic SPOT 5/6 images and Landsat 5/8 orthorectification images. Experimental results show that the registration error lies in about 1 pixel of high-resolution images and demonstrate that the proposed I-SIFT-SCC approach is suitable for fine registration of optical satellite images from medium spatial resolution to high spatial resolution with resolution ratio up to 6.     

Generating Questions Based on Semi-Automated and End-to-End Neural Network

With the emergence of large-scale knowledge base, how to use triple information to generate natural questions is a key technology in question answering systems. The traditional way of generating questions require a lot of manual intervention and produce lots of noise. To solve these problems, we propose a joint model based on semi-automated model and End-to-End neural network to automatically generate questions. The semi-automated model can generate question templates and real questions combining the knowledge base and center graph. The End-to-End neural network directly sends the knowledge base and real questions to BiLSTM network. Meanwhile, the attention mechanism is utilized in the decoding layer, which makes the triples and generated questions more relevant. Finally, the experimental results on SimpleQuestions demonstrate the effectiveness of the proposed approach.     

炼油废白土在水泥厂燃煤自备电厂中再利用的实践

本项目主要研究和实现了工业废白土在BAYAH燃煤自备电厂中的再利用,实现变废为宝,减少了环境污染,同时为企业创造了一定的经济效益。针对废白土的特性,对燃料输送系统给煤机、皮带机、煤仓、下料溜子和排渣系统进行了改造。通过修改操作规程消除废白土对锅炉运行的影响。     

Anaerobic co-digestion of food waste and FOG with sewage sludge – realising its potential in Ireland

The severe environmental pollution in many countries is caused by indiscriminate discharge of large quantities of food waste (FW), fat oil and grease (FOG) and sewage sludge (SS) to the environment. There are many possible treatment routes, but anaerobic digestion (AD) is now well accepted for treating several kinds of organic wastes. But AD of FW alone presents some operational challenges because of substrates and variability. Anaerobic co-digestion of two or more substrates is better than single substrate digestion. This can use a plant’s unused capacity, in line with the trend to renewable energy. Co-digestion technology, although well established in many European countries, is still in its infancy in Ireland. There are problems with different regulatory arrangements. They should be resolved. The paper reviews anaerobic co-digestion technology is reviewed, with special focus on possible application in Ireland.     

SDN中基于KMOBPSO的高可靠性控制器部署算法

针对SDN中控制器系统的单节点故障问题,兼顾系统成本和系统时延,应用N+1冗余备份模型来提高SDN控制器部署的可靠性,并将其抽象为多目标优化问题.同时,提出了一种融合K-means聚类算法和遗传算子的多目标二进制粒子群算法——KMOBPSO算法,以求解SDN控制器高可靠性部署问题的解.仿真结果表明,所提算法具有求解精度高、分布均匀、沿Pareto前沿面覆盖广的特点,能够显著提高SDN中控制器部署的可靠性.