A graph-based semi-supervised approach to classification learning in digital geographies

As the distinction between online and physical spaces rapidly degrades, social media have now become an integral component of how many people's everyday experiences are mediated. As such, increasing interest has emerged in exploring how the content shared through those online platforms comes to contribute to the collaborative creation of places in physical space at the urban scale. Exploring digital geographies of social media data using methods such as qualitative coding (i.e., content labelling) is a flexible but complex task, commonly limited to small samples due to its impracticality over large datasets. In this paper, we propose a new tool for studies in digital geographies, bridging qualitative and quantitative approaches, able to learn a set of arbitrary labels (qualitative codes) on a small, manually-created sample and apply the same labels on a larger set. We introduce a semi-supervised, deep neural network approach to classify geo-located social media posts based on their textual and image content, as well as geographical and temporal aspects. Our innovative approach is rooted in our understanding of social media posts as augmentations of the time-space configurations that places are, and it comprises a stacked multi-modal autoencoder neural network to create joint representations of text and images, and a spatio-temporal graph convolution neural network for semi-supervised classification. The results presented in this paper show that our approach performs the classification of social media content with higher accuracy than traditional machine learning models as well as two state-of-art deep learning frameworks.     

A band selection approach based on wavelet support vector machine ensemble model and membrane whale optimization algorithm for hyperspectral image

Applied Intelligence - Hyperspectral Image (HSI) has become one of the important remote sensing sources for object interpretation by its abundant band information. Among them, band selection is...     

BFO optimized RLS algorithm for power system harmonics estimation

In this paper a new estimation approach combining both Recursive Least Square (RLS) and Bacterial Foraging Optimization (BFO) is developed for accurate estimation of harmonics in distorted power system signals. The proposed RLS–BFO hybrid technique has been employed for estimating the fundamental as well as harmonic components present in power system voltage/current waveforms. The basic foraging strategy is made adaptive by using RLS that sequentially updates the unknown parameters of the signal. Simulation and experimental studies are included justifying the improvement in performance of this new estimation algorithm.     

3DGIS环境下雨雪天气实时仿真

3D GIS最重要的特征之一就是虚拟现实表现,其本质是可视化技术与GIS数据库的整合,以满足各种应用如生态农业、灾害预测等方面的需求。以GIS数据库的环境数据和气象数据为基础,通过对雨雪的效果模拟,将GIS气象数据以实时的可视化形式逼真地表现出来。实验方法采用粒子系统,对单个点元赋予利用Photoshop制作的大面积纹理,这样采用的粒子数减少到普通粒子系统的十分之一,渲染速度为普通粒子系统的十倍以上,以较小的系统资源消耗达到了更加实时逼真的效果,对雪的动态堆积和雨水地面效果采用GPU加速3维渲染,原型系统同时能接受用户对实验环境如粒子纹理、雨雪量的设置。提出根据气象数据进行天气模拟的自适应策略,从而更加适应实际应用需要。     

氮在钌单晶表面Ru(0001)上的吸附

钌系氨合成催化剂作为第二代氨合成催化剂,近年来日益受到重视。研究氮分子在钌表面上的离解吸附对提高钌催化剂的催化性能有着十分重要的意义。综述了氮分子在Ru(0001)单晶表面吸附的研究进展，并指出钌催化剂的发展方向。     

无水硫酸氢钾催化合成3-烷氧基噻吩

以CuBr为催化剂,N-甲基-2-吡咯烷酮为溶剂,在110℃用3-溴噻吩与过量的甲醇钠进行取代反应合成3-甲氧基噻吩,收率为82.3%。再以无水KHSO4为催化剂,3-甲氧基噻吩分别与乙醇、丙醇、丁醇、戊醇、己醇和辛醇在105~115℃反应2.5、2.5、3、3.5、3.5和3.5h,合成了3-乙氧基噻吩、3-丙氧基噻吩、3-丁氧基噻吩、3-戊氧基噻吩、3-己氧基噻吩和3-辛氧基噻吩,收率分别为75.8%、73.5%7、0.4%、68.7%、66.3%、55.3%。这些化合物结构都通过IR1、HNMR和MS进行了表征,还进行了初步香味评价。结果表明它们都具有基本肉香味的特征。     

对边缘不突出的显微镜影像进行边缘特征提取与Hough直线检测

文章主要介绍如何对边缘不突出的显微镜进行边缘特征提取与Hough直线检测,其中涉及到数字图像处理中的边缘检测、图像二值化及Hough直线检测算法。     

Decolorisation and mineralisation of CI Reactive Black 8 by the Fenton and ultrasound/Fenton methods

The effects of pH, ferrous ion and hydrogen peroxide dosage on the decolorisation and mineralisation of CI Reactive Black 8 by the Fenton process with/without ultrasonic irradiation were investigated. It was verified that the presence of ultrasonic irradiation did not enhance the decolorisation of CI Reactive Black 8 significantly by Fenton's reagents, but it enhanced the chemical oxygen demand removal efficiency. The enhancement was more pronounced for lower (<0.89 mm) or higher (>1.78 mm) ferrous ion dosage. The optimal pH for chemical oxygen demand removal was 3.0. Chemical oxygen demand removal efficiency increased with the increasing H₂O₂ dosage and reached the highest level at 5.88 mm, but further increase in H₂O₂ dosage would not increase removal efficiency significantly.     

Commutative encryption and watermarking based on orthogonal decomposition

Commutative Encryption and Watermarking (CEW) is a technology combined with encryption and watermarking, which is used for providing comprehensive security protection for multimedia information. This paper presents a novel CEW scheme based on orthogonal decomposition. Different from current CEW, the proposed CEW not only achieves the integration of encryption and watermarking in the final data but also has no specific restrictions in selecting encryption and watermarking algorithms. Therefore, the proposed CEW possesses higher security and applicability. Experimental results demonstrate that the proposed CEW can keep the performances of selected encryption and watermarking algorithm and show more robustness than other current CEW schemes.