In this paper, a robust color image encryption system using Lorenz-Rossler chaotic map is
proposed. The proposed encryption system uses hybrid of two chaotic systems namely …

Multilabel text categorization is an important task in modern text mining applications. Text
datasets comprise an excessive number of terms, and this can degrade the accuracy …

Spatio-temporal graphs (STGs) are important structures to describe urban sensory data, eg,
traffic speed and air quality. Predicting over spatio-temporal graphs enables many essential …

Recently, attention-based neural networks (NNs) have been widely used for aspect-level
sentiment classification (ASC). Most neural models focus on incorporating the aspect …

This paper proposes a novel reversible data hiding (RDH) algorithm with differential
compression (DC) in encrypted image, which has high embedding capacity. The key …

Incomplete multi-view clustering is an important technique to deal with real-world incomplete
multi-view data. Previous methods assume that all views have the same incompleteness, ie …

Multimodal data fusion (MMDF) is the process of combining disparate data streams (of
different dimensionality, resolution, type, etc.) to generate information in a form that is more …

Spatio-temporal forecasting has a wide range of applications in smart city efforts, such as
traffic forecasting and air quality prediction. Graph Convolutional Recurrent Neural Networks …

The pantograph–catenary system is crucial to the transmission of electrical power from
catenary lines to electrified trains. The occurrence of arcs could damage or interrupt railway …

A single infrared image or visible image for the same scene is usually insufficient to
simultaneously reveal the infrared objects and the scene details. Thus, image fusion …