Emotion lexicon is an important auxiliary resource for text emotion analysis. Previous works mainly focused on positive and negative classification and less on fine-grained emotion classification. Researchers use lexicon-based methods to find that patients with depression express more negative emotions on social media. Emotional characteristics are an effective feature in detecting depression, but the traditional emotion lexicon has limitations in detecting depression and ignores many depression words. Therefore, we build an emotion lexicon for depression to further study the differences between healthy users and patients with depression. The experimental results show that the depression lexicon constructed in this paper is effective and has a better effect of classifying users with depression.

Vehicular cloud (VC) extends cloud computing to vehicles participating in vehicular ad hoc networks, aiming to provide computing and storage services at low cost to vehicles, improve traffic efficiency and safety, ensure real-time services, etc. Due to the highly dynamic nature of VC, it is challenging to efficiently form a dynamic VC securely and anonymously or to securely deliver messages to the dynamic VC without potentially violating the privacy of cloud users. In this paper, we present a concrete secure and privacy-preserving communication scheme for VC establishment and data dissemination. Our scheme allows a group of vehicles that are geographically close to each other to form a VC securely, anonymously and dynamically. This allows vehicle resources to be integrated and shared securely. Once a VC is formed, any cloud user may deliver messages to be securely and anonymously processed in the VC.

Hyperspectral data contains abundant information in spectral domain, which is very useful for mineral classification and geological body mapping. But, due to the lack of labeled data, it is difficult to get an acceptable result by just using the small number of labeled data. We adopt a semi-supervised method called CNN, which can effectively extract inner features of hyperspectral image to classify hyperspectral data. However, with constraint to the size of receptive field, it can hardly get higher level features. We propose dilated CNN for mineral classification of hyperspectral data. At the same size of kernels, dilated CNN has bigger receptive field. At the meanwhile, it can get higher accuracy of classification. We test our model on hyperspectral data at Tianshan area, where is rich in minerals. From the result, we can find that our method can get a great result on the mineral classification task, which can be used for making geological map.

Hyperspectral remote sensing data contains near continuous spectral information of the object, which is very suitable for mineral classification and geologic body mapping. However, the collecting of a lot of labeled hyperspectral data is expensive, time-consuming and labor-intensive. We choose a semi-supervised method to classify hyperspectral data based on a generative adversarial nertwork (GAN), just use a small amount of labeled data, named HSGAN. The GAN is made up of a generator and a discriminator, and the generator generates data similar to the real data so that the discriminator cannot tell if it is real data or generated data. We designed a one-dimensional GAN to extract spectral features from hyperspectral data. Using this method, we test the Tianshan hyperspectral data and use the actual geological map as the ground-truth produced by us. We find that HSGAN still achieves better results than the traditional CNN and SVM.

A tactile sensor based varying contact point manipulation strategy that utilizes the mathematical models based on the assumption of fixed contact points is proposed to manipulate unknown objects with rolling contact for dexterous robot hand. In this strategy, fingertip tactile sensor is utilized to detect contact position and to update the size parameters about the finger end-link when rolling occurs. Experimental results show that the strategy can effectively improve the rolling contact manipulation performance when dexterous robot hand manipulates unknown objects.