This article reviews and summarizes the state-of-the-art methods and publicly available data sets from proximate sensing to support land-use analysis. Discussions highlight the challenges, strategies, and opportunities faced by the existing methods using proximate sensing imagery in urban land-use studies.

This paper investigates a new task, subjectivity word sense disambiguation (SWSD), which is to automatically determine which word instances in a corpus are being used with subjective senses, and which are being used with objective senses.

This article surveys previous work on negation with an emphasis on computational approaches.

This article discusses a bootstrapping method for building subjectivity lexicons for languages with scarce resources.

This article proves that a variant of the Courtois-Finiasz-Sendrier signature is strongly existentially unforgeable under chosen message attack in the random oracle model, assuming hardness of the Permuted Goppa Syndrome Decoding Problem (also known as the Niederreiter problem).

This article uses full-length 16S rRNA gene alignments from the SILVA database to simulate the PCR products of the combined variable regions.

This paper discusses learning multilingual subjective language via cross-lingual projections.

This paper discusses integrating knowledge for subjectivity sense labeling.

Article asserts that Alzheimer’s disease (AD) is a neurodegenerative disease that affects millions of people worldwide. The authors of the article propose two deep learning architectures based on RNN, namely Predicting Progression of Alzheimer’s Disease (PPAD) and PPAD-Autoencoder.

Article discussing a study that was conducted to understand the basis of a bacterial infection that is common among dairy cows.

This article provides a review of the Bayesian-inference-based methods applied to Hepatitis B Virus (HBV), Hepatitis C Virus (HCV), and Human Immunodeficiency Virus (HIV) studies with a focus on the detection of the viral mutations and various problems which are correlated to these mutations. The authors also provide a summary of the Bayesian methods' applications toward these viruses' studies, where several important and useful results have been discovered.