ReadingAct RGB-D action dataset and human action recognition from local features

For general home monitoring, a system should automatically interpret people’s actions. The system should be non-intrusive, and able to deal with a cluttered background, and loose clothes. An approach based on spatio-temporal local features and a Bag-of-Words (BoW) model is proposed for single-person action recognition from combined intensity and depth images. To restore the temporal structure lost in the traditional BoW method, a dynamic time alignment technique with temporal binning is applied in this work, which has not been previously implemented in the literature for human action recognition on depth imagery. A novel human action dataset with depth data has been created using two Microsoft Kinect sensors. The ReadingAct dataset contains 20 subjects and 19 actions for a total of 2340 videos. To investigate the effect of using depth images and the proposed method, testing was conducted on three depth datasets, and the proposed method was compared to traditional Bag-of-Words methods. Results showed that the proposed method improves recognition accuracy when adding depth to the conventional intensity data, and has advantages when dealing with long actions.

Optical sensors for monitoring water uptake in plants

The monitoring of water uptake in plants is becoming increasingly important. Optical sensors offer considerable advantages over conventional methods and several sensors have been developed including an optical potometer that monitors water uptake from individual roots, the detection of xylem cavitation using audio acoustic emissions with an interferometric force feedback microphone, and an optical fiber displacement transducer that detects changes in leaf thickness in relation to leaf-water potential.

Metalloporphyrin anion sensors: the effect of the metal centre on the anion binding properties of amide-functionalised and tetraphenyl metalloporphyrins

This article describes the synthesis and anion binding properties of a series of ‘picket fence’ metalloporphyrin complexes, within which the metal centre is systematically varied. The porphyrin structure contains four amide bonds and is the same for each metal. The anion binding properties of these receptors are further contrasted with those of their tetraphenylporphyrin congeners to elucidate both the effect of the metal centre and the influence of the amide groups on the anion recognition process. Anion binding was demonstrated using UV/visible and 1H NMR spectroscopies, electrochemistry and luminescence. The metal centre was found to be highly influential in the strength and selectivity of binding; for example, the cadmium and mercury complexes exhibited far greater affinities for anions than the zinc complexes in competitive solvents such as DMSO. The amide functionalities were found to enhance the anion binding process.

Sensors and the city: a review of urban meteorological networks

The heterogeneous nature of urban environments means that atmospheric research ideally requires a dense network of sensors to adequately resolve the local climate. With recent advances in sensor technology, a number of urban meteorological networks now exist with a range of research or operational objectives. This article reviews and assesses the current status of urban meteorological networks, by examining the fundamental scientific and logistical issues related to these networks. The article concludes by making recommendations for future deployments based on the challenges encountered by existing networks, including the need for better reporting and documentation of network characteristics, standardized approaches and guidelines, along with the need to overcome financial barriers via collaborative relationships in order to establish the long-term urban networks essential for advancing urban climate research. Copyright © 2013 Royal Meteorological Society