Air-Writing Character Recognition with Ultrasonic Transceivers.

The interfaces between users and systems are evolving into a more natural communication, including user gestures as part of the interaction, where air-writing is an emerging application for this purpose. The aim of this work is to propose a new air-writing system based on only one array of ultrasonic transceivers. This track will be obtained based on the pairwise distance of the hand marker with each transceiver. After acquiring the track, different deep learning algorithms, such as long short-term memory (LSTM), convolutional neural networks (CNN), convolutional autoencoder (ConvAutoencoder), and convolutional LSTM have been evaluated for character recognition. It has been shown how these algorithms provide high accuracy, where the best result is extracted from the ConvLSTM, with 99.51% accuracy and 71.01 milliseconds of latency. Real data were used in this work to evaluate the proposed system in a real scenario to demonstrate its high performance regarding data acquisition and classification.

Object Positioning Algorithm Based on Multidimensional Scaling and Optimization for Synthetic Gesture Data Generation.

This work studies the feasibility of a novel two-step algorithm for infrastructure and object positioning, using pairwise distances. The proposal is based on the optimization algorithms, Scaling-by-Majorizing-a-Complicated-Function and the Limited-Memory-Broyden-Fletcher-Goldfarb-Shannon. A qualitative evaluation of these algorithms is performed for 3D positioning. As the final stage, smoothing filtering techniques are applied to estimate the trajectory, from the previously obtained positions. This approach can also be used as a synthetic gesture data generator framework. This framework is independent from the hardware and can be used to simulate the estimation of trajectories from noisy distances gathered with a large range of sensors by modifying the noise properties of the initial distances. The framework is validated, using a system of ultrasound transceivers. The results show this framework to be an efficient and simple positioning and filtering approach, accurately reconstructing the real path followed by the mobile object while maintaining low latency. Furthermore, these capabilities can be exploited by using the proposed algorithms for synthetic data generation, as demonstrated in this work, where synthetic ultrasound gesture data are generated.

Genotoxic effects of environmental exposure to arsenic and lead on children in region Lagunera, Mexico.

DNA damage and DNA repair ability by means of the comet assay and the hydrogen peroxide challenge in lymphocytes from 65 children exposed simultaneously to As and Pb in Region Lagunera, Mexico. The first exposure scenario was concerned with natural As contamination in drinking water affecting all children, particularly those attending the schools farthest from (Gomez Palacio) and closest to the smelter (Pedro Garcia). The second scenario related to additional Pb and As soil and dust contamination in the schools located in the smelter vicinity (Heroe de Nacozari and Pedro Garcia). Most children (93%) had As in urine (AsU) above 50 microg/L and 65% had blood Pb (PbB) above 10 microg/dL. The highest AsU median levels were observed in the school farthest from the smelter, whereas the highest PbB values were observed in the closest school. DNA damage and a decreased repair ability observed in children attending the schools were more severe than those reported for healthy Mexican children. However, the multivariate analysis did not show significant associations between DNA basal damage and PbB or AsU. Lymphocytes from 58% of the children did not respond to the peroxide challenge, and those had a more severe basal DNA damage. DNA repair capacity showed a slowed response and was negatively associated with AsU. Thus, in addition to reduced exposure, further studies are needed to ascertain if the deficiency in DNA repair is transient or if children are already displaying a mutator phenotype and are at risk of developing cancer.