Confidentiality in medical images through a genetic-based steganography algorithm in artificial intelligence.

Nowadays, image steganography has an important role in hiding information in advanced applications, such as medical image communication, confidential communication and secret data storing, protection of data alteration, access control system for digital content distribution and media database systems. In these applications, one of the most important aspects is to hide information in a cover image whithout suffering any alteration. Currently, all existing approaches used to hide a secret message in a cover image produce some level of distortion in this image. Although these levels of distortion present acceptable PSNR values, this causes minimal visual degradation that can be detected by steganalysis techniques. In this work, we propose a steganographic method based on a genetic algorithm to improve the PSNR level reduction. To achieve this aim, the proposed algorithm requires a private key composed of two values. The first value serves as a seed to generate the random values required on the genetic algorithm, and the second value represents the sequence of bit locations of the secret medical image within the cover image. At least the seed must be shared by a secure communication channel. The results demonstrate that the proposed method exhibits higher capacity in terms of PNSR level compared with existing works.

A biologically inspired spiking neural P system in selective visual attention for efficient feature extraction from human motion.

Nowadays, human action recognition has become an essential task in health care and other fields. During the last decade, several authors have developed algorithms for human activity detection and recognition by exploiting at the maximum the high-performance computing devices to improve the quality and efficiency of their results. However, in real-time and practical human action recognition applications, the simulation of these algorithms exceed the capacity of current computer systems by considering several factors, such as camera movement, complex scene and occlusion. One potential solution to decrease the computational complexity in the human action detection and recognition can be found in the nature of the human visual perception. Specifically, this process is called selective visual attention. Inspired by this neural phenomena, we propose for the first time a spiking neural P system for efficient feature extraction from human motion. Specifically, we propose this neural structure to carry out a pre-processing stage since many studies have revealed that an analysis of visual information of the human brain proceeds in a sequence of operations, in which each one is applied to a specific location or locations. In this way, this specialized processing have allowed to focus the recognition of the objects in a simpler manner. To create a compact and high speed spiking neural P system, we use their cutting-edge variants, such as rules on the synapses, communication on request and astrocyte-like control. Our results have demonstrated that the use of the proposed neural P system increases significantly the performance of low-computational complexity neural classifiers up to more 97% in the human action recognition.

Physical demands of para-footballers with cerebral palsy in a small-sided game.

BACKGROUND: Cerebral palsy (CP) Football is a para-sport performed by individuals with physical impairments of athetosis, ataxia, or hypertonia. However, little is known about the physical demands of para-footballers with CP, and no previous study has analysed those demands in a small-sided game (SSG). This study aims to describe physical parameters using a global positioning system device in a SSG played by CP football players. METHODS: Fourteen male international para-footballers with CP took part in this study, which analysed their performance in an SSG of 3 vs. 3 players plus a goalkeeper per team. Also, a group of 12 football players participated as a control group. RESULTS: The total distance covered by the CP footballers during the SSG was 1931.1±213.6 m, and the distance covered per minute was 71.2±9.3 m/min, having lower scores than the control group. The maximum speed reached was 20.1±1.8 km/h, with a metabolic power of 6.2±0.9 W/kg and lower scores than the control group. Players with the minimal eligible impairment in this para-sport (i.e., sport class FT8) covered a greater distance in high-speed zones compared to players with more severe impairments. CONCLUSIONS: This study demonstrated that para-footballers with CP exhibited lower physical performance in an SSG compared to regular football players. Additional studies are necessary to identify the best format of an SSG for football players with CP and its application for training and evidence-based classification.

Aula Verde: art as experience in community-based environmental education.

After winning a class-action lawsuit against unconstitutional prison conditions in Puerto Rico, Marco Abarca managed to direct part of the fine monies accumulated throughout years of litigation toward an investment that would improve the living conditions in one of the largest and poorest housing projects in Puerto Rico. With the participation of parolees and probationers, he began to transform a mosquito-infested badland into a natural haven. Then, with the help of science educators, the group designed a workshop for elementary school children on urban ecology. As the participants organized, what developed was a community-based, self-employed enterprise known as Aula Verde.