A simple approach to solving the kinematics of the 4-UPS/PS (3R1T) parallel manipulator

Journal of Mechanical Science and Technology - This work reports on the position, velocity and acceleration analyses of a four-degrees-of-freedom parallel manipulator, 4-DoF-PM for brevity, which...     

Occupational therapy for people with physical disability using interactive environments

Universal Access in the Information Society - This paper preconizes the use of interactive environments as an accessible and inexpensive solution that allows supporting the recovery process of...     

A deep learning approach for the forensic evaluation of sexual assault

Despite the existence of patterns able to discriminate between consensual and non-consensual intercourse, the relevance of genital lesions in the corroboration of a legal rape complaint is currently under debate in many countries. The testimony of the physicians when assessing these lesions has been questioned in court due to several factors (e.g., a lack of comprehensive knowledge of lesions, wide spectrum of background area, among others). Therefore, it is relevant to provide automated tools to support the decision process in an objective manner. In this work, we evaluate the performance of state-of-the-art deep learning architectures for the forensic assessment of sexual assault. We propose a deep architecture and learning strategy to tackle the class imbalance on deep learning using ranking. The proposed methodologies achieved the best results when compared with handcrafted feature engineering and with other deep architectures.     

Smart Collaborative Mobile System for Taking Care of Disabled and Elderly People

Official statistics data show that in many countries the population is aging. In addition, there are several illnesses and disabilities that also affect a small sector of the population. In recent years, researchers and medical foundations are working in order to develop systems based on new technologies and enhance the quality of life of them. One of the cheapest ways is to take advantage of the features provided by the smartphones. Nowadays, the development of reduced size smartphones, but with high processing capacity, has increased dramatically. We can take profit of the sensors placed in smartphones in order to monitor disabled and elderly people. In this paper, we propose a smart collaborative system based on the sensors embedded in mobile devices, which permit us to monitor the status of a person based on what is happening in the environment, but comparing and taking decisions based on what is happening to its neighbors. The proposed protocol for the mobile ad hoc network and the smart system algorithm are described in detail. We provide some measurements showing the decisions taken for several common cases and we also show the performance of our proposal when there is a medium size group of disabled or elderly people. Our proposal can also be applied to take care of children in several situations.     

Modeling offenses among motorcyclists involved in crashes in Spain

In relative terms, Spanish motorcyclists are more likely to be involved in crashes than other drivers and this tendency is constantly increasing. The objective of this study is to identify the factors that are related to being an offender in motorcycle accidents. A binary logit model is used to differentiate between offender and non-offender motorcyclists. A motorcyclist was considered to be offender when s/he had committed at least one traffic offense at the moment previous to the crash. The analysis is based on the official accident database of the Spanish general directorate of traffic (DGT) for the 2003–2008 time period. A number of explanatory variables including motorcyclist characteristics and environmental factors have been evaluated. The results suggest that inexperienced, older females, not using helmets, absent-minded and non-fatigued riders are more likely to be offenders. Moreover, riding during the night, on weekends, for leisure purposes and along roads in perfect condition, mainly on curves, predict offenses among motorcyclists. The findings of this study are expected to be useful in developing traffic policy decisions in order to improve motorcyclist safety.     

Effect of raspberry pomace extracts isolated by high pressure extraction on the quality and shelf‐life of beef burgers

Raspberry pomace extracts isolated with supercritical carbon dioxide (SCE) and pressurised ethanol/water (ETE) were tested in beef burgers. Only ETE additives effectively inhibited lipid oxidation and the growth of microorganisms, as it was observed by measuring the changes of thiobarbituric acid reactive substances, bacterial counts and the content of O₂ and CO₂ during storage in the modified atmosphere package. ETE additives also demonstrated some meat colour preservation effects, which were assessed by the intensity of hamburger colour and metmyoglobin concentration. However, ETE additives did not alter burger's taste at the applied concentrations (up to 1%). It may be concluded that the most effective extracts possessing strong antioxidant and antimicrobial activity may be isolated from raspberry pomace by the pressurised liquid extraction with a hydroethanolic solvent; such extracts may be considered as promising additives in meat products for improving their stability and enriching with beneficial to health phytochemicals.