Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.

Vision-based portuguese sign language recognition system

Vision-based hand gesture recognition is an area of active current research in computer vision and machine learning. Being a natural way of human interaction, it is an area where many researchers are working on, with the goal of making human computer interaction (HCI) easier and natural, without the need for any extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them, for example, to convey information. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. Hand gestures are a powerful human communication modality with lots of potential applications and in this context we have sign language recognition, the communication method of deaf people. Sign lan- guages are not standard and universal and the grammars differ from country to coun- try. In this paper, a real-time system able to interpret the Portuguese Sign Language is presented and described. Experiments showed that the system was able to reliably recognize the vowels in real-time, with an accuracy of 99.4% with one dataset of fea- tures and an accuracy of 99.6% with a second dataset of features. Although the im- plemented solution was only trained to recognize the vowels, it is easily extended to recognize the rest of the alphabet, being a solid foundation for the development of any vision-based sign language recognition user interface system.

Mechanical performance of natural fiber-reinforced composites for the strengthening of masonry

The growing concerns regarding the environmental impact generated by the use of inorganic materials in different fields of application increased the interest towards products based on materials with low environmental impact. In recent years, researchers have turned their attention towards the development of materials obtained from renewable sources, easily recoverable or biodegradable at the end of use. In the field of civil structures, a few attempts have been done to replace the most common composites (e.g. carbon and glass fibers) by materials less harmful to the environment, as natural fibers. This work presents a comprehensive experimental research on the mechanical performance of natural fibers for the strengthening of masonry constructions. Flax, hemp, jute, sisal and coir fibers have been investigated both from physical and mechanical points of view. The fibers with better performance were tested together with three different matrices (two of organic nature) in order to produce composites. These experimental results represent a useful database for understanding the potentialities of natural fibers as strengthening systems.

Digital manipulatives as scaffolds for preschoolers’ language development

The study reported here aims at contributing to a deeper understanding of the educational possibilities offered by digital manipulatives in preschool contexts. It presents a study carried with a digital manipulative to enhance the development of lexical knowledge and language awareness, which are relevant language abilities for formal literacy learning. The study took place in a Portuguese preschool, with a class of 20 five-year-olds in collaboration with the teacher. The digital manipulative supported the construction of multiple fictional worlds, motivating children's verbal interactions, and the playing of words and sound games, thus contextualizing the learning of an extensive collection of vocabulary and language awareness abilities. The degree of engagement and involvement that the manipulative provided in supporting children’s imaginative play as well as the imitation, in their own play, of the playful pedagogical interventions that the teacher had designed, shows the importance of well- designed materials that support a child-centered learning model. As such, it sustains a discussion on the potential of digital manipulatives to enhance fundamental language development in the preschool years. Further, the study highlights the importance of multidisciplinary teams in the creation of innovative pedagogical materials.

Properties and thermal behavior of natural deep eutectic solvents

Natural deep eutectic solvents (NADES) have shown to be promising sustainable media for a wide range of applications. Nonetheless, very limited data is available on the properties of these solvents. A more comprehensive body of data on NADES is required for a deeper understanding of these solvents at molecular level, which will undoubtedly foster the development of new applications. NADES based on choline chloride, organic acids, amino acids and sugars were prepared, and their density, thermal behavior, conductivity and polarity were assessed, for different NADES compositions. The NADES studied can be stable up to 170 Â°C, depending on their composition. The thermal characterization revealed that all the NADES are glass formers and some, after water removal, exhibit crystallinity. The morphological characterization of the crystallizable materials was performed using polarized optical microscopy which also provided evidence of homogeneity/phase separation. The conductivity of the NADES was also assessed from 0 to 40 Â°C. The more polar, organic acid-based NADES presented the highest conductivities. The conductivity dependence on temperature was well described by the Vogelâ Fulcherâ Tammann equation for some of the NADES studied.