9 resultados para 280105 Interfaces and Presentation (excl. Computer-Human Interaction)

em Universidade do Minho


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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.

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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 humancomputer 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 vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM 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.

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High-risk human papillomavirus (hrHPV) is an essential cause of cervical carcinoma and is also strongly related to anal cancer development. The hrHPV E6 oncoprotein plays a major role in carcinogenesis. We aimed to evaluate the frequency of hrHPV DNA and E6 oncoprotein in the anuses of women with cervical carcinoma. We analyzed 117 women with cervical cancer and 103 controls for hrHPV and the E6 oncogene. Positive test results for a cervical carcinoma included 66.7 % with hrHPV-16 and 7.7 % with hrHPV-18. One case tested positive for both HPV variants (0.9 %). The samples from the anal canal were positive for HPV-16 in 59.8 % of the cases. Simultaneous presence of HPV in the cervix and anal canal was found in 53.8 % of the cases. Regarding expression of E6 RNA, positivity for HPV-16 in the anal canal was found in 21.2 % of the cases, positivity for HPV-16 in the cervix was found in 75.0 %, and positivity for HPV-18 in the cervix was found in 1.9 %. E6 expression in both the cervix and anal canal was found in 19.2 % of the cases. In the controls, 1 % tested positive for HPV-16 and 0 % for HPV-18. Anal samples from the controls showed a hrHPV frequency of 4.9 % (only HPV16). The presence of hrHPV in the anal canal of women with cervical cancer was detected at a high frequency. We also detected E6 RNA expression in the anal canal of women with cervical cancer, suggesting that these women are at risk for anal hrHPV infection.

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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.

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The present paper investigates the risks that arise from exposure to noise from powerpoles and powerlines in Serzedelo, in the municipality of Guimarães, in Portugal. This research focused on four guiding questions: Can powerlines cause noise? Do powerlines cause discomfort? Do powerlines cause discomfort due to noise? And can powerlines effect human health? Two groups were the basis of the study: people that were exposed to electromagnetic waves and people that were not. the research pointed to the harmful influence of the presence of powerlines and high-voltage masts in residential areas and the damage to the cells in the human body. This type of environmental noise, which has the spectral content of a low frequency, typically tonal noise and a very high speed of propagation, is a complex source to explain in terms of the health profiles of the human population living in Serzedelo, located in an area that is densely occupied by high voltage powerlines and powerpole.

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Currently in Portugal academic excellence in higher education is given recognition through merit prizes. Because honours students can be seen as having the potential to achieve imporant levels of professional expertise, especially if they have some personal skills, it is important to know not only the marks of the students but also the personal characteristics that contribute to academic success and which may also be important for career success. Some theoretical models of giftedness and excellence agree with this idea and this work considers the latest contribution of Renzulli (2005) where it is pointed out that excellent achievements result from the combination of motivational, intellectual and creative factors as well as from co-cognitive factors which are most associated with personality functioning in a particular context. The main purpose of this paper is to analyze how honours students differ from their classmates in various psychological dimensions: Cognition-creativity, Motivation and Learning Strategies, Persistence, Social Interaction, Drive for Excellence and Cultural Interest. These dimensions were measured by the Inventory of Psychological Characteristics Associated with Academic Performance (ICPADA), which was constructed taking into consideration the previous study of Scaeger et al. (2012). The sample included 914 Portuguese higher educatoin students from a first cycle degree in the Bologna process. Participants were selected from three different fields of study: Social and Human Sciences; Science and Technology; Arts and Humanities. The data collected through the administration of the ICPADA was presented, and the results revealed a higher self-perception by honours students in all areas analyzed, with the exception of the dimension of social interaction. In addition an interaction effect was revealed for persistence, social interaction, and cultural interest. The field of study and whether the participants were honours students or not were also taken into account. Some implications for future studies are presented here along with possible interventions for honours students.

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A high-resolution mtDNA phylogenetic tree allowed us to look backward in time to investigate purifying selection. Purifying selection was very strong in the last 2,500 years, continuously eliminating pathogenic mutations back until the end of the Younger Dryas (∼11,000 years ago), when a large population expansion likely relaxed selection pressure. This was preceded by a phase of stable selection until another relaxation occurred in the out-of-Africa migration. Demography and selection are closely related: expansions led to relaxation of selection and higher pathogenicity mutations significantly decreased the growth of descendants. The only detectible positive selection was the recurrence of highly pathogenic nonsynonymous mutations (m.3394T>C-m.3397A>G-m.3398T>C) at interior branches of the tree, preventing the formation of a dinucleotide STR (TATATA) in the MT-ND1 gene. At the most recent time scale in 124 mother-children transmissions, purifying selection was detectable through the loss of mtDNA variants with high predicted pathogenicity. A few haplogroup-defining sites were also heteroplasmic, agreeing with a significant propensity in 349 positions in the phylogenetic tree to revert back to the ancestral variant. This nonrandom mutation property explains the observation of heteroplasmic mutations at some haplogroup-defining sites in sequencing datasets, which may not indicate poor quality as has been claimed.

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This study aims to (a) identify and profile groups of infants according to their behavioral and physiological characteristics, considering their neurobehavioral organization, social withdrawal behavior, and endocrine reactivity to stress, and to (b) analyze group differences in the quality of mother–infant interaction. Ninety seven 8-week-old infants were examined using the Neonatal Behavioral Assessment Scale and the Alarm Distress Baby Scale. Cortisol levels were measured both before and after routine inoculation between 8 and 12 weeks. At 12 to 16 weeks mother–infant interaction was assessed using the Global Rating Scales of Mother–Infant Interaction. Three groups of infants were identified: (a) ‘‘withdrawn’’; (b) ‘‘extroverted’’; (c) ‘‘underaroused.’’ Differences between them were found regarding both infant and mother behaviors in the interaction and the overall quality of mother–infant interaction. The identification of behavioral and physiological profiles in infants is an important step in the study of developmental pathways.