Autenticação biométrica de usuários em sistemas de E-learning baseada em reconhecimento de faces a partir de vídeo

Pós-graduação em Ciência da Computação - IBILCE

Unsupervised manifold learning using Reciprocal kNN Graphs in image re-ranking and rank aggregation tasks

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Effect of short training on vaginal fluid microscopy (wet mount) learning

Objective: Is it feasible to learn the basics of wet mount microscopy of vaginal fluid in 10 hours?Materials and Methods: This is a pilot project wherein 6 students with different grades of education were invited for being tested on their ability to read wet mount microscopic slides before and after 10 hours of hands-on training. Microscopy was performed according to a standard protocol (Femicare, Tienen, Belgium). Before and after training, all students had to evaluate a different set of 50 digital slides. Different diagnoses and microscopic patterns had to be scored. kappa indices were calculated compared with the expert reading. Results: All readers improved their mean scores significantly, especially for the most important types of altered flora (p < .0001). The mean increase in reading concordance (kappa from 0.64 to 0.75) of 1 student with a solid previous experience with microscopy did not reach statistical significance, but the remaining 5 students all improved their scores from poor performance (all kappa < 0.20) to moderate (kappa = 0.53, n = 1) to good (kappa > 0.61, n = 4) concordance. Reading quality improved and reached fair to good concordance on all microscopic items studied, except for the detection of parabasal cells and cytolytic flora. Conclusions: Although further improvement is still possible, a short training course of 10 hours enables vast improvement on wet mount microscopy accuracy and results in fair to good concordance of the most important variables of the vaginal flora compared to a reference reader.

Biodegradation of PP and PE blended with PHBV in soil samples

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Supervised variational relevance learning, an analytic geometric feature selection with applications to omic datasets

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Semi-supervised learning for relevance feedback on image retrieval tasks

Relevance feedback approaches have been established as an important tool for interactive search, enabling users to express their needs. However, in view of the growth of multimedia collections available, the user efforts required by these methods tend to increase as well, demanding approaches for reducing the need of user interactions. In this context, this paper proposes a semi-supervised learning algorithm for relevance feedback to be used in image retrieval tasks. The proposed semi-supervised algorithm aims at using both supervised and unsupervised approaches simultaneously. While a supervised step is performed using the information collected from the user feedback, an unsupervised step exploits the intrinsic dataset structure, which is represented in terms of ranked lists of images. Several experiments were conducted for different image retrieval tasks involving shape, color, and texture descriptors and different datasets. The proposed approach was also evaluated on multimodal retrieval tasks, considering visual and textual descriptors. Experimental results demonstrate the effectiveness of the proposed approach.

A self-learning simulated annealing algorithm for global optimizations of electromagnetic devices

A self-learning simulated annealing algorithm is developed by combining the characteristics of simulated annealing and domain elimination methods. The algorithm is validated by using a standard mathematical function and by optimizing the end region of a practical power transformer. The numerical results show that the CPU time required by the proposed method is about one third of that using conventional simulated annealing algorithm.

Auditory middle latency response and phonological awareness in students with learning disabilities

Introduction Behavioral tests of auditory processing have been applied in schools and highlight the association between phonological awareness abilities and auditory processing, confirming that low performance on phonological awareness tests may be due to low performance on auditory processing tests. Objective To characterize the auditory middle latency response and the phonological awareness tests and to investigate correlations between responses in a group of children with learning disorders. Methods The study included 25 students with learning disabilities. Phonological awareness and auditory middle latency response were tested with electrodes placed on the left and right hemispheres. The correlation between the measurements was performed using the Spearman rank correlation coefficient. Results There is some correlation between the tests, especially between the Pa component and syllabic awareness, where moderate negative correlation is observed. Conclusion In this study, when phonological awareness subtests were performed, specifically phonemic awareness, the students showed a low score for the age group, although for the objective examination, prolonged Pa latency in the contralateral via was observed. Negative weak to moderate correlation for Pa wave latency was observed, as was positive weak correlation for Na-Pa amplitude.

A educação para os 'meios e os fins': a informação, o conhecimento e a comunicação na educação escolar básica e universitária

This research has as its main reference, the need to detect the development initiatives by public higher education, concepts, methods and teaching and pedagogical tools and to investigate the ability to transfer knowledge and practices of teaching and learning produced for other levels education. The task of providing appropriate training of teachers of basic education to university education is a vital political and administrative demands for a large country, which needs to adequately educate its people, so he can face in the right conditions, the huge and complex demands of regional and national development. The research presented here, aims to gauge the extent and adequacy of current media and information as tools for teaching and pedagogical transfer the knowledge and practices of teaching and learning as a tool for updating and also for training or non-presence blended Primary School Teacher Education. From the established goals will be carried out research, conceptual and field, to analyze and evaluate some educational practices and resulting forms of communication and also to assess the effects brought about by replacing the linear communication model and the model of unilateral to multilateral communication networks on digital models, and practices of schooling. The results obtained from both theoretical and practical will be on the selection of concepts, content production, methodologies and resources run by different "means" integrated with the cultural, economic and social development, both locally, regionally or nationally. The strategic aim will be to expand from the analysis, production and dissemination of concepts, methods and tools made by teachers of Basic Education and Higher Education, teaching and pedagogical possibilities of media and digital devices that are emerging as the derivation of network communication.

Cooperative Learning Groups in the Middle School Mathematics Classroom

In this action research study of my classroom of 8th grade mathematics, I investigated the inclusion of cooperative learning groups. Data was collected to see how cooperative learning groups affected oral and written communication, math scores, and attitudes toward mathematics. On the one hand, I discovered that many students enjoyed the opportunity to work within a group. On the other hand, there continues to be a handful of students who would rather work alone. The benefits outweigh the demands. Overall, students benefitted from the inclusion of cooperative learning groups. Oral explanations of solutions and methods improved during the study. Written expression also improved over this time period. As a result of this research, I plan to continue with the incorporation of cooperative learning groups in the middle school math classroom.

Is Competition Making a Comeback? Discovering Methods to Keep Female Adolescents Engaged in STEM: A Phenomenological Approach

The decreasing number of women who are graduating in the Science, Technology, Engineering and Mathematics (STEM) fields continues to be a major concern. Despite national support in the form of grants provided by National Science Foundation, National Center for Information and Technology and legislation passed such as the Deficit Reduction Act of 2005 that encourages women to enter the STEM fields, the number of women actually graduating in these fields is surprisingly low. This research study focuses on a robotics competition and its ability to engage female adolescents in STEM curricula. Data have been collected to help explain why young women are reticent to take technology or engineering type courses in high school and college. Factors that have been described include attitudes, parental support, social aspects, peer pressure, and lack of role models. Often these courses were thought to have masculine and “nerdy” overtones. The courses were usually majority male enrollments and appeared to be very competitive. With more female adolescents engaging in this type of competitive atmosphere, this study gathered information to discover what about the competition appealed to these young women. Focus groups were used to gather information from adolescent females who were participating in the First Lego League (FLL) and CEENBoT competitions. What enticed them to participate in a curriculum that data demonstrated many of their peers avoided? FLL and CEENBoT are robotics programs based on curricula that are taught in afterschool programs in non-formal environments. These programs culminate in a very large robotics competition. My research questions included: What are the factors that encouraged participants to participate in the robotics competition? What was the original enticement to the FLL and CEENBoT programs? What will make participants want to come back and what are the participants’ plans for the future? My research mirrored data of previous findings such as lack of role models, the need for parental support, social stigmatisms and peer pressure are still major factors that determine whether adolescent females seek out STEM activities. An interesting finding, which was an exception to previous findings, was these female adolescents enjoyed the challenge of the competition. The informal learning environments encouraged an atmosphere of social engagement and cooperative learning. Many volunteers that led the afterschool programs were women (role models) and a majority of parents showed support by accommodating an afterschool situation. The young women that were engaged in the competition noted it was a friendly competition, but they were all there to win. All who participated in the competition had a similar learning environment: competitive but cooperative. Further research is needed to determine if it is the learning environment that lures adolescent females to the program and entices them to continue in the STEM fields or if it is the competitive aspect of the culminating activity. Advisors: James King and Allen Steckelberg

Particle Competition and Cooperation in Networks for Semi-Supervised Learning

Semi-supervised learning is one of the important topics in machine learning, concerning with pattern classification where only a small subset of data is labeled. In this paper, a new network-based (or graph-based) semi-supervised classification model is proposed. It employs a combined random-greedy walk of particles, with competition and cooperation mechanisms, to propagate class labels to the whole network. Due to the competition mechanism, the proposed model has a local label spreading fashion, i.e., each particle only visits a portion of nodes potentially belonging to it, while it is not allowed to visit those nodes definitely occupied by particles of other classes. In this way, a "divide-and-conquer" effect is naturally embedded in the model. As a result, the proposed model can achieve a good classification rate while exhibiting low computational complexity order in comparison to other network-based semi-supervised algorithms. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method.

The place of (explicit) grammar within the methods and approaches of foreign language teaching: in the north, in the centre or on the margins?

This article analyzes the role that has been attributed to grammar throughout the history of foreign language teaching, with special emphasis on methods and approaches of the twentieth century. In order to support our argument, we discuss the notion of grammar by proposing a conceptual continuum that includes the main meanings of the term which are relevant to our research. We address as well the issue of "pedagogical grammar" and consider the position of grammar in the different approaches of the "era of the methods" and the current "post-method condition" in the field of language teaching and learning. The findings presented at the end of the text consist of recognizing the central role that grammar has played throughout the history of the methods and approaches, where grammar has always been present by the definition of the contents' progression. The rationale that we propose for this is the recognition of the fact that the dissociation between what is said and how it is said can not be more than theoretical and, thus, artificial.

Applying validated quality indicators to surgical antibiotic prophylaxis in a Brazilian hospital: Learning what should be learned

Background: Compliance with the best surgical antibiotic prophylaxis practice is usually low despite many published guidelines. Objective: This study investigated compliance with the Hospital Infection Control Committee guideline for antibiotic prophylaxis in a Brazilian hospital using quality indicators. Methods: A retrospective study was carried out from November 2009 to March 2010. Medical records from adult inpatients undergoing cardiac, neurologic, and orthopedic clean surgeries were included. The full compliance index was considered 100% when the antibiotic prophylaxis showed adequacy in all evaluated attributes. Analyses were conducted with 5% significance. Results: Medical records from 101 cardiac, 128 neurologic, and 519 orthopedic surgical patients were evaluated. The compliance index was 4.9%, and the compliance index according to specialty was 5.8%, 3.1%, and 3.0%, respectively, for orthopedic, neurologic, and cardiac surgeries. The attribute route of administration produced the best outcomes, whereas the attribute duration of antibiotic prophylaxis produced the worst. No association was identified between compliance to the attributes and patient characteristics. Conclusion: This study showed a low level of adherence to Hospital Infection Control Committee guidelines for antibiotic prophylaxis. This suggests that different strategies should be implemented to promote the best possible practice in the field of antibiotic prophylaxis with greater surgeon engagement. Copyright (C) 2012 by the Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

Using Machine Learning Classifiers to Assist Healthcare-Related Decisions: Classification of Electronic Patient Records

Surveillance Levels (SLs) are categories for medical patients (used in Brazil) that represent different types of medical recommendations. SLs are defined according to risk factors and the medical and developmental history of patients. Each SL is associated with specific educational and clinical measures. The objective of the present paper was to verify computer-aided, automatic assignment of SLs. The present paper proposes a computer-aided approach for automatic recommendation of SLs. The approach is based on the classification of information from patient electronic records. For this purpose, a software architecture composed of three layers was developed. The architecture is formed by a classification layer that includes a linguistic module and machine learning classification modules. The classification layer allows for the use of different classification methods, including the use of preprocessed, normalized language data drawn from the linguistic module. We report the verification and validation of the software architecture in a Brazilian pediatric healthcare institution. The results indicate that selection of attributes can have a great effect on the performance of the system. Nonetheless, our automatic recommendation of surveillance level can still benefit from improvements in processing procedures when the linguistic module is applied prior to classification. Results from our efforts can be applied to different types of medical systems. The results of systems supported by the framework presented in this paper may be used by healthcare and governmental institutions to improve healthcare services in terms of establishing preventive measures and alerting authorities about the possibility of an epidemic.