Particle competition and cooperation to prevent error propagation from mislabeled data in semi-supervised learning

Semi-supervised learning is applied to classification problems where only a small portion of the data items is labeled. In these cases, the reliability of the labels is a crucial factor, because mislabeled items may propagate wrong labels to a large portion or even the entire data set. This paper aims to address this problem by presenting a graph-based (network-based) semi-supervised learning method, specifically designed to handle data sets with mislabeled samples. The method uses teams of walking particles, with competitive and cooperative behavior, for label propagation in the network constructed from the input data set. The proposed model is nature-inspired and it incorporates some features to make it robust to a considerable amount of mislabeled data items. Computer simulations show the performance of the method in the presence of different percentage of mislabeled data, in networks of different sizes and average node degree. Importantly, these simulations reveals the existence of the critical points of the mislabeled subset size, below which the network is free of wrong label contamination, but above which the mislabeled samples start to propagate their labels to the rest of the network. Moreover, numerical comparisons have been made among the proposed method and other representative graph-based semi-supervised learning methods using both artificial and real-world data sets. Interestingly, the proposed method has increasing better performance than the others as the percentage of mislabeled samples is getting larger. © 2012 IEEE.

Creating capabilities in local environments and production networks

Includes bibliography

Aprendizagem Baseada em Problemas (PBL – Problem-Based Learning): estratégia para o ensino e aprendizagem de algoritmos e conteúdos computacionais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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

Prediction of Oncogenic Interactions and Cancer-Related Signaling Networks Based on Network Topology

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

An evolutionary approach to improve connectivity prediction in mobile wireless sensor networks

Connectivity is the basic factor for the proper operation of any wireless network. In a mobile wireless sensor network it is a challenge for applications and protocols to deal with connectivity problems, as links might get up and down frequently. In these scenarios, having knowledge of the node remaining connectivity time could both improve the performance of the protocols (e.g. handoff mechanisms) and save possible scarce nodes resources (CPU, bandwidth, and energy) by preventing unfruitful transmissions. The current paper provides a solution called Genetic Machine Learning Algorithm (GMLA) to forecast the remainder connectivity time in mobile environments. It consists in combining Classifier Systems with a Markov chain model of the RF link quality. The main advantage of using an evolutionary approach is that the Markov model parameters can be discovered on-the-fly, making it possible to cope with unknown environments and mobility patterns. Simulation results show that the proposal is a very suitable solution, as it overcomes the performance obtained by similar approaches.

Collaborative language learning in Teletandem: a resource for pre-service teacher education

This article presents some of the results of a qualitative research project about the influences of the pedagogic strategies used by a mediator (graduate student in applied linguistics) in the supervision process of a Teletandem partner (undergraduate student in languages) on her pedagogical practice. It was done within the project Teletandem Brazil: foreign language for all. Based on the reflective teaching paradigm and collaborative language learning, with special emphasis on tandem learning, we analyzed the contributions of the collaborative relationship established between the graduate student and the student-teacher in her first teaching experience. The results bring about implications for the field of language teacher education in a perspective of education within practice, evidencing the experience of collaborative learning in teletandem as an opportunity for reflective teacher education of pre-service teachers.

A method using artificial neural networks to morphologically assess mouse blastocyst quality

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

Tool condition monitoring of aluminum oxide grinding wheel in dressing operation using acoustic emission and neural networks

The grinding operation gives workpieces their final finish, minimizing surface roughness through the interaction between the abrasive grains of a tool (grinding wheel) and the workpiece. However, excessive grinding wheel wear due to friction renders the tool unsuitable for further use, thus requiring the dressing operation to remove and/or sharpen the cutting edges of the worn grains to render them reusable. The purpose of this study was to monitor the dressing operation using the acoustic emission (AE) signal and statistics derived from this signal, classifying the grinding wheel as sharp or dull by means of artificial neural networks. An aluminum oxide wheel installed on a surface grinding machine, a signal acquisition system, and a single-point dresser were used in the experiments. Tests were performed varying overlap ratios and dressing depths. The root mean square values and two additional statistics were calculated based on the raw AE data. A multilayer perceptron neural network was used with the Levenberg-Marquardt learning algorithm, whose inputs were the aforementioned statistics. The results indicate that this method was successful in classifying the conditions of the grinding wheel in the dressing process, identifying the tool as "sharp''(with cutting capacity) or "dull''(with loss of cutting capacity), thus reducing the time and cost of the operation and minimizing excessive removal of abrasive material from the grinding wheel.

O ensino de língua estrangeira nas escolas públicas estaduais paulistas e as novas tecnologias

Pós-graduação em Televisão Digital: Informação e Conhecimento - FAAC

Preliminary diagnosis of ophtalmological diseases through machine learning techniques

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

How to progress from discourse to practice? a new agenda for change in medical schools into the next decade

In the context of medical school instruction, the segmented approach of a focus on specialties and excessive use of technology seem to hamper the development of the professional-patient relationship and an understanding of the ethics of this relationship. The real world presents complexities that require multiple approaches. Engagement in the community where health competence is developed allows extending the usefulness of what is learned. Health services are spaces where the relationship between theory and practice in health care are real and where the social role of the university can be revealed. Yet some competencies are still lacking and may require an explicit agenda to enact. Ten topics are presented for focus here: environmental awareness, involvement of students in medical school, social networks, interprofessional learning, new technologies for the management of care, virtual reality, working with errors, training in management for results, concept of leadership, and internationalization of schools. Potential barriers to this agenda are an underinvestment in ambulatory care infrastructure and community-based health care facilities, as well as in information technology offered at these facilities; an inflexible departmental culture; and an environment centered on a discipline-based medical curriculum.

Making Learning Visible: Peer Review and the Scholarship of Teaching

This is the promotional brochure from the March 2004 national conference, Making Learning Visible: Peer Review and the Scholarship of Teaching. This conference was hosted by the UNL Peer Review of Teaching project and the University of Nebraska-Lincoln.

Traces, Patterns, Texture: In Search of Aesthetic Teaching/Learning Encounters

This inquiry reveals the crucial guidance of teachers toward surveying the capacity and needs of students, the formation of ideas, acting upon ideas, fostering connections, seeing potential, making judgments, and arranging conditions. Each aesthetic trace causes me to wonder how teachers learn to create experiences that foster student participation in the world aesthetically. The following considerations surface: • Given the emphasis in schools on outcomes and results, how do we encourage teachers to focus on acts of mind instead of end products in their work with students? • Given the orientations toward technical rationality, to fixed sequence, how do we help teachers experience fluid, purposeful learning adventures with students in which the imagi¬nation is given room to play? • Given the tendency to conceive of planning in teaching as the deciding of everything in advance, how do we help teachers and students become attuned to making good judgments derived from within learning experiences? • How do we help teachers build dialogical multivoiced conversations instead of monolithic curriculum? • What do we do to recover the pleasure dwelling in subject matter? How do we get teachers and students to engage thoughtfully in meaningful learning as opposed to covering curriculum7 • A capacity to attend sensitively, to perceive the complexity of relationships coming together in any teaching/learning experience seems critical. How do we help teachers and students attend to the unity of a learning experience and the play of meanings that arises from such undergoing and doing? The traces, patterns, and texture evidenced locate tremendous hope and wondrous possibilities alive within aesthetic teaching/learning encounters. It is such aliveness I encountered in the grade 4 art classroom that opened this account and continues to compel my attention. Possibilities for teaching, learning, and teacher education emerge. I am convinced they are most worthy of continued pursuit.

PBL and B-Learning for Civil Engineering Students in a Transportation Course

The results of a pedagogical strategy implemented at the University of Sao Paulo at Sao Carlos are presented and discussed. The initiative was conducted in a transportation course offered to Civil Engineering students. The approach is a combination of problem-based learning and project-based learning (PBL) and blended-learning (B-learning). Starting in 2006, a different problem was introduced every year. From 2009 on, however, the problem-based learning concept was expanded to project-based learning. The performance of the students was analyzed using the following elements: (1) grades in course activities; (2) answers from a questionnaire designed for course evaluation; and (3) cognitive maps made to assess the effects of PBL through the comparison of the responses provided by the students involved and those not involved in the experiment. The results showed positive aspects of the method, such as a strong involvement of several students with the subject. A gradual increase in the average scores obtained by the students in the project activities (from 6.77 in 2006 to 8.24 in 2009) was concomitant with a better evaluation of these activities and of the course as a whole (90 and 97% of options "Good" or "Very good" in 2009, respectively). A growing interest in the field of transportation engineering as an alternative for further studies was also noticed. DOI: 10.1061/(ASCE)EI.1943-5541.0000115. (C) 2012 American Society of Civil Engineers.