Adaptive back-propagation in on-line learning of multilayer networks

An adaptive back-propagation algorithm is studied and compared with gradient descent (standard back-propagation) for on-line learning in two-layer neural networks with an arbitrary number of hidden units. Within a statistical mechanics framework, both numerical studies and a rigorous analysis show that the adaptive back-propagation method results in faster training by breaking the symmetry between hidden units more efficiently and by providing faster convergence to optimal generalization than gradient descent.

Dynamics of on-line learning in radial basis function networks

On-line learning is examined for the radial basis function network, an important and practical type of neural network. The evolution of generalization error is calculated within a framework which allows the phenomena of the learning process, such as the specialization of the hidden units, to be analyzed. The distinct stages of training are elucidated, and the role of the learning rate described. The three most important stages of training, the symmetric phase, the symmetry-breaking phase, and the convergence phase, are analyzed in detail; the convergence phase analysis allows derivation of maximal and optimal learning rates. As well as finding the evolution of the mean system parameters, the variances of these parameters are derived and shown to be typically small. Finally, the analytic results are strongly confirmed by simulations.

On-line learning in neural networks

On-line learning is one of the most powerful and commonly used techniques for training large layered networks and has been used successfully in many real-world applications. Traditional analytical methods have been recently complemented by ones from statistical physics and Bayesian statistics. This powerful combination of analytical methods provides more insight and deeper understanding of existing algorithms and leads to novel and principled proposals for their improvement. This book presents a coherent picture of the state-of-the-art in the theoretical analysis of on-line learning. An introduction relates the subject to other developments in neural networks and explains the overall picture. Surveys by leading experts in the field combine new and established material and enable non-experts to learn more about the techniques and methods used. This book, the first in the area, provides a comprehensive view of the subject and will be welcomed by mathematicians, scientists and engineers, whether in industry or academia.

The theory of on-line learning: a statistical physics approach

In this paper we review recent theoretical approaches for analysing the dynamics of on-line learning in multilayer neural networks using methods adopted from statistical physics. The analysis is based on monitoring a set of macroscopic variables from which the generalisation error can be calculated. A closed set of dynamical equations for the macroscopic variables is derived analytically and solved numerically. The theoretical framework is then employed for defining optimal learning parameters and for analysing the incorporation of second order information into the learning process using natural gradient descent and matrix-momentum based methods. We will also briefly explain an extension of the original framework for analysing the case where training examples are sampled with repetition.

Feasibility studies of an on-line identification technique

This thesis is concerned with the study of a non-sequential identification technique, so that it may be applied to the identification of process plant mathematical models from process measurements with the greatest degree of accuracy and reliability. In order to study the accuracy of the technique under differing conditions, simple mathematical models were set up on a parallel hybrid. computer and these models identified from input/output measurements by a small on-line digital computer. Initially, the simulated models were identified on-line. However, this method of operation was found not suitable for a thorough study of the technique due to equipment limitations. Further analysis was carried out in a large off-line computer using data generated by the small on-line computer. Hence identification was not strictly on-line. Results of the work have shovm that the identification technique may be successfully applied in practice. An optimum sampling period is suggested, together with noise level limitations for maximum accuracy. A description of a double-effect evaporator is included in this thesis. It is proposed that the next stage in the work will be the identification of a mathematical model of this evaporator using the teclmique described.

Az információterjedés szerepe az innováció-elfogadásban. Az okostelefonok és az on-line kollektív intelligencia (Role of informationspread in the innovation acceptance: the smart phones and the online collective intelligence)

A tanulmány célja az innováció-terjedés marketingvonzatú irodalmának bemutatása, valamint betekintés az exploratív tartalomelemzés módszerével az informális, kollektív intelligenciát generáló on-line felületek, nevesül a blogok és fórumok kutathatóságába. Az okostelefonok innováció-elfogadásának példáján keresztül a szerzők megpróbálják felderíteni az információterjedés elméletének megvalósulását az elemzett felületeken. Bemutatnak három, a mintára jellemző információterjedési és felvett szerep mintát, melyek alapul szolgálhatnak a további célirányú kutatások számára. / === / Adaptive smart phones that give space for user-added functions create active online discussions. Committed users are ready to share information, advise others, while less expert users seek this information. In their paper the authors show that related user-generated content i.e. blogs and bulletin boards provide a rich data source for analysis, which gives them the opportunity to further elaborate on the diffusion of information in the case of smart phone usage among online Hungarian users. Online collective intelligence may well contribute to the diffusion of innovations through diffusing information. Following a thorough review on the literature on the diffusion of innovations, in their exploratory content analysis, they found two categories of users on the analyzed boards: a first group we dubbed "experts" (corresponding to innovators in Bass's typology) that made a special effort trying to solve particular problems thus contributing to collective intelligence, thus reducing (among others) the perceived complexity of these phones and adding to their trialability, both factors influencing users' innovation acceptance, and a second group, "simple users" (or imitators in Bass's typology), uninterested in product innovation, still asking questions and searching for solutions concerning extant technology. Manufacturers do not seem yet to regard these boards as a source of valuable data, even though these clearly serve as an important pool of information and a growing factor of decision for their potential customers.

Off-line and on-line affective recognition of a computer user through a biosignal processing approach

Physiological signals, which are controlled by the autonomic nervous system (ANS), could be used to detect the affective state of computer users and therefore find applications in medicine and engineering. The Pupil Diameter (PD) seems to provide a strong indication of the affective state, as found by previous research, but it has not been investigated fully yet. ^ In this study, new approaches based on monitoring and processing the PD signal for off-line and on-line affective assessment ("relaxation" vs. "stress") are proposed. Wavelet denoising and Kalman filtering methods are first used to remove abrupt changes in the raw Pupil Diameter (PD) signal. Then three features (PDmean, PDmax and PDWalsh) are extracted from the preprocessed PD signal for the affective state classification. In order to select more relevant and reliable physiological data for further analysis, two types of data selection methods are applied, which are based on the paired t-test and subject self-evaluation, respectively. In addition, five different kinds of the classifiers are implemented on the selected data, which achieve average accuracies up to 86.43% and 87.20%, respectively. Finally, the receiver operating characteristic (ROC) curve is utilized to investigate the discriminating potential of each individual feature by evaluation of the area under the ROC curve, which reaches values above 0.90. ^ For the on-line affective assessment, a hard threshold is implemented first in order to remove the eye blinks from the PD signal and then a moving average window is utilized to obtain the representative value PDr for every one-second time interval of PD. There are three main steps for the on-line affective assessment algorithm, which are preparation, feature-based decision voting and affective determination. The final results show that the accuracies are 72.30% and 73.55% for the data subsets, which were respectively chosen using two types of data selection methods (paired t-test and subject self-evaluation). ^ In order to further analyze the efficiency of affective recognition through the PD signal, the Galvanic Skin Response (GSR) was also monitored and processed. The highest affective assessment classification rate obtained from GSR processing is only 63.57% (based on the off-line processing algorithm). The overall results confirm that the PD signal should be considered as one of the most powerful physiological signals to involve in future automated real-time affective recognition systems, especially for detecting the "relaxation" vs. "stress" states.^

O BOCA A BOCA ON-LINE: AS IMPLICAÇÕES DA VOZ DO CONSUMIDOR NA COMUNICAÇÃO DE MERCADO

O consumidor contemporâneo, inserido em um novo ambiente de comunicação, potencializa suas expressões, capaz de avaliar uma marca ou produto e transmitir sua opinião pelas redes sociais, ou seja, o consumidor expressa suas opiniões e desejos dialogando com seus pares de forma espontânea nas redes sociais on-line. É neste ambiente de participação e interação (ciberespaço) que está nosso objeto de estudo, o boca a boca on-line – a voz do consumidor contemporâneo, também conhecido como uma manifestação informativa pessoal ou uma conversa, a opinion sharing. Proporcionado pelos consumidores nas redes sociais on-line, o boca a boca se fortalece em função das possibilidades de interação, característica da sociedade em rede. Nesse cenário, oobjetivo desta pesquisa é caracterizar o boca a boca on-line como um novo fluxo comunicacional entre consumidores, hoje potencializado pelas novas tecnologias da comunicação, capazes de alterar a percepção da marca e demonstrar o uso, pelas marcas, das redes sociais on-line ainda como um ambiente de comunicação unidirecional. Mediante três casos selecionados por conveniência (dois casos nacionais e um internacional), o corpus de análise de nossa pesquisa se limitou aos 5.084 comentários disponibilizados após publicação de matérias jornalísticas no Portal G1 e nas fanpages (Facebook), ambos relativos aos casos selecionados. Com a Análise de Conteúdo dos posts, identificamos e categorizamos a fala do consumidor contemporâneo, sendo assim possível comprovar que as organizações/marcas se valem da cultura do massivo, não dialogando com seus consumidores, pois utilizam as redes sociais on-line ainda de forma unidirecional, além de não darem a devida atenção ao atual fluxo onde se evidencia a opinião compartilhada dos consumidores da sociedade em rede.

As práticas comunicacionais do pós-venda: o SAC na era das redes sociais on-line

Estudo sobre as práticas comunicacionais da área de pós-vendas nas redes sociais on-line, com relação ao atendimento das empresas e os canais por elas disponibilizados para interação com o consumidor. Dentre as etapas, realizou-se uma análise sobre os hábitos dos consumidores de realizar buscas nas redes socais on-line; com o intuito de chamar a atenção das empresas sobre problemas de pós-venda nestes canais (reclamações, dúvidas técnicas, sugestões etc.). O objetivo principal foi elaborar de forma cronológica e estruturada a práticas de comunicação no pós-venda por meio dos diversos canais do SAC; resgatando as fases evolutivas do SAC, a lei de proteção do consumidor, desde a era analógica (sem acesso à internet e espontânea), até a chegada das redes sociais on-line. Para tal estudo foram realizados: levantamento bibliográfico, exploratório e documental sobre a área de pós-venda, marketing de relacionamento e de resultados de pesquisas sobre os hábitos dos consumidores conectados à internet; apresentação de casos que exemplificam as práticas comunicacionais do mercado; entrevista aplicada com oito especialistas do mercado; e formulário eletrônico aplicado com gestores das centrais de atendimento. Com todas essas análises, foi possível traçar um diagnóstico sobre a realidade atual da área de atendimento ao cliente das empresas selecionadas, nas redes sociais on-line, além de reforçar sensivelmente a ideia do consumidor produtor de conteúdo (prosumer) e a mudança no fluxo comunicacional consumidor versus empresa.

Short-term wind power forecast based on cluster analysis and artificial neural networks

[EN]In this paper an architecture for an estimator of short-term wind farm power is proposed. The estimator is made up of a Linear Machine classifier and a set of k Multilayer Perceptrons, training each one for a specific subspace of the input space. The splitting of the input dataset into the k clusters is done using a k-means technique, obtaining the equivalent Linear Machine classifier from the cluster centroids...

Off-line and On-line Affective Recognition of a Computer User through A Biosignal Processing Approach

Physiological signals, which are controlled by the autonomic nervous system (ANS), could be used to detect the affective state of computer users and therefore find applications in medicine and engineering. The Pupil Diameter (PD) seems to provide a strong indication of the affective state, as found by previous research, but it has not been investigated fully yet. In this study, new approaches based on monitoring and processing the PD signal for off-line and on-line affective assessment (“relaxation” vs. “stress”) are proposed. Wavelet denoising and Kalman filtering methods are first used to remove abrupt changes in the raw Pupil Diameter (PD) signal. Then three features (PDmean, PDmax and PDWalsh) are extracted from the preprocessed PD signal for the affective state classification. In order to select more relevant and reliable physiological data for further analysis, two types of data selection methods are applied, which are based on the paired t-test and subject self-evaluation, respectively. In addition, five different kinds of the classifiers are implemented on the selected data, which achieve average accuracies up to 86.43% and 87.20%, respectively. Finally, the receiver operating characteristic (ROC) curve is utilized to investigate the discriminating potential of each individual feature by evaluation of the area under the ROC curve, which reaches values above 0.90. For the on-line affective assessment, a hard threshold is implemented first in order to remove the eye blinks from the PD signal and then a moving average window is utilized to obtain the representative value PDr for every one-second time interval of PD. There are three main steps for the on-line affective assessment algorithm, which are preparation, feature-based decision voting and affective determination. The final results show that the accuracies are 72.30% and 73.55% for the data subsets, which were respectively chosen using two types of data selection methods (paired t-test and subject self-evaluation). In order to further analyze the efficiency of affective recognition through the PD signal, the Galvanic Skin Response (GSR) was also monitored and processed. The highest affective assessment classification rate obtained from GSR processing is only 63.57% (based on the off-line processing algorithm). The overall results confirm that the PD signal should be considered as one of the most powerful physiological signals to involve in future automated real-time affective recognition systems, especially for detecting the “relaxation” vs. “stress” states.

A experiência da ESEV TV - televisão académica on-line

The study focuses on the analysis of the academic experience entitled Television of the Superior School of Education from Viseu (ESEV TV). This academic project has been an online experience since 2011 and comprises a space of experimentation and broadcasting for audiovisual contents. The significance of the digital sphere embodied mostly through the internet places this medium as the ideal platform to the exchange of contents created by the academic community and favors its dissemination to a heterogeneous audience. The implementation of this audiovisual project encourages the collaboration and the creative initiative of those involved in it and, at the same time, intents to improve the capabilities of expression and communication skills of the participants. It is also an objective of this creative initiative to build an historical archive of audiovisual produced material as also as to promote the integration of students, strengthening ethical and moral values and increasing communication strategies. ESEV TV is available to all study cycles from the institution where it is allocated and represents a workshop camp where it is possible to practice techniques and develop knowledge in the television production area. The accomplishment of the project purpose is inextricably dependent on the existence of a working group constantly updated, also multidisciplinary, that aggregates students from different areas. This complex interdependent mission is guided by teachers with knowledge and experience in the audiovisual field. The team work expects to produce an interesting online schedule that reunites, at the same time, information, culture, education and entertainment.