Yes / Failure is an increasingly important issue in high performance computing and cloud systems. As large-scale systems continue to grow in scale and complexity, mitigating the impact of failure and providing accurate predictions with sufficient lead time remains a challenging research problem. Traditional existing fault-tolerance strategies such as regular checkpointing and replication are not adequate because of the emerging complexities of high performance computing systems. This necessitates the importance of having an effective as well as proactive failure management approach in place aimed at minimizing the effect of failure within the system. With the advent of machine learning techniques, the ability to learn from past information to predict future pattern of behaviours makes it possible to predict potential system failure more accurately. Thus, in this paper, we explore the predictive abilities of machine learning by applying a number of algorithms to improve the accuracy of failure prediction. We have developed a failure prediction model using time series and machine learning, and performed comparison based tests on the prediction accuracy. The primary algorithms we considered are the Support Vector Machine (SVM), Random Forest(RF), k-Nearest Neighbors (KNN), Classi cation and Regression Trees (CART) and Linear Discriminant Analysis (LDA). Experimental results show that the average prediction accuracy of our model using SVM when predicting failure is 90% accurate and effective compared to other algorithms. This fi nding means that our method can effectively predict all possible future system and application failures within the system. / The full-text of this article will be released for public view a year after publication.

Due to rapid changes in society (economic and social) the number of socially and pedagogically neglected children is increasing in Lithuania, schools are not appropriately prepared to accept children that got into asocial environment and create favourable conditions for their adaptation and education, because little resources are allocated for them, there is a shortage of qualified specialists; schools are not provided with proper technical education means, which guarantee successful functioning of integrated education system; there is not enough information, prepared references and prevention means in order to eliminate the reasons of ineffectual learning. Thus the assessment of state of Lithuanian general education schools is purposeful in order to correct and optimize the process of education, highlighting and determining the reasons of ineffectual learning. Purpose of the work: to explain the reasons of ineffectual learning at general education schools and the influence of family for ineffectual learning. Tasks of the work: • To survey various scientific pedagogical, psychological literature with reference to the problem being examined. • To reveal the reasons of ineffectual learning of pupils (4-10 grades). • To analyze the influence of family for ineffectual learning of pupils. • To prepare references for parents, whose children confront with troubles in learning and for pedagogues, who work with pupils experiencing failures in learning. Methods of the research:... [to full text]

Machine learning is a branch of artificial intelligence that uses data to automatically build inferences and models designed to generalise and make predictions. In this thesis, the use of machine learning in materials science is explored, for two different problems: the optimisation of gallium nitride optoelectronic devices, and the prediction of material failure in the setting of laboratory earthquakes. Light emitting diodes based on III-nitrides quantum wells have become ubiquitous as a light source, owing to their direct band-gap that covers UV, visible and infra-red light, and their very high quantum efficiency. This efficiency originates from most electronic transitions across the band-gap leading to the emission of a photon. At high currents however this efficiency sharply drops. In chapters 3 and 4 simulations are shown to provide an explanation for experimental results, shedding a new light on this drop of efficiency. Chapter 3 provides a simple and yet accurate model that explains the experimentally observed beneficial effect that silicon doping has on light emitting diodes. Chapter 4 provides a model for the experimentally observed detrimental effect that certain V-shaped defects have on light emitting diodes. These results pave the way for the association of simulations to detailed multi-microscopy. In the following chapters 5 to 7, it is shown that machine learning can leverage the use of device simulations, by replacing in a targeted and efficient way the very labour intensive tasks of making sure the numerical parameters of the simulations lead to convergence, and that the physical parameters reproduce experimental results. It is then shown that machine learning coupled with simulations can find optimal light emitting diodes structures, that have a greatly enhanced theoretical efficiency. These results demonstrate the power of machine learning for leveraging and automatising the exploration of device structures in simulations. Material failure is a very broad problem encountered in a variety of fields, ranging from engineering to Earth sciences. The phenomenon stems from complex and multi-scale physics, and failure experiments can provide a wealth of data that can be exploited by machine learning. In chapter 8 it is shown that by recording the acoustic waves emitted during the failure of a laboratory fault, an accurate predictive model can be built. The machine learning algorithm that is used retains the link with the physics of the experiment, and a new signal is thus discovered in the sound emitted by the fault. This new signal announces an upcoming laboratory earthquake, and is a signature of the stress state of the material. These results show that machine learning can help discover new signals in experiments where the amount of data is very large, and demonstrate a new method for the prediction of material failure.

Cette thèse s'inscrit dans le domaine de la didactique du français langue seconde. Elle concerne les causes de la réussite ou de l'échec de l'apprentissage du français par des étudiants chinois en France. Plus précisément, elle prend appui sur la perception de la réussite ou de l'échec d'apprentissage parmi ce public dont l'effectif ne cesse de croître et au sein duquel de nombreux individus éprouvent de grandes difficultés à apprendre la langue du pays d'accueil. Afin d'interroger les causes des sentiments de réussite ou d'échec dans l'apprentissage, trois hypothèses sont posées : le sentiment de réussite ou d'échec est conditionné par l'adaptation à la nouvelle culture d'apprentissage/enseignement ; certains traits de personnalité favorisent l'apprentissage de la langue ; la motivation des apprenants a des conséquences sur leur investissement et sur leur utilisation de stratégies dans l'apprentissage du français. Cette étude tend à montrer que le sentiment de réussite ou d'échec d'apprentissage résulte d'un cumul d'expériences émotionnellement positives ou négatives. Elle fait apparaître certains des facteurs qui facilitent ou empêchent l'apprentissage du français par des étudiants chinois en France. Par exemple, l'adaptation à la culture d'enseignement française favoriserait l'apprentissage et induirait chez l'apprenant un sentiment de réussite. Parmi les facteurs qui seraient susceptibles d'engendrer un sentiment d'échec, l'introversion empêcherait l'acquisition de compétences dans le domaine de l'expression orale et l'absence de contacts réguliers avec le français dans la vie quotidienne affaiblirait la motivation d'apprentissage. / This PhD. dissertation aims to contribute to research in teaching French as a second language. It analyzes the reasons why Chinese students in France succeed or not in learning French. More precisely, it is based on the perception of success or failure in learning French among a population whose numbers are growing and in which many individuals find it very difficult to learn the language of the host country. In order to examine the reasons for the feeling of success or failure in learning, three hypotheses are postulated: the feeling of success or failure is determined by the adaptation to the new culture of learning/teaching; certain personality traits promote language learning; learners' motivation has some consequences on their use of strategies in learning French. This research aims to show that the feeling of success or failure in learning results from the synthesis of experiences with positive or negative emotion. It also shows some of the factors that facilitate or hinder French learning by Chinese students in France. For example, adapting to the French culture of teaching would encourage learning and bring about learners' feeling of success. Among the factors that are likely to generate the feeling of failure, it appears that introversion prevents the acquisition of speaking skills and lack of regular contact with the French language in everyday life weakens motivation to learn.

Made available in DSpace on 2016-04-27T16:34:01Z (GMT). No. of bitstreams: 1 Marcos Daniel Nemitz.pdf: 2977915 bytes, checksum: cf262ace27ae358a9d5b6cfa42b58ad9 (MD5) Previous issue date: 2009-09-15 / Conselho Nacional de Desenvolvimento Científico e Tecnológico / This work was based in the psycho pedagogy periodical Brazilian Association Magazine of Psycho pedagogy, in the period 1982 2006. The periodical was considered the printed matter representative of the Brazilian Psycho pedagogy history, mostly because of the important role that is has played in the formation process of the psycho pedagogies and in the Psycho pedagogy as knowledge area in the Education field. In this research was used as theoretical reference Pierre Bourdieu s concept of field. This author understands field as a space in which it is established a competition relation. The dispute in this competition is the one for the authority monopolization and the scientific knowledge about the theme (Bourdieu, 1983). This research aim is the understanding of the printed matter as strategy for the constitution of the Psycho pedagogy as study area inside the Education field. The periodical is taken as research object and is been analyzed as dispositive to normatize the Psycho pedagogy practice, at the same time it is considered as a material support that permits to amplify the discussion within the Education field from a Psycho pedagogical point of view / Este trabalho foi desenvolvido sobre o periódico Psicopedagogia Revista da Associação Brasileira de Psicopedagogia, no período compreendido entre 1982 a 2006. O periódico foi considerado como o impresso representativo da história da Psicopedagogia no Brasil, principalmente pelo importante papel que tem desempenhado no processo de formação dos psicopedagogos, e na identificação da Psicopedagogia como área de conhecimento pertencente ao campo da Educação. Nesta pesquisa foi utilizado como referencial teórico o conceito de campo de Pierre Bourdieu. Para este autor, campo também é concebido como um espaço em que se estabelece uma relação de concorrência. A disputa estabelecida dentro desta concorrência refere-se à monopolização da autoridade e do saber científico sobre o tema. (Bourdieu, 1983) Esta pesquisa busca compreender o impresso como estratégia de constituição da área de estudos da Psicopedagogia dentro do campo da Educação. O periódico é tomado como objeto de pesquisa e analisado como um dispositivo de normatização da prática psicopedagógica, ao mesmo tempo em que é considerado como suporte material que permite ampliar a discussão existente dentro do campo educacional, de um ponto de vista psicopedagógico

The purpose of this mixed-methods research is to determine the effectiveness of the Kingdom Marketing (KM) intervention for improving Israeli SME marketing knowledge among managers and employees of Israeli small and medium-sized business. The secondary objective of the study was to portray the process of change in participating organisations. The newly developed KM intervention programme was designed to enhance Israeli SMEs’ marketing knowledge and marketing strategy, imparting new marketing skills and allowing SMEs to operate with better marketing knowledge. The intervention uses a metaphoric story-line approach to teach participants in mediator-led sessions to understand and use important marketing concepts, such as the difference between sales and marketing. Although the intervention has been used in business settings, it has not yet been empirically validated using rigorous methods. This study was conducted using a mixed methods paradigm with an embedded experimental design. Five Israeli based SMEs were recruited to take part in the training programme. The research consisted of three phases. In Phase 1, I administered a preintervention evaluation to measure five variables: awareness of marketing processes, mistaken marketing attitudes, incorrect marketing process beliefs, organisational marketing skills, and marketing need awareness. Participants were also interviewed during Phase 1. In Phase 2, I administered the KM intervention and collected qualitative data in the form of daily open-ended feedback and a researcher diary. In Phase 3, I administered a postintervention evaluation to assess change in the five quantitative variables, and I conducted a second round of interviews. The findings indicated that the KM intervention programme (a) increased awareness of marketing processes, (b) reduced mistaken marketing attitudes, (c) reduced incorrect marketing process believes, and (d) increased marketing need awareness. However, the intervention had no significant effect on organisational marketing skills. Qualitative analysis confirmed that, although the KM intervention empowered participants with marketing knowledge and skills, it did not result in broad organisational changes. I conclude that the KM intervention programme is valid and worthy of wider use for promoting the survival of SME businesses through marketing knowledge and skill improvement. However, the intervention should be used in conjunction with internal efforts to translate increased knowledge into lasting organisational change.