Design and implementation of an enterprise application integration solution for science and research outcomes information management using guaraná technology

This document presents an Enterprise Application Integration based proposal for research outcomes and technological information management. The proposal addresses national and international science and research outcomes information management, and corresponding information systems. Information systems interoperability problems, approaches, technologies and integration tools are presented and applied to the research outcomes information management case. A business and technological perspective is provided, including the conceptual analysis and modelling, an integration solution based in a Domain-Specific Language (DSL) and the integration platform to execute the proposed solution. For illustrative purposes, the role and information system needs of a research unit is assumed as the representative case.

Structural brain connectivity and cognitive ability differences: A multivariate distance matrix regression analysis

Neuroimaging research involves analyses of huge amounts of biological data that might or might not be related with cognition. This relationship is usually approached using univariate methods, and, therefore, correction methods are mandatory for reducing false positives. Nevertheless, the probability of false negatives is also increased. Multivariate frameworks have been proposed for helping to alleviate this balance. Here we apply multivariate distance matrix regression for the simultaneous analysis of biological and cognitive data, namely, structural connections among 82 brain regions and several latent factors estimating cognitive performance. We tested whether cognitive differences predict distances among individuals regarding their connectivity pattern. Beginning with 3,321 connections among regions, the 36 edges better predicted by the individuals' cognitive scores were selected. Cognitive scores were related to connectivity distances in both the full (3,321) and reduced (36) connectivity patterns. The selected edges connect regions distributed across the entire brain and the network defined by these edges supports high-order cognitive processes such as (a) (fluid) executive control, (b) (crystallized) recognition, learning, and language processing, and (c) visuospatial processing. This multivariate study suggests that one widespread, but limited number, of regions in the human brain, supports high-level cognitive ability differences. Hum Brain Mapp, 2016. © 2016 Wiley Periodicals, Inc.

A literary approach to teaching english language in a multicultural classroom

Literature is not generally considered as a coherent branch of the curriculum in relation to language development in either native or foreign language teaching. As teachers of English in multicultural Indian classrooms, we come across students with varying degrees of competence in English language learning. Although language learning is a natural process for natives, students of other languages put in colossal efforts to learn it. Despite their sincere efforts, they face challenges regarding pronunciation, spelling, and vocabulary. Indian classrooms are a microcosm of the larger society, so teaching English language in a manner that equips the students to face the cutthroat competition has become a necessity and a challenge for English language teachers. English today has become the key determinant for being successful in their careers. The hackneyed and stereotypical methods of teaching are not acceptable now. Teachers are no longer arbitrary dispensers of knowledge, but they are playing the role of a guide and facilitator for the students. Teachers of English are using innovative ideas to make English language teaching and learning interesting and simple. Teachers have started using literary texts and their analyses to explore and ignite the imagination and creative skills of the students. One needs to think and rethink the contribution of literature to intelligent thinking as well as its role in the process of teaching/learning. This article is, therefore, an attempt at exploring the nature of the literary experience in the present-day classrooms and the broader role of literature in life.

Digital literacy matters. Increasing workforce productivity through blended English language programmes

Current workplace demands newer forms of literacies that go beyond the ability to decode print. These involve not only competence to operate digital tools, but also the ability to create, represent, and share meaning in different modes and formats; ability to interact, collaborate and communicate effectively using digital tools, and engage critically with technology for developing one’s knowledge, skills, and full participation in civic, economic, and personal matters. This essay examines the application of the ecology of resources (EoR) model for delivering language learning outcomes (in this case, English) through blended classroom environments that use contextually available resources. The author proposes the implementation of the EoR model in blended learning environments to create authentic and sustainable learning environments for skilling courses. Applying the EoR model to Indian skilling instruction contexts, the article discusses how English language and technology literacy can be delivered using contextually available resources through a blended classroom environment. This would facilitate not only acquisition of language and digital literacy outcomes, but also consequent content literacy gain to a certain extent. This would ensure satisfactory achievement of not only communication/language literacy and technological literacy, but also active social participation, lifelong learning, and learner autonomy.

Steps to success : family-friendly guide for fifth grade : English language arts

This document is designed to: provide examples of the standards, skills, and knowledge your child will learn in English language arts and should be able to do upon exiting fifth grade ; suggest activities on how you can help your child at home ; offer additional resources for information and help.

Steps to success : family-friendly guide for fourth grade : English language arts

This document is designed to: provide examples of the standards, skills, and knowledge your child will learn in English language arts and should be able to do upon exiting fourth grade ; suggest activities on how you can help your child at home ; offer additional resources for information and help.

Steps to success : family-friendly guide for third grade : English language arts

This document is designed to: provide examples of the standards, skills, and knowledge your child will learn in English language arts and should be able to do upon exiting third grade ; suggest activities on how you can help your child at home ; offer additional resources for information and help.

Some contributions on reading and writing for 5 to 12 year olds / Quelques perspectives en lecture et en écriture chez les élèves de 5 à 12 ans

Cet ouvrage scientifique constitue les Actes du Symposium international sur la litéracie à l’école / International Symposium for Educational Literacy (SILE/ISEL), qui s’est tenu en août 2015 au Canada (Jouvence, Québec). L’objectif de ce symposium est de rassembler, à l’échelle internationale, des chercheurs de différentes disciplines (éducation, psychologie, linguistique, littérature) et de la santé qui s’intéressent à la réussite en lecture-écriture des élèves en maternelle et au primaire.

Regional variation and change in the history of English strong verbs

This thesis investigates how the strong verb system inherited from Old English evolved in the regional dialects of Middle English (ca. 1100-1500). Old English texts preserve a relatively complex system of strong verbs, in which traditionally seven different ablaut classes are distinguished. This system becomes seriously disrupted from the Late Old English and Early Middle English periods onwards. As a result, many strong verbs die out, or have their ablaut patterns affected by sound change and morphological analogy, or transfer to the weak conjugation. In my thesis, I study the beginnings of two of these developments in two strong verb classes to find out what the evidence from Middle English regional dialects can tell us about their origins and diffusion. Chapter 2 concentrates on the strong-to-weak shift in Class III verbs, and investigates to what extent strong, mixed and weak past tense and participle forms vary in Middle English dialects, and whether the variation is more pronounced in the paradigms of specific verbs or sub-classes. Chapter 3 analyses the regional distribution of ablaut levelling in strong Class IV verbs throughout the Middle English period. The Class III and IV data for the Early Middle English period are drawn from A Linguistic Atlas of Early Middle English, and the data for the Late Middle English period from a sub-corpus of files from The Penn-Helsinki Parsed Corpus of Middle English and The Middle English Grammar Corpus. Furthermore, The English Dialect Dictionary and Grammar are consulted as an additional reference point to find out to what extent the Middle English developments are reflected in Late Modern English dialects. Finally, referring to modern insights into language variation and change and linguistic interference, Chapter 4 discusses to what extent intra- and extra-linguistc factors, such as token and type frequency, stem structure and language contact, might correlate with the strong-to-weak shift and ablaut levelling in Class III and IV verbs in the Middle English period. The thesis is accompanied by six appendices that contain further information about my distinction of Middle English dialect areas (Appendix A), historical Class III and IV verbs (B and C) and the text samples and linguistic data from the Middle English text corpora (D, E and F).

Contributions of Neuroscience to Develop Teaching Strategies and Learning of Mathematics

The goal of the present work is to develop some strategies based on research in neurosciences that contribute to the teaching and learning of mathematics. The interrelationship of education with the brain, as well as the relationship of cerebral structures with mathematical thinking was discussed. Strategies were developed taking into consideration levels that include cognitive, semiotic, language, affect and the overcoming of phobias to the subject. The fundamental conclusion was the imperative educational requirement in the near future of a new teacher, whose pedagogic formation must include the knowledge on the cerebral function, its structures and its implications to education, as well as a change in pedagogy and curricular structure in the teaching of mathematics.

Supporting Scientific Research Through Machine and Deep Learning: Fluorescence Microscopy and Operational Intelligence Use Cases

Although the debate of what data science is has a long history and has not reached a complete consensus yet, Data Science can be summarized as the process of learning from data. Guided by the above vision, this thesis presents two independent data science projects developed in the scope of multidisciplinary applied research. The first part analyzes fluorescence microscopy images typically produced in life science experiments, where the objective is to count how many marked neuronal cells are present in each image. Aiming to automate the task for supporting research in the area, we propose a neural network architecture tuned specifically for this use case, cell ResUnet (c-ResUnet), and discuss the impact of alternative training strategies in overcoming particular challenges of our data. The approach provides good results in terms of both detection and counting, showing performance comparable to the interpretation of human operators. As a meaningful addition, we release the pre-trained model and the Fluorescent Neuronal Cells dataset collecting pixel-level annotations of where neuronal cells are located. In this way, we hope to help future research in the area and foster innovative methodologies for tackling similar problems. The second part deals with the problem of distributed data management in the context of LHC experiments, with a focus on supporting ATLAS operations concerning data transfer failures. In particular, we analyze error messages produced by failed transfers and propose a Machine Learning pipeline that leverages the word2vec language model and K-means clustering. This provides groups of similar errors that are presented to human operators as suggestions of potential issues to investigate. The approach is demonstrated on one full day of data, showing promising ability in understanding the message content and providing meaningful groupings, in line with previously reported incidents by human operators.

Performing inclusion and exclusion in the peer group. Children's social organization and peer socializing practices in the classroom

This PhD thesis investigates children’s peer practices in two primary schools in Italy, focusing on the ordinary and the Italian L2 classroom. The study is informed by the paradigm of language socialization and considers peer interactions as a ‘double opportunity space’, allowing both children’s co-construction of their social organization and children’s sociolinguistic development. These two foci of attention are explored on the basis of children’s social interaction and of the verbal, embodied, and material resources that children agentively deploy during their mundane activities in the peer group. The study is based on a video ethnography that lasted nine months. Approximately 30 hours of classroom interactions were video-recorded, transcribed, and analyzed with an approach that combines the micro-analytic instruments of Conversation Analysis and the use of ethnographic information. Three main social phenomena were selected for analysis: (a) children’s enactment of the role of the teacher, (b) children’s reproduction of must-formatted rules, and (c) children’s argumentative strategies during peer conflict. The analysis highlights the centrality of the institutional frame for children’s peer interactions in the classroom. Moreover, the study illustrates that children socialize their classmates to the linguistic, social, and moral expectations of the context in and through various practices. Notably, these practices are also germane to the local negotiation of children’s social organization and hierarchy. Therefore, the thesis underlines that children’s peer interactions are both a resource for children’s sociolinguistic development and a potentially problematic locus where social exclusion is constructed and brought to bear. These insights are relevant for teachers’ professional practice. Children’s peer interactions are a resource that can be integrated in everyday didactics. Nevertheless, the role of the teacher in supervising and steering children’s peer practices appears crucial: an acritical view of children’s autonomous work, often implied in teaching methods such as peer tutoring, needs to be problematized.

Methods for integrating machine learning and constrained optimization

In the framework of industrial problems, the application of Constrained Optimization is known to have overall very good modeling capability and performance and stands as one of the most powerful, explored, and exploited tool to address prescriptive tasks. The number of applications is huge, ranging from logistics to transportation, packing, production, telecommunication, scheduling, and much more. The main reason behind this success is to be found in the remarkable effort put in the last decades by the OR community to develop realistic models and devise exact or approximate methods to solve the largest variety of constrained or combinatorial optimization problems, together with the spread of computational power and easily accessible OR software and resources. On the other hand, the technological advancements lead to a data wealth never seen before and increasingly push towards methods able to extract useful knowledge from them; among the data-driven methods, Machine Learning techniques appear to be one of the most promising, thanks to its successes in domains like Image Recognition, Natural Language Processes and playing games, but also the amount of research involved. The purpose of the present research is to study how Machine Learning and Constrained Optimization can be used together to achieve systems able to leverage the strengths of both methods: this would open the way to exploiting decades of research on resolution techniques for COPs and constructing models able to adapt and learn from available data. In the first part of this work, we survey the existing techniques and classify them according to the type, method, or scope of the integration; subsequently, we introduce a novel and general algorithm devised to inject knowledge into learning models through constraints, Moving Target. In the last part of the thesis, two applications stemming from real-world projects and done in collaboration with Optit will be presented.

Concepts and methods for efficient decentralized learning in federated settings

Deep Neural Networks (DNNs) have revolutionized a wide range of applications beyond traditional machine learning and artificial intelligence fields, e.g., computer vision, healthcare, natural language processing and others. At the same time, edge devices have become central in our society, generating an unprecedented amount of data which could be used to train data-hungry models such as DNNs. However, the potentially sensitive or confidential nature of gathered data poses privacy concerns when storing and processing them in centralized locations. To this purpose, decentralized learning decouples model training from the need of directly accessing raw data, by alternating on-device training and periodic communications. The ability of distilling knowledge from decentralized data, however, comes at the cost of facing more challenging learning settings, such as coping with heterogeneous hardware and network connectivity, statistical diversity of data, and ensuring verifiable privacy guarantees. This Thesis proposes an extensive overview of decentralized learning literature, including a novel taxonomy and a detailed description of the most relevant system-level contributions in the related literature for privacy, communication efficiency, data and system heterogeneity, and poisoning defense. Next, this Thesis presents the design of an original solution to tackle communication efficiency and system heterogeneity, and empirically evaluates it on federated settings. For communication efficiency, an original method, specifically designed for Convolutional Neural Networks, is also described and evaluated against the state-of-the-art. Furthermore, this Thesis provides an in-depth review of recently proposed methods to tackle the performance degradation introduced by data heterogeneity, followed by empirical evaluations on challenging data distributions, highlighting strengths and possible weaknesses of the considered solutions. Finally, this Thesis presents a novel perspective on the usage of Knowledge Distillation as a mean for optimizing decentralized learning systems in settings characterized by data heterogeneity or system heterogeneity. Our vision on relevant future research directions close the manuscript.

Linguagem, cultura e alteridade: imagens do outro

Language, culture, and otherness are complementary and also confliting issues representing the central debate on childhood and the child who carries the signals of social and/or ethinical of exclusion. The debate on the social still connected to universal and absolute values and trues, therefore the theme needs a reavaliation on the realm of relativism. Questioning the fact that culture and otherness are expressed by language which are not always visible and explicit, requering a close and deep look at many social realities enpoorvered suburbs and rural areas, white and black children, homeless children, we kept their voices and speaches, their images from their own drawings to understand the way the percept mean they live and they are. These children have a word for school, and also about the process and agents to say by many different ways to express how they look their own world and how the world look at them.