Striving Intentionalities: Vision and Practice in Cloughjordan Eco-village

Eco-villages are intentional communities whose ultimate purpose is to provide alternative ways of living that are locally rooted, self-reliant, socially supportive, and ecologically sustainable. The issues that hinder these communities from realizing their vision and aspirations are the main draw of this study. Grounded in a six-month fieldwork, the present inquiry focuses on a particular intentional community project which is still at an early stage of implementation—Cloughjordan Eco-village (CEV). Accordingly, the forthcoming analysis and discussion endeavours, on the one, to grasp and interpret CEV’s vision in the light of the intentional communalism canon and different currents of green thinking and, on the other, to identify and comprehend some of the issues that have been challenging the translation of the enterprise’s aspirations into practice

Risk factors and outcomes associated to low birth weight

Orientador: Jose Guilherme CecattiDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Ciencias MedicasResumo: Introdução: O baixo peso (BP) ao nascimento (20 weeks whose weight ranged between 500 and 3,999g were included in the analysis. Stillbirths, twins and those cases with missing weight information were excluded. The newborns were divided into two groups: 1) LBW (<2,500g) and 2) normal birth weight (between 2,500 and 3,999g). Bivariate and multiple regression analysis determined the crude and adjusted odds ratios (OR) and risk ratios (RR) with their corresponding 95%CI for the association of LBW with its risk factors and outcomes, respectively. Results: Age, poor education, low maternal pre pregnancy weight, smoking beyond the fourth month of pregnancy, previous cesarean section, interdelivery interval =24 months and =37 months, maternal history of hypertension, cardiopathy and preterm delivery, few prenatal visits (=5) and late beginning prenatal care (after the 3rd month), premature rupture of membranes, increased blood pressure, infectious diseases and hemorrhages during current pregnancy were all associated with low birth weight. Maternal obesity and being a primigravida were found to be protective factors. LBW infants showed more often signs of perinatal compromise such as abnormal amniotic fluid (especially olygohydramnios), nonreassuring patterns of fetal heart rate, malformation, lower Apgar scores and lower gestational age at birth. They were associated with a greater risk of labor induction and cesarean delivery, but lower risk of forceps. Conclusion: There was a clear association between LBW and unfavorable maternal and neonatal outcomes. The LBW determinants in this population are mostly in accordance with the findings of previous studies. Many of the risk factors are modifiable or may be clinically controlled, which reinforces the importance of preconceptual counseling, the implementation of primary and secondary prevention of maternal morbidities and adequate prenatal care. Also worth mentioning is the importance of better labor surveillance in high risk pregnancies, especially women carrying growth restricted fetuses or presenting preterm laborMestradoTocoginecologiaMestre em Tocoginecologi

Situated web portal for local awareness and transient interaction

When used as part of a larger ubiquitous computing infrastructure, public displays have a great potential for enriching transitional spaces. They can enable brief encounters with information that is relevant for their specific situation, improving local awareness, promoting information sharing and enabling new and much engaging user experiences. The research presented in this paper introduces the concept of situated portal as being a web portal of situational relevant information, targeted for the public display and using large screens or wall projections,. In this paper we will briefly describe the architecture of our system, our initial prototype and our early results. Building in our experience of creating this system we then describe some of the main open issues that we plan to address in a multi-disciplinary research project

Automotive Interior Sensing - Anomaly Detection

Com o surgimento dos veículos autónomos partilhados não haverá condutores nos veículos capazes de manter o bem-estar dos passageiros. Por esta razão, é imperativo que exista um sistema preparado para detetar comportamentos anómalos, por exemplo, violência entre passageiros, e que responda de forma adequada. O tipo de anomalias pode ser tão diverso que ter um "dataset" para treino que contenha todas as anomalias possíveis neste contexto é impraticável, implicando que algoritmos tradicionais de classificação não sejam ideais para esta aplicação. Por estas razões, os algoritmos de deteção de anomalias são a melhor opção para construir um bom modelo discriminativo. Esta dissertação foca-se na utilização de técnicas de "deep learning", mais precisamente arquiteturas baseadas em "Spatiotemporal auto-encoders" que são treinadas apenas com sequências de "frames" de comportamentos normais e testadas com sequências normais e anómalas dos "datasets" internos da Bosch. O modelo foi treinado inicialmente com apenas uma categoria das ações não violentas e as iterações finais foram treinadas com todas as categorias de ações não violentas. A rede neuronal contém camadas convolucionais dedicadas à compressão e descompressão dos dados espaciais; e algumas camadas dedicadas à compressão e descompressão temporal dos dados, implementadas com células LSTM ("Long Short-Term Memory") convolucionais, que extraem informações relativas aos movimentos dos passageiros. A rede define como reconstruir corretamente as sequências de "frames" normais e durante os testes, cada sequência é classificada como normal ou anómala de acordo com o seu erro de reconstrução. Através dos erros de reconstrução são calculados os "regularity scores" que indicam a regularidade que o modelo previu para cada "frame". A "framework" resultante é uma adição viável aos algoritmos tradicionais de reconhecimento de ações visto que pode funcionar como um sistema que serve para detetar ações desconhecidas e contribuir para entender o significado de tais interações humanas.With the appearance of SAVs (Shared Autonomous Vehicles) there will no longer be a driver responsible for maintaining the car interior and well-being of passengers. To counter this, it is imperative to have a system that is able to detect any abnormal behaviours, e.g., violence between passengers, and trigger the appropriate response. Furthermore, the type of anomalous activities can be so diverse, that having a dataset that incorporates most use cases is unattainable, making traditional classification algorithms not ideal for this kind of application. In this sense, anomaly detection algorithms are a good approach in order to build a discriminative model. Taking this into account, this work focuses on the use of deep learning techniques, more precisely Spatiotemporal auto-encoder based frameworks, which are trained on human behavior video sequences and tested on use cases with normal and abnormal human interactions from Bosch's internal datasets. Initially, the model was trained on a single non-violent action category. Final iterations considered all of the identified non-violent actions as normal data. The network architecture presents a group of convolutional layers which encode and decode spatial data; and a temporal encoder/decoder structure, implemented as a convolutional Long Short Term Memory network, responsible for learning motion information. The network defines how to properly reconstruct the 'normal' frame sequences and during testing, each sequence is classified as normal or abnormal based on its reconstruction error. Based on these values, regularity scores are inferred showing the predicted regularity of each frame. The resulting framework is a viable addition to traditional action recognition algorithms since it can work as a tool for detecting unknown actions, strange/abnormal behaviours and aid in understanding the meaning of such human interactions

Restructuring the Software Architecture: A Case Study of the CoolBiz Core Banking Platform

As the structural engineering underpins the resilience of a city built on an active geological fault, software architecture becomes crucial in an increasingly digital society. This paper investigates the challenges of rigid, low cohesion software structures through a detailed case study of the CoolBiz Platform, an integrated Core Banking solution. The platform currently faces significant issues in its service support framework, including low flexibility, unsatisfactory cohesion, non-adherence to SOLID principles, absence of unit tests, and lack of documentation. This study aims to describe the planning and implementation of a new event-driven architecture for the CoolBiz Platform. This architecture is expected to not only resolve current technical challenges but also bring significant business benefits, such as the implementation of language agnosticism, a strategy aimed at facilitating talent recruitment and retention by not limiting recruitment to expertise in a specific programming language

A risk management framework for user-generated content on public display systems

Digital public displays can represent a powerful medium for personal expression and situated communication. However, before they can actually serve as an effective communication medium, they need to move towards more open models, in which user-generated content can play a more prominent role in their relevance and value proposition. The key challenge, however, is how to share control with users while being able to guarantee that published content matches the social expectations of a place and the goals of the display owner. In this study, we explore a risk management methodology as a comprehensive approach to this issue. We propose a framework that supports the systematic elicitation of the risks involved, their prioritisation, and the selection of the specific combination of moderation techniques that is able to reduce risk to a level that is deemed acceptable, while minimising the moderation effort and the impact on the willingness of users to publish their content. With this overall framework, we expect to help display owners to reason about the moderation needs of their displays and the best mapping between those needs and various moderation techniques.This work has been supported by FCT-Fundacao para a Ciencia e Tecnologia-within the Project Scope: UID/CEC/00319/2019

Media sharing in an open network of place-based displays

In this study, we aim to uncover emerging media practices for open place-based displays and understand how people appropriate the opportunities created by this new medium. Based on usage data from 43 displays, we study the role played by different publication paradigms, more specifically subscription of pre-defined content channels, integration of arbitrary content sources from social media and direct media creation. The results suggest that these different publication paradigms can all play an important role in an open model for public displays and that they complement each other in a very flexible way. This seems to confirm that openness can represent an important step towards more effective and more relevant uses of large screen displaysProject 11304 (16/SI/2015) , supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF)info:eu-repo/semantics/publishedVersio

Podcast in music education: report of an experiment

Neste artigo vamos apresentar uma experiência pedagógica realizada no corrente ano lectivo na disciplina de Educação Musical. Nesta experiência foram exploradas as várias potencialidades do podcast no processo de ensino e aprendizagem na Educação Musical. Para o efeito foi criado um podcast, no qual foram desenvolvidas diversas actividades, tornando os alunos produtores e consumidores da informação na Web. In this article we present a pedagogical experience held this year in the discipline of Music Education. With this experience, we explored various possibilities of the podcast in the process of teaching and learning in Music Education. For this experience, we created a podcast, in which we developed various activities, making the students producers and consumers of information on the Web

Developing a tangible interface for storytelling

This paper describes a first study of a paper based interface, consisting of a large format book and a set of picture cards that children can use to create stories. The handling of the picture cards has shown to be highly motivating and engaging, helping children to build a storyline creating logical relations among different characters and objects. The interface has shown to be an experimental space where children can play with the language and simultaneously reflect over it, in a collaborative process. We present the data collected with a group of five years old preschoolers and report our findings regarding the interaction design, as well as a reflection over future work.FC