VI Workshop on Computational Data Analysis and Numerical Methods: Book of Abstracts

The VI Workshop on Computational Data Analysis and Numerical Methods (WCDANM) is going to be held on June 27-29, 2019, in the Department of Mathematics of the University of Beira Interior (UBI), Covilhã, Portugal and it is a unique opportunity to disseminate scientific research related to the areas of Mathematics in general, with particular relevance to the areas of Computational Data Analysis and Numerical Methods in theoretical and/or practical field, using new techniques, giving especial emphasis to applications in Medicine, Biology, Biotechnology, Engineering, Industry, Environmental Sciences, Finance, Insurance, Management and Administration. The meeting will provide a forum for discussion and debate of ideas with interest to the scientific community in general. With this meeting new scientific collaborations among colleagues, namely new collaborations in Masters and PhD projects are expected. The event is open to the entire scientific community (with or without communication/poster)

Energy consumption and foreign direct investment: a panel data analysis for Portugal

This research considers the relationship between energy consumption and foreign direct investment (FDI) for the period 1990-2011. As econometric strategy, we use unit root test and panel data. The empirical results illustrate that the income per capita and political globalization present a positive impact on energy consumption. The selected components of globalization (cultural, social and political) show that these variables promote Portuguese foreign direct investment. The econometric models also considered two control variables, trade openness and exchange rate. These proxies are positively correlated with FDI. The variables of income per capita and the squared income per capita validate the environmental Kuznets curve assumptions.info:eu-repo/semantics/publishedVersio

Polyglot: Distributed Word Representations for Multilingual NLP

Distributed word representations (word embeddings) have recently contributed to competitive performance in language modeling and several NLP tasks. In this work, we train word embeddings for more than 100 languages using their corresponding Wikipedias. We quantitatively demonstrate the utility of our word embeddings by using them as the sole features for training a part of speech tagger for a subset of these languages. We find their performance to be competitive with near state-of-art methods in English, Danish and Swedish. Moreover, we investigate the semantic features captured by these embeddings through the proximity of word groupings. We will release these embeddings publicly to help researchers in the development and enhancement of multilingual applications.Comment: 10 pages, 2 figures, Proceedings of Conference on Computational Natural Language Learning CoNLL'201

Collaborative method to maintain business process models updated

Business process models are often forgotten after their creation and its representation is not usually updated. This appears to be negative as processes evolve over time. This paper discusses the issue of business process models maintenance through the definition of a collaborative method that creates interaction contexts enabling business actors to discuss about business processes, sharing business knowledge. The collaboration method extends the discussion about existing process representations to all stakeholders promoting their update. This collaborative method contributes to improve business process models, allowing updates based in change proposals and discussions, using a groupware tool that was developed. Four case studies were developed in real organizational environment. We came to the conclusion that the defined method and the developed tool can help organizations to maintain a business process model updated based on the inputs and consequent discussions taken by the organizational actors who participate in the processes.info:eu-repo/semantics/publishedVersio

Learning Language Representations for Typology Prediction

One central mystery of neural NLP is what neural models "know" about their subject matter. When a neural machine translation system learns to translate from one language to another, does it learn the syntax or semantics of the languages? Can this knowledge be extracted from the system to fill holes in human scientific knowledge? Existing typological databases contain relatively full feature specifications for only a few hundred languages. Exploiting the existence of parallel texts in more than a thousand languages, we build a massive many-to-one neural machine translation (NMT) system from 1017 languages into English, and use this to predict information missing from typological databases. Experiments show that the proposed method is able to infer not only syntactic, but also phonological and phonetic inventory features, and improves over a baseline that has access to information about the languages' geographic and phylogenetic neighbors.Comment: EMNLP 201

Immigrants’ Entrepreneurial Opportunities: The Case of the Chinese in Portugal

Why do some foreign nationalities seem to have entrepreneurial initiatives and others don’t? Why do certain foreign communities tend to build an ethnic economy, and others melt in the economy of the reception country? The analysis made so far of the modes of incorporation of the different Chinese immigrant communities in Portugal allowed to evidence that, unlike what some authors defend, it is not only the cultural factors that channel immigrants into certain segments of the labour market. Several structural factors associated to these immigrants’ arrival should be considered: the immigration policy of the host society; the reasons that generated the migratory flow; the existence of a co-ethnic community in the country and its economic incorporation; the operation of social networks; the possibility to acquire capital among the community (informal resources); and the potential market of the host society. Furthermore, in Portugal, as in Southern Europe, the informal economy can be an opportunity to self-employment - not so easy in North European countries where institutional control is stronger and competition is higher.Immigrants, Entrepreneurship, Structural opportunities, Ethnic resources