Gallery — Two-column

Custom Latex Document Class used exclusively by Engenius at Aveiro's University

The Observatory of Public Spending (or ODP, in Portuguese) is a special unit of Brazil's Ministry of Transparency, Monitoring and Office of the Comptroller-General (or CGU, in Portuguese) responsible for monitoring public spending and gathering managerial and audit information to support the work of CGU internal auditors. One of the most important themes monitored by this unit is Public Procurements and Government Suppliers which have won these procurement processes. Image analysis of many of these suppliers headquarters revealed suspicious landscapes, such as rural areas, isolated places or slums. These landscapes could be an indication of fake suppliers with poor capacity of delivering public goods and services. However, checking thousands of landscapes in order to find these fake suppliers would be a very expensive task. Our objective then is to discover what are the possible groups of scenes involving government suppliers, given that these images were not previously labeled, as automatically as possible. For that reason, we used Places CNN, a pretrained convolutional neural network for scene recognition presented by Zhou et al., which was trained on 205 scene categories with 2.5 million images, for scene recognition on Brazilian Government Suppliers.

Comprensión de un estudio realizado en la mica-epoxi para placas de circuitos. El estudio consistió en pruebas de resistencia para medir el desgaste en el tiempo del material y así determinar su tiempo de vida aproximado.

In this paper, we evaluate a baseline word embedding model for a set of clinical notes derived from patient records. For our baseline, we extract features for this embedding using the Word2Vec module from the gensim package. We also build two models, a word2vec skipgram model with negative sampling and a positive point-wise mutual information (PPMI) model by training on the processed clinical notes. Our evaluation shows that both the PPMI and the skipgram models show improved results for medically-related terms when compared with the baseline model. PPMI shows the best result out of all three models.

This is an IEEE based template that can be used for presenting your work on the Open Science Data Cloud. Use it for the PIRE Workshop challenge and other submissions such as the Supercomputing 2014 conference.

This paper provides a sample of a LATEX document for the NIME conference series. It conforms, somewhat loosely, to the formatting guidelines for ACM SIG Proceedings. It is an alternate style which produces a tighter-looking paper and was designed in response to concerns expressed, by authors, over page-budgets. It complements the document Author’s (Alternate) Guide to Preparing ACM SIG Proceedings Using LATEX2ε and BibTEX. This source file has been written with the intention of being compiled under LATEX2ε and BibTeX.

Template for final project reports for EEC 136AB Electronics Design Project, a senior capstone team-based design course at UC Davis.

Lab report template

This is a skeleton file demonstrating the use of IEEEtran.cls (requires IEEEtran.cls version 1.8b or later) with an IEEE Computer Society conference paper. For other IEEE conferences, please see the IEEE conference paper template, and to find additional IEEE templates please use the tags below. IEEEtran.cls version: 1.8b