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Felipe Costa

Publications and source records attributed to Felipe Costa.

6 recordsLinked to original sources
arXiv2025

Filters and Redundancies: An Exploration of Novel Coherent Noise Filters for High Energy Physics

This work presents radiation-tolerant implementations for the SALSA front-end readout ASIC through redundancy methods applied to two median-finding algorithms designed for coherent noise suppression. Bit-wise Median Finder (BWMF) and Combinatorial Sum Median Finder (CSMF) were implemented in TSMC \SI{65}{\nano\meter} and evaluated in terms of area, power, and latency. Three redundancy techniques were applied in this work to compare their impact: simple TMR, full TMR, and temporal TMR (TTMR). The simple and full TMR approach was applied in both algorithms to establish comparisons and TTMR was applied to CSMF as an improvement. The results indicate that the BWMF achieves efficient performance in terms of area and power under the simple TMR scheme, but exhibits significantly higher power consumption when using the more robust full TMR approach. The TTMR technique, in turn, offers reliable fault tolerance while maintaining a feasible balance between area and power.

physics.ins-det↗
arXiv2025

Using Open Source EDA Tools in ASICs for HEP: A Mixed Comparison

This work compares open-source electronic design automation tools with a commercial environment using three representative integrated circuit blocks in the IHP 130 nm open PDK: a common-mode noise filter, a finite-state machine, and a voltage-controlled oscillator. The study reports design effort and quality of results for digital logic, including area, power, and timing closure, and examines analog layout feasibility. For the finite-state machine at 50 MHz, the open-source flow reached 0.029 mm$^2$ (post-layout) and 4.37 mW (estimated) with 828 standard cells, whereas the commercial flow achieved 0.019 mm$^2$ and 2.00 mW with 497 cells, corresponding to increases of 53\% in area and 118\% in power. The common-mode noise filter totals 1.879 mm$^2$ with 1703 flip-flops at 50 MHz. The voltage-controlled oscillator occupies 0.0025 mm$^2$ and achieves a simulated maximum oscillation frequency of 2.65 GHz. The contribution is a side-by-side quantification of quality of results across digital and analog blocks in the IHP open PDK. The results indicate that open-source tools are viable for early prototyping, training, and collaboration, while commercial flows retain advantages in automation and quality of results when strict targets on power and area or precision analog layout are required.

physics.ins-det↗
arXiv2018

Improving Explainable Recommendations with Synthetic Reviews

An important task for a recommender system to provide interpretable explanations for the user. This is important for the credibility of the system. Current interpretable recommender systems tend to focus on certain features known to be important to the user and offer their explanations in a structured form. It is well known that user generated reviews and feedback from reviewers have strong leverage over the users' decisions. On the other hand, recent text generation works have been shown to generate text of similar quality to human written text, and we aim to show that generated text can be successfully used to explain recommendations. In this paper, we propose a framework consisting of popular review-oriented generation models aiming to create personalised explanations for recommendations. The interpretations are generated at both character and word levels. We build a dataset containing reviewers' feedback from the Amazon books review dataset. Our cross-domain experiments are designed to bridge from natural language processing to the recommender system domain. Besides language model evaluation methods, we employ DeepCoNN, a novel review-oriented recommender system using a deep neural network, to evaluate the recommendation performance of generated reviews by root mean square error (RMSE). We demonstrate that the synthetic personalised reviews have better recommendation performance than human written reviews. To our knowledge, this presents the first machine-generated natural language explanations for rating prediction.

cs.IR↗
arXiv2017

Automatic Generation of Natural Language Explanations

An important task for recommender system is to generate explanations according to a user's preferences. Most of the current methods for explainable recommendations use structured sentences to provide descriptions along with the recommendations they produce. However, those methods have neglected the review-oriented way of writing a text, even though it is known that these reviews have a strong influence over user's decision. In this paper, we propose a method for the automatic generation of natural language explanations, for predicting how a user would write about an item, based on user ratings from different items' features. We design a character-level recurrent neural network (RNN) model, which generates an item's review explanations using long-short term memories (LSTM). The model generates text reviews given a combination of the review and ratings score that express opinions about different factors or aspects of an item. Our network is trained on a sub-sample from the large real-world dataset BeerAdvocate. Our empirical evaluation using natural language processing metrics shows the generated text's quality is close to a real user written review, identifying negation, misspellings, and domain specific vocabulary.

cs.CL↗
arXiv2017

The Case for Pyriproxyfen as a Potential Cause for Microcephaly; From Biology to Epidemiology

The Zika virus has been found in individual cases but has not been confirmed as the cause of in the large number of cases of microcephaly in Brazil in 2015-6. Indeed, disparities between the incidence of Zika and microcephaly across geographic locations has led to questions about the virus's role. Here we consider whether the insecticide pyriproxyfen used in Brazilian drinking water might be the primary cause or a cofactor. Pyriproxifen is a juvenile hormone analog which has been shown to correspond in mammals to a number of fat soluble regulatory molecules including retinoic acid, a metabolite of vitamin A, with which it has cross-reactivity and whose application during development has been shown to cause microcephaly. Methoprene, another juvenile hormone analog approved as an insecticide in the 1970s has been shown to cause developmental disorders in mammals. Isotretinoin is another retinoid causing microcephaly via activation of the retinoid X receptor in developing fetuses. We review tests of pyriproxyfen by the manufacturer Sumitomo, which actually found some evidence for this effect, including low brain mass and arhinencephaly in exposed rat pups. Pyriproxyfen use in Brazil is unprecedented, never having been applied to a water supply on a large scale. Claims that its geographical pattern of use rule it out as a cause have not been documented or confirmed. On the other hand, the very few microcephaly cases reported in Colombia and the wide discrepancies of incidence in different states across Brazil despite large numbers of Zika cases undermine the claim that Zika is the cause. Given this combination of potential molecular mechanism, toxicological and epidemiological evidence we strongly recommend that the use of pyriproxyfen in Brazil be suspended until the potential causal link to microcephaly is investigated further.

q-bio.TO↗