Articles

Bayesian model fusion: Enabling test cost reduction of analog/RF circuits via wafer-level spatial variation modeling

Zhang S., Li X., Blanton R.D.S., Da Silva J.M., Carulli J.M., Butler K.M.

Proceedings - International Test Conference

2015

Abstract:

In this paper, a novel Bayesian model fusion (BMF) method is proposed for test cost reduction based on wafer-level spatial variation modeling. BMF relies on the assumption that a large number of wafers of the same circuit design (e.g., all wafers from the same lot) share a similar spatial pattern. Hence, the measurement data from one wafer can be borrowed to model the spatial variation of other wafers via Bayesian inference. By applying the Sherman-Morrison-Woodbury formula, a fast numerical algorithm is derived to reduce the computational cost of BMF for practical test applications. Furthermore, a new test methodology is developed based on BMF and it closely monitors the escape rate and yield loss. As is demonstrated by the wafer probe measurement data of an industrial RF transceiver, BMF achieves 1.125× reduction in test cost and 2.6× reduction in yield loss, compared to the conventional approach based on virtual probe (VP).

Behavioral polymorphism and parametricity in session-based communication

Caires L., Perez J.A., Pfenning F., Toninho B.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2013

Abstract:

We investigate a notion of behavioral genericity in the context of session type disciplines. To this end, we develop a logically motivated theory of parametric polymorphism, reminiscent of the Girard-Reynolds polymorphic λ-calculus, but casted in the setting of concurrent processes. In our theory, polymorphism accounts for the exchange of abstract communication protocols and dynamic instantiation of heterogeneous interfaces, as opposed to the exchange of data types and dynamic instantiation of individual message types. Our polymorphic session-typed process language satisfies strong forms of type preservation and global progress, is strongly normalizing, and enjoys a relational parametricity principle. Combined, our results confer strong correctness guarantees for communicating systems. In particular, parametricity is key to derive non-trivial results about internal protocol independence, a concurrent analogous of representation independence, and non-interference properties of modular, distributed systems.

BERT Embeddings Can Track Context in Conversational Search

Ferreira R., Semedo D., Magalhães J.

arXiv

2021

Abstract:

The use of conversational assistants to search for information is becoming increasingly more popular among the general public, pushing the research towards more advanced and sophisticated techniques. In the last few years, in particular, the interest in conversational search is increasing, not only because of the generalization of conversational assistants but also because conversational search is a step forward in allowing a more natural interaction with the system. In this work, the focus is on exploring the context present of the conversation via the historical utterances and respective embeddings with the aim of developing a conversational search system that helps people search for information in a natural way. In particular, this system must be able to understand the context where the question is posed, tracking the current state of the conversation and detecting mentions to previous questions and answers. We achieve this by using a context-tracking component based on neural query-rewriting models. Another crucial aspect of the system is to provide the most relevant answers given the question and the conversational history. To achieve this objective, we used a Transformer-based re-ranking method and expanded this architecture to use the conversational context. The results obtained with the system developed showed the advantages of using the context present in the natural language utterances and in the

Beyond blocks: Hyperbolic community detection

Araujo M., Gunnemann S., Mateos G., Faloutsos C.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2014

Abstract:

What do real communities in social networks look like? Community detection plays a key role in understanding the structure of real-life graphs with impact on recommendation systems, load balancing and routing. Previous community detection methods look for uniform blocks in adjacency matrices. However, after studying four real networks with ground-truth communities, we provide empirical evidence that communities are best represented as having an hyperbolic structure. We detail HyCoM – the Hyperbolic Community Model – as a better representation of communities and the relationships between their members, and show improvements in compression compared to standard methods. We also introduce HyCoM-FIT, a fast, parameter free algorithm to detect communities with hyperbolic structure. We show that our method is effective in finding communities with a similar structure to self-declared ones. We report findings in real social networks, including a community in a blogging platform with over 34 million edges in which more than 1000 users established over 300 000 relations.

Beyond the Self: Using Grounded Affordances to Interpret and Describe Others’ Actions

Saponaro G., Jamone L., Bernardino A. , Salvi G.

IEEE Transactions on Cognitive and Developmental Systems

2019

Abstract:

We propose a developmental approach that allows a robot to interpret and describe the actions of human agents by reusing previous experience. The robot first learns the association between words and object affordances by manipulating the objects in its environment. It then uses this information to learn a mapping between its own actions and those performed by a human in a shared environment. It finally fuses the information from these two models to interpret and describe human actions in light of its own experience. In our experiments, we show that the model can be used flexibly to do inference on different aspects of the scene. We can predict the effects of an action on the basis of object properties. We can revise the belief that a certain action occurred, given the observed effects of the human action. In an early action recognition fashion, we can anticipate the effects when the action has only been partially observed. By estimating the probability of words given the evidence and feeding them into a pre-defined grammar, we can generate relevant descriptions of the scene. We believe that this is a step towards providing robots with the fundamental skills to engage in social collaboration with humans.

Bi-Phasic Ag–In–Ga-Embedded Elastomer Inks for Digitally Printed, Ultra-Stretchable, Multi-layer Electronics

Pedro Alhais Lop , Daniel Félix Fernandes, André F. Silva, Daniel Green Marques, Aníbal T. de Almeida, Carmel Majidi, and Mahmoud Tavakoli

ACS Applied Materials & Interfaces

2021

Abstract:

A bi-phasic ternary Ag–In–Ga ink that demonstrates high electrical conductivity, extreme stretchability, and low electromechanical gauge factor (GF) is introduced. Unlike popular liquid metal alloys such as eutectic gallium–indium (EGaIn), this ink is easily printable and nonsmearing and bonds strongly to a variety of substrates. Using this ink and a simple extrusion printer, the ability to perform direct writing of ultrathin, multi-layer circuits that are highly stretchable (max. strain >600%), have excellent conductivity (7.02 × 105 S m–1), and exhibit only a modest GF (0.9) related to the ratio of percent increase in trace resistance with mechanical strain is demonstrated. The ink is synthesized by mixing optimized quantities of EGaIn, Ag microflakes, and styrene-isoprene block copolymers, which functions as a hyperelastic binder. When compared to the same composite without EGaIn, the Ag–In–Ga ink shows over 1 order of magnitude larger conductivity, up to ∼27× lower GF, and ∼5× greater maximum stretchability. No significant change over the resistance of the ink was observed after 1000 strain cycles. Microscopic analysis shows that mixing EGaIn and Ag microflakes promotes the formation of AgIn2 microparticles, resulting in a cohesive bi-phasic ink. The ink can be sintered at room temperature, making it compatible with many heat-sensitive substrates. Additionally, utilizing a simple commercial extrusion based printer, the ability to perform stencil-free, digital printing of multi-layer stretchable circuits over various substrates, including medical wound-dressing adhesives, is demonstrated for the first time.

Bi-Phasic Ag–In–Ga-Embedded Elastomer Inks for Digitally Printed, Ultra-Stretchable, Multi-layer Electronics

Lopes P., Fernandes D., Silva A., Marques D., Almeida A., Majidi C., Tavakoli M.

ACS Appl. Mater. Interfaces

2021

Abstract:

A bi-phasic ternary Ag–In–Ga ink that demonstrates high electrical conductivity, extreme stretchability, and low electromechanical gauge factor (GF) is introduced. Unlike popular liquid metal alloys such as eutectic gallium–indium (EGaIn), this ink is easily printable and nonsmearing and bonds strongly to a variety of substrates. Using this ink and a simple extrusion printer, the ability to perform direct writing of ultrathin, multi-layer circuits that are highly stretchable (max. strain >600%), have excellent conductivity (7.02 × 105 S m–1), and exhibit only a modest GF (0.9) related to the ratio of percent increase in trace resistance with mechanical strain is demonstrated. The ink is synthesized by mixing optimized quantities of EGaIn, Ag microflakes, and styrene-isoprene block copolymers, which functions as a hyperelastic binder. When compared to the same composite without EGaIn, the Ag–In–Ga ink shows over 1 order of magnitude larger conductivity, up to ∼27× lower GF, and ∼5× greater maximum stretchability. No significant change over the resistance of the ink was observed after 1000 strain cycles. Microscopic analysis shows that mixing EGaIn and Ag microflakes promotes the formation of AgIn2 microparticles, resulting in a cohesive bi-phasic ink. The ink can be sintered at room temperature, making it compatible with many heat-sensitive substrates. Additionally, utilizing a simple commercial extrusion based printer, the ability to perform stencil-free, digital printing of multi-layer stretchable circuits over various substrates, including medical wound-dressing adhesives, is demonstrated for the first time.

Bi-virus SIS epidemics over networks: Qualitative analysis

Santos A., Moura J.M.F., Xavier J.M.F.

IEEE Transactions on Network Science and Engineering

2015

Abstract:

The paper studies the qualitative behavior of a set of ordinary differential equations (ODE) that models the dynamics of bi-virus epidemics over bilayer networks. Each layer is a weighted digraph associated with a strain of virus; the weights gzίrepresent the rates of infection from node i to node j of strain z. We establish a sufficient condition on the g’s that guarantees survival of the fittest-only one strain survives. We propose an ordering of the weighted digraphs, the *-order, and show that if the weighted digraph of strain y is *-dominated by the weighted digraph of strain x, then y dies out in the long run. We prove that the orbits of the ODE accumulate to an attractor that captures the survival of the fittest phenomenon. Due to the coupled nonlinear high-dimension nature of the ODEs, there is no natural Lyapunov function to study their global qualitative behavior. We prove our results by combining two important properties of these ODEs: (i) monotonicity under a partial ordering on the set of graphs; and (ii) dimension-reduction under symmetry of the graphs. Property (ii) allows us to fully address the survival of the fittest for regular graphs. Then, by bounding the epidemics dynamics for generic networks by the dynamics on regular networks, we prove the result for general networks

BP2EP – Adaptation of Brazilian Portuguese texts to European Portuguese

Marujo L., Grazina N., Luis T., Ling W., Coheur L., Trancoso I.

Proceedings of the 15th International Conference of the European Association for Machine Translation, EAMT 2011

2011

Abstract:

This paper describes a method to effi-ciently leverage Brazilian Portuguese re-sources as European Portuguese resources. Brazilian Portuguese and European Por-tuguese are two Portuguese varieties that are very close and usually mutually in-telligible, but with several known differ-ences, which are studied in this work. Based on this study, we derived a rule based system to translate Brazilian Por-tuguese resources. Some resources were enriched with multiword units retrieved semi-automatically from phrase tables cre-ated using statistical machine translation tools. Our experiments suggest that ap-plying our translation step improves the translation quality between English and Portuguese, relatively to the same process without this adaptation step.