Special issue on computer graphics international 2022 part 1

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Deep Reinforcement Learning for Random Access in Machine-Type Communication

Fernando Perez Cruz

Random access (RA) schemes are a topic of high interest in machine-type communication (MTC). In RA protocols, backoff techniques such as exponential backoff (EB) are used to stabilize the system to avoid low throughput and excessive delays. However, these ...

IEEE2022

Deciding Robustness for Lower SQL Isolation Levels

Christoph Koch, Bas Ketsman

While serializability always guarantees application correctness, lower isolation levels can be chosen to improve transaction throughput at the risk of introducing certain anomalies. A set of transactions is robust against a given isolation level if every p ...

ASSOC COMPUTING MACHINERY2022

Design and Optimization of Quantum Electronic Circuits

Giovanni De Micheli

Quantum electronic circuits where the logic information is processed and stored in single flux quanta promise efficient computation in a performance/power metric, and thus are of utmost interest as possible replacement or enhancement of CMOS. Several elect ...

ASSOC COMPUTING MACHINERY2022

SafeAMC: Adversarial training for robust modulation classification models

Pascal Frossard, Javier Alejandro Maroto Morales

In communication systems, there are many tasks, like modulation classification, for which Deep Neural Networks (DNNs) have obtained promising performance. However, these models have been shown to be susceptible to adversarial perturbations, namely impercep ...

IEEE2022

Lightweight HI source finding for next generation radio surveys

Jean-Paul Richard Kneib, Frédéric Courbin, Aymeric Alexandre Galan, Austin Chandler Peel, Emma Elizabeth Tolley, Mark Thomas Sargent

Future deep HI surveys will be essential for understanding the nature of galaxies and the content of the Universe. However, the large volume of these data will require distributed and automated processing techniques. We introduce LiSA, a set of python modu ...

ELSEVIER2022

Distributed Graph Learning With Smooth Data Priors

Pascal Frossard, Mireille El Gheche, Isabela Cunha Maia Nobre

Graph learning is often a necessary step in processing or representing structured data, when the underlying graph is not given explicitly. Graph learning is generally performed centrally with a full knowledge of the graph signals, namely the data that live ...

IEEE2022

Request, Coalesce, Serve, and Forget: Miss-Optimized Memory Systems for Bandwidth-Bound Cache-Unfriendly Applications on FPGAs

Paolo Ienne, Mikhail Asiatici

Applications such as large-scale sparse linear algebra and graph analytics are challenging to accelerate on FPGAs due to the short irregular memory accesses, resulting in low cache hit rates. Nonblocking caches reduce the bandwidth required by misses by re ...

ASSOC COMPUTING MACHINERY2022

Statistical Emulation of Neural Simulators: Application to Neocortical L2/3 Large Basket Cells

Idan Segev, Werner Alfons Hilda Van Geit

Many scientific systems are studied using computer codes that simulate the phenomena of interest. Computer simulation enables scientists to study a broad range of possible conditions, generating large quantities of data at a faster rate than the laboratory ...

FRONTIERS MEDIA SA2022

The TACS Model: Understanding Primary School Teachers’ Adoption of Computer Science Pedagogical Content

Francesco Mondada, Barbara Bruno, Jessica Elke Dehler Zufferey, Laila Abdelsalam El-Hamamsy, Frédérique Michèle Chessel-Lazzarotto, Sunny Jonathan Jean-Jacques Laurent Avry

Context With the introduction of computer science (CS) into curricula worldwide, teachers’ adoption of CS-pedagogical content is essential to ensure the long-term success of reform initiatives. Continuing Professional Development (CPD) programs play a key ...

2022

Tunneling Current Through a Double Quantum Dots System

Jean-Michel Sallese, Farzan Jazaeri

Electrostatically confined quantum dots in semiconductors hold the promise to achieve high scalability and reliability levels for practical implementation of solid-state qubits where the electrochemical potentials of each quantum dot can be independently c ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

SKILL: Structured Knowledge Infusion for Large Language Models

Martin Jaggi

Large language models (LLMs) have demonstrated human-level performance on a vast spectrum of natural language tasks. However, it is largely unexplored whether they can better internalize knowledge from a structured data, such as a knowledge graph, or from ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2022

Wearable Ultrasound Interface for Prosthetic Hand Manipulation

Xingchen Yang

Ultrasound can non-invasively detect muscle deformations, which has great potential applications in prosthetic hand control. This research developed a miniaturized ultrasound device that could be integrated into a prosthetic hand socket. This compact syste ...

SPRINGER INTERNATIONAL PUBLISHING AG2022