Publications related to Special issue on computer graphics international 2022 part 1

Related publications (32)

A Large-Scale Characterization of How Readers Browse Wikipedia

Robert West, Tiziano Piccardi, Akhil Arora

Despite the importance and pervasiveness of Wikipedia as one of the largest platforms for open knowledge, surprisingly little is known about how people navigate its content when seeking information. To bridge this gap, we present the first systematic large ...

ASSOC COMPUTING MACHINERY2023

High-order accurate well-balanced energy stable adaptive moving mesh finite difference schemes for the shallow water equations with non-flat bottom topography

Junming Duan, Zhenying Zhang

This paper proposes high-order accurate well-balanced (WB) energy stable (ES) adaptive moving mesh finite difference schemes for the shallow water equations (SWEs) with non flat bottom topography. To enable the construction of the ES schemes on moving mesh ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

Event-based sampled ECG morphology reconstruction through self-similarity

David Atienza Alonso, Giovanni Ansaloni, Tomas Teijeiro Campo, Silvio Zanoli

Background and Objective: Event-based analog-to-digital converters allow for sparse bio-signal acquisition, enabling local sub-Nyquist sampling frequency. However, aggressive event selection can cause the loss of important bio-markers, not recoverable with ...

2023

Distributed Shadow Dynamic Consensus Optimization Framework for Power Market with Parameterization Bidding Strategy of GENCOs

Liying Yu, Sidi-Rachid Cherkaoui

This paper presents a distributed shadow dynamic consensus (DSDC) framework to address the generation company (GENCO) strategic bidding problem in the independent system operator (ISO) operation. First, each sub-group is defined according to the communicat ...

IEEE2023

Machine-learning predictor of nerve fiber firing rate allows the automatic optimization of electrical stimulation protocols

Silvestro Micera, Simone Romeni, Gabriele Marino

Computational models have been widely employed to study the electrical stimulation of the nervous system. Still, most applications either study fundamental mechanisms underlying stimulation, or address qualitative scientific questions. When quantitative qu ...

IEEE2023

A Practical Wave Optics Reflection Model for Hair and Fur

Mengqi Xia

Traditional fiber scattering models, based on ray optics, are missing some important visual aspects of fiber appearance. Previous work [Xia et al. 2020] on wave scattering from ideal extrusions demonstrated that diffraction produces strong forward scatteri ...

2023

A Stand-Alone Augmented Reality Intervention for Chronic Pain using Embodied Systolic Stimulation

Andrea Serino, Robert Leeb, Oliver Alan Kannape, Skander Mensi, Sylvain Cardin

Chronic pain presents a tremendous personal, societal, and financial burden. Treatment options are often limited to managing symptoms as opposed to treating the causes, and the consequences of pharmacological treatments can be immensely harmful as evidence ...

IEEE2023

TENET: Memory Safe and Fault Tolerant Persistent Transactional Memory

Sanidhya Kashyap, Diyu Zhou

Byte-addressable non-volatile memory (NVM) allows programs to directly access storage using memory interface without going through the expensive conventional storage stack. However, direct access to NVM makes the NVM data vulnerable to software bugs and ha ...

USENIX ASSOC2023

Filter-Informed Spectral Graph Wavelet Networks for Multiscale Feature Extraction and Intelligent Fault Diagnosis

Olga Fink

Intelligent fault diagnosis has been increasingly improved with the evolution of deep learning (DL) approaches. Recently, the emerging graph neural networks (GNNs) have also been introduced in the field of fault diagnosis with the goal to make better use o ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Passivating contact-based tunnel junction Si solar cells using machine learning for tandem cell applications

Christophe Ballif, Franz-Josef Haug, Aïcha Hessler-Wyser, Audrey Marie Isabelle Morisset

Tandem solar cells are a key technology for exceeding the theoretical efficiency limit of single-junction cells. One of the most promising combinations is the silicon-perovskite tandem cells, considering their potential for high efficiency, fabrication on ...

ELSEVIER2023

One Fuzz Doesn’t Fit All: Optimizing Directed Fuzzing via Target-tailored Program State Restriction

Mathias Josef Payer

Fuzzing is the de-facto default technique to discover software flaws, randomly testing programs to discover crashing test cases. Yet, a particular scenario may only care about specific code regions (for, e.g., bug reproduction, patch or regression testing) ...

ASSOC COMPUTING MACHINERY2022

Detailed Placement for Dedicated LUT-Level FPGA Interconnect

Paolo Ienne, Grace Zgheib, Stefan Nikolic

In this work, we develop timing-driven CAD support for FPGA architectures with direct connections between LUTs. We do so by proposing an efficient ILP-based detailed placer, which moves a carefully selected subset of LUTs from their original positions, so ...

ASSOC COMPUTING MACHINERY2022

Probabilistic Data Association for Semantic SLAM at Scale

Tony Alan Wood

With advances in image processing and machine learning, it is now feasible to incorporate semantic information into the problem of simultaneous localisation and mapping (SLAM). Previously, SLAM was carried out using lower level geometric features (points, ...

IEEE2022

The consensus number of a cryptocurrency (vol 35, pg 1, 2022)

Rachid Guerraoui, Matej Pavlovic, Dragos-Adrian Seredinschi, Matteo Monti

SPRINGER2022

PEAF: Learnable Power Efficient Analog Acoustic Features for Audio Recognition

Boris Bergsma

At the end of Moore's law, new computing paradigms are required to prolong the battery life of wearable and IoT smart audio devices. Theoretical analysis and physical validation have shown that analog signal processing (ASP) can be more power-efficient tha ...

ISCA-INT SPEECH COMMUNICATION ASSOC2022

Deep MinCut: Learning Node Embeddings by Detecting Communities

Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Chi Thang Duong

We present Deep MinCut (DMC), an unsupervised approach to learn node embeddings for graph -structured data. It derives node representations based on their membership in communities. As such, the embeddings directly provide insights into the graph structure ...

ELSEVIER SCI LTD2022

Motivating Children to Practice Perspective-Taking Through Playing Games with Cozmo

Pierre Dillenbourg

Recent studies with children have pointed out the importance of spatial thinking as an essential factor in determining later success in STEM-related fields. The current study explores the potential of using embodied activities with robots to aid the develo ...

IEEE2022

Learning Bayesian Networks in the Presence of Structural Side Information

Negar Kiyavash, Seyed Jalal Etesami, Ehsan Mokhtarian, Sina Akbari, Fateme Jamshidi

We study the problem of learning a Bayesian network (BN) of a set of variables when structural side information about the system is available. It is well known that learning the structure of a general BN is both computationally and statistically challengin ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2022

fGOT: Graph Distances Based on Filters and Optimal Transport

Pascal Frossard, Mireille El Gheche, Hermina Petric Maretic

Graph comparison deals with identifying similarities and dissimilarities between graphs. A major obstacle is the unknown alignment of graphs, as well as the lack of accurate and inexpensive comparison metrics. In this work we introduce the filter graph dis ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2022

BLOOM: Bimodal Lattice One-out-of-Many Proofs and Applications

Ngoc Khanh Karol Nguyen

We give a construction of an efficient one-out-of-many proof system, in which a prover shows that he knows the pre-image for one element in a set, based on the hardness of lattice problems. The construction employs the recent zero-knowledge framework of Ly ...

SPRINGER INTERNATIONAL PUBLISHING AG2022