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Studies of cybersickness (CS) often require a significant invest- ment in creating the primary VR environment and other experiment- related features. In addition, minor differences in VR content in independent studies may lead to opposite results. This mot ...

Acoustic emission (AE) monitoring is a useful technique to monitor the health of a structure continuously, helping to prevent potential failure. AE are elastic waves produced and emitted during fracture processes inside a material and are recorded by senso ...

Accessing input data is a critical operation in data analytics: i) slow data access significantly degrades performance, and ii) storing everything in the fastest medium, i.e., memory, incurs high operational and hardware costs. Further, while GPUs offer in ...

Lawful Interception (LI) is a legal obligation of Communication Service Providers (CSPs) to provide interception capabilities to Law Enforcement Agencies (LEAs) in order to gain insightful data from network communications for criminal proceedings, e.g., ne ...

Data-driven techniques are increasingly used to replace electronic-structure calculations of matter. In this context, a relevant question is whether machine learning (ML) should be applied directly to predict the desired properties or combined explicitly w ...

Electrochemical sensors play a pivotal role in advancing therapeutic drug monitoring (TDM) and personalized therapy. However, the insufficient selectivity of electrochemical sensors based on cytochromes P450 poses a great need for innovative machine learni ...

SwissCovid is the Swiss digital contact tracing app, which was deployed to help fighting against the COVID-19 pandemic. After a year of activity, it is high time to evaluate how effective it has been in its mission. At the highest peak, about 22% of the Sw ...

The creation of high fidelity synthetic data has long been an important goal in machine learning, particularly in fields like finance where the scarcity of available training and test data make it difficult to utilize many of the deep learning techniques w ...

We present the first public release of ShapePipe, an open-source and modular weak-lensing measurement, analysis, and validation pipeline written in Python. We describe the design of the software and justify the choices made. We provide a brief description ...

Computing servers play a key role in the development and process of emerging compute-intensive applications in recent years. However, they need to operate efficiently from an energy perspective viewpoint, while maximizing the performance and lifetime of th ...

Water is a crucial resource for all forms of life, yet it is becoming increasingly scarce. A significant portion of water loss in urban and industrial areas is attributed to leaks. Addressing this issue is critical for enhancing efficiency, sustainability, ...

In order to develop sustainable and more powerful information technology (IT) infrastructures, the challenges posed by the "memory wall" are critical for the design of high-performance and high-efficiency many-core computing systems. In this context, recen ...

This work presents a novel hybrid (physics- and data -driven) model for short-term (intra-day and day-ahead, 3h -24h) wind power forecasting (STWPF). Traditionally, STWPF predictors admitted very few meteorological variables only from the grid points close ...

Faster Parallel Training of Word Embeddings

Chattez avec Graph Search

Cybersickness assessment framework(CSAF): An Open Source Repository for Standardized Cybersickness Experiments

Automatic and high-precision acoustic emission-based structural health monitoring of concrete structures

HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

P3LI5: Practical and confidEntial Lawful Interception on the 5G core

Electronic Excited States from Physically Constrained Machine Learning

Identification and Quantification of Multiple Drugs by Machine Learning on Electrochemical Sensors for Therapeutic Drug Monitoring

SwissCovid in the Perspective of Its Goals

Macroeconomic Conditioned Synthetic Financial Markets

ShapePipe: A modular weak-lensing processing and analysis pipeline

Reinforcement Learning-Based Joint Reliability and Performance Optimization for Hybrid-Cache Computing Servers

A two-phase approach for leak detection and localization in water distribution systems using wavelet decomposition and machine learning

Full System Exploration of On-Chip Wireless Communication on Many-Core Architectures

A hybrid physics-based and data-driven model for intra-day and day-ahead wind power forecasting considering a drastically expanded predictor search space