Collaboration and abstract representations: towards predictive models based on raw speech and eye-tracking data

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Computing servers have played a key role in developing and processing emerging compute-intensive applications in recent years. Consolidating multiple virtual machines (VMs) inside one server to run various applications introduces severe competence for limi ...

A frequency scaling governor is critical for the performance management of cloud servers, as it enhances energy efficiency and helps to control operational temperatures, thereby ensuring system reliability. However, our in-depth analysis of the application ...

The acquisition of survey responses is a crucial component in conducting research aimed at comprehending public opinion. However, survey data collection can be arduous, time-consuming, and expensive, with no assurance of an adequate response rate. In this ...

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MALTA is a depleted monolithic active pixel sensor (DMAPS) developed in the Tower Semiconductor 180-nm CMOS imaging process. Monolithic CMOS sensors offer advantages over current hybrid imaging sensors in terms of both increased tracking performance due to ...

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Personalized ranking methods are at the core of many systems that learn to produce recommendations from user feedbacks. Their primary objective is to identify relevant items from very large vocabularies and to assist users in discovering new content. These ...

Over the past decade, interatomic potentials based on machine learning (ML) techniques have become an indispensable tool in the atomic-scale modeling of materials. Trained on energies and forces obtained from electronic-structure calculations, they inherit ...

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An attempt is made to translate five generic key performance indicators (KPIs) into a continuous real-time cost function in a batch order-based manufacturing environment. The challenge of controlling and optimizing resource utilization, production efficien ...

Collaboration and abstract representations: towards predictive models based on raw speech and eye-tracking data

Chat with Graph Search

On the added value of sequential deep learning for the upscaling of evapotranspiration

CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds

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Predicting Survey Response with Quotation-based Modeling: A Case Study on Favorability towards the United States

Dynamic power budget redistribution under a power cap on multi-application environments

The Case for Performance Interfaces for Hardware Accelerators

Radiation Hardness of MALTA2, a Monolithic Active Pixel Sensor for Tracking Applications

Thermal Design of a Medium Voltage Modular Multilevel Converter Cell

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

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An Integrated Approach to Designing Robust Turbocompressors on Gas Bearings Through Surrogate Modeling and Constrained Multi-Objective Optimization

Textual Explanations and Critiques in Recommendation Systems

Humans are Poor Few-Shot Classifiers for Sentinel-2 Land Cover

Auto-tuning ensemble models for estimating shear resistance of headed studs in concrete

Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs

Financial Risk Management with Machine Learning

Dynamic Personalized Ranking

Beyond potentials: Integrated machine learning models for materials

Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU

Cost-Based Decision Support System: A Dynamic Cost Estimation of Key Performance Indicators in Manufacturing