Smart Portable Pen for Continuous Monitoring of Anaesthetics in Human Serum With Machine Learning

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This paper presents a comparison of machine learning (ML) methods used for three-dimensional localization of partial discharges (PD) in a power transformer tank. The study examines ML and deep learning (DL) methods, ranging from support vector machines (SV ...

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

Example Data for DeepReefMap This dataset contains input videos in MP4 format taken with GoPro Hero 10 Cameras in Reefs in the Red Sea to demonstrate the DeepReefMap tool, which is described in the paper "Scalable Semantic 3D Mapping of Coral Reefs with De ...

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

Silver is one of the most studied electrode materials for the electrochemical reduction of carbon dioxide into carbon monoxide, a product with many industrial applications. There is a growing number of reports in which silver is implemented in gas diffusio ...

This repository contains microphysics routines, scripts, and processed data from the Weather Research and Forecasting (WRF) model simulations presented in the paper "RaFSIP: Parameterizing ice multiplication in models using a machine learning approach", by ...

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

Throughout history, the pace of knowledge and information sharing has evolved into an unthinkable speed and media. At the end of the XVII century, in Europe, the ideas that would shape the "Age of Enlightenment" were slowly being developed in coffeehouses, ...

Advanced battery electrodes require a cautious design of microscale particles with built-in nanoscale features to exploit the advantages of both micro- and nano-particles relative to their performance attributes. Herein, the dynamic behavior of nanosized S ...

The space industry has experienced substantial growth in recent years, leading to rapid advancements in space exploration and space-based technologies. Consequently, the study of electronics and sensor performance in extreme environments has become crucial ...

While momentum-based accelerated variants of stochastic gradient descent (SGD) are widely used when training machine learning models, there is little theoretical understanding on the generalization error of such methods. In this work, we first show that th ...

Renewable energy sources offer a promising solution for mitigating sustainability and CO2 emissions-related issues due to their vast energy generation capacity. They enable hydrogen production via water electrolysis, as well as carbon capture and utilizati ...

Digital twins are virtual models of physical objects or systems that enable real-time monitoring and analysis. In the ﬁeld of stone masonry buildings, digital twins can be used to assess damage, predict maintenance needs, and opti- mize building performanc ...

Implanted medical devices (IMDs) have been widely developed to support the monitoring and recording of biological data inside the body or brain. Wirelessly powered IMDs, a subset of implantable electronics, have been proposed to eliminate the limitations r ...

Discovering new materials is essential but challenging, time-consuming, and expensive. In many cases, simulations can be useful for estimating material properties. For many of the most interesting properties, however, simulations are infeasible because of ...

Object detection plays a critical role in various computer vision applications, encompassing domains like autonomous vehicles, object tracking, and scene understanding. These applica- tions rely on detectors that generate bounding boxes around known object ...

With the development of modern medical techniques, the application of orthopedic implants has been continually increasing in recent years. Passive materials, such as Ti and its alloys as well as CoCrMo alloys, are widely used in artificial joints due to th ...

We propose a novel system leveraging deep learning-based methods to predict urban traffic accidents and estimate their severity. The major challenge is the data imbalance problem in traffic accident prediction. The problem is caused by numerous zero values ...

Uric acid (UA) is produced from purine metabolism and serves as a prevalent biomarker for multiple diseases including cancer. Hyperuricemia or hypouricemia can cause multiple dysfunctions throughout the biological processes. Consequently, there is a pressi ...

With the overall goal of reducing the numerical burden of uncertainty quantification involved in seismic risk assessments, this paper examines opportunities for assessment of seismic collapse capacity and risk using data-driven surrogates as a complement t ...

Smart Portable Pen for Continuous Monitoring of Anaesthetics in Human Serum With Machine Learning

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Partial discharge localization in power transformer tanks using machine learning methods

Robust machine learning for neuroscientific inference

Data for Paper "Scalable Semantic 3D Mapping of Coral Reefs with Deep Learning"

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

Rate-Determining Step for Electrochemical Reduction of Carbon Dioxide into Carbon Monoxide at Silver Electrodes

Data and scripts for the RaFSIP scheme

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Machine Learning for Modeling Stock Returns

Dynamic Behavior of Spatially Confined Sn Clusters and Its Application in Highly Efficient Sodium Storage with High Initial Coulombic Efficiency

Single-Photon Avalanche Diode Image Sensors for Harsh Radiation Environments

On the Generalization of Stochastic Gradient Descent with Momentum

Tailoring nanocatalysts and reaction interfaces for water- and CO2-electrolysis

Digital Twins of Stone Masonry Buildings for Damage Assessment

Integrated Wireless Power, Data Communication, and Thermal Sensing System for Autonomous Multisite Brain Implants

Toward data-driven materials design: From atoms to pilot plants

Improving Object Detection under Domain Shifts

In-vivo investigation of electrochemical behavior of Ti and CoCrMo alloy in human synovial fluids

From Prediction to Prevention: Leveraging Deep Learning in Traffic Accident Prediction Systems

Review on Uric Acid Recognition by MOFs with a Future in Machine Learning

Surrogate modelling for seismic collapse risk assessment of steel moment resisting frames