BATC - A Benchmark for Aggregation Techniques in Crowdsourcing

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Electrochemical Impedance Spectroscopy (EIS) and Equivalent Circuit Models (ECMs) are widely used to characterize the impedance and estimate parameters of electrochemical systems such as batteries. We use a generic ECM with ten parameters grouped to model ...

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, ...

The ITER Electron Cyclotron Resonance Heating and Current Drive (ECRH&CD) system relies on 1 MW 170 GHz Gyrotrons to provide the mm-wave power needed for plasma heating, current drive, and magneto-hydrodynamic control. The design and modeling of the contro ...

Activity-based models offer the potential of a far deeper understanding of daily mobility behaviour than trip-based models. However, activity-based models used both in research and practice have often relied on applying sequential choice models between sub ...

The sequence-dependent statistical mechanics of double-stranded nucleic acid, or dsNA, is believed to be essential in its biological functions. In turn, the equilibrium statistical mechanics behaviour of dsNA depends strongly both on sequence-dependent per ...

The minimum amount of shear reinforcement to be provided in reinforced concrete members has been a topic of debate and research for decades without reaching a consensus. Defining such values is however instrumental to build in an economic manner and to saf ...

Augmented/virtual realities (ARs/VRs) promise to revolutionize STEM education. However, most easy-to-use tools are limited to static visualizations, which limits the approachable content, whereas more interactive and dynamic alternatives require costly har ...

Neuroscience incorporates knowledge from a range of scales, from single molecules to brain wide neural networks. Modeling is a valuable tool in understanding processes at a single scale or the interactions between two adjacent scales and researchers use a ...

Many engineering fields rely on frequency-domain dynamical systems for the mathematical modeling of physical (electrical/mechanical/etc.) structures. With the growing need for more accurate and reliable results, the computational burden incurred by frequen ...

The biophysical modeling efforts in diffusion MRI have grown considerably over the past 25 years. In this review, we dwell on the various challenges along the journey of bringing a biophysical model from initial design to clinical implementation, identifyi ...

This study evaluates and compares several machine learning methods on the effects of different parameters in lead adsorption capacity. pH, contact time, adsorbent dosage and initial lead concentration were considered as inputs and adsorption capacity was r ...

Moving from steam and waterpower, electricity and assembly lines, and computerization, to the adoption of cyber-physical systems, the Internet of Things and the Internet of Systems executed as intelligent machines, the world now dives into a new era called ...

The importance of additive manufacturing, also known as 3D printing, has grown exponentially in the recent years thanks to its high flexibility to manufacture intricate parts. This process can be divided into many different sub-categories, depending on the ...

Somatosensory thalamocortical (TC) neurons from the ventrobasal (VB) thalamus are central components in the flow of sensory information between the periphery and the cerebral cortex, and participate in the dynamic regulation of thalamocortical states inclu ...

This study evaluates and compares several machine learning methods on the effects of different parameters in the hydrothermal carbonisation (HTC) process of macroalgae Sargassum horneri. Reaction temperature, residence time, biomass particle size, the amou ...

We introduce a sequence-dependent coarse-grain model of double-stranded DNA with an explicit description of both the bases and the phosphate groups as interacting rigid-bodies. The model parameters are trained on extensive, state-of-the-art large scale mol ...

Mountain regions are considered to be the natural "water towers" of the world due to their importance as sources of many rivers. Reliable tools to estimate the availability and variability of streamflows in such regions are still rare. In this context, the ...

What-if analysis is a data-intensive exploration to inspect how changes in a set of input parameters of a model influence some outcomes. It is motivated by a user trying to understand the sensitivity of a model to a certain parameter in order to reach a se ...

Localizing the source of an epidemic is a crucial task in many contexts, including the detection of malicious users in social networks and the identification of patient zeros of disease outbreaks. The difficulty of this task lies in the strict limitation ...

BATC - A Benchmark for Aggregation Techniques in Crowdsourcing

Chattez avec Graph Search

On the use of Cramér-Rao Lower Bound for least-variance circuit parameters identification of Li-ion cells

Machine Learning for Modeling Stock Returns

Sensitivity Analysis of the Lumped Thermal Model of the EU 170 GHz Gyrotron Magnetron Injection Gun

OASIS: Optimisation-based Activity Scheduling with Integrated Simultaneous choice dimensions

cgNA plus web : A Visual Interface to the cgNA plus Sequence-dependent Statistical Mechanics Model of Double-stranded Nucleic Acids

Influence of amount of shear reinforcement and its post-yield response on the shear resistance of reinforced concrete members

MoleculARweb: A Web Site for Chemistry and Structural Biology Education through Interactive Augmented Reality out of the Box in Commodity Devices

A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience

Model order reduction based on functional rational approximants for parametric PDEs with meromorphic structure

Challenges for biophysical modeling of microstructure

Investigation of effective processes parameters on lead (II) adsorption from wastewater by biochar in mild air oxidation pyrolysis process

Broadening artificial intelligence education in K-12: Where to Start?

Operando X-ray diffraction during laser 3D printing: from machine design to experiments and computer simulations

Experimentally-constrained biophysical models of tonic and burst firing modes in thalamocortical neurons

Physico-chemical properties prediction of hydrochar in macroalgae Sargassum horneri hydrothermal carbonisation

A sequence-dependent coarse-grain model of B-DNA with explicit description of bases and phosphate groups parametrised from large scale Molecular Dynamics simulations

On flow duration curve modelling in Alpine catchments

Exploring Data Partitions for What-if Analysis

Localizing the Source of an Epidemic Using Few Observations

What-if Analysis with Conflicting Goals: Recommending Data Ranges for Exploration