Privacy Preserving and Cost Optimal Mobile Crowdsensing using Smart Contracts on Blockchain

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Generative language models (LMs) have become omnipresent across data science. For a wide variety of tasks, inputs can be phrased as natural language prompts for an LM, from whose output the solution can then be extracted. LM performance has consistently be ...

The scale and pervasiveness of the Internet make it a pillar of planetary communication, industry and economy, as well as a fundamental medium for public discourse and democratic engagement. In stark contrast with the Internet's decentralized infrastructur ...

Online platforms have banned ("deplatformed") influencers, communities, and even entire websites to reduce content deemed harmful. Deplatformed users often migrate to alternative platforms, which raises concerns about the effectiveness of deplatforming. He ...

In this paper, we consider the optimisation of a time varying scalar field by a network of agents with no gradient information. We propose a composite control law, blending extremum seeking with formation control in order to converge to the extrema faster ...

In this work we consider an online learning problem, called Online k-Clustering with Moving Costs, at which a learner maintains a set of k facilities over T rounds so as to minimize the connection cost of an adversarially selected sequence of clients. The ...

This paper proposes a tower-foot grounding system model compatible with EMT programs which might be useful for the simulation of lightning transients in overhead lines. The proposed model is based on the solution of the telegrapher's equations and the appl ...

ML-based edge devices may face memory and computational errors that affect applications' reliability and performance. These errors can be the result of particular working conditions (e.g., radiation areas in physical experiments or avionics) or could be th ...

A strategic roadmap for noncarbonized fuels is a global priority, and the reduction of carbon dioxide emissions is a key focus of the Paris Agreement to mitigate the effects of rising temperatures. In this context, hydrogen is a promising noncarbonized fue ...

The tribocorrosion mechanisms of a Ti-Nb-Zr-Ta (TNZT) alloy rubbing against a zirconia ball in a Phosphate Buffered Solution (PBS) were analyzed by considering the mechanical and chemical interactions that lead to the material degradation. To understand th ...

Time has always been a central factor in understanding the challenges of daily mobility. For a long time, and still today, methods of economic evaluation of transport projects have monetized time savings so that they can be included in the cost–benefit ana ...

Interactive mobile applications like web browsing and gaming are known to benefit significantly from low latency networking, as applications communicate with cloud servers and other users' devices. Emerging mobile channel standards have not met these needs ...

In this paper, we consider electric vehicle charging facilities that offer various levels of service, i.e., charging rates, for varying prices such that rational users choose a level of service that minimizes the total cost to themselves including an oppor ...

K-means is one of the fundamental unsupervised data clustering and machine learning methods. It has been well studied over the years: parallelized, approximated, and optimized for different cases and applications. With increasingly higher parallelism leadi ...

This work studies the power density (PD) optimization in wind farms, and its sensitivity to the available area size. A novel genetic algorithm (PDGA) is introduced, which optimizes PD and the turbine layout, by self-adapting to the PD and to the solutions ...

Background: The nature of the solid component of subsolid nodules (SSNs) can indicate tumor pathological invasiveness. However, preoperative solid component assessment still lacks a reference standard.Methods: In this retrospective study, an AI algorithm w ...

Lead halide perovskites are promising semiconducting materials for solar energy harvesting. However, the presence of heavy-metal lead ions is problematic when considering potential harmful leakage into the environment from broken cells and also from a publ ...

Natural language processing and other artificial intelligence fields have witnessed impressive progress over the past decade. Although some of this progress is due to algorithmic advances in deep learning, the majority has arguably been enabled by scaling ...

Last-mile delivery in the logistics chain contributes to congestion in urban networks due to frequent stops. Crowd-shipping is a sustainable and low-cost alternative to traditional delivery but relies heavily on the availability of occasional couriers. In ...

The industrialization of perovskite solar cells requires adequate materials and processes to make them economically viable and environmentally sustainable. Despite promising results in terms of power conversion efficiency and operational stability, several ...

In wearable-based human activity recognition (HAR) research, one of the major challenges is the large intra-class variability problem. The collected activity signal is often, if not always, coupled with noises or bias caused by personal, environmental, or ...

Privacy Preserving and Cost Optimal Mobile Crowdsensing using Smart Contracts on Blockchain

Chattez avec Graph Search

Fly-Swat or Cannon? Cost-Effective Language Model Choice via Meta-Modeling

Planetary-Scale Byzantine Fault Tolerance

Deplatforming did not decrease Parler users' activity on fringe social media

Gradient free cooperative seeking of a moving source

Efficient Online Clustering with Moving Costs

Tower-foot grounding model for EMT programs based on transmission line theory and Marti's model

Hardware-Software co-design Methodologies for Edge AI Optimization

Updates on Hydrogen Value Chain: A Strategic Roadmap

Current and friction transients during tribocorrosion of a biomedical titanium alloy sliding against zirconia

Appropriations and Uses of Travel Time

DChannel: Accelerating Mobile ApplicationsWith Parallel High-bandwidth and Low-latency Channels

Sensitivity to user mischaracterizations in electric vehicle charging

Improving K-means Clustering Using Speculation

Wind farm power density optimization according to the area size using a novel self-adaptive genetic algorithm

Deep learning-based solid component measuring enabled interpretable prediction of tumor invasiveness for lung adenocarcinoma

Lead immobilization for environmentally sustainable perovskite solar cells

Text Representation Learning for Low Cost Natural Language Understanding

A continuum approximation approach to the depot location problem in a crowd-shipping system

Nanocrystalline Flash Annealed Nickel Oxide for Large Area Perovskite Solar Cells

Learning Disentangled Behaviour Patterns for Wearable-based Human Activity Recognition