Collaborative inference enables resource-constrained edge devices to make inferences by uploading inputs (e.g., images) a server (i.e., cloud) where the heavy deep learning models run. While this setup works cost-effectively for successful inferences, it severely underperforms when model faces input samples on which was not trained (known as Out-of-Distribution (OOD) samples). If could, at leas...

In a complex soil environment, competitive and environmental factors interact with individual traits to influence plant’s root growth patterns ability compete for resources. Here, we examine how of focal plant, Plantago lanceolata L., responds resource heterogeneity presence two neighbor species, Centaurea jacea L.and Poa pratensis L. A full factorial experiment tested the effects nutrient hete...

This paper presents an application of the Fluid Stochastic Petri Net (FSPN) formalism for the analysis of the transfer time distribution in peer-to-peer (P2P) file sharing applications. The transfer of the resource follows a successful search; the transfer time is mainly dominated by network characteristics, application characteristics, resource characteristics, and user behavior. The proposed ...