iPaaS in Agriculture 4 0 An Industrial Case

Current automation approaches in the Industry 4.0 have generated increased interest in the utilization of Integration Platforms as a Service (iPaaS) cloudarchitectures . Existing iPaaS solutions present severalout-of-the-box connectors and automation engines for easier integration of customers’ projects, but show issues regarding overall adaptation outside their scope, brand locking, and occasionally high prices .…

Adaptive Shielding under Uncertainty

Previous works create so-called shields that correct an existing controller for the agent if it is about to take unbearable safety risks . This paper targets control problems that exhibit specific safety and performance requirements . The shield is independent of the controller, which may, for instance, take the form of a high-performing reinforcement learning agent .…

Orthogonal Decomposition of Tensor Trains

In this paper we study the problem of recovering a tensor networkdecomposition of a given tensor . In which the tensors at thevertices of the network are orthogonally decomposable, we show how to recover the decomposition by considering random linear combinations of slices .…

Convergence of the Finite Volume Method on Unstructured Meshes for a 3D Phase Field Model of Solidification

We present a convergence result for the finite volume method applied to an aparticular phase field problem suitable for simulation of pure substancesolidification . The model consists of the heat equation and the phase fieldequation with a general form of the reaction term which encompasses a variety of existing models governing dendrite growth and elementary interface trackingproblems .…

Multiscale Elliptic PDEs Upscaling and Function Approximation via Subsampled Data

There is an intimate connection between numerical upscaling of multiscalePDEs and scattered data approximation of heterogeneous functions . The lengthscale of the coarse data, which we refer to as the subsampledlengthscale, influences the accuracy of recovery, given limited computationalbudgets . We introduce a singular weight function to deal with it, both theoretically andnumerically.…

VECMAtk A Scalable Verification Validation and Uncertainty Quantification Toolkit for Scientific Simulations

VECMA toolkit (VECMAtk) is a flexible software environment for single and multiscale simulations . It introduces directly applicable andusable procedures for verification, validation (V&V), sensitivity analysis(SA) and uncertainty quantification (UQ) It enables users to verify keyaspects of their applications, systematically compare and validate the simulation outputs against observational or benchmark data, and run simulations on any platform from the desktop to current multi-petascalecomputers .…

Finding descending sequences through ill founded linear orders

In this work we investigate the Weihrauch degree of the problem of finding an infinite descending sequence through a given ill-founded linearorder . We show that the problem is rather weak in terms of uniform computational strength . We then generalize the problem by considering$\boldsymbol{\Gamma}$-presented orders, where $Gamma$ is a Borelpointclass .…

Adaptive Subcarrier Parameter and Power Allocation for Partitioned Edge Learning Over Broadband Channels

A main edge learning paradigm, called partitioned edge learning (PARTEL), is considered . It supports the distributed training of a large-scale AI model bydynamically partitioning the model and allocating the resultant parametricblocks to different devices for updating . Devices upload the updates to aserver where they are assembled and applied to updating the model .…

Two dimensional Fourier Continuation and applications

This paper presents a “two-dimensional Fourier Continuation” method (2D-FC) The approach can bedirectly generalized to domains of any given dimensionality, and even tonon-smooth domains, but such generalizations are not considered here . The method produces “blending-to-zero along normals” for the given function values .…

On Optimal Pointwise in Time Error Bounds and Difference Quotients for the Proper Orthogonal Decomposition

In this paper, we resolve several long standing issues dealing with optimalpointwise in time error bounds for proper orthogonal decomposition (POD)reduced order modeling of the heat equation . We study the roleplayed by difference quotients (DQs) in obtaining reduced order model (ROM)error bounds that are optimal with respect to both the time discretization error and the ROM discretizization error .…

Dissecting Hessian Understanding Common Structure of Hessian in Neural Networks

Hessian captures important properties of the deep neural network losslandscape . Eigenvectors and eigenspaces of the layer-wiseHessian for neural network objective have several interesting structures . Kroneckerfactorization can be combined with PAC-Bayes techniques to get better explicitgeneralization bounds . Our new understandingcan also explain why some of these structures become weaker when the network is trained with batch normalization.…

Strategies for Integrating Controls Flows in Software Defined In Vehicle Networks and Their Impact on Network Security

Current In-Vehicle Networks (IVNs) connect Electronic Control Units (ECUs)via domain busses . A gateway forwards messages between these domains . Software-Defined-Networking (SDN) has been identified as a useful buildingblock of the vehicular domain . We find visibility ofautomotive control flows within packet headers is essential for the network infrastructure to enable isolation and access control .…

Efficient Real Time Radial Distortion Correction for UAVs

In this paper we present a novel algorithm for onboard radial distortioncorrection for unmanned aerial vehicles (UAVs) We propose a fast and robust minimal solver for estimating the focal length, radial distortion profile and motion parameters from homographies . The proposed solver is tested on both synthetic and real data, and perform better or on par with state-of-the-art methods relying on pre-calibration procedures .…

Testing Differential Privacy with Dual Interpreters

DPCheck is the first fully automated framework to distinguish correct and buggy implementations of PrivTree, a probabilistically terminating algorithm that has not previously been mechanically checked . The framework requires no programmer annotations, handles all previously verified or tested algorithms .…

Randomized Overdrive Neural Networks

By processing audio signals in the time-domain with randomly weighted convolutional networks, we uncover a wide range of novel, yet controllable overdrive effects . These effects range from conventional overdrive anddistortion, to more extreme effects, as the receptive field grows, similar to afusion of distortion, equalization, delay, and reverb .…

5G Network Slice Isolation with WireGuard and Open Source MANO A VPNaaS Proof of Concept

The OSM-WireGuard framework provides up to 5.3 times higher network throughput and up to 41% lower latency compared to OpenVPN . OSM instantiates WireGuard-enabled services upand running in 4 min 26 sec, with potential the initialization time to go downto 2 min 44 sec if the operator prepares images with a pre-installed and updated version of WireGuard before the on-boarding process .…

Affine Invariant Robust Training

The field of adversarial robustness has attracted significant attention in machine learning . It aims at training models that are accurate for worst case inputs, hence it yields more robust and reliable models . The proposed method effectively yields robust models and allows introducing non-parametric adversarial perturbations, such as affine transformations, which were already considered in machine-learning within data augmentation .…

FastVC Fast Voice Conversion with non parallel data

FastVC is based on a conditionalAutoEncoder (AE) trained on non-parallel data and requires no annotations . Model’s latent representation is shown to be speaker-independent andsimilar to phonemes, which is a desirable feature for VC systems . Despite the simple structure of the proposed model, it outperforms the VC Challenge 2020 baselines on the cross-lingual task interms of naturalness .…

Dataset Augmentation and Dimensionality Reduction of Pinna Related Transfer Functions

Efficient modeling of the inter-individual variations of head-relatedtransfer functions (HRTFs) is a key matter to the individualization of binauralsynthesis . We find that the model trained on the WiDESpreaDdataset performsbest, regardless of the number of retained principal components . We investigate thedimensionalityreduction capacity of two principal component analysis (PCA) models ofmagnitude PRTFs, trained on WiDESPREaD and on the original dataset,respectively .…

comp syn Perceptually Grounded Word Embeddings with Color

Python package comp-syn provides grounded word embeddings based on the perceptually uniform colordistributions of Google Image search results . We demonstrate that comp-synsignificantly enriches models of distributional semantics . Comp-synis is open-source on PyPi and is compatible with mainstream machine-learningPython packages .…

Contextualisation of eCommerce Users

A scaleable modelling framework for the consumer intent within the setting ofe-Commerce is presented . The methodology applies contextualisation throughembeddings borrowed from Natural Language Processing . By considering the usersession journeys throughough the pages of a website as documents, we capturecontextual relationships between pages, as well as the topics of the of uservisits .…

A practical guide towards agile test driven development for scientific software projects

Software testing has received much attention over the last years and has reached such critical importance that agile software development practices put software testing at its core . Agile software development is successfully applied in large-scale industrial software developments but due to its granularresponsibilities with roles assigned to various members of the development team, these practices may not be applicable to scientific code development .…

Isometric and affine copies of a set in volumetric Helly results

We show that for any compact convex set $K$ is very similar to adisk, the shrinking factor is unavoidable . We prove similar results for affinecopies of $K$. We show how our results imply the existence of randomizedalgorithms that approximate the largest copy that fits inside a givenpolytope $P$ whose expected runtime is linear on the number of facets of $P$.…

Flipping the Perspective in Contact Tracing

Contact tracing has been a widely-discussed technique for controllingCOVID-19 . The traditional test-trace-isolate-support paradigm focuses on identifying people after they have been exposed to positive individuals, and isolating them to protect others . This article introduces an alternative andcomplementary approach, which appears to be the first to notify people before exposure happens, in the context of their interaction network, so that they candirectly take actions to avoid exposure themselves .…

Quantitative analysis of the co publications of Ukrainian scientists with the Nobel laureates 1994 2018 in Science

Most scientific papers today are co-authored by a large number of researchers . However, very few scientists can receive the Nobel Prize according to the Statutes of the Nobel Foundation . An analysis of the co-authorship of Nobel laureates will make it possible to identify employees of Ukrainian institutions who have collaborated with leadingscientists of the world, whose scientific works were noted by Nobel .…

Intrinsic Hierarchical Clustering Behavior Recovers Higher Dimensional Shape Information

We show that specific higher dimensional shape information of point clouddata can be recovered by observing lower dimensional hierarchical clusteringdynamics . We generate multiple point samples from point clouds and performhierarchical clustering within each sample to produce dendrograms . We take cluster evolution and merging data that capture clusteringbehavior to construct simplified diagrams that record the lifetime of clusters .…

Spatial temporal Analysis of COVID 19 s Impact on Human Mobility the Case of the United States

COVID-19 has been affecting every aspect of societal life including humanmobility since December, 2019 . The change of mobility patterns does notnecessarily correlate with government policies and guidelines, but is more related to people’s awareness of the pandemic . Our results show that it takes on average 14 days for the mobility patterns to adjust to the new situation, and a 14-day delay is found between the time when the largest number of clusters appears and the peak of Coronavirus-related search queries on GoogleTrends .…

Characterizing relationships between primary miners in Ethereum by analyzing on chain transactions

It is widely accepted that Ethereum mining is highly centralized . However, models of mining behavior assume that miners are eitherunrelated or only relate via mining pools under highly structured and transparent agreements . By characterizing the topology of the network of minertransactions, we find the emergence of highly connected clusters that controls significant amounts of hashing power and exhibit relationships in the oppositedirection of what theoretical models predict .…

Gender domain adaptation for automatic speech recognition task

This paper is focused on the finetuning of acoustic models for speakeradap-tation based on a given gender . We pretrained the Transformer baselinemodel on Librispeech-960 and conduct experiments . Our approach leads to 5% lower word error rate on male subset if the layers in the encoder and decoder are not frozen, but the tuning is started from the last checkpoints .…