GRAL Localization of Floating Wireless Sensors in Pipe Networks

Mobile wireless sensors are increasingly recognized as a valuable tool formitoring critical infrastructures . An important use case is the discovery ofleaks and inflows in pipe networks using a swarm of floating sensor nodes . We propose a novel algorithm for assigning location estimatesto recorded measurements once the sensor node leaves the inaccessible area and sends them via a gateway .…

Boosting Search Engines with Interactive Agents

Can machines learn to use a search engine as an interactive tool for finding information? That would have far reaching consequences for making the world’s knowledge more accessible? This paper presents first steps in designing agentsthat learn meta-strategies for contextual query refinements .…

Accelerating an Iterative Eigensolver for Nuclear Structure Configuration Interaction Calculations on GPUs using OpenACC

We modify a previously developed hybrid MPI/OpenMP implementation of aneigensolver written in FORTRAN 90 by using an OpenACC directives basedprogramming model . The optimal way to insert OpenACCdirectives may be different from the original way of inserting OpenMPdirectives . We compare the performance of the OpenACC basedimplementation executed on multiple GPUs with the performance ondistributed-memory many-core CPUs .…

Concurrent matching logic

We introduce concurrentmatching logic (CML) to reason about fault-free partial correctness of shared-memory concurrent programs . We also present a soundness proof for CML in terms of operational semantics . Undercertain assumptions, the assertion of CSL can be transformed into the assertionof CML .…

MORTAL A Tool of Automatically Designing Relational Storage Schemas for Multi model Data through Reinforcement Learning

We present a novel reinforcement learning-based tool calledMORTAL . It could automatically design a relational database to store multi-model data while having a great query performance . We are centered around the following modules: generating initial statebased on loaded multi-models data, influencing learning process by settingparameters, controlling generated relational schematures .…

An Unsupervised Method for Building Sentence Simplification Corpora in Multiple Languages

The availability of parallel sentence simplification (SS) is scarce forneural SS modelings . We propose an unsupervised method to build SS corpora from large-scale bilingual translation corpora, alleviating the need for SSsupervised corpora . The SS methodstrained by our corpora achieve the state-of-the-art results and significantly outperform the results on English benchmark WikiLarge.…

V2X Communication Between Connected and Automated Vehicles CAVs and Unmanned Aerial Vehicles UAVs

Connectivity between ground vehicles can be utilized and expanded to includeaerial vehicles for coordinated missions . Using Vehicle-to-Everything (V2X) technologies, a communication link can be established betweenConnected and Autonomous vehicles (CAVs) and Unmanned Aerial vehicles (UAVs) The aim was to send ground vehicle location information from the CAV to the UAV throughDSRC communication .…

Shallow pooling for sparse labels

Recent years have seen enormous gains in core IR tasks, including document and passage ranking . MS MARCO leaderboards track improvements with mean reciprocal rank (MRR) In essence, arelevant item is treated as the “right answer” with rankers scored on theirability to place this item high in ranking .…

Black Box Attacks on Sequential Recommenders via Data Free Model Extraction

We argue that sequential recommender systems are subject to unique vulnerabilities due to autoregressive regimes used to train them . We propose an API-based modelextraction method via limited-budget synthetic data generation and knowledgedistillation . We perform attacks in two stages. (1) Model extraction: given different types of synthetic data and their labels retrieved from ablack-box recommender .…

Moving intervals for packing and covering

We show that both packing and covering are W[1] hard with any one of $\kappa$ as single parameter, but are FPT with combined parameters . We also obtain improved polynomial-time algorithms for packing andcovering, including an $O(n\log^2 n)$ time algorithm for covering, when allintervals in $\mathcal{I}$ have the same length .…

V2X Communication Between Connected and Automated Vehicles CAVs and Unmanned Aerial Vehicles UAVs

Connectivity between ground vehicles can be utilized and expanded to includeaerial vehicles for coordinated missions . Using Vehicle-to-Everything (V2X) technologies, a communication link can be established betweenConnected and Autonomous vehicles (CAVs) and Unmanned Aerial vehicles (UAVs) The aim was to send ground vehicle location information from the CAV to the UAV throughDSRC communication .…

Quantitative Evaluation of SPH in TIG Spot Welding

Smoothed Particle Hydrodynamics (SPH) method for modeling welding processes has become increasingly popular in recent years . We propose a novel SPH model for the simulation of the tungsten inertgas (TIG) spot welding process . We show that SPH isable to yield excellent results, especially given the observed deviations between the investigated FEM methods and as such, we validate the accuracy of the method for an industrially relevant engineering application .…

Active Inference and Epistemic Value in Graphical Models

The Free Energy Principle postulates that biological agents perceive and interact with their environment in order to minimize a Variational FreeEnergy (VFE) with respect to a generative model of their environment . Crucially, variational optimization of the CBFE can be expressedin terms of message passing on free-form generative models .…

Mean absorption estimation from room impulse responses using virtually supervised learning

In the context of building acoustics and the acoustic diagnosis of anexisting room, this paper introduces and investigates a new approach toestimate mean absorption coefficients solely from a room impulse response . This inverse problem is tackled via virtually-supervised learning,namely, the RIR-to-absorption mapping is implicitly learned by regression on asimulated dataset using artificial neural networks .…

Variational Quantum Reinforcement Learning via Evolutionary Optimization

Recent advance in classical reinforcement learning (RL) and quantumcomputation points to a promising direction of performing RL on a quantumcomputer . Potential applications in quantum RL are limited by thenumber of qubits available in modern quantum devices . We present twoframeworks of deep quantum RL tasks using a gradient-free evolutionoptimization: First, we apply the amplitude encoding scheme to the Cart-Poleproblem .…

Algorithme de recherche approximative dans un dictionnaire fondé sur une distance d édition définie par blocs

The algorithm makes use of adivergence function between strings — broadly belonging to the family of editdistances . It finds dictionary entries whose distance to the search string is below a certain threshold . The divergence function is not the classical editdistance (DL distance) It is adaptable to a particular corpus, and is based onelementary alteration costs defined on character blocks, rather than on individual characters .…

A real time global re localization framework for 3D LiDAR SLAM

Simultaneous localization and mapping (SLAM) has been a hot research field inthe past years . Most global descriptors for point cloud can only be used for detection under a small local area . In order to re-localizeglobally in the map, point clouds and descriptors are denselycollected using a reconstructed mesh model at an offline stage by a physicalsimulation engine to expand the functional distance of point cloud descriptors .…

Accelerating an Iterative Eigensolver for Nuclear Structure Configuration Interaction Calculations on GPUs using OpenACC

We modify a previously developed hybrid MPI/OpenMP implementation of aneigensolver written in FORTRAN 90 by using an OpenACC directives basedprogramming model . The optimal way to insert OpenACCdirectives may be different from the original way of inserting OpenMPdirectives . We compare the performance of the OpenACC basedimplementation executed on multiple GPUs with the performance ondistributed-memory many-core CPUs .…

Category Level Metric Scale Object Shape and Pose Estimation

Advances in deep learning recognition have led to accurate object detection with 2D images . However, these 2D perception methods are insufficient forcomplete 3D world information . Advances focus on the shape itself, without considering metric scale . We propose a framework that jointly estimates a metricscale shape and pose from a single RGB image .…

Quantitative Evaluation of SPH in TIG Spot Welding

Smoothed Particle Hydrodynamics (SPH) method for modeling welding processes has become increasingly popular in recent years . We propose a novel SPH model for the simulation of the tungsten inertgas (TIG) spot welding process . We show that SPH isable to yield excellent results, especially given the observed deviations between the investigated FEM methods and as such, we validate the accuracy of the method for an industrially relevant engineering application .…

Justifying Groups in Multiwinner Approval Voting

Justified representation (JR) is a standard notion of representation in approval voting . We show that under the impartial culture model, $n/k$-justifying groups of size less than $k/2$ are likely to exist . Small groups can often be useful for obtaining a gender-balanced JR committee even though the problem is NP-hard .…

LightChain Scalable DHT Based Blockchain

LightChain is the first blockchain architecture that operates over aDistributed Hash Table (DHT) of participating peers . LightChain provides addressable blocks and transactions within the network, which makes them efficiently accessible by all peers . Eachblock and transaction is replicated within the DHT of peers and is retrieved in an on-demand manner .…

Moving intervals for packing and covering

We show that both packing and covering are W[1] hard with any one of $\kappa$ as single parameter, but are FPT with combined parameters . We also obtain improved polynomial-time algorithms for packing andcovering, including an $O(n\log^2 n)$ time algorithm for covering, when allintervals in $\mathcal{I}$ have the same length .…

A Gradient Sampling Algorithm for Stratified Maps with Applications to Topological Data Analysis

We introduce a novel gradient descent algorithm extending the well-knownGradient Sampling methodology to the class of stratifiably smooth objectivefunctions . For thisclass of functions, our algorithm achieves a sub-linear convergence rate . Wethen apply our method to objective functions based on the (extended) persistenthomology map computed over lower-star filters, which is a central tool ofTopological Data Analysis .…

Boolean proportions

Analogy-making is at the core of human intelligence and creativity with applications to such diverse tasks as commonsense reasoning, learning, languageacquisition, and story telling . This paper studies analogical proportions between booleans of the form `$a$ is to $b$ what $c$ is $d$’ called ‘booleanproportions’ It turns out that our notion of boolean proportions has appealingmathematical properties .…