## 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 .…

## Exploring deep learning methods for recognizing rare diseases and their clinical manifestations from texts

Approximately 300million people are affected by a rare disease . The early and accurate diagnosis of these conditions is a major challenge for general practitioners . Natural Language Processing (NLP) and DeepLearning can help to extract relevant information about rare diseases tofacilitate their diagnosis and treatments .…

## Storing Multi model Data in RDBMSs based on Reinforcement Learning

How to manage various data in a unified way is a significant research topic in databases . Researchers have proposed multi-model databases to support multiple data models in a uniform platform with a single unified query language . However, since relational databases are dominant in the current market, it is expensive to replace them with others .…

## 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 .…

## Crypto Currency Regulation and Law Enforcement Perspectives

This paper provides an overview of how crypto currency and blockchainengineering interacts with the law enforcement . We point out that a largeproportion of crypto users are amateur investors and the dominant and the largest segment in crypto crime are simply investment scams (!).…

## Application and Benchmark of SPH for Modeling the Impact in Thermal Spraying

A3D Smoothed Particle Hydrodynamics (SPH) model represents the moltendroplet as an incompressible fluid, while a semi-implicit Enthalpy-Porositymethod is applied for the mushy zone during solidification . We show that SPH is an excellent method for solving this freesurface problem accurately and efficiently .…

## 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 .…

## Cats vs Spectre An Axiomatic Approach to Modeling Speculative Execution Attacks

Spectre family of speculative execution attacks have required arethinking of formal methods for security . Approaches based on operationalspeculative semantics have made initial inroads towards finding vulnerable code . With each new attack grows the amount of microarchitectural detail that has to be integrated into the underlyingsemantics .…

## Multi model Machine Learning Inference Serving with GPU Spatial Partitioning

Machine learning (ML) inference servers have become critical for online service applications . Paper proposes a new ML inference scheduling framework for multi-model MLinference servers . The paper first shows that with SLO constraints, currentGPUs are not fully utilized for ML inference tasks .…

## 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 .…

## Pattern based Acquisition of Scientific Entities from Scholarly Article Titles

A subset of the acquisition algorithm is implemented for article titles inthe Computational Linguistics (CL) scholarly domain . It has extracted 19,799 research problems;18,111 solutions; 20,033 resources; 1,059 languages; 6,878 tools; and 21,687methods at an average extraction precision of 75% .…

## 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 .…

## Quantum Inspired Keyword Search on Multi Model Databases

With rising applications implemented in different domains, it isinevitable to require databases to adopt corresponding appropriate data modelsto store and exchange data derived from various sources . To handle these datamodels in a single platform, the community of databases introduces amulti-model database .…

## 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 .…

## Memory Augmented Multi Instance Contrastive Predictive Coding for Sequential Recommendation

The sequential recommendation aims to recommend items, such as products,songs and places, to users based on the sequential patterns of their historical records . The long-term preference is difficult to capture, and the supervision signal is too sparse to effectively train amodel .…

## Deployable Networks for Public Safety in 5G and Beyond A Coverage and Interference Study

Deployable networks are foreseen to be one of the key technologies for public safety in fifth generation (5G) mobile communications and beyond . They can beused to complement the existing public cellular networks to provide temporary and on-demand connectivity in emergency situations .…

## 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 .…

## Complex Event Forecasting with Prediction Suffix Trees Extended Technical Report

Complex Event Recognition (CER) systems have become popular in the past twodecades due to their ability to “instantly” detect patterns on real-timestreams of events . However, there is a lack of methods for forecasting when apattern might occur before such an occurrence is actually detected by a CERengine .…

## Fairness based Multi Preference Resource Allocation in Decentralised Open Markets

In this work, we focus on resource allocation in a decentralised open market . We propose a three-step resourceallocation approach that employs a reverse-auction paradigm . At the first step,priority label is attached to each bidding vendor based on the proposedpriority mechanism .…

## Complexity Measures for Multi objective Symbolic Regression

Multi-objective symbolic regression has the advantage that while the accuracyof the learned models is maximized, the complexity is automatically adapted . The result of the optimization is not a singlesolution anymore, but a whole Pareto-front describing the trade-off between accuracy and complexity .…

## 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 .…

## Chronic Pain and Language A Topic Modelling Approach to Personal Pain Descriptions

Wepropose and discuss a topic modelling approach to recognize patterns in verbaldescriptions of chronic pain . Our approaches allow for the extraction of novel insightson chronic pain experiences from the obtained topic models and latent spaces . We argue that our results are clinically relevant for the assessment andmanagement of chronic chronic pain.…

## 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 .…

## Pattern based Acquisition of Scientific Entities from Scholarly Article Titles

A subset of the acquisition algorithm is implemented for article titles inthe Computational Linguistics (CL) scholarly domain . It has extracted 19,799 research problems;18,111 solutions; 20,033 resources; 1,059 languages; 6,878 tools; and 21,687methods at an average extraction precision of 75% .…

Redundancy has contrasting effects on read and write latency . Read latency can be reduced by potential parallel access from multiple servers . Writelatency increases as a larger number of replicas have to be updated . We empirically show that this approximation is tight across all ranges of system parameters.…

## Decentralized Collaborative Video Caching in 5G Small Cell Base Station Cellular Networks

Collaborative Caching Algorithm (CCA) can efficiently compute a solution close to the optimal, where the degree ofsub-optimality depends on the worst case video-to-cache size ratio . We extend CCA to an online setting where the video popularities are not known a priori but are estimated over time through a limited amount of periodicinformation sharing between SBSs .…

## Multi Sample based Contrastive Loss for Top k Recommendation

The top-k recommendation is a fundamental task in recommendation systems . We propose a Multi-Samplebased Contrastive Loss (MSCL) function . The proposed MSCL is simple and can be applied in many methods . We will release our code on GitHub upon the acceptance of the accepted version of MSCL .…

## Unsub Extender a Python based web application for visualizing Unsub data

Unsub is a collection development dashboard that gathers and forecastsjournal-level usage metrics to provide academic libraries with deeper measures than traditional cost-per-use . Unsub Extender is a free Python-based web application that takes an Unsub export file and automates the creation of interactive plots and visualizations .…

## Application and Benchmark of SPH for Modeling the Impact in Thermal Spraying

A3D Smoothed Particle Hydrodynamics (SPH) model represents the moltendroplet as an incompressible fluid, while a semi-implicit Enthalpy-Porositymethod is applied for the mushy zone during solidification . We show that SPH is an excellent method for solving this freesurface problem accurately and efficiently .…

## Autonomous Cooperative Multi Vehicle System for Interception of Aerial and Stationary Targets in Unknown Environments

This paper presents the design, development, and testing of hardware-softwaresystems by the IISc-TCS team for Challenge 1 of the Mohammed Bin ZayedInternational Robotics Challenge 2020 . The goal of Challenge 1 was to grab aball suspended from a moving and maneuvering UAV and pop balloons anchored to the ground, using suitable manipulators .…

## A New Test for Hamming Weight Dependencies

We describe a new statistical test for pseudorandom number generators . Our test can find bias induced by dependencies among the Hammingweights of the outputs of a PRNG, even for PRNGs that pass state-of-the-art tests of the same kind from the literature .…

## 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 .…

## Fast Abstracts and Student Forum Proceedings 17th European Dependable Computing Conference EDCC 2021

Collection of manuscripts accepted for presentation at the Student Forum andFast Abstracts tracks of the 17th European Dependable Computing Conference(EDCC 2021)…

## 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 .…

## Clover an Anonymous Transaction Relay Protocol for the Bitcoin P2P Network

The Bitcoin P2P network currently represents a reference benchmark for modern cryptocurrencies . To protect user privacy, the identity of the node originating a message is kept hidden . An adversary observing the whole network can analyze the spread pattern of atransaction to trace it back to its source .…

## 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 .…

## EVReflex Dense Time to Impact Prediction for Event based Obstacle Avoidance

Traditional computer vision techniques using cameras and depth sensors often rely on priors about obstacles . Recent developments in bio-inspired sensors present event cameras as a compelling choice for dynamic scenes . We show fusion of events and depth overcomes failure cases of each modality when performing obstacle avoidance .…

## 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 .…