## Number and quality of diagrams in scholarly publications is associated with number of citations

Diagrams are often used in scholarly communication . We analyse a corpus of diagrams found in scholarly computational linguistics conference proceedings . Inclusion of over three diagrams in this8-page limit conference was found to correlate with a lower citation count .…

## Content based subject classification at article level in biomedical context

Wepropose a mixed approach, leveraging on embeddings technique in NLP to train classifiers with article metadata (title, abstract, keywords) and then apply these classifiers at the article level . We use this approach in the context of biomedical publications using metadata from Pubmed.…

## Evaluating Groundedness in Dialogue Systems The BEGIN Benchmark

The Benchmark for Evaluation of Grounded INteraction (BEGIN) consists of 8113 dialogue turns generated by language-model-based dialogue systems . These annotations are based on an extension of the naturallanguage inference paradigm . We use the benchmark to demonstrate theeffectiveness of adversarially generated data for improving an evaluationmetric based on existing natural language inference datasets .…

## Improving Response Quality with Backward Reasoning in Open domain Dialogue Systems

Encoder-decoder-baseddialogue models tend to produce generic and dull responses during the decoding step . The proposed bidirectionalresponse generation method achieves state-of-the-art performance for response quality . The advantage of our method isthat the forward generation and backward reasoning steps are trainedsimultaneously through the use of a latent variable .…

## An analysis of full size Russian complexly NER labelled corpus of Internet user reviews on the drugs based on deep learning and language neural nets

We present the full-size Russian complexly NER-labeled corpus of Internet user reviews . The evaluation of accuracy levels reached on thiscorpus by a set of advanced deep learning neural networks to extract thepharmacologically meaningful entities from Russian texts . The state of the art for the pharmacological entity extraction problem for Russian is established on afull-size labeled corpus .…

## Traceability Technology Adoption in Supply Chain Networks

Modern traceability technologies promise to improve supply chain management by simplifying recalls, increasing demand visibility, or ascertainings sustainable supplier practices . We introduce a model of the dynamics of traceability technology adoption insupply chain networks to tackle the problem of selecting the smallest set of early adopters guaranteeing broad dissemination .…

## Participatory Budgeting with Donations and Diversity Constraints

Participatory budgeting (PB) is a democratic process where citizens jointly decide on how to allocate public funds to indivisible projects . This paper focuses on PB processes where citizens may give additional money to projectsthey want to see funded . We introduce a formal framework for this kind of PB with donations .…

## Improving the Accessibility of Scientific Documents Current State User Needs and a System Solution to Enhance Scientific PDF Accessibility for Blind and Low Vision Users

The majority of scientific papers are distributed in PDF, which pose challenges for accessibility, especially for blind and low vision (BLV) readers . We introduce the SciA11y system to offset some of the issues around inaccessibility . We successfully produce HTMLrenders for over 12M papers, of which an open access subset of 1.5M are available for browsing at http://scia11y.org/…

## Wittgenstein and Turing Machines Language games and Forms of life

We propose here to make the connection between the definitions given by Turing and Wittgenstein about what it means to “follow a rule”. It will be here a presentation of the Turing test in order to observe that humans and machines have more in common than one might initially believe when it comes to interpreting signs .…

## Explanation Based Human Debugging of NLP Models A Survey

To fix a bug in a program, we need to locate where the bug is, understand why it causes the problem, and patch the code accordingly . This process becomes harder when the program is a trained machine learning model and even harder for opaque deep learning models .…

## Wittgenstein and Turing Machines Language games and Forms of life

We propose here to make the connection between the definitions given by Turing and Wittgenstein about what it means to “follow a rule”. It will be here a presentation of the Turing test in order to observe that humans and machines have more in common than one might initially believe when it comes to interpreting signs .…

## Anytime Decoding by Monte Carlo Tree Search

An anytime decoding algorithm for tree codes using Monte-Carlo tree search is proposed . The algorithm can approximate the maximum-likelihood sequencedecoding of tree codes . The proposed method may also be extended to the decoding ofconvolutional codes and block codes .…

## A Review on Bio Cyber Interfaces for Intrabody Molecular Communications Systems

Recent advancements in bio-engineering and wireless communications have motivated researchers to propose novel applications for telemedicine, therapeutics and human health monitoring . This technology can be furtherextended to use Bio-Nano devices to promote a real-time monitoring of the human health and storage of the gathered data in the cloud .…

## On the Computation of PSNR for a Set of Images or Video

When comparing learned image/video restoration and compression methods, it iscommon to report peak-signal to noise ratio (PSNR) results . However, there doesnot exist a generally agreed upon practice to compute PSNR for sets of imagesor video . Some authors report average of individual image/frame PSNR, which is equivalent to computing PSNR from geometric mean of individualimage/frame mean-square error (MSE) Others compute a single PSNR of Y-channel only, while others compute MSE/PSNR for RGB channels .…

## Open Source Memory Compiler for Automatic RRAM Generation and Verification

This is the first open-source memory compilers that has been developed specifically to automate ResistiveRandom Access Memory (RRAM) generation . RRAM holds the promise of achieving high speed, high density and non-volatility . A novel RRAM architecture,additionally is proposed, and a number of generated RRAM arrays are evaluated to identify their worst case control line parasitics and worst case settlingtime across the memristors of their cells .…

## Self Dimensioning and Planning of Small Cell Capacity in Multitenant 5G Networks

An important concept in the fifth generation of mobile networks ismultitenancy, which allows diverse operators sharing the same wireless infrastructure . This paper proposes a new framework for automated cell planning in multitenant small cell networks . The simulation results show the effectiveness of various methods to derive the planning specifications depending on the correlation between the tenant’s and network’s traffic demands .…

## Simplicial contagion in temporal higher order networks

Complex networks represent the natural backbone to study epidemic processes in populations of interacting individuals . Such a modeling framework is naturally limited to pairwise interactions, making it less suitable toproperly describe social contagion . Here we extend simplicial contagion to time-varying networks,where pairwise and higher-order simplices can be created or destroyed overtime .…

## Quantum Foundations of Classical Reversible Computing

The reversible computation paradigm aims to provide a new foundation for forgeneral classical digital computing that is capable of circumventing thethermodynamic limits to the energy efficiency of the conventional,non-reversible paradigm . We use the framework ofGorini-Kossakowski-Sudarshan-Lindblad dynamics (a.k.a. Lindbladians) with multiple asymptotic states, incorporating recent results from resource theory, full counting statistics, and stochastic thermodynamics .…

## Convergence Analysis and System Design for Federated Learning over Wireless Networks

Federated learning (FL) has recently emerged as an important and promising scheme in IoT, enabling devices to jointly learn a model without sharing their raw data sets . As the training data in FL is notcollected and stored centrally, FL training requires frequent model exchange, which is largely affected by the wireless communication network .…

## Black box adversarial attacks using Evolution Strategies

In the last decade, deep neural networks have proven to be very powerful incomputer vision tasks . However, they are not robust toperturbations of the input data . Several methods able to generateadversarial samples make use of gradients, which usually are not available to an attacker in real-world scenarios .…

## A Novel Approximate Hamming Weight Computing for Spiking Neural Networks an FPGA Friendly Architecture

Hamming weights of sparse and long binary vectors are important modules in scientific applications, particularly in spiking neural networks that areof our interest . We propose a method inspired from synaptic transmissionfailure for exploiting FPGA lookup tables to compress long input vectors .…

## Wittgenstein and Turing Machines Language games and Forms of life

We propose here to make the connection between the definitions given by Turing and Wittgenstein about what it means to “follow a rule”. It will be here a presentation of the Turing test in order to observe that humans and machines have more in common than one might initially believe when it comes to interpreting signs .…

## Cybersecurity in Power Grids Challenges and Opportunities

Increasing volatilities within power transmission and distribution force power grid operators to amplify their use of communication infrastructure to monitor and control their grid . The resulting increase in communication creates a larger attack surface for malicious actors . Cyber attacks on powergrids have already succeeded in causing temporary, large-scale blackouts in therecent past .…

## Unique Ergodicity in the Interconnections of Ensembles with Applications to Two Sided Markets

In a general discrete-time feedback model, we show conditions that assure that for each agent, there exists the limit of along-run average allocation of a resource to the agent . We call this property the unique ergodicity . Our model encompasses two-sided markets and more complicated interconnectionsof workers and customers, such as in a supply chain .…

## Improving Conversational Recommendation System by Pretraining on Billions Scale of Knowledge Graph

Conversational Recommender Systems (CRSs) in E-commerce platforms aim torecommend items to users via multiple conversational interactions . Most CRSs suffer from the problem of datascarcity and sparseness . We propose a novel knowledge-enhanced deep cross network (K-DCN), a two-step (pretrain andfine-tune) CTR prediction model to recommend items .…

## Dandelion multiplexing Byzantine agreements to unlock blockchain performance

Permissionless blockchain protocols are known to consume an outrageous amount of computing power and suffer from a trade-off between latency and confidence in transaction confirmation . In this paper, we empower Algorand’s protocol by multiplexing itsbyzantine agreements in order to improve performance .…

## Memory Optimality for Non Blocking Containers

A bounded container maintains a collection of elements that can be inserted and extracted as long as the number of stored elements does not exceed the capacity . We consider the concurrent implementations of a bounded container more or less memory-friendly depending on how much memory they use in addition to storing the elements .…

## LightIoT Lightweight and Secure Communication for Energy Efficient IoT in Health Informatics

Internet of Things (IoT) is considered as a key enabler of healthinformatics . IoT-enabled devices are used for in-hospital and in-home patientmonitoring to collect and transfer biomedical data pertaining to bloodpressure, electrocardiography (ECG), blood sugar levels, body temperature, etc. These devices generate data in real-time and transmitthem to nearby gateways and remote servers for processing and visualization .…

## A numerical exploration of signal detector arrangement in a spin wave reservoir computing device

This paper studies numerically how the signal detector arrangement influencesthe performance of reservoir computing using spin waves excited in aferrimagnetic garnet film . This investigation is essentially important sincethe input information is not only conveyed but also transformed by the spinwaves into high-dimensional information space when the waves propagate in the film in a spatially distributed manner .…

## Complementation in t perfect graphs

There are only five pairs of graphs such that both the graphs and their complements are minimally t-imperfect . A full characterization of t-perfection with respect to substitution has been obtained by Benchetrit in his Ph.D. thesis . In particular, there are only 5 pairs such that the graph and its complements and the graph is minimally perfect, such as in the case of a pair of pairs of perfect graphs with the same degree of complementation .…

## QoS Aware Placement of Deep Learning Services on the Edge with Multiple Service Implementations

Mobile edge computing pushes computationally-intensive services closer to the user to provide reduced delay due to physical proximity . This has led many toconsider deploying deep learning models on the edge — commonly known as edgeintelligence (EI) EI services can have many model implementations that providedifferent QoS.…

## GTN ED Event Detection Using Graph Transformer Networks

Recent works show that the graph structure of sentences, generated fromdependency parsers, has potential for improving event detection . However, they often only leverage the edges (dependencies) between words, and discard the labels (e.g., nominal-subject) labels . In this work, we propose a novel framework for incorporatingboth dependencies and their labels using a recently proposed technique calledGraph Transformer Networks (GTN) We integrate GTNs to leverage dependencyrelations on two existing homogeneous-graph-based models .…

## A combinatorial algorithm for computing the degree of the determinant of a generic partitioned polynomial matrix with 2 times 2 submatrices

In this paper, we consider the problem of computing the degree of the determinant of a block-structured symbolic matrix . This problem can be viewed as an algebraic generalization of themaximum weight perfect bipartite matching problem . The main result of this paper is a combinatorial $O(n^4)$-time algorithm for the deg-det computation of a $2 \times 2$-type generic partitioned polynomialmatrix of size \$2n .…

## Cross Modal Music Video Recommendation A Study of Design Choices

In this work, webuild upon a recent video-music retrieval system (the VM-NET), which originallyrelies on an audio representation obtained by a set of statistics computed overhandcrafted features . We demonstrate that using audio representationlearning such as the audio embeddings provided by the pre-trained MuSimNet,OpenL3, MusicCNN or by AudioSet, largely improves recommendations .…

## On the Hardness of Scheduling With Non Uniform Communication Delays

In the scheduling with non-uniform communication delay problem, the input is a set of jobs with precedence constraints . Associated with every precedenceconstraint between a pair of jobs is a communication delay . The objective is to assign the jobs to machines to minimizethe makespan of the schedule .…

## Energy Efficient Reconfigurable Intelligent Surface Enabled Mobile Edge Computing Networks with NOMA

Reconfigurable intelligent surface (RIS) has emerged as a promising technology for achieving high spectrum and energy efficiency in future wireless networks . The RIS-aided single-cellmulti-user mobile edge computing (MEC) system is deployed to support the communication between a base station (BS) equipped with MEC servers and multiple single-antenna users .…

## PSEUDo Interactive Pattern Search in Multivariate Time Series with Locality Sensitive Hashing and Relevance Feedback

We present PSEUDo, an adaptive feature learning technique for exploring visual patterns in multi-track sequential data . We can even accomplish both themodeling and comparison of 10,000 different 64-track time series, each with 100time steps (a typical EEG dataset) under 0.8 seconds .…

## Stochastic gradient descent with noise of machine learning type Part I Discrete time analysis

Stochastic gradient descent (SGD) is one of the most popular algorithms in machine learning . The noise encountered in these applications is different from that in theoretical analyses of stochastic gradientalgorithms . The energy landscape resembles that of overparametrized deep learning problems .…

## Wittgenstein and Turing Machines Language games and Forms of life

We propose here to make the connection between the definitions given by Turing and Wittgenstein about what it means to “follow a rule”. It will be here a presentation of the Turing test in order to observe that humans and machines have more in common than one might initially believe when it comes to interpreting signs .…

## Post war Civil War Propaganda Techniques and Media Spins in Nigeria and Journalism Practice

A spin is a form of propaganda achieved through knowingly presenting a biased interpretation of an event or issues . In war time, various forms of spin are employed by antagonists to push their brigades to victory and wearout the opponents .…

## Speeding up Python based Lagrangian Fluid Flow Particle Simulations via Dynamic Collection Data Structures

Array-like collection data structures are widely established in Python’s scientific computing-ecosystem for high-performance computations . High performance is,however, only guaranteed for static computations with a fixed computational domain . We show that for dynamic computations within an actively changing domain, the array-like collections provided by NumPy and itsderivatives are a bottleneck for large computations.…

## Learning Linear Temporal Properties from Noisy Data A MaxSAT Approach

We address the problem of inferring descriptions of system behavior usingLinear Temporal Logic (LTL) from a finite set of positive and negative examples . Our first algorithm infers minimal LTL formulas by reducing the inferenceproblem to a problem in maximum satisfiability .…

## Long Runs Imply Big Separators in Vector Addition Systems

The reachability problem for three-dimensional VASSes(3-VASSes) is only known to be PSpace-hard and not elementary . In 2010 Leroux has proventhat non-reachability between two configurations implies separability of thesource from target by some semilinear set, which is an inductive invariant .…

## Wittgenstein and Turing Machines Language games and Forms of life

We propose here to make the connection between the definitions given by Turing and Wittgenstein about what it means to “follow a rule”. It will be here a presentation of the Turing test in order to observe that humans and machines have more in common than one might initially believe when it comes to interpreting signs .…

## Methodology for Biasing Random Simulation for Rapid Coverage of Corner Cases in AMS Designs

Exploring the limits of an Analog and Mixed Signal (AMS) circuit by drivingappropriate inputs has been a serious challenge to the industry . In order to meet time-to-marketrequirements, often suboptimal coverage results of an integrated circuit (IC)are leveraged . No standards have been defined which can be used to identify a target in the continuous state space of analog domain such that the searching algorithm can be guided with some heuristics .…

## Performance evaluation results of evolutionary clustering algorithm star for clustering heterogeneous datasets

This article presents the data used to evaluate the performance ofevolutionary clustering algorithm star (ECA*) compared to five traditional and modern clustering algorithms . Two experimental methods are employed to examinethe performance of ECA* against genetic algorithm for clustering++(GENCLUST++), learning vector quantisation (LVQ) , expectation maximisation(EM) and K-means (KM) The results of the experiments performeddemonstrate some limitations in the ECA*: (i) ECA*.…

## Team MMSE Precoding with Applications to Cell free Massive MIMO

This article studies a novel distributed precoding design, coined teamminimum mean-square error (TMMSE) precoding . Building on the theory of teams, we derive a set of necessary and sufficientconditions for optimal TMMSE precoding, in the form of an infinite dimensionallinear system of equations .…

## User centric Cell free Massive MIMO Networks A Survey of Opportunities Challenges and Solutions

Densification of network base stations is indispensable to achieve the Quality of Service (QoS) requirements of future mobile networks . With a dense deployment of transmitters, interference management becomes an arduous task. To solve this issue, exploring radically new networkarchitectures with intelligent coordination and cooperation capabilities iscrucial.…

## Paraphrastic Representations at Scale

We present a system that allows users to train their own state-of-the-art paraphrastic sentence representations in a variety of languages . We alsorelease trained models for English, Arabic, German, French, Spanish, Russian,Turkish, and Chinese . We train these models on large amounts of data, achievingsignificantly improved performance from the original papers proposing themethods on a suite of monolingual semantic similarity, cross-lingual semanticsimilarity, and bitext mining tasks .…

## Event driven timeseries analysis and the comparison of public reactions on COVID 19

The rapid spread of COVID-19 has already affected human lives throughout the globe . Governments of different countries have taken various measures, but how they affected people lives is not clear . In this study, a rule-based and amachine-learning based models are applied to answer the above question using public tweets from Japan, USA, UK, and Australia .…