Meeting Effectiveness and Inclusiveness in Remote Collaboration

A primary goal of remote collaboration tools is to provide effective andinclusive meetings for all participants . Thisshows a method of measuring and understanding these metrics which are bothpractical and useful in a commercial CMC system . The model shows the following factors are correlated with inclusiveness, effectiveness, participation, and feeling comfortable to contribute in meetings: sending a pre-meeting communication, sending a meeting agenda, attendee location, remote-only meeting, audio/video quality and reliability, video usage, andmeeting size.…

Trends in Vehicle Re identification Past Present and Future A Comprehensive Review

Vehicle Re-identification (re-id) over surveillance camera network with non-overlapping field of view is an exciting and challenging task in intelligent transportation systems (ITS) Due to its versatile applicability inmetropolitan cities, it gained significant attention . However, it becomes more difficult due to inter-class similarity, intra-classvariability, viewpoint changes, and spatio-temporal uncertainty .…

Principled Simplicial Neural Networks for Trajectory Prediction

We consider the construction of neural network architectures for data onsimplicial complexes . In studying maps on the chain complex of a simplicialcomplex, we define three desirable properties of a neural networkarchitecture . The last property encodes the desirable feature that the output of the neural network depends on the entire simplicial complex and not on a subset of its dimensions .…

Simple Combinatorial Algorithms for the Minimum Dominating Set Problem in Bounded Arboricity Graphs

In the (standard) centralized setting, Bansal and Umboh gave an $O(\alpha)$-approximation LP rounding algorithm . The previous two non-LP-based algorithms, by Lenzen and Wattenhofer[LW10], and Jones et al. [JLR+13], achieve an approximation factor of $O(O(L) in linear time . We address the question of whether one can achieve a simple, elementary $O(‘O)$) algorithm not based on any LP-based methods, either in the centralized setting or in the distributed setting .…

WebRED Effective Pretraining And Finetuning For Relation Extraction On The Web

Relation extraction is used to populate knowledge bases that are important tomany applications . Prior datasets used to train relation extraction models suffer from noisy labels due to distant supervision . We therefore introduce WebRED(Web Relation Extraction Dataset), a strongly-supervised human annotateddataset for extracting relationships from a variety of text found on the WorldWide Web .…

A flow based IDS using Machine Learning in eBPF

eBPF is a new technology which allows dynamically loading pieces of code intothe Linux kernel . It can greatly speed up networking since it enables the kernel to process certain packets without the involvement of a userspaceprogram . So far it has been used for simple packet filtering applications such as firewalls or Denial of Service protection .…

Strong Diameter Network Decomposition

Network decomposition is a central concept in the study of distributed graphalgorithms . We present the first polylogarithmic-round deterministicdistributed algorithm with small messages that constructs a strong-diameternetwork decomposition . The algorithm uses small $O(\log n)-bit messages and with only moderate loss in the parameters .…

On Gradient Coding with Partial Recovery

We consider a generalization of the recently proposed gradient coding framework . Each workertransmits to a master node one or more linear combinations of the gradientsover the data subsets assigned to it . The broad goal of our work is to study the optimal computation andcommunication load per worker .…

Interest aware Message Passing GCN for Recommendation

Graph Convolution Networks (GCNs) manifest great potential in recommendation . When stacking more layers, node embeddings become more similar and eventually indistinguishable, resulted in performance degradation . In this paper, we propose a novel Interest-awareMessage-Passing GCN (IMP-GCN) recommendation model, which performs high-ordergraph convolution inside subgraphs .…

DyNetKAT An Algebra of Dynamic Networks

We introduce a formal language for specifying dynamic updates for SoftwareDefined Networks . Our language builds upon Network Kleene Algebra with Tests(NetKAT) and adds constructs for synchronisations and multi-packet behaviour . We provide a sound and ground-complete axiomatisation of our language .…

Asset Management Taxonomy A Roadmap

The concept of assets is not well-understood and generally delimited to a few types of assets . Artefacts whichhave inherent value for the organisation are assets, and as assets, they are subject to degradation . This degradation occurs over time, as artefacts age, and can be more immediate or slowly over a period of time, similar to the concept of technical debt .…

Causal Inference Q Network Toward Resilient Reinforcement Learning

Deep reinforcement learning (DRL) has demonstrated impressive performance invarious gaming simulators and real-world applications . In practice, aDRL agent may receive faulty observation by abrupt interferences such as black-out, frozen-screen, and adversarial perturbation . How to design aresilient DRL algorithm against these rare but mission-critical and safety-crucial scenarios is an important yet challenging task .…

Using Jupyter for reproducible scientific workflows

Literate computing has emerged as an important tool for computational studies and open science, with growing folklore of best practices . In this work, wereport two case studies – one in computational magnetism and another incomputational mathematics – where domain-specific software was exposed to the Jupyter environment .…

Implicit Regularization in Tensor Factorization

Deep learning is perceived as a tendency of gradient-based optimization to fit training data with predictors of minimal”complexity” The fact that only some types of data give rise to generalization is understood to result from them being especially amenable to fitting with lowcomplexity predictors .…

Approximating the Log Partition Function

Variational approximation, such as mean-field (MF) and tree-reweighted (TRW),provide a computationally efficient approximation of the log-partition function . TRW provably provides an upper bound, but the approximation ratio is generally not quantified . We argue that (a variant of) TRW produces an estimate that is within factor $1/2 of the true log-Partition function for any discrete pairwise graphical model over graph $G$ The ratio is $1$ for trees, $2/N$ for the complete graph over $N$ vertices .…

Co clustering Vertices and Hyperedges via Spectral Hypergraph Partitioning

We propose a novel method to co-cluster the vertices and hyperedges ofhypergraphs with edge-dependent vertices . We leverage randomwalks with EDVWs to construct a hypergraph Laplacian and use its spectralproperties to embed vertices in a common space . Numerical experiments using real-world data demonstratethe effectiveness of our proposed approach in comparison with state-of-the-art alternatives .…

Restorable Shortest Path Tiebreaking for Edge Faulty Graphs

The restoration lemma proves that, in an undirected unweighted graph, anyreplacement shortest path avoiding a failing edge can be expressed as theconcatenation of two original shortest paths . The lemma istiebreaking-sensitive: if one selects a particular canonical shortest path foreach node pair, it is no longer guaranteed that one can build replacement paths .…

Analysis of Growing Tumor on the Flow Velocity of Cerebrospinal Fluid in Human Brain Using Computational Modeling and Fluid Structure Interaction

Cerebrospinal fluid (CSF) plays a pivotal role in normal functioning of brain . Brain tumor on the other hand poses a similar challenge towardsdestabilization of CSF flow by compressing any section of ventricles therebyensuing obstruction . A 3D fluid-structure interaction (FSI) model is developed to study the effect of tumor growth on the flow of cerebro Spinal fluid .…

Dynamic VNF Placement Resource Allocation and Traffic Routing in 5G

5G networks are going to support a variety of vertical services, with adiverse set of key performance indicators (KPIs), by using enabling technologies such as software-defined networking and network functionvirtualization . A critical challenge is that requests may be highlyvarying over time, requiring a solution that accounts for their dynamicgeneration and termination .…

Controller Synthesis for Golog Programs over Finite Domains with Metric Temporal Constraints

Executing a Golog program on an actual robot typically requires additional steps to account for hardware or software details of the robot platform . We describe how to formulate constraints based on a modal variant of the Situation Calculus . We show that forprograms over finite domains and with fully known initial state, the problem ofsynthesizing a controller that satisfies the constraints can be reduced to MTL synthesis .…

Uncertainty Quantification for the 12 lead ECG a Lead Field Approach

The standard electrocardiogram (ECG) is a point-wise evaluation of the bodypotential at certain locations . These locations are subject touncertainty and may vary from patient to patient or even for a single patient . In order to avoid the high computational cost associated to the solution of the bidomain model in the entire torso, we propose a low-rank approach to solve the quantification problem .…

A Compiler Infrastructure for Accelerator Generators

Calyx is a new intermediate language (IL) for compiling high-level programs into hardware designs . Calyx combines a hardware-like structurallanguage with a software-like control flow representation with loops and conditionals . The Calyxcompiler lowers control flow constructs using finite-state machines andgenerates synthesizable hardware descriptions .…

An Overview of Forks and Coordination in Blockchain Development

This manuscript is aimed at elaborating the concept of blockchain technology alongside its coordination and implementation with other emerging technologies, such as smart contract . The discussion of blockchain forks is also covered in this manuscript,depicting fork events created in the blockchain process, their brief history,types, and impacts upon the blockchain development and operation .…

Volunteer contributions to Wikipedia increased during COVID 19 mobility restrictions

When the COVID-19 pandemic broke out, it was unclear whether Wikipediavolunteers would become less active in the face of the pandemic, or whether they would rise to meet the increased demand for high-quality information . Analyzing 223 million edits from 2018 to 2020 across twelve Wikipedia language editions, we find that Wikipedia’s global volunteer community responded remarkably to the crisis .…

Sorting Short Integers

We build boolean circuits of size $O(nm^2)$ and depth $O(\log(n) + m\log(m)$ for sorting $n$ integers each of $m$-bits . This improves on the result of Asharov et al. arXiv:2010.09884 and resolves some of their open questions .…

Tail Modulo Cons

OCaml function calls consume space on the system stack . If a program runs out of stack space, they get the dreaded “StackOverflow” exception — they crash . Tail-recursion requires the programmer to manually performsophisticated program transformations . In this work we propose an implementation of “Tail Modulo Cons” (TMC) forOCaml .…

B ETS A Trusted Blockchain based Emissions Trading System for Vehicle to Vehicle Networks

Urban areas are negatively impacted by Carbon Dioxide (CO2 ) and NitrogenOxide (NOx) emissions . The European Union (EU) introduced an Emissions Trading System (ETS) where organizations can buy or receive emission allowances as needed . However, the current ETS cannotefficiently cope with vehicle mobility, even though vehicles are one of the primary sources of CO2 and NOx emissions .…