Joint Autoregressive and Graph Models for Software and Developer Social Networks

Social network research has focused on hyperlink graphs, bibliographiccitations, friend/follow patterns, influence spread, etc. Large softwarerepositories form a highly valuable networked artifact, usually in the form of a collection of packages, their developers, dependencies among them,and bug reports . This “social network of code” is rarely studied by social network researchers .…

Multimodality in VR A survey

Virtual reality has the potential to change the way we create and consumecontent in our everyday life . Entertainment, training, design andmanufacturing, communication, or advertising are all applications that already benefit from this new medium reaching consumer level . In VR, like inthe real world, users integrate the multimodal sensory information they receive to create a unified perception of the virtual world .…

UNIT Unifying Tensorized Instruction Compilation

Tensorized instructions formixed-precision tensor operations, like Intel VNNI, Tensor Core, and ARM-DOT . These instructions involve a computing idiom that reduces multiple lowprecision elements into one high precision element . The generated end-to-end inference model achieves 1.3x speedup over Intel oneDNN on an x86 CPU and 1.13x speed up over TVM solution for ARM DOT on an ARM CPU .…

A Joint Diagonalization Based Efficient Approach to Underdetermined Blind Audio Source Separation Using the Multichannel Wiener Filter

This paper presents a computationally efficient approach to blind sourceseparation (BSS) of audio signals . When there are as manysources as microphones as microphones (i.e., the determined case), BSS can be performedcomputationally efficiently by independent component analysis (ICA) However, ICA is basically inapplicable to the underdeterminedcase .…

Assessing the Benefits of Model Ensembles in Neural Re Ranking for Passage Retrieval

Modelensembling can indeed benefit the ranking quality, particularly with supervisedlearning-to-rank although also with unsupervised rank aggregation . Tests with the MS-MARCO dataset show that modelensembled can benefit the rankings quality . We use a previous technique named FastGeometric Ensembling to generate multiple model instances from particulartraining schedules, then focusing or attention on different types of approaches to combining the results from the multiple models .…

Model based Policy Search for Partially Measurable Systems

Monte Carlo Probabilistic Inferencefor Learning COntrol for Partially Measurable Systems (MC-PILCO4PMS) relies onGaussian Processes (GPs) to model the system dynamics, and on a Monte Carlo approach to update the policy parameters . The effectiveness of the proposed algorithm has been tested both in simulation and in two real systems .…

Machine Learning Based Early Fire Detection System using a Low Cost Drone

This paper proposes a new machine learning based system for forest fireearlier detection in a low-cost and accurate manner . The common problem in the prevalent algorithms used in firedetection is the high false alarm and overlook rates. Confirming the resultobtained from the visualization with an additional supervision stage will increase the reliability of the system as well as guarantee the accuracy of the result.…

E commerce warehousing learning a storage policy

E-commerce with major online retailers is changing the way people consume . The goal of increasing delivery speed while remaining cost-effective posessificant new challenges for supply chains as they race to satisfy thegrowing and fast-changing demand . We propose formulating this system as a Partially Observable Markov Decision Process, and using a Deep Q-learningagent from Reinforcement Learning, to learn an efficient real-time storagepolicy that leverages repeated experiences and insightful forecasts .…

The Diagnosis of Asthma using Hilbert Huang Transform and Deep Learning on Lung Sounds

Lung auscultation is the most effective and indispensable method for diagnosing various respiratory disorders by using the sounds from the airways during inspirium and exhalation using a stethoscope . The proposed DBN separated lung sounds from asthmatic and healthy subjects with high classification performance rates of 84.61%, 85.83%, and 77.11% for overall accuracy, sensitivity, andselectivity, respectively using frequencytime analysis .…

Complete trace models of state and control

We consider a hierarchy of four typed call-by-value languages with either higher-order references or callcc or no control operator . The paper provides a systematic development ofoperational game semantics for all four cases, which represent the state-based face of the so-called semantic cube .…

Synwalk Community Detection via Random Walk Modelling

Synwalk builds upon a solid theoretical basis and detectscommunities by synthesizing the random walk induced by the given network from a class of candidate random walks . We thoroughly validate the effectiveness ofour approach on synthetic and empirical networks, respectively, and compare Synwalk’s performance with the performance of Infomap and Walktrap .…

Monitoring nonstationary processes based on recursive cointegration analysis and elastic weight consolidation

Traditional approaches generally misidentify the normal dynamic deviations as faults and thus lead to high false alarms . In this paper, recursive cointegrationanalysis (RCA) is first proposed to distinguish the real faults from normalsystems changes . When the systementers a new operating condition, the RCA-RPCA model is rebuilt to deal with the new condition .…

Work Patterns of Software Engineers in the Forced Working From Home Mode

The COVID-19 outbreak has caused a major disruption worldwide . But what happened to companies developing digital services? Were they interrupted as much or at all? And how has the enforcedWorking-From-Home (WFH) mode impacted their ability to deliver software? We hear that some managers are concerned that their engineers are not working effectively from home, or even lack the motivation to work in general, that teams lose touch and that managers do not notice when things go wrong .…

Commutative Event Sourcing vs Triple Graph Grammars

This paper proposes Commutative Event Sourcing as a simple and reliablemechanism for model synchronisation, bidirectional model to modeltransformations, incremental updates, and collaborative editing . It is a restricted form of a Triple Graph Grammar where the rules are either overwriting or commutative .…

Multi robot energy autonomy with wind and constrained resources

One aspect of the ever-growing need for long term autonomy of multi-robotsystems is ensuring energy sufficiency . In scenarios where charging facilities are limited, battery-powered robots need to coordinate to share access . In this work we extend previous results by considering robotsthat carry out a generic mission while sharing a single charging station, while being affected by air drag and wind fields .…

Boost then Convolve Gradient Boosting Meets Graph Neural Networks

Graph neural networks (GNNs) are powerful models that have been successful invarious graph representation learning tasks . Previous GNN models have mostly focused on networks withhomogeneous sparse features . In this work, we propose a novel architecture that trains GBDT and GNN jointly to get the best of both worlds: the GBDT modeeals with heterogeneous features, while GNN accounts for the graph structure .…

Ten Simple Rules for Attending Your First Conference

Conferences are a mainstay of most scientific disciplines, where scientists come together to share cutting-edge ideas and approaches . The authors of this piece have attended their fair share of conferences and have mentored hundreds of students in understanding the “unwrittenrules” and pro-tips of conference attendance .…

A Gauss Seidel projection method with the minimal number of updates for stray field in micromagnetic simulations

Magnetization dynamics in magnetic materials is often modeled by theLandau-Lifshitz equation . Inmicromagnetic simulations, the computational cost relies heavily on thetime-marching scheme and evaluation of stray field . Explicit marchingschemes are efficient but suffer from severe stability constraints . GSPM-BDF2 updates the stray field only once, leading to an efficiency improvement of about $60\%$ than the state-of-the-art GSPm for micromagnetic simulation .…

BOOSTR A Dataset for Accelerator Control Systems

BOOSTR (Booster Operation Optimization Sequential Time-Series for Reinforcement) was created to provide cycle-by-cycle time series of readings and settings from instruments and controllable devices of the Booster, Fermilab’s Rapid-Cycling Synchrotron (RCS) operating at 15 Hz . To our knowledge, this is the first known dataset of accelerator device device parameters made publicly available .…

A Fragile multi CPR Game

A Fragile CPR Game is an instance of a resource sharing game where a common-pool resource is shared among multiple players . Each player has a fixed initial endowment and is faced with the task of investing in the resource without forcing it to fail .…

User Aware Power Management for Mobile Devices

The power management techniques to extend battery lifespan is becomingincreasingly important due to longer user applications’ running time in mobiledevices . Even when users do not use any applications, battery lifespandecreases continually . In this paper, we propose anew power management system that recognizes idle time of the device to reduce the battery consumption of mobile devices .…

Centralized Collision free Polynomial Trajectories and Goal Assignment for Aerial Swarms

Computationally tractable methods are developed for centralized goalassignment and planning of collision-free polynomial-in-time trajectories for multiple aerial robots . The method first assigns robots to goals to minimize total time- in-motion based on initial trajectories . The plans are then refined by checking for potential collisions and resolving them using either start time delays or altitude assignment .…

Location Management in IP based Future LEO Satellite Networks A Review

Future integrated terrestrial, aerial, and space networks will involvethousands of Low Earth Orbit (LEO) satellites forming a network ofmega-constellations . We present acomprehensive and critical review of the state-of-the-art research in LEOSatNets location management . We give an overview of the InternetEngineering Task Force (IETF) mobility management standards (e.g.,…

Arabic Speech Recognition by End to End Modular Systems and Human

Recent advances in automatic speech recognition (ASR) have achieved accuracy levels comparable to human transcribers . Previous work focused on the Englishlanguage and modular hidden Markov model-deep neural network (HMM-DNN) systems . For ASR the end-to-end work led to 12.5%, 27.5% WER; a new milestone for the MGB2, MGB3, and MGB5 challenges respectively .…