Reservoir Based Distributed Machine Learning for Edge Operation

Current RF sensors lack the computational resources to support practical, in-situtraining for intelligent signal classification . Deepdelay Loop Reservoir Computing (DLR) delivers reductions in form factor, hardware complexity and latency compared to the State-ofthe- Art (SoA) neural nets . DLR enables mobile edge platforms to authenticate andthen track emitters with fast SEI retraining .…

An Evaluation of the Archive of Formal Proofs

Archive of Formal Proofs (AFP) is an online repository of formal proofs . It serves as a central location for publishing, discovering, and viewing libraries of proofs . Long-term users of the website are generally satisfied with the AFP but that there are anumber of areas, such as navigation, search and script browsing, that need improvement .…

TreeToaster Towards an IVM Optimized Compiler

A compiler’s optimizer operates over abstract syntax trees (ASTs), applying rewrite rules to replace subtrees of the AST with more efficient ones . Especially on large source repositories, even simply finding opportunities for a rewrite can be expensive . In this paper, we leverage the need to repeatedly find rewrites, and explore options for making the search faster through indexing and incrementalview maintenance (IVM) We consider bolt-on approaches that makeuse of embedded IVM systems like DBToaster, as well as two new approaches:Label-indexing and TreeToaster .…

Radar Target Detection aided by Reconfigurable Intelligent Surfaces

In this work, we consider the target detection problem in a sensingarchitecture where the radar is aided by a reconfigurable intelligent surface(RIS) The RIS is modeled as an array of sub-wavelength small reflectiveelements capable of imposing a tunable phase shift to the impinging waves and,ultimately, of providing the radar with an additional echo of the target .…

Deep Learning based Codebook Design for Code domain Non Orthogonal Multiple Access Achieving a Single User Bit Error Rate Performance

The codebook design for code-domain non-orthogonal multiple access (CD-NOMA) can be considered as a constellation design for multi-user multi-dimensionalmodulation (MU-MDM) This paper proposes an autoencoder (AE)-basedconstellation design for MU-MDm with the objective of achieving a comparablebit error rate (BER) performance to single-user multidimensional modulation (SU-M) It has been demonstrated that the proposed designachieves a single-users BER bound with only 0.2dB loss, equivalently outperforming the existing CD-NomA designs, while maintaining their overloadingfactor .…

Long Term Orbit Dynamics of Decommissioned Geostationary Satellites

In nominal mission scenarios, geostationary satellites perform end-of-lifeorbit maneuvers to reach suitable disposal orbits . This research investigates the long-term orbitevolution of decommissioned geostations . The model accounts for all the relevant harmonics of the gravity field and solar radiation pressure and third-body perturbations caused by the Moon and the Sun .…

Major Cooperative Transitions and Management Theory in the Game of Life

Biological and cultural evolution show a trend towards increasing hierarchical organization, in which entities at one level combine cooperatively to form a new entity at a higher level of organization . John Stewart has proposed a theoreticalframework called Management Theory, which attempts to explain all of the major cooperative transitions in biological and cultural .…

PATE AAE Incorporating Adversarial Autoencoder into Private Aggregation of Teacher Ensembles for Spoken Command Classification

We propose using an adversarial autoencoder (AAE) to replace generativeadversarial network (GAN) in the private aggregation of teacher ensembles . The AAE architecture allows us to obtain good synthetic speech leveraging upona discriminative training of latent vectors . Such synthetic speech is used tobuild a privacy-preserving classifier when non-sensitive data is notsufficiently available in the public domain .…

Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering

This paper presents new parallel algorithms for generating Euclidean minimumspanning trees and spatial clustering hierarchies . Our approach is based on generating a well-separated pair decomposition followed by using Kruskal’s minimum spanning tree algorithm and bichromatic closest paircomputations . We show that our algorithms are theoretically efficient: they have work (number ofoperations) matching their sequential counterparts, and polylogarithmic depth(parallel time) We implement our algorithms and propose a memory optimization that requiresonly a subset of well-Sepated pairs to be computed and materialized, leading to savings in both space (up to 10x) and time .…

Proving Non termination by Program Reversal

We present a new approach to proving non-termination of non-deterministic integer programs . Our technique is rather simple but efficient . It relies on apurely syntactic reversal of the program’s transition system followed by aconstraint-based invariant synthesis with constraints coming from both the original and reversed transition system .…

Catalogs of C and Python Antipatterns by CS1 Students

Understanding students’ programming misconceptions is critical . We propose catalogs ofantipatterns for two programming languages: C and Python . We analyzed the codes of 166 CS1 engineering students when they were codingsolutions to programming exercises . We catalog 41 CS1antipAtterns from 95 cataloged misconceptions in C and .…

Learning Online from Corrective Feedback A Meta Algorithm for Robotics

A key challenge in Imitation Learning (IL) is that optimal state actionsdemonstrations are difficult for the teacher to provide . As an alternative to state action demonstrations, the teacher can provide corrective feedback such as their preferences or rewards . Instead we propose that in orderto learn from a diversity of scenarios we need to learn a variety of feedback that is weakly correlated with the teacher’s true cost function .…

Use of off the shelf information extraction algorithms in clinical informatics a feasibility study of MetaMap annotation of Italian medical notes

Study tested feasibility of using ‘off the shelf’ information extraction algorithms to identify medical concepts from Italian clinical notes . We used MetaMap to map medical concepts to the Unified Medical Language System (UMLS) Results in EXP1 showed that theItalian UMLS Metathesaurus sources covered 91% of the medical terms of the’Disorders’ semantic group, as found in the studied dataset .…

The polarising effect of Review Bomb

The Review Bomb is a phenomenon consisting of a massiveattack by groups of Internet users on a website that displays users’ review on products . The Bomb occurs suddenly and for a shorttime, because in this way it leverages the notorious problem of cold-start: ifreviews are submitted by a lot of fresh new accounts, it makes hard to justifypreventative measures .…

Trends in eBusiness and eGovernment

The first chapter is a critical review and a case study in eBusiness, withspecial attention to the digital currencies resource and its possibilities . The last chapter s purpose was todevelop a measuring and modelling framework, an instrument of IBSQ for theSouth African banking sector .…

NPMs Neural Parametric Models for 3D Deformable Shapes

Parametric 3D models have enabled a wide variety of tasks in computer graphics and vision, such as modeling human bodies, faces, and hands . However, construction of these parametric models is often tedious, as it requires manual tweaking . To this end, we propose Neural ParametricModels (NPMs), a novel, learned alternative to traditional, parametric 3d models, which does not require hand-crafted, object-specific constraints .…

Fingerpad Contact Evolution Under Electrovibration

Displaying tactile feedback through a touchscreen via electrovibration has potential applications in mobile devices, consumer electronics, home appliances, and automotive industry though our knowledge and understanding on the underlying contact mechanics is very limited . The main cause of the increasein friction during full slip is due to an increase in real contact area and the .reduction…

Fairness in Network Friendly Recommendations

Mobile traffic is dominated by content services (e.g., video), which typically use recommendation systems . NFR increase the network performance at the cost of being unfair towards certain contents when compared to the standard recommendations . Fair-NFR can achieve high network gains (similar to non-fair) with little unfairness, authors say .…

Continuum Deformation Coordination of Multi Agent Systems Using Cooperative Localization

This paper studies the problem of decentralized continuum deformation coordination of multi-agent systems aided by cooperative localization . We treatagents as particles inside a triangular continuum (deformable body) in a2-Dmotion space . Followers distributed inside theleading tri-angle acquire continuum deformed in a decentralized fashion byintegrating cooperative localization and local communication .…

Time Series Imaging for Link Layer Anomaly Classification in Wireless Networks

The number of end devices that use the last mile wireless connectivity isdramatically increasing with the rise of smart infrastructures . Toefficiently manage such massive wireless networks, more advanced and accurate monitoring and malfunction detection solutions are required . The best performing model based on recurrence plot transformation leads to up to 55% increase compared to the state of the art where classical machine learning techniques are used .…

A remark on discretization of the uniform norm

Discretization of the uniform norm of functions from a given finitedimensional subspace of continuous functions is studied . We pay special attention to the case of trigonometric polynomials with frequencies from anarbitrary finite set with fixed cardinality . We prove a general result, which connects the upper bound on the number of sampling points in the discretization .…

Designing for human AI complementarity in K 12 education

Successful forms of human-AI partnership have rarely been demonstrated in real-world settings . Lumilo smartglasses help teachers help their students in AI-supported classrooms . Smartglasses provide real-time analytics about students’ learning, metacognition, and behavior . Results from a field study conducted in K-12 classrooms indicate that students learn more when teachers and AI tutors work together during class .…

From banks to DeFi the evolution of the lending market

The Internet of Value (IOV) with its distributed ledger technology (DLT)underpinning has created new forms of lending markets . Lending protocols are gaining traction, holding an aggregate liquidity supply of over $40 billion . We discuss the persisting reliance of DeFi lending on the traditional financial system, and conclude with the outlook of the lending market in the IOV era .…

VisQA X raying Vision and Language Reasoning in Transformers

Visual Question Answering systems target answering open-ended textual questions given input images . They are a testbed for learning high-levelreasoning with a primary use in HCI, for instance assistance for the visually impaired . Recent research has shown that state-of-the-art models tend toproduce answers exploiting biases and shortcuts in the training data .…

Data driven balancing of linear dynamical systems

We present a novel reformulation of balanced truncation, a classical model reduction method . The principal innovation comes through theuse of system response data that has been either measured or computed, withoutreference to any prescribed realization of the original model .…

A Comparison of Similarity Based Instance Selection Methods for Cross Project Defect Prediction

Previous studies have shown that training data instance selectionbased on nearest neighborhood (NN) information can lead to better performance in cross project defect prediction . Locality Sensitive Hashing (LSH) can be affective as exact methods . LSH and GIS favor recall more than precision, however, in environments where precision is considered more important NN-Filter should be considered .…

Neurological Status Classification Using Convolutional Neural Network

A Convolutional Neural Network (CNN) model is able to accuratelydiscriminate between 4 different phases of neurological status in a non-Electroencephalogram(EEG) dataset recorded in an experiment in which subjects are exposed to physical, cognitive and emotional stress . We show that CNN models outperformstradic classification methods such as SVM, and RF, in comparison to other methods, in robustnessto noise by 97.46% accuracy on a noisy dataset .…

How Powerful are Performance Predictors in Neural Architecture Search

In this work, we give the first large-scalestudy of performance predictors by analyzing 31 techniques ranging fromlearning curve extrapolation, to weight-sharing, to supervised learning, to “zero-cost” proxies . We test a number of correlation- and rank-based measures in a variety of settings, as well as the ability of each technique to speed up predictor-based NAS frameworks .…