SceneGen Learning to Generate Realistic Traffic Scenes

SceneGen is a neural autoregressive model of traffic scenes that eschews the need for rules and heuristics . SceneGen inserts actors of various classes into the scene and synthesizes their sizes, orientations, and velocities . It can be used to train perception models that generalize to the real world, we say .…

Strings and Coins and Nimstring are PSPACE complete

Strings-and-Coins is strongly PSPACE-complete onmultigraphs . This result improves the best previous result, NP-hardness, argued in Winning Ways . Our result also applies to the Nimstring variant, where thewinner is determined by normal play . One step in our reduction is the reduction (also from Winning Ways) from Nimstring toStrings andCoins .…

Hypernetworks From Posets to Geometry

We show that hypernetworks can be regarded as posets which, in their turn,have a natural interpretation as simplicial complexes . This greatly simplifies the geometric PersistentHomology method we previously proposed . This allows us to canonicallyassociate a simplicial complex structure to a hypernetwork, directed orundirected .…

Latent Variable Models for Visual Question Answering

Conventional models for Visual Question Answering (VQA) explore deterministic approaches with various types of image features, question features, and attention mechanisms . In this work, we propose latent variable models for VQA where extrainformation (e.g. captions and answer categories) are incorporated as latentvariables to improve inference, which in turn benefits question-answering performance .…

Weakly Supervised Hierarchical Models for Predicting Persuasive Strategies in Good faith Textual Requests

Modeling persuasive language has the potential to better facilitate ourdecision-making processes . We introduce a large-scalemulti-domain text corpus for modeling persuasive strategies in good-faith text requests . We design a hierarchical weakly-supervised latent variablemodel that can leverage partially labeled data to predict such associatedpersuasive strategies for each sentence .…

Intrusion Detection Systems for Smart Home IoT Devices Experimental Comparison Study

Intrusion Detection Systems are presented as pertinent tools that can provide network-level protection for smart devices deployed in home environments . These systems monitor the network activities of the smarthome-connected de-vices and focus on alerting suspicious or malicious activity . They also can deal with detected abnormal activities by hindering the impostorsin accessing the victim devices .…

Revisiting Driver Anonymity in ORide

ORide is a privacy-preserving RHS proposed in 2017 and uses SomewhatHomomorphic Encryption (SHE) In their protocol, a rider and all drivers in azone send their encrypted coordinates to the RHS Service Provider . The rider decrypts these and selects the optimal driver with leastEuclidean distance .…

SEDAT Security Enhanced Device Attestation with TPM2 0

Remote attestation is one of the ways to verify the state of an untrusteddevice . SEDAT provides a way for verifier to get on-demand device integrity and authenticity status via a secure channel . It also enablesthe verifier can detect counterfeit hardware, change in firmware, and softwarecode on the device .…

AR based Modern Healthcare A Review

Augmented reality has proposed numerous smart applications in healthcaredomain including wearable access, telemedicine, remote surgery, diagnosis of medical reports, emergency medicine, etc. The aim of the developed augmentedhealthcare application is to improve patient care, increase efficiency, anddecrease costs . This article explores the services of augmented-based healthcare solutions and throws light onrecently invented ones as well as their respective platforms.…

Galleon Reshaping the Square Peg of NFV

Software is often used for Network Functions (NFs) that are applied to traffic in thenetwork . The community has hoped that NFV would enable rapid development of newNFs and leverage commodity computing infrastructure . The challenge for researchers and operators has been to align the square peg of high-speed packetprocessing with the round hole of cloud computing infrastructures andabstractions, all while delivering performance, scalability, and isolation .…

Dynamic Ternary Content Addressable Memory Is Indeed Promising Design and Benchmarking Using Nanoelectromechanical Relays

Ternary content addressable memory (TCAM) has been a critical component incaches, routers, etc., in which density, speed, power efficiency, and reliability are the major design targets . This paper proposes a custom low-power dynamic TCAM using nanoelectromechanical(NEM) relay devices . By harnessing the unique NEM relay characteristics with a proposed novel cell structure, the proposed TCAM occupies a small footprint of only 3transistors (with two NEM relays integrated on the top through theback-end-of-line process), which significantly outperforms the density of16-transistor SRAM-based TCAM .…

Binary strings of finite VC dimension

The complexity of a string can be measured by the richness of its substrings . This kind of complexity is captured by the standard stringcomplexity function . Substrings can be viewed as subsets of an index set . This allows us to apply measures of subset complexity such as VC dimension .…

Evaluating User Experiences in Mixed Reality

Measure user experience in MR (i.e., AR/VR) user studies is essential . Researchers apply a wide range of measuring methods using objective (e.g.,biosignals, time logging), behavioral (e., gaze direction, movementamplitude) metrics . Many of these measurement instruments were adapted from use-cases outside of MR buthave not been validated for usage in MR experiments .…

Attention Based Video Summaries of Live Online Zoom Classes

Using facial attention analysis software we create personalised videosummaries composed of just the parts where a student’s attention was below somethreshold . We can also factor in other criteria into video summary generations such as parts where the student was not paying attention while others in the class were, and parts of the video that other students have replayedextensively .…

Self Supervised Multi Channel Hypergraph Convolutional Network for Social Recommendation

Hypergraph provides anatural way to model complex high-order relations, while its potential for social recommendation is under-explored . Social relations are often used to improve recommendation quality and mostexisting social recommendation models exploit pairwise relations to minepotential user preferences . We propose a multi-channel hypergraph convolutional network to enhance socialrecommendation .…

A Zero Attentive Relevance Matching Networkfor Review Modeling in Recommendation System

Review-based methods for recommendation can be categorized into two groups: siamese models that build static userand item representations from reviews . Interaction-based models encode user and item representations according to thesimilarity or relationships of their reviews . Our model implements a relevance matching model with regularized training losses to discover user relevant information from longitem reviews, and it also adapts a zero attention strategy to dynamicallybalance the item-dependent and item-independent information extracted from userreviews .…

An MCMC Method to Sample from Lattice Distributions

We introduce a Markov Chain Monte Carlo algorithm to generate samples from probability distributions supported on a $d-dimensional lattice . The algorithm is based on the Metropolis-Hastings framework . We show that our algorithm is uniformly ergodic if $-\log(\pi)$satisfies a gradient Lipschitz condition .…

New Low Rank Optimization Model and Convex Approach for Robust Spectral Compressed Sensing

This paper investigates recovery of an undamped spectrally sparse signal and its spectral components from a set of regularly spaced samples . We propose a new low rank optimization model partially inspired by forward-backward processing for line spectral estimation . We present convex relaxation approaches with the model and show their provable accuracy and robustness to bounded and sparsenoise.…

Community Detection in Blockchain Social Networks

In this work, we consider community detection in blockchain networks . For the Bitcoin network, wemodify the traditional community detection method and apply it to the transaction social network to cluster users with similar characteristics . Forthe Ethereum network, on the other hand, we define a bipartite social graph based on the smart contract transactions .…

Deciding What to Learn A Rate Distortion Approach

Agents that learn to select optimal actions represent a prominent focus of the sequential decision-making literature . In the face of a complex environment or constraints on time and resources, aiming to synthesize such anoptimal policy can become infeasible . In this work, leveraging rate-distortion theory, weautomate this process such that the designer need only express theirpreferences via a single hyperparameter and the agent is endowed with the ability to compute its own learning targets that best achieve the desired trade-off .…

A Hitchhiker s Guide to Structural Similarity

Structural Similarity (SSIM) Index is a very widely used image/video quality model . Several public implementations of the SSIMand Multiscale-SSIM algorithms have been developed, which differ inefficiency and performance . This “bendable ruler” makes the process of quality assessment of encoding algorithms unreliable .…

UFL Dual Spaces a proposal

This white paper highlights current limitations in the algebraic closureUnified Form Language (UFL) UFL currently represents forms over finite elementspaces . It proposes changes to the UFL language to support dual spaces as first classtypes in UFL . This document sketches the relevant mathematical areas and proposes changes in the language .…

A symbol based analysis for multigrid methods for Block Circulant and Block Toeplitz Systems

In the block-Toeplitz setting, that is, in the casewhere the matrix entries are small generic matrices instead of scalars . We treatmatrix-valued trigonometric polynomials which can be non-diagonalizable andsingular at all points . We extend the analysis to the V-cycle method proving a linear convergence rate understronger conditions, which resemble those given in the scalar case .…

Asymptotic analysis in multivariate average case approximation with Gaussian kernels

We consider tensor product random fields $Y_d$ and $d\in\mathbb{N}$, whosecovariance funtions are Gaussian kernels . We investigate the growth of $n^{Y_D}(\varepsilon)$ forarbitrary fixed $d(0,1)$ and  $d(d)\to\infty) We find criteria of boundedness for $n.y_d$. We show that only special quantiles of self-decomposable distributionfunctions appear as functions $q$ in a given asymptotics .…

Overlap Minimization Scheduling Strategy for Data Transmission in VANET

The vehicular ad-hoc network (VANET) based on dedicated short-rangecommunication (DSRC) is a distributed communication system . The competition and backoff mechanisms ofCSMA/CA often bring additional delays and data packet collisions, which mayhardly meet the QoS requirements in terms of delay and packets delivery ratio(PDR) This paper presents a connection-level scheduling algorithm overlaid on CSMA/ca to schedule the start sending time of each transmission .…

Blind Optimal User Association in Small Cell Networks

Finding an optimal user association policy in dynamic environments is challenging because trafficdemand fluctuations over time are non-stationary and difficult to characterizestatistically . We introduce a periodic benchmark for OCO problems that generalizes state-of-the-art benchmarks . We exploit inherentproperties of the online user association problem and propose PerOnE, a simple online learning scheme that dynamically adapts the association policy toarbitrary traffic demand variations .…

From hand to brain and back Grip forces deliver insight into the functional plasticity of somatosensory processes

The human somatosensory cortex is intimately linked to other central brain functions such as vision, audition, mechanoreception, and motor planning andcontrol . These links are established through brain learning, and display aconsiderable functional plasticity . Variations in human grip force are adirect reflection of this kind of functional Plasticity .…

Wearable Sensors for Spatio Temporal Grip Force Profiling

Wearable biosensor technology enables real-time, convenient, and continuousmonitoring of users behavioral signals . Such include signals relative to bodymotion, body temperature, biological or biochemical markers, and individualgrip forces . A four step pick and drop imageguided and robot assisted precision task has been designed for exploiting awearable wireless sensor glove system .…