On line Optimal Ranging Sensor Deployment for Robotic Exploration

The approach is general for any class of mobile system, we run simulations and experiments with indoor drones . We provide a detailed analysis of the uncertainty of the positioning system while the UWB infrastructure grows . We developed a genetic algorithm that minimizes the deployment of newanchors, saving energy and resources on the mobile robot and maximizing the mission .…

A New Approach to Complex Dynamic Geofencing for Unmanned Aerial Vehicles

Geofences are proposed as one line of defence to limit UAVs from flying into perimeters of other aircraft and restricted locations . Geofencing algorithms lack accuracy during the calculation of complex geofences, particularly in dynamic urban environments . We propose a new algorithm based on alpha shapes and Voronoi diagrams, which we integrate into an on-drone framework using an open-source mapping database from OpenStreetMap .…

Learning Realtime One Counter Automata

Ouralgorithm uses membership and equivalence queries as in Angluin’s L* algorithm . In a partialequivalence query, we ask the teacher whether the language of a givenfinite-state automaton coincides with a counter-bounded subset of the targetlanguage . We evaluate an implementation of our algorithm on a number of randombenchmarks .…

Mobility Label Based Network Hierarchical Mobility Management and Packet Forwarding Architecture

Mobility LabelBased Network (MLBN) is a new approach to the network layer mobility management problem that relies solely on MPLS to provide both macro- and micro-mobility for IPv4 and IPv6 mobile hosts and routers . This new approach does not rely on the existing IP mobility management protocols such as Mobile IP and is based on the combination of Multi- Protocol BGP (MP-BGP) and MPLS .…

Algorithms Using Local Graph Features to Predict Epidemics

We study a simple model of epidemics where an infected node transmits theinfection to its neighbors independently with probability $p$. This is alsoknown as the independent cascade or Susceptible-Infected-Recovered (SIR) model . The size of an outbreak in this model is closelyrelated to that of the giant connected component in “edge percolation”, whereeach edge of the graph is kept independently .…

Dynamic Tolling for Inducing Socially Optimal Traffic Loads

How to design tolls that induce socially optimal traffic loads? We propose atwo-timescale discrete-time stochastic dynamics that adaptively adjusts thetoll prices on a parallel link network . We show that the loads and the tolls concentrate in a neighborhood of the fixed point, which correspondsto the socially optimal load and toll price .…

DNA Codes over the Ring mathbb Z _4 w mathbb Z _4

We extend the Gau map andGau distance, defined in DKBG, over all the $16$ rings$\mathcal{R}__\theta . An isometry between the codes over the rings and the analogous DNA codes is established in general . We propose family of DNA codes that satisfies reverse and reverse-complement constraints using the Reed-Muller type codes .…

Empirical Policy Optimization for n Player Markov Games

In single-agent Markov decision processes, an agent can optimize its policy based on the interaction with environment . In multi-player Markov games, the interaction is non-stationary due to the behaviors of other players . The core is to evolve one’s policy according to not just its current in-game performance, but an aggregation of its performance over history .…

Projected Model Counting Beyond Independent Support

The past decade has witnessed a surge of interest in practical techniques forprojected model counting . Despite significant advancements, performance scaling remains the Achilles’ heel of this field . Inapplications such as verification of binarized neural networks, quantification of information flow, reliability of power grids etc.,…

Comparing Deep Neural Nets with UMAP Tour

A tool, UMAP Tour, is built to visually inspect and compare behavior of real-world neural network models . The method used in the visualization alsoimplies a new similarity measure between neural network layers . Using the tool and the similarity measure, we find concepts learned instate-of-the-art models and dissimilarities between them, such as GoogLeNet andResNet .…

State Space Constraints Improve the Generalization of the Differentiable Neural Computer in some Algorithmic Tasks

Memory-augmented neural networks (MANNs) can solve algorithmic tasks like sorting . However, they often do not generalize to lengths of input sequences seen in the training phase . We introduce two approaches: state compression and state regularization . We show that both approaches can improve the generalization capability of a particular type of MANN, the differentiableneural computer (DNC) We also compare our approaches to a stateful and a statelesscontroller on a set of tasks .…

Mode I and Mode II stress intensity factors and dislocation density behaviour in strain gradient plasticity

In this study, we use the mechanism-based strain gradient plasticity theory to evaluate both crack tip dislocation density behaviour and the coupled effectof the material plastic properties and the intrinsic material length onnon-linear amplitude factors . The constitutive relations are based on Taylor’s dislocation model, which enables gaining insights into the role of the increased dislocationdensity associated with large gradients in plastic strain near cracks .…

Don t Judge Me by My Face An Indirect Adversarial Approach to Remove Sensitive Information From Multimodal Neural Representation in Asynchronous Job Video Interviews

Adversarial methods have been proven to effectively remove sensitive information from the latent representation of neural networks without the need to collect any sensitive variable . This is the first application of adversarial techniques for obtaining a multimodal fair representation in the context of video job interviews .…

Turing Tumble is Turing Complete

It is shown that the toy Turing Tumble, suitably extended with an infinitelylong game board and unlimited supply of pieces, is Turing-Complete . This isachieved via direct simulation of a Turing machine . Unlike previouslyinformally presented constructions, we do not encode the finite controlinfinitely many times, we need only one trigger/ball-hopper pair, and we proveour construction correct .…

Color Image Segmentation Using Multi Objective Swarm Optimizer and Multi level Histogram Thresholding

This paper presents a new way forunsupervised image segmentation by combining histogram thresholding methods and multi-objective swarm intelligence algorithms . Segmenting entire color channels with the same thresholds also benefits from the fact that our proposed method needs fewer thresholds to segment the image than otherthresholding algorithms; thus, it requires less memory space to savethresholds .…

Evaluating NISQ Devices with Quadratic Nonresidues

Algorithmsshowing a quantum advantage are often tailored precisely to what a particular NISQ does well . We prove quantum computers can find quadratic nonresidues indeterministic polynomial time . Classical version of this problem remains unsolved after hundreds of years . A success rate greater than 75% provides evidence of quantumadvantage.…

Context aware Reranking with Utility Maximization for Recommendation

Reranking rearranges items in the initial rankinglists from the previous ranking stage to better meet users’ demands . An ideal reranking algorithm should consider the counterfactual context — the position and the alignment of the items in reranked lists . CRUM significantly outperforms the state-of-the-art models in terms of both relevance-based metrics and utility-based metric metrics.…

Neural network learning of SPOD latent dynamics

We aim to reconstruct the latent space dynamics of high dimensional systems using model order reduction via the spectral proper orthogonal decomposition(SPOD) The proposed method is based on three fundamental steps: in the first,we compress the data from a high-dimensional representation to a lowerdimensional one by constructing the SPOD latent space .…

An Empirical Study of Protocols in Smart Contracts

Smart contracts are programs that are executed on a blockhain . They have been used for applications in voting, decentralized finance, and supply chainmanagement . But vulnerabilities in smart contracts have been abused by hackers, leading to financial losses . Understanding state machine protocols has been identified as important to catching common bugs, improving documentation, and optimizing smart contracts .…

Semantics of Conjectures

This paper aims to expand and detail the notion of formal semantics of Conjectures by applying a theoretic-model approach . After a short introduction to the concepts and basics, we will start from the concept ofSimple Interpretation of RDF, applying and extending the semantic rules and conditions to fully cover the concepts .…

Ctrl Shift How Privacy Sentiment Changed from 2019 to 2021

People’s privacy sentiments drive changes in legislation and may influencetheir willingness to use a variety of technologies . After the onset of COVID-19, we observe significant changes in Americans’ privacy sentimentstoward government- and health-related data uses . We observe additionalchanges in the context of other national events such as the U.S.…

Small Data and Process in Data Visualization The Radical Translations Case Study

This paper uses the collaborative project Radical Translations as case study to examine some of the theoretical perspectives informing the adoption andcritique of data visualization in the digital humanities . It showcases how data visualization is used within a King’s DigitalLab project lifecycle to facilitate collaborative data exploration within the project interdisciplinary team .…

Fair and Efficient Allocations of Chores under Bivalued Preferences

We study the problem of fair and efficient allocation of a set of indivisible chores to agents with additive cost functions . We consider the popular fairnessnotion of envy-freeness up to one good (EF1) with the efficiency notion ofPareto-optimality (PO) While it is known that an EF1+PO allocation exists andcan be computed in pseudo-polynomial time in the case of goods, the same problem is open for chores .…

Wideband and Entropy Aware Deep Soft Bit Quantization

Deep learning has been recently applied to physical layer processing indigital communication systems . We introduce a novel deep learning solution for soft bitquantization across wideband channels . Our method is trained end-to-end withquantization- and entropy-aware augmentations to the loss function .…

A Primer on the Statistical Relation between Wireless Ultra Reliability and Location Estimation

This letter statistically characterizes the impact of location estimationuncertainty in the wireless communication reliability . The reliability – characterized by how likely the outage probabilityis to be above a target threshold – can be sensitive to location errors . We highlight the difficulty of choosing a rate that both meets targetreliability and accounts for the location uncertainty, and that the most directsolutions suffer from being too conservative .…

The search of Type I codes

A self-dual binary linear code is called Type I code if it has singly-evencodewords, i.e.~it has codewords with weight divisible by $2.$ The purpose of this paper is to investigate interesting properties of Type I codes . Further, we build up a computer-based code-searching program .…

DNA Codes over the Ring mathbb Z _4 w mathbb Z _4

We extend the Gau map andGau distance, defined in DKBG, over all the $16$ rings$\mathcal{R}__\theta . An isometry between the codes over the rings and the analogous DNA codes is established in general . We propose family of DNA codes that satisfies reverse and reverse-complement constraints using the Reed-Muller type codes .…