Learning to Decode Reinforcement Learning for Decoding of Sparse Graph Based Channel Codes

Low-density parity check (LDPC) codes have been standardized in the context of 5G cellular communications systems . These codes are typically decoded via belief propagation iterative decoding on the corresponding bipartite (Tanner) graph of the code via flooding . In contrast, we utilize a sequential update policy which selects the optimumcheck node (CN) scheduling in order to improve decoding performance .…

Continuous Safety Verification of Neural Networks

Deploying deep neural networks (DNNs) as core functions in autonomous drivingcreates unique verification and validation challenges . This paper considersapproaches to transfer results established in the previous DNN safetyverification problem to the modified problem setting . The overall concept is evaluated in a$1/10$-scaled vehicle that equips a DNN controller to determine the visualwaypoint from the perceived image .…

Discriminative Sounding Objects Localization via Self supervised Audiovisual Matching

Discriminatively localizing sounding objects in cocktail-party scenes is commonplace for humans, but still challenging for machines . We propose a two-stage learning framework to perform self-supervised class-aware sounding object localization . Code is available athttps://://://github.com/DTaoo/Discriminative-Sounding-Objects-Localization. The model is superior in filtering out silent objects and pointing out thelocation of sounding objects of different classes .…

Structured strong boldsymbol ell ifications for structured matrix polynomials in the monomial basis

Most of the matrixpolynomials arising in applications are structured polynomials . The standard way to solve Polynomial Eigenvalue Problems is by means oflinearizations . The most frequently used linearizations belong to generalconstructions, known as companion linearizations . In this paper, we present, for the first time, a family of (generalized)companion $ell$-ifications that preserve any of these structures .…

Efficient high order accurate Fresnel diffraction via areal quadrature and the nonuniform FFT

We present a fast algorithm for computing the diffracted field from arbitrarybinary (hard-edged) planar apertures and occulters in the scalar Fresnelapproximation . It combines the high accuracy of edge integral methods with the high speedof Fourier methods . It is roughly $10^4\times$ faster than the state of the art in accurately computing the set oftelescope pupil wavefronts .…

A Neurochaos Learning Architecture for Genome Classification

There has been empirical evidence of presence of non-linearity and chaos atthe level of single neurons in biological neural networks . The properties ofchaotic neurons inspires us to employ them in artificial learning systems . Here, we propose a Neurochaos Learning (NL) architecture, where the neurons used to extract features from data are 1D chaotic maps .…

On Bivariate Fractal Interpolation for Countable Data and Associated Nonlinear Fractal Operator

We provide a framework to construct fractal interpolation surfaces for a prescribed countably infinite data set on a rectangular grid . We obtain a family of bivariate fractal functions simultaneously interpolating and approximating a prescribedbivariate continuous function . Some elementary properties of the associatednonlinear (not necessarily linear) fractal operator are established, therebyinitiating the interaction of the notion of fractal .…

Towards Somaesthetics Inspired Games Exploring the Influence of a Mirror Effect on Self Presentation in a Public Setting

We report on an initial user study, which explores how players of anaugmented mirror game, self-style or self-present themselves when they are allowed to see themselves in the mirror compared to when they do not seethemselves . Ultimately, presenting a self-image to gamers in a social setting resulted in behavior change, which we argue could be utilized carefully from a Somaesthetics perspective as an experience design feature in futuregames.…

An Elastic IoT Device Management Platform

An IoT testbed plays a vital role in aiding developers to test their applications without being deploying it to the target environment . This testbed would be best suited for testing applications which demand robust nature, remote monitoring and control, incorporation of .…

Power law dynamics in genealogical graphs

Several populational networks present complex topologies when implemented inevolutionary algorithms . A common feature of these topologies is the emergence of a power law . In genealogical networks, the power law can be observed by measuring the impact of individuals in the population, which can be calculated using the Event Takeover Value algorithm .…

The Greatest Teacher Failure is Using Reinforcement Learning for SFC Placement Based on Availability and Energy Consumption

Software defined networking (SDN) and network functions virtualisation (NFV)are making networks programmable and consequently much more flexible and agile . An availability- and energy-aware solution based on reinforcement learning (RL) is proposed for dynamic SFC placement . PPO2 generally outperformed A2Cand a greedy approach both in terms of acceptance rate and energy consumption .…

FedAT A Communication Efficient Federated Learning Method with Asynchronous Tiers under Non IID Data

Federated learning involves training a model over massive distributevices, while keeping the training data localized . FedAT uses astraggler-aware, weighted aggregation heuristic to steer and balance the training for further accuracy improvement. FedAT compresses the uplink anddownlink communications using an efficient, polyline-encoding-based compressional algorithm, therefore minimizing the communication cost.…

Robots State Estimation and Observability Analysis Based on Statistical Motion Models

This paper presents a generic motion model to capture mobile robots’ dynamicbehaviors (translation and rotation) The model is based on statistical models driven by white random processes and is formulated into a full state estimational algorithm based on the error-state extended Kalman filtering framework (ESEKF) Major benefits of this method are its versatility, being applicable todifferent robotic systems without accurately modeling the robots’ specificynamics .…

Preliminary Development of a Wearable Device to Help Children with Unilateral Cerebral Palsy Increase Their Consciousness of Their Upper Extremity

The prototype consists of an accelerometer, avibration motor and a microcontroller with an algorithm that detects movement of the limb . After a given period of inactivity, the watch starts vibrating toalert the user . The watch vibrates to remind children with unilateral cerebral palsy touse their most affected limb, and which increase sensory afferents to possibly influence brain plasticity .…

DynamiTe Dynamic Termination and Non termination Proofs

There is growing interest in termination reasoning for non-linear programs . Recent dynamic strategies have shown they are able to inferinvariants for such challenging programs . In this paper, we exploit dynamic analysis and draw terminationand non-termination as well as static and dynamic strategies closer together .…

Predicting Short term Mobile Internet Traffic from Internet Activity using Recurrent Neural Networks

Mobile network traffic prediction is an important input in to network capacity planning and optimization . Existing approaches may lack the speed and complexity to account for bursting, non-linear patterns or other correlations in time series mobile network data . Long Short-Term Memory (LSTM)and Gated Recurrent Unit (GRU) were effective in modeling Internet activity and seasonality, both within days and across two months .…

Genetic Bi objective Optimization Approach to Habitability Score

Genetic Algorithm is a classic evolutionary algorithm used for solving optimization problems . It is based on Darwin’s theory of evolution, “Survival of the fittest” The Cobb-DouglasHabitability Function is formulated as a bi-objective as well as a single objective optimization problem to find the optimal values for a set of promising exoplanets to maximize their habitability score .…

HiFi GAN Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis

HiFi-GAN generates high-fidelity audio 167.9 times faster than real-time on a single V100 GPU . A subjective human evaluation (mean opinion score,MOS) of a single speaker dataset indicates that our proposed methoddemonstrates similarity to human quality . We further show the generality of the method to the mel-spectrogram inversion ofunseen speakers and end-to-end speech synthesis .…

Rooting Formal Methods within Higher Education Curricula for Computer Science and Software Engineering A White Paper

This white paper argues that formal methods need to be better rooted in higher education curricula for computer science and software engineering programmes of study . It advocates (i) improved teaching of formal methods; (ii) systematic highlighting of formal . methods within existing,`classical’ computer science courses; and (iii) the inclusion of a compulsory .…

Conditioning Trick for Training Stable GANs

In this paper we propose a conditioning trick, called difference departurefrom normality, applied on the generator network in response to instability issues during GAN training . We force the generator to get closer to thedeparture from normality function of real samples computed in the spectral domain of Schur decomposition .…

Using the Parameterized Quantum Circuit combined with Variational Quantum Eigensolver VQE to create an Intelligent social workers schedule problem solver

The social worker scheduling problem is a class of combinatorial optimization problems that combines scheduling with routing issues . We propose an adaptive and intelligence solution, which efficiently recalculates the schedules of social workers . The quantum feasibility of the algorithm will be modelled with docplex and tested on IBMQ computers .…

Towards International Relations Data Science Mining the CIA World Factbook

The rise of the “Fourth Paradigm – Data Intensive Scientific Discovery” and the strengthening of data science offer an alternative: “ComputationalInternational Relations” The use of traditional and contemporary data-centered tools can help to update the field of IR by making it morerelevant to reality (Koutsoupias, Mikelis, 2020) The “wedding” between DataScience and IR is no panacea though.…

How to Hijack Twitter Online Polarisation Strategies of Germany s Political Far Right

German far-right partyAlternative f\”ur Deutschland (AfD) use of a “hashjacking” strategy . Findings suggest right-wing politicians actively and effectively polarise the discourse not just using their own party hashtags, but also using the politicalparty hashtags of other established parties . The results underline the success of right wing parties, online and inelections, not entirely as a result of external effects (e.g.…

Designing a 9 channel location microphone from scratch

The design of a 9-channel microphone system for location recording of mainly atmosphere will be described . The key concept is matching the recording and recording andreproduction angles of the individual sectors . The rig is designed for theAURO-3D nine-channel playback system (4 height speakers) An analysis of thereproduction layout will be included, as well as recording concepts like theStereo Recording Angle (SRA) and Williams curves .…

Activation function impact on Sparse Neural Networks

Sparse Evolutionary Training allows for significantly lower complexity when compared to fully connected models by reducing redundant connections . This research provides insights into the relationship between the activation function used and the network performance at various sparsity levels . The research was published in the journal Ars Arseneggio, a journal that focuses on computer science and computer science research at the University of Cambridge, England, in the US, Canada and Australia .…