## Monotone cubic spline interpolation for functions with a strong gradient

Spline interpolation has been used in several applications due to its smoothness and accuracy of the interpolant . When there exists a discontinuity or a steep gradient in the data, artifacts can appear due to the Gibbs phenomenon . Preservation of data monotonicity is a requirement in some applications, and that property is not automatically verified by the interpolator .…

## Higher order phase averaging for highly oscillatory systems

We introduce a higher order phase averaging method for nonlinear oscillatorysystems . Phaseaveraging is useful for deriving reduced models that can be solved numerically . We illustrate the properties of this method on an ODE thatdescribes the dynamics of a swinging spring due to Lynch (2002) Although idealized, this model shows an interesting analogy to geophysical flows as it exhibits a slow dynamics that arises through the resonance between fastoscillations .…

## Models we Can Trust Toward a Systematic Discipline of Agent Based Model Interpretation and Validation

We advocate the development of a discipline of interacting with and extracting information from models, both mathematical (e.g. game-theoreticones) and computational models . We outline some directions for the development . of a such a discipline: – development of logical frameworks for the systematic formalspecification of stylized facts and social mechanisms in (mathematical andcomputational) social science .…

## Blending Dynamic Programming with Monte Carlo Simulation for Bounding the Running Time of Evolutionary Algorithms

Aims to provide absolute lower bounds for the best possible runningtimes that can be achieved by $(1+\lambda)$-type search heuristics on common benchmark problems . We apply our hybrid Monte Carlo dynamic programming approach to aconcatenated jump function and demonstrate how the obtained bounds can be used to gain a deeper understanding into parameter control schemes .…

## Optimal Prediction Intervals for Macroeconomic Time Series Using Chaos and NSGA II

In a first-of-its-kind study, this paper proposes the formulation ofconstructing prediction intervals (PIs) in a time series as a bi-objectiveoptimization problem and solves it with the help of Nondominated SortingGenetic Algorithm (NSGA-II) The proposed models when applied to the macroeconomic time series, yielded better results interms of both prediction interval coverage probability (PICP) and predictioninterval average width (PIAW) Compared to the state-of the art Lower UpperBound Estimation Method (LUBE) with Gradient Descent (GD) The 3-stage modelyielded better PICP compared to the 2-stage model but showed similarperformance in PIAW with added computation cost of running NSGA-I second time .…

## A Generalized Eulerian Lagrangian Discontinuous Galerkin Method for Transport Problems

We propose a generalized Eulerian-Lagrangian (GEL) discontinuous Galerkin(DG) method . The GEL DG method is motivated for solving linear hyperbolicsystems with variable coefficients . The velocity field for adjointproblems of the test functions is frozen to constant . Numerical results on 1D and 2D linear transport problems are presented to demonstrate great properties of the method .…

## Neuroscience Inspired Algorithms for the Predictive Maintenance of Manufacturing Systems

If machine failures can be detected preemptively, maintenance and repairs can be performed more efficiently, reducing production costs . Hierarchical Temporal Memory (HTM) outperforms state-of-the-art algorithms at preemptively detecting real-world cases of bearing failures and simulated 3D printer failures . Using the Numenta AnomalyBenchmark, our approach achieves anaverage score of 64.71 .…

## Large Scale Global Optimization Algorithms for IoT Networks A Comparative Study

This work studies the optimization of a wireless sensor network (WNS)at higher dimensions by focusing to the power allocation of decentralizeddetection . To the best of the authors knowledge, this is the first time that LGSO algorithms are applied to the optimal power allocation in IoT networks .…

## Explicit high order generalized α methods for isogeometric analysis of structural dynamics

We propose a new family of high-order explicit generalized-$\alpha$ methods for hyperbolic problems . The user can control the numerical dissipation in the discretespectrum’s high-frequency regions by adjusting the method’s coefficients . We exploit efficient preconditioners for the isogeometric matrix to minimize the computational cost .…

## Lower Bounds on the State Complexity of Population Protocols

Population protocols are a model of computation in which an arbitrary number of indistinguishable finite-state agents interact in pairs . The goal of the agents is to decide by stable consensus whether their initial globalconfiguration satisfies a given property, specified as a predicate on the set of all initial configurations .…

## Three Ways to Solve Partial Differential Equations with Neural Networks A Review

Neural networks are increasingly used to construct numerical solution methods for partial differential equations . The article is accompanied by a suite of expository software in the form of Jupyter notebooks in which each basic methodology is explained step by step .…

## State Augmented Constrained Reinforcement Learning Overcoming the Limitations of Learning with Rewards

Constrained reinforcement learning involves multiple rewards that must accumulate to given thresholds . In this class of problems, we show a simple example in which the desired optimal policy cannot be induced by any combination of rewards . This work addresses this shortcoming by augmenting the state with Lagrange multipliers and reinterpreting primal-dualmethods as the portion of the dynamics that drives the multipliers evolution .…

## Unidirectional Memory Self Attention Transducer for Online Speech Recognition

Self-attention models have been successfully applied in end-to-end speechrecognition systems . However, such attention-based models cannot be used in online speech recognition . Memory-Self-Attention (MSA) Transducer only needs localtime features as inputs . MSA efficiently models long temporal contexts by attending memory states .…

## Experimental Study on Probabilistic ToA and AoA Joint Localization in Real Indoor Environments

Joint localization algorithm significantly outperforms baselines using only ToA or AoA measurements . It achieves 2-D sub-meter accuracy at the90%-ile. We also numerically demonstrate that the algorithmis more robust to synchronization errors than the baseline using ToAmeasurements only. We evaluate the algorithm performance using aproprietary prototype deployed in an indoor factory environment.…

## A Robotic Model of Hippocampal Reverse Replay for Reinforcement Learning

Hippocampal reverse replay is thought to contribute to learning, andparticularly reinforcement learning, in animals . We present a computational model of learning in the hippocampus that builds on a previous model of the hippocampus . We conclude that reverse replay may enhance reinforcement learning inthe mammalian hippocampal-striatal system rather than provide its coremechanism.…

## Syntactic completeness of proper display calculi

A recent strand of research in structural proof theory aims at exploring thenotion of analytic calculi that support general and modularproof-strategies for cut elimination . In this context, the proof that the givencalculus is complete w.r.t. the original logic is usually carried outsyntactically, i.e.…

## On Sexual Selection

Sexual selection is a fundamental aspect of evolution for all eukaryotic organisms with mating types . This paper suggests intersexual selection is bestviewed as a mechanism to compensate for the unavoidable dynamics of coevolution between sexes that emerge with isogamy .…

## Comparative evaluation of CNN architectures for Image Caption Generation

Aided by recent advances in Deep Learning, Image Caption Generation has seentremendous progress over the last few years . Most methods use transfer learning to extract visual information, in the form of image features, with the help of pre-trained Convolutional Neural Network models followed by transformation of the visual information using a Caption Generator module to generate the outputsentences .…

## High order positivity preserving and asymptotic preserving multi derivative methods

In this work we present multi-derivative implicit-explicit (IMEX)Runge–Kutta schemes . We derive their order conditions up to third order, and show that such methods can preserve positivity (and more generally strongstability) with a time-step restriction independent of the stiff term, undermild assumptions on the operators .…

## Induction principles for type theories internally to presheaf categories

In order to combine the internal languages of multiplepresheaf categories, we use Dependent Right Adjoints and Multimodal TypeTheory . Categorical gluing is used to prove these induction principles, but it is not visible in their statements, which involve a notion of model withoutcontext extensions .…

## Improving Deep Learning Sound Events Classifiers using Gram Matrix Feature wise Correlations

In this paper, we propose a new Sound Event Classification (SEC) method which is inspired in recent works for out-of-distribution detection . In our method,we analyse all the activations of a generic CNN in order to produce featurerepresentations using Gram Matrices .…

Acoustic modeling for child speech is challenging due to the high acousticvariability caused by physiological differences in the vocal tract . We propose a feature adaptation approach by exploiting adversarial multi-tasktraining to minimize acoustic mismatch between adult and child speech .…

## Text to Audio Grounding Building Correspondence Between Captions and Sound Events

Automated Audio Captioning is a cross-modal task, generating natural languagedescriptions to summarize the audio clips’ sound events . This paper contributes an AudioGrounding dataset, which provides correspondence between sound events and captions provided inAudiocaps . A baseline approach is provided, resulting in an event-F1 score of 28.3% and a Polyphonic Sound Detection Score (PSDS) score of 14.7% .…

## End to End Dereverberation Beamforming and Speech Recognition with Improved Numerical Stability and Advanced Frontend

Recently, the end-to-end approach has been successfully applied tomulti-speaker speech separation and recognition in both single-channel and multichannel conditions . However, severe performance degradation is stillobserved in the reverberant and noisy scenarios, and there is still a large performance gap between anechoic and reverberant conditions .…

## Practical Mutation Testing at Scale

Mutation testing builds on top of mutation analysis and is a testingtechnique that uses mutants as test goals to create or improve a test suite . Google has a codebase of two billion lines of code and more than 500,000,000 tests are executed on adaily basis .…

## Investigating Deep Neural Structures and their Interpretability in the Domain of Voice Conversion

Voice Conversion (VC) is a subset of voicetranslation that involves translating the paralinguistic features of a sourcespeaker to a target speaker while preserving the linguistic information . The aim of non-parallel conditional GANs for VC is to translate an acoustic speechfeature sequence from one domain to another without the use of paired data .…

## Using Fault Injection on the Nanosatellite Subsystems Integration Testing

Fault injection technique has been used to test NanosatC-BR-2, a 2-U Cubesat based nanosatellite underdevelopment by INPE . It is very useful technique to test systems prototypes . The FEM is modelled to work at the communication bus emulating eventual faults of the communicatingsubsystems in the messages exchanged .…

## Chasm in Hegemony Explaining and Reproducing Disparities in Homophilous Networks

In networks with a minority and a majority community, it is well-studied thatminorities are under-represented at the top of the social hierarchy . But, lower in the ladder, as you ascend, the representation of the minority community improves . We refer to this opposing phenomenon between the upper-level and lower-level asthe \emph{chasm effect .…

## Toward Speeding up Mutation Analysis by Memoizing Expensive Methods

Mutation analysis has many applications, such as assessing the quality of test cases, fault localization, test input generation, security analysis, etc. Such applications involve running test suites against a large number of programmutants leading to poor scalability . This paper presents anovel approach, named MeMu, for reducing the execution time of the mutants, bymemoizing the most expensive methods in the system .…

## The SmartSHARK Repository Mining Data

The SmartSHARK repository mining data is a collection of rich and detailed information about the evolution of software projects . The data set provides a rich source of data that enables us to explore research questions that require data from different sources and/or longitudinal data over time .…

## Exact epidemic models from a tensor product formulation

A general framework for obtaining exact transition rate matrices forstochastic systems on networks is presented and applied to many well-known models of epidemiology . The state of the population is described as a vector in the tensor product space of $N$ individual probability vectorspaces, whose dimension equals the number of compartments of theepidemiological model $n_c$.…

## The State of Practice in Requirements Elicitation An Extended Interview Study at 12 Companies

Group interaction techniques, including meetings and workshops, are the most popular type of elicitation techniques employed by the practitioners, except in the case of small projects . Technical staff (for example, developers and architects) are more frequently involved in the elicitation process compared to the involvement of business- or strategic staff .…

## Grounded Relational Inference Domain Knowledge Driven Explainable Autonomous Driving

Explainability is essential for autonomous vehicles and other roboticssystems interacting with humans and other objects during operation . Humans need to understand and anticipate the actions taken by the machines for trustful and safe cooperation . Grounded Relational Inference (GRI) aims to enable the explainability of an autonomous driving system at the design stage by incorporating expert domainknowledge into the model .…

## Recurrent Model Predictive Control

Recurrent Model Predictive Control (RMPC) algorithm can converge to the optimal policy by minimizing the designed loss function . The number of prediction steps is equal to the number of recurrent cycles of the learned policy function . We further prove the convergence and optimality of the RMPC algorithm thoroughBellman optimality principle, and demonstrate its generality and efficiencyusing two numerical examples .…

## Online Stochastic Gradient Descent Learns Linear Dynamical Systems from A Single Trajectory

This work investigates the problem of estimating the weight matrices of astable time-invariant linear dynamical system from a single sequence of noisy measures . We show that SGD converges linearly in expectation to anyarbitrary small Frobenius norm distance from the ground truth weights .…

## DeepThermal Combustion Optimization for Thermal Power Generating Units Using Offline Reinforcement Learning

Thermal power generation plays a dominant role in the world’s electricity supply . It consumes large amounts of coal worldwide, and causes serious airpollution . At its core, is a new model-based reinforcement learning (RL) framework, called MORE, which leverages historical operational data of a TPGU to solve a highly complex Markov decision process problem via purely offline training .…

## An ontological analysis of misinformation in online social networks

Misinformation nowadays can refer to a continuous spectrumbetween what can be seen as “facts” or “truth”, if humans agree on theexistence of such, to false information that everyone agrees that it is false . The internet, Online Social Networks (OSNs) and smart phones enable users to create tremendous amount of information .…

## Revisiting the Memristor Concept within Basic Circuit Theory

In this paper we revisit the memristor concept within circuit theory . We show that for general memristive systems the $\varphi-q$ curve is not single-valued or not even closed . An approach suitable to explain the inductive behavior of the giant squid axon had already been developed in the 1960s, with the introduction of “time-variant resistors” We also point out the ambiguities resulting from anon rigorous usage of the flux linkage concept .…

## An Interaction aware Evaluation Method for Highly Automated Vehicles

It is important to build a rigorous verification and validation (V&V) processto evaluate the safety of highly automated vehicles before their widedeployment on public roads . In this paper, we propose an interaction-aware framework for HAV safety evaluation which is suitable for somehighly-interactive driving scenarios including highway merging, roundaboutentering, etc.…

## MultiWalk A Framework to Generate Node Embeddings Based on an Ensemble of Walk Methods

Graph embeddings are low dimensional representations of nodes, edges or wholegraphs . Such representations allow for data in a network format to be used with machine learning models for a variety of tasks (e.g., nodeclassification), where using a similarity matrix would be impractical .…

## The Curious Case of Integrator Reach Sets Part I Basic Theory

This is the first of a two part paper investigating the geometry of theintegrator reach sets . In this Part I, we establish that this compact convex set is semialgebraic, translated zonoid, andnot a spectrahedron . We also deduce the closedform formula for the volume and diameter of this set, and discuss their scaling with state dimension and time .…

## Smart Navigation for an In pipe Robot Through Multi phase Motion Control and Particle Filtering Method

In-pipe robots are promising solutions for condition assessment, leakdetection, water quality monitoring in a variety of other tasks in pipelinenetworks . Smart navigation is an extremely challenging task for these robots as a result of highly uncertain and disturbing environment for operation .…

## Automating Test Case Identification in Open Source Projects on GitHub

Software testing is one of the very important Quality Assurance (QA) components . The analysis was performed on 38 GitHub open sourcerepositories thoroughly selected from the set of 4.3M GitHub projects . The results show that: (i) there exists weak correlation (r= 0.655) between the word test and test cases presence in a class; (ii) the proposed algorithm using static file analysis correctly detected 95\% of test cases; (iii) 15% of the analyzed classes used main() function whose represent regular Java programs that test the production code without using any third-party framework.…

## Esports Agents with a Theory of Mind Towards Better Engagement Education and Engineering

The role of AI in esports is shifting from leveraging games as a testbed for improving AI algorithms to addressing the needs of the esports players . For AI agents to be able to effectively address such needs in esports, AI agents require atheory of mind, that is, the ability to infer players’ tactics and intents .…

## Practical application of the multi model approach in the study of complex systems

Different kinds of models are used to study various natural and technicalphenomena . The paper describes several model approaches which we used in the study of the random early detection algorithm for active queue management . Both the model approaches themselves and their implementation and the results obtained are described .…

## Targeted False Data Injection Attack against DC State Estimation without Line Parameters

A novel false data injection attack (FDIA) model against DC state estimation is proposed . It requires no network parameters and exploits only limitedphasor measurement unit (PMU) data . The proposed FDIA model can target specificstates and launch large deviation attacks using estimated line parameters .…

## Dual Path Modeling for Long Recording Speech Separation in Meetings

The continuous speech separation (CSS) is a task to separate the speech sources from a long, partially overlapped recording, which involves a varying number of speakers . A straightforward extension of conventional utterance-level speech separation to the CSS task is to segment the long recording with asize-fixed window and process each window separately .…

## A discontinuous Galerkin method based on a hierarchical orthogonal basis for Lagrangian hydrodynamics on curvilinear grids

We present a new high-order accurate Lagrangian discontinuous Galerkin (DG)hydrodynamic method to simulate material dynamics (for e.g., gasses, fluids,and solids) with up to fourth-order accuracy on cubic meshes . The variables, such as specific volume, velocity, specific total energy, and deformation gradient fields within a cell, are represented with a polynomial constructed with a novel hierarchical orthogonal basis about the center of mass .…

## Explore the Context Optimal Data Collection for Context Conditional Dynamics Models

In this paper, we learn dynamics models for parametrized families of systems with varying properties . The dynamics models are formulated as stochastic processes conditioned on a latent context variable . The probabilisticformulation allows us to compute an action sequence which, for a limited number of environment interactions, optimally explores the given system within the given family .…

## The landscape of software for tensor computations

Tensors (also commonly seen as multi-linear operators) are ubiquitous in scientific computing and in data science . We have observed an explosion in libraries, compilers, packages, and toolboxes for tensor operations . These efforts are scattered among the different domains, and inevitably suffer from replication, suboptimalimplementations, and in many cases, limited visibility .…