## ProbRobScene A Probabilistic Specification Language for 3D Robotic Manipulation Environments

ProbRobScene is aprobabilistic specification language for describing robotic manipulation environments . The language combines aspects of probabilistic programming languages and convex geometry . It can be used to debug a roboticcontroller in a tabletop robot manipulation environment . We provide a way to sample the space of possible environments efficiently .…

## Survival prediction and risk estimation of Glioma patients using mRNA expressions

Gliomas are lethal type of central nervous system tumors with a poor prognosis . Recently, with the advancements in the micro-array technologiesthousands of gene expression related data of glioma patients are acquired . Genomics are been emerged into the field of prognosis analysis .…

## Three discontinuous Galerkin methods for one and two dimensional nonlinear Dirac equations with a scalar self interaction

This paper develops three high-order accurate discontinuous Galerkin (DG) methods . The RKDG method uses the spatial DGapproximation to discretize the NLD equations . The LWDG and TSDG methods give the one-stage fourth-order Lax-Wendroff type time discretizaiton (LWDG) and the two-stage 4th-order timediscretizations .…

## Block Full Rank Linearizations of Rational Matrices

Block full rank pencils introduced in [Dopico et al., Local linearizations ofrational matrices] allow us to obtain localinformation about zeros that are not poles of rational matrices . This new family of linearizations is important as it generalizes and includes the structures appearing in most of the .…

## Deep Feature Augmentation for Occluded Image Classification

The proposed approach achieves 11.21% and 9.14%average increases in classification accuracy for the ResNet50 networks fine-tuned on the occlusion-exclusive and occlusions-inclusive training sets . The experiments on various datasets and networkstructures show that the deep feature augmentation significantly improves theclassification accuracy of occluded images without a noticeable influence on the performance of clean images .…

## Stability and Transparency in Series Elastic Actuation A Two Port Analysis

Series Elastic Actuation (SEA) enables high fidelity and robust force control, improving the safety of physical human-robot interaction (pHRI) Safety is an imperative design criterion that limits interaction performance . In the literature,coupled stability of one-port models of SEA has been studied for various controllers while rendering certain basic environments, and the necessary andsufficient conditions for such passive terminations have been derived .…

## Real to Sim Registration of Deformable Soft Tissue with Position Based Dynamics for Surgical Robot Autonomy

Autonomy in robotic surgery is very challenging in unstructured environments, especially when interacting with deformable soft tissues . This creates a challenge for model-based control methods that must account for deformationdynamics during tissue manipulation . The PBD method is employed to simulate soft tissuedynamics as well as rigid tool interactions .…

## Fast Biconnectivity Restoration in Multi Robot Systems for Robust Communication Maintenance

The Fast Biconnectivity Restoration (FBR) problem aims to repair a connected network to make it biconnected as fast as possible . We develop a Quadratically Constrained Program (QCP)formulation of the FBR problem, which provides a way to optimally solve the problem .…

## Learning Sequences of Manipulation Primitives for Robotic Assembly

Manipulation Primitives have enough complexity to keep the search tree shallow . They are generic enough to generalize across a wide range of assembly tasks . Direct sim2real transfer (without retraining in real) achieves excellent success rates on challenging assembly tasks, such as round peginsertion with 100 micron clearance or square peg insertion with large holeposition/orientation estimation errors .…

## Time Series Forecasting with Stacked Long Short Term Memory Networks

Long Short-Term Memory (LSTM) networks are often used to capture temporaldependency patterns . By stacking multi-layer LSTM networks, it can capture evenmore complex patterns . Being able to predict traffic volume more accurately can result in better planning, thus greatly reduce the operationcost and improve overall efficiency .…

## PAC Confidence Predictions for Deep Neural Network Classifiers

A key challenge for deploying deep neural networks in safety critical settings is the need to provide rigorous ways to quantify their uncertainty . In this paper, we propose a novel algorithm for constructing predictedclassification confidences for DNNs that comes with provable correctnessguarantees .…

## The effect of quadrature rules on finite element solutions of Maxwell variational problems Consistency estimates on meshes with straight and curved elements

We study the effects of numerical quadrature rules on error convergence rates on Maxwell-type variational problems . We detail sufficient conditions with respect to mesh refinement and precision for the quadratures rules so as to guarantee convergence rates . On curved domains, we isolatethe error contribution to numerical quirality rules.…

## LDG approximation of large deformations of prestrained plates

A reduced model for large deformations of prestrained plates consists of minimizing a second order bending energy subject to a nonconvex metricconstraint . We discuss aformal derivation of this reduced model along with an equivalent formulation that makes it amenable computationally .…

## CABiNet Efficient Context Aggregation Network for Low Latency Semantic Segmentation

CABiNet (Context Aggregated Bi-lateral Network) is a dual branchconvolutional neural network (CNN) with significantly lower computationalcosts as compared to the state-of-the-art . We achieve 76.6% and 75.9% mIOU on Cityscapes validation and test sets respectively, at 76 FPSon an NVIDIA RTX 2080Ti and 8 FPS on a Jetson Xavier NX .…

## FeatherTTS Robust and Efficient attention based Neural TTS

Attention based neural TTS is elegant speech synthesis pipeline and has shown a powerful ability to generate natural speech . However, it is still not robust enough to meet the stability requirements for industrial products . The proposed FeatherTTScan would be $35$x faster than real-time on a single CPU .…

## Sound Event Detection and Separation a Benchmark on Desed Synthetic Soundscapes

We propose a benchmark of state-of-the-art sound event detection systems . We analyze the performance of the submissions to DCASE2021 task 4 depending on time related modifications . We show that the localization in time of sound events is still a problem for SED systems.…

## Learning generic feature representation with synthetic data for weakly supervised sound event detection by inter frame distance loss

Synthetic data to improve sound event detection system performance has been a new research focus . We find the best performance can be achieved when the two methods being used together . The experiment on DCASE 2018 task 4test set and DCASE 2019 task 4 synthetic set both show competitive results.…

## Site to Site Internet Traffic Control

Queues allow network operators to control traffic: where queues build, they can enforce scheduling and shaping policies . Bundler uses a novel inner control loop between asendbox (in the sender’s site) and a receivebox . Enforcing this sending rate ensures that bottleneck queues that would have built up from the bundle’s packets now shift from the bottleneck to the sendbox .…

## Self Concordant Analysis of Generalized Linear Bandits with Forgetting

Generalized Linear Bandits (GLB) offer a solid theoretical framework to address them . We propose a novel confidence-based algorithm for the maximum-likehoodestimator with forgetting and analyze its perfomance in abruptly changing environments . We focus on self-concordant GLB (which include logistic and Poisson regression) withforgetting achieved either by the use of a sliding window or exponentialweights .…

## Distributed Machine Learning for Computational Engineering using MPI

We propose a framework for training neural networks that are coupled withpartial differential equations (PDEs) in a parallel computing environment . Our parallel computing model views datacommunication as a node in the computational graph for numerical simulation . The advantage of our model is that data communication and computing are cleanlyseparated and thus provide better flexibility, modularity, and testability .…

## Identification of Matrix Joint Block Diagonalization

The joint block diagonalization problem (BJBDP) plays an important role in independent subspace analysis (ISA) Numerical simulations validate our theoretical results . We propose a “bi-block diagonalization” method to solve BJBDP, and establish sufficient conditions under which the method is able to accomplish the task .…

## DRF A Framework for High Accuracy Autonomous Driving Vehicle Modeling

An accurate vehicle dynamic model is the key to bridge the gap betweensimulation and real road test in autonomous driving . In this paper, we present a Dynamic model-Residual correction model Framework (DRF) for vehicle dynamicmodeling . Compared to classic rule-based and learning-based vehicle dynamic models, DRFaccomplishes as high as 74.12% to 85.02% of absolute trajectory error drop among all DRF variations .…

## Sparse Multilevel Roadmaps on Fiber Bundles for High Dimensional Motion Planning

Sparse roadmaps are important to compactly represent state spaces . However, they do not scale well to high-dimensional planning problems . In this work, we generalize sparse roadmaps to multilevel abstractions by developing a novel algorithm . We argue SMLR to beprobabilistically complete and asymptotically near-optimal by inheritance fromsparse roadmap planners .…

## Opinion Dynamics of Online Social Network Users A Micro Level Analysis

In this paper, we present an empirical study of the opinion dynamics of online social network users . Opinions of users areestimated based on their subscriptions to information sources and we analyzehow friendship connections affect the dynamics of these estimations .…

## Semi supervised Autoencoding Projective Dependency Parsing

We describe two end-to-end autoencoding models for semi-supervisedgraph-based dependency parsing . Both models consist of two parts: an encoder enhanced by deep neuralnetworks (DNN) that can utilize the contextual information to encode the input into latent variables, with exactinference . Both LAP and GAP admit a unified structure of loss functions for labeled and unlabeled data with shared parameters .…

## What s All the FUSS About Free Universal Sound Separation Data

The Free Universal Sound Separation (FUSS) dataset is a new corpus for experiments in separating mixtures of an unknown number of sounds . The dataset consists of 23 hours of single-sourceaudio data drawn from 357 classes . To simulate reverberation, an acoustic room simulator is used to generate impulse responses of box shaped rooms with frequency-dependentreflective walls .…

## Unified greedy approximability beyond submodular maximization

We propose a new class of objective functions of cardinality constrainedmaximization problems for which the greedy algorithm guarantees a constantapproximation . We show a tight bound of $\frac{\alpha$-$\alpha$-augmentablefunctions . For weighted rankfunctions of independence systems, our tight bound becomes $1/q$ forindependence systems of rank quotient at least $q$.…

## Reframing the Test Pyramid for Digitally Transformed Organizations

The test pyramid is a conceptual model that describes how quality checks can be organized to ensure coverage of all components of a system, at all scales . The value of acceptance tests and integration tests increasingly depends on the integrity of the underlying data, models, and pipelines .…

## Pushing the Envelope of Rotation Averaging for Visual SLAM

Motion averaging is an essential part of structure from motion (SfM) and SimultaneousLocalization and Mapping (SLAM) systems . We show that our approach can exhibit up to 10x faster speed with comparable accuracy against the state of the art on public benchmarks .…

## At most 4 47 n stable matchings

We improve the upper bound for the maximum possible number of stablematchings among $n$ men and \$n# women . We develop a novel formulation of a probabilistictechnique that is easy to apply and may be of independent interest in counting other combinatorial objects .…

## CVC Contrastive Learning for Non parallel Voice Conversion

CVC only requires one-way GAN training when it comes tonon-parallel one-to-one voice conversion, while improving speech quality and reducing training time . CVC further demonstrates performance improvements in many-out-speaker conversion, enabling the conversion from unseen speakers . We propose CVC, acontrastive learning-based adversarial model for voice conversion .…

## Characterizing and Utilizing the Interplay Between Core and Truss Decompositions

Finding dense regions in a graph is an important problem in network analysis . Core decomposition and truss decomposition address this problem from different perspectives . Core-TRUSSDD is an algorithm to identify discrepancies between core andtruss decompositions . Ouralgorithm provides an efficient solution to retrieve the outliers in thenetworks, which correspond to the two anomalous behaviors .…

## Into the Wild with AudioScope Unsupervised Audio Visual Separation of On Screen Sounds

AudioScope is a novel audio-visual sound separation framework that can be betrained without supervision to isolate on-screen sound sources from realin-the-wild videos . The training procedure for AudioScope usesmixture invariant training (MixIT) to separate synthetic mixtures of mixtures into individual sources .…

## Membrane Fusion Based Transmitter Design for Molecular Communication Systems

This paper proposes a novel imperfect spherical transmitter (TX) model that adopts MF between a vesicle and the TX membrane to release molecules encapsulated within the vesicles . Incorporating molecular degradationand a fully-absorbing receiver (RX), the end-to-end molecule hittingprobability at the RX is also derived .…

## Search based Kinodynamic Motion Planning for Omnidirectional Quadruped Robots

Autonomous navigation has played an increasingly significant role inquadruped robots system . But existing works on path planning used traditional search-based or sample-based methods which did not consider thekinodynamic characteristics of quadruped robots . The superior performance of our work is demonstrated through simulated comparisons and by using our quadruped robotJueying Mini in our experiments .…

## Differential Dynamic Programming with Nonlinear Safety Constraints Under System Uncertainties

Safe operation of systems such as robots requires them to plan and executetrajectories subject to safety constraints . When those systems are subject touncertainties in their dynamics, ensuring that the constraints are not violated is challenging . In this paper, we propose a safe trajectory optimization andcontrol approach (Safe-CDDP) for systems under additive uncertainties and non-linear safety constraints based on constrained differential dynamic dynamicprogramming .…

## Focusing Phenomena in Linear Discrete Inverse Problems in Acoustics

The development is given in the context of sound-field reproduction where the source strengths are the inverse solution needed to recreate aprescribed pressure field at discrete locations . The behaviour of the system isfundamentally tied to the amount of acoustic crosstalk at each control point as a result of the focusing operation inherent to the pseudoinverse .…

## Employing Partial Least Squares Regression with Discriminant Analysis for Bug Prediction

Having an estimation of those parts of a software system that mostlikely contain bugs may help focus testing efforts, reduce costs, and improveproduct quality . PLS-DA based prediction model achievessuperior performances compared to the state-of-the-art approaches compared to other approaches .…

## Budget Sharing for Multi Analyst Differential Privacy

Differentially private mechanisms are designed to answer a single set of queries and optimize the total accuracy across the entire set . Multiple stakeholders that need to be satisfied by the datarelease often have competing goals and priorities . We present novel DPalgorithms that provably satisfy all our desiderata and empirically demonstratethat they incur low error on realistic tasks .…

## Multi Robot Coverage and Exploration using Spatial Graph Neural Networks

The multi-robot coverage problem is an essential building block for systemsthat perform tasks like inspection or search and rescue . We discretize the coverage problem to induce a spatial graph of locations and represent robots as nodes in the graph .…

## Multi Armed Bandits with Censored Consumption of Resources

We consider a resource-aware variant of the classical multi-armed banditproblem: In each round, the learner selects an arm and determines a resourcelimit . In a simulation study, we show thatour learning algorithm outperforms straightforward extensions of standard multi-arm bandit algorithms .…

## A Formally Verified Fail Operational Safety Concept for Automated Driving

Modern Automated Driving (AD) systems rely on safety measures to handle faults and to bring vehicle to a safe state . We present a holistic safety concept unifying advanced safety measures for handling multiple-point faults . We developed an executable model of the safety concept in the formal specification language mCRL2 .…

## Blockchain for Decentralization of Internet Prospects Trends and Challenges

This paper focuses on using using using Blockchain to provide a robust and secure decentralizedcomputing system . The paper conducts a literature review on Bitcoin-based methods capable for the decentralization of the future Internet . We have identified three consensus algorithmsbeing PoP, Paxos, and PoAH to be more adequate for reaching consensus inBlockchain-enabled Internet architecture .…

## Exponential Polynomial Time Integrators

In this paper we extend the polynomial time integration framework to includeexponential integration for both partitioned and unpartitioned initial value problems . We then demonstrate its utility by constructing a new class ofparallel exponential block methods based on the Legendre points .…

## Ant Colony Inspired Machine Learning Algorithm for Identifying and Emulating Virtual Sensors

The scale of systems employed in industrial environments demands a largenumber of sensors to facilitate meticulous monitoring and functioning . The datacoming from various sensors is often correlated due to the underlyingrelations in the system parameters that the sensors monitor .…

## Grasping in the Dark Compliant Grasping using Shadow Dexterous Hand and BioTac Tactile Sensor

The task of imitating human hand in robotic end-effectors, especially in scenarios where visual input is limited or absent, is an extremely challenging one . In this paper we present an adaptive, compliantgrasping strategy using only tactile feedback . The proposed algorithm can grasp objects of varying shapes, sizes and weights without having a priori knowledge of the objects .…

## VIO UWB Based Collaborative Localization and Dense Scene Reconstruction within Heterogeneous Multi Robot Systems

This paper introduces a novel approach to collaborativelocalization for dense scene reconstruction in heterogeneous multi-robotsystems . We solve theproblem of full relative pose estimation without sliding time windows by relying on UWB-based ranging and Visual Inertial Odometry (VIO)-based egomotionestimation for localization .…

## Mobile Human Ad Hoc Networks A Communication Engineering Viewpoint on Interhuman Airborne Pathogen Transmission

Pathogens such as viruses and bacteria play a vital role in human life, sincethey cause infectious diseases which can lead to epidemics . Recent coronavirusdisease 2019 epidemic has shown that taking effective prevention measures suchas wearing masks are important to reduce the human deaths and side effects of the epidemic .…

## Controlled Perturbation Induced Switching in Pulse Coupled Oscillator Networks

Pulse-coupled systems such as spiking neural networks exhibit nontrivialinvariant sets in the form of attracting yet unstable saddle periodic orbits . Heteroclinic connections between suchorbits may in principle support switching processes in those networks andenable novel kinds of neural computations .…

## Equality Constrained Linear Optimal Control With Factor Graphs

This paper presents a novel factor graph-based approach to solve the Linear Quadratic Regulator problem subject to auxiliary linear equality constraints within and across time steps . We prove that our approach has the same order ofcomputational complexity as the state-of-the-art dynamic programming approach .…