Enhanced U Net A Feature Enhancement Network for Polyp Segmentation

Colonoscopy is a procedure to detect colorectal polyps which are the primary cause for developing colorctal cancer . Polyp segmentation is a challenging task due to the diverse shape, size, color, and texture of polyps . Instead of directly adding encoder features to the respective decoder layer, we introduce anAdaptive Global Context Module (AGCM) which focuses only on the encoder’ssignificant and hard fine-grained features .…

Embedded training of neural network sub grid scale turbulence models

The weights of a deep neural network model are optimized in conjunction with the governing flow equations to provide a model for sub-grid-scale stresses in a turbulent jet at Reynolds number $Re_0=6\,000$. In-sample and out-of-sample testing on multipledual-jet configurations show that its required mesh density in each coordinatedirection for prediction of mean flow, Reynolds stresses, and spectra is half that needed by the dynamic Smagorinsky model for comparable accuracy .…

Generative Adversarial Reward Learning for Generalized Behavior Tendency Inference

Recent advances in reinforcement learning have inspired increasing interest in learning user modeling adaptively through dynamic interactions . We propose a generative inversereinforcement learning for user behavioral preference modelling . Instead of using predefined reward functions, our model canautomatically learn the rewards from user’s actions based on discriminativeactor-critic network and Wasserstein GAN .…

Robust Control for Lane Keeping System Using Linear Parameter Varying Approach with Scheduling Variables Reduction

This paper presents a robust controller using a Linear Parameter Varying(LPV) model of the lane-keeping system with parameter reduction . Multiple varying parameters lead to a high number of scheduling variables and cause massive computational complexity . We designed the LPV robust feedback controller using the reducedmodel solving a set of Linear Matrix Inequality (LMI) The effectiveness of the proposed system is validated with full vehicle dynamics from CarSim on aninterchange road .…

On the Stability of Multilinear Systems

In this letter, we investigate the stability properties of a discrete-timemultilinear system . We establish theoretical results on the criteria fordetermining the internal stability of multilinare systems via tensor spectraltheory . In particular, we show that the Z-eigenvalues of the dynamic tensorplay a significant role in the stability analysis .…

An Efficient and Secure Location based Alert Protocol using Searchable Encryption and Huffman Codes

Location data are widely used in mobile apps, ranging from location-basedrecommendations, to social media and navigation . But serious privacy concerns arise if users share their locationhistory with the service provider in plaintext . The underlying searchable encryption primitives required to perform the matching on ciphertexts are expensive, and without a proper encoding oflocations and search predicates, the performance can degrade a lot .…

DeepMPCVS Deep Model Predictive Control for Visual Servoing

The simplicity of the visual servoing approach makes it an attractive option for tasks dealing with vision-based control of robots in many real-world applications . Attaining precise alignment for unseen environments pose a challenge to existing visual servoational approaches . The recent data-driven approaches face issues when generalizing to novel environments .…

Initialization and Regularization of Factorized Neural Layers

Factorized layers–operations parameterized by products of two or morematrices–occur in a variety of deep learning contexts . We study how to initialize and regularize deepnets containing such layers . We highlight the benefits of spectralinitialization and Frobenius decay . In modelcompression, we show that they enable low-rank methods to significantlyoutperform both unstructured sparsity and tensor methods on the task of training low-memory residual networks .…

Metadata Interpretation Driven Development

Despite decades of engineering and scientific research efforts, separation of concerns in software development remains not fully achieved . We show that business-domain codeinscriptions play an even larger role in this challenge than the crosscutting of concerns phenomenon . We introduce a new methodology, called MetadataInterpretation Driven Development (MIDD) that suggests a possible path to .…

Present and Future of Reconfigurable Intelligent Surface Empowered Communications

Signal processing and communication communities have witnessed the rise of exciting communication technologies in recent years . We discuss the recent developments in the field and put forward promising candidates for future research and development . We also envision an ultimate RIS architecture, which is able to adjust its operation modes dynamically, and introduce the new concept of PHY slicing over RISs towards 6G wireless networks.…

Thinking Outside the Lab VR Size Depth Perception in the Wild

Size and distance perception in Virtual Reality have been widelystudied in a controlled laboratory setting with a small number of participants . We describe a fully remote perceptual study with a gamified protocol to encourage participant engagement . Varying eye-height from the floor plane showed no significant effect on the judgements .…

Optimal Maximal Leakage Distortion Tradeoff

Most methods for publishing data with privacy guarantees introduce randomness, which reduces the utility of the published data . In this paper, we study the privacy-utility tradeoff by taking maximal leakage as the privacy measure and the expected Hamming distortion as the utility measure .…

A guide to design disturbance observer based motion control systems

This paper proposes new practical design tools for the robust motion controlsystems based on disturbance observer (DOB) Although DOB has long been used in several motion control applications, it has insufficient analysis and designtools . The paper proposes a new practical robustness constraint, which improve the robustness at high frequencies, on the bandwidth of a DOB and nominalinertia .…

Bounds of MIN_NCC and MAX_NCC and filtering scheme for graph domain variables

Beldiceanu et al.presented a generic filtering scheme for global constraints based on graph properties . This scheme strongly relies on the computation of graph properties’bounds and can be used in the context of graph domain variables and constraints . Bounds of MIN_NCC had been defined for the graph-based representation of global constraint for the path_with_loops graphclass .…

Accessibility Across Borders

Cultural differences influence user preferences and interaction methods . We believe that it is equally important to apply this inquiry to digital accessibility and how accessibility fits within the design process around the world . We hope that this inquiry will also be applied to how digital accessibility fits into design process .…

Autonomous parafoil precision landing using convex real time optimized guidance and control

An efficient real-time convex optimized guidance and control strategy is presented . Successive convexification of the parafoil guidanceproblem guarantees local optimality . Exhaustive Monte-Carlo simulations show performanceimprovements of about one order of magnitude . The concept proposed is simple,yet general, as it scales to any atmospheric parfoil landing system and allow efficient implementation relying only on the turn rate information .…

Explaining how your AI system is fair

To implement fair machine learning in a sustainable way, choosing the rightfairness objective is key . The most appropriate fairness definition for an artificial intelligence system is a matter of ethical standards and legal requirements . In thisposition paper, we propose to use a decision tree as means to explain andjustify the implemented kind of fairness to the end users .…

Reachability of Black Box Nonlinear Systems after Koopman Operator Linearization

Reachability analysis of nonlinear dynamical systems is a challenging andcomputationally expensive task . Computing the reachable states for linear systems, in contrast, can often be done efficiently in high dimensions . The Koopman operator links the behaviors of a nonlinear system to a linear system embedded in a higher dimensional space, with an additional set of so-calledobservable variables .…

Discovering Diverse Athletic Jumping Strategies

We present a framework that enables the discovery of diverse andnatural-looking motion strategies for athletic skills such as the high jump . The strategies are realized as control policies for physics-based characters . We propose a Pose Variational Autoencoder(P-VAE) to constrain the actions to a subspace of natural poses .…

Artificial compressibility methods for the incompressible Navier Stokes equations using lowest order face based schemes on polytopal meshes

We investigate artificial compressibility (AC) techniques for the timediscretization of the incompressible Navier-Stokes equations . AC timestepping uncouples at each time step thevelocity update from the pressure update . We consider both first-order and second-order time schemes and either an implicit or an explicit treatment of the nonlinear convection term .…

Channels of Small Log Ratio Leakage and Characterization of Two Party Differentially Private Computation

We consider measuring the protocol leakage by the log-ratio distance (which was popularized by its use in the differential privacy framework) We show that a protocol with (noticeable) accuracy can betransformed into an OT protocol . Our results hold for both theinformation theoretic and the computational settings, and can be viewed as a”fine grained” approach to “weak OT amplification” We then use the above result to fully characterize the complexity ofdifferentially private two-party computation for the XOR function .…

Pattern Complexity of Aperiodic Substitutive Subshifts

This paper aims to better understand the link between aperiodicity in subshifts and pattern complexity . We prove aquadratic lower bound on their pattern complexity for a class of substitutive sub-shifts . We also prove that the recent bound ofKari and Moutot, showing that any aperiodic subshift has pattern complexity atleast $mn+1$, is optimal for fixed $m$ and $n$.…

What s Decidable about Atomic Polymorphism

In this paper, we investigate System Fat, or atomic System F, a weak predicative fragment of System F whose typable terms coincide with the simply typable ones . We show that the type-checking problem for Fat is decidable and we propose an algorithm which sheds some new light on the source of undecidability in full System F .…

A Machine Learning Based Ensemble Method for Automatic Multiclass Classification of Decisions

Stakeholders make various types of decisions with respect to requirements, design, management, and so on during the software development life cycle . These decisions are typically not well documented and classified due to limited human resources, time, and budget . In this paper, we aimed at automaticallyclassifying decisions into five types to help stakeholders better document and understand decisions .…

High order space time finite element methods for the Poisson Nernst Planck equations Positivity and unconditional energy stability

We present a novel class of high-order space-time finite element schemes for the Poisson-Nernst-Planck (PNP) equations . We prove that our schemes are massconservative, positivity preserving, and unconditionally energy stable for any order of approximation . This is the first class of (arbitrarily) high order accurate schemes for PNP equations that simultaneously achieve all these three properties .…

Generalized Spatially Coupled Parallel Concatenated Convolutional Codes With Partial Repetition

We introduce generalized spatially coupled parallel concatenated codes (GSC-PCCs) as a class of turbo-like turbo-style codes . We show that the proposed codes have some niceproperties such as threshold saturation and that their decoding thresholdsimprove with the repetition factor $q$. We also suggest that the codes asymptotically approach the capacity as $q$ tends toinfinity with any given constituent convolutional code .…

Formalizing the Four layer Metamodeling Stack Potential and Benefits

Enterprise modeling deals with the increasing complexity of processes and systems by operationalizing model content and by linking complementary modelsand languages . To enable this amplification and turn models intocomputer-processable structures a comprehensive formalization is needed . Thispaper presents a generic formalism based on typed first-order logic and provides a perspective on the potential and benefits arising for a variety of research issues in conceptual modeling .…

3 D Deployment of UAV Swarm for Massive MIMO Communications

We consider the uplink transmission between a multi-antenna ground station and an unmanned aerial vehicle (UAV) swarm . The UAVs are assumed as intelligent agents, which can explore their optimal three dimensional (3-D) deployment tomaximize the channel capacity of the multiple input multiple output (MIMO)system .…