A Calculus for Flow Limited Authorization

Real-world applications routinely make authorization decisions based on dynamic computation . Integrity of the system might be compromised if attackers can improperly influence the authorizing computation . Confidentiality can also becompromised by authorization, since authorization decisions are often based on sensitive data such as membership lists and passwords .…

Towards Exploratory Landscape Analysis for Large scale Optimization A Dimensionality Reduction Framework

Little is known about the scalability of the ELA approach for large-scale optimization . Two important feature classes (ela_level and ela_meta) cannot be applied to optimization due to their high computational cost . Adimensionality reduction framework proposes a framework that computes features in a reducedlower-dimensional space than the original solution space .…

Model aided Deep Reinforcement Learning for Sample efficient UAV Trajectory Design in IoT Networks

Deep Reinforcement Learning (DRL) has become a prominent paradigm to designtrajectories for autonomous unmanned aerial vehicles . We propose a model-aided deep Q-learning approach that, in contrastto previous work, requires a minimum of expensive training data samples and isable to guide a flight-time restricted UAV on a data harvesting mission without prior knowledge of wireless channel characteristics and limited knowledge of node locations .…

Predictive analytics using Social Big Data and machine learning

The ever-increase in the quality and quantity of data generated fromday-to-day businesses operations in conjunction with the continuously importedrelated social data have made the traditional statistical approaches inadequateto tackle such data floods . This chapter sheds the light on coreaspects that lay the foundations for social big data analytics .…

On the Width of Regular Classes of Finite Structures

In this work, we introduce the notion of decisional width of a finiterelational structure . We also introduce the idea of decisionality of a regular class offinite structures . Our main result states that given a first-order formula, and a finite automaton F over a suitablealphabet B, one can decide in time f (f) whether some {\tau}-structure in C satisfies {\psi}.…

Deep Music Retrieval for Fine Grained Videos by Exploiting Cross Modal Encoded Voice Overs

Growing popularity of short videos has intensified the need for a background music retrieval system . Existing video-music retrieval methods onlybased on the visual modality cannot show promising performance regarding videos with fine-grained virtual contents . In our framework, we use theself-attention (SA) and the cross-modal attention (CMA) modules to explore theintra- and the inter-relationships of different modalities respectively .…

HDR Fuzz Detecting Buffer Overruns using AddressSanitizer Instrumentation and Fuzzing

Buffer-overruns are a prevalent vulnerability in software libraries and applications . Fuzz testing is one of the effective techniques to detect vulnerabilities in general . We propose a new ground-up approach for detecting buffer-overrun vulnerabilities . This approach uses an extended version of ASAN(Address Sanitizer) that runs in parallel with the fuzzer, and reports back to test inputs that happen to come closer to exposing vulnerabilities .…

Efficient Sparse Coding using Hierarchical Riemannian Pursuit

Sparse coding is a class of unsupervised methods for learning a sparserepresentation of the input data in the form of a linear combination of adictionary and a sparse code . Initial non-convexapproaches learn the dictionary in the sparse coding problem sequentially in anatom-by-atom manner, which leads to a long execution time .…

Modular Verification of Collaborating Smart Contracts

Smart contracts are programs that execute inside blockchains such as Ethereum to manipulate digital assets . Since bugs in smart contracts may lead to substantial financial losses, there is considerable interest in formallyproving their correctness . Current reasoning techniques do notfully address these challenges, being restricted in their scope orexpressiveness (in particular, in the presence of re-entrant calls) In this paper, we present a novel specification methodology tailored to the domain of smart contracts .…

Unification of computer reality

The work attempts to unify the conceptual model of the user’s virtualcomputer environment . The aim of combining the local environments of operating systems and the global Internet environment into a single virtualenvironment built on general principles . The use of the spatialconceptual basis “object – place” with the concepts of “domain”, “site”, and”data object” allows to completely virtualize the user environment, separatingit from the hardware concepts .…

Lossless Compression with Latent Variable Models

We develop a simple and elegant method for lossless compression using latentvariable models . The method involves interleaving encode and decode steps, andachieves an optimal rate when compressing batches of data . We demonstrate it firstly on the MNIST test set, showing that state-of-the-art losslesscompression is possible using a small variational autoencoder (VAE) model .…

Wireless Sensing With Deep Spectrogram Network and Primitive Based Autoregressive Hybrid Channel Model

Human motion recognition (HMR) based on wireless sensing is a low-costtechnique for scene understanding . Current HMR systems adopt support vectormachines (SVMs) and convolutional neural networks (CNNs) to classify radarsignals . On the other hand, training a machinelearning model requires a large dataset, but data gathering from experiment iscost-expensive and time-consuming .…

A Polyhedral Approach to Some Max min Problems

We consider a max-min variation of the classical problem of maximizing alinear function over the base of a polymatroid . In our problem we assume that the vector of coefficients of the linear function is not a known parameter of the problem but is some vertices of a simplex .…

Waveform Phasicity Prediction from Arterial Sounds through Spectogram Analysis using Convolutional Neural Networks for Limb Perfusion Assessment

Peripheral Arterial Disease (PAD) is a common form of arterial occlusivedisease that is challenging to evaluate at the point-of-care . Misdiagnoses are also possible with subjective interpretation of doppler waveforms . This paper presents a DeepLearning system that has the ability to predict waveform phasicity throughanalysis of hand-helddoppler sounds .…

Development of digitally obtainable 10 year risk scores for depression and anxiety in the general population

The burden of depression and anxiety in the world is rising . Identification of individuals at increased risk of developing these conditions would help totarget them for prevention and ultimately reduce the healthcare burden . Wedeveloped a 10-year predictive algorithm using thefull cohort of over 400,000 UK Biobank participants without pre-existingdepression or anxiety using digitally obtainable information from the UKBiobank .…

Optimal Design of Electric Micromobility Vehicles

This paper presents a modeling and optimization framework to design batteryelectric micromobility vehicles, minimizing their total cost of ownership . We identify a model of the electric powertrain of ane-scooter and an e-moped consisting of a battery, a single electric motor and atransmission .…

An Initial Algebra Theorem Without Iteration

The Initial Algebra Theorem states that an endofunctor has an initial algebra provided it has a pre-fixed point . The proof crucially depends on transfinitely iterating the functor and shows that the (transfinite)initial-algebra chain stops . This is madepossible by using Pataraia’s .…

Active and sparse methods in smoothed model checking

Smoothed model checking based on Gaussian process classification provides apowerful approach for statistical model checking of parametric continuous timeMarkov chain models . The method constructs a model for the functionaldependence of satisfaction probability on the Markov chain parameters . In this work we considerextensions to smoothed model-checking based on sparse variational methods and active learning .…

Demystifying Regular Expression Bugs A comprehensive study on regular expression bug causes fixes and testing

An empirical study of 356 mergedregex-related pull request bugs from Apache, Mozilla, Facebook, and GoogleGitHub repositories . Correct regular expression behavior is the dominant root cause of regular expression bugs . The remaining root causes are incorrect API usage (9.3%)and other code issues that require regular expression changes in the fix(29.5%) Fixing regular expressions is nontrivial as it takes more time and more lines of code to fix them compared to general pull requests .…

Kalman based interacting multiple model wind speed estimator for wind turbines

State estimation technique offers a means of inferring therotor-effective wind speed based upon solely standard measurements of theturbine . Large model mismatch, particularly in the powercoefficient, could lead to degradation in estimation performance . The proposedestimator is composed of a bank of extended Kalman filters and each filtermodel is developed based on different power coefficient mapping to match the operating turbine parameter .…

Whether the Health Care Practices For the Patients With Comorbidities Have Changed After the Outbreak of COVID 19 Big Data Public Sentiment Analysis

After the pandemic of SARS-CoV-2, it has influenced the health care practices around the world . Initial investigations indicate that patients withcomorbidities are more fragile to this SARS infection . Most of the tweets are reasonable (52.6%)compared to the negative ones (24.3) We developed polarity and subjectivitydistribution to better recognise the positivity/negativity in the sentiment .Results…

EduPal leaves no professor behind Supporting faculty via a peer powered recommender system

We propose asmart, knowledge-based chatbot that addresses issues of knowledge distillation and provides faculty with personalized recommendations . Our collaborativesystem crowdsources useful pedagogical practices and continuously filters recommendations based on theory and user feedback . We build a prototype for our local STEM faculty as a proof concept and receive favorable feedback that encourages us to extend our development and outreach, especially to underresourced faculty, especially .…

GDDR GNN based Data Driven Routing

We explore the feasibility of combining Graph Neural Network-based policyarchitectures with Deep Reinforcement Learning as an approach to problems insystems . This fits particularly well with operations on networks, which take the form of graphs . As a case study, we take the idea of data-driven routing in intradomain traffic engineering, whereby the routing of data in a network can be managed taking into account the data itself .…

Distributed nonlinear model predictive control of an autonomous tractor trailer system

This paper addresses the trajectory tracking problem of an autonomoustractor-trailer system by using a fast distributed nonlinear model predictivecontrol algorithm in combination with nonlinear moving horizon estimation for the state and parameters estimation . The proposed control algorithm is capable of driving the tractor-Trailer system to any desired trajectory ensuring high accuracy and robustness .…

Gradient Matching for Domain Generalization

Machine learning systems typically assume that the distributions of training and test sets match closely . We propose an inter-domain gradient matching objective that targets domaingeneralization by maximizing the inner product between gradients from different domains . We demonstrate the efficacy of Fish on 6 datasets from the Wildsbenchmark, which captures distribution shift across a diverse range ofmodalities .…

A cappella Audio visual Singing Voice Separation

Y-Net is an audio-visualconvolutional neural network that achieves state-of-the-art singing voiceseparation results on the Acappella dataset . The code, the pre-trained models and the dataset will be publicly available at https://ipcv.io/Acappella/ The code is available at http://ipCV.io/. We demonstrate that our model can outperform the baseline models in the singing voice separation task in suchchallenging scenarios.…

On link deletion and point deletion in games on graphs

We discuss link and point deletion operators on graph games and provide acomparative logic-algorithmic study of the same . In particular, we focus on apopular notion of invariance in transition systems, namely, bisimulation, between the respective games on graphs . We present both logical and algorithmicanalyses of the concepts .…

Neural Tree Expansion for Multi Robot Planning in Non Cooperative Environments

We present a self-improving, neural tree expansion method for multi-robotonline planning in non-cooperative environments . Our algorithm adapts the centralized, perfect information,discrete-action space method from Alpha Zero to a decentralized, partial information, continuous action space setting . Our numerical experiments demonstrate neural expansion generatescompact search trees with better solution quality and 20 times less computing expense compared to MCTS without neural expansion .…

Particle Swarms Reformulated towards a Unified and Flexible Framework

The Particle Swarm Optimisation (PSO) algorithm has undergone countless modifications and adaptations since its original formulation in 1995 . The proposed formulation generalises, decouples and incorporates features to the method providing more flexibility to the behaviour of each particle . The closed forms of the trajectory difference equation are obtained, different types of behaviour are identified, stochasticity is decoupled, and global features such as sociometries and constraint-handling arere-defined as particle’s attributes .…

On the social and cognitive dimensions of wicked environmental problems characterized by conceptual and solution uncertainty

Wicked problems reflect our incomplete understanding of interdependent global systems and the hyper-risk they pose . Such problems escape solutions because they are often ill-defined and thus mis-identified andunder-appreciated by problem-solvers and the communities they constitute . We develop a quantitative framework for understanding the class of wicked problems that emerge at the intersections of natural, social, and technological complex systems .…

Tactile Perception based on Injected Vibration in Soft Sensor

Tactile perception using vibration sensation helps robots recognize theirenvironment’s physical properties and perform complex tasks . A sliding motion is infeasible due to geometrical constraints in the environment or an object’s fragility which cannot resist friction forces . A mechanical vibration is applied to a soft tactile sensor from a small, mountedpiezoelectric actuator .…