## Sensitivity as a Complexity Measure for Sequence Classification Tasks

The sensitivity of a function quantifies the number of disjoint subsets of the input sequence that can each be individually changed to change the output . We argue that standard sequence classification methods are biased towards learning low-sensitivity functions, so that tasks requiring high sensitivity are more difficult .…

## Game Theory to Study Interactions between Mobility Stakeholders

Increasing urbanization and exacerbation of sustainability goals threaten theoperational efficiency of current transportation systems . Rise of private, profit-maximizing Mobility Service Providers leveragingpublic resources, such as ride-hailing companies, entangles current regulationschemes . In this paper, we provide a game-theoretic framework to study interactions between stakeholders of the mobility ecosystem, modeling regulatory aspectssuch as taxes and public transport prices, as well as operational matters forMobility Services Providers such as pricing strategy, fleet sizing, and vehicledesign .…

## On reduction and normalization in the computational core

We study the reduction in a lambda-calculus derived from Moggi’s computational core . The reduction relationconsists of rules obtained by orienting three monadic laws . We investigate the central notions of returning a value versus having a normal form, and address the question of normalizing strategies .…

## Three Dimensional Mesh Steganography and Steganalysis A Review

Three-dimensional (3-D) meshes are commonly used to represent virtualsurfaces and volumes . Over the past decade, 3-D meshes have emerged in industrial, medical, and entertainment applications . We propose a new taxonomy of steganographic algorithms with four categories: 1) two-state domain, 2- LSB domain, 3) permutation domain, 4) transform domain .…

## Voice2Mesh Cross Modal 3D Face Model Generation from Voices

Previous works for cross-modal facesynthesis study image generation from voices . However, image synthesis includesvariations such as hairstyles, backgrounds, and facial textures, that arearguably irrelevant to voice . Weinstead investigate the ability to reconstruct 3D faces to concentrate on onlygeometry, which is more physiologically grounded .…

## Improving Test Distance for Failure Clustering with Hypergraph Modelling

An unknown number of faults can independently cause multiple test case failures . Automated debugging techniques are typically designed under the Single Fault Assumption . We introduce a new test distance metric based on hypergraphs and evaluate their accuracy using multi-fault benchmarks .…

## FireFly Autonomous Drone Project

FireFly drone-based rescue consists of a squad of highly equipped drones that will be the first responders to the fire site . As soon as the fire is detected by in-building implantedsensors, the fire department would deploy a set of FireFly drones that would scan the site, scan the building, and send live fire status information to the Fire fighter team .…

## MuseMorphose Full Song and Fine Grained Music Style Transfer with Just One Transformer VAE

Transformers and variational autoencoders have been extensivelyemployed for symbolic (e.g., MIDI) domain music generation . The latter allow users to exert control over different parts of the musicto be generated . The resulting MuseMorphose model outperforms recurrent neural network (RNN) based prior art on numerous widely-used metrics for style transfer tasks .…

## FireFly Autonomous Drone Project

FireFly drone-based rescue consists of a squad of highly equipped drones that will be the first responders to the fire site . As soon as the fire is detected by in-building implantedsensors, the fire department would deploy a set of FireFly drones that would scan the site, scan the building, and send live fire status information to the Fire fighter team .…

## Machine Learning Assisted Optimization Strategies for Phase Change Materials Embedded within Electronic Packages

Leveraging the latent heat of phase change materials (PCMs) can reduce the peak temperatures and transient variations in temperature in electronic devices . As the power levels increase, the thermal conduction pathway from the heat source to the heat sink limits the effectiveness of these systems .…

## Electrification of Commercial E buses by Utilizing Stationary Battery Energy Storage Systems for Mass Transportation Network in Los Angeles

The 2028 LA Olympics is approaching, and the mass transportation network needs to be expanded . The introduction of a large electric bus fleet will increasethe peak load demand, which will adversely affect the grid . The potential implementationof stationary battery energy storage systems is investigated to shave the peakload demand by providing energy during peak hours .…

## 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}.…

## 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 .…

## Reduced order modeling of LPV systems in the Loewner framework

We propose a model reduction method for LPV systems . We consider LPV state-space representations with an affine dependence on the schedulingvariables . The main idea behind the proposed method is to compute the reducedorder model in such a manner that its frequency domain transfer function matches with that of the original model for some frequencies .…

## Robust Testing and Estimation under Manipulation Attacks

We study robust testing and estimation of discrete distributions in thestrong contamination model . We consider both the “centralized setting” and the “distributed setting with information constraints” including communication and privacy (LDP) constraints . Our technique relates the strength ofmanipulation attacks to the earth-mover distance using Hamming distance as themetric between messages(samples) from the users .…

## Accelerating SpMM Kernel with Cache First Edge Sampling for Graph Neural Networks

Current GNNs suffer from poor performance of their sparse-dense matrix multiplication (SpMM) operator . 95% of the inference time could be spent on SpMM when running popular GNN models on NVIDIA’s advanced V100 GPU . ES-SpMM uses edge sampling to downsize the graph to fit into GPU’s shared memory .…

## Adversarial Training for Deep Learning based Intrusion Detection Systems

Deep Neural Networks (DNNs) report state-of-the-art results in many machine learning areas, including intrusion detection . Recent studies in computer vision have shown that DNNs can be vulnerable toadversarial attacks that are capable of deceiving them into misclassification by injecting specially crafted data .…

## 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 .…

## Nonlinear Tracking and Rejection using Linear Parameter Varying Control

The Linear Parameter-Varying (LPV) framework has been introduced with the intention to provide stability and performance guarantees for analysis andcontroller synthesis for Nonlinear (NL) systems via convex methods . We propose to solve this problem by the application of incremental stability and .…

## 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 .…

## Strategies for COVID 19 vaccination under a shortage scenario a geo stochastic modelling approach

SEIRS stochastic model of geographical spreading of the virus is extended by adding a compartment for vaccinated people . The parameters of the model were fitted to describe the pandemic evolution in Argentina,Mexico and Spain to analyze the effect of the proposed vaccination strategies .…

## GPS denied Navigation Attitude Position Linear Velocity and Gravity Estimation with Nonlinear Stochastic Observer

Successful navigation of a rigid-body traveling with six degrees of freedom(6 DoF) requires accurate estimation of attitude , position, and linearvelocity . The true navigation dynamics are highly nonlinear and are modeled on the matrix Lie group of SE2(3). This paper presents novel geometric nonlinearcontinuous stochastic navigation observers .…

## Decidability and Complexity in Weakening and Contraction Hypersequent Substructural Logics

We establish decidability for the infinitely many axiomatic extensions of the Full Lambek logic with weakening FLew (i.e. IMALLW) that have acut-free hypersequent proof calculus . Decidability of the corresponding extensions of itscontraction counterpart FLec was established recently but their computationalcomplexity was left unanswered .…

## On the Impact of Word Error Rate on Acoustic Linguistic Speech Emotion Recognition An Update for the Deep Learning Era

Text encodings from automatic speech recognition (ASR) transcripts and audiorepresentations have shown promise in speech emotion recognition (SER) eversince . Yet, it is challenging to explain the effect of each information stream on the SER systems . More clarification is required for analysing the impact of ASR’s word error rate (WER) on linguistic emotion recognition per seand in the context of fusion with acoustic information exploitation in the age of deep ASR systems .…

## Locally Private k Means in One Round

We provide an approximation algorithm for k-means clustering in the one-round(aka non-interactive) local model of differential privacy (DP) This algorithmachieves an approximation ratio arbitrarily close to the best non-approximation algorithm, improving upon previously known algorithms that only guarantee large (constant) approximation ratios .…

## Passive Transparent and Selective TLS Decryption for Network Security Monitoring

Internet traffic is increasingly encrypted . Many enterprise networks have deployed man-in-the-middle (MitM) proxies that intercept connections at the networkborder . But studies have shown that interception often reduces connection security and potentially introduces additional attack vectors to the network .…

## Simple Type Theory is not too Simple Grothendieck s Schemes without Dependent Types

We report on a formalization of schemes in the proof assistant Isabelle/HOL . Schemes aresophisticated mathematical objects in algebraic geometry introduced by Grothendieck in 1960 . We show how the powerful dependent types of Coq or Lean can be traded for a minimalist apparatus called locales .…

## Towards Solving Multimodal Comprehension

This paper targets the problem of procedural multimodal machine comprehension(M3C) This task requires an AI to comprehend given steps of multimodalinstructions and then answer questions . Yagcioglu etal. [35] introduced RecipeQA dataset to evaluate M3C . We hypothesized that naturally occurring bias present in the dataset affects even the bestperforming model .…

## Rapid feasibility assessment of components formed through hot stamping A deep learning approach

The novel non-isothermal Hot Forming and cold die Quenching (HFQ) process canenable the cost-effective production of complex shaped, high strength aluminiumalloy panel components . However, the unfamiliarity of designing for the new process prevents its widescale adoption in industrial settings .…

## Robust Sensor Fusion Algorithms Against VoiceCommand Attacks in Autonomous Vehicles

Voice Control Systems have becomeincreasingly adopted as human-vehicle interaction methods . This technology enables drivers to use voice commands to control the vehicle and will be soon available in Advanced Driver Assistance Systems (ADAS) Prior work has shown that Siri, Alexa and Cortana, are highly vulnerable to inaudible commandattacks .…

## Crystal structure prediction of materials with high symmetry using differential evolution

Crystal structure determines properties of materials . Many physical and chemical properties can be predicted by first-principles calculations or machine learning models . We propose to use PyXtal to generate and filter random crystal structures with given symmetry constraints based on the information such as chemical formulas and space groups .…

## Efficient Retrieval Optimized Multi task Learning

Recently, there have been significant advances in neural methods for tackling knowledge-intensive tasks such as open domain question answering . Using our framework, we achieve comparable or better performance than recent methods on QA, while drastically reducing thenumber of parameters .…

## Mapping Moral Valence of Tweets Following the Killing of George Floyd

The viral video documenting the killing of George Floyd by Minneapolis police officer Derek Chauvin inspired nation-wide protests . The use of social media by the BlackLives Matter movement was a primary route for activists to promote the cause . Recent research arguesthat moral discussions on social media are a catalyst for social change .…

## Computing homotopy classes for diagrams

We present an algorithm that computes the set $[X,Y]^A_G$ of homotopyclasses of equivariant maps . For fixed \$n = \operatorname{dim} X, the algorithm runsin polynomial time . The algorithm can be utilized to compute homotopopy invariants in theequivariant setting . Further, one can apply the result to solve problems from computational topology .…

## Distributed Online Aggregative Optimization for Dynamic Multi robot Coordination

This paper focuses on an online version of the emerging distributedconstrained aggregative optimization framework . Agents in a network want tominimize the sum of local cost functions, each one depending both on a localoptimization variable, subject to a local constraint, and on an aggregatedversion of all the variables (e.g.,…

## Hypervolume Optimal μ Distributions on Line Plane based Pareto Fronts in Three Dimensions

Hypervolume is widely used in the evolutionary multi-objective optimization field to evaluate quality of a solution set . A larger hypervolume means a better solutionset . We show that a uniform solution set on theplane-based Pareto front is not always optimal for hypervolume maximization .…