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 .…

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 .…

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 .…

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 .…

On the rank of Z_2 matrices with free entries on the diagonal

We prove that for each non-negative integer $k$ there is a polynomial in $n$ algorithm deciding whether $R(M) \leq k$ (whosecomplexity may depend on $k) These results haveapplications to graph drawings on non-orientable surfaces . For an $n \times n$ matrix $M$ with entries in $\mathbb{Z}_2$ denote by$R(m)$ the minimal rank of all the matrices .…

Enabling Fast Exploration and Validation of Thermal Dissipation Requirements for Heterogeneous SoCs

Paper discusses an approach that enables fast exploration and validation of heterogeneous systemon chips (SoCs) platform configurations with respect to their thermaldissipation . Such platforms can be configured to find the optimal trade-off between performance and power consumption . This directly reflects in the headdissipation of the platform, which when increases over a given threshold will actually decrease the performance .…

Label Synchronous Speech to Text Alignment for ASR Using Forward and Backward Transformers

The speech-to-text alignment is a problem of splitting long audio recordings with un-aligned transcripts into utterance-wise pairs of speech and text . Unlike conventional methods, the proposed method re-defines the problem as a label-synchronous text mapping problem . Thisenables an accurate alignment benefiting from the strong inference ability of the state-of-the-art attention-based encoder-decoder models, which cannot be applied to the conventional methods .…

What s The Context Long Context NLM Adaptation for ASR Rescoring in Conversational Agents

Neural Language Models (NLM) consistently outperform n-gram language models and NLMs that use limited context . We propose the use of attention layer over lexicalmetadata to improve feature based augmentation . We adapt ourcontextual NLM towards user provided on-the-fly speech patterns by leveragingencodings from a large pre-trained masked language model and performing fusion with a Transformer-XL based NLM .…

On the Path to 6G Low Orbit is the New High

We provide an overview of the key aspects of low Earth orbit (LEO) satellitecommunication networks towards 6G . Offering space-based Internet services withmega-constellations of LEO satellites is a promising solution to connecting theunserved and underserved . Integrating LEOsatellite access in cellular systems will be one of the connectivity’s newfrontiers on the path to 6G.…

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 .…

Market Value of Differentially Private Smart Meter Data

This paper proposes a framework to investigate the value of sharingprivacy-protected smart meter data between domestic consumers and load servingentities . The framework consists of a discounted differential privacy model toensure individuals cannot be identified from aggregated data . It also includes a ANN-basedshort-term load forecasting to quantify the impact of data availability and privacy protection on the forecasting error and an optimal procurement day-ahead and balancing markets to assess the market value of the privacy-utility trade-off .…

Autonomous Situational Awareness for UAS Swarms

This paper describes a technique for the autonomous mission planning of unmanned aerial system swarms . Given a swarm operating in a known area, acentral command system generates measurements from the swarm . If those measurements indicate changes to the mission situation such as target movement, swarm planning is updated to reflect the new situation .…

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 .…

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 .…

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 .…

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 .…

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 .…

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 .…