VPPS ART An Efficient Implementation of Fixed Size Candidate Set Adaptive Random Testing using Vantage Point Partitioning Strategy

Vantage Point PartitioningStrategy based ART (VPPS-ART) attempts to solve the computational overhead problem of FSCS-ART using vantage point partitioning strategy . VPPS-AR achieves the partitioning of the input domain space by using a Vantage point tree (VP-tree) and finds the nearest executed test cases of a candidate test case in thepartitioned sub-domains, which reduces the time overhead significantly compared to the entire input domain search computation .…

Geometric Model Checking of Continuous Space

Spatial Logicof Closure Spaces, SLCS, extends Modal Logic with reachability connectivesthat, in turn, can be used for expressing interesting spatial properties . SLCS constitutes the kernel of asolid logical framework for reasoning about discrete space, such as graphs and digital images, interpreted as quasi discrete closure spaces .…

SoK Practical Foundations for Spectre Defenses

Spectre vulnerabilities violate our fundamental assumptions aboutarchitectural abstractions . This paper systematizes the community’s current knowledge about softwareverification and mitigation for Spectre . We study state-of-the-art softwaredefenses, both with and without associated formal models, and use a cohesive framework to compare the security properties each defense provides .…

Edge Augmentation with Controllability Constraints in Directed Laplacian Networks

In this paper, we study the maximum edge augmentation problem in directedLaplacian networks to improve their robustness while preserving lower bounds on their strong structural controllability (SSC) The main objective is to maximallydensify a given network by selectively adding missing edges while ensuring thatSSC of the network does not deteriorate beyond certain levels specified by theSSC bounds .…

Modeling and Evaluation of Clustering Patient Care into Bubbles

COVID-19 has caused an enormous burden on healthcare facilities around the world . Cohorting patients and healthcare professionals (HCPs) into “bubbles” has been proposed as an infection-control mechanism . This model aims to control avariety of costs to patients/residents and HCPs so as to avoid hidden, downstream adverse effects of clustering patient care .…

Fairness and Discrimination in Information Access Systems

Recommendation, information retrieval, and other information access systemspose unique challenges for investigating and applying the fairness and non-discrimination concepts that have been developed for studying other machinelearning systems . Fair information access shares many commonalities with fair classification, the rank-based problem setting, the centrality of personalization in many cases, and the role of user response complicate the problem of identifying what types and operationalizations of fairness may berelevant, let alone measuring or promoting them .…

A Hybrid Wired Wireless Deterministic Network for Smart Grid

Hybrid wired/wireless high-precision timesynchronization network based on a combination of high-speed TTE and 5GUltra-Reliable and Low-Latency Communications (URLLC) is proposed . The mainmotivation is to comply with the low latency, low jitter, and high reliability requirements of time critical applications, such as smart grid synchrophasorcommunications .…

HeunNet Extending ResNet using Heun s Methods

There is an analogy between the ResNet (Residual Network) architecture for deep neural networks and an Euler solver for an ODE . HeunNet achieves high accuracy with low computational(both training and test) time compared to both vanilla recurrent neuralnetworks and other ResNet variants .…

The Inductive Approach to Verifying Cryptographic Protocols

The approach is based on ordinarypredicate calculus and copes with infinite-state systems . The model spyknows some private keys and can forge messages using components decrypted from previous traffic . The human effort required to analyze a protocol can be as little as a week or two, yielding a proof script that takes a few minutes torun .…

DataExposer Exposing Disconnect between Data and Systems

DataExposer is a framework to identify data properties, called profiles, that are the root causes of performance degradation or failure of a system that operates on the data . The framework is based on causal reasoning through interventions, which alters the data profiles and observes changes in the system’s behavior due to the changes made by those changes .…

Forensic Analysis of Video Files Using Metadata

The ability to manipulate video content has led to arapid spread of manipulated media . The availability of video editing tools has increased in recent years, allowing one to easily generate photo-realistic alterations . Such manipulations can leave traces in themetadata embedded in video files .…

Changeable Sweep Coverage Problem

Paper studies the sweep coverage of rechargeable sensors . It is difficult for sensors to reduce energy consumption by reducing the moving distances . Charging technology is the best way to extend the lifetime of the sweep coveragenetwork . The validity and scalability of the proposed algorithms is proved by theoretical proof and experimental simulation .…

Analysis of Busy Time Scheduling on Heterogeneous Machines

This paper studies a generalized busy-time scheduling model on heterogeneousmachines . Each job has a size and a time interval during which it should be processed . Different types of machines have distinct capacities and cost rates . Each machine used is charged according to the time duration in which it is busy, i.e.,…

Orienting Framing Bridging Magic and Counseling How Data Scientists Navigate the Outer Loop of Client Collaborations in Industry and Academia

Data scientists often collaborate with clients to analyze data to meet a client’s needs . They work with clients in a six-stage outer-loop workflow, which involves laying groundwork by building trust before a project begins, orienting to the constraints of the client’s environment, 3) collaborativelyframing the problem, 4) bridging the gap between data science and domainexpertise, 5) the inner loop of technical data analysis work, 6) counseling tohelp clients emotionally cope with analysis results .…

Improving Code Autocompletion with Transfer Learning

Software language models have achieved promising results predicting codecompletion usages . We find pretraining autocompletion models improve model accuracy by over 50% on very small fine-tuningdatasets and over 10% on 50k labeled examples . We confirm the real-world impact of these pretrainings in an online setting through A/B testing on thousands of users, finding that pretraining is responsible for increases of up to 6.63% autocom completion usage.…

On the Monitorability of Session Types in Theory and Practice

In concurrent and distributed systems, software components are expected tocommunicate according to protocols and APIs . If a component does not observe these protocols, the system’s reliability is compromised . This work takes a fresh look at the run-time verification of communicating systems using session types, in theory and in practice .…

OpenFL An open source framework for Federated Learning

Open Federated Learning (OpenFL) is an open-source framework for training ML algorithms using the data-privatecollaborative learning paradigm of FL . FL is a computational paradigm that enables organizations to collaborate on machine learning (ML) projects without sharingsensitive data, such as, patient records, financial data, or classified secrets .…

Causal Intervention for Leveraging Popularity Bias in Recommendation

Recommender system usually faces popularity bias issues: from the dataperspective, items exhibit uneven (long-tail) distribution on the interactionfrequency . Collaborative filtering methods areprone to amplify the bias by over-recommending popular items . We propose a new training and inference paradigm for recommendation named Popularity-bias Deconfounding and Adjusting (PDA) It removes theconfounding popularity bias in model training and adjusts the recommendationscore with desired popularity bias via causal intervention .…

Equilibria in Schelling Games Computational Complexity and Robustness

In the simplest game-theoretic formulation of Schelling’s model ofsegregation on graphs, agents of two different types each select their ownvertex in a given graph such as to maximize the fraction of agents of theirtype in their occupied neighborhood . Two ways of modeling agent movement here are either to allow two agents to swap their vertices or to allow an agent to jump to a free vertice .…

An Algorithm for Limited Visibility Graph Searching

We study a graph search problem in which a team of searchers attempts to find a mobile target located in a graph . We formulate the Limited Visibility Graph Search (LVGS)problem and present the LVGS algorithm . Our LVGSalgorithm is a conversion of Guibas and Lavalle’s polygonal region searchalgorithm.…

Two Influence Maximization Games on Graphs Made Temporal

To address the dynamic nature of real-world networks, we generalizecompetitive diffusion games and Voronoi games from static to temporal graphs, where edges may appear or disappear over time . This establishes a new direction of studies in the area of graph games, motivated by applications such asinfluence spreading .…

Trusted Authentication using hybrid security algorithm in VANET

VANETs are vulnerable to variety of security attacks from malicious entities . Elliptic Curve Cryptography can provide impressive levels of security standards while keeping down the cost of certain issues, primarily storagespace . Sensors will benefit from having to store relatively smaller keyscoupled with increased computational capability and this will be a stronger design as the bit-level security is improved .…

Multi target DoA Estimation with an Audio visual Fusion Mechanism

Humans use auditory and visual senses to detect the presence of sound sources . We propose to use neural networks with audio and visual signals for multi-speaker localization . The use ofheterogeneous sensors can provide complementary information to overcome challenges such as noise, reverberation, illumination variations,and occlusions .…

A Graphical Calculus for Lagrangian Relations

The category of linear Lagrangianrelations between symplectic vector spaces is a symmetric monoidal subcategory of relations . It gives a semantics for the evolution of the evolution — and more generally, constraints — of various physical systems . We prove the equivalence of the prop of affine LAGrangian relations with the prop .…

A Unified Metamodel for NoSQL and Relational Databases

Multi-model database tools normally use a generic or unified metamodel to represent schemas of the data model that they support . The number of mappings required to migrate databases from a data model to another is reduced . Polyglot persistence is envisioned as the architecture to be prevalent in the future .…

Hedging Against Sore Loser Attacks in Cross Chain Transactions

A *sore loser attack* in cross-blockchain commerce rises when one party decides to halt participation partway through, leaving other parties’ assets locked up for a long duration . This paper proposes new distributed protocols for hedging a range of cross-chain transactions in a synchronous communication model, such astwo-party swaps, $n$ swaps, brokered transactions, and auctions .…

A Large Scale Benchmark for Food Image Segmentation

Food image segmentation is a critical and indispensible task for developing health-related applications such as estimating food calories and nutrients . There is a lack of high quality food image datasets with fine-grainedingredient labels and pixel-wise location masks . In this work, we build a new food image dataset FoodSeg103 (and its extensionFoodSeg154) containing 9,490 images .…

On Minimizing the Number of Running Buffers for Tabletop Rearrangement

For tabletop rearrangement problems with overhand grasps, storage space outside the workspace or buffers can temporarily hold objects which facilitate the resolution of a given task . We show that finding the minimum number of running buffers (MRB) can be carried out on a dependency graph abstracted from a problem instance, and show that computing MRB on dependency graphs isNP-hard .…

Graph Learning based Recommender Systems A Review

Recent years have witnessed the fast development of the emerging topic ofGraph Learning based Recommender Systems (GLRS) GLRS employ advanced graphlearning approaches to model users’ preferences and intentions as well as items’ characteristics for recommendations . Differently from other RSapproaches, including content-based filtering and collaborative filtering, GLRSare built on graphs where the important objects, e.g.,…

DeepQAMVS Query Aware Hierarchical Pointer Networks for Multi Video Summarization

DeepQAMVS is trained withreinforcement learning, incorporating rewards that capture representativeness, diversity, query-adaptability and temporal coherence . We achievestate-of-the-art results on the MVS1K dataset, with inference time scalinglinearly with the number of input video frames . We design ahierarchical attention model that factorizes over three distributions, eachcollecting evidence from a different modality, followed by a pointer network that selects frames to include in the summary .…

Deciding FO definability of Regular Languages

We prove that FO-languages are known to define regular languages that are decidable in AC0 and ACC0 . We obtain these results by showing that known algebraiccharacterisations of FO-definability of L(A) can be captured by `localisable’properties of the transition monoid of A .…

Implementing Quantum Finite Automata Algorithms on Noisy Devices

Quantum finite automata (QFAs) literature offers an alternative mathematical model for studying quantum systems with finite memory . In this paper we present improved circuit based implementations for QFA algorithms recognizing the $MOD_p $ problem using the Qiskit framework . We focus on the case $p=11$ and provide a 3 qubit implementation for the $mod_{11}$ problem reducing the total number of required gates using alternative approaches .…

SIDE I Infer the State I Want to Learn

State Inference for valueDEcomposition (SIDE) can be extended to any value decomposition method, as well as multi-agent algorithms in the case of Dec-POMDP . SIDE can construct the current statethat contributes to the reinforcement learning process based on past local observations .…