## A Projection Stable Grammatical Model for the Distributed Execution of Administrative Processes with Emphasis on Actors Views

The decentralized execution of business processes has been one of the main research topics in Business ProcessManagement . LSAWfP is among themost recent in this area: it helps to specify administrative processes with grammatical models indicating, in addition to their fundamental elements, thepermissions (reading, writing and execution) of each actor in relation to each of their tasks .…

## CheckSoft A Scalable Event Driven Software Architecture for Keeping Track of People and Things in People Centric Spaces

The architecture works off the video data generated in real time by a network of surveillance cameras . The architecture is based on multi-processing in which a separate process is assigned to each human and to each “storage container” for the objects .…

## Generalized Gapped kmer Filters for Robust Frequency Estimation

In this paper, we study the generalized gapped k-mer filters and derive a closed form solution for their coefficients . We develop aM\”obius-like function which helps us to obtain closed forms for a complete set of mutually orthogonal eigenvectors of $A^{\top} A$ .…

## Mining EL Bases with Adaptable Role Depth

In Formal Concept Analysis, a base for a finite structure is a set of implications that characterizes all valid implications of the structure . Thisnotion can be adapted to the context of Description Logic, where concept expressions can be arbitrarily large .…

## Dimensions of Timescales in Neuromorphic Computing Systems

This article is a public deliverable of the EU project “Memory technologieswith multi-scale time constants for neuromorphic architectures” (MeMScales,https://memscales.eu, Call ICT-06-2019 Unconventional Nanoelectronics, projectnumber 871371) This arXiv version is a verbatim copy of the deliverablereport, with administrative information stripped . It collects a wide and variedassortment of phenomena, models, research themes and algorithmic techniquesthat are connected with timescale phenomena in the fields of computationalneuroscience, mathematics, machine learning and computer science .…

## Model Checking for Decision Making System of Long Endurance Unmanned Surface Vehicle

This work aims to develop a model checking method to verify the decisionmaking system of Unmanned Surface Vehicle (USV) in a long range surveillance mission . The scenario in this work was captured from a long endurance USVsurveillance mission using C-Enduro, an USV manufactured by ASV Ltd.…

## Almost Full EFX Exists for Four Agents and Beyond

The existence of EFX allocations is a major open problem in fair division,even for additive valuations . EFX exists if onecan leave $n-1$ items unallocated, where $n$ is the number of agents . We develop new techniques that allow us to push the boundaries of the EFX problem beyond these known results, and, arguably, to simplifyproofs of earlier results .…

## A Game Theoretic Approach for Hierarchical Policy Making

We present the design and analysis of a multi-level game-theoretic model of hierarchical policy-making . Our model captures the potentially mismatched priorities among ahierarchy of policy-makers (e.g., federal, state, and local governments) Our model includes a crucial third factor in decisions: a cost of non-compliance with the policy-maker immediately above in thehierarchy .…

## Dealing with Non Stationarity in Multi Agent Reinforcement Learning via Trust Region Decomposition

Non-stationarity is one thorny issue in multi-agent reinforcement learning . Simple policyfactorization like mean-field approximation will mislead to larger policydivergence, which can be considered as trust region decomposition dilemma . MAMT can adjust the trust region of the local policies adaptively in an end-to-end manner, thereby approximately approximately constraining the divergence of joint policy to alleviate the non-stationaryproblem .…

## Mastering Terra Mystica Applying Self Play to Multi agent Cooperative Board Games

In this paper, we explore and compare multiple algorithms for solving the complex strategy game of Terra Mystica, hereafter abbreviated as TM . We call this modified algorithm with our novel state-representation AlphaTM . We discuss the success and shortcomings of this method by comparing against multiple baselines and typicalhuman scores .…

## Contextual First Price Auctions with Budgets

The internet advertising market is a multi-billion dollar industry . In recent years, the industry has shifted to first-price auctions as the preferred paradigm for selling advertising slots . We show the existence of a natural value-pacing-based Bayes-Nash equilibrium under very mild assumptions .…

## Towards Immersive Virtual Reality Simulations of Bionic Vision

Bionic vision is a rapidly advancing field aimed at developing visualneuroprostheses to restore useful vision to people who are blind . A major outstanding challenge is predicting what people ‘see’ when they use their devices . The limited field of view of current devicesnecessitates head movements to scan the scene, which is difficult to simulate on a computer screen .…

## User interface for in vehicle systems with on wheel finger spreading gestures and head up displays

A novel on-wheel finger spreading gestural interface combined with ahead-up display (HUD) allows the user to choose a menu displayed in the HUD with a gesture . This interface displays audio and air conditioning functions on the central console of a HUD and enables their control using a specific number of fingers while keeping both hands on the steering wheel .…

## Genetic Meta Structure Search for Recommendation on Heterogeneous Information Network

The heterogeneous information network (HIN) has become animportant methodology for modern recommender systems . The number of meta-structures growsexponentially with its size and the number of node types, which prohibits brute force search . We propose GeneticMeta-Structure Search (GEMS) to automatically optimize meta-structure designs for recommendation on HINs .…

## EXTRA Explanation Ranking Datasets for Explainable Recommendation

Research on explainable recommender systems (RS) has drawn muchattention from both academia and industry . We provide three benchmark datasets for EXplanaTion RAnking(denoted as EXTRA) on which explainability can be measured by ranking-orientedmetrics . Constructing such datasets presents great challenges, since it has quadratic runtime complexity to estimate the similarity between any two sentences .…

## Relative Expressiveness of Defeasible Logics II

Maher 2012 introduced an approach for relative expressiveness of defeasiblelogics . We show that all thedefeasible logics in the DL framework are equally expressive under this form . We also show that logics incorporating individual defeat are equally expressive as those with team defeat .…

## Logics of Dependence and Independence The Local Variants

Modern logics of dependence and independence are based on team semantics . This means formulae are evaluated on a set of assignments, called a team . This leads to highexpressive power, on the level of existential second-order logic . Baltag and van Benthem have proposed a local variant of dependencelogic, called logic of functional dependence (LFD) For the variant of LFD without equality, the satisfiability problem is decidable .…

## Multi Agent Consensus Subject to Communication and Privacy Constraints

We consider a multi-agent consensus problem in the presence of adversarial adversaries . The adversaries are able to listen to the inter-agent communicationsand try to estimate the state of the agents . We propose aconsensus protocol that is protected against the adversaries, i.e.,…

Policy gradient methods can solve complex tasks but often fail when thedimensionality of the action-space or objective multiplicity grow very large . This occurs, in part, because the variance on score-based gradient estimators scales quadratically with the number of targets .…

## Convergence rate of DeepONets for learning operators arising from advection diffusion equations

We present convergence rates of operator learning in [Chen and Chen 1995] and[Lu et al. 2020] when the operators are solution operators of differentialequations . In particular, we consider solutions operators of both linear andnonlinear advection-diffusion equations .…

## Bifurcation analysis of two dimensional Rayleigh Bénard convection

We perform a bifurcation analysis of the steady state solutions of Rayleigh–B\’enard convection with no-slip boundary conditions in twodimensions using a numerical method called deflated continuation . By combining this method with an initialisation strategy based on the eigenmodes of theconducting state, we are able to discover multiple solutions to this non-linearproblem .…

## A new efficient operator splitting method for stochastic Maxwell equations

This paper proposes and analyzes a new operator splitting method forstochastic Maxwell equations driven by additive noise . The method is numerically efficient, and preserves the symplecticity, the growth rate of the averaged energy . Adetailed $H^2$-regularity analysis of stochastic equations is obtained, which is a crucial prerequisite of the error analysis .…

## Dynamic Selective Positioning for High Precision Accuracy in 5G NR V2X Networks

The capability to achieve high-precision positioning accuracy has been considered as one of the most critical requirements for vehicle-to-everything(V2X) services in the fifth-generation (5G) cellular networks . We propose a novel selective positioning solution to dynamicallyswitch between different positioning technologies to improve the overall positioning accuracy in NR V2X services .…

## STDP enhances learning by backpropagation in a spiking neural network

The proposed method consists of supervised learning by backpropagation and unsupervised learning by spike-timing-dependent plasticity (STDP), which is a biologically plausible learning rule . Numerical experiments show that the proposed method improves the accuracy without additional labeling when a small amount of labeled data is used .…

## Neural Sampling Machine with Stochastic Synapse allows Brain like Learning and Inference

Many real-world mission-critical applications require continual onlinelearning from noisy data and real-time decision making with a defined confidence level . Harnessing the inherentnon-linearities and stochasticity occurring at the atomic level in emergingmaterials and devices . We alsoshowcase the Bayesian inferencing capability introduced by the stochasticsynapse introduces a multiplicativestochastic noise within the synapses of the neural network that samples the conductance states of the FeFET, both during learning and inference .…

## Liberalisation of the International Gateway and Internet Development in Zambia The Genesis Opportunities Challenges and Future Directions

Telecommunication reforms in Zambia and the subsequent liberalisation of the international gateway was perceived as one of the means of promoting social and economic growth in both the urban and rural areas of the country . The outcome of this undertaking propelled the rapid development of Internet which has brought about unprecedented paradigm shifts in the use of Informationand Communication Technologies (ICTs) It is indisputable that ICTs, and theInternet in particular, have revolutionalised the way we communicate today.…

## CFLMEC Cooperative Federated Learning for Mobile Edge Computing

We investigate a cooperative federated learning framework among devices formobile edge computing, named CFLMEC . Devices can transmit local models to the corresponding devices or the edge server in a relay race manner . We proposecommunication resource allocation algorithms with and without sufficientsub-channels for strong reliance on edge servers (SRs) in cellular link, and interference aware communication resource allocation algorithm for less reliance on the edge servers in D2D link .…

## Customized Slicing for 6G Enforcing Artificial Intelligence on Resource Management

Next generation wireless networks are expected to support diverse vertical industries and offer countless emerging use cases . E2Eresource management is decomposed into two problems, multi-dimensional resourceallocation decision based on slice-level feedback and real-time slice adaption . Simulation results demonstratethe effectiveness of AI-based customized slicing are simulated .…

## GMA A Pareto Optimal Distributed Resource Allocation Algorithm

Global myopic allocation (GMA) algorithm is asolution to the problem of over-allocating resources . The algorithm is Pareto optimal with respect to the allocationsize . The resulting path allocations are large enough to fit therequirements of practically relevant applications, authors say .…

## Overcoming Restraint Modular Refinement using Cogent s Principled Foreign Function Interface

Cogent is a restricted functional language designed to reduce the cost of developing verified systems code . It does not support recursion nor iteration, and its type system imposes restrictions that are sometimes toostrong for low-level system programming . To overcome these restrictions, Cogsent provides a foreign function interface (FFI) that allows for implementing those parts of the system which cannot be expressed in C can be implemented in C and called from C .…

## Learnable MFCCs for Speaker Verification

We propose a learnable mel-frequency cepstral coefficient (MFCC) frontendarchitecture for deep neural network (DNN) based automatic speakerverification . In practice, we formulate data-driven versions of the four linear transforms of a standard MFCC extractor . Results reported reach up to6.7\% (VoxCeleb1) and 9.7% (SITW) relative improvement in term of equal errorrate (EER) from static MFCCs .…

## Social Networks Analysis to Retrieve Critical Comments on Online Platforms

Social networks are rich source of data to analyze user habits in all aspect of life . User’s behavior is decisive component of a health system in variouscountries . Promoting good behavior can improve the public health significantly. Promoting thehealthy life style in the high risk online users of social media havesignificant effect on public health and reducing the effect of global pandemic .…

## Phase field modeling on the diffusion driven processes in metallic conductors and lithium ion batteries

Diffusion-driven processes are important phenomena of materials science inthe field of energy conversion and transmission . During the conversion fromchemical energy to electrical energy, the species diffusion is generally linked to the rate of exchange, and hence to the performance of the conversion device .…

## On guarding polygons with holes

There is an old conjecture by Shermer \cite{sher} that in a polygon with $n$vertices and $h$ holes, the guards aresufficient to guard the entire polygon . In this paper, we prove a theorem similar to the Shermer’s conjecture for aspecial case where the goal is to guard vertices of the polygon (not theentire polygon) which is equivalent to finding a dominating set for thevisibility graph .…

## Spotting Silent Buffer Overflows in Execution Trace through Graph Neural Network Assisted Data Flow Analysis

A software vulnerability could be exploited without any visible symptoms . A graph neuralnetwork (GNN) assisted data flow analysis method for spotting silent bufferoverflows in execution traces . The proposed method is, to our best knowledge, the first general-purposeanalysis method for silent buffer overflows.…

## A Novel Key Generation Scheme Using Quaternary PUF Responses and Wiretap Polar Coding

Physical unclonable functions (PUFs) are widely considered in secret keygeneration for resource constrained devices . However, PUFs require additional hardware overhead . A novel method for extractingquaternary PUF responses is proposed to increase the entropy of a PUF response . A 2-bit response is extracted from evaluating a single PUF cell multiple times .…

## Cybersecurity Awareness Platform with Virtual Coach and Automated Challenge Assessment

The number of cyber-attacks on industrial control systems has been steadily increasing . Proper softwaredevelopment plays a vital role in keeping these systems secure . To achievesecure software, developers need to be aware of secure coding guidelines and secure coding best practices .…

## When Crowdsensing Meets Federated Learning Privacy Preserving Mobile Crowdsensing System

Mobile crowdsensing (MCS) is an emerging sensing data collection pattern withscalability, low deployment cost, and distributed characteristics . Traditional MCS systems suffer from privacy concerns and fair reward distribution . In order to protect privacy, participants locally process sensing data via federated learning and only upload encrypted training models .…

## WaNet Imperceptible Warping based Backdoor Attack

The proposed backdoor outperforms the previous methods in a human inspection test by a wide margin, proving its stealthiness . Backdoor attacks are all built on noise perturbation triggers, making them noticeable to humans . To make such models undetectable by machine defenders, we propose a novel training mode, called the “noise mode .…

## Heterogeneous Demand Effects of Recommendation Strategies in a Mobile Application Evidence from Econometric Models and Machine Learning Instruments

In this paper, we examine the effectiveness of various recommendationstrategies in the mobile channel . We find significant differences ineffectiveness among various recommendation strategies . Interestingly,recommendation strategies that directly embed social proofs for the recommendedalternatives outperform other recommendations . We also facilitate the estimation of causal effects in the presence of endogeneity using machine-learning methods .…

## An ecologically valid examination of event based and time based prospective memory using immersive virtual reality the effects of delay and task type on everyday prospective memory

Recent research has focused on assessing either event- or time-basedprospective memory (PM) using laboratory tasks . Yet, the findings pertaining to PM performance on laboratory tasks are often inconsistent with the findings on naturalistic experiments . The Virtual Reality Everyday Assessment Lab(VR-EAL) was implemented to comprehensively assess everyday PM(i.e.e.,…

## Everything is Relative Understanding Fairness with Optimal Transport

To study discrimination in automated decision-making systems, scholars have proposed several definitions of fairness, each expressing a different fairideal . We present an optimal transport-based approach to fairness that offers an interpretable andquantifiable exploration of bias and its structure by comparing a pair of outcomes to one another .…

## Byzantine Agreement with Unknown Participants and Failures

A set of mutually distrusting participants that want to agree on a common opinion must solve an instance of a Byzantine agreement problem . Most of the existingsolutions assume that the participants are aware of $n$ — the total number of participants in the system — and $f$ — an upper bound on the number ofByzantine participants .…

## GIST Distributed Training for Large Scale Graph Convolutional Networks

GIST is a hybrid layer and graphsampling method, which disjointly partitions the global model into several,smaller sub-GCNs that are independently trained across multiple GPUs in parallel . This distributed framework improves model performance and significantly decreases wall-clock training time . GIST seeks to enable large-scale GCN experimentation with the goal of bridging the existing gap inscale between graph machine learning and deep learning .…

## A Python Framework for Fast Modelling and Simulation of Cellular Nonlinear Networks and other Finite difference Time domain Systems

The simulator is designed as a Jupyter notebook written in Python and functionally tested and optimized to run on the freely available cloud platform Google Collaboratory . The simulator, in its actual form, is designed to model the FitzHugh Nagumo Reaction-Diffusion cellular nonlinearnetwork .…

## Stability and Resilience of Distributed Information Spreading in Aggregate Computing

Spreading information through a network of devices is a core activity formost distributed systems . Self-stabilizing algorithms implementinginformation spreading are one of the key building blocks enabling aggregatecomputing to provide resilient coordination in open complex distributedsystems . The ultimate bounds dependonly on the magnitude of the largest perturbation and the network diameter, and three design parameters trade off competing aspects of performance .…

## ALTO Adaptive Linearized Storage of Sparse Tensors

Real-world sparse tensors are challenging to process due to their irregular shapes and data distributions . We propose theAdaptive Linearized Tensor Order (ALTO) format . ALTO achieves a geometricmean speedup of 8X over the best mode-agnostic format, while delivering ageometric mean compression ratio of more than 4X relative to the bestmode-specific format .…

## Making an H Free Graph k Colorable

We study the question: How few edges can we delete from any$H$-free graph on $n$ vertices in order to make the resulting graph$k$-colorable? It turns out that various classical problems in extremal graphtheory are special cases of this question . We prove an upper bound when $H$ is a fixed clique that we conjecture istight up to a constant factor, and prove upper bounds for more general familiesof graphs .…

## Towards the k server conjecture A unifying potential pushing the frontier to the circle

The $k$-server conjecture, first posed by Manasse, McGeoch and Sleator in 1988, states that a deterministic deterministic algorithm for the $k$.-serverproblem exists . It is conjectured that the work function algorithm (WFA) achieves this guarantee, a multi-purpose algorithm with applications to variousonline problems .…

## Online Stochastic Max Weight Bipartite Matching Beyond Prophet Inequalities

We present a polynomial-time algorithm which approximates optimal onlinewithin a factor of $0.51$ beating the best-possible prophet inequality . In contrast, we show that it is PSPACE-hard to approximate this problem within some constant $\alpha< 1$ The problem was recently introduced by Ezra, Feldman, Gravin and Tang (EC'20), who gave a $1/2$-competitive algorithm for it . At thecore of our result are a new linear program formulation, an algorithm that tries to match the arriving vertices in two attempts, and an analysis that bounds the correlation resulting from the second attempts . This is the best possible ratio,as this problem is a generalization of the original single-item prophetinequality. This problem is the generalization, as this problem was a generalizing of the . problem is generalized of the old single- …