## 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 .…

## 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.…

## 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 .…

## 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 .…

## 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 .…

## 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.,…

## 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 .…

## 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 .…

## 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 .…

## 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 .…

## GenFloor Interactive Generative Space Layout System via Encoded Tree Graphs

Automated floorplanning or space layout planning has been a long-standing NP-hard problem in the field of computer-aided design . GenFloor is an interactive design system that takesgeometrical, topological, and performance goals and constraints as input and provides optimized spatial design solutions as output .…

## 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 .…

## 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 .…

## 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 .…

## 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 unbiased ray marching transmittance estimator

We present an in-depth analysis of the sources of variance in unbiased volumetric transmittance estimators . We also propose new methods for improving their efficiency . These combine to produce asingle estimator that is universally optimal relative to prior work, with up toseveral orders of magnitude lower variance at the same cost, and has zerovariance for any ray with non-varying extinction .…

## 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- …

## Learning to Persuade on the Fly Robustness Against Ignorance

We study a repeated persuasion setting between a sender and a receiver . The sender does not know the prior, and has to persuade while gradually learning the prior on the fly . We study the sender’s learning problem of making persuasive action recommendations to achieve low regret against the optimal persuasion mechanism .…

## 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 .…

## All Chalcogenide Programmable All Optical Deep Neural Networks

All-optical neural networkswithout any electro-optic conversions could alleviate these shortcomings . Optical neural networks that bypass electrooptic conversionaltogether hold promise for network-edge machine learning applications such as for autonomous vehicles ornavigation systems such as signal pre-processing of LIDAR systems . We show how the structural phasetransitions in a wide-bandgap phase-change material enables storing the neuralnetwork weights via non-volatile photonic memory, whilst resonant bonddestabilisation is used as a nonlinear activation threshold without changing the material .…

Mechanism design has traditionally assumed that the set of participants are fixed and known to the mechanism (the market owner) in advance . However, in practice, the market owner can only directly reach a small number of participants (her neighbours) The owner often needs costly promotions to recruit more participants in order to get desirable outcomes such as social welfare or revenue maximization .…

## Simplest Non Regular Deterministic Context Free Language

A problem is C-simpleif it can be reduced to each problem in C . This can be viewed as a conceptualcounterpart to C-hard problems to which all problems in C reduce . Our concreteexample is the class of non-regular deterministic deterministic context-free languages(DCFL’), with a truth-table reduction by Mealy machines .…

## Sim Env Decoupling OpenAI Gym Environments from Simulation Models

Reinforcement learning (RL) is one of the most active fields of AI research . Despite interest demonstrated by the research community in reinforcementlearning, the development methodology still lags behind . The Sim-Env Pythonlibrary generates OpenAI-Gym-compatible reinforcement learning environmentsthat use existing or purposely created domain models as their simulationback-ends .…

## Tuning as a Means of Assessing the Benefits of New Ideas in Interplay with Existing Algorithmic Modules

New algorithmic ideas are a key part of the continuous improvement of existing optimization algorithms . When introducing a new component into an algorithm, assessing its potential benefits is a challenging task . Often, the component is added to a default implementation of the underlying algorithm and compared against a limited set of other variants .…

## Clarification of Video Retrieval Query Results by the Automated Insertion of Supporting Shots

Computational Video Editing Systems output video generally follows aparticular form, e.g. conversation or music videos, in this way they are domainspecific . We describe a recent development in our video annotation and segmentation system to support general computational video editing in which wederive a single generic editing strategy from general cinema narrativeprinciples instead of using a hierarchical film gram-mar .…

## Crowbar Behavioral Symbolic Execution for Deductive Verification of Active Objects

Crowbar is a deductive verification system for the ABSlanguage . Crowbar models distributed systems with the Active Object concurrencymodel . Each method issymbolically executed, but specification and prior static analyses influencethe shape of the symbolic execution tree . User interaction is realized throughguided counterexamples, which present failed proof branches in terms of the input program.…

## MHDeep Mental Health Disorder Detection System based on Body Area and Deep Neural Networks

Mental health problems impact quality of life of millions of people around the world . Diagnosis of mental health disorders is a challenging problem that often relies on self-reporting by patients . MHDeep uses body-area networks consisting of aplethora of accurate sensors embedded in smartwatches and smartphones and deepneural networks (DNNs) points towards a possible solution .…

## 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 .…

## FM 2 Field matrixed Factorization Machines for Recommender Systems

Click-through rate (CTR) prediction plays a critical role in recommendersystems and online advertising . Fieldinformation is proved to be important and there are several works consideringfields in their models . In this paper, we proposed a novel approach to model the field information effectively and efficiently .…

## Automatic Programming Through Combinatorial Evolution

Only a few iterations seem to be required to already achieve complex objects . Computers generate computer programs of increasing complexity through combinatorial evolution . Combinatorial evolution seems to be a promising approach for automatic programming, authors say . We found that reserved key words of a programming language are suitable for defining the basic code blocks at the beginning of the simulation.…

## Making a Case for Federated Learning in the Internet of Vehicles and Intelligent Transportation Systems

With the introduction of 5G networks and the advancement of intechnologies, new and emerging networking technologies and use cases are takingshape . Federated Learning, a collaborative and distributed intelligence technique, is suggested . With the ability of a federated model deployed on roadside infrastructure throughout the network, leveraging group intelligence while reducing recoverytime and restoring acceptable system performance is highlighted .…

## Merly jl Web Framework in Julia

Merly.jl is a package for creating web applications in Julia . It presents a familiar syntax with the rest of the most popular web frameworks without neglecting the execution performance . This manuscript mentions the operation and main features of the main feature of the package .…

## TransMask A Compact and Fast Speech Separation Model Based on Transformer

Speech separation is an important problem in speech processing, which targetsto separate and generate clean speech from a mixed audio containing speech from different speakers . By fully un-leashing the power of self-attention on long-term dependency exception, we demonstrate the size of TransMask is morethan 60% smaller and the inference is more than 2 times faster than state-of-the-art solutions .…

## A unified construction of all speed HLL type schemes for hypersonic heating computations

In this paper, a unified framework to develop all-speed HLL-type schemes forhypersonic heating computations is constructed . Such a unified constructionmethod combines two effective improving techniques: a shock robustnessimprovement and a low-Mach number fix . It is implemented by modifying the approximate solutions of the local Riemann problem in the HLL framework .…

## The Accented English Speech Recognition Challenge 2020 Open Datasets Tracks Baselines Results and Methods

AESRC2020 is designed for providing a common testbed and promoting accent-related research . 160 hours of accented English speech collected from 8 countries is released with labels as the training set . 20 hours of speech without labels is later released as the test set .…

## CyberSecurity Challenges Serious Games for Awareness Training in Industrial Environments

New serious gamedesigned for software developers in the industry . Game addresses softwaredevelopers’ needs and is well suited for raising secure codingawareness of software developers . Awareness of cybersecurity topics, e.g., related to secure coding guidelines, is vital inindustrial environments for the products and services in criticalinfrastructures .…

## FLACK Counterexample Guided Fault Localization for Alloy Models

FLACK is a tool that takes as input an Alloy model consisting of some violated assertion . It returns a ranked list of suspicious expressions contributing to the assertion violation . The tool is efficient (can handle complex, real-world Alloymodels with thousand lines of code within 5 seconds) FLACK can be useful (can often narrow down the error to the exact location within the suspicious expressions).…

## A theory of capacity and sparse neural encoding

We study sparse neural maps from an input layer to a target layer with sparse activity . We mathematically prove that $K$ undergoes a phase transition and that sparsity inthe target layers increases the storage capacity of the map . The target vectors can be chosen arbitrarily, including in random fashion, and the memories can be encoded and decoded by networks trained using local learning rules .…

## Raising Security Awareness using Cybersecurity Challenges in Embedded Programming Courses

Security bugs are errors in code that, when exploited, can lead to serious software vulnerabilities . These bugs could allow an attacker to take over an application and steal information . The Sifu platform was developed in the industry with the aim to raise software developers’ awareness of secure coding .…

## DemSelf a Mobile App for Self Administered Touch Based Cognitive Screening Participatory Design With Stakeholders

DemSelf was developed by adapting an examiner-administered paper-based instrument, the Quick Mild Cognitive Impairment (Qmci) screen . We conducted fivesemi-structured expert interviews including a think-aloud phase to evaluateusability problems . Participants identified usability issues in all components of the DemSelf prototype .…

## Towards Teachable Conversational Agents

The traditional process of building interactive machine learning systems can be viewed as a teacher-learner interaction scenario . In this work, we explore the idea of using a conversational interface to investigate the interaction between human-teachers and interactive machine-learners . Results validate the concept of teachable AI agents and highlight the factors relevant for the development of machine-learning systems that intend to learn from conversational interactions, such as human-learning algorithms .…

## Singer Identification Using Deep Timbre Feature Learning with KNN Net

In this paper, we study the issue of automatic singer identification (SID) in popular music recordings . The main challenge for this investigation lies in the fact that asinger’s singing voice changes and intertwines with the signal of backgroundaccompaniment in time domain .…

## CDA a Cost Efficient Content based Multilingual Web Document Aligner

Content-based Document Alignment approach (CDA) works in two steps: projecting documents of a web domain to a shared multilingual space; then aligning them based on thesimilarity of their representations in such space . CDA achieves performance comparable with state-of-the-art systems in the WMT-16 BilingualDocument Alignment Shared Task benchmark .…

## Design Patterns for Blockchain Based Payment Applications

Blockchain technology facilitates fast, secure, and cross-border payments without the need for intermediaries such as banks . As the killer application of blockchain technology, blockchain-based payments have attracted extensive attention ranging from hobbyists to corporates toregulatory bodies . We present 15 design patterns that cover critical aspects in enabling the state transitions of a token in blockchain-related payment applications .…

## On the Similarity between von Neumann Graph Entropy and Structural Information Interpretation Computation and Applications

The von Neumann graph entropy is a measure of graph complexity based on theLaplacian spectrum . It has recently found applications in various learning tasks driven by networked data . However, it is computational demanding and hard to interpret using simple structural patterns .…

## Kokkos Kernels Performance Portable Sparse Dense Linear Algebra and Graph Kernels

Kokkos Kernels is a library of kernels that serve the needs of several CSE applications and software frameworks . Wedescribe the design principles of such a library and demonstrate portableperformance of the library using some selected kernels . Specifically, wedemonstrate the performance of four sparse kernels, three dense batchedkernels, two graph kernels and one team level algorithm.…

## Principled Simplicial Neural Networks for Trajectory Prediction

We consider the construction of neural network architectures for data onsimplicial complexes . In studying maps on the chain complex of a simplicialcomplex, we define three desirable properties of a neural networkarchitecture . The last property encodes the desirable feature that the output of the neural network depends on the entire simplicial complex and not on a subset of its dimensions .…

## SEPAL Towards a Large scale Analysis of SEAndroid Policy Customization

SEPAL applies the NLP technique and employs and trains awide&deep model to quickly and precisely predict whether one rule isunregulated or not . SEPAAL outperforms the state-art approach (i.e.,EASEAndroid) by 15% accuracy rate on average . We further discover the policycustomization problem is getting worse in newer Android versions (e.g.,…

## Random Walks with Erasure Diversifying Personalized Recommendations on Social and Information Networks

Most existing personalization systems promote items that match a user’s previous choices or those that are popular among similar users . This results in recommendations that are highly similar to the ones users are already exposed to, resulting in their isolation inside familiar but insulated informationsilos .…

## Characterizing and Mitigating Self Admitted Build Debt

Technical Debt is a metaphor used to describe the situation in which code quality is traded for short-term goals in software projects . In recent years, the concept of self-admitted technical debt (SATD) was proposed, which focuses on debt that is intentionally introduced and described bydevelopers .…