Ripple Simplified Large Scale Computation on Heterogeneous Architectures with Polymorphic Data Layout

Ripple library provides a unified view of the computational space across multiple dimensions and multiple GPUs . It allows polymorphic datalayout, and provides a simple graph interface to describe an algorithm fromwhich inter-GPU data transfers can be optimally scheduled . We describe the abstractions provided by Ripple to allow complex computations to be describedsimply, and to execute efficiently across many GPUs with minimal overhead .…

Verified Double Sided Auctions for Financial Markets

Double sided auctions are widely used in financial markets to match demand and supply . We extend notions of double sided auctions to incorporate multiple quantity trade requests . We establish new uniqueness theorems that enable automatic detection ofviolations in an exchange program by comparing its output with that of averified program .…

Ponzi Scheme Detection in EthereumTransaction Network

Paper mainly focuses on the Ponzi scheme, atypical fraud, which has caused large property damage to the users in Ethereum . It proposes a detecting model based on graph convolutionalnetwork (GCN) to precisely distinguishPonzi contracts . Experiments on differentreal-world . datasets demonstrate that our proposed model has promising results compared with .…

A Graph guided Multi round Retrieval Method for Conversational Open domain Question Answering

In recent years, conversational agents have provided a natural and convenient access to useful information in people’s daily life . The main challenge is how to well capture and fullyexplore the historical context in conversation to facilitate effectivelarge-scale retrieval . We propose a novel graph-guided retrieval method to model the relations amonganswers across conversation turns .…

A Surface Geometry Model for LiDAR Depth Completion

LiDAR depth completion is a task that predicts depth values for every pixel on the corresponding camera frame . Most of the existing state-of-the-art solutions are based on deepneural networks . In this letter, a novel non-learning depth completionmethod is proposed by exploiting the local surface geometry that is enhanced by an outlier removal algorithm .…

ASBERT Siamese and Triplet network embedding for open question answering

Answer selection (AS) is an essential subtask in the field of naturallanguage processing with an objective to identify the most likely answer to agiven question from a corpus containing candidate answer sentences . ASBERT is a framework built on the BERT architecture that uses Siamese and Triplet neural networks to learn an encoding function that maps a text to a fixed-size vector in an embedded space .…

CTU Depth Decision Algorithms for HEVC A Survey

High-Efficiency Video Coding (HEVC) surpasses its predecessors in encoding efficiency by introducing new coding tools at the cost of an increased encodingtime-complexity . The Coding Tree Unit (CTU) is the main building block used in HEVC . In the HEVC standard, frames are divided into CTUs with the predeterminedsize of up to 64×64 pixels .…

LAMPRET Layout Aware Multimodal PreTraining for Document Understanding

Document layout comprises both structural and visual (eg. font-sizes)information that is vital but often ignored by machine learning models . We propose a novel layout-aware multimodalhierarchical framework, LAMPreT, to model the blocks and the whole document . We evaluate the proposed model on twolayout-aware tasks — text block filling and image suggestion — and show the effectiveness of our proposed hierarchical architecture as well as pretrainingtechniques .…

IITP in COLIEE ICAIL 2019 Legal Information Retrieval usingBM25 and BERT

The Competition on Legal Information Extraction/Entailment (COLIEE-2019) run in association with the International Conference on Artificial Intelligence andLaw (ICAIL)-2019 has come up with few challenging tasks . We obtain encouraging results in all these four sub-tasks (i.e. Task1, Task2, Task3 and Task4), which will be able toprovide few automated systems to the judicial system .…

Labeling Schemes for Deterministic Radio Multi Broadcast

We consider the multi-broadcast problem in arbitrary connected radio networks . Each source node has a distinct piece of information that it wants to share with all nodes in the network . We set out todetermine the shortest possible labels so that the problem can be solveddeterministically in the labeled radio network by some universal deterministic algorithm .…

KazakhTTS An Open Source Kazakh Text to Speech Synthesis Dataset

This paper introduces a high-quality open-source speech synthesis dataset for Kazakh . The dataset consists of about 91 hours of transcribed audio recordings spoken by two professional speakers . It is the first publicly available large-scale dataset developed to promote Kazakh text-to-speech (TTS) applications in both academia and industry .…

MIMO Self attentive RNN Beamformer for Multi speaker Speech Separation

Recently, proposed recurrent neural network (RNN) based all deep learningminimum variance distortionless response (ADL-MVDR) beamformer method yielded superior performance over the conventional MVDR by replacing the matrixinversion and eigenvalue decomposition with two RNNs . Temporal-spatial self-attention module is proposed to better learn thebeamforming weights from the speech and noise spatial spatial spatial covariance matrices .…

Mixed Gibbs Sampling Detector in High Order Modulation Large Scale MIMO Systems

A neighborhood restricted Mixed Gibbs Sampling (MGS) based approach is proposed for low-complexity high-order modulation large-scale Multiple-Scale Multiple-InputMultiple-Output (LS-MIMO) detection . Numerical simulation results considering 64-QAM demonstrated that the proposed detectionmethod can substantially improve the MGS algorithm convergence, whereas noextra computational complexity per iteration is required .…

H_ infty Almost Output and Regulated Output Synchronization of Heterogeneous Multi agent Systems A Scale free Protocol Design

This paper studies scale-free protocol design for H_\infty almost output and regulated output synchronization of heterogeneous multi-agent systems . The collaborative linear protocol designs are based on localizedinformation exchange over the same communication network, which do not require knowledge of the directed network topology and spectrum of the associatedLaplacian matrix .…

Learning to Boost the Efficiency of Modern Code Review

Modern Code Review (MCR) is a standard in all kinds of organizations thatdevelop software . The goal of this thesis is to boost the efficiency of MCR by developing AI techniques that can partially replace or assist human reviewers . The envisioned techniques distinguish from existing MCR-related AImodels in that we interpret these challenges as graph-learning problems .…

Joint Beamforming Design for Multiuser MISO Downlink Aided by a Reconfigurable Intelligent Surfaces and a Relay

Reconfigurable intelligent surfaces (RIS) have drawn considerable attention due to their controllable scattering elements . RISs share somesimilarities with relays, but the two have fundamental differences impacting their performance . A multi-usercommunication system is proposed in this paper wherein a relay and an RIScooperate to improve performance in terms of energy efficiency .…

Comparison of remote experiments using crowdsourcing and laboratory experiments on speech intelligibility

Many subjective experiments have been performed to develop objective speechintelligibility measures . The novel coronavirus outbreak has made it verydifficult to conduct experiments in a laboratory . One solution is to performremote testing using crowdsourcing . Because we cannot control the listening conditions, it is unclear whether the results are entirely reliable .…

Fast mass lumped multiscale wave propagation modelling

In this paper, we investigate the use of a mass lumped fully explicit timestepping scheme for the discretisation of the wave equation with underlying material parameters that vary at arbitrarily fine scales . We prove that the methodverges with second order in the energy norm, with a leading constant that does not depend on the scales at which the material parameters vary .…

Models and Predictive Control for Nonplanar Vehicle Navigation

Aparametric surface is used to describe the nonplanar road which can describe a combination of curvature, bank and slope . We show that the proposedmodeling approach generalizes planar vehicle models that reference acenterline, such as the Frenet model . We use the proposed approach for vehicle path planning and following using model predictive control .…

A Timecop s Chase Around the Table

We consider the cops and robber game variant consisting of one cop and onerobber on time-varying graphs (TVG) The considered TVGs are edge periodicgraphs, i.e., for each edge, a binary string $s_e$ determines in which timestep the edge is present .…

Towards Fortifying the Multi Factor Based Online Account Ecosystem

Chain Reaction Attack exploits weakest point in Online Account Ecosystem . Vulnerability stems from defective multi-factor authentication (MFA), specifically the ones with SMS-based verification, and dependencies among accounts on different platforms . We propose countermeasures including the online account exposedinformation protection mechanism and the built-in authentication to fortify thesecurity of Online Account ecurity of Online Accounts and proposes feasible countermeasures .…

SoK Design Tools for Side Channel Aware Implementions

Traditional approaches for leakage detection measure the physical properties of the device and fail to provide root cause analysis . An alternative approach that is gaining traction is to automate leakage detection by modeling the device . We survey the proposed tools to determine the current knowledge levelacross the domain and identify open problems .…

Machine learning assisted surrogate construction for full core fuel performance analysis

Accurately predicting the behavior of a nuclear reactor requires multiphysicssimulation of coupled neutronics, thermal-hydraulics and fuel thermo-mechanics . This work presents methodologies forfull-core surrogate construction based on several realistic equilibrium PWRcore designs . It also sets stage for full-core fuelperformance analysis with BISON where the computational cost becomes moreburdensome.…

High Quality Automated Program Repair

Automatic program repair (APR) has recently gained attention because it proposes to fix software defects with no human intervention . While APR tools can produce patches that appear to fix the defect for 11-19% of the defects in real-world software, most of the patches produced are not correct or acceptable to developers because they overfit to the tests used during the repair process .…

Reinforced Neighborhood Selection Guided Multi Relational Graph Neural Networks

Graph Neural Networks have been widely used for the representationlearning of various structured graph data . RioGNN can learn more discriminative node embedding with enhanced explainability due to therecognition of individual importance of each relation via the filteringthreshold mechanism . A reinforced relation-awareneighbor selection mechanism is developed to choose the most similar neighborsof a targeting node within a relation before aggregating all neighborhood information from different relations to obtain the eventual node embeding .…

Exploring software developers work practices Task differences participation engagement and speed of task resolution

An increasing number of studies have sought to understand the processes enacted during software development . These explorations would reveal how team processes occur during all softwaredevelopment efforts . The outcomes suggest that behavioral and intrinsic issues mayinteract with extrinsic factors becoming significant predictors of the speed ofsoftware task resolution .…

Learning Feature Interactions With and Without Specifications

Features in product lines and highly configurable systems can interact in ways contrary to developers’ intent . Current methods to identify suchunanticipated feature interactions are costly and inadequate . The contribution of the paper is to use program analysis to extract feature-relevant learning models from the source code in order to detectunwanted feature interactions .…

Flexible Educational Software Architecture

EAs.LiT is an e-assessment management and analysis software for whichcontextual requirements and usage scenarios changed over time . We consider the microservicearchitecture productive and recommend it for usage in other educational projects . This architectural styleand a few adopted technologies, like RDF as a data format, enabled an eased implementation of various use cases .…