R2LIVE A Robust Real time LiDAR Inertial Visual tightly coupled state Estimator and mapping

In this letter, we propose a robust, real-time tightly-coupled multi-sensor fusion framework, which fuses measurement from LiDAR, inertial sensor, and visual camera to achieve robust and accurate state estimation . The algorithm is robust enough to run inreal-time on an on-board computation platform, as shown by extensive experiments conducted in indoor, outdoor, and mixed environment of different scale .…

Analyzing Confidentiality and Privacy Concerns Insights from Android Issue Logs

Post-release user feedback plays an integral role in improving software quality and informing new features . Confidentiality and privacy concernsvaried in severity, and were most prevalent over Jelly Bean releases . Community users also expressed divergent preferences for new security features, ranging from more relaxed to very strict .…

Practitioners Perceptions of the Goals and Visual Explanations of Defect Prediction Models

Software defect prediction models are classifiers that are constructed from historical software data . LIME is the most preferred technique for understanding the mostimportant characteristics that contributed to a prediction of a file, while ANOVA/VarImp is the second most preferred techniques .…

An Aligned Rank Transform Procedure for Multifactor Contrast Tests

The Aligned Rank Transform(ART) is a popular nonparametric analysis technique that can find main andinteraction effects in nonconforming data . We created a new algorithm called ART-C forconducting contrasts within the ART paradigm and validated it on 72,000 datasets . We also extended a tool called ARTool with our new algorithm for both Windows and R .…

Re Evaluating GermEval17 Using German Pre Trained Language Models

The lack of a commonly used benchmark data set for evaluation of non-Englishpre-trained language models is a severe shortcoming of current English-centric NLP-research . We evaluate the performance of the German andmultilingual BERT-based models currently available via the huggingfacetransformers library on the four tasks of the GermEval17 workshop .…

Triplet loss based embeddings for forensic speaker identification in Spanish

Forensic speaker identification has been looking to shed light on the problem by quantifying how much a speech recording belongs to a particularperson in relation to a population . In this work, we explore the use of speechembeddings obtained by training a CNN using the triplet loss .…

Learning to Shift Attention for Motion Generation

One challenge of motion generation using robot learning from demonstrationtechniques is that human demonstrations follow a distribution with multiplemodes for one task query . Previous approaches fail to capture all modes or tend to average modes of the demonstrations and thus generate invalid trajectories .…

Explaining Safety Failures in NetKAT

This work introduces a concept of explanations with respect to the violation of safe behaviours within software defined networks . In our setting, a safe behaviour is characterised by aNetKAT policy, or program, which does not enable forwarding packets from aningress i to an undesirable egress e .…

Multichannel LSTM CNN for Telugu Technical Domain Identification

Domain Identification plays a significant role in Machine Translation, Text Summarization, Question Answering,Information Extraction, and Sentiment Analysis . System got 69.9% of the F1score on the test dataset and 90.01% on the validation set . This architecture was used and evaluated in the context of the ICONshared task TechDOfication 2020 (task h) Thematic keywords give a compressedrepresentation of the text, and usually, Domain Identification is used in machine translation .…

Measuring HTTP 3 Adoption and Performance

The third version of the Hypertext Transfer Protocol (HTTP) is currently in its final standardization phase by the IETF . Besides better security and increased flexibility, it promises benefits in terms of performance . We run a large-scalemeasurement campaign toward thousands of websites adopting HTTP/3, aiming at understanding to what extent it achieves better performance than HTTP/2 .…

Equal Affection or Random Selection the Quality of Subjective Feedback from a Group Perspective

In the setting where a group of agents is asked a single subjectivemulti-choice question (e.g. which one do you prefer? cat or dog?), we are interested in evaluating the quality of the collected feedback . We assume that informativerespondents’ predictions strongly depend on their own choices while uninformative respondents’ do not .…

Designing zonal based flexible bus services under stochatic demand

In this paper, we develop a zonal-based flexible bus services (ZBFBS) by considering both passenger demands spatial (origin-destination or OD) and volume stochastic variations . Service requests are grouped by zonal OD pairsand number of passengers per request, and aggregated into demand categories .…

Sparse online variational Bayesian regression

This work considers variational Bayesian inference as an inexpensive and scalable alternative to a fully Bayesian approach in the context ofsparsity-promoting priors . For linear modelsthe method requires only the iterative solution of deterministic least squaresproblems . For large p an approximation is able toachieve promising results for a cost of O(p) in both computation and memory .…

A Trident Quaternion Framework for Inertial based Navigation Part II Error Models and Application to Initial Alignment

This work deals with error models for trident quaternion framework proposed in companion paper “A Trident Quaternion Framework for Inertial-basedNavigation Part I: Motion Representation and Computation” It further uses them to investigate the static and in-motion alignment for land vehicles .…

A Survey on Consortium Blockchain Consensus Mechanisms

Consensus algorithm is an agreement to validate the correctness of blockchain transactions . Unlike a public blockchain, a consortium blockchain does not contend with the issues of creating a resource-savingglobal consensus protocol . This paper presents the mechanisms of these and other consensus protocols, and analyzes and compares their advantages and drawbacks .…

The non positive circuit weight problem in parametric graphs a fast solution based on dioid theory

In this paper, we design an algorithm thatsolves the Non-positive Circuit weight Problem (NCP) on this class ofparametric graphs . The proposed algorithm isbased on max-plus algebra and formal languages and runs faster than otherexisting approaches . It achieves strongly polynomial time complexity$\mathcal{O}(n^4)$ (where $n$ is the number of nodes in the graph) The proposed algorithms are based on max plus algebra, and run faster than existing approaches .…

Density Sketches for Sampling and Estimation

We introduce Density sketches (DS) as a succinct online summary of the datadistribution . DS can accurately estimate point wise probability density . DS also provides a capability to sample unseen novel data from the underlying data distribution . DS construction is an online algorithm.…

Hero On the Chaos When PATH Meets Modules

The heterogeneous use of library-referencing modes across Golang projects has caused numerous dependency management issues, incurring reference inconsistencies and even build failures . We reported 280 issues, among which 181 (64.6\%) issues have been confirmed, and 160 of them (88.4\%) have been fixed or areunder fixing .…

Facilitating Asynchronous Participatory Design of Open Source Software Bringing End Users into the Loop

As open source software (OSS) becomes increasingly mature and popular, thereare significant challenges with properly accounting for usability concerns for the diverse end users . This work paves the road for future studies about tool design that would eventually help improve OSS usability .…

Towards Optimized Distributed Multi Robot Printing An Algorithmic Approach

This paper presents a distributed multi-robot printing method which utilizes an optimization approach to decompose and allocate a printing task to a group of mobile robots . The motivation for this problem is to minimize the printingtime of the robots by using an appropriate task decomposition algorithm .…

NLRG at SemEval 2021 Task 5 Toxic Spans Detection Leveraging BERT based Token Classification and Span Prediction Techniques

In SemEval-2021 Task-5 Toxic Spans Detection, the focus is on detecting toxicspans within passages . We use BERT-based models — BERT, RoBERTa, and SpanBERT for both approaches . We investigate results on four hybrid approaches — Multi-Span, Span+Token, LSTM-CRF, and a combinationof predicted offsets using union/intersection .…

The Logical Options Framework

Logical Options Framework (LOF) learns policies that are satisfying, optimal, and composable . LOF efficiently learns policies thatsatisfy tasks by representing the task as an automaton and integrating it into learning and planning . We evaluate LOF on four tasks in discrete and continuous domains, including a 3D pick-and-place environment .…

An Iterative Approach to Finding Global Solutions of AC Optimal Power Flow Problems

The existence of multiple solutions to AC optimal power flow (ACOPF) problems has been noted for decades . Existing solvers are generally successful infinding local solutions, which are stationary points but may not be globallyoptimal . In this paper, we propose a simple iterative approach to find globally optimal solutions for ACOPF problems .…

A Computation Offloading Model over Collaborative Cloud Edge Networks with Optimal Transport Theory

As novel applications spring up in future network scenarios, the requirements on network service capabilities for differentiated services or burst servicesare diverse . Migrating computing tasks to the edge and cloudfor computing requires a comprehensive consideration of energy consumption, bandwidth, and delay .…

With the popularity of online access in virtual reality (VR) devices, it will become important to investigate exclusive and interactive CAPTCHA designs for VR devices . In this paper, we present four traditional two-dimensional (2D) CAPTCHAs in VR . Then, based on the three-dimensional interactioncharacteristics of VR devices, we propose two vrCAPTCHA design prototypes .…

Combining Off and On Policy Training in Model Based Reinforcement Learning

Deep learning and Monte Carlo Tree Search (MCTS) has shownto be effective in various domains, such as board and video games . MuZero demonstrated that it is possible to masterboth Atari games and board games by directly learning a model of theenvironment .…

Modelling a CubeSat based Space Mission and its Operation

Model Based approaches are trying to help inthese problems as they help software developers along the last years . With more than 1000 CubeSats launched they still achieve less than 50% rate of successful missions and that is causedmainly by poor V&V processes .…

Rigid and non rigid motion compensation in weight bearing cone beam CT of the knee using noisy inertial measurements

Involuntary subject motion is the main source of artifacts in weight-bearingcone-beam CT of the knee . To achieve image quality for clinical diagnosis, themotion needs to be compensated . We propose to use inertial measurement units(IMUs) attached to the leg for motion estimation .…

A Trident Quaternion Framework for Inertial based Navigation Part I Rigid Motion Representation and Computation

Strapdown inertial navigation research involves the parameterization andcomputation of the attitude, velocity and position of a rigid body in a chosen reference frame . This paper proposes a compact andelegant representation of the body’s attitude, position and velocity . Thekinematics of strapdown INS are cohesively unified in one concise differentialequation .…

Contingency Model Predictive Control for Linear Time Varying Systems

Contingency Model Predictive Control (CMPC) anticipates emergency and keeps the controlled system in asafe state that is selectively robust to the identified hazard . This article presents a linear formulation for CMPC, illustrates its keyfeatures on a toy problem, and then demonstrates its efficacy experimentally on a full-size automated road vehicle that encounters a realistic pop-outobstacle .…

The rich still get richer Empirical comparison of preferential attachment via linking statistics in Bitcoin and Ethereum

Bitcoin and Ethereum transactions present one of the largest real-world complex networks that are publicly available for study . Preference attachment continues to be a key factor in the evolution of both the Bitcoin and . Ethereum, the second most important cryptocurrency, continues to evolve, authors say .…

Scaling Distributed Ledgers and Privacy Preserving Applications

This thesis proposes techniques aiming to make blockchain technologies andsmart contract platforms practical by improving their scalability, latency, andprivacy . This thesis starts by presenting the design and implementation ofChainspace, a distributed ledger that supports user defined smart contracts and executes user-supplied transactions .…

Revisit Recommender System in the Permutation Prospective

Recommender systems (RS) work effective at alleviating information overloadand matching user interests in various web-scale applications . Most RS retrieve the user’s favorite candidates and then rank them by the rating scores in thegreedy manner . We propose a novel permutation-wise framework PRS in there-ranking stage of RS, which consists of Permutation-Matching (PMatch) and PRank) stages successively .…

No Regret Algorithms for Private Gaussian Process Bandit Optimization

The widespread proliferation of data-driven decision-making has ushered in interest in the design of privacy-preserving algorithms . We propose a solution for differentially private GP bandit optimization that combines a uniform kernelapproximator with random perturbations . For twospecific DP settings – joint and local differential privacy, we provide algorithms based on efficient quadrature Fourier feature approximators that are computationally efficient and provably no-regret for popular stationary kernel functions .…

Property Business Classification Model Based on Indonesia E Commerce Data

Indonesia’s e-commerce property business has positive trend shown by increasing sales of more than 500% from 2011 to 2015 . Data is easily obtained, there are many open data from E-commerce sites . People regularly visit the site to find the right property or to sell the property using price information which collectively available as opendata .…

Long term IaaS Provider Selection using Short term Trial Experience

We propose a novel approach to select privacy-sensitive IaaS providers for along-term period . The proposed approach leverages a consumer’s short-term trialexperiences for long-term selection . We design a novel equivalence partitioningbased trial strategy to discover the temporal and unknown QoS performancevariability of an IAAS provider .…

Deep Reinforcement Learning for Safe Landing Site Selection with Concurrent Consideration of Divert Maneuvers

This research proposes a new integrated framework for identifying safelanding locations and planning in-flight divert maneuvers . The proposed framework wasable to achieve 94.8% of successful landing in highly challenging landingsites where over 80$\%$ of the area around the initial target lading point ishazardous, by effectively updating the target landing site and feedback controlgain during descent .…

Memory based Deep Reinforcement Learning for POMDP

A promising characteristic of Deep Reinforcement Learning (DRL) is itsability to learn optimal policy in an end-to-end manner without relying on feature engineering . Most approaches assume a fully observable statespace, i.e. fully observable Markov Decision Process (MDP) In real-worldrobotics, this assumption is unpractical, because of sensor issues such assensors’ capacity limitation and sensor noise .…

LRG at SemEval 2021 Task 4 Improving Reading Comprehension with Abstract Words using Augmentation Linguistic Features and Voting

SemEval-2021 Task-4: Reading Comprehension of Abstract Meaning . Given a fill-in-the-blank-type question and a corresponding context, the task is to predict the most suitableword from a list of 5 options . We use encoders of transformers-based models pre-trained on themasked language modelling (MLM) task .…

Parameterized Temperature Scaling for Boosting the Expressive Power in Post Hoc Uncertainty Calibration

Standard deepneural networks typically yield uncalibrated predictions, which can be betransformed into confidence scores using post-hoc calibration methods . We address the problem of uncertainty calibration and introduce a novel method, Parametrized Temperature Scaling (PTS) We show that our novel accuracy-preserving approach consistently outperforms existing algorithms across a large number of modelarchitectures, datasets and metrics .…

Multiplicative Reweighting for Robust Neural Network Optimization

Deep neural networks suffer from degraded performance in the presence of noisy labels at traintime or adversarial examples during inference . Multiplicative weights updates (MW) updates were recently shown to be robust to moderate adversarial corruptions . MW improves network’s accuracy in the .…

GPU aware Communication with UCX in Parallel Programming Models Charm MPI and Python

We demonstrate the capability of the Unified Communication X (UCX)framework to compose a GPU-aware communication layer that serves multiple parallel programming models developed out of the Charm++ ecosystem . We observe increasesin bandwidth of up to 9.6x in Charm++, 10x in AMPI, and 10.5X in Charm4py .…

How Can Human Values Be Addressed in Agile Methods A Case Study on SAFe

Human values are what an individual or a society considers important in life . Ignoring these human values in software can pose difficulties or risks for all stakeholders . Agile methods are predominantly focused on delivering business values . Study suggests new and exclusive values-based artefacts(e.g.,…

Symmetric distinguishability as a quantum resource

We develop a resource theory of symmetric distinguishability . We study the resource theory for two different classes of free operations . The optimal rate of converting oneelementary source to another is equal to the ratio of their quantum Chernoff divergences .…

Thoughts on the potential to compensate a hearing loss in noise

The effect of hearing impairment on speech perception was described by Plomp(1978) as a sum of a loss of class A, due to signal attenuation, and class D, which severely limits the benefit of hearing aids in noisy listening conditions .…

Adversarial Robustness with Non uniform Perturbations

Robustness of machine learning models is critical for security related applications . We propose using characteristics of the empirical datadistribution, both on correlations between the features and the importance of the features themselves . The key idea of our proposed approach is to enable non-uniformperturbations that can adequately represent these feature dependencies during training .…

Convergence in the maximum norm of ADI type methods for parabolic problems

Results on unconditional convergence in the Maximum norm for ADI-typemethods are quite difficult to get, mainly when thenumber of space dimensions $m$ is greater than two . Such a result is obtained under quite general conditions on the PDE problem in case that Dirichlet boundary conditions are imposed .…

Lossless Compression of Efficient Private Local Randomizers

Locally Differentially Private (LDP) Reports are commonly used for collection of statistics and machine learning in the federated setting . LDP reports are known to have relatively little information about the user’s data due to randomization . Several schemes are known that exploit this fact to design low-communication versions of LDP algorithms but all of them do so at the expense of a significant loss in utility .…

Frequency Dynamics with Grid Forming Inverters A New Stability Paradigm

Traditional power system frequency dynamics are driven by Newtonian physics,where a synchronous generator (SG), the historical primary source of power,follows a deceleration frequency trajectory upon power imbalances . Subsequent to a disturbance, an SG will modifypre-converter, mechanical power as a function of frequency .…

SocialNLP EmotionGIF 2020 Challenge Overview Predicting Reaction GIF Categories on Social Media

EmotionGIF2020 Challenge was held at the 8th International Workshop on Natural Language Processing for Social Media . The challenge required predictingaffective reactions to online texts . The novel dataset included 40Ktweets with their reaction GIFs . A total of 84 teams registered for the task .…