## Post Quantum Succinct Arguments

We prove that Kilian’s four-message succinct argument system is post-quantumsecure in the standard model . At the heart of our proof is a new “measure-and-repair” quantum rewinding procedure that achieves asymptotically optimal knowledge error .…

## Beyond Image to Depth Improving Depth Prediction using Echoes

We address the problem of estimating depth with multi modal audio visual data . Inspired by the ability of animals, such as bats and dolphins, to infer distance of objects with echolocation, some recent methods have utilized echoes for depth estimation .…

## Machine Learning for Nondestructive Wear Assessment in Large Internal Combustion Engines

Existing state-of-the-art methods for quantifying wear require disassembly and cutting of the examined liner . Adeep-learning framework is proposed that allows computation of the surface-representing bearing load curves from reflection RGB images of the liner surface that can be collected with a simple handheld device .…

## Compositional Security for Reentrant Applications

We do not know how to write code that is secure in composition with malicious code . We formalize a generaldefinition of reentrancy and introduce a security condition that allows modules like smart contracts to protect their key invariants . We present a security type system that provably enforces secure information flow .…

## Take a Bite of the Reality Sandwich Revisiting the Security of Progressive Message Authentication Codes

Message authentication guarantees the integrity of messages exchanged overuntrusted channels . However, the required per-message authentication tagsconsiderably expand packet sizes . We propose R2-D2, which relies on (i)optimal message dependencies, (ii) parametrizable security guarantees, (iii)randomized bit dependencies, and (iv) optional immediate protection bits to address this problem .…

## Crossing the Tepper Line An Emerging Ontology for Describing the Dynamic Sociality of Embodied AI

Artificial intelligences are increasingly being embodied and embedded inthe world to carry out tasks and support decision-making with and for people . We define this as the state thatembodied AI “circumstantially” take on within interactive contexts when perceived as both social and agentic by people.…

## Multi party Private Set Operations with an External Decider

A Private Set Operation (PSO) protocol involves at least two parties with their private input sets . The goal of the protocol is for the parties to learnt the output of a set operation, i.e. set intersection, on their input sets, without revealing any information about the items that are not in the outputset .…

## Lasry Lions Envelopes and Nonconvex Optimization A Homotopy Approach

In large-scale optimization, the presence of nonsmooth and nonconvex terms in a given problem typically makes it hard to solve . Lasry-Lions double envelopes are an extension of the Moreau ones but exhibit an additionalsmoothness property that makes them amenable to fast optimization algorithms .…

## Beyond ANN Exploiting Structural Knowledge for Efficient Place Recognition

Many approaches in the literature perform computationally inefficient full image comparisons between queries and all database images . In this paper, we propose a novel fast sequence-based method for efficient place recognition that can be applied online . It uses relocalization to recover from sequence losses, and exploits usually available but often unused intra-database similarities for potential detection of all matching database images for each query in case of loops or stops in the database .…

## Knowledge driven Description Synthesis for Floor Plan Interpretation

Image captioning is a widely known problem in the area of AI . Captiongeneration from floor plan images has applications in indoor path planning,real estate, and providing architectural solutions . The two models take advantage of modern deep neural networks for visual feature extraction and textgeneration .…

## I Nema A Biological Image Dataset for Nematode Recognition

Nematode worms are one of most abundant metazoan groups on the earth,occupying diverse ecological niches . Accurate recognition or identification of Nematodes is of great importance for pest control, soil ecology and soil ecology . We propose animage dataset consisting of diverse nematodes (both laboratory cultured andnaturally isolated), which, to our knowledge, is the first time in the community .…

## Automatically Lock Your Neural Networks When You re Away

The smartphone and laptop can be unlocked by face or fingerprint recognition, while neural networks which confront numerous requests every day have littlecapability to distinguish between untrustworthy and credible users . In this paper, we propose Model-Lock (M-LOCK) to realize an end-to-endneural network with local dynamic access control, which is similar to the automatic locking function of the smartphone to prevent malicious attackers from obtaining available performance actively when you are away .…

## Sent2Matrix Folding Character Sequences in Serpentine Manifolds for Two Dimensional Sentence

We study text representation methods using deep models . We propose to convert texts into 2-D representations and develop the Sent2Matrix method . Our method allows for the explicit incorporation of both word morphologies and boundaries . This method is the first attempt to represent texts in 2D formats .…

## BLOFF A Blockchain based Forensic Model in IoT

Cybercriminals of today have the tools and the technology to deploy millions of sophisticated attacks . Digital forensics comes into play, but it is not easy to conduct a forensic investigation in IoT systems because of the heterogeneous nature of the IoT environment .…

## Multi view Subword Regularization

Multilingual pretrained representations generally rely on subwordsegmentation algorithms to create a shared multilingual vocabulary . Standard heuristic algorithms often lead to sub-optimal segmentation, especially for languages with limited amounts of data . We propose Multi-view Subword Subword Regularization (MVR), a method that enforces the consistencybetween predictions of using inputs tokenized by the standard and probabilisticsegmentations .…

## Which K Space Sampling Schemes is good for Motion Artifact Detection in Magnetic Resonance Imaging

Motion artifacts are a common occurrence in the Magnetic Resonance Imaging(MRI) exam . Motion artifacts in MRI have a complex nature and it is related to the k-space sampling scheme . Cartesian samplers, on the otherhand, are the best in terms of deep learning motion detection because they can better reflect motion .…

## GRIHA Synthesizing 2 Dimensional Building Layouts from Images Captured using a Smart Phone

Most existing methods either use RGB-D images, requiring a depth camera, or depending on panoramic photos, assuming that there is little to no occlusion in the rooms . In this work, we proposed GRIHA(Generating Room Interior of a House using ARCore), a framework for generating a layout using an RGB image captured using a simple mobile phone camera .…

## Metric Learning for Anti Compression Facial Forgery Detection

Forgery images and videos are usually compressed to different formats such as JPEG and H264 when circulating on the Internet . Existing forgery-detection methods trained on uncompressed data often havesignificantly decreased performance in identifying them . To solve this problem, we propose a novel anti-compression facial forgery detection framework, whichlearns a compression-insensitive embedding feature space utilizing bothoriginal and compressed forgeries .…

## Return Oriented Programming on RISC V

This paper provides the first analysis on the feasibility of Return-OrientedProgramming (ROP) on RISC-V . We show the existence of a new class of gadgets, usingseveral Linear Code Sequences And Jumps (LCSAJ) undetected by currentGalileo-based ROP gadget searching tools . We argue that this class is rich enough on Risc-V to mount complex ROP attacks, bypassing traditionalmitigation like DEP, ASLR, stack canaries, G-Free, as well as somecompiler-based backward-edge CFI, by jumping over any guard inserted by acompiler to protect indirect jump instructions .…

## Electronic Structure in a Fixed Basis is QMA complete

Finding the ground state energy of electrons subject to an external electricfield is a fundamental problem in computational chemistry . Schuch and Verstraete haveshown hardness for the electronic-structure problem with an additionalsite-specific external magnetic field, but without the restriction to a fixedbasis .…

## Rectilinear Steiner Trees in Narrow Strips

A rectilinear Steiner tree for a set $P$ of points in $mathbb{R}^2$ is atree that connects the points using horizontal and vertical linesegments . We present an algorithm with running time $n^{O(\sqrt{\delta) n$ for sparse point sets, that is, point sets where each$1\times\delta$ rectangle inside the strip contains $O(1)$ points .…

## RoRD Rotation Robust Descriptors and Orthographic Views for Local Feature Matching

The use of local detectors and descriptors in typical computer vision pipelines work well until variations in viewpoint and appearance change becomeextreme . We propose a novel framework that combines learning of invariant descriptorsthrough data augmentation and orthographic viewpoint projection .…

## Sampling free Variational Inference for Neural Networks with Multiplicative Activation Noise

Bayesian neural networks (BNNs) provideuncertainty estimates by averaging predictions with respect to the posteriorweight distribution . Variational inference methods for BNNs approximate theintractable weight posterior with a tractable distribution . They mostly rely on sampling from the variational distribution during training and inference .…

## Quantum Private Distributed Learning Through Blind Quantum Computing

Private distributed learning studies the problem of how multiple distributedentities collaboratively train a shared deep network with their private data . With the security provided by the protocols of blind quantumcomputation, the cooperation between quantum physics and machine learning maylead to unparalleled prospect for solving private distributed learning tasks .…

## Learning Frequency aware Dynamic Network for Efficient Super Resolution

Deep learning based methods, especially convolutional neural networks (CNNs) have been successfully applied in the field of single image super-resolution(SISR) To obtain better fidelity and visual quality, most of existing networksare of heavy design with massive computation . To this end, this paper explores a novel frequency-awaredynamic network for dividing input into multiple parts according to itscoefficients in the discrete cosine transform (DCT) domain .…

## 3D FFS Faster 3D object detection with Focused Frustum Search in sensor fusion based networks

3D-FFS is a novel approach to make sensor fusion based3D object detection networks significantly faster using a class ofcomputationally inexpensive heuristics . Compared to F-ConvNet, we achieve improvements in training andinference times by up to 62.84% and 56.46% . We achieve 0.59%, 2.03% and 3.34%improvements in accuracy for the Car, Pedestrian and Cyclist classes,respectively.…

## DeepOPG Improving Orthopantomogram Finding Summarization with Weak Supervision

Finding summaries from an orthopantomogram, or a dental panoramic radiograph, have significant potential to improve patient communication and to speed up clinical judgments . A finding summary has to not only find teeth in the imaging study but alsolabel the teeth with several types of treatments .…

## XLST Cross lingual Self training to Learn Multilingual Representation for Low Resource Speech Recognition

Cross-lingual self-training (XLST) is able toutilize a small amount of annotated data from high-resource languages to improve representation learning on multilingual un-annotated data . XLST uses a supervised trained model to produce initial representations and another model to learn from them, by maximizing thesimilarity between output embeddings of these two models .…

## BLOWN A Blockchain Protocol for Wireless Networks under Adversarial SINR

Blockchain can empower wireless networks with identity management, data integrity, access control, and high-level security . We formalizeBLOWN with the universal composition framework and prove its securityproperties, namely persistence and liveness, against adversarial jamming, double-spending, and Sybil attacks . We propose a novel consensusprotocol named Proof-of-Channel (PoC) leveraging the natural properties ofwireless networks, and a BLOWN protocol (BLOckchain protocol for WirelessNetworks) for wireless networks under an adversarial SINR model .…

## Rotation Coordinate Descent for Fast Globally Optimal Rotation Averaging

Rotationaveraging satisfies strong duality, which enables global solutions to be obtained via semidefinite programming (SDP) relaxation . However, genericsolvers for SDP are rather slow in practice, even on rotation averaging instances of moderate size . In this paper, we present a fast algorithm that achieves global optimality calledrotation coordinate descent (RCD) Unlike block coordinate descent, RCD maintains and updates all valid rotations throughout the iterations .This…

## S AT GCN Spatial Attention Graph Convolution Network based Feature Enhancement for 3D Object Detection

3D object detection plays a crucial role in environmental perception for autonomous vehicles . The Spatial-AttentionGraph Convolution (S-AT GCN) uses the graph convolution and thespatial attention mechanism to extract local geometrical structure features . FE layersboost the pedestrian class performance by 3.62\% and cyclist class by 4.21\% 3DmAP.…

## Get Your Vitamin C Robust Fact Verification with Contrastive Evidence

Typical fact verification models use retrieved written evidence to verify claims . Evidence sources often change over time as more information is gathered and revised . In order to adapt, models must be sensitive to subtledifferences in supporting evidence . We present VitaminC, a benchmark infused with challenging cases that require models to discern and adjust to slight factual changes .…

## Uncertainty Based Biological Age Estimation of Brain MRI Scans

Current BA estimation approaches are restricted to skeletal images or rely on non-imaging modalities that yield a whole-body BA assessment . Various organ systems may exhibit different aging characteristics due to lifestyle and genetic factors . In thisinitial study, we propose a new framework for organ-specific BA estimation using 3D magnetic resonance image (MRI) scans .…

## DiaRet A browser based application for the grading of Diabetic Retinopathy with Integrated Gradients

Diabetes is a metabolic disorder that results from defects in autoimmunebeta-cell destruction in Type 1, peripheral resistance to insulin action in Type 2 or, most commonly, both . Patients with long-standing diabetes often fall prey to Diabetic Retinopathy (DR) resulting in changes in the retina of the human eye, which may lead to loss of vision in extreme cases .…

## UrbanVCA a vector based cellular automata framework to simulate the urban land use change at the land parcel level

The UrbanVCAsimulates multiple types of urban land-use changes at the land-parcel level have achieved a high accuracy (FoM=0.243) and the landscape index similarityreaches 87.3% . The simulation results in 2030 show that the eco-protectionscenario can promote urban agglomeration and reduce ecological aggression and loss of arable land by at least 60% .…

## Enclosing Depth and other Depth Measures

We study families of depth measures defined by natural sets of axioms . Weshow that any such depth measure is a constant factor approximation of Tukeydepth . We further investigate the dimensions of depth regions, showing that theCascade conjecture, introduced by Kalai for Tverberg depth, holds for all depthmeasures .…

## BGPeek a Boo Active BGP based Traceback for Amplification DDoS Attacks

BGPeek-a-Boo monitors DDoS attacks with honeypots and uses BGP poisoning to temporarily shutdown ingress traffic from selected Autonomous Systems . We then show how a graph-based model of BGP route propagation can reduce the search space, resulting in a 5x median speed-up and over 20x for 1/4 of all cases .…

## Efficient Intrusion Detection Using Evidence Theory

Intrusion Detection Systems (IDS) are now an essential element when it comesto securing computers and networks . Despite the huge research efforts done inthe field, handling sources’ reliability remains an open issue . To address thisproblem, this paper proposes a novel contextual discounting method based on reliability and their distinguishing ability between normal andnormal behavior .…

## Margin Preserving Self paced Contrastive Learning Towards Domain Adaptation for Medical Image Segmentation

A novel marginpreserving self-paced contrastive Learning (MPSCL) model for cross-modal medical image segmentation . MPSCL significantlyimproves semantic segmentation performance, and outperforms a wide variety of state-of-the-art methods by a large margin . Unlike the conventional construction of contrastivepairs in contrastive learning, the domain-adaptive category prototypes are used to constitute the positive and negative sample pairs .…

## Formal Modelling and Security Analysis of Bitcoin s Payment Protocol

Payment Protocol standard BIP70, specifying how payments in Bitcoin are performed by merchants and customers, is supported by the largest paymentprocessors and most widely-used wallets . The Payment Protocol has been shown to be vulnerable to refund attacks due to lack of authentication of refund addresses .…

## A novel approach for the efficient modeling of material dissolution in electrochemical machining

This work presents a novel approach to efficiently model anodic dissolution in electrochemical machining . Earlier modeling approaches employ a strict spacediscretization of the anodic surface that is associated with a remeshingprocedure at every time step . This inner variable allows the modeling of the complex dissolution process without the necessity of computationally expensiveremeshing by controlling the effective material parameters .…

## A Systematic Review of Reproducibility Research in Natural Language Processing

The NLP field is becoming increasingly interested in, and conscientious about, the reproducibility of its results . The past few years have seen an impressive range of new initiatives, events and active research inthe area . However, the field is far from reaching a consensus about howreproducibility should be defined, measured and addressed, with diversity of views currently increasing rather than converging .…

## SemVLP Vision Language Pre training by Aligning Semantics at Multiple Levels

Vision-language pre-training (VLP) on large-scale image-text pairs has witnessed rapid progress for learning cross-modal representations . SemVLP jointly aligns both the low-level and high-level semantics between image and text representations . An extensive set of experiments have been conducted on four well-established vision-language understanding tasks todemonstrate the effectiveness of the proposed model .…