May 2022 arXiv papers — page 122

Huiyun Yang, Huadong Chen, Hao Zhou, Lei Li

Based on large-scale pre-trained multilingual representations, recent cross-lingual transfer methods have achieved impressive transfer performances. However, the performance of target languages still lags far behind the source language. In this paper, our analyses indicate such a performance gap is strongly associated with the cross-lingual representation di

Xiaokun Zhang, Bo Xu, Liang Yang, Chenliang Li

Session-based recommendation aims to predict items that an anonymous user would like to purchase based on her short behavior sequence. The current approaches towards session-based recommendation only focus on modeling users' interest preferences, while they all ignore a key attribute of an item, i.e., the price. Many marketing studies have shown that the

Keyu Wu, Yifan Ye, Lingchen Yang, Hongbo Fu

Undoubtedly, high-fidelity 3D hair plays an indispensable role in digital humans. However, existing monocular hair modeling methods are either tricky to deploy in digital systems (e.g., due to their dependence on complex user interactions or large databases) or can produce only a coarse geometry. In this paper, we introduce NeuralHDHair, a flexible, fully au

Manuel Baum, Oliver Brock

Robotic manipulation behavior should be robust to disturbances that violate high-level task-structure. Such robustness can be achieved by constantly monitoring the environment to observe the discrete high-level state of the task. This is possible because different phases of a task are characterized by different sensor patterns and by monitoring these pattern

Dominique Bourn, Alberto Facchini, Mara Pompili

We examine the pointed protomodular category SKB of left skew braces. We study the notion of commutator of ideals in a left skew brace. Notice that in the literature, "product" of ideals of skew braces is often considered. We show that Huq=Smith for left skew braces. Finally, we give a set of generators for the commutator of two ideals, and prove tha

Nam H. Hoang, Federico Mogavero, Jacques Laskar

Apart from being chaotic, the inner planets in the Solar System constitute an open system, as they are forced by the regular long-term motion of the outer ones. No integrals of motion can bound a priori the stochastic wanderings in their high-dimensional phase space. Still, the probability of a dynamical instability is remarkably low over the next 5 billion

Satoshi Funabashi, Tomoki Isobe, Fei Hongyi, Atsumu Hiramoto

Multi-fingered hands could be used to achieve many dexterous manipulation tasks, similarly to humans, and tactile sensing could enhance the manipulation stability for a variety of objects. However, tactile sensors on multi-fingered hands have a variety of sizes and shapes. Convolutional neural networks (CNN) can be useful for processing tactile information,

Si Chen, Chen Lin, Wanxian Guan, Jiayi Wei

Extracting expressive visual features is crucial for accurate Click-Through-Rate (CTR) prediction in visual search advertising systems. Current commercial systems use off-the-shelf visual encoders to facilitate fast online service. However, the extracted visual features are coarse-grained and/or biased. In this paper, we present a visual encoding framework f

Marco Marini, Lorenzo Capponi, Ilaria Battistoni, Tommaso Tocci

Background: At the beginning of 2020, a high number of COVID-19 cases affected Italy in a short period, causing a difficult supply of medical equipment. To deal with the problem, many healthcare operators readapted different masks to medical devices, but no experiment was conducted to evaluate their performance. The aims of our study were: to assess the perf

Iason Katsamenis, Matthaios Bimpas, Eftychios Protopapadakis, Charalampos Zafeiropoulos

Of all public assets, road infrastructure tops the list. Roads are crucial for economic development and growth, providing access to education, health, and employment. The maintenance, repair, and upgrade of roads are therefore vital to road users' health and safety as well as to a well-functioning and prosperous modern economy. The EU-funded HERON projec

Yinjie Zhang, Yi Liu, Wei Guo

Remote sensing semantic segmentation aims to assign automatically each pixel on aerial images with specific label. In this letter, we proposed a new module, called improved-flow warp module (IFWM), to adjust semantic feature maps across different scales for remote sensing semantic segmentation. The improved-flow warp module is applied along with the feature

Gül Varol, Liliane Momeni, Samuel Albanie, Triantafyllos Afouras

The focus of this work is $\textit{sign spotting}$ - given a video of an isolated sign, our task is to identify $\textit{whether}$ and $\textit{where}$ it has been signed in a continuous, co-articulated sign language video. To achieve this sign spotting task, we train a model using multiple types of available supervision by: (1) $\textit{watching}$ existing

M. Cuciniello, T. Amorese, G. Cordasco, S. Marrone

The present study aims to explore user acceptance and perceptions toward different quality levels of synthetical voices. To achieve this, four voices have been exploited considering two main factors: the quality of the voices (low vs high) and their gender (male and female). 186 volunteers were recruited and subsequently allocated into four groups of differe

A. Aguilar-Arevalo, C. Canet, M. A. Cruz-Pérez, A. Deisting

The World Health Organisation (WHO) presents an upper limit for lead in drinking water of 10 parts per billion ppb. Typically, to reach this level of sensitivity, expensive metrology is required. To increase the sensitivity of low cost devices, this paper explores the prospects of using a volume reduction technique of a boiled water sample doped with Lead-21

Vera Colombo, Alessandro Tundo, Michele Ciavotta, Leonardo Mariani

Monitoring is a critical component in fog environments: it promptly provides insights about the behavior of systems, reveals Service Level Agreements (SLAs) violations, enables the autonomous orchestration of services and platforms, calls for the intervention of operators, and triggers self-healing actions. In such environments, monitoring solutions have to

Rajnikant Upadhyay, Manjari Shukla, Rachana Sain, Martin Tolkiehn

We herein present the spin freezing dynamics of stuffed polycrystalline compound Dy$_2$Ti$_{1.8}$Mn$_{0.2}$O$_7$. In Dy$_2$Ti$_2$O$_7$, spin freezes with ice-like spin relaxations at a temperature around 3 K (T$_i$) along with another spin freezing at a temperature around 0.7 K (T\textless T$_i$). These relaxations can be observed prominently with an applica

Thanh Tung Khuat, David Jacob Kedziora, Bogdan Gabrys

As automated machine learning (AutoML) systems continue to progress in both sophistication and performance, it becomes important to understand the `how' and `why' of human-computer interaction (HCI) within these frameworks, both current and expected. Such a discussion is necessary for optimal system design, leveraging advanced data-processing capabil

Wanchang Zhang

A single unit of a good is sold to one of two bidders. Each bidder has either a high prior valuation or a low prior valuation for the good. Their prior valuations are independently and identically distributed. Each bidder may observe an independently and identically distributed signal about her prior valuation. The seller knows the distribution of the prior

Omid Sedehi, Costas Papadimitriou, Lambros S. Katafygiotis

This paper develops a Hierarchical Bayesian Modeling (HBM) framework for uncertainty quantification of Finite Element (FE) models based on modal information. This framework uses an existing Fast Fourier Transform (FFT) approach to identify experimental modal parameters from time-history data and employs a class of maximum-entropy probability distributions to

Alessandro Valenti

Models of spontaneous CP violation can solve the Strong CP problem without the need of an anomalous Peccei-Quinn symmetry. In this work we review the Nelson-Barr approach, quantifying a peculiar coincidence between unrelated mass scales that these models must satisfy in order to correctly reproduce the Standard Model quark masses and CP violation. We investi

Huang-Hsiang Lin, Alexander Croy, Rafael Gutierrez, Gianaurelio Cuniberti

Molecule- and solid-state gears build the elementary constituents of nanoscale mechanical machineries. Recent experimental advances in fabrication technologies in the field have strongly contributed to better delineate the roadmap towards the ultimate goal of engineering molecular-scale mechanical devices. To complement experimental studies, computer simulat

Fang-Yu Ma

Two infinite sequences A and B of non-negative integers are called additive complements, if their sum contains all sufficiently large integers. Let $A(x)$ and $B(x)$ be the counting functions of A and B. In this paper, we extend the results of Liu and Fang in 2016 and obtain some results on additive complements. For example, we prove that there exist additiv

Stefano Mangini, Alessia Marruzzo, Marco Piantanida, Dario Gerace

Quantum computing technologies are in the process of moving from academic research to real industrial applications, with the first hints of quantum advantage demonstrated in recent months. In these early practical uses of quantum computers it is relevant to develop algorithms that are useful for actual industrial processes. In this work we propose a quantum

Eduard Feireisl, Mária Lukáčová - Medviďová, Bangwei She, Yuhuan Yuan

The goal of this paper is to study convergence and error estimates of the Monte Carlo method for the Navier-Stokes equations with random data. To discretize in space and time, the Monte Carlo method is combined with a suitable deterministic discretization scheme, such as a finite volume method. We assume that the initial data, force and the viscosity coeffic

Xiao-lin Chen, Wen-jun Hou

Gaze recognition can significantly reduce the amount of eye movement data for a better understanding of cognitive and visual processing. Gaze recognition is an essential precondition for eye-based interaction applications in virtual reality. However, the three-dimensional characteristics of virtual reality environments also pose new challenges to existing re

Yang Li, Cheng Yu, Guangzhi Sun, Hua Jiang

Modelling prosody variation is critical for synthesizing natural and expressive speech in end-to-end text-to-speech (TTS) systems. In this paper, a cross-utterance conditional VAE (CUC-VAE) is proposed to estimate a posterior probability distribution of the latent prosody features for each phoneme by conditioning on acoustic features, speaker information, an

Ziji Shao, Jinghua Liang, Qirui Cui, Mairbek Chshiev

Exploring novel two-dimensional multiferroic materials that can realize electric-field control of two-dimensional magnetism has become an emerging topic in spintronics. Using first-principles calculations, we demonstrate that non-metallic bilayer transition metal dichalcogenides (TMDs) can be an ideal platform for building multiferroics by intercalated magne

Hojun Jin, Sangkeum Lee, Sarvar Hussain Nengroo, Dongsoo Har

As the number of electric vehicles (EVs) significantly increases, the excessive charging demand of parked EVs in the charging station may incur an instability problem to the electricity network during peak hours. For the charging station to take a microgrid (MG) structure, an economical and energy-efficient power management scheme is required for the power p

Wei Zhu, Le Lu, Jing Xiao, Mei Han

Deep learning methods can struggle to handle domain shifts not seen in training data, which can cause them to not generalize well to unseen domains. This has led to research attention on domain generalization (DG), which aims to the model's generalization ability to out-of-distribution. Adversarial domain generalization is a popular approach to DG, but c

Thierry Bodineau, Isabelle Gallagher, Laure Saint-Raymond, Sergio Simonella

In [7], a cluster expansion method has been developed to study the fluctuations of the hard sphere dynamics around the Boltzmann equation. This method provides a precise control on the exponential moments of the empirical measure, from which the fluctuating Boltzmann equation and large deviation estimates have been deduced. The cluster expansion in [7] was i

Ying Zhou, Xuanang Chen, Ben He, Zheng Ye

Knowledge graph completion (KGC) aims to infer missing knowledge triples based on known facts in a knowledge graph. Current KGC research mostly follows an entity ranking protocol, wherein the effectiveness is measured by the predicted rank of a masked entity in a test triple. The overall performance is then given by a micro(-average) metric over all individu

Sangshin Oh, Seyun Um, Hong-Goo Kang

The Gumbel-softmax distribution, or Concrete distribution, is often used to relax the discrete characteristics of a categorical distribution and enable back-propagation through differentiable reparameterization. Although it reliably yields low variance gradients, it still relies on a stochastic sampling process for optimization. In this work, we present a re

Samuel Nalin, Guillaume Theyssier

This paper is about turedos, which are Turing machine whose head can move in the plane (or in a higher-dimensional space) but only in a selfavoiding way, by putting marks (letters) on visited positions and moving only to unmarked, therefore unvisited, positions. The key parameter of turedos is their lookup radius: the distance up to which the head can look a

Tristan Guillot, Leigh N. Fletcher, Ravit Helled, Masahiro Ikoma

Giant planets acquire gas, ices and rocks during the early formation stages of planetary systems and thus inform us on the formation process itself. Proceeding from inside out, examining the connections between the deep interiors and the observable atmospheres, linking detailed measurements on giant planets in the solar system to the wealth of data on brown

Mudhahir Al Ajmi, Mark Hindmarsh

One of the key observables in a gravitational wave power spectrum from a first order phase transition in the early Universe is the mean bubble spacing, which depends on the rate of nucleation of bubbles of the stable phase, as well as the bubble wall speed. When the bubbles expand as deflagrations, it is expected that the heating of the fluid in front of the

Mauro Abela, Mauro Mameli, Vadim Nikolayev, Sauro Filippeschi

A multi-parametric transient numerical simulation of the start-up of a large diameter Pulsating Heat Pipe (PHP) specially designed for future experiments on the International Space Station (ISS) are compared to the results obtained during a parabolic flight campaign supported by the European Space Agency. Since the channel diameter is larger than the capilla

Nicolas W. Remerscheid, Alexander Ziller, Daniel Rueckert, Georgios Kaissis

The arguably most widely employed algorithm to train deep neural networks with Differential Privacy is DPSGD, which requires clipping and noising of per-sample gradients. This introduces a reduction in model utility compared to non-private training. Empirically, it can be observed that this accuracy degradation is strongly dependent on the model architecture

Abhinav Ramesh Kashyap, Devamanyu Hazarika, Min-Yen Kan, Roger Zimmermann

Automatic transfer of text between domains has become popular in recent times. One of its aims is to preserve the semantic content of text being translated from source to target domain. However, it does not explicitly maintain other attributes between the source and translated text, for e.g., text length and descriptiveness. Maintaining constraints in transf

Lisette Jager

This paper deals with positivity properties for a pseudodifferential calculus, generalizing Weyl's classical quantization, and set on an infinite dimensional phase space, the Wiener space. In this frame, we show that a positive symbol does not, in general, give a positive operator. In order to measure the nonpositivity, we establish a Gårding's inequ

Shengjie Zheng, Xianfeng Man, Ze-Lin Kong, Zhi-Kang Lin

Topological phases of matter have been extensively investigated in solid state materials and classical wave systems with integer dimensions. However, topological states in non-integer dimensions remain largely unexplored. Fractals, being nearly the same at different scales, are one of the intriguing complex geometries with non-integer dimensions. Here, we de

Nicolas Ugrinovic, Albert Pumarola, Alberto Sanfeliu, Francesc Moreno-Noguer

Recent advances in 3D human shape reconstruction from single images have shown impressive results, leveraging on deep networks that model the so-called implicit function to learn the occupancy status of arbitrarily dense 3D points in space. However, while current algorithms based on this paradigm, like PiFuHD, are able to estimate accurate geometry of the hu

Dan Malkin, Tomasz Limisiewicz, Gabriel Stanovsky

We show that the choice of pretraining languages affects downstream cross-lingual transfer for BERT-based models. We inspect zero-shot performance in balanced data conditions to mitigate data size confounds, classifying pretraining languages that improve downstream performance as donors, and languages that are improved in zero-shot performance as recipients.

Debajyoti Choudhuri

The short note here is to give a few heuristic arguments on the weird looking fractional Laplacian operator. This is certainly going to expand the vision of a reader who is looking to develope a taste for research in this direction.

Xinyu Wang, Yohan Lee, Juneyoung Park

This paper surveys and organizes research works in an under-studied area, which we call automated evaluation for student argumentative writing. Unlike traditional automated writing evaluation that focuses on holistic essay scoring, this field is more specific: it focuses on evaluating argumentative essays and offers specific feedback, including argumentation

Cory Palmer, Balázs Patkós

We connect two classical results in extremal graph theory concerning the number of maximal independent sets. The maximum number mis$(n)$ of maximal independent sets in an $n$-vertex graph was determined by Moon and Moser. The maximum number mis$_\bigtriangleup(n)$ of maximal independent sets in an $n$-vertex triangle-free graph was determined by Hujter and T

Eduard Feireisl, Mária Lukáčová-Medviďová, Bangwei She

We present new error estimates for the finite volume and finite difference methods applied to the compressible Navier-Stokes equations. The main innovative ingredients of the improved error estimates are a refined consistency analysis combined with a continuous version of the relative energy inequality. Consequently, we obtain better convergence rates than t

Ahmad Jafar Arifi, Ho-Meoyng Choi, Chueng-Ryong ji, Yongseok Oh

The mass spectra and wave functions of both $1S$ and $2S$ state heavy pseudoscalar ($P$) and vector ($V$) mesons are analyzed within the light-front quark model. Important empirical constraints employed in our analysis of the mass spectra and wave functions are the experimental mass-gap relation, $ΔM_P > ΔM_V$, where $ΔM_{P(V)}=M^{2S}_{P(V)}-M^{1S}_{P(V)}$ a

Xuhui Peng, Lihu Xu

We consider a stochastic 2D Navier-Stokes equation in a bounded domain. The random force is assumed to be non-degenerate and periodic in time, its law has a support localised with respect to both time and space. Slightly strengthening the conditions in the pioneering work about exponential ergodicity by Shirikyan [Shi15], we prove that the stochastic system

Weixin Feng, Xingyuan Bu, Chenchen Zhang, Xubin Li

Multimodal supervision has achieved promising results in many visual language understanding tasks, where the language plays an essential role as a hint or context for recognizing and locating instances. However, due to the defects of the human-annotated language corpus, multimodal supervision remains unexplored in fully supervised object detection scenarios.

Clément Denis

We give a description of a magnetohydrodynamical system in $n$ dimension using the exterior derivative. We then prove existence of global solutions for small initial data and local existence for arbitrary large data in two classes of critical spaces -- $L^q_tL^p_x$ and $\mathcal{C}_tL^p_x$, as well as uniqueness for solutions in $\mathcal{C}_tL^p_x$.

Robert S MacKay

For Schrodinger operators with suitable 1D potentials, focussing particularly on those that go to infinity at infinity, a characteristic function is constructed, via shooting functions. It is proved to be entire and its zeroes to be the eigenvalues.

W. Yang, C. Li

A quantity of particular experimental interest is the forward-backward asymmetry in the angular distribution of positively and negatively charged fermions produced in $Z^0$ decays. Measurements of this asymmetry can enable independent determinations of the neutral-current couplings of these fermions, i.e. the $Z^0$ boson couplings for left- and right-handed

Minhan Xu, Yu Hong

We leverage embedding duplication between aligned sub-words to extend the Parent-Child transfer learning method, so as to improve low-resource machine translation. We conduct experiments on benchmark datasets of My-En, Id-En and Tr-En translation scenarios. The test results show that our method produces substantial improvements, achieving the BLEU scores of

Min Peng, Chongyang Wang, Yuan Gao, Yu Shi

Video question answering (VideoQA) is challenging given its multimodal combination of visual understanding and natural language processing. While most existing approaches ignore the visual appearance-motion information at different temporal scales, it is unknown how to incorporate the multilevel processing capacity of a deep learning model with such multisca

Ivo Welch

Kossin et al. (2020) successfully test (over the last four decades) the prediction of climate-change models that conditional tropical cyclone intensity (the frequency of major [category 3-5] cyclones divided by the frequency of all cyclones) should increase. Yet, the highest relative proportional increase in incidence occurred in category 3 cyclones. The hig

Divya Tahelyani, Ashok B. Joshi, Dipanjan Dey, Pankaj S. Joshi

In the present paper, we study the thermal properties of the geometrically thin accretion disks surrounding the null naked singularity (NNS) and the first type of Joshi-Malafarina-Narayan (JMN1) spacetimes and compare the results with the accretion disk around equally massive Schwarzschild black hole. First, we examine the properties of the circular orbits i

Yusheng Hou, Feng Xue, Liang Qiu, Zhe Wang

Two-dimensional van der Waals Janus materials and their heterostructures offer fertile platforms for designing fascinating functionalities. Here, by means of systematic first-principles studies on van der Waals Janus monolayer Cr-based dichalcogenide halides CrYX (Y=S, Se, Te; X=Cl, Br, I), we find that CrSX (X=Cl, Br, I) are the very desirable high TC ferro

Mandar Joshi, Terra Blevins, Mike Lewis, Daniel S. Weld

Creating labeled natural language training data is expensive and requires significant human effort. We mine input output examples from large corpora using a supervised mining function trained using a small seed set of only 100 examples. The mining consists of two stages -- (1) a biencoder-based recall-oriented dense search which pairs inputs with potential o

M. A. Jalil, M. N. I. Khan, S. Mandal, F. -U. -Z. Chowdhury

In this study, a complete study of the effect of hydrothermal reaction temperatures on the synthesis and physical properties of V2O5 using the green facile mild hydrothermal method has been performed with six different temperatures 100 °C to 200 °C, in the step of 20 °C. . The XRD pattern confirm the stable orthorhombic crystal structure of the synthesized s

Lin Sun, Qijin Chen

We study the ground state phase diagram of population balanced and imbalanced ultracold atomic Fermi gases with a short range attractive interaction throughout the crossover from BCS to Bose-Einstein condensation (BEC), in a two-dimensional optical lattice (2DOL) comprised of two lattice and one continuum dimensions. We find that the mixing of lattice and co

Yan-Ran, Wang, Liangqiong Qu, Natasha Diba Sheybani

Despite its tremendous value for the diagnosis, treatment monitoring and surveillance of children with cancer, whole body staging with positron emission tomography (PET) is time consuming and associated with considerable radiation exposure. 100x (1% of the standard clinical dosage) ultra-low-dose/ultra-fast whole-body PET reconstruction has the potential for

Wei Zhu, Dongjin Song, Yuncong Chen, Wei Cheng

Despite the fact that many anomaly detection approaches have been developed for multivariate time series data, limited effort has been made on federated settings in which multivariate time series data are heterogeneously distributed among different edge devices while data sharing is prohibited. In this paper, we investigate the problem of federated unsupervi

Zi-Yuan Li, Zhen Qian, Jie-Han He, Wei He

Precise vertex reconstruction is essential for large liquid scintillator detectors. A novel method based on machine learning has been successfully developed to reconstruct the event vertex in JUNO previously. In this paper, the performance of machine learning based vertex reconstruction is further improved by optimizing the input images of the neural network

Alex Worland, Sridevi Wagle, Boris Kovalerchuk

Visualization of Machine Learning (ML) models is an important part of the ML process to enhance the interpretability and prediction accuracy of the ML models. This paper proposes a new method SPC-DT to visualize the Decision Tree (DT) as interpretable models. These methods use a version of General Line Coordinates called Shifted Paired Coordinates (SPC). In

Xue Han, Zihuai Lin

In this paper, we developed innovative digital twins of cattle status that are powered by artificial intelligence (AI). The work was built on a farm IoT system that remotely monitors and tracks the state of cattle. A digital twin model of cattle health based on Deep Learning (DL) was generated using the sensor data acquired from the farm IoT system. The heal

Charles Recaido, Boris Kovalerchuk

This paper contributes to interpretable machine learning via visual knowledge discovery in general line coordinates (GLC). The concepts of hyperblocks as interpretable dataset units and general line coordinates are combined to create a visual self-service machine learning model. The DSC1 and DSC2 lossless multidimensional coordinate systems are proposed. DSC

Milad Nonahal, Chi Li, Febiana Tjiptoharsono, Lu Ding

Spin-dependent optical transitions are attractive for a plethora of applications in quantum technologies. Here we report on utilization of high quality ring resonators fabricated from TiO2 to enhance the emission from negatively charged boron vacancies in hexagonal Boron Nitride. We show that the emission from these defects can efficiently couple into the wh

Chilam Cheang, Haitao Lin, Yanwei Fu, Xiangyang Xue

This paper studies the task of any objects grasping from the known categories by free-form language instructions. This task demands the technique in computer vision, natural language processing, and robotics. We bring these disciplines together on this open challenge, which is essential to human-robot interaction. Critically, the key challenge lies in inferr

Haitao Lin, Chilam Cheang, Yanwei Fu, Xiangyang Xue

In this paper, we are interested in the problem of generating target grasps by understanding freehand sketches. The sketch is useful for the persons who cannot formulate language and the cases where a textual description is not available on the fly. However, very few works are aware of the usability of this novel interactive way between humans and robots. To

Maria Nădejde, Anna Currey, Benjamin Hsu, Xing Niu

The machine translation (MT) task is typically formulated as that of returning a single translation for an input segment. However, in many cases, multiple different translations are valid and the appropriate translation may depend on the intended target audience, characteristics of the speaker, or even the relationship between speakers. Specific problems ari

Rui Han, Svetlana Jitomirskaya, Fan Yang

We develop the technique to prove localization through the analysis of eigenfunctions in presence of both exponential frequency resonances and exponential phase barriers (anti-resonances) and use it to prove localization for the Maryland model for all parameters.

Cong Zheng, Cheng Cheng, Qiyu Sun

In this paper, we consider Wiener filters to reconstruct deterministic and (wide-band) stationary graph signals from their observations corrupted by random noises, and we propose distributed algorithms to implement Wiener filters and inverse filters on networks in which agents are equipped with a data processing subsystem for limited data storage and computa

Ruizhen Hu, Xiangyu Su, Xiangkai Chen, Oliver Van Kaick

We introduce a method for assigning photorealistic relightable materials to 3D shapes in an automatic manner. Our method takes as input a photo exemplar of a real object and a 3D object with segmentation, and uses the exemplar to guide the assignment of materials to the parts of the shape, so that the appearance of the resulting shape is as similar as possib

Nikhil Padhye, Ajay Vallabh

Bonding between polymeric interfaces is encountered widely in several industrial applications. Many of these bonding processes rely on time-consuming and temperature-dependent classical mechanism of polymer interdiffusion via reptation in a melt state. Here, for the first time, we report a new mechanistic pathway for achieving solid-state polymer bonding by

Xinyu Huang, Conghao Zhou, Wen Wu, Mushu Li

In this paper, we present a digital twin (DT)-assisted adaptive video streaming scheme to enhance personalized quality-of-experience (PQoE). Since PQoE models are user-specific and time-varying, existing schemes based on universal and time-invariant PQoE models may suffer from performance degradation. To address this issue, we first propose a DT-assisted PQo

Thinh Hung Truong, Timothy Baldwin, Trevor Cohn, Karin Verspoor

Negation is a common linguistic feature that is crucial in many language understanding tasks, yet it remains a hard problem due to diversity in its expression in different types of text. Recent work has shown that state-of-the-art NLP models underperform on samples containing negation in various tasks, and that negation detection models do not transfer well

Tian-Yu Ye

The first quantum private comparison (QPC) protocol via cavity quantum electrodynamics (QED) is proposed in this paper by making full use of the evolution law of atom via cavity QED, where the third party (TP) is allowed to misbehave on his own but cannot conspire with either of the two users. The proposed protocol adopts two-atom product states rather than

Tian-Yu Ye

Recently, Liu W et al. proposed a two-party quantum private comparison (QPC) protocol using entanglement swapping of Bell entangled state (Commun. Theor. Phys. 57(2012)583-588). Subsequently, Liu W J et al. pointed out that in Liu W et al.'s protocol, the TP can extract the two users' secret inputs without being detected by launching the Bell-basis m

Jingtao Li, Adnan Siraj Rakin, Xing Chen, Zhezhi He

This work aims to tackle Model Inversion (MI) attack on Split Federated Learning (SFL). SFL is a recent distributed training scheme where multiple clients send intermediate activations (i.e., feature map), instead of raw data, to a central server. While such a scheme helps reduce the computational load at the client end, it opens itself to reconstruction of

Eda Okur, Saurav Sahay, Lama Nachman

Contextually aware intelligent agents are often required to understand the users and their surroundings in real-time. Our goal is to build Artificial Intelligence (AI) systems that can assist children in their learning process. Within such complex frameworks, Spoken Dialogue Systems (SDS) are crucial building blocks to handle efficient task-oriented communic

Lincoln Best, Ernest Foo, Hui Tian

The proliferation and variety of Internet of Things devices means that they have increasingly become a viable target for malicious users. This has created a need for anomaly detection algorithms that can work across multiple devices. This thesis suggests a potential alternative to the current anomaly detection algorithms to be implemented within IoT systems

Yuanhao Li, Yu Liu, Zhiqiang Ma, Panfeng Huang

The vision-based grasp detection method is an important research direction in the field of robotics. However, due to the rectangle metric of the grasp detection rectangle's limitation, a false-positive grasp occurs, resulting in the failure of the real-world robot grasp task. In this paper, we propose a novel generative convolutional neural network model

Hong-Yi Wang, Tian-Sheuan Chang

Following the success of the natural language processing, the transformer for vision applications has attracted significant attention in recent years due to its excellent performance. However, existing deep learning hardware accelerators for vision cannot execute this structure efficiently due to significant model architecture differences. As a result, this

An-Jung Huang, Kai-Chieh Hsu, Tian-Sheuan Chang

Deep learning based superresolution achieves high-quality results, but its heavy computational workload, large buffer, and high external memory bandwidth inhibit its usage in mobile devices. To solve the above issues, this paper proposes a real-time hardware accelerator with the tilted layer fusion method that reduces the external DRAM bandwidth by 92\% and

Yu-Hsiang Chiang, Cheng En Ni, Yun Sung, Tuo-Hung Hou

In-memory computing is becoming a popular architecture for deep-learning hardware accelerators recently due to its highly parallel computing, low power, and low area cost. However, in-RRAM computing (IRC) suffered from large device variation and numerous nonideal effects in hardware. Although previous approaches including these effects in model training succ

Xiaosong Ma, Jie Zhang, Song Guo, Wenchao Xu

Personalized Federated Learning (pFL) not only can capture the common priors from broad range of distributed data, but also support customized models for heterogeneous clients. Researches over the past few years have applied the weighted aggregation manner to produce personalized models, where the weights are determined by calibrating the distance of the ent

Ling Hei Tsang

Motivated by definitions in mixed Hodge theory, we define the weight filtration and the monodromy weight filtration on the combinatorial intersection cohomology of a fan. These filtrations give a natural definition of the multivariable invariants of subdivisions of polytopes, lattice polytopes and fans, namely the mixed $h$-polynomial, the refined limit mixe

Simon Stevenson, Reinhold Willcox, Alejandro Vigna-Gomez, Floor Broekgaarden

Neutron stars receive velocity kicks at birth in supernovae. Those formed in electron-capture supernovae from super asymptotic giant branch stars -- the lowest mass stars to end their lives in supernovae -- may receive significantly lower kicks than typical neutron stars. Given that many massive stars are members of wide binaries, this suggests the existence

Ling-Meng Fang, Yu-Gang Ma, Song Zhang

We used an Isospin dependent Quantum Molecular Dynamics (IQMD) model to simulate Au + Au collisions at beam energy $E_{beam}$ = 1.23$A$ GeV, which corresponds to center of mass energy $\sqrt{s_{NN}} = 2.4$ GeV. Firstly, we obtained reasonable rapidity and transverse mass spectra of $π^-$ and $π^+$ as well as "apparent" temperature parameters in compa

Michele Bennett, Mehdi Nekouei, Armand Prieditis Rajesh Mehta, Ewa Kleczyk

It is common for researchers to holdout data from a study pool to be used for external validation as well as for future research, and the same desire is true to those using machine learning modeling research. For this discussion, the purpose of the holdout sample it is preserve data for research studies that will be analysis-naive and randomly selected from

Sergey N. Galyamin

Modern trends in beam-driven radiation sources involve interaction of Cherenkov wakefields with open-ended circular waveguide structures having complicated dielectric lining, with a three-layer dielectric capillary recently offered for reducing the radiation divergency being a representative example \cite{Jiang2020}. This paper presents rigorous approach all

Alexander Varchenko

We consider an example of the joint system of dynamical differential equations and qKZ difference equations with parameters corresponding to equations for elliptic integrals. We solve this system of equations modulo any power $p^n$ of a prime integer $p$. We show that the $p$-adic limit of these solutions as $n\to\infty$ determines a sequence of line bundles

Aiswarya Sankar, Ankit Chadha

Abstractive multi document summarization has evolved as a task through the basic sequence to sequence approaches to transformer and graph based techniques. Each of these approaches has primarily focused on the issues of multi document information synthesis and attention based approaches to extract salient information. A challenge that arises with multi docum

Tianyu Liu, Yuchen Eleanor Jiang, Ryan Cotterell, Mrinmaya Sachan

Many natural language processing tasks, e.g., coreference resolution and semantic role labeling, require selecting text spans and making decisions about them. A typical approach to such tasks is to score all possible spans and greedily select spans for task-specific downstream processing. This approach, however, does not incorporate any inductive bias about

Sarah Arpin, Mingjie Chen, Kristin E. Lauter, Renate Scheidler

The paper concerns several theoretical aspects of oriented supersingular $\ell$-isogeny volcanoes and their relationship to closed walks in the supersingular $\ell$-isogeny graph. Our main result is a bijection between the rims of the union of all oriented supersingular $\ell$-isogeny volcanoes over $\overline{\mathbb{F}}_p$ (up to conjugation of the orienta

Anthony J. Ardizzi, Alexander Y. Choi, Bekari Gabritchidze, Jacob Kooi

The fundamental limits of the microwave noise performance of high electron mobility transistors (HEMTs) are of scientific and practical interest for applications in radio astronomy and quantum computing. Self-heating at cryogenic temperatures has been reported to be a limiting mechanism for the noise, but cryogenic cooling strategies to mitigate it, for inst

Azzeddine Boudjaj, Youssef Rami

In this paper, we establish the rationality conjecture raised in \cite{FKS} for any $(r-1)$-connected ($r\geq 2$) $kr$-dimensional CW-complex $X$ ($k\geq 2$) having a unique spherical cohomology class $u\in \tilde{H}^r(X, \mathbb{Z})$ such that $u^k\not =0$. %which is nilpotent with order of nilpotency equal to $k+1$. Next, we illustrate (topologically) our

Yan Long, Chen Yan, Shilin Xiao, Shivan Prasad

Using mathematical modeling and human subjects experiments, this research explores the extent to which emerging webcams might leak recognizable textual and graphical information gleaming from eyeglass reflections captured by webcams. The primary goal of our work is to measure, compute, and predict the factors, limits, and thresholds of recognizability as web

Ian Flint, Nick Golding, Peter Vesk, Yan Wang

In an effort to effectively model observed patterns in the spatial configuration of individuals of multiple species in nature, we introduce the saturated pairwise interaction Gibbs point process. Its main strength lies in its ability to model both attraction and repulsion within and between species, over different scales. As such, it is particularly well-sui

Enamul Hoque, Parsa Kavehzadeh, Ahmed Masry

Information visualizations such as bar charts and line charts are very common for analyzing data and discovering critical insights. Often people analyze charts to answer questions that they have in mind. Answering such questions can be challenging as they often require a significant amount of perceptual and cognitive effort. Chart Question Answering (CQA) sy