January 2022 arXiv papers — page 121

T. Taleb, A. Ksentini, P. Frangoudis

The trend towards the cloudification of the 3GPP LTE mobile network architecture and the emergence of federated cloud infrastructures call for alternative service delivery strategies for improved user experience and efficient resource utilization. We propose Follow-Me Cloud (FMC), a design tailored to this environment, but with a broader applicability, which

Junseok Kim, Seongwon Kim, T. Taleb, Sunghyun Choi

With the increasing number of Internet of Things (IoT) devices, Machine Type Communication (MTC) has become an important use case of the Fifth Generation (5G) communication systems. Since MTC devices are mostly disconnected from Base Station (BS) for power saving, random access procedure is required for devices to transmit data. If many devices try random ac

Adrian J. Brown

This paper discusses the mathematical aspects of band fitting and introduces the mathematics of the Asymmetric Gaussian shape and its tangent space for the first time. First, we derive an equation for an Asymmetric Gaussian shape. We then use this equation to derive a rule for the resolution of two Gaussian shaped bands. We then use the Asymmetrical Gaussian

T. Taleb, P. A. Frangoudis, I. Benkacem, A. Ksentini

We present an architecture for the provision of video Content Delivery Network (CDN) functionality as a service over a multi-domain cloud. We introduce the concept of a CDN slice, that is, a CDN service instance which is created upon a content provider's request, is autonomously managed, and spans multiple potentially heterogeneous edge cloud infrastruct

O. El Marai, T. Taleb

Self-driving vehicles are expected to bring many benefits among which enhancing traffic efficiency and relia-bility, and reducing fuel consumption which would have a great economical and environmental impact. The success of this technology heavily relies on the full situational awareness of its surrounding entities. This is achievable only when everything is

I. Afolabi, J. P. Garzon, M. Bagaa, T. Taleb

Network slicing allows different applications and network services to be deployed on virtualized resources running on a common underlying physical infrastructure. Developing a scalable system for the orchestration of end-to-end (E2E) mobile network slices requires careful planning and very reliable algorithms. In this paper, we propose a novel E2E Network Sl

Mohammad Ayman Mursaleen, Adem Kilicman, Md. Nasiruzzaman

Our main purpose of this article is to study the convergence and other related properties of q-Bernstein-Kantorovich operators including the shifted knots of real positive numbers. We design the shifted knots of Bernstein-Kantorovich operators generated by the basic q-calculus. More precisely, we study the convergence properties of our new operators in the s

Stefan Schrod, Andreas Schäfer, Stefan Solbrig, Robert Lohmayer

Estimating the effects of interventions on patient outcome is one of the key aspects of personalized medicine. Their inference is often challenged by the fact that the training data comprises only the outcome for the administered treatment, and not for alternative treatments (the so-called counterfactual outcomes). Several methods were suggested for this sce

O. El Marai, M. Bagaa, T. Taleb

Dynamic Adaptive Streaming over HTTP(DASH) is becoming the defacto method for effective video traffic delivery at large scale.Its primer success factor returns to the full autonomy given to the streaming clients making them smarter and enabling decentralized logic of video quality decision at granular video chunks following a pull-based paradigm. However,the

B. Yang, T. Taleb, Z. Wu, L. Ma

With the assistance of device-to-device (D2D) communications, unmanned aerial vehicle (UAV) networks are anticipated to support widespread applications in the fifth generation (5G) and beyond wireless systems, by providing seamless coverage, flexible deployment, and high channel rate. However, the networks face significant security threats from malicious eav

M. Bagaa, T. Taleb, J. B. Bernabe, A. Skarmeta

Network Function Virtualization (NFV) and Software Distributed Networking (SDN) technologies play a crucial role in enabling 5G system and beyond. A synergy between these both technologies has been identified for enabling a new concept dubbed service function chains (SFC) that aims to reduce both the capital expenditures (CAPEX) and operating expenses (OPEX)

C. Benzaid, T. Taleb

Artificial Intelligence (AI) is envisioned to play a pivotal role in empowering intelligent, adaptive and autonomous security management in 5G and beyond networks, thanks to its potential to uncover hidden patterns from a large set of time-varying multi-dimensional data, and deliver faster and accurate decisions. Unfortunately, AI's capabilities and vuln

Tariku Adane Gelaw, Misgina Tsighe Hagos

Poor sitting habits have been identified as a risk factor to musculoskeletal disorders and lower back pain especially on the elderly, disabled people, and office workers. In the current computerized world, even while involved in leisure or work activity, people tend to spend most of their days sitting at computer desks. This can result in spinal pain and rel

Vibhor Gautam, Vikalp Shishodia

Electronic Intelligence (ELINT), often known as E-Intelligence, is intelligence obtained through electronic sensors. Other than personal communications, ELINT intelligence is usually obtained. The goal is usually to determine a target's capabilities, such as radar placement. Active or passive sensors can be employed to collect data. A provided signal is

Ildar Rakhmatulin, Sebastian Volkl

This paper presents an inexpensive, high-precision, but at the same time, easy-to-maintain PIEEG board to convert a RaspberryPI to a Brain-computer interface. This shield allows measuring and processing eight real-time EEG (Electroencephalography) signals. We used the most popular programming languages - C, C++ and Python to read the signals, recorded by the

Evan Alexander, Emily Burns, John Ross, Jesse Stovall

We study the isoperimetric problem on $\mathbb{R}^1$ with a prescribed density function $f(x) = |x|$. Under these conditions, we find that isoperimetric $3$-bubble and $4$-bubble results satisfy a regular structure. As our regions increase in size, the intervals that form them alternate back-and-forth across the origin, with the smaller regions closer to the

A. Abada, Y. Bin, T. Taleb

This paper investigates traffic flow modeling issue in multi-services oriented unmanned aerial vehicle (UAV)-enabled wireless networks, which is critical for supporting future various applications of such networks. We propose a general traffic flow model for multi-services oriented UAV-enable wireless networks. Under this model, we first classify the network

He Liu, Tao Wang, Congyan Lang, Songhe Feng

Differentiable solvers for the linear assignment problem (LAP) have attracted much research attention in recent years, which are usually embedded into learning frameworks as components. However, previous algorithms, with or without learning strategies, usually suffer from the degradation of the optimality with the increment of the problem size. In this paper

Corneliu Arsene

The electrical generation and transmission infrastructures of many countries are under increased pressure. This partially reflects the move towards low carbon economies and the increased reliance on renewable power generation systems. There has been a reduction in the use of traditional fossil fuel generation systems, which provide a stable base load, and th

Alexandra Ruth Stewart, Li-Ta Lo, Oleg Korobkin, Irina Sagert

Neutron star mergers are cosmic catastrophes that produce some of the most energetic observed phenomena: short gamma-ray bursts, gravitational wave signals, and kilonovae. The latter are optical transients, powered by radioactive nuclides which are synthesized when the neutron-rich ejecta of a disrupted neutron star undergoes decompression. We model this dec

Marco Castronovo

Given a strictly concave rational PL function $ϕ$ on a complete $n$-dimensional fan $Σ$, we construct an exact symplectic structure of finite volume on $(\mathbb{C}^\times)^n$ and a family of functions $H_{ϕ,ε}$ called polyhedral Hamiltonians. We prove that for each $ε$ the one-periodic orbits of $H_{ϕ,ε}$ come in families corresponding to finitely many prim

J. Jesenovec, C. Pansegrau, M. D. McCluskey, J. S. McCloy

Beta-Ga2O3 is an ultra-wide bandgap semiconductor with emerging applications in power electronics. The introduction of acceptor dopants yields semi-insulating substrates necessary for thin-film devices. In the present work, exposure of Cu-doped Ga2O3 to UV light > 4 eV is shown to cause large, persistent photo-induced darkening at room temperature. Electron

Taras Rumezhak, Oles Dobosevych, Rostyslav Hryniv, Vladyslav Selotkin

3D scanning is a complex multistage process that generates a point cloud of an object typically containing damaged parts due to occlusions, reflections, shadows, scanner motion, specific properties of the object surface, imperfect reconstruction algorithms, etc. Point cloud completion is specifically designed to fill in the missing parts of the object and ob

Mengda Xu, Sumitra Ganesh, Pranay Pasula

Continual learning in environments with shifting data distributions is a challenging problem with several real-world applications. In this paper we consider settings in which the data distribution(task) shifts abruptly and the timing of these shifts are not known. Furthermore, we consider a semi-supervised task-agnostic setting in which the learning algorith

Belle Collaboration, T. Pang, V. Savinov, I. Adachi

We report the results of the first search for the decay $B_s^0 \to η^\prime K_S^0$ using $121.4\,{\rm fb}^{-1}$ of data collected at the $Υ(5S)$ resonance with the Belle detector at the KEKB asymmetric-energy $e^+ e^-$ collider. We observe no signal and set a 90\% confidence-level upper limit of $8.16 \times 10^{-6}$ on the $B_s^0 \to η^\prime K_S^0$ branchi

Guo-Yang Li, Artur L. Gower, Michel Destrade, Seok-Hyun Yun

Knowing the stress within a soft material is of fundamental interest to basic research and practical applications, such as soft matter devices, biomaterial engineering, and medical sciences. However, it is challenging to measure stress fields in situ in a non-invasive way. It becomes even more difficult if the mechanical properties of the material are unknow

Xinyu Fu, Valeria Krzhizhanovskaya, Alexey Yakovlev, Sergey Kovalchuk

The optimisation in the ambulance dispatching process is significant for patients who need early treatments. However, the problem of dynamic ambulance redeployment for destination hospital selection has rarely been investigated. The paper proposes an approach to model and simulate the ambulance dispatching process in multi-agents healthcare environments of l

Sariel Har-Peled, Eliot Wong Robson

The intersection graph induced by a set $\Disks$ of $n$ disks can be dense. It is thus natural to try and sparsify it, while preserving connectivity. Unfortunately, sparse graphs can always be made disconnected by removing a small number of vertices. In this work, we present a sparsification algorithm that maintains connectivity between two disks in the comp

Makan Zamanipour

For the Internet-of-unmanned aerial vehicles (UAVs) some challenges in broadcasting and from new points of view are explored. In this paper, first, we investigate a single broadcast transceiver. From a control of noisy-channel viewpoint, we consider: (\textit{i}) Alice sends $\mathcal{X}$ to Bob as more \textcolor{black}{efficient} as possible while she wish

Zheng-Xin Yong, Patrick D. Watson, Tiago Timponi Torrent, Oliver Czulo

Frame shift is a cross-linguistic phenomenon in translation which results in corresponding pairs of linguistic material evoking different frames. The ability to predict frame shifts enables automatic creation of multilingual FrameNets through annotation projection. Here, we propose the Frame Shift Prediction task and demonstrate that graph attention networks

Anthony GX-Chen, Veronica Chelu, Blake A. Richards, Joelle Pineau

Estimating value functions is a core component of reinforcement learning algorithms. Temporal difference (TD) learning algorithms use bootstrapping, i.e. they update the value function toward a learning target using value estimates at subsequent time-steps. Alternatively, the value function can be updated toward a learning target constructed by separately pr

D. J. Zamora, C. Tsallis

We analyze the thermodynamical consistency of entropic-force cosmological models. Our analysis is based on a generalized entropy scaling with an arbitrary power of the Hubble radius. The Bekenstein-Hawking entropy, proportional to the area, and the nonadditive $S_{δ=3/2}$-entropy, proportional to the volume, are particular cases. One of the points to be solv

Deniz Gurevin, Chenglu Jin, Phuong Ha Nguyen, Omer Khan

Recent years have witnessed a trend of secure processor design in both academia and industry. Secure processors with hardware-enforced isolation can be a solid foundation of cloud computation in the future. However, due to recent side-channel attacks, the commercial secure processors failed to deliver the promises of a secure isolated execution environment.

Makan Zamanipour

We analyse the common information problem for the generalised Gray-Wyner problem. We aim to explore the problem and solution in relation to the non-orthogonality among the source decoders' components. We consider a simple networked control system consisting of 2 groups of users: (i) one sender or Observer named Alice; and (ii) a group of multiple receive

Mehdi SadeghiBakhi, Hamidreza Pourreza, Hamidreza Mahyar

Objective: Multiple Sclerosis (MS) is an autoimmune, and demyelinating disease that leads to lesions in the central nervous system. This disease can be tracked and diagnosed using Magnetic Resonance Imaging (MRI). Up to now a multitude of multimodality automatic biomedical approaches is used to segment lesions which are not beneficial for patients in terms o

Bingfan Zhang, Jordan Weil, Antonio Beita Guerra, Pramir Maharjan

Environmental temperature (ET) often changes the nutrient intake/output for layers. Changing feed formulations based on ET may need to be utilized to obtain optimum performance, shell quality and bone status. This study was conducted to investigate the effects of temperature, Ca intake, non-phytate P (NPP) intake and in vitro limestone solubility (LS) on egg

Jiangbang Liu, Song Bo, Benjamin Decardi-Nelson, Jinfeng Liu

Economic model predictive control and tracking model predictive control are two popular advanced process control strategies used in various of fields. Nevertheless, which one should be chosen to achieve better performance in the presence of noise is uncertain when designing a control system. To this end, a sensitivity-based performance assessment approach is

Mehdi Soleimanifar, John Wright

Devising schemes for testing the amount of entanglement in quantum systems has played a crucial role in quantum computing and information theory. Here, we study the problem of testing whether an unknown state $|ψ\rangle$ is a matrix product state (MPS) in the property testing model. MPS are a class of physically-relevant quantum states which arise in the stu

S. Sivertsson, J. I. Read, H. Silverwood, P. F. de Salas

The density of dark matter near the Sun is important for experiments hunting for dark matter particles in the laboratory, and for constraining the local shape of the Milky Way's dark matter halo. Estimates to date have typically assumed that the Milky Way's stellar disc is axisymmetric and in a steady-state. Yet the Milky Way disc is neither, exhibit

J. S. Inca, D. A. Martinez, C. Vilchez

Background and Objective: Several studies confirm that the age of hens has a tremendous impact on external and internal egg quality characteristics. Egg production could be at serious risk if egg quality characteristics and age of hens are not seriously considered. This study was conducted to analyze the phenotypic correlations between some internal and exte

Diana Kim, Ahmed Elgammal, Marian Mazzone

We present a machine learning system that can quantify fine art paintings with a set of visual elements and principles of art. This formal analysis is fundamental for understanding art, but developing such a system is challenging. Paintings have high visual complexities, but it is also difficult to collect enough training data with direct labels. To resolve

Diego A. Martinez, Carol L. Ponce-de-Leon, Carlos Vilchez

Background and Objective: In the current study, we sought to determine the value of a meta-analysis to improve decision-making processes related to nutrition in the poultry industry. To this end, nine commercial size experiments were conducted to test the effect of a phytogenic feed additive and three approaches were applied to the data. Materials and Method

Kavya Kopparapu, Edgar A. Duéñez-Guzmán, Jayd Matyas, Alexander Sasha Vezhnevets

A key challenge in the study of multiagent cooperation is the need for individual agents not only to cooperate effectively, but to decide with whom to cooperate. This is particularly critical in situations when other agents have hidden, possibly misaligned motivations and goals. Social deduction games offer an avenue to study how individuals might learn to s

Benjamin Decardi-Nelson, Jinfeng Liu

Several studies have reported the importance of optimally operating the absorption column in a post-combustion CO2 capture (PCC) plant. It has been demonstrated in our previous work how economic Model Predictive Control (EMPC) has a great potential to improve the operation of the PCC plant. However, the use of a general economic objective such as maximizing

John Ross

We study the isoperimetric problem on $\mathbb{R}^1$ with a prescribed density function $f$ that affects how area and perimeter are measured. We examine density functions that are symmetric, radially increasing, and satisfy two additional conditions: they have a point of zero density (at the origin), and they satisfy a "log-concavity" requirement $\l

Kowshik Thopalli, Jayaraman J Thiagarajan, Rushil Anirudh, Pavan K Turaga

Unsupervised domain adaptation (UDA) aims to transfer and adapt knowledge from a labeled source domain to an unlabeled target domain. Traditionally, subspace-based methods form an important class of solutions to this problem. Despite their mathematical elegance and tractability, these methods are often found to be ineffective at producing domain-invariant fe

Claudio Fantinuoli, Giulia Marchesini, David Landan, Lukas Horak

High-quality human interpretation requires linguistic and factual preparation as well as the ability to retrieve information in real-time. This situation becomes particularly relevant in the context of remote simultaneous interpreting (RSI) where time-to-event may be short, posing new challenges to professional interpreters and their commitment to delivering

A. R. Gomes-Júnior, B. E. Morgado, G. Benedetti-Rossi, R. C. Boufleur

The stellar occultation technique provides competitive accuracy in determining the sizes, shapes, astrometry, etc., of the occulting body, comparable to in-situ observations by spacecraft. With the increase in the number of known Solar System objects expected from the LSST, the highly precise astrometric catalogues, such as Gaia, and the improvement of ephem

Beth Bjorkman, Chassidy Bozeman, Daniela Ferrero, Mary Flagg

The study of token addition and removal and token jumping reconfiguration graphs for power domination is initiated. Some results established here can be extended by applying the methods used for power domination to reconfiguration graphs for other parameters such as domination and zero forcing, so these results are first established in a universal framework.

Marc W. Howard

The idea that memory behavior relies on a gradually-changing internal state has a long history in mathematical psychology. This chapter traces this line of thought from statistical learning theory in the 1950s, through distributed memory models in the latter part of the 20th century and early part of the 21st century through to modern models based on a scale

Mark Elin, Fiana Jacobzon

In this note we present a remark on the paper "On the coefficient inequalities for a class of holomorphic mappings associated with spirallike mappings in several complex variables" by Y.~Lai and Q.~Xu \cite{LX} published recently in the journal {\it Results in Mathematics}. We show that one of the theorems in \cite{LX} concerning the finite-dimension

W. J. Yang, K. M. Menten, A. Y. Yang, F. Wyrowski

Gravitational collapse is one of the most important processes in high-mass star formation. Compared with the classic blue-skewed profiles, redshifted absorption against continuum emission is a more reliable method to detect inward motions within high-mass star formation regions. We aim to test if methanol transitions can be used to trace infall motions withi

Raghav G. Jha

We study the $q$-state Potts models on a cubic lattice in the thermodynamic limit using tensor renormalization group transformations with the triad approximation. By computing the thermodynamic potentials, we locate the first-order phase transitions for $10 < q \le 20$ which has not been explored using any method. We also examine the efficiency of the triad

Tom Seccull

The Jupiter Trojan asteroid 128383 (2004 JW52) was recently reported to have optical colors that are incongruous with its dynamical class. New and archival observations show that this is not the case. This is a reminder that we must always rule out the possibility that the Point Spread Function (PSF) of a minor planet is blended with that of a background sid

Matthias von Davier, Lillian Tyack, Lale Khorramdel

Automated scoring of free drawings or images as responses has yet to be utilized in large-scale assessments of student achievement. In this study, we propose artificial neural networks to classify these types of graphical responses from a computer based international mathematics and science assessment. We are comparing classification accuracy of convolutiona

Cheng Zhan, Licheng Zhang, Xin Zhao, Chang-Chun Lee

Over the year, people have been using deep learning to tackle inversion problems, and we see the framework has been applied to build relationship between recording wavefield and velocity (Yang et al., 2016). Here we will extend the work from 2 perspectives, one is deriving a more appropriate loss function, as we now, pixel-2-pixel comparison might not be the

Linyi Yang, Jiazheng Li, Ruihai Dong, Yue Zhang

Financial forecasting has been an important and active area of machine learning research because of the challenges it presents and the potential rewards that even minor improvements in prediction accuracy or forecasting may entail. Traditionally, financial forecasting has heavily relied on quantitative indicators and metrics derived from structured financial

Natalia Osorio-Clavijo, Omaira González-Martín, Sebastián F. Sánchez-Sánchez, Donaji Esparza-Arredondo

According to theory, the torus of active galactic nuclei (AGN) is sustained from a wind coming off the accretion disk, and for low efficient AGN, it has been proposed that such structure disappears. However, the exact conditions for its disappearance remain unclear. This can be studied throughout the reflection component at X-rays, which is associated with d

Hui Chen, Tai-Peng Tsai, Ting Zhang

In this note, a new local regularity criteria for the axisymmetric solutions to the 3D Navier--Stokes equations is investigated. It is slightly supercritical and implies an upper bound for the oscillation of $Γ=r u^θ$: for any $0< τ<1$, there exists a constant $c>0$, $$ |Γ(r,x_{3},t)|\leq N e^{-c\, |\ln r|^τ},\ 0<r\leq \frac{1}{4}. $$

Edward Nathan, Adam Ingram, Jeroen Homan, Daniela Huppenkothen

Quasi-periodic oscillations (QPOs) are often present in the X-ray flux from accreting stellar-mass black holes (BHs). If they are due to relativistic (Lense-Thirring) precession of an inner accretion flow which is misaligned with the disc, the iron emission line caused by irradiation of the disc by the inner flow will rock systematically between red and blue

Tiago C. Barbosa, Andreij C. Gadelha, Douglas A. A. Ohlberg, Kenji Watanabe

In this work, we study the Raman spectra of twisted bilayer graphene samples as a function of their twist-angles ($θ$), ranging from 0.03$^\circ$ to 3.40$^\circ$, where local $θ$ are determined by analysis of their associated moire superlattices, as imaged by scanning microwave impedance microscopy. Three standard excitation laser lines are used (457, 532, a

Xinliang Lyu, Christina Daniel, James K. Freericks

We generalize Schroedinger&#39;s factorization method for Hydrogen from the conventional separation into angular and radial coordinates to a Cartesian-based factorization. Unique to this approach, is the fact that the Hamiltonian is represented as a sum over factorizations in terms of coupled operators that depend on the coordinates and momenta in each Carte

Carlos G. Escudero, Arianna Cortesi, Favio R. Faifer, Leandro A. Sesto

NGC 4382 is a merger-remnant galaxy that has been classified as morphological type E2, S0, and even Sa. In this work, we performed a photometric and spectroscopic analysis of the globular cluster (GC) system of this peculiar galaxy in order to provide additional information about its history. We used a combination of photometric data in different filters, an

Eitan Frachtenberg, Rhody D. Kaner

The gender gap in computer science (CS) research is a well-studied problem, with an estimated ratio of 15%--30% women researchers. However, far less is known about gender representation in specific fields within CS. Here, we investigate the gender gap in one large field, computer systems. To this end, we combined data from 53 leading systems conferences with

Hunmin Lee, Jaya Krishna Mandivarapu, Nahom Ogbazghi, Yingshu Li

Capacitive sensing is a prominent technology that is cost-effective and low power consuming with fast recognition speed compared to existing sensing systems. On account of these advantages, Capacitive sensing has been widely studied and commercialized in the domains of touch sensing, localization, existence detection, and contact sensing interface applicatio

Sudev Pradhan, Amlandeep Nayak, Sritam Kumar Satpathy, Tanmaya Shree Behera

The one-dimensional Ising model with its connections to several physical concepts plays a vital role in comprehension of several principles, phenomena and numerical methods. The Hamiltonian of a coupled one-dimensional dissipative spin system in the presence of magnetic field can be obtained from the Ising model. We simulate the above Hamiltonian by designin

Kevin Patel, Diptesh Kanojia, Pushpak Bhattacharyya

Wordnets are rich lexico-semantic resources. Linked wordnets are extensions of wordnets, which link similar concepts in wordnets of different languages. Such resources are extremely useful in many Natural Language Processing (NLP) applications, primarily those based on knowledge-based approaches. In such approaches, these resources are considered as gold sta

Zhiyu Lei, Bolun Hu, Xingbo Zhao

We study the electron-positron pair production process in strong background electric fields with spatio-temporal inhomogeneity in the time-dependent Basis Light-front Quantization approach. We calculate the observables such as the invariant mass and the longitudinal momentum distribution of the produced pairs as functions of evolution time and compare the va

John Alex, Keith Hall, Donald Metzler

We argue that current IR metrics, modeled on optimizing user experience, measure too narrow a portion of the IR space. If IR systems are weak, these metrics undersample or completely filter out the deeper documents that need improvement. If IR systems are relatively strong, these metrics undersample deeper relevant documents that could underpin even stronger

Vishal Katariya

The aim of this thesis is to develop a theoretical framework to study parameter estimation of quantum channels. We study the task of estimating unknown parameters encoded in a channel in the sequential setting. A sequential strategy is the most general way to use a channel multiple times. Our goal is to establish lower bounds (called Cramer-Rao bounds) on th

Niladri Modak, Sayantan Das, Priyanuj Bordoloi, Nirmalya Ghosh

We demonstrate an intriguing giant optical beam shift in a tilted polarizer system analogous to the Imbert-Fedorov shift in partial reflection around the Brewster&#39;s angle of incidence. We explain this giant shift using a generalized theoretical treatment for beam shift in a tilted uniaxial anisotropic material incorporating the three-dimensional orientat

Mireille Louys, Laurent Michel, François Bonnarel, Joann Vetter

With the success and widespread of the IVOA Table Access Protocol (1) for discovering and querying tabular data in astronomy, more than one hundred of TAP services exposing altogether 22 thousands of tables are accessible from the IVOA Registries at the time of writing. Currently the TAP protocol presents table data and metadata via a {TAP\_SCHEMA} describin

Antonio Finozzi, Francesco Sanfedino, Daniel Alazard

Modern and future high precision pointing space missions face increasingly high challenges related to the widespread use of large flexible structures. The development of new modeling tools which are able to account for the multidisciplinary nature of this problem becomes extremely relevant in order to meet both structure and control performance criteria. Thi

S. D. Raducan, M. Jutzi, T. M. Davison, M. E. DeCoster

The DART spacecraft will impact Didymos&#39;s secondary, Dimorphos, at the end of 2022 and cause a change in the orbital period of the secondary. For simplicity, most previous numerical simulations of the impact used a spherical projectile geometry to model the DART spacecraft. To investigate the effects of alternative, simple projectile geometries on the DA

Fabio Cuzzolin

Probability intervals are an attractive tool for reasoning under uncertainty. Unlike belief functions, though, they lack a natural probability transformation to be used for decision making in a utility theory framework. In this paper we propose the use of the intersection probability, a transform derived originally for belief functions in the framework of th

Juan Pons, Tabaré Gallardo

We study the secular evolution of a particle in deep mean motion resonance (MMR) with a planet in the planar elliptic restricted three body problem. We do not consider any restriction neither in the planet&#39;s eccentricity $e_p$ nor in the particle&#39;s eccentricity $e$. The methodology used is based on a semi-analytical model that consists on calculating

Alberto Bressan, Maria Teresa Chiri, Najmeh Salehi

Motivated by the control of invasive biological populations, we consider a class of optimization problems for moving sets $t\mapsto Ω(t)\subset\mathbb{R}^2$. Given an initial set $Ω_0$, the goal is to minimize the area of the contaminated set $Ω(t)$ over time, plus a cost related to the control effort. Here the control function is the inward normal speed alo

Paweł Weroński, Karolina Pałka

Surface roughness of particle monolayer is one of its fundamental characteristics, conventionally described in terms of power spectral density. We derive a general equation for this function and demonstrate its similarity to those applied in the theory of scattering. We validate our analytical results by comparison with numerical results for a system with pa

Pilar Paez-Guillan, Salvatore Siciliano, David A. Towers

In this paper we study the lattice of restricted subalgebras of a restricted Lie algebra. In particular, we consider those algebras in which this lattice is dually atomistic, lower or upper semimodular, or in which every restricted subalgebra is a quasi-ideal. The fact that there are one-dimensional subalgebras which are not restricted results in some of the

Marcin Aftowicz, Ievgen Kabin, Zoya Dyka, Peter Langendoerfer

Evaluation of the resistance of implemented cryptographic algorithms against SCA attacks, as well as detecting of SCA leakage sources at an early stage of the design process, is important for an efficient re-design of the implementation. Thus, effective SCA methods that do not depend on the key processed in the cryptographic operations are beneficially and c

Stav Ashur, Sariel Har-Peled

$\newcommand{\Emph}[1]{\it{#1}} \newcommand{\FF}{\mathcal{F}}\newcommand{\region}{\mathsf{r}}\newcommand{\restrictY}[2]{#1 \cap {#2}}$For a set of points $P \subseteq \mathbb{R}^2$, and a family of regions $\FF$, a $\Emph{local~t-spanner}$ of $P$, is a sparse graph $G$ over $P$, such that, for any region $\region \in \FF$, the subgraph restricted to $\region

Sunil K. Chebolu, Papa A. Sissokho

A vector $(v_{1}, v_{2}, \cdots, v_{d})$ in $\mathbb{Z}_n^{d}$ is said to be a zero-sum-free $d$-tuple if there is no non-empty subset of its components whose sum is zero in $\mathbb{Z}_n$. We denote the cardinality of this collection by $α_n^d$. We let $β_n^d$ denote the cardinality of the set of zero-sum-free tuples in $\mathbb{Z}_n^{d}$ where $\gcd(v_1, \

Samuel Gill, Solene Ulmer-Moll, Peter J. Wheatley, Daniel Bayliss

We are using precise radial velocities from CORALIE together with precision photometry from the Next Generation Transit Survey (NGTS) to follow up stars with single-transit events detected with the Transiting Exoplanet Survey Satellite (TESS). As part of this survey we identified a single transit on the star TIC-320687387, a bright (T=11.6) G-dwarf observed

Ahmed F. Abdelshafy, Filippo Capolino, Alexander Figotin

Abstract -- We construct an analytical model for the dispersion of the hot modes in a traveling wave tube (TWT) based on the Lagrangian field theory, upgrading its constants to be frequency-dependent. The frequency dependence of the parameters of the TWT slow wave structure (SWS) is recovered from full-wave simulations by standard software (e.g., CST). We ap

Marcin Aftowicz, Ievgen Kabin, Dan Klann, Yauhen Varabei

Side Channel Analysis attacks take advantage of the information leaked from the implementations of cryptographic algorithms. In this paper we describe two key revealing methods which are based on machine learning algorithms: K-means and PCA. We performed the attacks against ECDSA implementations without any prior knowledge about the key and achieved 100% acc

Ryley McConkey, Eugene Yee, Fue-Sang Lien

Despite well-known limitations of Reynolds-averaged Navier-Stokes (RANS) simulations, this methodology remains the most widely used tool for predicting many turbulent flows, due to computational efficiency. Machine learning is a promising approach to improve the accuracy of RANS simulations. One major area of improvement is using machine learning models to r

Samuil Stoychev, Hatice Gunes

Deep neural networks have proved hugely successful, achieving human-like performance on a variety of tasks. However, they are also computationally expensive, which has motivated the development of model compression techniques which reduce the resource consumption associated with deep learning models. Nevertheless, recent studies have suggested that model com

Avi Chawla

Reading Comprehension (RC) is a task of answering a question from a given passage or a set of passages. In the case of multiple passages, the task is to find the best possible answer to the question. Recent trials and experiments in the field of Natural Language Processing (NLP) have proved that machines can be provided with the ability to not only process t

Saurabh Kumar, Nishant Sinha

TryOnGAN is a recent virtual try-on approach, which generates highly realistic images and outperforms most previous approaches. In this article, we reproduce the TryOnGAN implementation and probe it along diverse angles: impact of transfer learning, variants of conditioning image generation with poses and properties of latent space interpolation. Some of the

Swaraja Salaskar, Diptesh Kanojia, Malhar Kulkarni

In today&#39;s digital world language technology has gained importance. Several softwares, have been developed and are available in the field of computational linguistics. Such tools play a crucial role in making classical language texts easily accessible. Some Indian philosophical schools have contributed towards various techniques of verbal cognition to an

G. Bertuccio, M. Ahangarianabhari, C. Graziani, D. Macera

We present a spectroscopic system constituted by a Silicon Drift Detector (SDD) coupled to a CMOS charge sensitive preamplifier, named SIRIO, specifically designed to reach ultimate low noise levels. The SDD, with an active area of 13 mm , has been manufactured by optimizing the production processes in order to reduce the anode current, successfully reaching

James P. Edwards

We give a pedagogical review to alternative, first quantised approaches to calculating graviton scattering amplitudes, giving an introduction to string inspired approaches and presenting more recent work based on the worldline formalism of quantum field theory that is motivated by these historic results. We describe how these first quantised techniques can g

Diptesh Kanojia, Malhar Kulkarni, Sayali Ghodekar, Eivind Kahrs

This paper describes additional aspects of a digital tool called the &#39;Textual History Tool&#39;. We describe its various salient features with special reference to those of its features that may help the philologist digitize commentaries and sub-commentaries on a text. This tool captures the historical evolution of a text through various temporal stages,

Paul C. Bressloff

In this paper we analyze the relaxation to steady-state of intracellular diffusion in a pair of cells with gap-junction coupling. Gap junctions are prevalent in most animal organs and tissues, providing a direct diffusion pathway for both electrical and chemical communication between cells. Most analytical models of gap junctions focus on the steady-state di

A. Deconto-Machado, R. A. Riffel, G. S. Ilha, S. B. Rembold

We analyse the kinematics of 170 AGN host galaxies as compared to those of a matched control sample of non-active galaxies from the MaNGA survey in order to characterise and estimate the extents of the Narrow Line Region (NLR) and of the kinematically disturbed region (KDR) by the AGN. We define the observed NLR radius as the farthest distance from the nucle

Ni Wang, Remco A. Verzijlbergh, Petra W. Heijnen, Paulien M. Herder

Investments into renewable energy are increasing rapidly around the world. Energy system models are able to provide insights into optimal investment capacities and thus are widely used to aid the long-term investment decision-making under an electricity market environment. Existing energy system models, however, fail to consider bilateral electricity markets

Farui Wang, Weizhe Zhang, Shichao Lai, Meng Hao

GPUs are widely used to accelerate the training of machine learning workloads. As modern machine learning models become increasingly larger, they require a longer time to train, leading to higher GPU energy consumption. This paper presents GPOEO, an online GPU energy optimization framework for machine learning training workloads. GPOEO dynamically determines

Euan J. Allen, Jacob F. F. Bulmer, Simon D. Small

This document explores how to make music using quantum computing algorithms. The text is an unedited pre-publication chapter which will appear in the book &#34;Quantum Computer Music&#34;, Miranda, E. R. (Editor). This chapters provides the background and specific details of a collaboration formed in 2021 between the Quantum Engineering Technology Labs - a q

Alexander Voigt

We compare different methods for the computation of the real dilogarithm regarding their ability for using instruction-level parallelism when executed on appropriate CPUs. As a result we present an instruction-level-aware method and compare it to existing implementations.

Paul C. Bressloff

Many processes in cell biology involve diffusion in a domain $Ω$ that contains a target $\calU$ whose boundary $\partial \calU$ is a chemically reactive surface. Such a target could represent a single reactive molecule, an intracellular compartment or a whole cell. Recently, a probabilistic framework for studying diffusion-mediated surface reactions has been