January 2022 arXiv papers — page 73

J. Ruiz Ruiz, F. I. Parra, V. H. Hall-Chen, N. Christen

A linear response, local model for the DBS amplitude applied to gyrokinetic simulations shows that radial correlation Doppler reflectometry measurements (RCDR, Schirmer et al., Plasma Phys. Control. Fusion 49 1019 (2007)) are not sensitive to the average turbulence radial correlation length, but to a correlation length that depends on the binormal wavenumber

Juni Schindler, Jonathan Clarke, Mauricio Barahona

From the perspective of human mobility, the COVID-19 pandemic constituted a natural experiment of enormous reach in space and time. Here, we analyse the inherent multiple scales of human mobility using Facebook Movement Maps collected before and during the first UK lockdown. First, we obtain the pre-lockdown UK mobility graph, and employ multiscale community

Wouter Castryck, Floris Vermeulen, Yongqiang Zhao

We give an explicit minimal graded free resolution, in terms of representations of the symmetric group $S_d$, of a Galois-theoretic configuration of $d$ points in $\mathbb{P}^{d-2}$ that was studied by Bhargava in the context of ring parametrizations. When applied to the geometric generic fiber of a simply branched degree $d$ cover of $\mathbb{P}^1$ by a rel

Kalifou René Traoré, Andrés Camero, Xiao Xiang Zhu

With the rapid rise of neural architecture search, the ability to understand its complexity from the perspective of a search algorithm is desirable. Recently, Traor\'e et al. have proposed the framework of Fitness Landscape Footprint to help describe and compare neural architecture search problems. It attempts at describing why a search strategy might be suc

Z. Sela

The JSJ decomposition encodes the automorphisms and the virtually cyclic splittings of a hyperbolic group. For general finitely presented groups, the JSJ decomposition encodes only their splittings. In this sequence of papers we study the automorphisms of a hierarchically hyperbolic group that satisfies some weak acylindricity conditions. To study these auto

Sören Bettels, Sojung Kim, Stefan Weber

We extend the scope of risk measures for which backtesting models are available by proposing a multinomial backtesting method for general distortion risk measures. The method relies on a stratification and randomization of risk levels. We illustrate the performance of our methods in numerical case studies.

Amir Dayan, Yi Huang, Alex Schuchinsky

Passive intermodulation (PIM) is a niggling phenomenon that debilitates performance of modern communications and navigation systems. PIM products interfere with the information signals and cause their nonlinear distortion. The sources and basic mechanisms of PIM were studied in literature but PIM remains a serious problem of signal integrity. In this paper,

Ozan Özdemir, Matthias Kerzel, Cornelius Weber, Jae Hee Lee

Human infants learn language while interacting with their environment in which their caregivers may describe the objects and actions they perform. Similar to human infants, artificial agents can learn language while interacting with their environment. In this work, first, we present a neural model that bidirectionally binds robot actions and their language d

Christian Bierlich, Smita Chakraborty, Gösta Gustafson, Leif Lönnblad

We revisit the recipe for hadron formation in the Lund string hadronization model. Given an incoming quark or quark-diquark pair, weights for hadron formation are updated to take hyperfine splitting effects arising from the mass difference between u, d-type and s-type quarks. We find that the procedure improves the description of hadron yields in $\mathrm{e}

Xiaoxiao Xu, Chen Yang, Qian Yu, Zhiwei Fang

We propose a general Variational Embedding Learning Framework (VELF) for alleviating the severe cold-start problem in CTR prediction. VELF addresses the cold start problem via alleviating over-fits caused by data-sparsity in two ways: learning probabilistic embedding, and incorporating trainable and regularized priors which utilize the rich side information

Hannah Price, Yidong Chong, Alexander Khanikaev, Henning Schomerus

Topological photonics seeks to control the behaviour of the light through the design of protected topological modes in photonic structures. While this approach originated from studying the behaviour of electrons in solid-state materials, it has since blossomed into a field that is at the very forefront of the search for new topological types of matter. This

Giacomo Meanti, Luigi Carratino, Ernesto De Vito, Lorenzo Rosasco

Kernel methods provide a principled approach to nonparametric learning. While their basic implementations scale poorly to large problems, recent advances showed that approximate solvers can efficiently handle massive datasets. A shortcoming of these solutions is that hyperparameter tuning is not taken care of, and left for the user to perform. Hyperparameter

Milad Vazan, Fatemeh Sadat Masoumi, Sepideh Saeedi Majd

Aspect-based sentiment analysis is of great importance and application because of its ability to identify all aspects discussed in the text. However, aspect-based sentiment analysis will be most effective when, in addition to identifying all the aspects discussed in the text, it can also identify their polarity. Most previous methods use the pipeline approac

Yehia Abd Alrahman, Shaun Azzopardi, Nir Piterman

Reconfigurable multi-agent systems consist of a set of autonomous agents, with integrated interaction capabilities that feature opportunistic interaction. Agents seemingly reconfigure their interactions interfaces by forming collectives, and interact based on mutual interests. Finding ways to design and analyse the behaviour of these systems is a vigorously

Elena Luna, Juan C. SanMiguel, José M. Martínez, Pablo Carballeira

Cross-camera image data association is essential for many multi-camera computer vision tasks, such as multi-camera pedestrian detection, multi-camera multi-target tracking, 3D pose estimation, etc. This association task is typically stated as a bipartite graph matching problem and often solved by applying minimum-cost flow techniques, which may be computatio

Iñigo Martinez, Elisabeth Viles, Igor G. Olaizola

In recent years, the data science community has pursued excellence and made significant research efforts to develop advanced analytics, focusing on solving technical problems at the expense of organizational and socio-technical challenges. According to previous surveys on the state of data science project management, there is a significant gap between techni

Pengfei Liu, Kun Li, Helen Meng

Emotion recognition is a challenging and actively-studied research area that plays a critical role in emotion-aware human-computer interaction systems. In a multimodal setting, temporal alignment between different modalities has not been well investigated yet. This paper presents a new model named as Gated Bidirectional Alignment Network (GBAN), which consis

Hua Yan, Jiaozi Wang, Wen-ge Wang

We study the long-time average of the reduced density matrix (RDM) of an $m$-level central system, which is locally coupled to a large environment, under an overall Schr\"{o}dinger evolution of the total system. We consider a class of interaction Hamiltonian, whose environmental part satisfies the so-called eigenstate thermalization hypothesis (ETH) ansatz w

David Cabezas, María Cueto-Avellaneda, Daisuke Hirota, Takeshi Miura

We prove that every commutative JB$^*$-triple satisfies the complex Mazur--Ulam property. Thanks to the representation theory, we can identify commutative JB$^*$-triples as spaces of complex-valued continuous functions on a principal $\mathbb{T}$-bundle $L$ in the form $$C_0^\mathbb{T}(L):=\{a\in C_0(L):a(\lambda t)=\lambda a(t)\text{ for every } (\lambda,t)

Oliver Tan

A supersequence over a finite set is a sequence that contains as subsequence all permutations of the set. This paper defines an infinite array of methods to create supersequences of decreasing lengths. This yields the shortest known supersequences over larger sets. It also provides the best results asymptotically. It is based on a general proof using a new p

J. Borreguero, F. Galve, J. M. Algarín, J. M. Benlloch

Purpose: To expand the capabilities of Zero Echo Time (ZTE) pulse sequences with a slice selection method suitable for the shortest-lived tissues in the body. Methods: We introduce two new sequences that integrate spin-locking pulses into standard ZTE imaging to achieve slice selection: one for moderately short $T_2$ (DiSLoP), the other for ultra-short $T_2$

Xu Chen, Yahong Han, Xiaohan Wang, Yifan Sun

Reducing redundancy is crucial for improving the efficiency of video recognition models. An effective approach is to select informative content from the holistic video, yielding a popular family of dynamic video recognition methods. However, existing dynamic methods focus on either temporal or spatial selection independently while neglecting a reality that t

M. Sahnawaz Alam, B. Prasanna Venkatesh

We propose and analyze the theoretical model for a two-stroke quantum heat engine with one of the heat baths replaced by a non-selective quantum measurement. We show that the engine's invariant reference state depends on whether the cycle is monitored or unmonitored via diagnostic measurements to determine the engine's work output. We explore in detail the a

Justyna Czestochowska, Kristina Gligoric, Maxime Peyrard, Yann Mentha

Emojis come with prepacked semantics making them great candidates to create new forms of more accessible communications. Yet, little is known about how much of this emojis semantic is agreed upon by humans, outside of textual contexts. Thus, we collected a crowdsourced dataset of one-word emoji descriptions for 1,289 emojis presented to participants with no

Matilde Fiore, Lilla Koloszar, Miguel Alfonso Mendez, Matthieu Duponcheel

Liquid metals play a central role in new generation liquid metal cooled nuclear reactors, for which numerical investigations require the use of appropriate thermal turbulence models for low Prandtl number fluids. Given the limitations of traditional modelling approaches and the increasing availability of high-fidelity data for this class of fluids, we propos

Yuhan Wang, Youlong Wu

Coded distributed computing can reduce the communication load for distributed computing systems by introducing redundant computation and creating multicasting opportunities. However, the existing schemes require delicate data placement and output function assignment, which is not feasible when distributed nodes fetch data without the orchestration of a maste

Jonas B. Profe, Dante M. Kennes

Describing the emergence of phases of condensed matter is one of the central challenges in physics. For this purpose many numerical and analytical methods have been developed, each with their own strengths and limitations. The functional renormalization group is one of these methods bridging between efficiency and accuracy. In this paper we derive a new trun

Jinrae Kim, Youdan Kim

Parameterized max-affine (PMA) and parameterized log-sum-exp (PLSE) networks are proposed for general decision-making problems. The proposed approximators generalize existing convex approximators, namely, max-affine (MA) and log-sum-exp (LSE) networks, by considering function arguments of condition and decision variables and replacing the network parameters

Sharu Theresa Jose, Osvaldo Simeone

A key component of a quantum machine learning model operating on classical inputs is the design of an embedding circuit mapping inputs to a quantum state. This paper studies a transfer learning setting in which classical-to-quantum embedding is carried out by an arbitrary parametric quantum circuit that is pre-trained based on data from a source task. At run

Sven Zschocke

The light trajectory in the gravitational field of one body at rest with monopole and quadrupole structure is determined in the second post-Newtonian (2PN) approximation. The terms in the geodesic equation for light rays are separated into time-independent tensorial coefficients and four kind of time-dependent scalar functions. Accordingly, the first and sec

Yifei Xu, Zhigang Cao, Zonghao Yuan, Yuanqiang Cai

Filtering properties of locally resonant periodic foundations (LRPFs) have inspired an innovative direction towards the mitigation of structural vibrations. To mitigate the structure-borne vibrations from subways, this study proposes an LRPF equipped with a negative stiffness device connecting the resonator and primary structure. The proposed LRPF can exhibi

Guo-Jing Tang, Xin-Tao He, Fu-Long Shi, Jian-Wei Liu

The recent research of topological photonics has not only proposed and realized novel topological phenomena such as one-way broadband propagation and robust transport of light, but also designed and fabricated photonic devices with high-performance indexes which are immune to fabrication errors such as defects or disorders. Photonic crystals, which are perio

Marco Di Giovanni, Francesco Pierri, Christopher Torres-Lugo, Marco Brambilla

Despite the increasing limitations for unvaccinated people, in many European countries there is still a non-negligible fraction of individuals who refuse to get vaccinated against SARS-CoV-2, undermining governmental efforts to eradicate the virus. We study the role of online social media in influencing individuals' opinion towards getting vaccinated by desi

Alberto Gubbiotti, Mauro Chinappi, Carlo Massimo Casciola

Electrohydrodynamics is crucial in many nanofluidic and biotechnological applications. In such small scales, the complexity due to the coupling of fluid dynamics with the dynamics of ions is increased by the relevance of thermal fluctuations. Here, we present a mesoscale method based on the Dissipative Particle Dynamics (DPD) model of the fluid. Two scalar q

Ka Ian Im, In Kio Choi, Pak Kio Lei, Hou Fai Chan

We proposed a mathematical model for designing the layout diagram of stand locations at the Macao Food Festival. The optimal layout diagram may be defined in such a way that, while requiring the distance between every pair of stands should not be too far away from each other, the crowd control is well managed so that people may patronize stands more effectiv

Zhiqiu Lin, Jia Shi, Deepak Pathak, Deva Ramanan

Continual learning (CL) is widely regarded as crucial challenge for lifelong AI. However, existing CL benchmarks, e.g. Permuted-MNIST and Split-CIFAR, make use of artificial temporal variation and do not align with or generalize to the real-world. In this paper, we introduce CLEAR, the first continual image classification benchmark dataset with a natural tem

Rustem Ospanov, Changqing Feng, Wenhao Dong, Wenhao Feng

This paper reports on the development of a resource-efficient FPGA-based neural network regression model for potential applications in the future hardware muon trigger system of the ATLAS experiment at the Large Hadron Collider (LHC). Effective real-time selection of muon candidates is the cornerstone of the ATLAS physics programme. With the planned ATLAS up

Kuangchao Wu, Wen-Bin Shen, Xiao Sun, Chenghui Cai

According to general relativity theory (GRT), by comparing the frequencies between two precise clocks at two different stations, the gravity potential (geopotential) difference between the two stations can be determined due to the gravity frequency shift effect. Here, we provide experimental results of geopotential difference determination based on frequency

Anik Jacobsen, Salar Mohtaj, Sebastian Möller

Vocabulary learning is vital to foreign language learning. Correct and adequate feedback is essential to successful and satisfying vocabulary training. However, many vocabulary and language evaluation systems perform on simple rules and do not account for real-life user learning data. This work introduces Multi-Language Vocabulary Evaluation Data Set (MuLVE)

Sarita Bugalia, Jai Prakash Tripathi, Hao Wang

Since December 2020, variants of COVID-19 (especially Delta and Omicron) appeared with different characteristics that influenced death and transmissibility emerged around the world. To address the novel dynamics of the disease, we propose a dynamical model of two strains, namely native and mutant, transmission dynamics with mutation and imperfect vaccination

Manuel Cortés-Izurdiaga, Pedro A. Guil Asensio

Two elements $a,b$ in a ring $R$ form a right coprime pair, written $\langle a,b\rangle$, if $aR+bR=R$. Right coprime pairs have shown to be quite useful in the study of left cotorsion or exchange rings. In this paper, we define the class of strongly right exchange rings in terms of descending chains of them. We show that they are semiregular and that this c

Giovanni Mana, Stephan Schlamminger

With the redefinition of the international system of units, the value of the Planck constant was fixed, similarly to the values of the unperturbed ground state hyperfine transition frequency of the $^{133}$Cs atom, speed of light in vacuum. Theoretically and differently from the past, the kilogram is now explicitly defined as the unit of inertial mass. Exper

Daniel Vargas-Montoya

The notion of strong Frobenius structure is classically studied in the theory of $p$-adic differential operators. In the present work, we introduce a new definition of the notion of strong Frobenius structure for $q$-difference operators. The relevance of this definition is supported by two main results. The first one deals with \emph{confluence}. We show th

Yann Thanwerdas, Xavier Pennec

In contrast to SPD matrices, few tools exist to perform Riemannian statistics on the open elliptope of full-rank correlation matrices. The quotient-affine metric was recently built as the quotient of the affine-invariant metric by the congruence action of positive diagonal matrices. The space of SPD matrices had always been thought of as a Riemannian homogen

Li You, Xiaoyu Qiang, Ke-Xin Li, Christos G. Tsinos

Massive multiple-input multiple-output (MIMO) is promising for low earth orbit (LEO) satellite communications due to the potential in enhancing the spectral efficiency. However, the conventional fully digital precoding architectures might lead to high implementation complexity and energy consumption. In this paper, hybrid analog/digital precoding solutions a

Susumu Ito, Nariya Uchida

Fish exhibit various patterns of collective motion, in which individual fish sense the gravitational field and tend to move horizonally. We study the effect of gravity on the collective patterns by incorporating suppression of vertical motion in an agent-based model. The gravitational factor induces a tornado which is a vertically and highly elongated form o

Takeshi Fukuyama, Yukihiro Mimura, Yuichi Uesaka

The constructions of the new high-intensity muon beamlines are progressing in facilities around the world, and new physics searches related to the muons are expected. The facilities can observe the transverse positron polarization of the polarized $\mu^+$ decay to test the standard model. The transition of muonium into antimuonium (Mu-to-$\bar{\text{Mu}}$ tr

Paweł Przybyłowicz, Verena Schwarz, Alexander Steinicke, Michaela Szölgyenyi

In this paper we show the existence of a universal Skorohod measurable functional representation for a large class of semimartingale-driven stochastic differential equations. For this we prove that paths of the strong solutions of stochastic differential equations can be written as measurable functions of the paths of their driving processes into the space o

Olivier Coudray, Christine Keribin, Pascal Massart, Patrick Pamphile

Positive-unlabeled learning (PU learning) is known as a special case of semi-supervised binary classification where only a fraction of positive examples are labeled. The challenge is then to find the correct classifier despite this lack of information. Recently, new methodologies have been introduced to address the case where the probability of being labeled

Shumpei Kubosawa, Takashi Onishi, Makoto Sakahara, Yoshimasa Tsuruoka

The number of railway service disruptions has been increasing owing to intensification of natural disasters. In addition, abrupt changes in social situations such as the COVID-19 pandemic require railway companies to modify the traffic schedule frequently. Therefore, automatic support for optimal scheduling is anticipated. In this study, an automatic railway

Nicolas Six, Nicolas Herbaut, Camille Salinesi

Designing blockchain-based applications is a tedious task. Compared to traditional software engineering, software architects cannot rely on previous experiences or proven practices, often formalized as software patterns. Also, the selection of an adequate blockchain technology is difficult without deep knowledge of the technology. This paper introduces Harmo

Thomas F Burns, Robert Tang

Gridworlds have been long-utilised in AI research, particularly in reinforcement learning, as they provide simple yet scalable models for many real-world applications such as robot navigation, emergent behaviour, and operations research. We initiate a study of gridworlds using the mathematical framework of reconfigurable systems and state complexes due to Ab

Olivier Augereau, Gabriel Brocheton, Pedro Paulo Do Prado Neto

The cognitive load can be used to assess if someone is struggling while performing a task. It can be used in many different situations such as in driving, piloting, studying, playing, working, etc. This information can help to design better systems and even to create interactive systems that can be aware of the user's cognitive load and adapt itself to the u

Henrik Parsamyan, Khachik Sahakyan, Khachatur Nerkararyan

The optical bistability caused by the coupling between modes of the parallel-plate waveguide and a nonlinear hemicylindrical crystal is studied using theoretical and numerical analysis. In such a system a waveguide channel is parallelly coupled to whispering gallery modes of a hemicylindrical microresonator ensuring bistable behaviour at input intensities of

Simon Bicaïs, Jean-Baptiste Doré, Majed Saad, Mohammad Alawieh

Wireless communication in millimetre wave bands, namely above 20 GHz and up to 300 GHz, is foreseen as a key enabler technology for the next generation of wireless systems. The huge available bandwidth is contemplated to achieve high data-rate wireless communications, and hence, to fulfil the requirements of future wireless networks. In this paper, we discus

Yu. M. Shabelski, A. G. Shuvaev

The differential elastic cross sections of $^{12}$C -- $^{12}$C and $^{11}$Li -- $^{12}$C nuclei are calculated in the complete Glauber theory. The role of the possible correlations connected to the shell effects in $^{11}$Li nucleus is considered.

Milan Janjic

Results of this paper concern $n$-determinants which we defined in the paper \cite{jan}. In the paper \cite{jabo}, $2$-determinants are considered. In this paper, we extend results from \cite{jabo} on $n$-determinants by proving that Cassini, d'Ocagne, Catalan and Vajda identities may be extended to hold for $n$-step Fibonacci numbers.

Lukas Hedegaard, Arian Bakhtiarnia, Alexandros Iosifidis

Transformers in their common form are inherently limited to operate on whole token sequences rather than on one token at a time. Consequently, their use during online inference on time-series data entails considerable redundancy due to the overlap in successive token sequences. In this work, we propose novel formulations of the Scaled Dot-Product Attention,

Hideyuki Muneta, Ryoichi Horisaki, Yohei Nishizaki, Makoto Naruse

In this paper, we present a method for single-shot blind deconvolution incorporating a coded aperture (CA). In this method, we utilize the CA, inserted on the pupil plane, as support constraints in blind deconvolution. Not only an object but also a point spread function of turbulence are estimated from a single captured image by a reconstruction algorithm wi

Célia Borlido, Anna Laura Suarez

We lay down the foundations for a pointfree theory of Pervin spaces. A Pervin space is a set equipped with a bounded sublattice of its powerset, and it is known that these objects characterize those quasi-uniform spaces that are transitive and totally bounded. The pointfree notion of a Pervin space, which we call Frith frame, consists of a frame equipped wit

Meng Zeng, Dong-Hui Xu, Zi-Ming Wang, Lun-Hui Hu

An unconventional superconductor is distinguished with two types of gap functions: unitary and non-unitary. This core subject has been concentrated on purely spin-triplet or singlet-triplet mixed superconductors. However, the generalization to a purely spin-singlet superconductor has remained primarily of theoretical interest, which requires at least a multi

Lars Bojer Madsen

The limit of decreasing laser frequency can not be considered independently from nondipole effects due to increase in the laser-induced continuum electron speed in this limit. Therefore, in this work, tunneling ionization in the adiabatic limit is considered for an effective field that includes effects beyond the electric-dipole term to first order in $1/c$,

Yifan Liu, Zhisen Zhang, Panpan Yu, Yijing Wu

Multiplexing multiple orbital angular momentum (OAM) modes of light has the potential to increase data capacity in optical communication. However, the distribution of such modes over long distances remains challenging. Free-space transmission is strongly influenced by atmospheric turbulence and light scattering, while the wave distortion induced by the mode

Namhoon Cho, Hyo-Sang Shin

This study presents a policy optimisation framework for structured nonlinear control of continuous-time (deterministic) dynamic systems. The proposed approach prescribes a structure for the controller based on relevant scientific knowledge (such as Lyapunov stability theory or domain experiences) while considering the tunable elements inside the given struct

Hans Triebel

The composition of the Fourier transform in $\mathbb{R}^n$ with a suitable pseudodifferential operator is called a Fourier operator. It is compact in appropriate function spaces. The paper deals with its spectral theory. This is based on mapping properties of the Fourier transform as developed in a preceding paper and related assertions for pseudodifferentia

Tianyi Xie, Liucheng Liao, Cheng Bi, Benlai Tang

The task of few-shot visual dubbing focuses on synchronizing the lip movements with arbitrary speech input for any talking head video. Albeit moderate improvements in current approaches, they commonly require high-quality homologous data sources of videos and audios, thus causing the failure to leverage heterogeneous data sufficiently. In practice, it may be

Florian Thamm, Felix Denzinger, Leonhard Rist, Celia Martin Vicario

In this report we want to present our method and results for the Carotid Artery Vessel Wall Segmentation Challenge. We propose an image-based pipeline utilizing the U-Net architecture and location priors to solve the segmentation problem at hand.

Yishu Huang, Jun Zheng, Bingcheng Pan, Lijia Song

Optical modulators are required to have high modulation bandwidths and a compact footprint. In this paper we experimentally demonstrate a novel Si/In$_2$O$_3$ hybrid plasmonic waveguide modulator, which is realized by an asymmetric directional coupler (ADC) consisting of a silicon photonic waveguide and a Si/In$_2$O$_3$ hybrid plasmonic waveguide. The optica

Jingqing Ruan, Yali Du, Xuantang Xiong, Dengpeng Xing

Many real-world scenarios involve a team of agents that have to coordinate their policies to achieve a shared goal. Previous studies mainly focus on decentralized control to maximize a common reward and barely consider the coordination among control policies, which is critical in dynamic and complicated environments. In this work, we propose factorizing the

Steven W. Gagniere, Yushan Han, Yizhou Chen, David A. B. Hyde

The creation of a volumetric mesh representing the interior of an input polygonal mesh is a common requirement in graphics and computational mechanics applications. Most mesh creation techniques assume that the input surface is not self-intersecting. However, due to numerical and/or user error, input surfaces are commonly self-intersecting to some degree. Th

Jeremie S. Kim, Can Firtina, Meryem Banu Cavlak, Damla Senol Cali

A genome read data set can be quickly and efficiently remapped from one reference to another similar reference (e.g., between two reference versions or two similar species) using a variety of tools, e.g., the commonly-used CrossMap tool. With the explosion of available genomic data sets and references, high-performance remapping tools will be even more impor

Zizhao Zhang, Yifei Zhao, Guangda Huzhang

As a measure of the long-term contribution produced by customers in a service or product relationship, life-time value, or LTV, can more comprehensively find the optimal strategy for service delivery. However, it is challenging to accurately abstract the LTV scene, model it reasonably, and find the optimal solution. The current theories either cannot precise

Weijun Gao, Xuyang Lu, Chong Han, Zhi Chen

Terahertz (THz) communications have naturally promising physical layer security (PLS) performance in the angular domain due to the high directivity feature brought by the ultra-massive multiple-antenna techniques. However, traditional multiple-antenna techniques fail to combat eavesdroppers residing in the THz beam sector, even when the communication distanc

Jianrong Zhou, Kun He, Jiongzhi Zheng, Chu-Min Li

We propose a new and strengthened Branch-and-Bound (BnB) algorithm for the maximum common (connected) induced subgraph problem based on two new operators, Long-Short Memory (LSM) and Leaf vertex Union Match (LUM). Given two graphs for which we search for the maximum common (connected) induced subgraph, the first operator of LSM maintains a score for the bran

Ikboljon Sobirov, Otabek Nazarov, Hussain Alasmawi, Mohammad Yaqub

Cancer is one of the leading causes of death worldwide, and head and neck (H&N) cancer is amongst the most prevalent types. Positron emission tomography and computed tomography are used to detect, segment and quantify the tumor region. Clinically, tumor segmentation is extensively time-consuming and prone to error. Machine learning, and deep learning in part

Karthik K, Sowmya Kamath S

In clinical diagnosis, diagnostic images that are obtained from the scanning devices serve as preliminary evidence for further investigation in the process of delivering quality healthcare. However, often the medical image may contain fault artifacts, introduced due to noise, blur and faulty equipment. The reason for this may be the low-quality or older scan

Madhura Ghosh Dastidar, Gniewomir Sarbicki

We consider a subgroup of unitary transformations on a mode of light induced by a Mach-Zehnder Interferometer and an algebra of observables describing a photon-number detector proceeded by an interferometer. We explore the uncertainty principles between such observables and their usefulness in performing a Bell-like experiment to show a violation of the CHSH

Fatemeh Mohades Deilami, Hossein Sadr, Mojdeh Nazari

Personality can be defined as the combination of behavior, emotion, motivation, and thoughts that aim at describing various aspects of human behavior based on a few stable and measurable characteristics. Considering the fact that our personality has a remarkable influence in our daily life, automatic recognition of a person's personality attributes can provi

Doyup Lee, Sungwoong Kim, Ildoo Kim, Yeongjae Cheon

Consistency regularization on label predictions becomes a fundamental technique in semi-supervised learning, but it still requires a large number of training iterations for high performance. In this study, we analyze that the consistency regularization restricts the propagation of labeling information due to the exclusion of samples with unconfident pseudo-l

S. V. Kozyrev

The relationship between the Landau-Zener model (which describes transitions between energy levels for a time-dependent Hamiltonian) and non-secular master equations is discussed. This approach allows to describe the widely discussed in the literature on quantum photosynthesis resonance of the energy of the vibron and the difference of exciton energies for t

Yue Li, Zhi-Cheng He, Xinxing Yuan, Mengxiang Zhang

Along with the scaling of dimensions in quantum systems, transitions between the system's energy levels would become close in frequency, which are conventionally resolved by weak and lengthy pulses. Here, we extend and experimentally demonstrate analytically based swift quantum control techniques on a four-level trapped ion system, where we perform individua

Juri Belikov, Jaan Kalda

The COVID-19 pandemic triggered a question of how to measure and evaluate adequacy of the applied restrictions. Available studies propose various methods mainly grouped to statistical and machine learning techniques. The current paper joins this line of research by introducing a simple-yet-accurate linear regression model which eliminates effects of weekly c

Ayoob Salari, Mahyar Shirvanimoghaddam, Muhammad Basit Shahab, Reza Arablouei

We propose a joint channel estimation and signal detection approach for the uplink non-orthogonal multiple access (NOMA) using unsupervised machine learning. We apply a Gaussian mixture model (GMM) to cluster the received signals, and accordingly optimize the decision regions to enhance the symbol error rate (SER) performance. We show that, when the received

Yimin Huang, Xinyu Feng, Wanwan Wang, Hao He

Federated learning allows multiple participants to conduct joint modeling without disclosing their local data. Vertical federated learning (VFL) handles the situation where participants share the same ID space and different feature spaces. In most VFL frameworks, to protect the security and privacy of the participants' local data, a third party is needed to

Jin Cao, Chuanchang Zeng, Xiao-Ping Li, Maoyuan Wang

Novel fermions with relativistic linear dispersion can emerge as low-energy excitations in topological semimetal materials. Here, we show that the orbital moment contribution in the circular photomagnetic effect for these topological semimetals exhibit an unconventional $\omega^{-1}$ frequency scaling, leading to significantly enhanced response in the low fr

Zhuo Chen, Honglei Lang, Zhangju Liu

Given a Lie groupoid $\mathcal{G}$ over $M$, $A$ the tangent Lie algebroid of $\mathcal{G}$, and $\rho: A\rightarrow TM$ the anchor map, we provide a formula that decomposes an arbitrary multiplicative $k$-form $\Theta$ on $\mathcal{G}$ into two parts. The first part is $e$, a $1$-cocycle of $\mathfrak{J}\mathcal{G}$ valued in $\wedge^k T^*M$, and the second

Ibrahim Yildirim, Ertugrul Basar

One of the most critical aspects of enabling next-generation wireless technologies is developing an accurate and consistent channel model to be validated effectively with the help of real-world measurements. From this point of view, remarkable research has recently been conducted to model propagation channels involving the modification of the wireless propag

Pavan Dharanipragada, Semanti Dutta, Bala Sathiapalan

Recently, a method was described for deriving Holographic RG equation in $AdS_{D+1}$ space starting from an Exact RG equation of a $D$-dimensional boundary CFT (Sathiapalan, Sonoda, 2017). The evolution operator corresponding to the Exact RG equation was rewritten as a functional integral of a $D+1$ dimensional field theory in $AdS_{D+1}$ space. This method

ZhenZhe Ying, Zhuoer Xu, Zhifeng Li, Weiqiang Wang

Despite the success of deep learning in computer vision and natural language processing, Gradient Boosted Decision Tree (GBDT) is yet one of the most powerful tools for applications with tabular data such as e-commerce and FinTech. However, applying GBDT to multi-task learning is still a challenge. Unlike deep models that can jointly learn a shared latent re

Ling Chen, Miaomiao Dong

Nowadays, different types of context information are integrated into mobile messaging to increase expressiveness and awareness, including mobile device setting, location, activity, and heart rate. Due to low recognition accuracy, sometimes users cannot accurately infer others' status through activity awareness. Recently, activity recognition technology has a

N. D. Khanh, T. Nakajima, S. Hayami, S. Gao

Magnetic skyrmion is a topologically stable particle-like swirling spin texture potentially suitable for high-density information bit, which was first observed in noncentrosymmetric magnets with Dzyaloshinskii-Moriya interaction. Recently, nanometric skyrmion has also been discovered in centrosymmetric rare-earth compounds, and the identification of their sk

Xing Lin, Han Cai, Xiaohu Tang

In this paper, a new repair scheme for a modified construction of MDS codes is studied. The obtained repair scheme has optimal bandwidth for multiple failed nodes under the cooperative repair model. In addition, the repair scheme has relatively low access property, where the number of data accessed is less than two times the optimal value.

Xiaoyu Sun, Xiao Chen, Kui Liu, Sheng Wen

While extremely valuable to achieve advanced functions, mobile phone sensors can be abused by attackers to implement malicious activities in Android apps, as experimentally demonstrated by many state-of-the-art studies. There is hence a strong need to regulate the usage of mobile sensors so as to keep them from being exploited by malicious attackers. However

Mamuka Meskhishvili

For the given regular plane polygon and an arbitrary point in the plane of the polygon, the distances from the point to the vertices of the polygon are defined. We proved that there is one more non-congruent regular polygon having the vertices at the same distances from the point. The sizes of both regular polygons are uniquely determined by these distances.

Bing-Qiang Qiao, Qing Luo, Qiang Yuan, Yi-Qing Guo

The energy spectra and anisotropies are very important probes of the origin of cosmic rays. Recent measurements show that complicated but very interesting structures exist, at similar energies, in both the spectra and energy-dependent anisotropies, indicating a common origin of these structures. Particularly interesting phenomenon is that there is a reversal

Jian-hao Kang, Nan-jing Huang, Zhihao Hu, Ben-Zhang Yang

This paper considers a robust time-consistent mean-variance-skewness portfolio selection problem for an ambiguity-averse investor by taking into account wealth-dependent risk aversion and wealth-dependent skewness preference as well as model uncertainty. The robust equilibrium investment strategy and corresponding equilibrium value function are characterized

Trajan Hammonds, Seoyoung Kim, Steven J. Miller, Arjun Nigam

In this paper, we define a $k$-Diophantine $m$-tuple to be a set of $m$ positive integers such that the product of any $k$ distinct positive integers is one less than a perfect square. We study these sets in finite fields $\mathbb{F}_p$ for odd prime $p$ and guarantee the existence of a $k$-Diophantine m-tuple provided $p$ is larger than some explicit lower

Yajuan Liu, Han Cai, Xiaohu Tang

Cooperative repair model is an available technology to deal with multiple node failures in distributed storage systems. Recently, explicit constructions of cooperative MSR codes were given by Ye (IEEE Transactions on Information Theory, 2020) with sub-packetization level $(d-k+h)(d-k+1)^n$. Specifically, the sub-packetization level is $(h+1)2^n$ when $d=k+1$

Alessandro Oltramari, Jonathan Francis, Filip Ilievski, Kaixin Ma

This chapter illustrates how suitable neuro-symbolic models for language understanding can enable domain generalizability and robustness in downstream tasks. Different methods for integrating neural language models and knowledge graphs are discussed. The situations in which this combination is most appropriate are characterized, including quantitative evalua

Jianing Chu, Wenbin Lu, Shu Yang

Personalized decision-making, aiming to derive optimal treatment regimes based on individual characteristics, has recently attracted increasing attention in many fields, such as medicine, social services, and economics. Current literature mainly focuses on estimating treatment regimes from a single source population. In real-world applications, the distribut