arXiv papers from September 2023

Kritika Vashishtha, Anas Saad, Reza Faieghi, Fengfeng Xi

The lighting requirements are subjective and one light setting cannot work for all. However, there is little work on developing smart lighting algorithms that can adapt to user preferences. To address this gap, this paper uses fuzzy logic and reinforcement learning to develop an adaptive lighting algorithm. In particular, we develop a baseline fuzzy inferenc

Jiani Ding, Piero Madau, J. Xavier Prochaska

We present new measurements of the mean transmitted flux in the hydrogen Ly$\rm \alpha$ and a relative transmitted flux measurement in Ly$\rm \beta$ using 27,008 quasar spectra from the Fourteenth Data Release (DR14) of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS). Individual spectra are first combined into 16 composites with mean redshifts i

Egor Gladin, Alexander Gasnikov, Pavel Dvurechensky

Accuracy certificates for convex minimization problems allow for online verification of the accuracy of approximate solutions and provide a theoretically valid online stopping criterion. When solving the Lagrange dual problem, accuracy certificates produce a simple way to recover an approximate primal solution and estimate its accuracy. In this paper, we gen

Hayden Jananthan, Jeremy Kepner, Michael Jones, William Arcand

Expanding the scientific tools available to protect computer networks can be aided by a deeper understanding of the underlying statistical distributions of network traffic and their potential geometric interpretations. Analyses of large scale network observations provide a unique window into studying those underlying statistics. Newly developed GraphBLAS hyp

Daniel Juteau, Paul Levy, Eric Sommers

This paper includes the classification, in a simple Lie algebra, of the singularities of Slodowy slices between special nilpotent orbits that are adjacent in the partial order on nilpotent orbits. The irreducible components of most singularities are (up to normalization) either a simple surface singularity or the closure of a minimal special nilpotent orbit

Adam Ball, Shounak De, Akshay Yelleshpur Srikant, Anastasia Volovich

We compute scattering amplitudes involving one massive scalar and two, three, or four gravitons. We show that when the conformal dimension of the massive scalar is set to zero, the resulting celestial correlators depend {\it only} on the coordinates of the gravitons. Such correlators of gravitons are well-defined and do not suffer from divergences associated

Takahito Kashiwabara

A theoretical analysis of the finite element method for a generalized Robin boundary value problem, which involves a second-order differential operator on the boundary, is presented. If $\Omega$ is a general smooth domain with a curved boundary, we need to introduce an approximate domain $\Omega_h$ and to address issues owing to the domain perturbation $\Ome

Hailan Ma, Zhenhong Sun, Daoyi Dong, Dong Gong

Quantum state tomography (QST) is the process of reconstructing the complete state of a quantum system (mathematically described as a density matrix) through a series of different measurements. These measurements are performed on a number of identical copies of the quantum system, with outcomes gathered as frequencies. QST aims to recover the density matrix

Luana Barros, Levy Chaves, Sandra Avila

Melanoma is the most severe type of skin cancer due to its ability to cause metastasis. It is more common in black people, often affecting acral regions: palms, soles, and nails. Deep neural networks have shown tremendous potential for improving clinical care and skin cancer diagnosis. Nevertheless, prevailing studies predominantly rely on datasets of white

Salim Sazzed, Sharif Ullah

Malware poses a significant security risk to individuals, organizations, and critical infrastructure by compromising systems and data. Leveraging memory dumps that offer snapshots of computer memory can aid the analysis and detection of malicious content, including malware. To improve the efficacy and address privacy concerns in malware classification system

Mari Ohfuchi, Akihiko Sekine

We used density functional theory to investigate the lateral heteromonolayers of WTe2 and MoTe2. We confirmed that topologically nontrivial and trivial phases are energetically favored for the WTe2 and MoTe2 monolayers, taken out of bulk Td-WTe2 and 2H-MoTe2, respectively. We considered heteromonolayers consisting of these stable building blocks. In the Td-W

Tamás Kátay, László Márton Tóth, Zoltán Vidnyánszky

We study Constraint Satisfaction Problems (CSPs) in an infinite context. We show that the dichotomy between easy and hard problems -- established already in the finite case -- presents itself as the strength of the corresponding De Bruijin-Erd\H{o}s-type compactness theorem over ZF. More precisely, if $\mathcal{D}$ is a structure, let $K_\mathcal{D}$ stand f

Chelsea Edmonds, Lawrence C. Paulson

Formalised libraries of combinatorial mathematics have rapidly expanded over the last five years, but few use one of the most important tools: probability. How can often intuitive probabilistic arguments on the existence of combinatorial structures, such as hypergraphs, be translated into a formal text? We present a modular framework using locales in Isabell

Golam Md Muktadir

This paper presents a comprehensive exploration of the evolution of prompt engineering and generation in the field of natural language processing (NLP). Starting from the early language models and information retrieval systems, we trace the key developments that have shaped prompt engineering over the years. The introduction of attention mechanisms in 2015 r

Lawk Mineh

Let $G$ be a relatively hyperbolic group and let $Q$ and $R$ be relatively quasiconvex subgroups. It is known that there are many pairs of finite index subgroups $Q' \leqslant_f Q$ and $R' \leqslant_f R$ such that the subgroup join $\langle Q', R' \rangle$ is also relatively quasiconvex, given suitable assumptions on the profinite topology of $G$. We show th

Boris Ndjia Njike, Xavier Siebert

Cost-sensitive learning is a common type of machine learning problem where different errors of prediction incur different costs. In this paper, we design a generic nonparametric active learning algorithm for cost-sensitive classification. Based on the construction of confidence bounds for the expected prediction cost functions of each label, our algorithm se

Tobias Ginsburg, Kyle Hippe, Ryan Lewis, Doga Ozgulbas

Self Driving Labs (SDLs) that combine automation of experimental procedures with autonomous decision making are gaining popularity as a means of increasing the throughput of scientific workflows. The task of identifying quantities of supplied colored pigments that match a target color, the color matching problem, provides a simple and flexible SDL test case,

Xu Shang, Jiawei Wang, Yang Zheng

The recently developed DeeP-LCC (Data-EnablEd Predictive Leading Cruise Control) method has shown promising performance for data-driven predictive control of Connected and Autonomous Vehicles (CAVs) in mixed traffic. However, its simplistic zero assumption of the future velocity errors for the head vehicle may pose safety concerns and limit its performance o

Prerit Pramod

This paper presents a systematic and comprehensive analysis of the impact of parameter imbalance in permanent magnet synchronous machines. Analytical models that reveal the effects of imbalance are obtained for each parameter. Thereafter, the models are verified for accuracy by comparison with complex simulations that closely represent true machine behavior.

Ulrich D. Jentschura, Dylan C. Yost

The so-called proton radius puzzle (the current discrepancy of proton radii determined from spectroscopic measurements in ordinary versus muonic hydrogen) could be addressed via an accurate measurement of the Rydberg constant, because the proton radius and the Rydberg constant values are linked through high-precision optical spectroscopy. We argue that, with

Nikita Kornilov, Eduard Gorbunov, Mohammad Alkousa, Fedor Stonyakin

This paper is devoted to first-order algorithms for smooth convex optimization with inexact gradients. Unlike the majority of the literature on this topic, we consider the setting of relative rather than absolute inexactness. More precisely, we assume that an additive error in the gradient is proportional to the gradient norm, rather than being globally boun

Amin Ranem, Niklas Babendererde, Moritz Fuchs, Anirban Mukhopadhyay

Medical imaging plays a critical role in the diagnosis and treatment planning of various medical conditions, with radiology and pathology heavily reliant on precise image segmentation. The Segment Anything Model (SAM) has emerged as a promising framework for addressing segmentation challenges across different domains. In this white paper, we delve into SAM,

Alina Elena Baia, Valentina Poggioni, Andrea Cavallaro

Explainable AI (XAI) methods aim to describe the decision process of deep neural networks. Early XAI methods produced visual explanations, whereas more recent techniques generate multimodal explanations that include textual information and visual representations. Visual XAI methods have been shown to be vulnerable to white-box and gray-box adversarial attack

Lucrezia Bottegoni

The notion of semifunctor between categories, due to S. Hayashi (1985), is defined as a functor that does not necessarily preserve identities. In this paper we study how several properties of functors, such as fullness, full faithfulness, separability, natural fullness, can be formulated for semifunctors. Since a full semifunctor is actually a functor, we ar

Masoud Ahmadi, Atul Atul, Sytze de Graaf, Ewout van der Veer

Concurrent structural and electronic transformations in VO2 thin films are of twofold importance: enabling fine-tuning of the emergent electrical properties in functional devices, yet creating an intricate interfacial domain structure of transitional phases. Despite the importance of understanding the structure of VO2 thin films, a detailed real space atomic

Mohammad Mahdi Derakhshani, Ivona Najdenkoska, Cees G. M. Snoek, Marcel Worring

We present Self-Context Adaptation (SeCAt), a self-supervised approach that unlocks few-shot abilities for open-ended classification with small visual language models. Our approach imitates image captions in a self-supervised way based on clustering a large pool of images followed by assigning semantically-unrelated names to clusters. By doing so, we constru

Mehdi Biderang, Jeehoon Kim, Reza Molavi, Alireza Akbari

We propose a comprehensive theoretical formulation of magnetic penetration depth, $\lambda(T)$, based on the microscopic calculations for a general superconducting gap symmetry. Our findings admit the significant role of band structure and Fermi surface topology together with the symmetry of superconducting order parameter. We employ our findings pertaining

Jake Ketchum, Sophia Schiffer, Muchen Sun, Pranav Kaarthik

Gait generation for soft robots is challenging due to the nonlinear dynamics and high dimensional input spaces of soft actuators. Limitations in soft robotic control and perception force researchers to hand-craft open loop controllers for gait sequences, which is a non-trivial process. Moreover, short soft actuator lifespans and natural variations in actuato

Behzad Tahmasebzadeh, Ling Zhu, Juntai Shen, Dimitri A. Gadotti

We apply the barred Schwarzschild method developed by Tahmasebzadeh et al. (2022) to a barred S0 galaxy, NGC 4371, observed by IFU instruments from the TIMER and ATLAS3D projects. We construct the gravitational potential by combining a fixed black hole mass, a spherical dark matter halo, and stellar mass distribution deprojected from $3.6$ $\mu$m S$^4$G imag

Cameron Shinn, Collin McCarthy, Saurav Muralidharan, Muhammad Osama

We introduce the Sparsity Roofline, a visual performance model for evaluating sparsity in neural networks. The Sparsity Roofline jointly models network accuracy, sparsity, and theoretical inference speedup. Our approach does not require implementing and benchmarking optimized kernels, and the theoretical speedup becomes equal to the actual speedup when the c

M. Menichelli, L. Antognini, S. Aziz, A. Bashiri

Hydrogenated amorphous silicon (a-Si:H) is a material having an intrinsically high radiation hardness that can be deposited on flexible substrates like Polyimide. For these properties a-Si:H can be used for the production of flexible sensors. a-Si:H sensors can be successfully utilized in dosimetry, beam monitoring for particle physics (x-ray, electron, gamm

Steven R. Lippold

Based on work presented in [4], we define $S^2$-Upper Triangular Matrices and $S^2$-Lower Triangular Matrices, two special types of $d\times d(2d-1)$ matrices generalizing Upper and Lower Triangular Matrices, respectively. Then, we show that the property that the determinant of an Upper Triangular Matrix is the product of its diagonal entries is generalized

Chris Kapulkin, Nathan Kershaw

We show that the category of (reflexive) graphs and graph maps carries exactly two closed symmetric monoidal products: the box product and the categorical product.

Xuansheng Wu, Wenlin Yao, Jianshu Chen, Xiaoman Pan

Large Language Models (LLMs) have achieved remarkable success, where instruction tuning is the critical step in aligning LLMs with user intentions. In this work, we investigate how the instruction tuning adjusts pre-trained models with a focus on intrinsic changes. Specifically, we first develop several local and global explanation methods, including a gradi

Gaurav Jain, Basel Hindi, Zihao Zhang, Koushik Srinivasula

Blind and low-vision (BLV) people rely on GPS-based systems for outdoor navigation. GPS's inaccuracy, however, causes them to veer off track, run into obstacles, and struggle to reach precise destinations. While prior work has made precise navigation possible indoors via hardware installations, enabling this outdoors remains a challenge. Interestingly, many

Ali Namaki, Reza Eyvazloo, Shahin Ramtinnia

Early warning systems (EWSs) are critical for forecasting and preventing economic and financial crises. EWSs are designed to provide early warning signs of financial troubles, allowing policymakers and market participants to intervene before a crisis expands. The 2008 financial crisis highlighted the importance of detecting financial distress early and takin

Louis Rosenberg, Gregg Willcox, Hans Schumann

When generating insights from human groups, conversational deliberation is a key method for exploring issues, surfacing ideas, debating options, and converging on solutions. Unfortunately, real-time conversations are difficult to scale, losing effectiveness in groups above 4 to 7 members. Conversational Swarm Intelligence (CSI) is a new technology that enabl

Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang

Imitation learning, which learns agent policy by mimicking expert demonstration, has shown promising results in many applications such as medical treatment regimes and self-driving vehicles. However, it remains a difficult task to interpret control policies learned by the agent. Difficulties mainly come from two aspects: 1) agents in imitation learning are u

Young In Kim, Andrea Agiollo, Pratiksha Agrawal, Johannes O. Royset

Optimization algorithms that seek flatter minima, such as Sharpness-Aware Minimization (SAM), are credited with improved generalization and robustness to noise. We ask whether such gains impact membership privacy. Surprisingly, we find that SAM is more prone to Membership Inference Attacks (MIA) than classical SGD across multiple datasets and attack methods,

Xinchen Zhou

Maintaining temperature is crucial in both daily life and industrial settings, ensuring human comfort and device functionality. In the quest for energy conservation and emission reduction, several contemporary passive temperature control technologies have emerged, including phase change temperature control, shape memory alloys, solar thermal utilization, sky

Wen Wu, Wenlin Chen, Chao Zhang, Philip C. Woodland

Human annotator simulation (HAS) serves as a cost-effective substitute for human evaluation such as data annotation and system assessment. Human perception and behaviour during human evaluation exhibit inherent variability due to diverse cognitive processes and subjective interpretations, which should be taken into account in modelling to better mimic the wa

Claude Duhr, Yu Jiao Zhu

We report on the analytic computation of the 2-loop amplitude for Bhabha scattering in QED. We study the analytic structure of the amplitude, and reveal its underlying connections to hyperbolic Coxeter groups and arithmetic geometries of elliptic curves.

Artem Lopatin, Pedro Antonio Muniz Martins

We described a minimal separating set for the algebra of $O(F_q)$-invariant polynomial functions of $m$-tuples of two-dimensional vectors over a finite field $F_q$.

Vincent Li, Nick Doiron

Unit testing is a commonly-used approach in software engineering to test the correctness and robustness of written code. Unit tests are tests designed to test small components of a codebase in isolation, such as an individual function or method. Although unit tests have historically been written by human programmers, recent advancements in AI, particularly L

Karl Royen, Suman Mondal, Frank Pollmann, Fabian Heidrich-Meisner

In the study of the thermalization of closed quantum systems, the role of kinetic constraints on the temporal dynamics and the eventual thermalization is attracting significant interest. Kinetic constraints typically lead to long-lived metastable states depending on initial conditions. We consider a model of interacting hardcore bosons with an additional kin

Chak Lam Shek, Xiyang Wu, Wesley A. Suttle, Carl Busart

Navigating robots through unstructured terrains is challenging, primarily due to the dynamic environmental changes. While humans adeptly navigate such terrains by using context from their observations, creating a similar context-aware navigation system for robots is difficult. The essence of the issue lies in the acquisition and interpretation of context inf

Hejia Geng, Boxun Xu, Peng Li

Large Language Models (LLMs) have demonstrated impressive inferential capabilities, with numerous research endeavors devoted to enhancing this capacity through prompting. Despite these efforts, a unified epistemological foundation is still conspicuously absent. Drawing inspiration from Kant's a priori philosophy, we propose the UPAR prompting framework, desi

Atul C. Thakur, Richard C. Remsing

Organic molecular solids can exhibit rich phase diagrams. In addition to structurally unique phases, translational and rotational degrees of freedom can melt at different state points, giving rise to partially disordered solid phases. The structural and dynamic disorder in these materials can have a significant impact on the physical properties of the organi

David Baron, Ammar Eltigani, S. Loepp, AnaMaria Perez

Let $T$ be a complete local (Noetherian) ring of characteristic zero. We find necessary and sufficient conditions for $T$ to be the completion of a quasi-excellent local domain. In the case that $T$ contains the rationals, we provide necessary and sufficient conditions for $T$ to be the completion of a countable quasi-excellent local domain. We also prove re

Max Aehle, Lorenzo Arsini, R. Belén Barreiro, Anastasios Belias

In this article we examine recent developments in the research area concerning the creation of end-to-end models for the complete optimization of measuring instruments. The models we consider rely on differentiable programming methods and on the specification of a software pipeline including all factors impacting performance -- from the data-generating proce

Kisnney Almeida, Igor Lima, Oscar Ocampo

In this paper, we study subgroup separability (also known as LERF) and related properties for surface braid groups and virtual (singular) braid groups.

Artem Lopatin

The algebra of ${\rm GL}_n$-invariants of $m$-tuples of $n\times n$ matrices with respect to the action by simultaneous conjugation is a classical topic in case of infinite base field. On the other hand, in case of a finite field generators of polynomial invariants even in case of a pair of $2\times 2$ matrices are not known. Working over an arbitrary field

Jennyfer Juliana Calderón Moreno, Artem Lopatin

We established two-sided Curto-Herrero conjecture for pairs of matrices, where the first matrix has a simple spectrum. Namely, it is shown that these pairs are separated by ranks of non-commutative polynomials in matrices. Moreover, we provided some upper bound on degrees of non-commutative polynomials which should be considered.

Rongzhi Dong, Nihang Fu, dirisuriya M. D. Siriwardane, Jianjun Hu

Due to the vast chemical space, discovering materials with a specific function is challenging. Chemical formulas are obligated to conform to a set of exacting criteria such as charge neutrality, balanced electronegativity, synthesizability, and mechanical stability. In response to this formidable task, we introduce a deep learning-based generative model for

Matthew J. Gorban, William D. Julius, Ramesh Radhakrishnan, Gerald B. Cleaver

The interaction between the quantum vacuum and time-dependent boundaries can produce particles via the dynamical Casimir effect. It is known that, for asymmetric Casimir systems, there is an imbalance in the particle production on either side of the boundary. Here, we consider a real massless scalar field in 1+1 dimensions interacting with a moving $\delta-\

Antoine Marot, Noureddine Henka, Benjamin Donnot, Sami Tazi

Flexible grid topology has become a key enabler of flexibility in modern power grids, particularly for congestion management. Studying the effects of combinatorial topological changes is therefore of significant interest, though it remains computationally intensive in most cases. To address this, we revisit the superposition theorem, which has served as the

Trager Joswig-Jones, Baosen Zhang

Grid-interfacing inverters act as the interface between renewable resources and the electric grid, and have the potential to offer fast and programmable controls compared to synchronous generators. With this flexibility there has been significant research efforts into determining the best way to control these inverters. Inverters are limited in their maximum

Fırtına Küçük

The main objective of this article is to establish the $p$-adic Artin formalism for the algebraic $p$-adic $L$-functions attached to the adjoint representations of Coleman families of modular forms. In particular, we prove a factorization formula involving the determinants of appropriate Selmer complexes, using tools from rigid geometry, homological algebra,

Toushiqul Islam, Md Samin Ashiq Aziz, Sadib Fardin, Abrar Faiyad

Inconel-718's compatibility with additive manufacturing (AM) has made it a center of attention for researchers. This paper focuses on how cooling rates affect the hardness of AM Inconel-718. To study the AM process, monocrystalline and polycrystalline Inconel-718 layers were added to a pristine substrate and equilibrated at 2000 K before being cooled to 300

Erman Cineli, Viktor L. Ginzburg, Basak Z. Gurel

The main result of the paper is that for any closed symplectic manifold the spectral norm of the iterates of a Hamiltonian diffeomorphism is locally uniformly bounded away from zero $C^\infty$-generically.

Axel Huebl, Arianna Formenti, Marco Garten, Jean-Luc Vay

Visualization of dynamic processes in scientific high-performance computing is an immensely data intensive endeavor. Application codes have recently demonstrated scaling to full-size Exascale machines, and generating high-quality data for visualization is consequently on the machine-scale, easily spanning 100s of TBytes of input to generate a single video fr

Mustafa O. Karabag, Sophia Smith, Negar Mehr, David Fridovich-Keil

When interacting with other decision-making agents in non-adversarial scenarios, it is critical for an autonomous agent to have inferable behavior: The agent's actions must convey their intention and strategy. We model the inferability problem using Stackelberg games with observations where a leader and a follower repeatedly interact. During the interactions

Phuc-Lu Le, Son Hoang Dau, Hy Dinh Ngo, Thuc D. Nguyen

We investigate in this work the problem of Erasure Combinatorial Batch Codes, in which $n$ files are stored on $m$ servers so that every set of $n-r$ servers allows a client to retrieve at most $k$ distinct files by downloading at most $t$ files from each server. Previous studies have solved this problem for the special case of $t=1$ using Combinatorial Batc

JosÉ Ignacio Royo Prieto, Martintxo Saralegi-Aranguren, Robert Wolak

The Hard Lefschetz Property (HLP) has recently been formulated in the context of isometric flows without singularities on manifolds. In this category, two versions of the HLP (transverse and not) have been proven to be equivalent, thus generalizing what happens in the important cases of both K-contact and Sasakian manifolds. In this work we define both versi

Linda Lastrico, Nuno Ferreira Duarte, Alessandro Carfì, Francesco Rea

Implicit communication plays such a crucial role during social exchanges that it must be considered for a good experience in human-robot interaction. This work addresses implicit communication associated with the detection of physical properties, transport, and manipulation of objects. We propose an ecological approach to infer object characteristics from su

David Kalaj

Let $L^p(\mathbf{T})$ be the Lesbegue space of complex-valued functions defined in the unit circle $\mathbf{T}=\{z: |z|=1\}\subseteq \mathbb{C}$. In this paper, we address the problem of finding the best constant in the inequality of the form: $$\|f\|_{L^p(\mathbf{T})}\le A_{p,b} \|(|P_+ f|^2+b| P_{-} f|^2)^{1/2}\|_{L^p(\mathbf{T})}.$$ Here $p\in[1,2]$, $b>0

Jonathan Tremblay, Bowen Wen, Valts Blukis, Balakumar Sundaralingam

We introduce Diff-DOPE, a 6-DoF pose refiner that takes as input an image, a 3D textured model of an object, and an initial pose of the object. The method uses differentiable rendering to update the object pose to minimize the visual error between the image and the projection of the model. We show that this simple, yet effective, idea is able to achieve stat

Satarupa Barman, Ranjan Sharma

Tolman VII solution [Phys. Rev. 55 (4), 364 (1939)] is an exact analytic solution to the Einstein field equations describing the space-time of a static spherically symmetric distribution of matter. The solution has been shown to be capable of describing the interior of compact objects like neutron stars. Generalized [Phys. Rev. D 92(12), 124005 (2015)] and m

Schmidt F., Way M. J., Costard F., Bouley S.

What was the nature of the Late Hesperian climate? Warm and wet or cold and dry? Formulated this way the question leads to an apparent paradox since both options seem implausible. A warm and wet climate would have produced extensive fluvial erosion but few valley networks have been observed at the age of the late Hesperian. A too cold climate would have kept

Bryan Semon, Michael Jaffe, Haifeng Wang, Lauren Priddy

Currently, a large number of stored tissue samples are unavailable for spectroscopic study without the time consuming and destructive process of paraffin removal. Instead, a structurally sensitive technique, sum frequency generation, and a chemically sensitive technique, coherent anti-Stokes Raman scattering enables imaging through the paraffin. This method

Ian Rabago, Zhaohuan Zhu, Stephen Lubow, Rebecca G. Martin

Disc warping, and possibly disc breaking, has been observed in protoplanetary discs around both single and multiple stars. Large warps can break the disc, producing multiple observational signatures. In this work, we use comparisons of disc timescales to derive updated formulae for disc breaking, with better predictions as to when and where a disc is expecte

Melvyn Tyloo, Marc Vuffray, Andrey Y. Lokhov

Malfunctioning equipment, erroneous operating conditions or periodic load variations can cause periodic disturbances that would persist over time, creating an undesirable transfer of energy across the system -- an effect referred to as forced oscillations. Wide-area oscillations may damage assets, trigger inadvertent tripping or control actions, and be the c

Hanif Kia, Mansour Vali, Hadi Sabahi

Heart failure (HF) is a critical condition in which the accurate prediction of mortality plays a vital role in guiding patient management decisions. However, clinical datasets used for mortality prediction in HF often suffer from an imbalanced distribution of classes, posing significant challenges. In this paper, we explore preprocessing methods for enhancin

P. Kumari, S. Rani, S. Kar, T. Mukherjee

The Quantum Materials group at Indian Institute of Technology Patna is working on a range of topics relating to nanoelectronics, spintronics, clean energy and memory design etc. The PI has past experiences of working extensively with superconducting systems like cuprates [1, 2], ruthanate [3], pnictide [4, 5], thin film heterostructures [6, 7] etc and magnet

Wenjie Yin, Qingyuan Yao, Yi Yu, Hang Yin

Lyrics often convey information about the songs that are beyond the auditory dimension, enriching the semantic meaning of movements and musical themes. Such insights are important in the dance choreography domain. However, most existing dance synthesis methods mainly focus on music-to-dance generation, without considering the semantic information. To complem

Fadillah Maani, Asim Ukaye, Nada Saadi, Numan Saeed

Echocardiography has become an indispensable clinical imaging modality for general heart health assessment. From calculating biomarkers such as ejection fraction to the probability of a patient's heart failure, accurate segmentation of the heart structures allows doctors to assess the heart's condition and devise treatments with greater precision and accurac

Loren E. Held, George Mamatsashvili, Martin E. Pessah

The discovery of the first binary neutron star merger, GW170817, has spawned a plethora of global numerical relativity simulations. These simulations are often ideal (with dissipation determined by the grid) and/or axisymmetric (invoking ad hoc mean-field dynamos). However, binary neutron star mergers (similar to X-ray binaries and active galactic nuclei inn

Oem Trivedi, Simran Kaur Saggu, Pankaj S. Joshi

The pursuit of unraveling the true essence of dark energy has become an immensely captivating endeavor in modern cosmology. Alongside the conventional cosmological constant approach, a diverse range of ideas has been proposed, encompassing scalar field-based models and various modified gravity approaches. A particularly intriguing notion involves exploring s

Shashank Shekhar, Asif Salim, Adesh Bansode, Vivaswan Jinturkar

Counterfactual explanations (CFE) are methods that explain a machine learning model by giving an alternate class prediction of a data point with some minimal changes in its features. It helps the users to identify their data attributes that caused an undesirable prediction like a loan or credit card rejection. We describe an efficient and an actionable count

Saaketh Medepalli, Naren Doraiswamy

Meta-learning frameworks for few-shot learning aims to learn models that can learn new skills or adapt to new environments rapidly with a few training examples. This has led to the generalizability of the developed model towards new classes with just a few labelled samples. However these networks are seen as black-box models and understanding the representat

Chiaki Ohae, Kenji Hasegawa, Masato Nagano, Soma Tahara

On the basis of standard wavelength conversion by the use of angular phase matching of nonlinear optical crystals arranged in free space, applicable to a wide range of wavelengths and laser intensities, we both numerically and experimentally present an optimal design for achieving near-full energy conversion while maintaining good single-mode properties of f

Said Hamoun, Youssef Rami, Lucile Vandembroucq

In this work, we show that, for any simply-connected elliptic space $S$ admitting a pure minimal Sullivan model with a differential of constant length, we have ${\rm TC}_0(S)\leq 2{\rm cat}_0(S)+\chi_{\pi}(S)$ where $\chi_{\pi}(S)$ is the homotopy characteristic. This is a consequence of a structure theorem for this type of models, which is actually our main

Christian Internò, Eloisa Ambrosini

In recent years, there is strong emphasis on mining medical data using machine learning techniques. A common problem is to obtain a noiseless set of textual documents, with a relevant content for the research question, and developing a Question Answering (QA) model for a specific medical field. The purpose of this paper is to present a new methodology for bu

Babak Taheri, Daniel K. Molzahn

Many power system operation and planning problems use the DC power flow approximation to address computational challenges from the nonlinearity of the AC power flow equations. The DC power flow simplifies the AC power flow equations to a linear form that relates active power flows to phase angle differences across branches, parameterized by coefficients base

Luca Mungo, Alexandra Brintrup, Diego Garlaschelli, François Lafond

Network reconstruction is a well-developed sub-field of network science, but it has only recently been applied to production networks, where nodes are firms and edges represent customer-supplier relationships. We review the literature that has flourished to infer the topology of these networks by partial, aggregate, or indirect observation of the data. We di

Douglas P. Wiens

We present a result according to which certain functions of covariance matrices are maximized at scalar multiples of the identity matrix. This is used to show that experimental designs that are optimal under an assumption of independent, homoscedastic responses can be minimax robust, in broad classes of alternate covariance structures. In particular it can j

Xin Xie, Jiangqiong Li, Haining Wang

Lu Xun and Zhou Zuoren stand as two of the most influential writers in modern Chinese literature. Beyond their familial ties as brothers, they were also intimate collaborators during the nascent stages of their writing careers. This research employs quantitative methods to revisit three disputed essays pseudonymously published by the brothers in 1912. Our st

Saikat Basu, Arnav Das, Amit Saha, Amlan Chakrabarti

Quantum computers must meet extremely stringent qualitative and quantitative requirements on their qubits in order to solve real-life problems. Quantum circuit fragmentation techniques divide a large quantum circuit into a number of sub-circuits that can be executed on the smaller noisy quantum hardware available. However, the process of quantum circuit frag

Mahmud Hasan, Mathias Muia

Information Maximizing Generative Adversarial Network (infoGAN) can be understood as a minimax problem involving two neural networks: discriminators and generators with mutual information functions. The infoGAN incorporates various components, including latent variables, mutual information, and objective function. This research demonstrates the Generalizatio

H. Hawley-Herrera

The Scintillating Bubble Chamber (SBC) collaboration is constructing a 10~kg liquid argon (LAr) bubble chamber at SNOLAB called SBC-SNOLAB having the main objective of detecting dark matter. One of the most novel aspects of SBC-SNOLAB is the scintillation system, consisting of LAr doped with on the order of 10~ppm Xe, 48 FBK VUV silicon photomultipliers (SiP

Nisarg Ujjainkar, Ethan Shahan, Kenneth Chen, Budmonde Duinkharjav

Virtual Reality (VR) has the potential of becoming the next ubiquitous computing platform. Continued progress in the burgeoning field of VR depends critically on an efficient computing substrate. In particular, DRAM access energy is known to contribute to a significant portion of system energy. Today's framebuffer compression system alleviates the DRAM traff

Sadib Fardin, Md. Jawarul Moresalein, Toushiqul Islam, Abrar Faiyad

In recent years, lead-free solder alloys based on tin, silver, or copper have gained popularity over lead-based solder alloys due to their improved mechanical and electrical properties and their non-toxic nature. In our previous studies, we examined the stress-strain behavior of SAC305 under varying cooling rates. This study extends our investigation to vari

Congqin Zheng, Xin Li, Yuhui Huang, Yongjun Wu

Molecular ferroelectric materials have attracted widespread attention due to their abundant chemical diversity, structural tunability, low synthesis temperature, and high flexibility. Meanwhile, the integration of molecular ferroelectric materials and Si is still challenging, while the fundamental understanding of the ferroelectric switching process is still

David Khachaturov, Yue Gao, Ilia Shumailov, Robert Mullins

Visual adversarial examples have so far been restricted to pixel-level image manipulations in the digital world, or have required sophisticated equipment such as 2D or 3D printers to be produced in the physical real world. We present the first ever method of generating human-producible adversarial examples for the real world that requires nothing more compli

Eduardo Bittencourt, Alan G. Cesar, Jonas P. Pereira

We study the problem of the gravitational collapse of an object as seen by an external observer. We assume that the resultant spacetime is a match of an external Vaidya spacetime with an interior Friedmann-Lema\^itre-Robertson-Walker (FRLW) spacetime of any spatial curvature and with a scalar field both minimally and non-minimally coupled to the metric. With

Haining Wang

Authorship identification ascertains the authorship of texts whose origins remain undisclosed. That authorship identification techniques work as reliably as they do has been attributed to the fact that authorial style is properly captured and represented. Although modern authorship identification methods have evolved significantly over the years and have pro

Silviu Pitis

As the capabilities of artificial agents improve, they are being increasingly deployed to service multiple diverse objectives and stakeholders. However, the composition of these objectives is often performed ad hoc, with no clear justification. This paper takes a normative approach to multi-objective agency: from a set of intuitively appealing axioms, it is

Zhiyao Sun, Tian Lv, Sheng Ye, Matthieu Lin

The generation of stylistic 3D facial animations driven by speech presents a significant challenge as it requires learning a many-to-many mapping between speech, style, and the corresponding natural facial motion. However, existing methods either employ a deterministic model for speech-to-motion mapping or encode the style using a one-hot encoding scheme. No

Snehal Jauhri, Sophie Lueth, Georgia Chalvatzaki

Mobile Manipulation (MoMa) systems incorporate the benefits of mobility and dexterity, due to the enlarged space in which they can move and interact with their environment. However, even when equipped with onboard sensors, e.g., an embodied camera, extracting task-relevant visual information in unstructured and cluttered environments, such as households, rem

Kyle Thompson, Kehui Li, Daniela Angulo, Vida-Michelle Nixon

When a single photon traverses a cloud of 2-level atoms, the average time it spends as an atomic excitation -- as measured by weakly probing the atoms -- can be shown to be the spontaneous lifetime of the atoms multiplied by the probability of the photon being scattered into a side mode. A tempting inference from this is that an average scattered photon spen