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Integrated sensing and communication (ISAC) is anticipated to play a crucial role in sixth-generation (6G) mobile communication networks. A significant challenge in ISAC systems is the degradation of localization accuracy due to poor propagation conditions, such as multipath effects and non-line-of-sight (NLoS) scenarios. These conditions result in outlier measurements that can severely impact localization performance. This paper investigates the enhancement of target localization accuracy in multistatic ISAC systems under both line-of-sight (LoS) and NLoS conditions. We leverage positioning reference signal (PRS), which is currently employed in fifth-generation (5G) new radio (NR) for user equipment (UE) positioning, as the sensing signal. We introduce a novel algorithm to improve localization accuracy by mitigating the impact of outliers in range measurements, while also accounting for errors due to PRS range resolution. Eventually, through simulation results, we demonstrate the superiority of the proposed method over previous approaches. Indeed, we achieve up to 28% and 20% improvements in average localization error over least squares (LS) and iteratively reweighted least squares (IRLS) methods, respectively. Additionally, we observe up to 16% and 13% enhancements in the 90th percentile of localization error compared to LS and IRLS, respectively. Our simulation is based on 3rd Generation Partnership Project (3GPP) standards, ensuring the applicability of our results across diverse environments, including urban and indoor areas., Comment: copyright 2025 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Space debris presents a critical challenge for the sustainability of future space missions, emphasizing the need for robust and standardized identification methods. However, a comprehensive benchmark for rocket body classification remains absent. This paper addresses this gap by introducing the RoBo6 dataset for rocket body classification based on light curves. The dataset, derived from the Mini Mega Tortora database, includes light curves for six rocket body classes: CZ-3B, Atlas 5 Centaur, Falcon 9, H-2A, Ariane 5, and Delta 4. With 5,676 training and 1,404 test samples, it addresses data inconsistencies using resampling, normalization, and filtering techniques. Several machine learning models were evaluated, including CNN and transformer-based approaches, with Astroconformer reporting the best performance. The dataset establishes a common benchmark for future comparisons and advancements in rocket body classification tasks., Comment: 6 pages, 1 figure, 5 tables, Accepted on Machine Learning and the Physical Sciences Workshop, NeurIPS 2024

This study details our approach for the CASE 2024 Shared Task on Climate Activism Stance and Hate Event Detection, focusing on Hate Speech Detection, Hate Speech Target Identification, and Stance Detection as classification challenges. We explored the capability of Large Language Models (LLMs), particularly GPT-4, in zero- or few-shot settings enhanced by retrieval augmentation and re-ranking for Tweet classification. Our goal was to determine if LLMs could match or surpass traditional methods in this context. We conducted an ablation study with LLaMA for comparison, and our results indicate that our models significantly outperformed the baselines, securing second place in the Target Detection task. The code for our submission is available at https://github.com/NaiveNeuron/bryndza-case-2024, Comment: Accepted to the 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2024)

We introduce Universal NER (UNER), an open, community-driven project to develop gold-standard NER benchmarks in many languages. The overarching goal of UNER is to provide high-quality, cross-lingually consistent annotations to facilitate and standardize multilingual NER research. UNER v1 contains 18 datasets annotated with named entities in a cross-lingual consistent schema across 12 diverse languages. In this paper, we detail the dataset creation and composition of UNER; we also provide initial modeling baselines on both in-language and cross-lingual learning settings. We release the data, code, and fitted models to the public., Comment: NAACL 2024 Camera-ready

We study some properties of a triad of circles associated with a triangle. Each circle is inside the triangle, tangent to two sides of the triangle, and externally tangent to the circle on the third side as diameter. In particular, we find a nice relation involving the radii of the inner and outer Apollonius circles of the three circles in the triad., Comment: arXiv admin note: text overlap with arXiv:2310.12896

We study properties of certain circles associated with a triangle. Each circle is inside the triangle, tangent to two sides of the triangle, and externally tangent to the arc of a circle erected internally on the third side.

Named Entity Recognition (NER) is a fundamental NLP tasks with a wide range of practical applications. The performance of state-of-the-art NER methods depends on high quality manually anotated datasets which still do not exist for some languages. In this work we aim to remedy this situation in Slovak by introducing WikiGoldSK, the first sizable human labelled Slovak NER dataset. We benchmark it by evaluating state-of-the-art multilingual Pretrained Language Models and comparing it to the existing silver-standard Slovak NER dataset. We also conduct few-shot experiments and show that training on a sliver-standard dataset yields better results. To enable future work that can be based on Slovak NER, we release the dataset, code, as well as the trained models publicly under permissible licensing terms at https://github.com/NaiveNeuron/WikiGoldSK., Comment: BSNLP 2023 Workshop at EACL 2023

Let P be a point inside a convex quadrilateral ABCD. The lines from P to the vertices of the quadrilateral divide the quadrilateral into four triangles. If we locate a triangle center in each of these triangles, the four triangle centers form another quadrilateral called a central quadrilateral. For each of various shaped quadrilaterals, and each of 1000 different triangle centers, we compare the reference quadrilateral to the central quadrilateral. Using a computer, we determine how the two quadrilaterals are related. For example, we test to see if the two quadrilaterals are congruent, similar, have the same area, or have the same perimeter. We also look for such relationships when P is a special point associated with the reference quadrilateral, such as being the diagonal point, Steiner point, or Poncelet point.

The diagonals of a quadrilateral form four component triangles (in two ways). For each of various shaped quadrilaterals, we examine 1000 triangle centers located in these four component triangles. Using a computer, we determine when the four centers form a special quadrilateral, such as a rhombus or a cyclic quadrilateral. A typical result is the following. The diagonals of an equidiagonal quadrilateral divide the quadrilateral into four nonoverlapping triangles. Then the Nagel points of these four triangles form an orthodiagonal quadrilateral.

The incircle of a triangle touches the sides of the triangle in three points. It is well known that the lines from these points to the opposite vertices meet at a point known as the Gergonne point of the triangle. We use a computer to discover and catalog properties of the Gergonne point.

Hand Gesture Recognition (HGR) based on inertial data has grown considerably in recent years, with the state-of-the-art approaches utilizing a single handheld sensor and a vocabulary comprised of simple gestures. In this work we explore the benefits of using multiple inertial sensors. Using WaveGlove, a custom hardware prototype in the form of a glove with five inertial sensors, we acquire two datasets consisting of over $11000$ samples. To make them comparable with prior work, they are normalized along with $9$ other publicly available datasets, and subsequently used to evaluate a range of Machine Learning approaches for gesture recognition, including a newly proposed Transformer-based architecture. Our results show that even complex gestures involving different fingers can be recognized with high accuracy. An ablation study performed on the acquired datasets demonstrates the importance of multiple sensors, with an increase in performance when using up to three sensors and no significant improvements beyond that., Comment: Accepted to EUSIPCO 2021

Introductory UNIX courses are typically organized as lectures, accompanied by a set of exercises, whose solutions are submitted to and reviewed by the lecturers. While this arrangement has become standard practice, it often requires the use of an external tool or interface for submission and does not automatically check its correctness. That in turn leads to increased workload and makes it difficult to deal with potential plagiarism. In this work we present TermAdventure (TA), a suite of tools for creating interactive UNIX exercises. These resemble text adventure games, which immerse the user in a text environment and let them interact with it using textual commands. In our case the ''adventure'' takes place inside a UNIX system and the user interaction happens via the standard UNIX command line. The adventure is a set of exercises, which are presented and automatically evaluated by the system, all from within the command line environment. The suite is released under an open source license, has minimal dependencies and can be used either on a UNIX-style server or a desktop computer running any major OS platform through Docker. We also reflect on our experience of using the presented suite as the primary teaching tool for an introductory UNIX course for Data Scientists and discuss the implications of its deployment in similar courses. The suite is released under the terms of an open-source license at \url{https://github.com/NaiveNeuron/TermAdventure}., Comment: Accepted at ITiCSE 2021

In this study we demonstrate the viability of deploying BERT-style models to serverless environments in a production setting. Since the freely available pre-trained models are too large to be deployed in this way, we utilize knowledge distillation and fine-tune the models on proprietary datasets for two real-world tasks: sentiment analysis and semantic textual similarity. As a result, we obtain models that are tuned for a specific domain and deployable in serverless environments. The subsequent performance analysis shows that this solution results in latency levels acceptable for production use and that it is also a cost-effective approach for small-to-medium size deployments of BERT models, all without any infrastructure overhead., Comment: NAACL-HLT 2021 Industry Track Camera Ready

We calculate the optical conductivity in a clean system of quasiparticles coupled to charge-ordering collective modes. The absorption induced by these modes may produce an anomalous frequency and temperature dependence of low-energy optical absorption in some cuprates. However, the coupling with lattice degrees of freedom introduces a non-universal energy scale leading to scaling violation in low-temperature optical conductivity., Comment: Proceedings of M2S 2006. To appear in Physica C

We calculate the Raman response contribution due to collective modes, finding a strong dependence on the photon polarizations and on the characteristic wavevectors of the modes. We compare our results with recent Raman spectroscopy experiments in underdoped cuprates, $La_{2-x}Sr_xCuO_4$ and $(Y_{1.97}Ca_{0.3})Ba_2CuO_{6.05}$, where anomalous low-energy peaks are observed, which soften upon lowering the temperature. We show that the specific dependence on doping and on photon polarizations of these peaks is only compatible with charge collective excitations at finite wavelength., Comment: 5 pages, 3 figures

Within the stripe quantum critical point theory for high T_c superconductors, we point out that there is a direct contribution of charge collective fluctuations to the optical absorption and to the Raman spectra. In this latter case, we find that the critical charge collective modes can or can not be excited depending on the direction of their wavevector and on the polarization of the incoming and outgoing photons. This indicates a marked distinction between quasiparticles which are strongly and weakly coupled to critical collective modes and provides a direct confirmation that the order associated to the quantum critical point near optimal doping of cuprates occurs at finite wavevectors., Comment: 6 pages and 4 figures. Proceedings of SNS04 Conference, Sitges, Spain, 2004

We study a solid-on-solid model for depinning transitions of two directed heteropolymers with an effective long range interaction decaying as the inverse square of their distance. Exact calculations of the localization length and specific heat non-universal critical exponents indicate that new universality classes govern the depinning transitions, different from those found for interacting homopolymers. Disorder driven change in the order of the phase transition and in the sign of the specific heat exponent are predicted., Comment: 4 pages, 2 figures

We consider problems of one dimensional interacting fermions confined to a finite size, multichannel geometry. Concentrating on Luttinger liquids and carbon nanotubes, we use nontrivial boundary conditions to represent the effect of external leads, and apply our framework to transport problems in a Josephson junction setup. We present an exact computation of all correlation functions, including finite-size and temperature effects, for two sets of solvable boundary conditions. In all cases, we compute physical quantities like the Josephson current and the pairing order parameter profile., Comment: 30 pages, 2 EPS figures

We present an analitical study of the dynamical process of the approach to steady state for a driven diffusive system represented by the microemulsion phase of a ternary mixture. The external applied field is given by a plane Couette shear flow and the problem is studied within the framework of a time-dependent Ginzburg-Landau model. A Fokker-Planck equation for the probability distribution of the concentration fluctuations is developed in a self-consistent one-loop approximation and solved exactly, giving an analytical expression for the dynamic correlation functions of the system. For comparison to experimental work, we also show grey-scale plots of the scattering function at different times during the dynamical process for two different shear rates., Comment: 14 pages, 3 figures. To appear on Physica A

Steady-state properties of microemulsions in shear flow are studied in the context of a Ginzburg-Landau free-energy approach. Explicit expressions are given for the structure factor and the time correlation function at the one loop level of approximation. Our results predict a four-peak pattern for the structure factor, implying the simultaneous presence of interfaces aligned with two different orientations. Due to the peculiar interface structure a non-monotonous relaxation of the time correlator is also found., Comment: 5 pages, 3 figures

We extend the analysis of the mean field schematic model recently introduced for the description of glass forming liquids to the case of a supercooled fluid subjected to a shear flow of rate $\gamma$. After quenching the system to a low temperature $T$, a slow glassy regime is observed before stationarity is achieved at the characteristic time $\tau_g$. $\tau_g$ is of the order of the usual equilibration time without shear $\tau_g^o$ for weak shear, $\gamma \tau_g ^o<1$. For larger shear, $\gamma \tau_g ^o>1$, local rearrangement of dense regions is instead enhanced by the flow, and $\tau_g \simeq 1/(T\gamma)$., Comment: 8 pages, 3 figures, changed content Pacs{64}{70.Pf}{Glass transitions} Pacs{05}{70.Ln}{Non-equilibrium thermodynamics, irreversible processes} Pacs{83}{50.Ax}{Steady shear flows}

The effect of shear flow on the phase-ordering dynamics of a binary mixture with field-dependent mobility is investigated. The problem is addressed in the context of the time-dependent Ginzburg-Landau equation with an external velocity term, studied in self-consistent approximation. Assuming a scaling ansatz for the structure factor, the asymptotic behavior of the observables in the scaling regime can be analytically calculated. All the observables show log-time periodic oscillations which we interpret as due to a cyclical mechanism of stretching and break-up of domains. These oscillations are dumped as consequence of the vanishing of the mobility in the bulk phase., Comment: 9 pages, 4 figures, EPJ style