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Algorithmic fairness in recommender systems requires close attention to the needs of a diverse set of stakeholders that may have competing interests. Previous work in this area has often been limited by fixed, single-objective definitions of fairness, built into algorithms or optimization criteria that are applied to a single fairness dimension or, at most, applied identically across dimensions. These narrow conceptualizations limit the ability to adapt fairness-aware solutions to the wide range of stakeholder needs and fairness definitions that arise in practice. Our work approaches recommendation fairness from the standpoint of computational social choice, using a multi-agent framework. In this paper, we explore the properties of different social choice mechanisms and demonstrate the successful integration of multiple, heterogeneous fairness definitions across multiple data sets.

Synthetic data is a useful resource for algorithmic research. It allows for the evaluation of systems under a range of conditions that might be difficult to achieve in real world settings. In recommender systems, the use of synthetic data is somewhat limited; some work has concentrated on building user-item interaction data at large scale. We believe that fairness-aware recommendation research can benefit from simulated data as it allows the study of protected groups and their interactions without depending on sensitive data that needs privacy protection. In this paper, we propose a novel type of data for fairness-aware recommendation: synthetic recommender system outputs that can be used to study re-ranking algorithms.

Malware detection is a constant challenge in cybersecurity due to the rapid development of new attack techniques. Traditional signature-based approaches struggle to keep pace with the sheer volume of malware samples. Machine learning offers a promising solution, but faces issues of generalization to unseen samples and a lack of explanation for the instances identified as malware. However, human-understandable explanations are especially important in security-critical fields, where understanding model decisions is crucial for trust and legal compliance. While deep learning models excel at malware detection, their black-box nature hinders explainability. Conversely, interpretable models often fall short in performance. To bridge this gap in this application domain, we propose the use of Logic Explained Networks (LENs), which are a recently proposed class of interpretable neural networks providing explanations in the form of First-Order Logic (FOL) rules. This paper extends the application of LENs to the complex domain of malware detection, specifically using the large-scale EMBER dataset. In the experimental results we show that LENs achieve robustness that exceeds traditional interpretable methods and that are rivaling black-box models. Moreover, we introduce a tailored version of LENs that is shown to generate logic explanations with higher fidelity with respect to the model's predictions.

Ontologies are a standard tool for creating semantic schemata in many knowledge intensive domains of human interest. They are becoming increasingly important also in the areas that have been until very recently dominated by subsymbolic knowledge representation and machine-learning (ML) based data processing. One such area is information security, and specifically, malware detection. We thus propose PE Malware Ontology that offers a reusable semantic schema for Portable Executable (PE - the Windows binary format) malware files. This ontology is inspired by the structure of the EMBER dataset, which focuses on the static malware analysis of PE files. With this proposal, we hope to provide a unified semantic representation for the existing and future PE-malware datasets and facilitate the application of symbolic, neuro-symbolic, or otherwise explainable approaches in the PE-malware-detection domain, which may produce interpretable results described by the terms defined in our ontology. In addition, we also publish semantically treated EMBER data, including fractional datasets, to support the reproducibility of experiments on EMBER. We supplement our work with a preliminary case study, conducted using concept learning, to show the general feasibility of our approach. While we were not able to match the precision of the state-of-the-art ML tools, the learned malware discriminators were interesting and highly interpretable., Comment: arXiv admin note: substantial text overlap with arXiv:2301.00153

This contribution presents the recent research developments within the Cosmic Ray Extremely Distributed Observatory (CREDO) in the search for resolution of various scientific puzzles, ranging from fundamental physical questions to applications like the determination of earthquake precursors. The state-of-the art theoretical, numerical and computational aspects of these phenomena are addressed, as well as recent experimental developments for detection., Comment: 9 pages, 7 figures. Based on the contribution to the XVIII Mexican Workshop on Particles and Fields in Puebla, Mexico, November 2022. M\'exico

In this contribution we study the possibility of the formation of cosmic ray ensembles (CRE) created by the interaction of ultra-high energy (UHE) photons with the magnetic field of the Sun. The lack of observation of those UHE and the difficulties for their identification given the current methodologies motivates this study. We performed simulations using the PRESHOWER program in order to simulate the expected extensive air showers which might be spatially correlated generated upon entering the Earth's atmosphere. We found characteristic features like very thing and extremely elongates cascades of secondary photons with their corresponding energies spanning the entire cosmic range spectrum. Shower footprints are as large as hundreds of kilometres. An application of this study is the scenario of gamma-ray emission from the vicinity of the Sun as a result of ultra-high energy photon cascading in the solar magnetic field in order to understand recent observations made by the HAWC and Fermi-LAT observatories., Comment: 8 pages, 4 figures, 38th International Cosmic Ray Conference (ICRC2023) 26 July - 3 August, 2023 Nagoya, Japan

Ontologies are a standard for semantic schemata in many knowledge-intensive domains of human interest. They are now becoming increasingly important also in areas until very recently dominated by subsymbolic representations and machine-learning-based data processing. One such area is information security, and more specifically malware detection. We propose PE Malware Ontology that offers a reusable semantic schema for Portable Executable (PE, Windows binary format) malware files. The ontology was inspired by the structure of the data in the EMBER dataset and it currently covers the data intended for static malware analysis. With this proposal, we hope to achieve: a) a unified semantic representation for PE malware datasets that are available or will be published in the future; (b) applicability of symbolic, neural-symbolic, or otherwise explainable approaches in the PE Malware domain that may lead to improved interpretability of results which may now be characterized by the terms defined in the ontology; and (c)by joint publishing of semantically treated EMBER data, including fractional datasets, also improved reproducibility of experiments.

After a natural disaster, such as a hurricane, millions are left in need of emergency assistance. To allocate resources optimally, human planners need to accurately analyze data that can flow in large volumes from several sources. This motivates the development of multimodal machine learning frameworks that can integrate multiple data sources and leverage them efficiently. To date, the research community has mainly focused on unimodal reasoning to provide granular assessments of the damage. Moreover, previous studies mostly rely on post-disaster images, which may take several days to become available. In this work, we propose a multimodal framework (GaLeNet) for assessing the severity of damage by complementing pre-disaster images with weather data and the trajectory of the hurricane. Through extensive experiments on data from two hurricanes, we demonstrate (i) the merits of multimodal approaches compared to unimodal methods, and (ii) the effectiveness of GaLeNet at fusing various modalities. Furthermore, we show that GaLeNet can leverage pre-disaster images in the absence of post-disaster images, preventing substantial delays in decision making., Comment: Accepted to CVPR 2022 Workshop on Multimodal Learning for Earth and Environment

Both the lack of observation of ultra-high energy (UHE) photons and the limitations of the state-of-the-art methodology being applied for their identification motivate studies on alternative approaches to the relevant simulations and the related observational strategies. One of such new approaches is proposed in this report and it concerns new observables allowing indirect identification of UHE photons through cosmic ray phenomena composed of many spatially correlated extensive air showers or primary cosmic rays observed at one time. The study is based on simulations of interactions of UHE photons with the magnetic field of the Sun using the PRESHOWER program with some essential modifications. One of the expected results of such interactions is a generation of cosmic ray ensembles (CRE) in the form of very thin and very elongated cascades of secondary photons of energies spanning the whole cosmic ray energy spectrum. Upon entering the Earth's atmosphere, these cascades or their parts may generate uniquely characteristic walls of spatially correlated extensive air showers, and the effect is expected also in cases when primary UHE photons are not directed towards the Earth. Particle distributions in these multi-primary UHE photon footprints are expected to have thicknesses of the order of meters and elongations reaching even hundreds of millions kilometers, making them potentially observable with a global, multi-experiment approach, including re-exploring of the historical data, with the expected event rate exceeding the capabilities of even very large cosmic ray observatories. The methods described in this report allow for simulating potentially observable quantities related to CRE induced by UHE photons: densities, energy spectra and geographical orientations of particles at the top of the Earth's atmosphere., Comment: 15 pages, 9 figures

The present white paper is submitted as part of the "Snowmass" process to help inform the long-term plans of the United States Department of Energy and the National Science Foundation for high-energy physics. It summarizes the science questions driving the Ultra-High-Energy Cosmic-Ray (UHECR) community and provides recommendations on the strategy to answer them in the next two decades., Comment: Prepared as a solicited white paper for the 2021 Snowmass process. To be published in the Journal of High Energy Astrophysics. v2: fixed typos in author list. v3: included all community feedback received by July 1st 2022 and added the list of endorsers. v4 is the post-reviewer preprint accepted to Astroparticle Physics vol. 149

The search for correlations between secondary cosmic ray detection rates and seismic effects has long been a subject of investigation motivated by the hope of identifying a new precursor type that could feed a global early warning system against earthquakes. Here we show for the first time that the average variation of the cosmic ray detection rates correlates with the global seismic activity to be observed with a time lag of approximately two weeks, and that the significance of the effect varies with a periodicity resembling the undecenal solar cycle, with a shift in phase of around three years, exceeding 6 sigma at local maxima. The precursor characteristics of the observed correlations point to a pioneer perspective of an early warning system against earthquakes., Comment: 16 pages, 4 figures in the main article and 11 pages and 4 figures in the Suplementary Material

The last decade has brought about a profound transformation in multimessenger science. Ten years ago, facilities had been built or were under construction that would eventually discover the nature of objects in our universe could be detected through multiple messengers. Nonetheless, multimessenger science was hardly more than a dream. The rewards for our foresight were finally realized through IceCube's discovery of the diffuse astrophysical neutrino flux, the first observation of gravitational waves by LIGO, and the first joint detections in gravitational waves and photons and in neutrinos and photons. Today we live in the dawn of the multimessenger era. The successes of the multimessenger campaigns of the last decade have pushed multimessenger science to the forefront of priority science areas in both the particle physics and the astrophysics communities. Multimessenger science provides new methods of testing fundamental theories about the nature of matter and energy, particularly in conditions that are not reproducible on Earth. This white paper will present the science and facilities that will provide opportunities for the particle physics community renew its commitment and maintain its leadership in multimessenger science., Comment: 174 pages, 12 figures. Contribution to Snowmass 2021. Solicited white paper from CF07. Comments and endorsers welcome. Still accepting contributions (contact editors)

Cosmic Ray Ensembles (CRE) are yet not observed groups of cosmic rays with a common primary interaction vertex or the same parent particle. One of the processes capable of initiating identifiable CRE is an interaction of an ultra-high energy (UHE) photon with the solar magnetic field which results in an electron pair production and the subsequent synchrotron radiation. The resultant electromagnetic cascade forms a very characteristic line-like front of a very small width ($\sim$ meters), stretching from tens of thousands to even many millions of kilometers. In this contribution we present the results of applying a toy model to simulate detections of such CRE at the ground level with an array of ideal detectors of different dimensions. The adopted approach allows us to assess the CRE detection feasibility for a specific configuration of a detector array. The process of initiation and propagation of an electromagnetic cascade originated from an UHE photon passing near the Sun, as well as the resultant particle distribution on ground, were simulated using the CORSIKA program with the PRESHOWER option, both modified accordingly. The studied scenario results in photons forming a cascade that extends even over tens of millions of kilometers when it arrives at the top of the Earth's atmosphere, and the photon energies span practically the whole cosmic ray energy spectrum. The topology of the signal consists of very extended CRE shapes, and the characteristic, very much elongated disk-shape of the particle distribution on ground illustrates the potential for identification of CRE of this type., Comment: 8 pages, 3 figures. Proceedings of the International Cosmic Rays Conference 2021, 12-23 July, Berlin, Germany

The wealth of smartphone data collected by the Cosmic Ray Extremely Distributed Observatory(CREDO) greatly surpasses the capabilities of manual analysis. So, efficient means of rejectingthe non-cosmic-ray noise and identification of signals attributable to extensive air showers arenecessary. To address these problems we discuss a Convolutional Neural Network-based method ofartefact rejection and complementary method of particle identification based on common statisticalclassifiers as well as their ensemble extensions. These approaches are based on supervised learning,so we need to provide a representative subset of the CREDO dataset for training and validation.According to this approach over 2300 images were chosen and manually labeled by 5 judges.The images were split into spot, track, worm (collectively named signals) and artefact classes.Then the preprocessing consisting of luminance summation of RGB channels (grayscaling) andbackground removal by adaptive thresholding was performed. For purposes of artefact rejectionthe binary CNN-based classifier was proposed which is able to distinguish between artefacts andsignals. The classifier was fed with input data in the form of Daubechies wavelet transformedimages. In the case of cosmic ray signal classification, the well-known feature-based classifierswere considered. As feature descriptors, we used Zernike moments with additional feature relatedto total image luminance. For the problem of artefact rejection, we obtained an accuracy of 99%. For the 4-class signal classification, the best performing classifiers achieved a recognition rate of 88%., Comment: 9 pages,4 figurek, ICRC 2021 contribution

The Cosmic Ray Extremely Distributed Observatory (CREDO) is a newly formed, global collaboration dedicated to observing and studying cosmic rays (CR) and cosmic ray ensembles (CRE): groups of a minimum of two CR with a common primary interaction vertex or the same parent particle. The CREDO program embraces testing known CR and CRE scenarios, and preparing to observe unexpected physics, it is also suitable for multi-messenger and multi-mission applications. Perfectly matched to CREDO capabilities, CRE could be formed both within classical models (e.g. as products of photon-photon interactions), and exotic scenarios (e.g. as results of decay of Super Heavy Dark Matter particles). Their fronts might be significantly extended in space and time, and they might include cosmic rays of energies spanning the whole cosmic ray energy spectrum, with a footprint composed of at least two extensive air showers with correlated arrival directions and arrival times. Since CRE are mostly expected to be spread over large areas and, because of the expected wide energy range of the contributing particles, CRE detection might only be feasible when using available cosmic ray infrastructure collectively, i.e. as a globally extended network of detectors. Thus, with this review article, the CREDO Collaboration invites the astroparticle physics community to actively join or to contribute to the research dedicated to CRE, and in particular to share any cosmic ray data useful for the specific CRE detection strategies., Comment: 59 pages, 23 figures

The Cosmic-Ray Extremely Distributed Observatory (CREDO) is a project created a few years ago in the Institute of Nuclear Physics PAS in Krak\'ow and dedicated is to global studies of extremely extended cosmic-ray phenomena. The main reason for creating such a project was that the cosmic-ray ensembles (CRE) are beyond the capabilities of existing detectors and observatories. Until now, cosmic ray studies, even in major observatories, have been limited to the recording and analysis of individual air showers therefore ensembles of cosmic-rays, which may spread over a significant fraction of the Earth were neither recorded nor analyzed. In this paper the status and perspectives of the CREDO project are presented., Comment: 8 pages, 5 figures

We study the feasibility of detecting preshower initiated by ultra-high energy photons using Monte-Carlo simulations of nearly horizontal air showers for the example of the La Palma site of the Cherenkov Telescope Array. We investigate the efficiency of multivariate analysis in correctly identifying preshower events initiated by 40 EeV photons and cosmic-ray dominated background simulated in the energy range 10 TeV -- 10 EeV. The effective areas for such kind of events are also investigated and event rate predictions related to different ultra-high energy photons production models are presented. While the expected number of preshowers from diffuse emission of UHE photon for 30 hours of observation is estimated around $3.3\times10^{-5}$ based on the upper limits put by the Pierre Auger Observatory, this value is at the level of $2.7\times10^{-4}$ ($5.7\times 10^{-5}$) when considering the upper limits of the Pierre Auger Observatory (Telescope Array) on UHE photon point sources. However, UHE photon emission may undergo possible "boosting" due to gamma-ray burst, increasing the expected number of preshower events up to 0.17 and yielding a minimum required flux of $\sim 0.2$ $\mathrm{km^{-2}yr^{-1}}$ to obtain one preshower event, which is about a factor 10 higher than upper limits put by the Pierre Auger Observatory and Telescope Array (0.034 and 0.019 $\mathrm{km^{-2}yr^{-1}}$, respectively)., Comment: 16 pages, 16 figures, 4 tables

Muons and other ionizing radiation produced by cosmic rays and radiative decays affect CMOS/CCD sensor. When particles colliding with sensors atoms cause specific kind of noise on images recorded by cameras. We present a concept and preliminary implementation of method for recognizing those events and algorithms for image processing and their classification by machine learning. Our method consists of analyzing the shape of traces present in images recorded by a camera sensor and metadata related to an image like camera model, GPS location of camera, vertical and horizontal orientation of a camera sensor, timestamp of image acquisition, and other events recognized near-by sensors. The so created feature vectors are classified as either a muon-like event, an electron-like event or the other event, possibly noise. For muon-like events our method estimates azimuth of a muon track. Source of the data is database of CREDO (Cosmic-Ray Extremely Distributed Observatory) project and ESO (European Southern Observatory) archives. The telescope dark frames from ESO are analysed. CREDO project collected so far over 2 millions images of events from many kinds of cameralike: smartphones camera, laptop webcams and Internet of Things cameras localised around the globe., Comment: 36th International Cosmic Ray Conference (ICRC2019)

The search for Cosmic-Ray Ensembles (CRE), groups of correlated cosmic rays that might be distributed over very large areas, even of the size of the planet, requires a globally spread and dense network of detectors, as proposed by the Cosmic-Ray Extremely Distributed Observatory (CREDO) Collaboration. This proposal motivates an effort towards exploring the potential of using even very much diversified detection technologies within one system, with detection units located even in hard-to-reach places, where, nevertheless, the sensors could work independently - without human intervention. For these reasons we have developed a dedicated communication solution enabling the connection of many different types of detectors, in a range of environments. The proposed data transmission system uses radio waves as an information carrier on the 169MHz frequency band in a contrast to the typical commercially used frequencies in a IoT systems (868MHz). The connectivity within the system is based on the star topology, which ensures the least energy consumption. The solution is now being prepared to being implemented using the prototype detection system based on the CosmicWatch open hardware design: a portable, pocket size, and economy particle detector using the scintillation technique. Our prototype detector is equipped with a dedicated software that integrates it with the already operational CREDO server system., Comment: ICRC2019

The Cosmic-Ray Extremely Distributed Observatory (CREDO) uses the hunt for particle cascades from deep space as a vehicle for a unique "bottom-up" approach to scientific research. By engaging the non-specialist public of all ages as "citizen scientists" we create opportunities for lifelong learning for individuals as well as for cooperation and the sharing of common educational tools amongst institutions. The discoveries of these citizen scientists will feed directly into a pioneering new area of scientific research oriented on Cosmic Ray Ensembles (CRE). The detection (or non-detection) of such particle groups promises to open up a new method for exploring our universe, and a new channel on the multi-messenger stage, oriented on both astro- and geo-investigations. The opportunities this would create for cross-disciplinary research are significant and beneficial for individuals, networks of institutions and the global communities of both professional scientists and science enthusiasts., Comment: 4 pages, 3 figures, Proceedings The New Era of Multi-Messenger Astrophysics - Asterics2019, 25 - 29 March, 2019 Groningen, The Netherlands

Ultra-high energy photons constitute one of the most important pieces of the astroparticle physics problems. Their observation may provide new insight on several phenomena such as supermassive particle annihilation or the GZK effect. Because of the absence of any significant photon identification by a leading experiments such as the Pierre Auger Observatory, we consider a screening phenomenon called preshower effect which could efficiently affect ultra-high energy photon propagation. This effect is a consequence of photon interactions with the geomagnetic field and results in large electromagnetic cascade of particles several thousands kilometers above the atmosphere. This collection of particles, called cosmic-ray ensembles (CRE), may reach the atmosphere and produce the well-known air showers. In this paper we propose to use gamma-ray telescopes to look for air showers induced by CRE. Possible sources of ultra-high energy photons include the GZK effect and Super Heavy Dark Matter particles. Simulations involving the preshower effect and detectors response are performed and properties of these peculiar air showers are investigated. The use of boosted decision trees to obtain the best cosmic-ray ensemble/hadron separation, the aperture and event rate predictions for a few models of photon production are also presented., Comment: 8 pages, 3 figures, International Cosmic Ray Conference 2019

Propagation of ultra-high energy photons in the galactic and intergalactic space gives rise to cascades comprising thousands of photons. Using Monte Carlo simulations, we investigate the development of such cascades in the solar magnetosphere, and find that the photons in the cascades are distributed over hundreds of kilometers as they arrive at the top of the Earth's atmosphere. We also perform similar study for cascades starting as far as 10 Mpc away from us using relevant magnetic field models. A few photons correlated in time are expected to arrive at the Earth from the latter type of cascade. We present our simulation results and discuss the prospects for detection of these cascades with the Cosmic-Ray Extremely Distributed Observatory.

The Cosmic-Ray Extremely Distributed Observatory (CREDO) is a project dedicated to global studies of extremely extended cosmic-ray phenomena, the cosmic-ray ensembles (CRE), beyond the capabilities of existing detectors and observatories. Up to date cosmic-ray research has been focused on detecting single air showers, while the search for ensembles of cosmic-rays, which may spread over a significant fraction of the Earth, is a scientific terra incognita. The key idea of CREDO is to combine existing cosmic-ray detectors (large professional arrays, educational instruments, individual detectors, such as smartphones, etc.) into a worldwide network, thus enabling a global analysis. The second goal of CREDO involves a large number of participants (citizen science!), assuring the geographical spread of the detectors and managing manpower necessary to deal with vast amount of data to search for evidence for cosmic-ray ensembles. In this paper the status and perspectives of the project are presented., Comment: Proceedings of 36th International Cosmic Ray Conference - ICRC2019 - July 24th - August 1st, 2019 Madison, WI, U.S.A

Neutrinos with energies above $10^{17}$ eV are detectable with the Surface Detector Array of the Pierre Auger Observatory. The identification is efficiently performed for neutrinos of all flavors interacting in the atmosphere at large zenith angles, as well as for Earth-skimming $\tau$ neutrinos with nearly tangential trajectories relative to the earth. No neutrino candidates were found in $\sim\,14.7$ years of data taken up to 31 August 2018. This leads to restrictive upper bounds on their flux. The $90\%$ C.L. single-flavor limit to the diffuse flux of ultra-high-energy neutrinos with an $E_\nu^{-2}$ spectrum in the energy range $1.0 \times 10^{17}~{\rm eV} - 2.5 \times 10^{19}~{\rm eV}$ is $E^2 {\rm d}N_\nu/{\rm d}E_\nu < 4.4 \times 10^{-9}~{\rm GeV~cm^{-2}~s^{-1}~sr^{-1}}$, placing strong constraints on several models of neutrino production at EeV energies and on the properties of the sources of ultra-high-energy cosmic rays., Comment: Published version, 27 pages, 7 figures, 2 tables

With the Surface Detector array (SD) of the Pierre Auger Observatory we can detect neutrinos with energy between $10^{17}\,$eV and $10^{20}\,$eV from point-like sources across the sky, from close to the Southern Celestial Pole up to $60^\circ$ in declination, with peak sensitivities at declinations around $\sim -53^\circ$ and $\sim+55^\circ$, and an unmatched sensitivity for arrival directions in the Northern hemisphere. A search has been performed for highly-inclined air showers induced by neutrinos of all flavours with no candidate events found in data taken between 1 Jan 2004 and 31 Aug 2018. Upper limits on the neutrino flux from point-like steady sources have been derived as a function of source declination. An unrivaled sensitivity is achieved in searches for transient sources with emission lasting over an hour or less, if they occur within the field of view corresponding to the zenith angle range between $60^\circ$ and $~95^\circ$ where the SD of the Pierre Auger Observatory is most sensitive to neutrinos., Comment: 25 pages, 9 figures

An overview of the multi-messenger capabilities of the Pierre Auger Observatory is presented. The techniques and performance of searching for Ultra-High Energy neutrinos, photons and neutrons are described. Some of the most relevant results are reviewed, such as stringent upper bounds that were placed to a flux of diffuse cosmogenic neutrinos and photons, bounds placed on neutrinos emitted from compact binary mergers that were detected by LIGO and Virgo during their first and second observing runs, as well as searches for high energy photons and neutrons from the Galactic center that constrain the properties of the putative Galactic PeVatron, observed by the H.E.S.S.\ collaboration. The observation of directional correlations between ultra-high energy cosmic rays and either high energy astrophysical neutrinos or specific source populations, weighted by their electromagnetic radiation, are also discussed. They constitute additional multi-messenger approaches aimed at identifying the sources of high energy cosmic rays., Comment: 28 pages, 7 figures, Review published in Frontiers in Astronomy and Space Sciences