bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hardware Sequence Combinators
Authors: Taylor Stephen , Pope Gunnar 
Published: March 2024

Recent advances in formal methods for constructing parsers have employed the notion of combinators: primitive elemental parsers with well-defined methods for combining them in sequences or through choice. This paper explores the subtleties associated with leveraging sequence combinators to produce compact, custom hardware traffic validators. This involves a fully automated process that takes as input a formal grammar specifying message formats and produces a parsing circuit capable of validating traffic headers and payload content. The resulting circuit is deployed through network guard appliances that employ Field Programmable Gate Array (FPGA) devices, or alternatively, within the on-chip FPGA associated with System-on-Chip (SoC) devices, such as the Xilinx UltraScale MPSoC. Each guard appliance acts as a hidden “bump-in-the-wire” that either forwards or drops individual packets based on the message parsing outcome, thereby hardening network segments against zero-day attacks and persistent implants. Guards may operate on a wide variety traffic protocols and formats including TCP/IP, CAN/J1939, or MIL-STD-1553. The central step in parser construction is to build a collection of standard shift/reduce parsing tables that can be employed by a push-down automata to check each byte in a message. Typically, these tables are sparse, resulting in excessive use of FPGA circuit resources to represent them. By leveraging sequence combinators, along with other optimizations, we have been able to produce highly compact representations that can reduce table size by up to 95% for non-trivial grammars. Depending on the grammar, this translates directly into FPGA resource reductions. The reductions now make it viable to implement complex parsers on small, inexpensive FPGA’s, or alternatively combine parsers with encryption and encapsulation to enhance guard capabilities.
Chain of Custody and Evidence Integrity Verification Using Blockchain Technology
Authors: Miller Adir , Singh Avinash 
Published: March 2024

The validity and integrity of digital evidence and the chain of custody are crucial to all digital forensic investigations. All new evidence and access logs of the original evidence should be logged in a document called the ‘chain of custody’. This document shows the timeline of any piece of evidence from the time it was recorded until the end of the investigation. In a traditional digital investigation, trusted parties, such as an investigator, are allowed access to the digital evidence and follow a strict process when dealing with data. These trusted parties have the capability to alter the data making the evidence inadmissible in a court of law. Alternatively, these trusted parties may also alter the data accidentally or with malicious intent, due to a lack of transparency and non-repudiation. Blockchain technology can solve this issue, however, existing research shows that adopting blockchain does not provide adequate transparent access control mechanisms. Consequently, this makes blockchain difficult to adopt due to the one-to-one mapping and the inability to easily validate the chain of custody and evidence admissibility. Current methodologies rely on an external off-chain access control mechanism, which, regrettably, remains susceptible to potential breaches that could compromise its integrity and validity. This paper proposes an enhanced model to provide access control through smart contracts, ensuring immutability, flexibility, transparency, and non-repudiation of both the access control mechanisms and the digital evidence itself. This is achieved by moving the access control mechanism to the blockchain. This tracks any changes made through the access control mechanism, further ensuring transparency and integrity. This smart contract-based access control builds off role-based access control, allowing for more complex hierarchies to be used. This model aims to allow for both modularity, making adoption easier for existing digital forensic tools, and encouraging digital investigation and litigation to become more streamlined. Existing tools can easily integrate with the proposed model adding an extra layer of non-repudiation, transparency, and integrity.
Authentication in a Hyperconnected World: Challenges, Opportunities and Approaches
Authors: Lipps Christoph , Herbst Jan , Reddy Rekha , Rüb Matthias , Schotten Hans D. 
Published: March 2024

Authentication and integrity are the prerequisites for trustworthy and secure communication. Without unambiguous knowledge of who is being interacted with, no confidential content can be exchanged, no (remote) access to systems and equipment can be granted, and no trust can be established. This situation is further exacerbated by an increasing interconnection and globalization towards a hyperconnected world. (Communication) Participants are no longer necessarily in close physical and social proximity and do not need to know each other, but can have their source/destination anywhere in the world.
An authentication process is used to verify that someone -whether human or machine-, is in fact who she claims to be: The process thus includes a validation step to evaluate an assertion. However, systems differ in terms of their requirements, for instance with regard to the authentication options available, the time period required for re-authentication and the frequency of re-authentication, as well as the level of security to be achieved with authentication. The latter particularly with regard to the cost/benefit ratio of the application. Additionally, there are efforts to finally abolish traditional passwords, passphrases and pin codes and render them obsolete.
In this work, technologies and methods for authentication beyond passwords and trustworthy authentication will be examined, particularly with regard to future communication infrastructures such as Beyond 5G and Sixth Generation (6G) wireless systems. Thereby, the impact of Artificial Intelligence (AI) methods, but also the relevance to Quantum Key Distribution (QKD) and Post Quantum Cryptography, as well as the use of 6G-enabling technologies like Reconfigurable Intelligent Surfaces (RISs), Wireless Optical Communication (WOC) and Physical Layer Security (PhySec), for example as additional factors of a multi-factor authentication process, will be considered, along with Body Area Networks (BANs) and the integration of the human body relying on biometrics. The various concepts are compared with regard to their requirements, limitations and possible applications in order to provide the user with an orientation as to which authentication method is conceivable and useful in which specific scenarios.
Unpacking AI Security Considerations
Authors: Veerasamy Namosha , Badenhorst Danielle , Ntshangase Mazwi , Baloyi Errol , Siphambili Noku , Mahlasela Oyena 
Published: March 2024

The field of Artificial Intelligence has emerged as a convincing tool to be used in a myriad of applications like finance, traffic prediction, health and travel sectors. Due to the enormous benefits provided in terms of automation, convenience, processing time, reduced manhours, and productivity, AI is being seen as the next technical revolution. AI is being showcased as a useful tool to stimulate creativity as well as provide support with its tremendous computational power. The release of tools like ChatGPT has exploded onto the technological scene. Users are making use of Large Language Models (LLMs) and tools to perform a host of activities like writing an essay, translating documents, and finding travel plans. However, the popularity of these tools has not been without risk. In the technology marketplace, the race to dominance can force competitors to waive safety concerns in favour of product adoption. Many are unaware of the potential dangers and risks that may inherently reside within AI tools. This paper looks at the potential risks of AI tools such the creation of misinformation or scams. AI security has now become a paramount concern that should not be ignored. In this paper, the potential risks and threat vectors of Artificial Intelligence will be covered. The aim will be to provide insight into the malicious use of Artificial Intelligence Tools through a discussion of techniques to bypass security controls. The paper aims to provide a more detailed account on how AI can be manipulated in order to empower users about the latest attack schemes.
Modeling the Semantics of Failure Context as a means to offer Context-Adaptive Maintenance Support
Authors: Pistofidis Petros , Emmanouilidis Christos , Papadopoulos Aggelos , N. Botsaris Pantelis 
Published: March 2024

Acting upon the data involved in typical diagnostics and prognostics tasks is often confounded by the complexity of the corresponding situation and needs to take into account domain-specific or even installation-specific knowledge considerations. While domain knowledge is often captured in various forms, such as is typically done in Fault Modes, Effects and Criticality Analysis (FMECA), the contextualisation of the captured data and related knowledge to a corresponding situation, in other words a situated-aware modeling of data and knowledge, is often missing. Our research leverages the efficiency of maintenance support for mobile actors. Investing in modern service provision technologies, this work targets the effectiveness of capturing and sharing field expertise. An analysis of both the modeling specification and the functional requirements for such an approach. is provided. The semantics of “Failure Context”, a context that guides user’s navigation towards relevant diagnostics and maintenance-related knowledge, are mapped into an appropriate data schema. Based on this, a system capable of managing the core information of the Failure Context, while offering adequate tools that support experts to build on, browse through, and reach contextuallyrelevant decisions is implemented. The development follows a reference-annotation design pattern to deliver on spot capture and enrichment of maintenance-related knowledge. Thus, the developed system provides the means for the effective management and exploitation of 'micro-knowledge fragments', associated with FMECA-related entities and knowledge. This is a significant enabler for the effective elicitation and management of field-captured expertise, enabling the enrichment and validation of maintenancerelated knowledge.
Simulation of wind turbine faulty production profiles and performance assessment of fault monitoring methods
Authors: Aziz Usama , Charbonnier Sylvie , Bérenguer Christophe , Lebranchu Alexis , Prevost Frederic 
Published: March 2024

Wind turbines being one of the fastest growing sources of renewable energy have garnered significant scientific interest for the monitoring and fault analysis using SCADA data. Various monitoring approaches using power curves, i.e. industry wide characteristic curves expressing produced power as a function of wind speed, have been proposed in the literature. However, an objective comparison of the performance of these methods is difficult. The difficulty comes from (i) the variability in operational and environmental conditions taken into account; (ii) the nature, size and type of data-sets used and (iii) the type and signatures of faults considered for validation. To solve this problem, an approach with a twofold contribution is proposed in this work: 1) an original procedure to generate realistic and controlled simulations of 10 minutes SCADA data, simulating situations when the wind turbine is operating in normal or faulty conditions, is presented; 2) a framework for objective performance assessment of the fault detection methods, based on the proposed controlled and standardized simulation scheme is presented. Objective performance evaluation metrics, such as detection probability and false alarm rates are computed and represented as characteristic Receiver Operating Curves (ROC). The proposed simulation approach is shown to provide a useful global framework for objective performance analysis. A number of realistically simulated and controlled data streams are used to compare and discuss the performances of two fault detection methods referenced in the literature.
Predicting RUL of Bearings in the Pumps of a Critical Industrial Air Treatment System
Authors: Beirami Hani , Calzà Davide , Cimatti Alessandro , Islam Manjurul M , Roveri Marco , Svaizer Piergiorgio 
Published: March 2024

Predictive maintenance is emerging as a promising technique to overcome the limitations of periodic maintenance. It integrates automatic condition monitoring to evaluate the health status of a system or device, with the estimation of Remaining Useful Life (RUL) of its components, in order to schedule maintenance only when really needed, minimizing the downtime of a plant.
In this paper, we report our results in evaluating the health conditions of the rotating ball bearings of a critical air pump which is part of the Clean Room industrial facility operating in the Micro-Technologies Laboratory of Fondazione Bruno Kessler. We instrumented such component with vibration and acoustic sensors with the aim of identifying a model of the evolving degradation and estimating the RUL of the bearings. The current dataset covers a period of one month before bearing replacement and about six months after the replacement. The first models, based on regression and particle filter processing of critical spectral components extracted from the sensors, indicate an estimated RUL of about 12 months that is in agreement with the average lifetime based on scheduled maintenance. Subsequent model evolutions have been observed in conjunction with scheduled greasing and periods of lower stress, which resulted in remarkable deviations from the initial degradation trends and in a consequent notable increase of the estimated RUL.
Results achieved so far are promising and could be used to extend the temporal distance among periodic maintenance interventions according to the estimated RUL.
CONCEPÇÕES E PRÁTICAS DE PROFESSORES DE MATEMÁTICA DO ENSINO MÉDIO DE JI-PARANÁ (RO):
Authors: Dos Santos Ivone Aparecida , Fonseca de Castro Rafael 
Published: March 2024

Este artigo é fruto de uma pesquisa que investigou as concepções e as práticas pedagógicas de 18 professores de Matemática que atuam no Ensino Médio, em onze escolas públicas urbanas do município de Ji-Paraná (RO), interior do estado de Rondônia. O presente artigo analisa as percepções desses professores quanto a suas concepções teóricas e suas práticas pedagógicas no escopo da Educação Matemática na sociedade contemporânea, com fundamentação teórica em pressupostos da Teoria Histórico-Cultural e dialogando com pesquisadores que estudam a Educação Matemática. Trata-se de uma investigação de abordagem qualitativa, do tipo exploratória, com dados coletados mediante questionário disponibilizado on-line via Google Forms. A análise textual discursiva dos dados revelou, fundamentalmente, o seguinte: a) 33,33% dos professores adotam concepções tradicionais de ensino; b) 22,22% vinculam suas práticas ao construtivismo e às teorias do “aprender a aprender”; c) apenas 22,22% buscam inovar em suas atividades docentes; d) 22,22% não sustentam sua prática em nenhuma teoria educacional ou psicológica; e) autores ou pressupostos vinculados à Teoria Histórico-Cultural praticamente não são mencionados pelos professores pesquisados, indo ao encontro de outros
estudos por nós realizados na Amazônia Ocidental. A pesquisa ajuda a melhor compreender as concepções teórico-práticas de professores de Matemática atuantes no Ensino Médio, especificamente, no estado de Rondônia. São necessários, porém, novos estudos, em diferentes contextos históricos e culturais do país, para poder constituir um panorama mais abrangente em termos nacionais.
Ebbinghaus, Müller-Lyer, and Ponzo: Three examples of bidirectional space-time interference
Authors: Bratzke Daniel 
Published: March 2024

AbstractPrevious studies have shown interference between illusory size and perceived duration. The present study replicated this space-time interference in three classic visual-spatial illusions, the Ebbinghaus, the Müller-Lyer, and the Ponzo illusion. The results showed bidirectional interference between illusory size and duration for all three illusions. That is, subjectively larger stimuli were judged to be presented longer, and stimuli that were presented longer were judged to be larger. Thus, cross-dimensional interference between illusory size and duration appears to be a robust phenomenon and to generalize across a wide range of visual size illusions. This space-time interference most likely arises at the memory level and supports the theoretical notion of a common representational metric for space and time.
Quantifying resource sharing in working memory
Authors: Pougeon Julie , Camos Valérie , Belletier Clément , Barrouillet Pierre 
Published: March 2024

AbstractSeveral models of working memory (WM), the cognitive system devoted to the temporary maintenance of a small amount of information in view of its treatment, assume that these two functions of storage and processing share a common and limited resource. However, the predictions issued from these models concerning this resource-sharing remain usually qualitative, and at which precise extent these functions are affected by their concurrent implementation remains undecided. The aim of the present study was to quantify this resource sharing by expressing storage and processing performance during a complex span task in terms of the proportion of the highest level of performance each participant was able to reach (i.e., their span) in each component when performed in isolation. Two experiments demonstrated that, despite substantial dual-task decrements, participants managed to preserve half or more of their best performance in both components, testifying for a remarkable robustness of the human cognitive system. The implications of these results for the main WM models are discussed.
HBMIRT: A SAS macro for estimating uni- and multidimensional 1- and 2-parameter item response models in small (and large!) samples
Authors: Wagner Wolfgang , Zitzmann Steffen , Hecht Martin 
Published: March 2024

AbstractItem response theory (IRT) has evolved as a standard psychometric approach in recent years, in particular for test construction based on dichotomous (i.e., true/false) items. Unfortunately, large samples are typically needed for item refinement in unidimensional models and even more so in the multidimensional case. However, Bayesian IRT approaches with hierarchical priors have recently been shown to be promising for estimating even complex models in small samples. Still, it may be challenging for applied researchers to set up such IRT models in general purpose or specialized statistical computer programs. Therefore, we developed a user-friendly tool – a SAS macro called HBMIRT – that allows to estimate uni- and multidimensional IRT models with dichotomous items. We explain the capabilities and features of the macro and demonstrate the particular advantages of the implemented hierarchical priors in rather small samples over weakly informative priors and traditional maximum likelihood estimation with the help of a simulation study. The macro can also be used with the online version of SAS OnDemand for Academics that is freely accessible for academic researchers.
A Self-consistent Data-driven Model for Determining Stellar Parameters from Optical and Near-infrared Spectra
Authors: Sizemore Logan , Llanes Diego , Kounkel Marina , Hutchinson Brian , Stassun Keivan G. , Chandra Vedant 
Published: March 2024

Abstract
Data-driven models, which apply machine learning to infer physical properties from large quantities of data, have become increasingly important for extracting stellar properties from spectra. In general, these methods have been applied to data in one wavelength regime or another. For example, APOGEE Net has been applied to near-IR spectra from the Sloan Digital Sky Survey (SDSS)–V APOGEE survey to predict stellar parameters (T
eff, log g, and [Fe/H]) for all stars with T
eff from 3000 to 50,000 K, including pre-main-sequence stars, OB stars, main-sequence dwarfs, and red giants. The increasing number of large surveys across multiple wavelength regimes provides the opportunity to improve data-driven models through learning from multiple data sets at once. In SDSS-V, a number of spectra of stars will be observed not just with APOGEE in the near-IR, but also with BOSS in the optical regime. Here, we aim to develop a complementary model, BOSS Net, that will replicate the performance of APOGEE Net in these optical data through label transfer. We further improve the model by extending it to brown dwarfs, as well as white dwarfs, resulting in a comprehensive coverage between 1700 < T
eff < 100,000 K and 0 <

log
g

< 10, to ensure BOSS Net can reliably measure parameters of most of the commonly observed objects within this parameter space. We also update APOGEE Net to achieve a comparable performance in the near-IR regime. The resulting models provide a robust tool for measuring stellar evolutionary states, and, in turn, enable characterization of the star-forming history of the Galaxy.
Self-consistent Atmosphere Representation and Interaction in Photon Monte Carlo Simulations
Authors: Peterson J. R. , Sembroski G. , Dutta A. , Remocaldo C. 
Published: March 2024

Abstract
We present a self-consistent representation of the atmosphere and implement the interactions of light with the atmosphere using a photon Monte Carlo approach. We compile global climate distributions based on historical data, self-consistent vertical profiles of thermodynamic quantities, spatial models of cloud variation and cover, and global distributions of four kinds of aerosols. We then implement refraction, Rayleigh scattering, molecular interactions, and Tyndall–Mie scattering to all photons emitted from astronomical sources and various background components using physics first principles. This results in emergent image properties that include: differential astrometry and elliptical point spread functions (PSFs) predicted completely to the horizon, arcminute-scale spatial-dependent photometry variations at 20 mmag for short exposures, excess background spatial variations at 0.2% due to the atmosphere, and a PSF wing due to water droplets. We use a common atmosphere representation framework to self-consistently model all phenomena by simulating individual photons. We reproduce the well-known correlations in image characteristics: correlations in altitude with absolute photometry (overall transmission) and relative photometry (spectrally dependent transmission), anticorrelations of altitude with differential astrometry (nonideal astrometric patterns) and background levels, and an anticorrelation in absolute photometry with cloud depth. However, we also find further subtle correlations including an anticorrelation of temperature with background and differential astrometry, a correlation of temperature with absolute and relative photometry, an anticorrelation of absolute photometry with humidity, a correlation of humidity with lunar background, a significant correlation of PSF wing with cloud depth, an anticorrelation of background with cloud depth, and a correlation of lunar background with cloud depth.