The widespread adoption of edge computing for resource-constrained devices presents challenges in computational straggler issues, primarily due to the heterogeneity of edge node resources. This research addresses these issues by introducing a novel r...
Continuous monitoring of patients involves collecting and analyzing sensory data from a multitude of sources. To overcome communication overhead, ensure data privacy and security, reduce data loss, and maintain efficient resource usage, the processin...
Sub-federal enforcement of immigration law has expanded significantly in the last decade raising questions concerning policing, rights violations, and remedies. While the Fourth Amendment has historically provided an avenue for potentially suppressin...
This study presents Federated National Web Trust (FNWT), a compositional cryptographic protocol profile for institutional web-origin authentication. A signed Domain Identity Credential binds a legal-entity identifier, a Hypertext Transfer Protocol Se...
Despite their abundance and ecological importance, little is known about the diversity of marine viruses, in part because most cannot be cultured in the laboratory. Here, we used high-throughput viral metagenomics of uncultivated viruses to investiga...
14 January 2022
This study aimed to describe the dyslipidemia prevalence and pattern among adult populations from different regions (n = 13) of the Russian Federation (RF). Randomly selected samples (n = 22,258, aged 25–64) were studied according to the ESSE-R...
School meals play a critical role in supporting students’ biopsychosocial growth, development, learning, academic performance, and the establishment of healthy eating habits. In public institutions, food procurement is conducted through formal...
3 November 2022
Emotional intelligence has been a topic of great interest to researchers in many different areas as it is associated with mental, psychosomatic, and physical health. In the sports context, it is a significant variable that can play an important role...
The rapid growth of online learning platforms has intensified the need for privacy-aware methods that can analyze learner behavior without centralizing sensitive activity logs. This study presents a Federated Learning-Based Graph Representation Learn...
1 May 2015
Security Assertion Markup Language is one of the most widely used technologies to enable Identity Federations among different organisations. Despite its several advantages, one of its key disadvantages is that it does not allow creating a federation...
5 February 2022
Institutional trust plays a crucial role when a nation is facing mega crises (e.g., the COVID-19 pandemic) and has implications for employee work experiences and well-being. To date, researchers largely consider how institutional trust or trust in go...
This article presents the results of broad research developed by a group of Brazilian scholars to make an assessment of affirmative action policies in admissions to higher education in Brazil, namely the quota legislation in place since 2012, which r...
This research investigates whether, why, and how open government data (OGD) is used and reused by Brazilian state and district public administrations. A new online questionnaire was developed and collected data from 26 of the 27 federation units betw...
Introduction: Malignant neoplasia of the glans penis (MNG), represented by squamous cell carcinoma, is a major health problem, especially in developing countries, where prevalence is higher and diagnoses tend to occur at advanced stages [...]
Background: Gastrointestinal (GI) cancers remain a major global health concern, where timely and accurate interpretation of endoscopic findings plays a decisive role in patient outcomes. In recent years, deep learning–based decision support sys...
Intelligent Transportation Systems (ITS) have progressively incorporated machine learning to optimize traffic efficiency, enhance safety, and improve real-time decision-making. However, the traditional centralized machine learning (ML) paradigm faces...
The proliferation of Internet of Things (IoT) devices operating at the network edge has created unprecedented demand for distributed machine learning capable of functioning under severe resource constraints. Federated learning (FL) has emerged as a p...
Background: Health-related behaviors often cluster during young adulthood, potentially increasing the risk of long-term adverse health outcomes. Understanding how lifestyle risk behaviors co-occur among university students is essential for developing...
Federated Learning (FL) presents a promising approach for collaborative intrusion detection while preserving data privacy. However, current FL frameworks face challenges with non-independent and identically distributed (non-IID) data and class imbala...
A fractional-order equivalent circuit model (FOECM) provides a compact and physically interpretable representation of the memory-dependent polarization behavior of lithium-ion batteries. Leveraging this property, a fractional order model-guided resid...
Introduction: Understanding delivery trends is crucial for maternal and neonatal health planning [...]
Antimicrobial resistance (AMR) is a major public health concern influenced by antimicrobial use (AMU) in animal production systems. In swine, metaphylactic treatments may contribute to the emergence and dissemination of resistance genes. In this stud...
Real-time road accident prediction under dynamic climatic conditions remains a critical challenge for intelligent transportation systems, especially in peripheral and rural regions with limited communication infrastructure. This study proposes and ev...
Objective: Talent identification in youth tennis remains challenging because current assessment approaches often evaluate physical, technical, and cognitive characteristics separately rather than within an integrated multidimensional framework. The p...
Federated learning (FL) enables distributed IoT devices to train machine learning models collaboratively without sharing raw data. However, energy heterogeneity among devices significantly challenges efficient and equitable participation, particularl...
We propose an edge-enhanced federated learning framework for real-time itinerary optimization in elderly oriented adventure tourism, addressing the critical need for adaptive scheduling that balances activity intensity with health constraints. The sy...
18 June 2020
The psychological variables that affect competitive performance are called the psychological profile of athletes. In recent years, the interest in female soccer players and the psychological characteristics that affect their performance has increased...
This study considers the simulation of hydrological processes in the Mzymta River (Russian Federation) using regularized Physics-Informed Neural Networks (PINNs). The Mzymta is the longest river in the Russian Federation and flows into the Black Sea....
28 September 2022
The objective of the study was to identify the profiles of support for autonomy perceived by athletes and compare them with motivation, basic psychological needs, and the intention to be physically active. A cross-sectional descriptive study was carr...
The evolution of cellular networks from fifth-generation (5G) architectures to beyond 5G (B5G) and sixth-generation (6G) systems necessitates innovative solutions to overcome the limitations of traditional Radio Access Network (RAN) infrastructures....
4 May 2019
Background: The purpose of this study was to examine the relationship between coaches’ interpersonal style and fear of failure in athletes. Methods: A sample of 340 athletes at the Federation Level with a mean age of 18.96 years (SD = 5.69 year...
Human non-polio enteroviruses (NPEVs) are the etiological agents involved in most cases of hand-foot-and-mouth disease (HFMD), herpangina and aseptic meningitis. Information on the epidemiology profiles of NPEV in the Ural Federal District and Wester...
This paper presents a federated learning (FL) architecture tailored for anomaly detection in wire arc additive manufacturing (WAAM) that preserves data privacy while enabling secure and distributed model training across heterogeneous process units. W...
10 October 2021
Considering the high prevalence and negative consequences of non-maltreatment adverse childhood experiences (NM-ACEs), it is critical to understand their impacts on the resilient functioning of young children. This study sought to examine heterogenei...
Internet of Things (IoT) botnet detection requires high predictive performance, low client-side resource demands, and limited exposure of raw traffic data. This paper presents a traffic-constrained multi-client split-learning (TC-SL) intrusion-detect...
A driving cycle is a record intended to reflect the regular use of a given type of vehicle, presented as a speed profile recorded over a certain period of time. It is used for the assessment of engine pollutant emissions, fuel consumption analysis an...
The inadequate and abusive usage of psychoactive substances is something real that affects Brazil’s elderly population, and it is a huge challenge for the public health system and its professionals. Aware of the social impact involving the use...
Federated learning techniques aim to train and build machine learning models based on distributed datasets across multiple devices while avoiding data leakage. The main idea is to perform training on remote devices or isolated data centers without tr...
Federated learning (FL) enables cellular traffic prediction without centralizing raw base-station data, but statistical heterogeneity makes a single global model unsuitable for many clients. This paper proposes federated clustering with adaptive pers...
In the post-pandemic era, monitoring adaptive immunity of the population to emerging SARS-CoV-2 variants remains an important public health priority. To address this need, we developed a test that can simultaneously assess the neutralization ability...
One of the stated purposes of this Special Issue is to “discuss when and why intelligence has disappeared” in education. In this paper, I argue that intelligence is still heavily involved in public education in the United States due to th...
Identifying what motivates public servants and how those motives vary across agencies is essential for both theory and practice, yet most existing “types of bureaucrats” remain untested against real workforces. Drawing on reputation theor...
Despite forest remnants being crucial components of the urban environment, they have been insufficiently studied in terms of their economic value. This study aimed to assess the economic value of the Arboretum at the University of Brasília (Un...
In line with several European directives, residents are strongly encouraged to invest in renewable power plants and flexible consumption systems, enabling them to share energy within their Renewable Energy Community at lower procurement costs. This,...
Modern vehicles have extensive instrumentation that can be used to actively assess the condition of infrastructure such as pavement markings, signs, and pavement smoothness. Currently, pavement condition evaluations are performed by state and federal...
This paper aims to detect railway vehicle wheel flats and polygonized wheels using an envelope spectrum analysis. First, a brief explanation of railway vehicle wheel problems is presented, focusing particularly on wheel flats and polygonal wheels. Th...
The capabilities of hovering unmanned aerial vehicles (UAVs) in low-altitude sensing of atmospheric turbulence with high spatial resolution are studied experimentally. The vertical profile of atmospheric turbulence was measured at the Basic Experimen...
Machine unlearning in federated graph learning must satisfy the multi-level indistinguishability requirement of the deletion of a target node being undetectable at the level of the global model, of the unlearning client’s local model, and of ev...
This paper addresses the optimization of contracted electricity demand (CD) for commercial and industrial entities, focusing on cost reduction within the Brazilian time-of-use electricity tariff scheme. Leveraging genetic algorithms (GAs), this study...
Background/Objectives: The precise identification of Alzheimer’s disease (AD) stages through clinical data is crucial for early diagnosis and suitable therapy. This classification remains troublesome due to overlap in cognitive profiles across...
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