Frontiers in Computer Science | New and Recent Articles

Federated learning (FL) is a decentralized machine learning (ML) approach that can be used for intrusion detection in Internet of Things (IoT) devices. It involves the local training of AI models and their aggregation at a central server. This methodology eliminates the need for data sharing between IoT devices while fostering collaborative model improvement. Nonetheless, concerns arise from the …

Platform engineering has become the dominant approach to managing developer infrastructure at scale, with industry surveys indicating that 94% of organizations have adopted or plan to adopt dedicated platform teams. Despite this rapid practitioner uptake, academic research remains scarce: a systematic search across five major databases identified fewer than a dozen peer-reviewed papers from reput…

As Machine Learning Operations (MLOps) adoption accelerates, systematic integration of explainability is imperative for reliability, transparency, and continuous quality assurance. This paper presents a scoping review examining how explainability is integrated across the MLOps lifecycle, encompassing data handling, model development, and deployment. Each phase is further analyzed through its suba…

IntroductionRadio labeling of graphs extends the channel assignment problem by assigning non-negative integers to vertices of a connected graph G such that |h(℘)−h(𝓆)|≥diam(ℊ)+1−d(℘, 𝓆). The objective is to minimize the span, leading to the radio number rn(G).MethodsWe consider a class of outerplanar graphs with vertex set {u1, v1, x1, …, xn, y1, …, yn} and a structured edge set combining path an…

The increasing reliance on Deep Learning models, combined with their inherent lack of transparency, has spurred the development of a novel field of study known as eXplainable AI (XAI) methods. These methods aim to enhance end-users' trust in automated systems by providing insights into the rationale behind their decisions. This paper presents a novel trust measure in XAI systems, allowing their r…

Real-time weapon detection in video surveillance is a critical capability for artificial intelligence assisted security systems, particularly in scenarios constrained by low latency, limited computational resources, and strict power efficiency requirements typical of edge artificial intelligence deployments. This work presents a comparative analysis of lightweight YOLO based object detectors, nam…

IntroductionDifferences in prior knowledge among incoming medical students pose a persistent challenge for universities. To promote more individualized and equitable preparation, a large language model-based learning platform is being developed at the University Medical Center Hamburg-Eppendorf. A central component of this platform is the automated generation of multiple-choice questions (MCQs) f…

IntroductionDrivers supervising Level 2 automation must maintain situation awareness while the system controls steering and speed. Miscalibrated trust can contribute to overreliance and lapses in monitoring, whereas insufficient trust leads to disuse. Prolonged supervision is associated with increased mind-wandering, which can slow reactions to critical events. This study tested whether brief edu…

Flipped classrooms require learners to actively regulate their learning processes, yet the relationships among self-regulated learning (SRL), engagement, social–emotional intelligence (SEI), and academic performance remain insufficiently integrated within learning analytics research. This study examined 96 third-year Computer Science and Engineering students enrolled in a semester-long Database M…

IntroductionThis systematic review investigates the role of technology in advancing inclusivity and sustainability in educational spaces.MethodsA structured methodology was applied to analyze 20 studies published between 2015 and 2025, sourced from IEEE Xplore, ACM Digital Library, and ScienceDirect.ResultsThe findings reveal that technologies such as artificial intelligence (AI), the Internet of…

IntroductionAlthough physiological signals such as heart rate, perspiration, and facial muscle activity are recognized as markers of emotional events, precisely classifying affective states from these data remains a significant challenge. Addressing this issue is fundamental for developing advanced human-computer interaction and assistive technologies. While emotion recognition in adults has been…

IntroductionThe translation of paintings into tactile 2.5D models (i.e., bas-reliefs) represents a significant advancement in improving accessibility for blind and visually impaired individuals. However, reconstructing spatial structure from a single painted image without explicit perspective is inherently ill-posed, particularly in modern and contemporary artworks where perspective, illumination…

As a result of the increase in industrial Internet of Things (IoT) applications, fog computing (FC) has become a major area of research. A decentralized computing system called fog computing extends cloud computing to the network’s edge. The cloud allows for real-time insights and analysis by processing and storing enormous volumes of data produced by IoT devices. Consequently, the task schedulin…

Artificial intelligence (AI) is reshaping medical education, particularly in the teaching of physical examination and the development of clinical judgement in digitally mediated contexts. This study presents a critical narrative review examining the ethical, pedagogical, and humanistic implications of AI integration into physical examination training in Latin America. A structured search of liter…