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This paper explores the application of convolutional neural networks (CNNs) in predictive modelling for seismic events and flood risks, with a particular focus on forecasting extreme quantile events that exceed historica...

ABSTRACT Adversarial jamming attacks have increased on communication systems, causing distortion and threatening transmissions. Typical attacks rely on traditional, well‐defined cryptographic protocols and frequency‐...

Accurate detection of pediatric fractures in radiographs remains challenging due to subtle visual cues and the high prevalence of false-positive detections produced by automated systems. To address this limitation, we pr...

Abstract Physical sciences are essential to the predictive modeling of complex environmental systems, particularly environmental monitoring and sustainability applications, as they provide the deterministic foundation re...

Cloud computing environments face persistent structural challenges in cost control, dynamic resource allocation, and security risk management, which traditional infrastructure approaches fail to address adequately. This ...

ABSTRACT Intelligent and adaptive defence systems that can quickly thwart changing cyberthreats are becoming more and more necessary in the dynamic and data‐intensive Internet of things (IoT) environment. Using the NSL...

Abstract The emergence of Internet-of-Things devices and expanding data processing demands have led to the popularization of edge computing. But energy efficiency challenges and security problems also remain difficult in...

The rapid proliferation of digital devices has generated vast amounts of data, presenting significant challenges in collection, processing, and analysis that traditional systems struggle to overcome. This study investiga...

This paper addresses the growing need for implementing intelligent Natural Language Processing (NLP) systems on low-power, memory-limited devices such as Raspberry Pi, mobile phones, and IoT edge hardware. As edge comput...

Abstract Quantum networks (QNs) have been predominantly driven by discrete-variable (DV) architectures. Yet, optical platforms naturally generate Gaussian states—the common states of continuous-variable (CV) systems, m...

The huge rise in the number of medical images has caused a major problem in radiology departments. Radiologists are now working harder than ever, which affects the quality of their diagnoses and patient care. It takes 15...

Abstract Smart home networks are a rapidly evolving part of the Internet of Things (IoT), where connected devices exchange information to automate energy use, enhance comfort, and improve user safety. Despite their benef...

Abstract Modern broadband access networks increasingly carry heterogeneous, delay-sensitive traffic generated by cloud-assisted applications, real-time communication services, and short-form multimedia exchanges. These w...

A Federated System is a collection of independent, cooperative, possibly heterogeneous and autonomous computer systems (usually database systems) which allows sharing all or some of its data. A Service-Oriented Architect...

One of the major breakthroughs in VLSI technology has been its ability to implement signal processing algorithms and architectures onto cost-effective ASIC and DSP chips. Works in this area are highly interdisciplinary;...

Modern computers present a big gap between peak performance and sustained performance. There are many reasons for this situation, but mainly involving an inefficient usage of computational resources. Nowadays the memory ...

Chip-multiprocessor systems or CMPs have emerged as a high-perfomance organization for the increasing number of transistors available on a chip, and are projected to dominate the market of server and desktop computers. C...

Vision based applications are present anywhere. A special market is industry, allowing to improve product quality and to reduce manufacturing costs. The vision systems applied to industries are known as machine vision sy...

Multiscale feature extraction from the visual environment in an active vision system Y.Machrouh 1, J.-S.Liénard 1, P.Tarroux 1, 2 Abstract. This paper presents a visual architecture able to identify salient regions in a...

Fault tolerance has become an important issue for parallel applications in the last few years. The parallel systems' users want them to be reliable considering two main dimensions, availability and data consistency. Avai...

CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecular simulation program. It has been developed over the last three decades with a primary focus on molecules of biological inte...

An attentional mechanism has lately been used to improve neural machine translation (NMT) by selectively focusing on parts of the source sentence during translation. However, there has been little work exploring useful a...

Feature pyramids are a basic component in recognition systems for detecting objects at different scales. But pyramid representations have been avoided in recent object detectors that are based on deep convolutional netwo...

Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradient based learning technique. Given an appropriate network architecture, gradient-based learning alg...