15 papers · ranked by Valyu relevance
Babatoundé Moctard Olouladé, Jesper Leth Bak, Peter Borgen Sørensen, Haomin Yu + 1 more
Accurate predictions of heathland plant species are crucial for ecological monitoring and assessing biodiversity. Previous research has predominantly utilised convolutional neural networks (CNNs), which process images arranged on a regular grid. Although CNNs are effective at extracting local visual features, they…
Sabina Szymoniak, Mariusz Kubanek, Giacomo Peruzzi
The expansion of the Internet of Things (IoT) has increased the complexity of securing distributed systems against growing threats to data security, privacy, and reliability. Conventional centralised cybersecurity methods are often insufficient for environments characterised by scale, heterogeneity, and dynamic…
Kevin Garner, Polykarpos Thomadakis, Nikos Chrisochoides
This paper presents a distributed memory method for anisotropic mesh adaptation that is designed to avoid the use of collective communication and global synchronization techniques. In the presented method, meshing functionality is separated from performance aspects by utilizing a separate entity for each - a multicore…
Phanindra Reddy Madduru, Bijo Thomas
This paper proposes a preprocessing framework for optimizing large-scale graph database ingestion through intelligent edge filtering based on value ranking. We combine adapted PageRank algorithms with business-specific metrics and edge type importance to evaluate and rank edges, enabling selective retention of…
Mohamad Hayek, Martin Golasowski, Stephan Hachinger, Rubén J. García-Hernández + 8 more
Modern data-management frameworks promise a flexible and efficient management of data and metadata across storage backends. However, such claims need to be put to a meaningful test in daily practice. We conjecture that such frameworks should be fit to construct a data backend for workflows which use geographically…
Simon Jones, Sabine Hauert
Building a distributed spatial awareness within a swarm of locally sensing and communicating robots enables new swarm algorithms. We use local observations by robots of each other and Gaussian belief propagation message passing combined with continuous swarm movement to build a global and distributed swarm-centric…
Quanrun Cheng, Yuhong Zhang, Cao Zeng, Zhigang Zhou + 3 more
With respect to distributed MIMO radar systems, conventional far-field detection methods fail under near-field conditions due to significant wavefront curvature, which inevitably results in target energy loss and erroneous parameter estimation. To solve this problem, we propose a near-field target detection framework…
Yingxin Wei, Wei Zhou, Jinghua Zhao, Zhenjiang Tan + 2 more
To address the issue of further collaboratively optimizing process continuity, time cost, and equipment utilization in identical two-workshop distributed integrated scheduling, an identical two-workshop distributed integrated scheduling algorithm based on the improved bipartite graph (DISA-IBG) is proposed. The method…
Alessandro Meoli, Raffaele Vallifuoco, Agnese Coscetta, Luigi Zeni + 2 more
Distributed vibration sensing based on optical vector network analysis (OVNA) is a promising technique for measuring dynamic perturbations in optical fibers, but its practical use is limited by the high computational cost of short-time Fourier transform (STFT) and cross-correlation stages. In this work, we present a…
Liu Yang, Changhua You, Gang Wang, Xuan Zhang + 5 more
Distributed neural interfaces for multi-region implantation require both scalable interconnects and robust telemetry, yet conventional centralized or fully distributed architectures often trade-off wiring complexity, resource reuse, and transmission stability. This work presents a distributed wireless neural recording…
Samar Awad, Marwa Gamal, Khaled Abd El Salam, Rehab F. Abdel-Kader
With the rapid advancement of fog-cloud computing, task offloading and workflow scheduling have become pivotal in determining system performance and cost efficiency. To address the inherent complexity of this heterogeneous environment, a novel hybrid optimization strategy is introduced, integrating the Improved…
Bahman Arasteh, Seyed Salar Sefati, Huseyin Kusetogullari, Farzad Kiani + 3 more
Efficient task scheduling remains a key challenge in High-Performance Computing and Internet of Things (IoT) systems, where the sequential execution of nested loops often limits parallelism. This paper proposes a hybrid approach that dynamically parallelizes nested loops in heterogeneous IoT environments. The suggested…
Lütfiye Özlem Akkan, AbdElRahman Ahmed ElSaid
The rapid development and expansion of the Internet of Things (IoT) ecosystem require managing increasing computational demands with the aid of advanced hierarchical architectures. The integration of a complete four-tier hierarchy-including Mobile, Edge, Fog, and Cloud layers-and the priority requirements are being…
Huan Wang, Shu Yang, Zhen Chen, Haoyu Sun + 6 more
Lightweight Unmanned Aerial Vehicles (UAVs) have limited space, low payload capacity, and constrained power supply capabilities. Therefore, their payloads are constrained by size, weight, and power (SWaP). Thus, designing edge-side signal processing architectures for the payloads of UAVs faces severe challenges.…
Junya Nakanishi, Jun Baba, Yuichiro Yoshikawa, Hiroko Kamide + 1 more
This paper discusses the functional advantages of the Selection-Broadcast Cycle structure proposed by Global Workspace Theory (GWT), inspired by human consciousness, particularly focusing on its applicability to artificial intelligence and robotics in dynamic, real-time scenarios. While previous studies often examined…