Related papers: An Information Network Overlay Architecture for th…
Serving deep learning (DL) models on relational data has become a critical requirement across diverse commercial and scientific domains, sparking growing interest recently. In this visionary paper, we embark on a comprehensive exploration…
We are offering a particular interpretation (well within the range of experimentally and theoretically accepted notions) of neural connectivity and dynamics and discuss it as the data-and-process architecture of the visual system. In this…
The Internet s ability to support a wide range of services depends on the network architecture and theoretical and practical innovations necessary for future networks. Network architecture in this context refers to the structure of a…
Standard Federated Learning (FL) techniques are limited to clients with identical network architectures. This restricts potential use-cases like cross-platform training or inter-organizational collaboration when both data privacy and…
Decentralized federated learning (DFL) uses peer-to-peer communication to avoid the single point of failure problem in federated learning and has been considered an attractive solution for machine learning tasks on distributed devices. We…
This work presents the architecture used in the ongoing OntologyNavigator project. It is a research tool to help advanced learners to find adapted IT papers to create scientific bibliographies. The purpose is the use of an IT representation…
Forwarding data by name has been assumed to be a necessary aspect of an information-centric redesign of the current Internet architecture that makes content access, dissemination, and storage more efficient. The Named Data Networking (NDN)…
Wireless communication systems exhibit structural and functional similarities to neural networks: signals propagate through cascaded elements, interact with the environment, and undergo transformations. Building upon this perspective, we…
Real-world networks typically exhibit several aspects, or layers, of interactions among their nodes. By permuting the role of the nodes and the layers, we establish a new criterion to construct the dual of a network. This approach allows to…
The Resource Description Framework (RDF) is continuing to grow outside the bounds of its initial function as a metadata framework and into the domain of general-purpose data modeling. This expansion has been facilitated by the continued…
Advanced bioimaging technologies have enabled the large-scale acquisition of multidimensional data, yet effective metadata management and interoperability remain significant challenges. To address these issues, we propose a new…
Since decades, the modelling of metadata has been core to the functioning of any academic library. Its importance has only enhanced with the increasing pervasiveness of Generative Artificial Intelligence (AI)-driven information activities…
Materials informatics (MI), emerging from the integration of materials science and data science, is expected to significantly accelerate material development and discovery. The data used in MI are derived from both computational and…
The prevailing model for disseminating scientific knowledge relies on individual publications dispersed across numerous journals and archives. This legacy system is ill suited to the recent exponential proliferation of publications,…
The paper considers the concept of building the architecture of an information system that provides a seamless connection between architectural representations of various levels of abstraction. The concept is based on the application of the…
We propose the object-oriented networking (OON) framework, for meeting the generalized interconnection, mobility and technology integration requirements underlining the Internet. In OON, the various objects that need to be accessed through…
Information-centric networking (ICN) proposes to redesign the Internet by replacing its host centric design with an information centric one, by establishing communication at the naming level, with the receiver side acting as the driving…
This paper contains description of such knowledge representation model as Object-Oriented Dynamic Network (OODN), which gives us an opportunity to represent knowledge, which can be modified in time, to build new relations between objects…
The objective of knowledge graph embedding is to encode both entities and relations of knowledge graphs into continuous low-dimensional vector spaces. Previously, most works focused on symbolic representation of knowledge graph with…
The International Lattice Datagrid (ILDG) is a federation of several regional grids. Since most of these grids have reached production level, an increasing number of lattice scientists start to benefit from this new research infrastructure.…