Dimitris Ntalaperas

Quantum Local Density of States for Random k-SAT: An Amplitude-Estimation Primitive and a Clause-Width Regime for Quantum Advantage

Michail Gerogiannis, Dimitris Ntalaperas, Nikos Konofaos

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A Quantum-Accelerated Mapping Algorithm for Sequence Alignment

Konstantinos Prousalis, Dimitris Ntalaperas, Konstantinos Georgiou, Andreas Kalogeropoulos et autres

A novel quantum algorithm for biological sequence alignment is presented and analyzed. The large volumes of data generated through genome sequencing, de novo assembly, resequencing, and transcriptome sequencing at the DNA and RNA levels foreshadow the growing demand for higher computational power …

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A Survey on Sequence Alignment Algorithms and State-of-the-Art Aligners

Konstantinos P. Prousalis, Konstantinos Georgiou, Andreas Kalogeropoulos, Dimitris Ntalaperas et autres

Vast amounts of genomic, proteomic, transcriptomics and other forms, commonly referred to as -omics data, are generated daily in an unprecedented way thanks to high-throughput Next Generation Sequencing technologies. One of the main processes to generate value and insights from this data …

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Human-Centric AI-Enabled Extended Reality Reference Architecture for Industry 5.0

Nikolaos Tousert, Anastasia Dimitra Lipitakis, Thanos Giannakopoulos, Dimitris Ntalaperas et autres

Industry 5.0 improves human-machine collaboration by integrating Artificial Intelligence (AI) and Extended Reality (XR) into industrial environments. This paper presents a structured Reference Architecture for a system that addresses industrial environments within the Industry 5.0 paradigm, iteratively refined based on evolving business …

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Qutrit Control for Bucket Brigade RAM Using Transmon Systems

Lazaros Spyridopoulos, Dimitris Ntalaperas, Nikos Konofaos

Qudits allow the encoding and manipulation of additional quantum information compared to that stored to a two-level qubit system. Although manipulations of qudit states are generally more complex and can introduce extra sources of noise, qudits can still be used in a …

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XR5.0: Human-Centric AI-Enabled Extended Reality Applications for Industry 5.0

Athanasios Kiourtis, Argyro Mavrogiorgou, Georgios Makridis, Dimosthenis Kyriazis et autres

Applications for Extended Reality (XR) are rapidly expanding across a wide range of industries, including gaming, entertainment, and healthcare. Accompanying this trend is the field of digital manufacturing, which encompasses a broad range of applications such as quick product design, remote maintenance, …

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Decentralized Data Governance, Provenance and Reliability V2

Dimitris Ntalaperas

This deliverable presents the second iteration of the AI4Gov Decentralised Data Governance (DDG) model, focusing on the implementation of mechanisms that ensure data provenance, reliability, and GDPR-compliant privacy within a decentralized architecture. It details the finalized system design and supporting prototypes that …

Decentralized Data Governance, Provenance and Reliability V2

Dimitris Ntalaperas

This deliverable presents the second iteration of the AI4Gov Decentralised Data Governance (DDG) model, focusing on the implementation of mechanisms that ensure data provenance, reliability, and GDPR-compliant privacy within a decentralized architecture. It details the finalized system design and supporting prototypes that …

An algorithm based on quantum phase estimation for the identification of patterns

Dimitris Ntalaperas, Andreas Kalogeropoulos, Nikos Konofaos

Abstract The quantum phase estimation algorithm has been utilized by a variety of quantum algorithms, most notably Shor’s algorithm, to obtain information regarding the period of a function that is appropriately encoded into a unitary operator. In many cases, it is desired …

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A novel quantum algorithm for Biological Sequence Alignment using Quantum Accelerated Mapping in Seed-and-Extend Technique.

Konstantinos P. Prousalis, Dimitris Ntalaperas, Κωνσταντίνος Γεωργίου, Andreas Kalogeropoulos et autres

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AI-based solutions for predicting sepsis in ICUs

Charithea Stylianides, Christina‐Athanasia Alexandropoulou, Ilias E. Panagiotopoulos, Styliani Kleanthous et autres

Artificial Intelligence (AI) advances in healthcare underpin timely and informed interventions that can elevate the quality of care for the benefit of the citizen. This can be especially beneficial for Intensive Care Unit (ICU) patients. The goal of this study is to …

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AI-Enabled Solutions, Explainability and Ethical Concerns for Predicting Sepsis in ICUs: A Systematic Review

Christina‐Athanasia Alexandropoulou, Ilias E. Panagiotopoulos, Styliani Kleanthous, George J. Dimitrakopoulos et autres

Artificial Intelligence (AI) advances are pushing the boundaries across research domains with AI-driven solutions in healthcare claiming a significant share. A key objective of these studies concerns the timely prediction of various pathological conditions. Sepsis is a life-threatening syndrome and one of …

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