Academic Articles & Research Papers

Hyperuricemia and dementia – a case-control study

Abstract Background There is evidence that uric acid may have antioxidant and neuroprotective effects and might therefore alter the risk for neurodegenerative diseases such as dementia. So far, the relation between serum uric acid (SUA) lev...

Cost-Based Competition and Market Share Determination: A CES Analytical Framework

This study examines the micro-level mechanisms through which increasing market concentration and the entrenchment of competitive advantage arise. We develop a theoretical framework based on a constant elasticity of substitution (CES) produc...

Robots at Work

We analyze for the first time the economic contributions of modern industrial robots, which are flexible, versatile, and autonomous machines. We use novel panel data on robot adoption within industries in seventeen countries from 1993 to 20...

Editorial: Advancements in AI-driven multimodal interfaces for robot-aided rehabilitation

Computing Ground State Properties with Early Fault-Tolerant Quantum Computers

Significant effort in applied quantum computing has been devoted to the problem of ground state energy estimation for molecules and materials. Yet, for many applications of practical value, additional properties of the ground state must be ...

Functional Matrices on Quantum Computing Simulation

In simulating Quantum Computing by using the circuit model the size of the matrices to deal with, together with the number of products and additions required to apply every quantum gate becomes a really hard computational restriction. This ...

The Role and Application of Matrices in Artificial Intelligence: Foundations, Methods, and Advancements

Matrices are foundational to artificial intelligence (AI), serving as critical tools for data representation, manipulation, and transformation across various applications. From machine learning algorithms to neural network architectures, ma...

Quantum Structure for Modelling Emotion Space of Robots

Utilising the properties of quantum mechanics, i.e., entanglement, parallelism, etc., a quantum structure is proposed for representing and manipulating emotion space of robots. This quantum emotion space (QES) provides a mechanism to extend...

Approaching quantum computing

1 Preface 2 Introduction 2.1 Computing and the Laws of Physics 2.2 Quantum Information 2.3 Quantum Computers 2.4 The Wave and the Corpuscular Nature of Light 2.5 Deterministic versus Probabilistic Photon Behavior 2.6 State Description, Supe...

Emerging quantum computing algorithms for quantum chemistry

Abstract Digital quantum computers provide a computational framework for solving the Schrödinger equation for a variety of many‐particle systems. Quantum computing algorithms for the quantum simulation of these systems have recently witness...

A Procedural Formalism for Quantum Computing

Despite many common concepts with classical computer science, quantum computing is still widely considered as a special discipline within the broad field of theoretical physics. One reason for the slow adoption of QC by the computer science...

Selfish caching in distributed systems

We analyze replication of resources by server nodes that act selfishly, using a game-theoretic approach. We refer to this as the selfish caching problem. In our model, nodes incur either cost for replicating resources or cost for access to ...

Cybersecurity For Defense Economists

Cybersecurity plays a role in national security. This study introduces cybersecurity concepts in ways familiar to defense economists and identifies parallel methods of analysis in the fields. The theoretical tools of both fields include mic...

Cybersecurity

In an increasingly digital business landscape, cybersecurity has evolved from a technical concern to a strategic imperative. As organisations shift operations online, the complexities and potential consequences of cyber threats have grown e...

Spectrally-normalized margin bounds for neural networks

This paper presents a margin-based multiclass generalization bound for neural networks that scales with their margin-normalized "spectral complexity": their Lipschitz constant, meaning the product of the spectral norms of the weight matrice...

Introduction to artificial neural networks

The coupling of computer science and theoretical bases such as nonlinear dynamics and chaos theory allows the creation of 'intelligent' agents, such as artificial neural networks (ANNs), able to adapt themselves dynamically to problems of h...

Tensorizing Neural Networks

Deep neural networks currently demonstrate state-of-the-art performance in several domains. At the same time, models of this class are very demanding in terms of computational resources. In particular, a large amount of memory is required b...

Back Propagation Neural Networks

(1998). Back Propagation Neural Networks. Substance Use & Misuse: Vol. 33, No. 2, pp. 233-270....

Neural networks for financial forecasting

When applied to the world of finance, neural networks are automated trading systems, based on mapping inputs and outputs for forecasting probable future values. In Neural Networks for Financial Forecasting - the first book to focus on the r...

Joint Optimization of Transform and Quantization for High Efficiency Video Coding

In high efficiency video coding (HEVC), transformation and quantization are separately performed to eliminate the perceptual redundancy of visual signals. However, a uniform quantizer can inevitably degrade the compression efficiency of fix...