Antonio Ramírez de Arellano Marrero

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• Doctor of Engineering
• Lecturer at University of Seville

Natural computing is a research area of computer science where different models of computation arise from the inspiration of real-life natural processes. In particular, virus machines are devices inspired by the transmission of viruses between different hosts, and how they replicate in the organism. This paradigm provides devices that can be seen a...

The security that resides in the public-key cryptosystems relies on the presumed computational hardness of mathematical problems behind the systems themselves (e.g. the semiprime factorization problem in the RSA cryptosystem), that is because there is not known any polynomial time (classical) algorithm to solve them. The paper focuses on the comput...

Considering a class R comprising recognizer membrane systems with the capability of providing polynomial-time and uniform solutions for NP-complete problems (referred to as a “presumably efficient” class), the corresponding polynomial-time complexity class PMCR encompasses both the NP and co-NP classes. Specifically, when R represents the class of...

Virus machines are computing devices inspired by the transmission and replication of viruses. This model of computation has been proved to be as powerful as Turing machines, while using very simple semantics: instructions can open channels to let viruses travel between different hosts. The basic model is sequential, in the sense that only one instr...

Virus machines are computational devices inspired by the movement of viruses between hosts and their capacity to replicate using the resources of the hosts. This behavior is controlled by an external graph of instructions that opens different channels of the system to make viruses capable of moving. This model of computation has been demonstrated t...

Surpassing the classical computing architecture is one of the great challenges of computer science today. The branch that approaches it from a theoretical point of view, inspired by nature, is called natural computation. Within this field, a paradigm arises, called virus machines (VMs), inspired by the propagation and replication of the biological...

Virus machines are computing devices inspired by the transmission and replication of viruses. This model of computation has been proved to be as powerful as Turing machines, while using very simple semantics: instructions can open channels to let viruses travel between different hosts. The basic model is sequential, in the sense that only one instr...

In the present work, we further study the computational power of virus machines (VMs in short). VMs provide a computing paradigm inspired by the transmission and replication networks of viruses. VMs consist of process units (called hosts) structured by a directed graph whose arcs are called channels and an instruction graph that controls the transm...

The virus machine model represents a young computing paradigm inspired by the virus transmission and replication. In this paper, a novel extension called channel parallel virus machines to enhance both parallelism and semantics of the basic devices is proposed. Based on this, new channel parallel virus machine models representing production rules f...

Within the branch of Natural Computing, several models or types of computation arise, some of them are well-established such as neural networks, evolutionary computing or membrane computing, while others have yet to be studied and developed. One such model is virus machines, which draws inspiration from the replication and transmission mechanisms o...

Membranes are one of the key concepts in P systems and membrane computing, and a lot of research activities focus on their properties and possible extensions: membrane division, membrane dissolution, mobile membranes, etc. In this work, we explore the possibility of using membranes for thinking about the emergence of milieu separations at the origi...

Deep learning technology has been successfully used in Chest X-ray (CXR) images of COVID-19 patients. However, due to the characteristics of COVID-19 pneumonia and X-ray imaging, the deep learning methods still face many challenges, such as lower imaging quality, fewer training samples, complex radiological features and irregular shapes. To address...

Spiking Neural P Systems (SNP) are well-established computing models that take inspiration from spikes between biological neurons; these models have been widely used for both theoretical studies and practical applications. Virus machines (VMs) are an emerging computing paradigm inspired by viral transmission and replication. In this work, a novel e...

Deep convolutional neural networks have shown advanced performance in accurately segmenting images. In this paper, an SNP-like convolutional neuron structure is introduced, abstracted from the nonlinear mechanism in nonlinear spiking neural P (NSNP) systems. Then, a U-shaped convolutional neural network named SNP-like parallel-convolutional network...

The security that resides in the public-key cryptosystems relies on the presumed computational hardness of mathematical problems behind the systems themselves (e.g. the semiprime factorization problem in the RSA cryptosystem), that is because there is not known any polynomial time (classical) algorithm to solve them. The paper focuses on the comput...

We present a new method to obtain a combinatorial representation for the behaviour of a submanifold isometrically immersed in a Riemannian manifold based on the second fundamental form. We also present several results applying this new way of representation.

In Natural Computing, several models of computation based on processes occurring in nature exist. While some of them are well-established computing framework, there are some types of devices that are underdeveloped. This is the case of Virus Machines, framework inspired by the movement of viruses between hosts, and how can they be replicated while...