Carmen Paz Suarez Araujo

Carmen Paz Suarez Araujo
Universidad de Las Palmas de Gran Canaria | ULPGC · Instituto Universitario de Ciencias y Tecnologías Cibernéticas (IUCTC) & Department of Computer Sciences and Systems

PhD. Professor in Computer Sciences and Artificial Intelligence. Bs. Physics; PhD. Computer Sciences

About

81
Publications
8,055
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
319
Citations
Additional affiliations
January 1983 - present
Universidad de Las Palmas de Gran Canaria

Publications

Publications (81)
Article
We present a computational study whose objective is to show the capacity of the Nitric Oxide (NO) diffusion for information recovery and indexing related to the classical neural architecture Sparse Distributed Memory (SDM). The study is carried out by introducing NO diffusion dynamics by means of a Multi-compartment based NO Diffusion Model in the...
Article
Full-text available
Motion pattern analysis uses a variety of methods to recognise physical activities recorded by wearable sensors, video-cameras, and global navigation satellite systems. This paper presents motion analysis during cycling, using data from a heart rate monitor, accelerometric signals recorded by a navigation system, and the sensors of a mobile phone....
Chapter
Nowadays there is a world pandemic of a challenging respiratory illness, COVID-19. A large part of COVID-19 patients evolves to severe or fatal complications and require an ICU admission. COVID-19 mortality rate approaches 30% due to complications such as obstruction of the trachea and bronchi of patients during the ICU stay.
Chapter
Nowadays, there is a population ageing which leads to an increasing of geriatric and non-communicable diseases. One of the major socio-sanitary challenges our society is facing is dementia, with Alzheimer’s disease (AD) as the most prevalent one. AD is a progressive neurodegenerative disorder over years, with several stages. One of them is the prod...
Chapter
Due to COVID-19 related complications, many of the diagnosed patients end up needing intensive care. Complications are often severe, to such an extent that mortality rates in these patients may be high. Among the wide variety of complications, we find necrotizing tracheobronchitis, which appears suddenly with the obstruction of the endotracheal tub...
Article
Full-text available
Clinical procedure for mild cognitive impairment (MCI) is mainly based on clinical records and short cognitive tests. However, low suspicion and difficulties in understanding test cut-offs make diagnostic accuracy being low, particularly in primary care. Artificial neural networks (ANNs) are suitable to design computed aided diagnostic systems beca...
Chapter
The detection and quantification of rainfall is of paramount importance in many application contexts. The research work we present here is devoted to design a system to detect meteorological phenomena in situations of risk. Particularly, we extend the usage of systems designed for other specific purposes incorporating them weather observation as a...
Conference Paper
In this work we will focus on MCI and AD early detection systems based on neural computing, including Deep Learning (DL) approaches. We will analyze both the main efforts of the last decade in this context and the trends in clinical features that are used in such diagnostic tools. Finally, we will also propose a computational solution based on onto...
Chapter
Spam, or unsolicited messages sent massively, is one of the threats that affects email and other media. Its huge quantity generates considerable economic and time losses. A solution to this issue is presented: a hybrid anti-spam filter based on unsupervised Artificial Neural Networks (ANNs). It consists of two steps, preprocessing and processing, b...
Chapter
Electronic spam, or unsolicited and undesired messages sent massively, is one of the threats that affects email and other media. The high volume and ratio of email spam have generated enormous time and economic losses. Due to this, many different email anti-spam defenses have been used. This translated into more complex spams in order to surpass th...
Conference Paper
The paper presents a new algorithm for adaptive classification of sleep stages using multimodal data recorded in the sleep laboratory during overnight polysomnography records. The proposed method includes the learning process applied for the set of individuals with their sleep stages classified by an experienced neurologist. Features evaluated for...
Article
Full-text available
Benzimidazole fungicides (BFs) are a type of pesticide of high environmental interest characterized by a heavy fluorescence spectral overlap which complicates its detection in mixtures. In this paper, we present a computational study based on supervised neural networks for a multi-label classification problem. Specifically, backpropagation networks...
Conference Paper
Spam, or unsolicited messages sent massively, is one of the threats that affects email and other media. Its high volume generates substantial time and economic losses. A solution to this problem is presented: a hybrid anti-spam filter based on unsupervised Artificial Neural Networks (ANNs). It consists of two steps, preprocessing and processing, bo...
Conference Paper
General methods of video processing and three dimensional modelling have a wide range of applications in engineering, archaeology and spacial objects study. The paper is devoted to applications of these methods in biomedicine and neurology using MS Kinect depth sensor for non-contact monitoring of breathing. A special attention is paid to visualiza...
Conference Paper
Full-text available
The volume transmission (VT), a new type of cellular sig-naling, is based on the diffusion of neuro-active substances such as Nitric Oxide (NO) in the Extracellular Space (ECS). It is not homogeneous, critically dependent on, and limited by, its structure and physico-chemical properties. We present a different computational model of the NO diffusio...
Conference Paper
Full-text available
Dementia is considered to be the emergent and uncontrolled epidemic of nowadays, and one of the major sodo-sanitary challenges our sodeties face. Alzheimer's disease (AD) is the most prevalent cause of dementia, and a progressive disorder. Thus, the detection of mild cognitive impairment (MCI), syndrome equivalent to the prodromal stage of AD, is i...
Conference Paper
Full-text available
Cellular communiction is one mechanism that connects nerve cells to cognition. At present it seems that synaptic transmission may not be the only type of signal processing between cells. Volume transmission (VT) is a process that is performed by means of a gas diffusion process , which is obtained with a diffusive type of signal. This work shows a...
Chapter
In the recent years, the sociological importance of the elderly has grown significantly because of the increase of the prevalence of degenerative disorders, among which Mild Cognitive Impairment (MCI), Alzheimer’s Disease (AD) and other cortical dementias should be highlighted. Using actual diagnostic criteria, by the time a patient is diagnosed wi...
Conference Paper
Benzimidazole fungicides (BFs) are a type of pesticide of high environmental interest with heavy spectral overlap which compli- cates its detection in mixtures. In this paper we present a computational study based on supervised neural networks, Backpropagation (BPN), with data fusion and ensembles schemes for the simultaneous resolution of difficul...
Conference Paper
Full-text available
In this work we introduce a novel over-sampling method to face the problem of imbalanced classes' classification. This method, based on the Sanger neural network, is capable of dealing with high-dimensional datasets. Moreover, it extends the capability of over-sampling methods and allows generating samples from both minority and majority classes. W...
Conference Paper
Full-text available
Alzheimer's Disease (AD) and other dementias are one of the public health challenges mainly because of the relationship between population longevity and the increase of the pathology incidence. Furthermore, first symptoms appear several years after beginning of the disease and the progression of the cognitive decline rises over time. Therefore, it...
Chapter
Full-text available
Dementia is one of the most prevalent diseases associated to aging. The two most common variations of this disease are Alzheimer Dementia (AD) type and Vascular Dementia (VD) type, but there are other many forms (OTD): Lewi Body, Subcortical, Parkinson, Trauma, Infectious dementias, etc. All of these forms can be associated with different patterns...
Book
This volume is a collection of 19 chapters on intelligent engineering systems written by respectable experts of the fields. The book consists of three parts. The first part is devoted to the foundational aspects of computational intelligence. It consists of 8 chapters that include studies in genetic algorithms, fuzzy logic connectives, enhanced int...
Article
An underlying mechanism of Volume Transmission (VT) is the diffusion of Nitric Oxide (NO), which affects all types of brain activity. In this paper we present a new discrete Model based on Automata Networks for Diffusion of NO (ANDINO). The main objectives are to demonstrate its ability to observe the dynamics of diffusion of NO from a molecular pe...
Chapter
Detection and early alert of Denial of Service (DoS) attacks are very important actions to make appropriate decisions in order to minimize their negative impact. DoS attacks have been catalogued as of high-catastrophic index and hard to defend against. Our study presents advances in the area of computer security against DoS attacks. In this chapter...
Conference Paper
Full-text available
An important way to reach a qualitative improvement of Artificial Neural Networks (ANNs) is to incorporate biological features in the networks. Our proposal introduces modularity at two different levels, first, at the network level and second, at the intrinsic level of the networks, generating neural network ensembles (NNEs). We designed three NNEs...
Article
Full-text available
This paper presents a computational study on the dynamic of nitric oxide (NO) in both the biological and artificial environments, by means the analysis of important nitric oxide diffusion attributes, which are defined in this work. We apply the compartmental model of NO diffusion as a formal tool, using a computational neuroscience point of view. T...
Conference Paper
This work presents an e-Health framework to aid diagnosis, prognosis and monitoring of Alzheimer’s Disease and other dementias (EDEVITALZH) by interacting with Intelligent Systems for Diagnosis. Conceived as an intelligent Clinical Workstation, it provides healthcare professionals methods and tools to perform their examinations in an efficient way....
Chapter
Full-text available
Computational intelligence and signal analysis of multi-channel data form an interdisciplinary research area based upon general digital signal processing methods and adaptive algorithms. The chapter is restricted to their use in biomedicine and particularly in electroencephalogram signal processing to find specific components of such multi-channel...
Article
A clear tendency of an aging population (2.5 billion elders are estimated on a global scale by the year 2050) has brought about an increase of its associated diseases, one of which is the higher prevalence dementia focusing in Alzheimer's Disease (AD). Today, it is estimated that there are 18 million people suffering from AD worldwide, and the dise...
Conference Paper
Full-text available
Dementia is one of the associated diseases to aging most prevalents. An important issue about this neuropathology, as of yet unsolved, is the absence of therapeutic tools that manage or stop its progression and symptoms in a constant and supported way. In the present study, we propose a new computational intelligent tool to diagnose the Severity Le...
Conference Paper
Full-text available
Signal analysis of multi-channel data form a specific area of general digital signal processing methods. The paper is devoted to application of these methods for electroencephalogram (EEG) signal processing including signal de-noising, evaluation of its principal components and segmentation based upon feature detection both by the discrete wavelet...
Conference Paper
Full-text available
Denial of Service (DoS) attacks are some of the biggest problems for computer security. Detection and early alert of these attacks would be helpful information which could be used to make appropriate decisions in order to minimize their negative impact. This paper proposes a new approach based on SOM-type unsupervised artificial neural networks for...
Conference Paper
Full-text available
In a clinical context, dementia refers to a syndrome of acquired cognitive deterioration that can be associated with various potential stages of the disease. The two most common variations of this disease are Alzheimer type dementia and Vascular type dementia, although there are other forms known as mixed dementia. All of these forms can be associa...
Conference Paper
Differential and early diagnosis of cognitive impairment (CI) continues being one of the crucial points to which clinical medicine faces at every level of attention, and a significant public health concern. This work proposes new CI diagnostic tools based on a data fusion scheme, artificial neural networks and ensemble systems. Concretely we have d...
Article
In this paper, we approach, using neural computation and ensemble systems, a pattern classification problem in fluorescence spectrometry, the resolution of difficult multi-fungicide mixtures (overlapping), specifically the benzimidazole fungicides, benomyl, carbendazim, thiabendazole and fuberidazole. These fungicides are compounds of an important...
Conference Paper
This paper presents a computational study on a fundamental aspect concerning with the dynamic of nitric oxide (NO) both in the biological and artificial neural networks, the Diffuse Neighbourhood (DNB). We apply the compartmental model of NO diffusion as formal tool, using a computational neuroscience point of view. The main objective is the analys...
Conference Paper
This work applies new techniques of automatic learning to diagnose neuro decline processes usually related to aging. Early detection of cognitive decline (CD) is an advisable practice under multiple perspectives. A study of neuropsychological tests from 267 consultations on 30 patients by the Alzheimer's Patient Association of Gran Canaria is carri...
Conference Paper
Full-text available
This work tries to go a step further in the development of methods based on automatic learning techniques to parse and interpret data relating to cognitive decline (CD). There have been studied the neuropsychological tests of 267 consultations made over 30 patients by the Alzheimer’s Patient Association of Gran Canaria in 2005. The Sanger neural ne...
Chapter
This paper has a theoretic nature. We introduce a new concept in systems theory, the intersensorial transformations (IT). This concept is transparent and general enough to include sensory-motor transformations for robotic actions. The analysis of this transformations leads to the existence of various levels of generalized mapping between representa...
Conference Paper
The data-driven decision support tool built around the SAS technology has been developed to support the evaluation and monitoring of the quality of educational process. The tool forms an integrated framework that can be used for managing of teaching and learning processes and for performing comparative studies in the participating institutions. The...
Chapter
This paper is oriented to a computational theory of invariant perception by the cortex. Based on the idea that the cortex has adopted representations and computational strategies that make the computation of invariants efficient, we suggest that in the cortex there are, at least, two paths for computing invariances. A path computes the parameters o...
Conference Paper
The Computational Neuroscience has as main goal the understanding of the computational style of the brain and developing artificial systems with brain capabilities. Our paper belongs to this field. We will use an Hebbian neural ensemble which follow a non-linear differential equation system namely Hebbian System (HS), which represent the neurodynam...
Article
Full-text available
In this article we present a web application for an interactive and modular virtual clinical environment, (EDEVITALZH), which constitutes an essential part of an intelligent system of neural computation to assist the diagnosis of Alzheimer's disease and other dementias (SICONMID3), based on the HUMANN neural architecture. By using EDEVITALZH, it is...
Article
A theoretical approach that aims to the identification of information processing that may be responsible for emotional dimensions of subjective experience is studied as an initial step in the construction of a neural net model of affective dimensions of psychological experiences. In this paper it is suggested that a way of orientated recombination...
Article
In this paper we present a parametric study of a hierarchical unsupervised modular adaptive neural network (HUMANN), in dealing with noise. HUMANN is a biologically plausible feedforward neural architecture which has the capacity for working in domains with noise and overlapping classes, with no priori information of the number of different classes...
Conference Paper
In this paper, we show how the diffusion of the Nitric Oxide retrograde neuromessenger (NO) in the neural tissue produces Diffusive Hybrid Neuromodulation (DHN), as well as positively inuencing the learning process in the artificial and biological neural networks. It also considers whether the DHN, together with the correlational character that hel...
Conference Paper
Chemical reactions provide new insights concerning information processing in neural networks. Batch reactions are considered in first place and it is presented a model in which computational instructions will be conceptualised as being sent in parallel to multiple operational structures in sites where they are transformed in a way that generates a...
Conference Paper
In this paper an extension of HUMANN (hierarchical unsupervised modular adaptive neural network) is presented together with a parametric study of this network in dealing with noise and with classes of any shape and size. The study has been made based on the two most noise dependent HUMANN parameters, λ and μ, using synthesised databases (bidimensio...
Conference Paper
At present, a new type of process for signalling between cells seems to be emerging, the diffusion or volume transmission. The volume transmission is performed by means of a gas diffusion process, which is obtained with a diffusive type of signal (NO). We present in this paper a CAST approach, in order to develop a NOdi ffusion model, away from a b...
Article
We present in this work a theoretical and conceptual study and some reflections on a fundamental aspect concerning with the structure and brain function: the Cellular Communication. The main interests of our study are the signal transmission mechanisms and the neuronal mechanisms responsible to learning. We propose the consideration of a new kind o...
Article
Full-text available
. We show how to use recursive function theory to prove Turing universality of finite analog recurrent neural nets, with a piecewise linear sigmoid function as activation function. We emphasize the modular construction of nets within nets, a relevant issue from the software engineering point of view. Keywords. Neural computation, recursive function...
Article
The understanding of the brain structure and function and its computational style is one of the biggest challenges both in Neuroscience and Neural Computation. In order to reach this and to test the predictions of neural network modeling, it is necessary to observe the activity of neural populations. In this paper we propose a hybrid modular comput...
Article
In this paper we propose a theoretical approach toinvariant perception. Invariant perception is an importantaspect in both natural and artificial perception systems, and itremains an important unsolved problem in heuristically basedpattern recognition. Our approach is based on a general theoryof neural networks and studies of invariant perception b...
Article
Image algebra as a mathematical structure provides a much broader framework of neural computing. The matrix product in the basic equations of the current linear-based neural networks are furnished by the generalized matrix product obtaining new computational models as morphological neural networks (MNN). In this paper we propose a theoretic approac...
Article
Image algebra as a mathematical structure provides a much broader framework of neural computing. The matrix product in the basic equations of the current linear-based neural networks are furnished by the generalized matrix product obtaining new computational models as morphological neural networks (MNN). In this paper we propose a theoretic approac...
Conference Paper
Formal neural nets considered here are McCulloch-Pitts type with interactions of afferents, that is formal neurons capable of computing any logical function of the inputs. The main problem considered by the CAST system is that of network synthesis from the state transition matrix of a net. The system consists of three blocks: an input block, which...