In this research work a novel two-step system for anomaly detection is presented and tested over several real datasets. In the first step the novel Exploratory Projection Pursuit, Beta Hebbian Learning algorithm, is applied over each dataset, either to reduce the dimensionality of the original dataset or to face nonlinear datasets by generating a new subspace of the original dataset with lower, or even higher, dimensionality selecting the right activation function. Finally, in the second step Principal Component Analysis anomaly detection (...) is applied to the new subspace to detect the anomalies and improve its classification capabilities. This new approach has been tested over several different real datasets, in terms of number of variables, number of samples and number of anomalies. In almost all cases, the novel approach obtained better results in terms of area under the curve with similar standard deviation values. In case of computational cost, this improvement is only remarkable when complexity of the dataset in terms of number of variables is high. (shrink)

The slime mould Physarum polycephalum has been used in developing unconventional computing devices for in which the slime mould played a role of a sensing, actuating, and computing device. These devices treated the slime mould as an active living substrate, yet it is a self-consistent living creature which evolved over millions of years and occupied most parts of the world, but in any case, that living entity did not own true cognition, just automated biochemical mechanisms. To “rehabilitate” slime mould from (...) the rank of a purely living electronics element to a “creature of thoughts” we are analyzing the cognitive potential of P. polycephalum. We base our theory of minimal cognition of the slime mould on a bottom-up approach, from the biological and biophysical nature of the slime mould and its regulatory systems using frameworks such as Lyon’s biogenic cognition, Muller, di Primio-Lengelerś modifiable pathways, Bateson's “patterns that connect” framework, Maturana's autopoietic network, or proto-consciousness and Morgan's Canon. (shrink)

Este estudio cualitativo fenomenológico-hermenéutico interpreta los discursos narrativos de estudiantes sobre sus vivencias en entornos virtuales con respecto al proceso de retroalimentación vinculado con el modelo socioformativo asumido por su universidad. Es un estudio retrospectivo que se focaliza en los dos primeros años de pandemia de la COVID-19 y la información se obtuvo mediante el análisis documentario y grupos focales que permiten, desde las voces de los estudiantes, dar aportes que sustenten la acción pedagógica de docentes en diferentes modalidades formativas (...) que después de la pandemia de la COVID 19 estarán presentes en el proceso formativo a nivel mundial. (shrink)

Nowadays, the quality standards of higher education institutions pay special attention to the performance and evaluation of the students. Then, having a complete academic record of each student, such as number of attempts, average grade and so on, plays a key role. In this context, the existence of missing data, which can happen for different reasons, leads to affect adversely interesting future analysis. Therefore, the use of imputation techniques is presented as a helpful tool to estimate the value of missing (...) data. This work deals with the academic records of engineering students, in which imputation techniques are applied. More specifically, it is assessed and compared to the performance of the multivariate imputation by chained equations methodology, the adaptive assignation algorithm based on multivariate adaptive regression splines and a hybridization based on self-organisation maps with Mahalanobis distances and AAA algorithm. The results show that proposed methods obtain successfully results regardless the number of missing values, in general terms. (shrink)

This book is based on the outcome of the ""2012 Interdisciplinary Symposium on Complex Systems"" held at the island of Kos. The book consists of 12 selected papers of the symposium starting with a comprehensive overview and classification of complexity problems, continuing by chapters about complexity, its observation, modeling and its applications to solving various problems including real-life applications. More exactly, readers will have an encounter with the structural complexity of vortex flows, the use of chaotic dynamics within evolutionary algorithms, (...) complexity in synthetic biology. (shrink)

Nowadays, batteries play an important role in a lot of different applications like energy storage, electro-mobility, consumer electronic and so on. All the battery types have a common factor that is their complexity, independently of its nature. Usually, the batteries have an electrochemical nature. Several different test are accomplished to check the batteries performance, and commonly, it is predictable how they work depending of their technology. The present research describes the hybrid intelligent system created to accomplish fault detection over a (...) Lithium Iron Phosphate—LiFePO4 power cell type, commonly used in electro-mobility applications. The approach is based on the cell temperatures behaviour for voltage and current specific values. Taken into account the operating range of a real system based on a LiFePO4 cell, a large set of points of operation have been used to achieve the dataset. The different behaviour zones have been obtained by clustering as a first step. Then, different regression techniques have been used over each cluster. Polynomial regression, artificial neural networks and support vector regression were the combined techniques to develop the hybrid intelligent model proposed. The intelligent system gives very good results over the operating range, detecting all the faults tested during the validation. (shrink)

In this study, a hybrid model based on intelligent techniques is developed to predict the active power generated in a bioclimatic house by a low power wind turbine. Contrary to other researches that predict the generated power taking into account the speed and the direction of the wind, the model developed in this paper only uses the speed of the wind, measured mainly in a weather station from the government meteorological agency (MeteoGalicia). The wind speed is measured at different heights, (...) against the usual measurements in others researches, which uses the wind speed and the direction measured in a weather station on the wind turbine nacelle. The prediction is performed 30 minutes ahead, what ensures that the Building Management System knows the energy generated by the low power wind turbine 30 minutes before, and it can adapt the consumption of different equipment in the house to optimize the power use. The main objective is to allow the Building Management System to optimize the uses of energy, taking into account the predicted amount of energy that will be produced and the energy consumed in the house. The developed model uses a hybrid topology with four clusters to improve the prediction, achieving an error lower than 6.5% for Mean Absolute Error measured in a final test. To perform this test, part of the original dataset was isolated from the beginning of the training process to check the model with a dataset that is not used before, simulating the model as it is receiving new data. (shrink)

En la ciudad de Medellín se hace uso de herramientas y dispositivos, en el marco de la llamada Gestión Social, para ejecutar importantes obras para el llamado desarrollo urbano, que bien pueden configurar una “Gestión social del despojo”, en el marco de una “Planeación institucional de la miseria y el desarraigo”, generando víctimas ya no del conflicto armado sino del desarrollo. Es necesario problematizar esta suerte de modelo de desarrollo urbano, su gestión e implementación.

This paper reports the experience of using the PAELLA algorithm as a helper tool in robust regression instead of as originally intended for outlier identification and removal. This novel usage of the algorithm takes advantage of the occurrence vector calculated by the algorithm in order to strengthen the effect of the more reliable samples and lessen the impact of those that otherwise would be considered outliers. Following that aim, a series of experiments is conducted in order to learn how to (...) better use the information contained in the occurrence vector. Using a contrively difficult artificial data set, a reference predictive model is fit using the whole raw dataset. The second experiment reports the results of fitting a similar predictive model but discarding the samples marked as outliers by PAELLA. The third experiment uses the occurrence vector provided by PAELLA in order to classify the observations in multiple bins and fit every possible model changing which bins are considered for fitting and which are discarded in that particular model. The fourth experiment introduces a sampling process before fitting in which the occurrence vector represents the likelihood of being considered in the training data set. The fifth experiment considers the sampling process as an internal step to be performed interleaved between the training epochs. The last experiment compares our approach using weighted neural networks to a state of the art method. (shrink)

The paper discusses Dr. Floris Tomasini's paper “What Is Bioethics: Notes toward a New Approach?”. Based on Tomasini's account of methodological and ethical pluralism, the paper explores the demarcation problem of bioethics and suggests a full methodological laissez-faire.

We present a generalization of the problem of pattern recognition to arbitrary probabilistic models. This version deals with the problem of recognizing an individual pattern among a family of different species or classes of objects which obey probabilistic laws which do not comply with Kolmogorov’s axioms. We show that such a scenario accommodates many important examples, and in particular, we provide a rigorous definition of the classical and the quantum pattern recognition problems, respectively. Our framework allows for the introduction of (...) non-trivial correlations between the different species involved, opening the door to a new way of harnessing these physical resources for solving pattern recognition problems. Finally, we present some examples and discuss the computational complexity of the quantum pattern recognition problem, showing that the most important quantum computation algorithms can be described as non-Kolmogorovian pattern recognition problems. (shrink)

IntroductionCardiology is characterized by its state-of-the-art biomedical technology and the predominance of Evidence-Based Medicine. This predominance makes it difficult for healthcare professionals to deal with the ethical dilemmas that emerge in this subspecialty. This paper is a first endeavor to empirically investigate the axiological foundations of the healthcare professionals in a cardiology hospital. Our pilot study selected, as the target population, cardiology personnel not only because of their difficult ethical deliberations but also because of the stringent conditions in which they (...) have to make them. Therefore, there is an urgent need to reconsider clinical ethics and Value-Based Medicine. This study proposes a qualitative analysis of the values and the virtues of healthcare professionals in a cardiology hospital in order to establish how the former impact upon the medical and ethical decisions made by the latter.ResultsWe point out the need for strengthening the roles of healthcare personnel as educators and guidance counselors in order to meet the ends of medicine, as well as the need for an ethical discernment that is compatible with our results, namely, that the ethical values developed by healthcare professionals stem from their life history as well as their professional education.ConclusionWe establish the kind of actions, communication skills and empathy that are required to build a stronger patient-healthcare professional relationship, which at the same time improves prognosis, treatment efficiency and therapeutic adhesion. (shrink)

The similarity of documents in a large database of published Fractals articles was examined for redundancy. Three different text matching techniques were used on published Abstracts to identify redundancy candidates, and predictions were verified by reading full text versions of the redundancy candidate articles. A small fraction of the total articles in the database was judged to be redundant. This was viewed as a lower limit, because it excluded cases where the concepts remained the same, but the text was altered (...) substantially.Far more pervasive than redundant publications were publications that did not violate the letter of redundancy but rather violated the spirit of redundancy. There appeared to be widespread publication maximization strategies. Studies that resulted in one comprehensive paper decades ago now result in multiple papers that focus on one major problem, but are differentiated by parameter ranges, or other stratifying variables. This ‘paper inflation’ is due in large part to the increasing use of metrics (publications, patents, citations, etc) to evaluate research performance, and the researchers’ motivation to maximize the metrics. (shrink)

Understanding how the chordate body plan originated and evolved is still controversial. The discovery by Spemann and Mangold in 1924 of the vertebrate organizer and its inductive properties in patterning the AP and DV axis was followed by a long gap until the 1960s when scientists started characterizing the molecular events responsible for such inductions. However, the evolutionary origin of the organizer itself remained obscure until very recently; did it appear together with the origin and radiation of vertebrates, or was (...) it a chordate affair? A recent study by Yu and collaborators,1 which analyses the expression of several organizer‐specific genes in amphioxus together with recent phylogenetic data that reversed the position of invertebrate extant chordates (e.g. urochordates and cephalochordates), indicates that the organizer probably appeared in early chordates. It likely had separate signalling centres generating BMP and Wnt signalling gradients along the DV and AP axis. The organizer was then lost in the urochordate lineage, most probably as an adaptation to a rapid and determinate development. BioEssays 29:619–624, 2007. © 2007 Wiley Periodicals, Inc. (shrink)

Closed-loop administration of propofol for the control of hypnosis in anesthesia has evidenced an outperformance when comparing it with manual administration in terms of drug consumption and post-operative recovery of patients. Unlike other systems, the success of this strategy lies on the availability of a feedback variable capable of quantifying the current hypnotic state of the patient. However, the appearance of anomalies during the anesthetic process may result in inaccurate actions of the automatic controller. These anomalies may come from the (...) monitors, the syringe pumps, the actions of the surgeon or even from alterations in patients. This could produce adverse side effects that can affect the patient postoperative and reduce the safety of the patient in the operating room. Then, the use of anomaly detection techniques plays a significant role to avoid this undesirable situations. This work assesses different one-class intelligent techniques to detect anomalies in patients undergoing general anesthesia. Due to the difficulty of obtaining real data from anomaly situations, artificial outliers are generated to check the performance of each classifier. The final model presents successful performance. (shrink)

The use of batteries became essential in our daily life in electronic devices, electric vehicles and energy storage systems in general terms. As they play a key role in many devices, their design and implementation must follow a thorough test process to check their features at different operating points. In this circumstance, the appearance of any kind of deviation from the expected operation must be detected. This research deals with real data registered during the testing phase of a lithium iron (...) phosphate—LiFePO4—battery. The process is divided into four different working points, alternating charging, discharging and resting periods. This work proposes a hybrid classifier, based on one-class techniques, whose aim is to detect anomalous situations during the battery test. The faults are created by modifying the measured cell temperature a slight ratio from their real value. A detailed analysis of each technique performance is presented. The average performance of the chosen classifier presents successful results. (shrink)

This paper aims to enhance security in IoT device networks through a visual tool that utilizes three projection techniques, including Beta Hebbian Learning (BHL), t-distributed Stochastic Neighbor Embedding (t-SNE) and ISOMAP, in order to facilitate the identification of network attacks by human experts. This work research begins with the creation of a testing environment with IoT devices and web clients, simulating attacks over Message Queuing Telemetry Transport (MQTT) for recording all relevant traffic information. The unsupervised algorithms chosen provide a set (...) of projections that enable human experts to visually identify most attacks in real-time, making it a powerful tool that can be implemented in IoT environments easily. (shrink)

The Internet of Things (IoT) is a fast-growing technology that connects everyday devices to the Internet, enabling wireless, low-consumption and low-cost communication and data exchange. IoT has revolutionized the way devices interact with each other and the internet. The more devices become connected, the greater the risk of security breaches. There is currently a need for new approaches to algorithms that can detect malware regardless of the size of the network and that can adapt to dynamic changes in the network. (...) Through the use of a multi-agent reinforcement learning algorithm, this paper proposes a novel algorithm for malware detection in IoT devices. The proposed algorithm is not strongly dependent on the size of the IoT network due to the that its training is adapted using time differences if the IoT network size is small or Monte Carlo otherwise. To validate the proposed algorithm in an environment as close to reality as possible, we proposed a scenario based on a real IoT network, where we tested different malware propagation models. Different simulations varying the number of agents and nodes in the IoT network have been developed. The result of these simulations proves the efficiency and adaptability of the proposed algorithm in detecting malware, regardless of the malware propagation model. (shrink)

A systematic literature review was conducted on the production and publication of research articles related to the study of variables, financial technology (Fintech), and Bioeconomy. The purpose of this research was to know the main characteristics of the publications registered in the SD, WoS, and Scopus databases during the period 2007-2024, to February 8, 2024, achieving the identification of 46 publications in total. The information provided by these platforms was organized using graphs and figures, categorizing the information by CO-occurrence of (...) Keywords, Year of Publication, Country of Origin, and Area of Knowledge. Once these characteristics were described, a qualitative analysis was conducted to refer to the position of the different authors on the proposed topic. Among the main results of this research, Germany and the United States were the countries with the highest number of publications, with a total of 7 publications each, followed by Brazil with 6 publications, while 60% of the publications are concentrated and originate in European countries. The area of knowledge that contributed the most to the study variables was Environmental Sciences, with 18 articles. This systematic literature review allowed us to conclude that the study of the intersection of bioeconomy and financial technologies is an issue that is gaining attention. There has been a boom in scientific publications in the last decade. (shrink)

Nature contact has associations with emotional ill-being and well-being. However, the mechanisms underlying these associations are not fully understood. We hypothesised that increased adaptive and decreased maladaptive emotion regulation strategies would be a pathway linking nature contact to ill-being and well-being. Using data from a survey of 600 U.S.-based adults administered online in 2022, we conducted structural equation modelling to test our hypotheses. We found that (1) frequency of nature contact was significantly associated with lesser emotional ill-being and greater emotional (...) well-being, (2) effective emotion regulation was significantly associated with lesser emotional ill-being and greater emotional well-being, and (3) the associations of higher frequency of nature contact with these benefits were partly explained via emotion regulation. Moreover, we found a nonlinear relationship for the associations of duration of nature contact with some outcomes, with a rise in benefits up to certain amounts of time, and a levelling off after these points. These findings support and extend previous work that demonstrates that the associations of nature contact with emotional ill-being and well-being may be partly explained by changes in emotion regulation. (shrink)

The present research describes a novel adaptive anomaly detection method to optimize the performance of nonlinear and time-varying systems. The proposal integrates a centroid-based approach with the real-time identification technique Recursive Least Squares. In order to find anomalies, the approach compares the present system dynamics with the average (centroid) of the dynamics found in earlier states for a given setpoint. The system labels the dynamics difference as an anomaly if it rises over a determinate threshold. To validate the proposal, two (...) different datasets obtained from a level control plant operation have been used, to which anomalies have been artificially added. The results shown have determined a satisfactory performance of the method, especially in those processes with low noise. (shrink)

'Computationalism' is a relatively vague term used to describe attempts to apply Turing's model of computation to phenomena outside its original purview: in modelling the human mind, in physics, mathematics, etc. Early versions of computationalism faced strong objections from many (and varied) quarters, from philosophers to practitioners of the aforementioned disciplines. Here we will not address the fundamental question of whether computational models are appropriate for describing some or all of the wide range of processes that they have been applied (...) to, but will focus instead on whether `renovated' versions of the \textit{new computationalism} shed any new light on or resolve previous tensions between proponents and skeptics. We find this, however, not to be the case, because the 'new computationalism' falls short by using limited versions of "traditional computation", or proposing computational models that easily fall within the scope of Turing's original model, or else proffering versions of hypercomputation with its many pitfalls. (shrink)

With the advent of COVID-19, a sudden, unexpected, and forced shift has been produced in the field of psychotherapy. Worldwide, many therapists closed their offices and started to deliver psychotherapy online through a screen. Although different media started to be incorporated, videoconferencing is undoubtedly the most common way in which therapists are doing therapy these days. This is catalyzing a rapid change in the practice of psychotherapy with probable lasting effects and deserves to be carefully reflected upon. Therefore, in this (...) paper our aim is to outline the main challenges for a medium that may have arrived to stay. In that sense, we review the literature to describe the state-of-the-art regarding the main aspects of videoconferencing psychotherapy as well as to suggest possible avenues for future research and practice. (shrink)

The ambiguous-cue task is composed of two-choice simultaneous discriminations involving three stimuli: positive (P), ambiguous (A) and negative (N). Two different trial types are presented: PA and NA. The ambiguous cue (A) served as an S- in PA trials, but as an S+ in NA trials. When using this procedure, it is typical to observe a less accurate performance in PA trials than in NA trials. This is called the ambiguous-cue effect. Recently, it was reported in starlings that the ambiguous-cue (...) effect decreases when the stimuli are presented on an angled (120°) panel. The hypothesis is that the angled panel facilitates that the two cues from each discrimination are perceived as a compound, precluding value transfer via a second-order conditioning mechanism. In this experiment, we used pigeons and a flat panel. Nevertheless, our data were quite similar to the previous data in starlings. We conclude that the form of the panel cannot explain the ambiguous-cue effect. Several alternatives to be explored in future experiments are suggested. The riddle of the ambiguous-cue problem still remains unsolved. (shrink)

Untimely -- "More Einsteinian than Einstein" -- Science or philosophy? -- The twin paradox -- Bergson's achilles' heel -- Worth mentioning? -- Bergson writes to Lorentz -- Bergson meets Michelson -- The debate spreads -- Back from Paris -- Two months later -- Logical positivism -- The immediate aftermath -- An imaginary dialog -- "Full-blooded" time -- The previous spring -- The church -- The end of universal time -- Quantum mechanics -- Things -- Clocks and wristwatches -- Telegraph, telephone, (...) and radio -- Atoms and molecules -- Einstein's films: reversible -- Bergson's movies: out-of-control -- Microbes and ghosts -- One new point: recording devices -- Bergson's last comments -- Einstein's last thoughts. (shrink)