Detecting intrusions in large networks is a highly demanding task. In order to reduce the computation demand of analysing every single packet travelling along one of such networks, some years ago flows were proposed as a way of summarizing traffic information. Very few research works have addressed intrusion detection in flows from a visualizations perspective. In order to bridge this gap, the present paper proposes the application of a novel projection method (Beta Hebbian Learning) under this framework. With the aim (...) to validate this method, 8 traffic segments, containing many flows, have been analysed by means of this projection method. The promising results obtained for these segments, extracted from the University of Twente dataset, validate the proposed application. (shrink)

En este artículo se examina la influencia que ejerce la violencia en la construcción del Estado. Asimismo, desde la perspectiva de Hannah Arendt, se analiza la política como espacio donde se afirma y protege la vida a través de la acción política y las normas jurídicas. Se trata de razonar el dualismo política-violencia, y violencia-normas jurídicas. En este sentido, la pregunta que da origen al presente escrito se enuncia en los siguientes términos: ¿cómo es posible reafirmar la vida como voluntad (...) a través de la política y cuidar de la existencia humana en un contexto en donde la violencia pareciera ser consustancial a la forma de estado y al medio por el cual se construye la comunidad política? Un examen riguroso de las circunstancian que fuerzan el análisis de este interrogante conduce necesariamente a sostener que: solo se podrá afirmar la vida a través del ejercicio de la política, cuando la sociedad política sea concebida como una construcción institucional cuya meta principal sea combinar la libertad de los individuos y las colectividades con la unidad de las normas jurídicas. (shrink)

Este artículo analiza el proceso de integración del Mercosur en el que participan Argentina, Brasil, Paraguay y Uruguay y sus efectos sobre la ciudadanía política y social. En la primera parte del mismo los autores examinan los rasgos, el contexto de nacimiento y la filosofía del proceso de integración mercosureño. La segunda parte analiza la evolución de la democracia y de la justicia social durante el proceso de integración. Los autores llegan a la conclusión de que el modelo de integración (...) mercosureño no puede contrarrestar la crisis de la democracia y de la justicia social que tienen lugar especialmente en Argentina y Brasil. (shrink)

A large part of technological advances, especially in the field of industry, have been focused on the optimization of productive processes. However, the detection of anomalies has turned out to be a great challenge in fields like industry, medicine or stock markets. The present work addresses anomaly detection on a control level plant. We propose the application of different intelligent techniques, which allow to obtain one-class classifiers using real data taken from the correct plant operation. The performance of each classifier (...) is assessed and validated with real created faults, achieving successful overall results. (shrink)

Este articulo analiza el proceso de integración del Mercosur en el que participan Argentina, Brasil, Paraguay y Uruguay y sus efectos sobre la ciudadanía política y social. En la primera parte del mismo los autores examinan los rasgos, el contexto de nacimiento y la filos ofía del proceso de integración mercosureño. La segunda parte analiza la evoluciónde la democracia y de la justicia social durante el proceso de integración. Los autores llegan a la conclusión de que el modelo de integración (...) mercosureño no puede contrarrestar la crisis de la democracia y de la justicia social que tienen lugar especialmente en Argentina y Brasil. (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)

Batteries are a fundamental storage component due to its various applications in mobility, renewable energies and consumer electronics among others. Regardless of the battery typology, one key variable from a user’s perspective is the remaining energy in the battery. It is usually presented as the percentage of remaining energy compared to the total energy that can be stored and is labeled State Of Charge (SOC). This work addresses the development of a hybrid model based on a Lithium Iron Phosphate (LiFePO4) (...) power cell, due to its broad implementation. The proposed model calculates the SOC, by means of voltage and electric current as inputs and the latter as the output. Therefore, four models based on k-Means, Agglomerative Clustering, Gaussian Mixture and Spectral Clustering techniques have been tested in order to obtain an optimal solution. (shrink)

A hemi-implicative lattice is an algebra \((A,\wedge,\vee,\rightarrow,1)\) of type (2, 2, 2, 0) such that \((A,\wedge,\vee,1)\) is a lattice with top and for every \(a,b\in A\), \(a\rightarrow a = 1\) and \(a\wedge (a\rightarrow b) \le b\). A new variety of hemi-implicative lattices, here named sub-Hilbert lattices, containing both the variety generated by the \(\{\wedge,\vee,\rightarrow,1\}\) -reducts of subresiduated lattices and that of Hilbert lattices as proper subvarieties is defined. It is shown that any sub-Hilbert lattice is determined (up to isomorphism) by (...) a triple (_L_, _D_, _S_) which satisfies the following conditions: _L_ is a bounded distributive lattice, _D_ is a sublattice of _L_ containing 0, 1 such that for each \(a, b \in L\) there is an element \(c \in D\) with the property that for all \(d \in D\), \(a \wedge d \le b\) if and only if \(d \le c\) (we write \(a \rightarrow _D b\) for the element _c_), and _S_ is a non void subset of _L_ such that _S_ is closed under \(\rightarrow _D\) and _S_, with its inherited order, is itself a lattice. Finally, the congruences of sub-Hilbert lattices are studied. (shrink)

In daily academic life, students are exposed to a wide range of potentially stressful situations which could negatively affect their academic achievement and their health. Among the factors that could be weakened by academic stress, attention has been paid to expectations of self-efficacy, which are considered one of the most important determinants for student engagement, persistence, and academic success. From a proactive perspective, research on academic stress has emphasized the importance of coping strategies in preventing harmful consequences. In recent years, (...) there has been a growing interest in discovering the extent to which individuals are able to combine different coping strategies and the adaptive consequences this flexibility entails. However, studies using this person-centered approach are still scarce in the academic context. On that basis, this current study had two objectives: (a) to examine the existence of different profiles of university students based on how they combined different approach coping strategies (positive reappraisal, support seeking, and planning); and (b) to determine the existence of differences in general expectations of self-efficacy between those coping profiles. 1072 university students participated in the study. The coping profiles were determined by Latent Profile Analysis (LPA). The differences in the self-efficacy variable were determined using ANCOVA, with gender, university year, and degree type as covariates. Four approach coping profiles were identified: (a) low generalized use of approach coping strategies; (b) predominance of social approach coping approaches; (c) predominance of cognitive approach coping approaches; (d) high generalized use of approach coping strategies. The profile that showed that a greater combination of the three strategies was related to higher general self-efficacy expectations, and vice versa. These results suggest that encouraging flexibility in coping strategies would help to improve university students’ self-efficacy. (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)

Some business schools have come under considerable criticism for what observers see as their complicit involvement in the corporate scandals and financial crises of the last 15 years. Much of the discussion about changes that schools might undertake has been focused on curriculum issues. However, revisiting the curriculum does not get at the root cause of the problem. Instead, it might create a new challenge: the risk of decoupling the discussion of the curriculum from broader issues of institutional purpose. In (...) this article, we argue that the most pressing need facing business schools is not to teach new courses to be responsive to social demands and stay relevant. Instead, it is to revisit their basic mission—the principles and beliefs on which they were founded—and then to re-evaluate their curriculum design choices in this light. We contrast the Spartan and Athenian educational paradigms as a way of shedding light on the nature of a coherent response. (shrink)

The large number of sensors and actuators that make up the Internet of Things obliges these systems to use diverse technologies and protocols. This means that IoT networks are more heterogeneous than traditional networks. This gives rise to new challenges in cybersecurity to protect these systems and devices which are characterized by being connected continuously to the Internet. Intrusion detection systems are used to protect IoT systems from the various anomalies and attacks at the network level. Intrusion Detection Systems can (...) be improved through machine learning techniques. Our work focuses on creating classification models that can feed an IDS using a dataset containing frames under attacks of an IoT system that uses the MQTT protocol. We have addressed two types of method for classifying the attacks, ensemble methods and deep learning models, more specifically recurrent networks with very satisfactory results. (shrink)

The concept of polarity is pervasive in natural language. It relates syntax, semantics and pragmatics narrowly, Semantics: an international handbook of natural language meaning, De Gruyter Mouton, Berlin, 2011; Israel in The grammar of polarity: pragmatics, sensitivity, and the logic of scales, Cambridge studies in linguistics, Cambridge University Press, Cambridge, 2014), it refers to items of many syntactic categories such as nouns, verbs and adverbs. Neutral polarity items appear in affirmative and negative sentences, negative polarity items cannot appear in affirmative (...) sentences, and positive polarity items cannot appear in negative sentences. A way of reasoning in Natural Language is through Natural Logic. This logic is based on the concept of polarity in order to make the meaning of a sentence weaker o stronger without changing its truth value. There exist many proposals to compute polarity in the Natural Logic context, the most widely known are the ones by: van Benthem, Sánchez-Valencia, Dowty, and van Eijck, 6th international Tbilisi symposium on logic, language, and computation, Batumi, Georgia, Springer, 2007). If Natural Logic is going to be used, as an inferential mechanism between text fragments, in Natural Language Processing applications such as text summarization, question answering, and information extraction, it is a priority to know what the existing relationship among the aforementioned algorithms is; for example, to implement the most general. We show in this paper the equivalence among the analyzed algorithms, filling a gap in Natural Logic research, particularly in computing polarity, and the soundness of their algorithms. (shrink)

Investiga a produção científica na temática Epistemologia e Historiografia da Ciência da informação a partir dos Anais do Encontro Nacional de Pesquisa em Ciência da informação, de dados da Plataforma Lattes e da literatura indexada na Base de Dados da Ciência da informação. Identifica o coletivo de pesquisadores que dão continuidade e consistência ao trabalho epistemológico e historiográfico da área. Destaca, na temática abordada, um grupo que consegue produzir mais que a maioria dos demais pesquisadores. Pesquisadores com alunos na pós-graduação (...) tendem a publicar mais artigos em colaboração do que os outros autores que se não encaixam nesse perfil. Os resultados permitiram a descrição de perfis de pesquisadores a partir de um recorte. Conclui que as pesquisas sobre a referida temática, alinhadas aos preceitos dos estudos métricos, podem permitir o desenvolvimento de teias conceituais e metodológicas da Ciência da Informação. (shrink)

O presente artigo procura refletir sobre o modo pelo qual Gramsci debate com os autores de seu tempo, a fim de recolocar o marxismo no terreno da história e da dialética. Tomamos como referência o confronto de Gramsci com o neo-idealismo italiano, representado por Benedetto Croce, e com o marxismo economicista, representado por Nicolai Bukharin. Com isso, procuraremos analisar se Gramsci seria autenticamente um marxista ou, dito de outro modo, até que ponto ele teria se afastado de Marx pela aproximação (...) a Hegel. O confronto de Gramsci com o neo-idealismo de Croce e o determinismo de Bukharin evidenciará, como veremos, sua perspectiva crítica. (shrink)

Automatic control of physiological variables is one of the most active areas in biomedical engineering. This paper is centered in the prediction of the analgesic variables evolution in patients undergoing surgery. The proposal is based on the use of hybrid intelligent modelling methods. The study considers the Analgesia Nociception Index to assess the pain in the patient and remifentanil as intravenous analgesic. The model proposed is able to make a one-step-ahead prediction of the remifentanil dose corresponding to the current state (...) of the patient. The input information is the previous remifentanil dose, the ANI variable and the electromyogram signal. Modelling techniques used are Artificial Neural Networks and Support Vector machines for Regression combined with clustering methods. Both training and validation were done with a real dataset from different patients. Results obtained show the potential of this methodology to calculate the drug dose corresponding to a given analgesic state of the patient. (shrink)

Emotional intelligence is a psychological skill that aids athletes in the control of emotions and optimization of sports performance. The present study investigated the psychometric properties of the Self-Report Emotional Intelligence Test in 508 Brazilian youth and adult athletes. Data analysis was conducted through Exploratory and Confirmatory Factor Analysis, Cronbach’s alpha, composite reliability and Pearson’s Correlation. EFA revealed the one-factor model with 26 items with the best adjustment. CFA confirmed the one-factor model with 26 items with best greater fit. No (...) evidence of invariance was found, suggesting that the SSEIT must be used with caution when comparing gender and age groups. The external validity was found in the correlation of EI and cognitive anxiety and self-confidence. It is concluded that the Brazilian version of SSEIT for the sports context presented acceptable psychometric properties, however, showed limitations that should be explored in the future. (shrink)

Present research proposes the application of unsupervised and supervised machine-learning techniques to characterize Android malware families. More precisely, a novel unsupervised neural-projection method for dimensionality-reduction, namely, Beta Hebbian Learning, is applied to visually analyze such malware. Additionally, well-known supervised Decision Trees are also applied for the first time in order to improve characterization of such families and compare the original features that are identified as the most important ones. The proposed techniques are validated when facing real-life Android malware data by (...) means of the well-known and publicly available Malgenome dataset. Obtained results support the proposed approach, confirming the validity of BHL and DTs to gain deep knowledge on Android malware. (shrink)

The interest of assigning homework is frequently discussed due to its alleged low impact on student achievement. One of the current lines of research is to emphasize the quality of student homework engagement rather than the amount of time spent on homework. The aim of this study was to determine (a) the extent to which students’ prior achievement affects their homework engagement (i.e., time spent, time management, and amount of teacher-assigned homework done), and (b) how students’ intrinsic motivation towards homework (...) may mediate or moderate the relationship between prior achievement and the homework engagement variables. A large sample of students from the first four years of Secondary Education (N = 1899) completed questionnaires. The results showed that intrinsic motivation partially mediates, but does not moderate, the effect of prior achievement on the three variables related to homework engagement (time spent, time management, and amount of teacher-assigned homework done). These results highlight the importance of considering both students’ current level of achievement and their motivation towards homework engagement when assigning homework. (shrink)

The present study aimed to verify the quarantine’s effects during a serious viral outbreak on the cardiovascular and performance associated with the Yo-Yo test in a sample of professional soccer players. 20 high-level soccer players participated in this study. The intermittent Yo-Yo test was performed pre- and post- COVID-19 quarantine in a random order. During each test, the soccer players’ running performance outcomes were monitored using a portable 5-Hz GPS with a 100 Hz accelerometer and a paired t-test was conducted (...) at a p-value of ≤ 0.05. The main results demonstrated significant differences between pre- versus post-COVID-19 quarantine in the following variables: relative distance, maximal speed, acceleration, deceleration, sprints > 19 km/h [0.8 % >0.5 %], and in high intensity running distance [16.48 m > 0.827 m]. We concluded that COVID-19-related restrictions and quarantine COVID-19 demonstrated adverse effects on professional soccer players’ Yo-Yo tests performance. (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 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)

This volume has 41 chapters written to honor the 100th birthday of Mario Bunge. It celebrates the work of this influential Argentine/Canadian physicist and philosopher. Contributions show the value of Bunge’s science-informed philosophy and his systematic approach to philosophical problems. The chapters explore the exceptionally wide spectrum of Bunge’s contributions to: metaphysics, methodology and philosophy of science, philosophy of mathematics, philosophy of physics, philosophy of psychology, philosophy of social science, philosophy of biology, philosophy of technology, moral philosophy, social and political (...) philosophy, medical philosophy, and education. The contributors include scholars from 16 countries. Bunge combines ontological realism with epistemological fallibilism. He believes that science provides the best and most warranted knowledge of the natural and social world, and that such knowledge is the only sound basis for moral decision making and social and political reform. Bunge argues for the unity of knowledge. In his eyes, science and philosophy constitute a fruitful and necessary partnership. Readers will discover the wisdom of this approach and will gain insight into the utility of cross-disciplinary scholarship. This anthology will appeal to researchers, students, and teachers in philosophy of science, social science, and liberal education programmes. 1. Introduction Section I. An Academic Vocation Section II. Philosophy Section III. Physics and Philosophy of Physics Section IV. Cognitive Science and Philosophy of Mind Section V. Sociology and Social Theory Section VI. Ethics and Political Philosophy Section VII. Biology and Philosophy of Biology Section VIII. Mathematics Section IX. Education Section X. Varia Section XI. Bibliography. (shrink)

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)

As it is well known, mobile phones have become a basic gadget for any individual that usually stores sensitive information. This mainly motivates the increase in the number of attacks aimed at jeopardizing smartphones, being an extreme concern above all on Android OS, which is the most popular platform in the market. Consequently, a strong effort has been devoted for mitigating mentioned incidents in recent years, even though few researchers have addressed the application of visualization techniques for the analysis of (...) malware. Within this field, the present work proposes the extension of a new technique called Hybrid Unsupervised Exploratory Plots to visualize Android malware datasets. More precisely, the novel Beta-Hebbian Learning (BHL) method is applied for the first time and validated under the frame of Hybrid Unsupervised Exploratory Plots, in conjunction with clustering methods. The informative visualization achieved provides a picture of the structure of the malware families, allowing subsequent analysis of their organization. To validate the Hybrid Unsupervised Exploratory Plot extension and its tuning, the popular Android Malware Genome dataset has been used in the experimental setting. Promising results have been obtained, suggesting that BHL applied in combination with clustering techniques in Hybrid Unsupervised Exploratory Plots are a viable resource for the visualization of malware families. (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)

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)

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)

This volume presents the concept of Ecoscape as spatial interrelations, or spatially patterned processes, that are constitutive of an environment_an ecosystem. Contributors investigate environmental issues concerning the human impact on geohistory, food distribution, genetically modified biota, waste management, scientific mapping, and the rethinking of human identity.

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)