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Este trabajo presenta un breve análisis de vulnerabilidades en dispositivos del Internet de las cosas (IoT) en Ecuador, mediante el desarrollo de una herramienta de software que busca direcciones IPv4 que están dentro del rango del territorio ecuatoriano y analiza los puertos de comunicación comunes de estas direcciones observando si dichos puertos están activos o abiertos exponiendo información sensible. Los resultados obtenidos durante el proceso de búsqueda de direcciones IPv4 han sido satisfactorios, encontrando información como: cámaras web, servidores Apache, páginas web e incluso petición de credenciales para acceder a la configuración de un router, con estos resultados se refleja que el nivel de seguridad informática en el Ecuador se encuentra en un nivel bajo. Considerando que Pichincha y Guayas, son las dos provincias más grandes del Ecuador, tienen la mayor cantidad de direcciones IPv4 con puertos activos y la mayor cantidad de exposición de información sensible sin medidas de seguridad.

The potential of fifth generation (5G) networks will contribute to the development of countries. The capabilities of 5G, such as a huge increase in transmission speed, decreased latency, improvement of the service delivery in places with a high user density and facilitates ubiquitous communication between devices. This allows 5G cellular networks to be the required support to establish reliable communications in real time with a view to the massification of the services established in Internet of Everything (IoE). In particular, the challenges and opportunities involved in the deployment of 5G in Ecuador are analyzed and discussed. This paper presents a review of recent literature on the deployment of 5G networks and the status of the implementation of this technology in Ecuador, considering its advantages, health implications and policy strategies on the use of frequencies and deployment. In addition, potential applications are mentioned that could be used to take advantage of many problems that have arisen during the COVID-19 pandemic, such as the lack of Internet access networks. In particular, it analyzes and discuss the challenges and opportunities involved in the 5G deployment in Ecuador.

Lysophosphatidic acid (LPA) is a lysophospholipid that acts as an extracellular signal through the activation of cognate G protein-coupled receptors (GPCRs). There are six known LPA receptors (LPA1–6). The first such receptor, LPA1, was identified in the embryonic brain and has been studied extensively for gene expression throughout the body, including through studies of receptor-null mice. However, identifying receptor protein expression in situ and in vivo within living cells and tissues has been difficult because of biologically low receptor expression and variable antibody specificity. To visualize native LPA1 receptor expression in situ, we generated a knock-in mouse produced by homologous recombination in murine embryonic stem (ES) cells to replace a wildtype Lpar1 allele with a mutant allele created by in-frame fusion of EGFP to the 4th exon of Lpar1 (Lpar1-EGFP knock-in allele). Homozygous knock-in mice appeared normal and the expected mendelian ratios of knock-in allele transmission were present in females and males. Histological assessments of the fetal and adult central nervous system (CNS) demonstrated expression patterns that were consistent with prior in situ hybridization studies. This new mouse line will be useful for studies of LPA1 in the developing and adult CNS, as well as other tissues, and for receptor assessments in living tissues and disease models.

SummaryFTY720 (fingolimod) is a sphingosine 1-phosphate (S1P) receptor modulator and sphingosine analogue approved for multiple sclerosis (MS) therapy, which can functionally antagonize the S1P receptor, S1P1. Vitamin B12 (B12) deficiency produces neurological manifestations resembling MS. Here, we report a new mechanism where FTY720 suppresses neuroinflammation by regulating B12 metabolic pathways. Nuclear RNA-seq of c-Fos-activated astrocytes (called ieAstrocytes) from experimental autoimmune encephalomyelitis (EAE) spinal cords identified up-regulation of CD320, a transcobalamin 2 (TCN2)-B12 receptor, by S1P1 inhibition. CD320 was reduced in MS plaques. Deficiency of CD320 or dietary B12 worsened EAE and eliminated FTY720’s efficacy, while concomitantly down-regulating type I interferon signaling. TCN2 functioned as a chaperone for FTY720 and sphingosine, which induced astrocytic CD320 internalization. An accompanying paper identified a requirement for astrocyte sphingosine kinases in FTY720 efficacy and its altered expression in MS brains, molecularly linking MS and B12 deficiency that can be accessed by sphingolipid/fingolimod metabolic pathways.

SummaryMultiple sclerosis (MS) is an immune-mediated demyelinating disease that alters central nervous system (CNS) functions. Relapsing-remitting MS (RRMS) is the most common form, which can transform into secondary-progressive MS (SPMS) that is associated with progressive neurodegeneration. Single-nucleus RNA sequencing (snRNA-seq) of MS lesions identified disease-related transcriptomic alterations; however, their relationship to non-lesioned MS brain regions has not been reported and which could identify prodromal or other disease susceptibility signatures. Here, snRNA-seq was used to generate high-quality RRMS vs. SPMS datasets of 33,197 nuclei from 8 normal-appearing MS brains, which revealed divergent cell type-specific changes. Notably, SPMS brains downregulated astrocytic sphingosine kinases (SPHK1/2) – the enzymes required to phosphorylate and activate the MS drug, fingolimod. This reduction was modeled with astrocyte-specific Sphk1/2 null mice in which fingolimod lost activity, supporting functionality of observed transcriptomic changes. These data provide an initial resource for studies of single cells from non-lesioned RRMS and SPMS brains.

Ponesimod is a sphingosine 1-phosphate (S1P) receptor (S1PR) modulator that was recently approved for treating relapsing forms of multiple sclerosis (MS). Three other FDA-approved S1PR modulators for MS-fingolimod, siponimod, and ozanimod-share peripheral immunological effects via common S1P

The recent increasing cases released worldwide on espionage require a knowledge systematization study in this area. This paper presents a general scheme of cyber espionage process based on a literature review of remarkable cases which generated news about this topic and includes the malware report analysis made by security vendors. To understand the aspects involved and the approaches employed, we defined a general model to cover all phases used by cyber espionage. Our model considers two main aspects: first, the technical aspect driven by the rapid advance of information and communication technologies (ICT), as well as the software engineering level used by cybercriminals to create sophisticated malware; second, the human aspect influenced by the power struggle between nations and politicians, also considering the lack of technological knowledge or training in organizations. As a result, it allows the attackers using social engineering as the most effective mean for systems intruding.

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In this work, a study of the molecular adsorption and geometry of phenol on the nonpolar (1010) ZnO surface has been carried out. In an attempt to reproduce a more realistic system, an oxygen vacancy has been introduced in the surface, which leads to an increase in the band gap, from 1.16 eV for the pristine surface to 1.38 eV in the defective one, and a local level within the band gap, which corresponds to an F-center type. Calculations performed after the introduction of a phenol molecule in different configurations over the surface suggest that dissociative chemisorption is the main phenomena, with two interesting scenarios: first, the charge can be transferred from the molecule toward the surface, and vice versa, depending on the adsorption site.

Freeware is proprietary software that can be used free of charge. A popular vector for distributing freeware are download portals, i.e., websites that index, categorize, and host programs. Download portals can be abused to distribute potentially unwanted programs (PUP) and malware. The abuse can be due to PUP and malware authors uploading their ware, by benign freeware authors joining as affiliate publishers of PPI services and other affiliate programs, or by malicious download portal owners. In this work, we perform a systematic study of abuse in download portals. We build a platform to crawl download portals and apply it to download 191K Windows freeware installers from 20 download portals. We analyze the collected installers and execute them in a sandbox to monitor their installation. We measure an overall ratio of PUP and malware between 8% (conservative estimate) and 26% (lax estimate). In 18 of the 20 download portals examined the amount of PUP and malware is below 9%. But, we also find two download portals exclusively used to distribute PPI downloaders. Finally, we detail different abusive behaviors that authors of undesirable programs use to distribute their programs through download portals.

The reduction of mechanical vibrations is field of continuous research in engineering in order to reduce damage and improve the performance of structures, machinery, piping and others systems, when they are in presence of dynamical forces. In this sense, different alternatives have been proposed over time, the active vibration absorber highlights as an alternative which can absorb the vibration from a primary system for different excitation frequency in real time. In this study, an active vibration absorber has been modelled as an electromechanical device composed of a 1-DOF model for the absorber and an equivalent electrical circuit for the electromagnetic actuator. It was implemented in a real structure represented by a cantilever beam continuous model, which is the most accurate model that can be used. A set of differential equations which represent the dynamical behaviour of the cantilever beam implemented with the active vibration absorber was obtained from the complete model and it was simulated in Matlab Simulink®. An application of the active vibration absorber for an industry piping system based on the finite element model formulation is presented and developed. Results indicate that the active vibration absorber is able to significantly reduce the vibrations amplitude of the primary system, especially in resonance conditions, for a discrete frequency range. The analytic model and procedure developed here can easily widespread to any more complex primary system.

Visual Abstract, Glutamate is the principal excitatory neurotransmitter in the human brain. Following neurotransmission, astrocytes remove excess extracellular glutamate to prevent neurotoxicity. Glutamate neurotoxicity has been reported in multiple neurologic diseases including multiple sclerosis (MS), representing a shared neurodegenerative mechanism. A potential modulator of glutamate neurotoxicity is the bioactive lysophospholipid sphingosine 1-phosphate (S1P) that signals through five cognate G-protein-coupled receptors, S1P1–S1P5; however, a clear link between glutamate homeostasis and S1P signaling has not been established. Here, S1P receptor knock-out mice, primary astrocyte cultures, and receptor-selective chemical tools were used to examine the effects of S1P on glutamate uptake. S1P inhibited astrocytic glutamate uptake in a dose-dependent manner and increased mitochondrial oxygen consumption, primarily through S1P2. Primary cultures of wild-type mouse astrocytes expressed S1P1,2,3 transcripts, and selective deletion of S1P1 and/or S1P3 in cerebral cortical astrocytes, did not alter S1P-mediated, dose-dependent inhibition of glutamate uptake. Pharmacological antagonists, S1P2-null astrocytes, and Gα12 hemizygous-null astrocytes indicated that S1P2-Gα12-Rho/ROCK signaling was primarily responsible for the S1P-dependent inhibition of glutamate uptake. In addition, S1P exposure increased mitochondrial oxygen consumption rates (OCRs) in wild-type astrocytes and reduced OCRs in S1P2-null astrocytes, implicating receptor selective metabolic consequences of S1P-mediated glutamate uptake inhibition. Astrocytic S1P-S1P2 signaling increased extracellular glutamate, which could contribute to neurotoxicity. This effect was not observed with the FDA-approved S1P receptor modulators, siponimod and fingolimod. Development and use of S1P2-selective antagonists may provide a new approach to reduce glutamate neurotoxicity in neurologic diseases.

As shaped polycrystalline diamond compact (PDC) cutter geometries become more prevalent across the industry, this paper statistically reviews field testing of novel shaped PDC cutters in a variety of challenging applications. Firstly, the paper identifies the improvement in efficiency when compared with conventional PDC cutter geometries. Secondly, it confirms the reliability and robustness of the aforementioned shaped cutter geometries. After several years of field testing shaped PDC cutter geometries, the question of how they hold up against conventional cylinder-shaped cutters remains unanswered. This study looks at drill bits that have the same overall design; however, each bit has different shape configurations that are deployed in a range of hole sizes and drilling applications. Data was collected from more than 100 runs and included advanced dull evaluation techniques, data mining, and comparative analyses. During data collation and interpretation, several statistical methods were used to improve the accuracy of comparisons and observing trends. These results are statistically profound, they show that in the majority of cases, shaped cutter geometries enhance drilling efficiency either in line or beyond laboratory testing. For a comparable parameter envelop, an improvement of between 20-40% in rate of penetration (ROP) was observed in various hole sizes, particularly in carbonates through Arabian Gulf reservoir formations. The reliability assessment, which speaks to the number of runs per serial number, has shown an improvement over conventional type cutters and in some cases reaching six re-runs. Cutter robustness was deduced by comparing the average interval drilled, while also reviewing the overall dull in context to the typical dull condition. When considering all three metrics over the large data set, it can be concluded that shaped cutters have, at a minimum, equivalency in both robustness and reliability, but, more importantly, bring an efficiency advantage over their legacy generation of PDC cutters. When considering the deployment of shaped cutter technology, the study has highlighted a significant flexibility in vertical, directional, and extended lateral applications from hard and abrasive rock to highly interbedded formations. Overall, shaped cutter efficiency and robustness have been validated in the laboratory and now proven to bring greater change in drilling performance and reliability. This paper pushes beyond the claims within laboratory testing and statistically proves the robustness, reliability, and efficiency of shaped cutter geometries within the drill bit market. Not only is their usage growth now statistically proven, but a methodology has been developed to comparatively assess this technology during field testing. As PDC shaped cutter technology continues to grow, it is important to define its limitation along with determining where to deploy its strengths to obtain peak drilling performance.

International audience; Lysphosphatidic acid (LPA) is a major natural bioactive lipid mediator whose biological functions affect multiple organs. These include bone as demonstrated by global Lpar1-knockout mice (Lpar1-/-) which present a bone growth defect. LPA acts on all bone cells including osteoblasts, that are responsible for bone formation, and osteoclasts, which are specialized cells that resorb bone. LPA appears as a potential new coupling molecule during bone remodeling. LPA1 is the most ubiquitous LPA receptor among the six LPA receptor family members (LPA1-6). To better understand the specific role of LPA via its receptor LPA1 in osteoblastic cell lineage we generated osteoblast-specific Lpar1 knockout mice (Lpar1-∆Ob) by crossing Lpar1flox/flox and Osx:Cre+ mouse lines. Lpar1-∆Ob mice do not recapitulate the bone defects of Lpar1-/- mice but revealed reduced bone mineralization and decreased cortical thickness, as well as increased bone porosity associated with an augmentation in the lacunae areas of osteocyte and their apoptotic yield. In vitro, primary Lpar1-∆Ob and immortalized cl1-Ob-Lpar1-/- osteoblasts revealed a remarkable premature expression of alkaline phosphatase, reduced cell proliferation associated with decreased YAP-P nuclear accumulation, and reduced mineralization activity. Osteocyte specification is markedly impaired as demonstrated by reduced expression of early (E11) and late (DMP1, DKK1, SOST) osteocyte markers ex vivo in enriched osteocytic fractions of Lpar1-∆Ob mouse bone explants. In addition, E11 expression and dendrite formation induced by FGF2 are markedly impaired in both primary Lpar1-∆Ob and immortalized cl1-Ob-Lpar1-/- osteoblasts. Taken together these results suggest a new role for LPA in bone mass control via bone mineralization and osteocyte function.

LPA1 is one of the six known receptors (LPA1-6) for lysophosphatidic acid (LPA). Constitutive Lpar1 null mutant mice have been instrumental in identifying roles for LPA-LPA1 signaling in neurobiological processes, brain development, and behavior as well as modelling human neurological diseases like neuropathic pain. Constitutive Lpar1 null mutant mice are protected from partial sciatic nerve ligation (PSNL)-induced neuropathic pain, however Lpar1 expressing cell types that are functionally responsible for mediating this protective effect are unknown. Here we report generation of a Lpar1flox/flox conditional null mutant mouse that allows cre-mediated conditional deletion combined with its use in a PSNL pain model. Lpar1flox/flox mice were crossed with cre transgenic lines driven by neural gene promoters for nestin (all neural cells), synapsin (neurons), or P0 (Schwann cells). CD11b-cre transgenic mice were also used to delete Lpar1 in microglia. PSNL-initiated pain responses were reduced following cre-mediated Lpar1 deletion with all 3 neural promoters but not the microglial promoter, supporting involvement of Schwann cells and central and/or peripheral neurons in mediating pain. Interestingly, rescue responses that were due to conditional deletion were non-identical, implicating distinct roles for Lpar1-expressing cell types. Our results with a new Lpar1 conditional mouse mutant expand an understanding of LPA1 signaling in the PSNL model of neuropathic pain.

Neuropathic pain (NP) is a complex chronic pain state with a prevalence of almost 10% in the general population. Pharmacological options for NP are limited and weakly effective, so there is a need to develop more efficacious NP attenuating drugs. Activation of the type 1 lysophosphatidic acid (LPA(1)) receptor is a crucial factor in the initiation of NP. Hence, it is conceivable that a functional antagonism strategy could lead to NP mitigation. Here we describe a new series of LPA(1) agonists among which derivative (S)-17 (UCM-05194) stands out as the most potent and selective LPA(1) receptor agonist described so far (E(max) = 118%, EC(50) = 0.24 µM, K(D) = 19.6 nM; inactive at autotaxin and LPA(2-6) receptors). This compound induces characteristic LPA(1)-mediated cellular effects and prompts the internalization of the receptor leading to its functional inactivation in primary sensory neurons and to an efficacious attenuation of the pain perception in an in vivo model of NP.

The diversity and complexity of the human brain are widely assumed to be encoded within a constant genome. Somatic gene recombination, which changes germline DNA sequences to increase molecular diversity, could theoretically alter this code but has not been documented in the brain, to our knowledge. Here we describe recombination of the Alzheimer's disease-related gene APP, which encodes amyloid precursor protein, in human neurons, occurring mosaically as thousands of variant 'genomic cDNAs' (gencDNAs). gencDNAs lacked introns and ranged from full-length cDNA copies of expressed, brain-specific RNA splice variants to myriad smaller forms that contained intra-exonic junctions, insertions, deletions, and/or single nucleotide variations. DNA in situ hybridization identified gencDNAs within single neurons that were distinct from wild-type loci and absent from non-neuronal cells. Mechanistic studies supported neuronal 'retro-insertion' of RNA to produce gencDNAs; this process involved transcription, DNA breaks, reverse transcriptase activity, and age. Neurons from individuals with sporadic Alzheimer's disease showed increased gencDNA diversity, including eleven mutations known to be associated with familial Alzheimer's disease that were absent from healthy neurons. Neuronal gene recombination may allow 'recording' of neural activity for selective 'playback' of preferred gene variants whose expression bypasses splicing; this has implications for cellular diversity, learning and memory, plasticity, and diseases of the human brain.

The Density Functional Theory (DFT) within the Generalized Gradient Approximation (GGA) approach and van der Waals (vdW) corrections have been used to study the molecular adsorption of ethanol over the BaTiO3 (0 0 1) surface. Two kinds of surfaces have been considered: (i) a non-defective surface, and, to model a more realistic system, (ii) a surface with the presence of an oxygen vacancy (VO). Chemisorption and physisorption has been found to occur. The O deficiency included at surface provokes the appearance of a small magnetic moment (−0.48 µB), and the presence of non-confined electrons, which leads to n-type electrical conductivity. In chemisorption, the oxygen of the molecule binds with 2 barium atoms at the surface, while a hydrogen atom is dissociated from the molecule to bind with an oxygen atom at the surface or to occupy the VO region; attained adsorption energies fluctuate from −1.00 eV to −2.26 eV (VO surface). In physisorption, the oxygen of the molecule seems to bind with a barium at the surface, however, no impact over the structure and atomic charges of the molecule or surface has been perceived; obtained adsorption energies range from −0.20 eV to −0.50 eV (VO surface). Computed adsorption energies for clean and VO surfaces show that VO sites are more suitable for molecular adsorption to occur.

Neuropathic pain (NP) is a complex chronic pain state with a prevalence of almost 10% in the general population. Pharmacological options for NP are limited and slightly effective, so there is a need of developing more efficacious NP attenuating drugs. Activation of the type 1 lysophosphatidic acid (LPA(1)) receptor is a crucial factor in the initiation of NP. Hence, it is conceivable that a functional antagonism strategy could lead to NP mitigation. Here we describe a new series of LPA(1) agonists among which derivative (S)-17 (UCM-05194) stands out as the most potent and selective LPA(1) receptor agonist described so far (E(max)=118%, EC(50)=0.24 μM, K(D)=19.6 nM; inactive at autotaxin and LPA(2–6) receptors). This compound induces characteristic LPA(1)-mediated cellular effects and prompts the internalization of the receptor leading to its functional inactivation in primary sensory neurons and to an efficacious attenuation of the pain perception in an in vivo model of NP.

Day by day cities over the world become more intelligent. The Internet of Things(IoT) has had an important impact in the evolution of the interaction between people, things and the Internet. This paper studies the current status of the IoT development in Ecuador, its challenges and opportunities of IoT deployment. From the point of view of Ecuador, this paper analyzes such challenges on industry, infrastructure and technology, security and privacy, legal aspects, education and society. Moreover, several opportunities and potential applications were identified in order to contribute to the development of the country. Finally, this paper discusses the need to develop a legal framework to guarantee an adequate IoT deployment accompanied by a reasonable support for IoT initiatives in the country.

In recent years, the widespread use of artificial neural networks in the field of image processing has been of vital relevance to research. The main objective of this research work is to present an effective and efficient method for the detection of eyes, nose and lips in images that include faces of Alzheimer’s patients. The methods to be used are based on the extraction of deep features from a well-designed convolutional neural network (CNN). The result focuses on the processing and detection of facial features of people with and without Alzheimer’s disease.

The interaction of the user with visual impairment with assistive technologies, and in particular with screen readers, generates a group of actions and events during their navigation. These interactions are defined as behavioral patterns, which have a sequence that occurs at specific time slot. Understanding user behavior by analyzing their interaction with applications, in addition, details the characteristics, relationships, structures and functions of the sequence of actions in a specific application domain. The objective of this document is to find activity patterns from a set of commands used by the user, combining data mining and a Bayesian model. This model calculates the probability of the functions used with the screen reader and generates a behavior profile to improve the user experience. For this study, the screen reader JAWS version 2018, the Open Journal Systems platform version 3.0.1 and a computer with Windows 10 operating system were used. During the first phase, command history used by the user by interacting with the Open Journal Systems platform were collected. The result is that the accessibility of users with visual impairment to interact with the computer and its applications has been improved by applying this model.

During the last decade social media have generated tons of data, that is the primal information resource for multiple applications. Analyzing this information let us to discover almost immediately unusual situations, such as traffic jumps, traffic accidents, state of the roads, etc.. This research proposes an approach for classifying pollution and traffic tweets automatically. Taking advantage of the information in tweets, it evaluates several machine learning supervised algorithms for text classification, where it determines that the support vector machine (SVM) algorithm achieves the highest accuracy value of 85,8% classifying events of traffic and not traffic. Furthermore, to determine the events that correspond to traffic or pollution we perform a multiclass classification. Where we obtain an accuracy of 78.9%.

This study focuses on the preprocessing of information for the selection of the most significant characteristics of a network traffic database, recovered from an Ecuadorian institution, using a method of classifying optimal entities and attributes, with the In order to achieve a complete understanding of its real composition to be able to generate patterns and identification of trends of behavior in the network, both of patterns that deviate from normal traffic behavior (intrusive), as well as normal, to detect with high precision possible attacks. Network management tools were used as a multifunctional security server software, as well as pre-processing of data tools for the selection of attributes, as well as the elimination of noise from the instances of the database, It allowed to identify which ins- tances and attributes are correct and contribute with effective information in the study. Among them we have: Greedy Stepwise Algorithm (Algoritmo Voraz), K-Means Algorithm, Discrete Chi-square Attributes and the use of computational models as Evolutionary Neural Networks and Gene Algorithms.

This research deals with editorial design based on user experience design. The traditional editorial design has had to adapt to the new digital media composition, where multimedia audiovisual elements unthinkable a few years ago need to be integrated. The participation of the reader, as an external observer who only receives information through texts and images, now has new scenarios in which he can actively participate and decide what will come to his hands. In this study, a work methodology based on UxD User Experience Design is presented, in which will generate the editorial design of an educational book on environmental issues, which includes augmented reality for children from 6 to 8 years of age. The aim of this study is to know if an editorial product with augmented reality and developed from the user experience design can improve meaningful learning in a playful and active way. For its development, a composition model based on the Fibonacci sequence and the golden ratio will be used. Additionally, its graphic composition will be guided by the Massimo Vignelli canon and will be complemented by the reticular model of Beth Tondreau. The augmented reality markers position will also be based on the composition model previously mentioned, which will allow keeping the attention of the reader in the printed document and in the augmented reality animations. The user experience design will be applied with teachers, parents and students from 4 schools in Quito and Ambato. Once the production is completed, the impact on teaching-learning process will be evaluated with a control and a test group, and the methodology with which they will work in the classroom with the educational material developed will be defined. At the end of the study, copies of the book will be delivered to the participating schools of this research for its implementation.

Education worldwide is a significant aspect for the development of the peoples and much more in developing countries such as those in Latin America, where less than 22% of its inhabitants have higher education. Research in this field is a matter of interest for each of the governments to improve education policies. Therefore, the analysis of data on the behavior of a student in an educational institution is of utmost importance, because multiple aspects of progress or student dropout rates during their professional training period can be identified. The most important variables to identify the student’s behavior are the socio-economic ones, since the psychological state and the economic deficiencies that the student faces while is studying can be detected. This data provides grades, scholarships, attendance and information on student progress. During the first phase of the study, all the information is analyzed and it is determined which provides relevant data to develop a profile of a student behavior, as well as the pre-processing of the data obtained. In this phase, voracious algorithms are applied for the selection of attributes, such as greedy stepwise, Chi-squared test, Anova, RefiefF, Gain Radio, among others. In this work, we apply the artificial intelligence techniques, the results obtained are compared to generate a normal and unusual behavior of each student according to their professional career. In addition, the most optimal model that has had a higher accuracy percentage, false positive rate, false negative rate and mean squared error in the tests results are determined.