Search results for: Jorge Aria de la Torre

Authors: Juan Carlos Montalvo-Rodriguez, Juan Felipe Espinosa-Cristia, Pablo Islas Madariaga, Jorge Cifuentes Valenzuela

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This article presents different relationships between top management and innovative companies, based on the developments of creativity and innovation management. First of all, it contextualizes the innovative company in relation to management, creativity, and innovation. Secondly, it delves into the vision of top management of innovative companies, from the perspectives of the management of creativity and innovation. Thirdly, their commonalities are highlighted, bearing in mind the importance that both approaches attribute to aspects such as leadership, networks, strategy, culture, technology, environment, and complexity in the top management of innovative companies. Based on the above, an integration of both fields of study is proposed, as an alternative to deepen the relationship between senior management and the innovative company.

Keywords: top management, creativity, innovation, innovative firm, leadership, strategy

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Authors: Ocotlán Díaz-Parra, Jorge A. Ruiz-Vanoye, Alejandro Fuentes-Penna, Beatriz Bernabe-Loranca, Patricia Ambrocio-Cruz, José J. Hernández-Flores

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The Maritime Platform Transport Problem of Solid, Special and Dangerous Waste consist of to minimize the monetary value of carry different types of waste from one location to another location using ships. We offer a novel mathematical, the characterization of the problem and the use CPLEX to find the optimal values to solve the Solid, Special and Hazardous Waste Transportation Problem of offshore platforms instances of Mexican state-owned petroleum company (PEMEX). The set of instances used are WTPLib real instances and the tool CPLEX solver to solve the MPTPSSDW problem.

Keywords: oil platform, transport problem, waste, solid waste

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Authors: L. Cruz-Lopes, M. Sell, P. Escudeiro, B. Esteves

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It might be difficult for deaf people to communicate since spoken and written languages are different from sign language. When it comes to getting information, going to places of cultural heritage, or using services and infrastructure, there is a clear lack of inclusiveness. By creating assistive technology that enables deaf individuals to get around communication hurdles and encourage inclusive tourism, the ICHT- Inclusive Cultural Heritage Tourism initiative hopes to increase knowledge of sign language. The purpose of the Inclusive Cultural Heritage Tourism (ICHT) project is to develop online and on-site sign language tools and material for usage at popular tourist destinations in the northern region of Portugal, including Torre dos Clérigos, the Lello bookstore, Maia Zoo, Porto wine cellars, and São Pedro do Sul (Viseu) thermae. The ICHT system consists of an application using holography, a mobile game, an online platform for collaboration with deaf and hearing users, and a collection of International Sign training courses. The project also offers a prospect for a more inclusive society by introducing a method of teaching sign languages to tourism industry professionals. As a result, the teaching and learning of sign language along with the assistive technology tools created by the project sets up an inclusive environment for the deaf community, producing results in the area of automatic sign language translation and aiding in the global recognition of the Portuguese tourism industry.

Keywords: inclusive tourism, games, international sign training, deaf community

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Authors: Jorge Fernandes Teixeira Filho, André Oliveira Alcantara Fontenele, Érick Aragão Ribeiro

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The constant emergence of new technologies used in automated processes makes it necessary for teachers and traders to apply new technologies in their classes. This paper presents an application of a new technology that will be employed in a didactic plant, which represents an effluent treatment process located in a laboratory of a federal educational institution. At work were studied in the first place, all components to be placed on automation laboratory in order to determine ways to program, parameterize and organize the plant. New technologies that have been implemented to the process are basically an AS-i network and a Profinet network, a SCADA system, which represented a major innovation in the laboratory. The project makes it possible to carry out in the laboratory various practices of industrial networks and SCADA systems.

Keywords: automation, industrial networks, SCADA systems, lab automation

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Authors: Fiúza A., Góis J. Leite M., Braga H., Lima A., Jorge P., Moutela P., Martins L., Futuro A.

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Lepidolite is an important lithium mineral that, to the author’s best knowledge, has not been used to produce lithium hydroxide, necessary for energy conversion to electric vehicles. Alkaline leaching of lithium concentrates allows the establishment of a production diagram avoiding most of the environmental drawbacks that are associated with the usage of acid reagents. The tested processes involve a pretreatment by digestion at high temperatures with additives, followed by leaching at hot atmospheric pressure. The solutions obtained must be compatible with solutions from the leaching of spodumene concentrates, allowing the development of a common treatment diagram, an important accomplishment for the feasible exploitation of Portuguese resources. Statistical programming and interpretation techniques are used to minimize the laboratory effort required by conventional approaches and also allow phenomenological comprehension.

Keywords: artificial intelligence, tailings free process, ferroelectric electrolyte battery, life cycle assessment

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Authors: Gabriel Chavira, Jorge Orozco, Salvador Nava, Eduardo Álvarez, Julio Rolón, Roberto Pichardo

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Ambient Intelligence promotes a shift in computing which involves fitting-out the environments with devices to support context-aware applications. One of main objectives is the reduction to a minimum of the user’s interactive effort, the diversity and quantity of devices with which people are surrounded with, in existing environments; increase the level of difficulty to achieve this goal. The mobile phones and their amazing global penetration, makes it an excellent device for delivering new services to the user, without requiring a learning effort. The environment will have to be able to perceive all of the interaction techniques. In this paper, we present the PICTAC model (Perceiving touch Interaction through TAgging Context), which similarly delivers service to members of a research group.

Keywords: ambient intelligence, tagging context, touch interaction, touching services

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Authors: Angeliki Peponi, Paulo Morgado, Jorge Trindade

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Artificial Neural Networks (ANNs) and Geographic Information Systems (GIS) are applied as a robust tool for modeling and forecasting the erosion changes in Costa Caparica, Lisbon, Portugal, for 2021. ANNs present noteworthy advantages compared with other methods used for prediction and decision making in urban coastal areas. Multilayer perceptron type of ANNs was used. Sensitivity analysis was conducted on natural and social forces and dynamic relations in the dune-beach system of the study area. Variations in network’s parameters were performed in order to select the optimum topology of the network. The developed methodology appears fitted to reality; however further steps would make it better suited.

Keywords: artificial neural networks, backpropagation, coastal urban zones, erosion prediction

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Authors: Vanessa Funk, Steven Blum, Stephanie Cole, Jorge Maciel, Matthew Lux

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Paper-based synthetic gene circuits offer a new paradigm for programmable, fieldable biodetection. We demonstrate that by freeze-drying gene circuits with in vitro expression machinery, we can use complimentary RNA sequences to trigger colorimetric changes upon rehydration. We have successfully utilized both green fluorescent protein and luciferase-based reporters for easy visualization purposes in solution. Through several efforts, we are aiming to use this new platform technology to address a variety of needs in portable detection by demonstrating several more expression and reporter systems for detection functions on paper. In addition to RNA-based biodetection, we are exploring the use of various mechanisms that cells use to respond to environmental conditions to move towards all-hazards detection. Examples include explosives, heavy metals for water quality, and toxic chemicals.

Keywords: cell-free lysates, detection, gene circuits, in vitro

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Authors: Jorge Maestre Vidal, Ana Lucila Sandoval Orozco, Luis Javier García Villalba

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With the increase in popularity of mobile devices, new and varied forms of malware have emerged. Consequently, the organizations for cyberdefense have echoed the need to deploy more effective defensive schemes adapted to the challenges posed by these recent monitoring environments. In order to contribute to their development, this paper presents a malware detection strategy for mobile devices based on sequence alignment algorithms. Unlike the previous proposals, only the system calls performed during the startup of applications are studied. In this way, it is possible to efficiently study in depth, the sequences of system calls executed by the applications just downloaded from app stores, and initialize them in a secure and isolated environment. As demonstrated in the performed experimentation, most of the analyzed malicious activities were successfully identified in their boot processes.

Keywords: android, information security, intrusion detection systems, malware, mobile devices

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Authors: Margarita Zavala, Gabriel Chavira, José González, Jorge Orozco, Julio Rolón, Roberto Pichardo

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Adolescence is a neuralgic stage in the formation of every human being, generally this stage is when the middle school level is studied. In 2006, Mexico incorporated 'mentoring' space to assist students in their integration and participation in life. In public middle schools, it is sometimes difficult to be aware of situations that affect students because of the number of them and traditional records management. With this, they lose the opportunity to provide timely support as a preventive way. In order to provide this support, it is required to know the students by detecting the relevant information that has greater impact on their learning process. This research is looking to check if it is possible to identify student’s relevant information to detect when it is at risk, and then to propose a model to manage in a proper way such information.

Keywords: adolescence, mentoring, middle school students, mentoring system support

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Authors: Jorge Olivares, Fernando Maass, Pablo Martin

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Fractional derivatives have been considered recently as a way to solve different problems in Engineering. In this way, second kind modified Bessel functions are considered here. The order α fractional differential equations of second kind Bessel functions, Kᵥ(x), are studied with simple initial conditions. The Laplace transform and Caputo definition of fractional derivatives are considered. Solutions have been found for ν=1/3, 1/2, 2/3, -1/3, -1/2 and (-2/3). In these cases, the solutions are the sum of two hypergeometric functions. The α fractional derivatives have been for α=1/3, 1/2 and 2/3, and the above values of ν. No convergence has been found for the integer values of ν Furthermore when α has been considered as a rational found m/p, no general solution has been found. Clearly, this case is more difficult to treat than those of first kind Bessel Function.

Keywords: Caputo, modified Bessel functions, hypergeometric, linear fractional differential equations, transform Laplace

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Authors: Carlos Roncero-Parra, Alfonso Parreño-Torres, Jorge Mateo Sotos, Alejandro L. Borja

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In this research, different methods based on machine/deep learning algorithms are presented for the classification and diagnosis of patients with mental disorders such as alzheimer. For this purpose, the signals obtained from 32 unipolar electrodes identified by non-invasive EEG were examined, and their basic properties were obtained. More specifically, different well-known machine learning based classifiers have been used, i.e., support vector machine (SVM), Bayesian linear discriminant analysis (BLDA), decision tree (DT), Gaussian Naïve Bayes (GNB), K-nearest neighbor (KNN) and Convolutional Neural Network (CNN). A total of 668 patients from five different hospitals have been studied in the period from 2011 to 2021. The best accuracy is obtained was around 93 % in both ADM and ADA classifications. It can be concluded that such a classification will enable the training of algorithms that can be used to identify and classify different mental disorders with high accuracy.

Keywords: alzheimer, machine learning, deep learning, EEG

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Authors: Margarita Zavala, Julio Rolón, Gabriel Chavira, José González, Jorge Orozco, Roberto Pichardo

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Adolescence is a neuralgic stage in the formation of every human being, generally at this stage is when the middle school level is studied. In 2006 in Mexico incorporated “mentoring" space to assist students in their integration and participation in life. In public middle schools, is sometimes difficult to be aware of situations that affect students because of the number of them and traditional records management. Whit this they lose the opportunity to provide timely support as a preventive way. In order to provide this support, it is required to know the students by detecting the relevant information that has greater impact on their learning process. This research is looking to check if it is possible to identify student’s relevant information to detect when it is at risk, and then to propose a model to manage in a proper way such information.

Keywords: adolescence, mentoring, middle school students, mentoring system support

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Authors: Diego Saqui, José H. Saito, José R. Campos, Lúcio A. de C. Jorge

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Hyperspectral images and remote sensing are important for many applications. A problem in the use of these images is the high volume of data to be processed, stored and transferred. Dimensionality reduction techniques can be used to reduce the volume of data. In this paper, an approach to band selection based on clustering algorithms is presented. This approach allows to reduce the volume of data. The proposed structure is based on Fuzzy C-Means (or K-Means) and NWHFC algorithms. New attributes in relation to other studies in the literature, such as kurtosis and low correlation, are also considered. A comparison of the results of the approach using the Fuzzy C-Means and K-Means with different attributes is performed. The use of both algorithms show similar good results but, particularly when used attributes variance and kurtosis in the clustering process, however applicable in hyperspectral images.

Keywords: band selection, fuzzy c-means, k-means, hyperspectral image

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Authors: Luis A. Anchordoqui, Jorge F. Soriano, Diego F. Torres

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Auger data show evidence for a correlation between ultrahigh-energy cosmic rays (UHECRs) and nearby starburst galaxies. This intriguing correlation is consistent with data collected by the Telescope Array, which have revealed a much more pronounced directional 'hot spot' in arrival directions not far from the starburst galaxy M82. In this work, we assume starbursts are sources of UHECRs, and we investigate the prospects to use the observed distribution of UHECR arrival directions to constrain galactic magnetic field models. We show that if the Telescope Array hot spot indeed originates on M82, UHECR data would place a strong constraint on the turbulent component of the galactic magnetic field.

Keywords: galactic magnetic field, Pierre Auger observatory, telescope array, ultra-high energy cosmic rays

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Authors: Anésio de Leles Ferreira Filho, Wesley Rodrigues de Oliveira, Jéssica Santoro Gonçalves, Jorge Andrés Cormane Angarita

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The increase in electric power demand in face of environmental issues has intensified the participation of renewable energy sources such as photovoltaics, in the energy matrix of various countries. Due to their operational characteristics, they can generate time-varying harmonic and inter-harmonic distortions. For this reason, the application of methods of measurement based on traditional Fourier analysis, as proposed by IEC 61000-4-7, can provide inaccurate results. Considering the aspects mentioned herein, came the idea of the development of this work which aims to present the results of a comparative evaluation between a methodology arising from the combination of the Prony method with the Kalman filter and another method based on the IEC 61000-4-30 and IEC 61000-4-7 standards. Employed in this study were synthetic signals and data acquired through measurements in a 50kWp photovoltaic installation.

Keywords: harmonics, inter-harmonics, iec61000-4-7, parametric estimators, photovoltaic generation

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Authors: Jorge A. Ruiz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, Daniel Vélez-Díaz, Edith Olaco García

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In this paper, we present the use of the discriminant analysis to select evolutionary algorithms that better solve instances of the vehicle routing problem with time windows. We use indicators as independent variables to obtain the classification criteria, and the best algorithm from the generic genetic algorithm (GA), random search (RS), steady-state genetic algorithm (SSGA), and sexual genetic algorithm (SXGA) as the dependent variable for the classification. The discriminant classification was trained with classic instances of the vehicle routing problem with time windows obtained from the Solomon benchmark. We obtained a classification of the discriminant analysis of 66.7%.

Keywords: Intelligent Transportation Systems, data-mining techniques, evolutionary algorithms, discriminant analysis, machine learning

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Authors: Javier De La Torre Costa, Belen Rubio Ballester, Martina Maier, Paul F. M. J. Verschure

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After a stroke, a great number of patients experience persistent motor impairments such as hemiparesis or weakness in one entire side of the body. As a result, the lack of use of the paretic limb might be one of the main contributors to functional loss after clinical discharge. We aim to reverse this cycle by promoting the use of the paretic limb during activities of daily living (ADLs). To do so, we describe the key components of a system that is composed of a wearable bracelet (i.e., a smartwatch) and a mobile phone, designed to bring a set of neurorehabilitation principles that promote acquisition, retention and generalization of skills to the home of the patient. A fundamental question is whether the loss in motor function derived from learned–non–use may emerge as a consequence of decision–making processes for motor optimization. Our system is based on well-established rehabilitation strategies that aim to reverse this behaviour by increasing the reward associated with action execution as well as implicitly reducing the expected cost associated with the use of the paretic limb, following the notion of the reinforcement–induced movement therapy (RIMT). Here we validate an accelerometer–based measure of arm use, and its capacity to discriminate different activities that require increasing movement of the arm. We also show how the system can act as a personalized assistant by providing specific goals and adjusting them depending on the performance of the patients. The usability and acceptance of the device as a rehabilitation tool is tested using a battery of self–reported and objective measurements obtained from acute/subacute patients and healthy controls. We believe that an extension of these technologies will allow for the deployment of unsupervised rehabilitation paradigms during and beyond the hospitalization time.

Keywords: stroke, wearables, learned non use, hemiparesis, ADLs

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Authors: José Eugenio Ortiz, Pierre Plaza, Josefa Herrero, Iván Cabria, José Luis Blanco, Javier Gavilanes, José Ignacio Escavy, Ignacio López-Cilla, Virginia Yagüe, César Pérez, Silvia Rodríguez, Jorge Rico, Cecilia Serrano, Jesús Bernat

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The development of Artificial Intelligence services in mining processes, specifically in aggregate quarries, is facilitating automation and improving numerous aspects of operations. Ultimately, AI is transforming the mining industry by improving efficiency, safety and sustainability. With the ability to analyze large amounts of data and make autonomous decisions, AI offers great opportunities to optimize mining operations and maximize the economic and social benefits of this vital industry. Within the framework of the European DIGIECOQUARRY project, various services were developed for the identification of material quality, production estimation, detection of anomalies and prediction of consumption and production automatically with good results.

Keywords: aggregates, artificial intelligence, automatization, mining operations

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Authors: Aria Teimourzadeh, Marc Favier, Samaneh Kakavand

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The emergence of social networks has revolutionized the exchange of information. Every behavior on these platforms contributes to the generation of data known as social network data that are processed, stored and published by the social network service providers. Hence, it is vital to investigate the role of these platforms in user data by considering the privacy measures, especially when we observe the increased number of individuals and organizations engaging with the current virtual platforms without being aware that the data related to their positioning, connections and behavior is uncovered and used by third parties. Performing analytics on social network datasets may result in the disclosure of confidential information about the individuals or organizations which are the members of these virtual environments. Analyzing separate datasets can reveal private information about relationships, interests and more, especially when the datasets are analyzed jointly. Intentional breaches of privacy is the result of such analysis. Addressing these privacy concerns requires an understanding of the nature of data being accumulated and relevant data privacy regulations, as well as motivations for disclosure of personal information on social network platforms. Some significant points about how user's online information is controlled by the influence of social factors and to what extent the users are concerned about future use of their personal information by the organizations, are highlighted in this paper. Firstly, this research presents a short literature review about the structure of a network and concept of privacy in Online Social Networks. Secondly, the factors of user behavior related to privacy protection and self-disclosure on these virtual communities are presented. In other words, we seek to demonstrates the impact of identified variables on user information disclosure that could be taken into account to explain the privacy preservation of individuals on social networking platforms. Thirdly, a few research directions are discussed to address this topic for new researchers.

Keywords: information disclosure, privacy measures, privacy preservation, social network analysis, user experience

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Authors: Eric Muñoz de la Torre, Julián González Trinidad, Efrén González Ramírez

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Rain varies greatly in its duration, intensity, and spatial coverage, it is important to have sub-daily rainfall data for various applications, including risk prevention. However, the ground measurements are limited by the low and irregular density of rain gauges. An alternative to this problem are the Satellite Precipitation Products (SPPs) that use passive microwave and infrared sensors to estimate rainfall, as IMERG, however, these SPPs have to be validated before their application. The aim of this study is to evaluate the performance of the IMERG: Integrated Multi-satellitE Retrievals for Global Precipitation Measurament final run V06B SPP in a semi-arid region of Mexico, using 4 automatic rain gauges (pluviographs) sub-daily data of October 2019 and June to September 2021, using the Minimum inter-event Time (MIT) criterion to separate unique rain events with a dry period of 10 hrs. for the purpose of evaluating the rainfall properties (depth, duration and intensity). Point to pixel analysis, continuous, categorical, and volumetric statistical metrics were used. Results show that IMERG is capable to estimate the rainfall depth with a slight overestimation but is unable to identify the real duration and intensity of the rain events, showing large overestimations and underestimations, respectively. The study zone presented 80 to 85 % of convective rain events, the rest were stratiform rain events, classified by the depth magnitude variation of IMERG pixels and pluviographs. IMERG showed poorer performance at detecting the first ones but had a good performance at estimating stratiform rain events that are originated by Cold Fronts.

Keywords: IMERG, rainfall, rain gauge, remote sensing, statistical evaluation

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Authors: Abosede Priscilla Ipadeola

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The quest for egalitarian justice requires a suitable theoretical foundation that can address the problem of marginalization and subjugation arising from various forms of oppression, such as sexism, racism, classism, and others. Many thinkers and societies have appealed to contractarianism, a theory that has been widely regarded as a doctrine of egalitarianism by some political theorists for about five centuries. Despite its numerous criticisms, the social contract still enjoys a prominent status as a key theory for egalitarian justice. However, Pateman and Mills have contended that the contractarian approach legitimizes gender and racial inequalities by excluding and marginalizing women and people of color from the original agreement. Therefore, the social contract is incapable of generating or fostering equality. This study proposes postcontractarianism, which is a viable alternative to the social contract. Postcontractarianism argues that the basis for egalitarianism cannot be grounded on agreement but rather on understanding. Postcontractarianism draws on Jorge Nef’s idea of mutual vulnerability and Obiri (an African theory of cosmology) to argue for the imperative of social equality.

Keywords: postcontractarianism, obiri, mutual vulnerability, egalitarianism, the social contract

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Authors: Fátima Gonçalves, Joaquim Brigas, Jorge Gonçalves

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As a way of managing the increasing volume and complexity of information that circulates in the present time, graphical representations are increasingly used, which add meaning to the information presented in communication media, through an efficient communication design. The visual culture itself, driven by technological evolution, has been redefining the forms of communication, so that contemporary visual communication represents a major impact on society. This article presents the results and respective comparative analysis of four publications in the Iberian press, focusing on the formal aspects of newspapers and the space they dedicate to the various communication elements. Two Portuguese newspapers and two Spanish newspapers were selected for this purpose. The findings indicated that the newspapers show a similarity in the use of graphic solutions, which corroborate a visual trend in communication design. The results also reveal that Spanish newspapers are more meticulous with graphic consistency. This study intended to contribute to improving knowledge of the Iberian generalist press.

Keywords: communication design, graphic resources, Iberian press, visual journalism

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Authors: Leidy M. Aldana, Jorge E. Camargo

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Adversarial Machine Learning has gained importance in recent years as Cybersecurity has gained too, especially malware, it has affected different entities and people in recent years. This paper shows a literature review about defense methods created to prevent adversarial machine learning attacks, firstable it shows an introduction about the context and the description of some terms, in the results section some of the attacks are described, focusing on detecting adversarial examples before coming to the machine learning algorithm and showing other categories that exist in defense. A method with five steps is proposed in the method section in order to define a way to make the literature review; in addition, this paper summarizes the contributions in this research field in the last seven years to identify research directions in this area. About the findings, the category with least quantity of challenges in defense is the Detection of adversarial examples being this one a viable research route with the adaptive approach in attack and defense.

Keywords: Malware, adversarial, machine learning, defense, attack

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Authors: Jorge Eliseo Muñiz-Gutierrez, Daniel Olvera-García, Cristina Sotelo-Salas

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The objective of this research is to allow the understanding of the hybridization process shown in culture through the architecture of mass production for the purpose of consumption, taking as a case study the mass-built housing of the city of Mexicali, Mexico. The methodology is born from the hermeneutical study of the meta-modified architectural object, which guided the research with a qualitative focus to be carried out in two stages, the first is based on the literature review regarding cultural hybridization, and the second stage is carried out in through an ethnographic study of the cultural exploration of the contextual landscape produced by the houses located in popular neighborhoods of the city of Mexicali, Mexico. The research shows that there is an unconscious hybridization process, the birth of a mixture of impositions guided by the popular and the personal aspirations of the inhabitant. The study presents the possibilities of a home and the relationship with its inhabitant and, in turn, its effects on the context and its contribution to culture through hybridization.

Keywords: hybridization, architectural landscape, architecture, mass housing

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Authors: Jorge Ferrada Herrera, Pablo M. Millán-Millán

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The delimitation in the cities of heritage areas implicit in strong processes of transformation, both social and material. The study shows how two cities, seemingly different as Seville (Spain) and Valparaiso (Chile), share the same transformation process from its declaration as heritage cities. The metdología used in research has been on the one hand the analytic-criticism has shown us all processes and the level of involvement of these. On the other hand the direct observation methodology has allowed us to ratify all studied. Faced with these processes research shows social resources that people have developed to address each of them. The study concludes the need to strengthen the social and associative fabric in heritage areas as a resource to ensure the survival of heritage, not only material but also social and cultural. As examples, we have chosen Seville and Valparaiso: the gentrification of Seville prior to the universal exhibition of ‘92 –with pretty specific plans-- is paralleled by Valparaiso’s plan to revitalize its port and its protected (UNESCO) area. The whole of our theoretical discourse will be based thereupon.

Keywords: historical centers, tourism, heritage, social processes

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Authors: Cecília M. Antão, Paulo Jorge Nogueira

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Breast cancer (BC) is the first cause of cancer mortality among Portuguese women. This retrospective observational study aimed at identifying comorbidities associated with BC female patients admitted to Portuguese public hospitals (2010-2018), investigating the effect of comorbidities on BC mortality rate, and building a predictive model using logistic regression. Results showed that the BC mortality in Portugal decreased in this period and reached 4.37% in 2018. Adjusted odds ratio indicated that secondary malignant neoplasms of liver, of bone and bone marrow, congestive heart failure, and diabetes were associated with an increased chance of dying from breast cancer. Although the Lisbon district (the most populated area) accounted for the largest percentage of BC patients, the logistic regression model showed that, besides patient’s age, being resident in Bragança, Castelo Branco, or Porto districts was directly associated with an increase of the mortality rate.

Keywords: breast cancer, comorbidities, logistic regression, adjusted odds ratio

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Authors: Jorge M. Uribe

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We propose a methodology for setting the price of an insurance contract targeted to manage the risk associated with weather conditions that affect variable renewable energy generation. The methodology relies on conditional quantile regressions to estimate the weather risk of a solar panel. It is illustrated using real daily radiation and weather data for three cities in Spain (Valencia, Barcelona and Madrid) from February 2/2004 to January 22/2019. We also adapt the concepts of value at risk and expected short fall from finance to this context, to provide a complete panorama of what we label as weather risk. The methodology is easy to implement and can be used by insurance companies to price a contract with the aforementioned characteristics when data about similar projects and accurate cash flow projections are lacking. Our methodology assigns a higher price to an insurance product with the stated characteristics in Madrid, compared to Valencia and Barcelona. This is consistent with Madrid showing the largest interquartile range of operational deficits and it is unrelated to the average value deficit, which illustrates the importance of our proposal.

Keywords: insurance, weather, vre, risk

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Authors: Shehret Tilvaldyev, Jorge Flores-Garay, Alfredo Villanueva, Erwin Martinez, Lazaro Rico

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The efficiency of modern transportation is severely compromised by the prevalence of turbulent drag. The high level of turbulent skin-friction occurring, e.g., on the surface of an aircraft, automobiles or the carriage of a high-speed train, is responsible for excess fuel consumption and increased carbon emissions. The environmental, political, and economic pressure to improve fuel efficiency and reduce carbon emissions associated with transportation means that reducing turbulent skin-friction drag is a pressing engineering problem. The dynamic pressure of subsonic airflow around solid objects creates lift, but also induces drag force. This paper is presenting the results of laboratory experiments, investigating appearance and magnitude of dynamic pressure in micro scale of subsonic air flow around right cylinder and symmetrical airfoil.

Keywords: airflow, dynamic pressure, micro scale, symmetric object

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Authors: Genaro Bolívar, Manuel Mas, Maria Tortolero, Jorge Salazar

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Due to the extensive use of water injection for oil displacement and pressure maintenance in oil fields, many reservoirs experience the problem of scale deposition when injection water starts to break through. In most cases the scaled-up wells are caused by the formation of sulfate and carbonate scales of calcium and strontium. Due to their relative hardness and low solubility, there are limited processes available for their removal and preventive measures such as the “squeeze” inhibitor treatment have to be taken. It is, therefore, important to gain a proper understanding of the kinetics of scale formation and its detrimental effects on formation damage under both inhibited and uninhibited conditions. Recently, the production of chitosan was started in our country and in the PDVSA-Intevep laboratories was synthesized and evaluated the properties of carboxymethyl chitosan (CMQ) as chelating agent of Ca2 + ions in water injection. In this regard, the characterization of the biopolymer by 13C - NMR, FTIR, TGA, and TM0374-2007 standard laboratory test has demonstrated the ability to remove up to 70% calcium ions in solution and shows a behavior that approaches that of commercial products.

Keywords: carboxymethyl chitosan, scale, calcium carbonate scale deposition, water injection

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