ItemDance Syntax and Possibility: Moving Beyond Structural Analysis(Akjournals, 2023) Miranda Medina, Juan Felipe; Galarza Flores, Marisol Cristel; López Yánez, María GabrielaIn this work we contend that studying dance syntax systematically is essential to gain a deeper understanding of dance practices. The reason is that syntax has to do with an essential aspect of dance, music and action in general, namely possibility. To the best of our knowledge, the efforts towards a systematic method to study dance syntax are scarce. Therefore, this work proposes the method of Finite-State Automata, borrowed from computer science, and presents three case studies of progressive complexity were the method is applied: (1) learning the basics of salsa, (2) diachronically comparing hip-pushing action in Afro-Ecuadorian Bomba del Chota, and (3) characterizing improvisation in Afro-Peruvian zapateo. While the first case is didactic and introduces the method progressively, the second and third cases are based on several years of fieldwork conducted by the authors with the Afro-Ecuadorian and Afro-Peruvian communities. The precondition for the application of the method we propose is structural analysis itself; that is, that the dance can be analyzed into small movement units that are combined progressively into more complex units. In regards to syntax, however, structural analysis is only the first step. The goal is a synthesis that brings forward the possibilities that arise from structural analysis; that is, the possibilities that are available to dancers and agents in a dance event. We trust that the approach to syntax this work presents will stimulate a renewed interest for researchers in dance, music and movement in general. ItemModeling and implementation of a 3 degrees of freedom delta robot through gestalt framework(Universidad Católica San Pablo, 2023) Condori Pacori, Luz Maria; Anchayhua Arestegui, Nilton CesarWe propose a design of a delta robot with 3 degrees of freedom to perform the pick and place trajectory through the Gestalt Framework. The robot was implemented through modeling, design and simulation stages. The Gestalt Framework allowed the control of the 3 arms to perform the desired trajec-tory. A displacement of 15 cm was generated between the origin and the end point, which coincides with the simulation performed. Finally, the purpose for which this robot was implemented is to improve the production of packaging. For this reason, the Gestalt Framework was used, as it allows the addition of the necessary functions for this type of process. ItemShallow window reduction for congestion control under TCP(IEEE, 2019) Quintanilla Carletto, Andrea Yvonne; Santisteban Pablo, Julio OmarCongestion control is one of the top problems in networking, and a key element for core networks to avoid congestion. The window size is used to pipelined packets on the network and is the means to manage the congestion in a network with an end-to-end approach. In the present work, we design a model for the reduction of the window in order to manage the congestion in a network. The reduction is shallow in-contrary to others approaches in which the reduction is drastic. The purpose of making the modification in the reduction algorithm of the window is to reduce the number of packets in the backbone network without affecting the end system. To do this, we test under NS2, modifying the TCP protocol code and proposing particular scenarios. ItemModular low-cost RF instrumentation to detect arsenic ions in water(IEEE, 2020) Quispe Huamani, Wilbert Jonathan; Zenteno Bolaños, EfrainEste artículo desarrolla un instrumento de bajo costo que utiliza una arquitectura similar a un receptor vectorial de un puerto destinado a estimar los iones de arsénico (As) diluidos en agua. El instrumento se implementa con componentes modulares listos para usar. Las mediciones se realizan con el prototipo diseñado conectado a un kit de evaluación dieléctrica 3.5 de Schmidt Partner Engineering AG y se comparan para diferentes niveles de arsénico disuelto en agua. Los resultados preliminares obtenidos son prometedores para continuar el estudio de esta instrumentación y allanan el camino para desarrollar más sensores e instrumentación para aplicaciones de monitoreo y detección de agua. ItemTowards an ontology for urban tourism(Association for Computing Machinery, 2021) Pinto De La Gala, Alexander; Cardinale, Yudith; Dongo, Irvin; Ticona-Herrera, Regina"Nowadays, diffusion and preservation of cultural heritage are being supported by technology on the Web. Thus, the online availability of urban tourism information, as part of cultural heritage, has been of enormous relevance to activate the tourism in many countries. The necessity of a well-defined and standard model for representing this knowledge is being managed by semantic web technologies, such as ontologies. However, current proposals represent partial knowledge of cultural heritage. In this context, this work proposes an ontology for indoor and outdoor environments of a city to represent the cultural heritage knowledge based on the UNESCO definitions. This ontology has a three-level architecture (Upper, Middle, and Lower ontologies) in accordance with a purpose of modularity and levels of specificity. To demonstrate the utility and suitability of our proposal, we have developed a parser to map and convert a museum repository (in CSV format) to RDF triples. With this case of study, we demonstrated that, by using our ontology, it is possible to represent the knowledge of urban tourism domains of a city. © 2021 Owner/Author" ItemApplication of social constraints for dynamic navigation considering semantic annotations on geo-referenced maps(IEEE Computer Society, 2021) Vilasboas, J.P.A.; Sampaio, M.S.C.A; Moreira, G.F.A.; Souza, A.B.A; DIaz-Amado, J.A.; Barrios-Aranibar, D.B.; Cardinale, Y.B.; Soares, J.E.A."With the robotics development, social robots interact with people, demanding they model the human being behavior to increase social navigation, considering proxemic spaces.However, human proxemic preferences can change in function of different social restrictions (e.g., culture, gender, local, the environment). Thus, robots should consider all these aspects to tailor their navigation. Towards an adaptable social navigation, in this article we develop the GProxemic Navigation system that allows identifying the robot localization in a geo-referenced map, with semantic annotations related to social restrictions, in function of which they chose the correct proxemic spaces they most respect in their autonomous navigation process. Results show that the GProxemic Navigation system efficiently obeys the proxemic space through the semantic annotations received. ©2021 IEEE" ItemA qualitative and quantitative comparison between Web scraping and API methods for Twitter credibility analysis(Emerald Group Holdings Ltd., 2021) Dongo, Irvin; Cardinale, Yudith; Aguilera, Ana; Martinez, Fabiola; Quintero, Yuni; Robayo, German; Cabeza, David"purpose: This paper aims to perform an exhaustive revision of relevant and recent related studies, which reveals that both extraction methods are currently used to analyze credibility on Twitter. Thus, there is clear evidence of the need of having different options to extract different data for this purpose. Nevertheless, none of these studies perform a comparative evaluation of both extraction techniques. Moreover, the authors extend a previous comparison, which uses a recent developed framework that offers both alternates of data extraction and implements a previously proposed credibility model, by adding a qualitative evaluation and a Twitter-Application Programming Interface (API) performance analysis from different locations. Design/methodology/approach: As one of the most popular social platforms, Twitter has been the focus of recent research aimed at analyzing the credibility of the shared information. To do so, several proposals use either Twitter API or Web scraping to extract the data to perform the analysis. Qualitative and quantitative evaluations are performed to discover the advantages and disadvantages of both extraction methods. Findings: The study demonstrates the differences in terms of accuracy and efficiency of both extraction methods and gives relevance to much more problems related to this area to pursue true transparency and legitimacy of information on the Web. Originality/value: Results report that some Twitter attributes cannot be retrieved by Web scraping. Both methods produce identical credibility values when a robust normalization process is applied to the text (i.e. tweet). Moreover, concerning the time performance, Web scraping is faster than Twitter API and it is more flexible in terms of obtaining data; however, Web scraping is very sensitive to website changes. Additionally, the response time of the Twitter API is proportional to the distance from the central server at San Francisco." ItemA Low-Cost IoT Platform for Heat Stress Monitoring in Dairy Cattle(Institute of Electrical and Electronics Engineers Inc., 2021) Choquehuanca-Zevallos, J.J.; Mayhua-Lopez, E.This paper presents a compact and modular system based on Internet-of- Things for monitoring cattle behavior and stress in real-time. It will help to model certain parameters such as temperature and certain weather variables such as relative humidity, solar radiation, among others thanks to Internet-of- Things (IoT) sensors localized in different points of barns and the fields for cattle farming. A main benefit of the system is that it is built with low-cost hardware and low battery consumption. The wireless system also allows the collection of data in real-time and obtains the temperature-humidity index. This index will give an approach to the heat stress in cattle not only on the farm but in the vicinity of the farm. Finally, the high amount of collected data will allow employing Big Data solutions for estimating the impact on milk productivity. In the future, more sensors will be deployed for a more detailed reading of weather variables and their impact on dairy cattle. © 2021 IEEE. ItemContext-aware and ontology-based recommender system for e-tourism(SciTePress, 2021) Castellanos, G.; Cardinale, Y.; Roose, P.Frequently, travelers try to collect information for planing a trip or when being at the destination. Usually, tourists depend on places’ reviews to make the choice, but this implies prior knowledge of the touristic places and explicit search for suggestions through interaction with applications (i.e., PULL paradigm). In contrast, a PUSH approach, in which the application proactively triggers a recommendation process according to users’ preferences and when necessary, seems to be a more reasonable solution. Recommender systems have become appropriate applications to help tourists in their trip planning. However, they still have limitations, such as poor consideration of users’ profiles and their contexts, their predictable suggestions, and the lack of a standard representation of the knowledge managed. We propose a user-centric recommender system architecture, that supports both PULL and PUSH approaches, assisted by an ontology-based spreading activation algorithm for context-aware recommendations, with a focus on decreasing predictable outputs and increasing serendipity, based on an aging-like approach. To demonstrate its suitability and performance, we develop a first prototype of the architecture and simulate different scenarios, varying users’ profiles, preferences, and context parameters. Results show that the ontology-based spreading activation and the proposed aging system provide relevant and varied recommendations according to users’ preferences, while considering their context and improving the serendipity of the system when comparing with a state-of-the-art work ItemA Methodological Approach to the Learning of Robotics with EDUROSC-Kids(Springer Science and Business Media B.V., 2021) Patiño-Escarcina, Raquel E.; Barrios-Aranibar, Dennis; Bernedo-Flores, Liz S;; Alsina, Pablo Javier; Gonçalves, Luiz M.G.With advances in science and technology, several innovative researches have been developed trying to figure out the main problems related to children’s learning. It is known that issues such as frustration and inattention, between others, affect student learning. In this fashion, robotics is an important resource that can be used towards helping to solve these issues, empowering our students in order to push their learning up. In this case, robotic tools are generally used considering two different paradigms: as the main focus and as a secondary focus. Actually, these paradigms define the way that Educational Robotics is implemented in schools. Most of the approaches have implemented it as the main focus, which is teaching Robotics. Nevertheless, there are quite a few works that implement robotics as a secondary focus, which is currently assisting the learning process in several disciplines. The main contribution of this work is a complete three steps methodology for Robotics in Education to guide projects in order to either use it alone or to teach robotics with others topics. Our experiments show the importance of devising a study plan and evaluation method because the process is iterative and could improve the final results. As a novelty, here we have joined and extended our previous works by proposing a new set of methods with guidelines and strategies for applying the educational robotics standard curriculum for kids, named EDUROSC-Kids. We propose several tools that have been developed to organize the learning topics of Robotics for children, including the desired outcomes during the learning process. As said our current approach is divided in three steps (or phases): setting up the environment, defining the project, and performing evaluation. The proposed curriculum organizes robotics contents into five disciplines: Robotics and Society, Mechanics, Electronics, Programming, and Control Theory. Also, it considers a set of topics for each discipline and defines the level of knowledge that is recommended to achieve each group of children based on Bloom’s Nomenclature. The contribution on this paper is a crucial step towards linking the general learning process with Educational Robotics approaches. Our methodology is validated by presenting practical experiences with application of EDUROSC-kids and the proposed method with a rubric guidelines into groups of children. ItemSafe path planning algorithms for mobile robots based on probabilistic foam(MDPI AG, 2021) Nascimento, L.B.P.; Barrios-Aranibar, D.; Santos, V.G.; Ribeiro, W.C.; Alsina, P.J.The planning of safe paths is an important issue for autonomous robot systems. The Probabilistic Foam method (PFM) is a planner that guarantees safe paths bounded by a sequence of structures called bubbles that provides safe regions. This method performs the planning by cov-ering the free configuration space with bubbles, an approach analogous to a breadth-first search. To improve the propagation process and keep the safety, we present three algorithms based on Probabilistic Foam: Goal-biased Probabilistic Foam (GBPF), Radius-biased Probabilistic Foam (RBPF), and Heuristic-guided Probabilistic Foam (HPF); the last two are proposed in this work. The variant GBPF is fast, HPF finds short paths, and RBPF finds high-clearance paths. Some simulations were performed using four different maps to analyze the behavior and performance of the methods. Besides, the safety was analyzed considering the new propagation strategies. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. ItemT-CrEO: A twitter credibility analysis frameworkT-CrEO: A twitter credibility analysis framework(Institute of Electrical and Electronics Engineers Inc., 2021) Cardinale, Yudith; Dongo, Irvin; Robayo, Germán; Cabeza, David; Medina, Sergio; Aguilera, Ana"Social media and other platforms on Internet are commonly used to communicate and generate information. In many cases, this information is not validated, which makes it difficult to use and analyze. Although there exist studies focused on information validation, most of them are limited to specific scenarios. Thus, a more general and flexible architecture is needed, that can be adapted to user/developer requirements and be independent of the social media platform. We propose a framework to automatically and in real-time perform credibility analysis of posts on social media, based on three levels of credibility: Text, User, and Social. The general architecture of our framework is composed of a front-end, a light client proposed as a web plug-in for any browser; a back-end that implements the logic of the credibility model; and a third-party services module. We develop a first version of the proposed system, called T-CREo (Twitter CREdibility analysis framework) and evaluate its performance and scalability. In summary, the main contributions of this work are: the general framework design; a credibility model adaptable to various social networks, integrated into the framework; and T-CREo as a proof of concept that demonstrates the framework applicability and allows evaluating its performance for unstructured information sources; results show that T-CREo qualifies as a highly scalable real-time service. The future work includes the improvement of T-CREo implementation, to provide a robust architecture for the development of third-party applications, as well as the extension of the credibility model for considering bots detection, semantic analysis and multimedia analysis" ItemApplication of a methodological approach to compare ontologies(Emerald Group Holdings Ltd., 2021) Cardinale, Yudith; Cornejo-Lupa, Maria Alejandra; Pinto-De la Gala, Alexander; Ticona-Herrera, Regina"Purpose: This study aims to the OQuaRE quality model to the developed methodology. Design/methodology/approach: Ontologies are formal, well-defined and flexible representations of knowledge related to a specific domain. They provide the base to develop efficient and interoperable solutions. Hence, a proliferation of ontologies in many domains is unleashed. Then, it is necessary to define how to compare such ontologies to decide which one is the most suitable for the specific needs of users/developers. As the emerging development of ontologies, several studies have proposed criteria to evaluate them. Findings: In a previous study, the authors propose a methodological process to qualitatively and quantitatively compare ontologies at Lexical, Structural and Domain Knowledge levels, considering correctness and quality perspectives. As the evaluation methods of the proposal are based on a golden-standard, it can be customized to compare ontologies in any domain. Practical implications: To show the suitability of the proposal, the authors apply the methodological approach to conduct comparative studies of ontologies in two different domains, one in the robotic area, in particular for the simultaneous localization and mapping (SLAM) problem; and the other one, in the cultural heritage domain. With these cases of study, the authors demonstrate that with this methodological comparative process, we are able to identify the strengths and weaknesses of ontologies, as well as the gaps still needed to fill in the target domains. Originality/value: Using these metrics and the quality model from OQuaRE, the authors are incorporating a standard of software engineering at the quality validation into the Semantic Web. " ItemCompact Dual and Wide Band Monopole-like Antenna Based on SRR for WLAN Applications(Institute of Electrical and Electronics Engineers Inc., 2021) Santos-Valdivia, N.; Castillo-Aranibar, P.; Lamperez, A.G.; Segovia-Vargas, D.In this paper, a dual band antenna based on Split Ring Resonators (SRR) with unequal rings fed through a coplanar waveguide transmission line is proposed. The design method ensures the control of the resonance frequencies and their respective bandwidths. The geometry of the dual band antenna is composed of two SRRs electromagnetically coupled which have monopole radiation characteristics. The results demonstrate that the proposed antenna has two relative bandwidths with gain over 2 dB and an omnidirectional radiation pattern over the first frequency band. ItemAn approach of social navigation based on proxemics for crowded environments of humans and robots(MDPI AG, 2021) Daza, Marcos; Barrios-Aranibar, Dennis; Diaz-Amado, José; Cardinale, Yudith; Vilasboas, João"Nowadays, mobile robots are playing an important role in different areas of science, industry, academia and even in everyday life. In this sense, their abilities and behaviours become increasingly complex. In particular, in indoor environments, such as hospitals, schools, banks and museums, where the robot coincides with people and other robots, its movement and navigation must be programmed and adapted to robot-robot and human-robot interactions. However, existing approaches are focused either on multi-robot navigation (robot-robot interaction) or social navigation with human presence (human-robot interaction), neglecting the integration of both approaches. Proxemic interaction is recently being used in this domain of research, to improve Human-Robot Interaction (HRI). In this context, we propose an autonomous navigation approach for mobile robots in indoor environments, based on the principles of proxemic theory, integrated with classical navigation algorithms, such as ORCA, Social Momentum, and A*. With this novel approach, the mobile robot adapts its behaviour, by analysing the proximity of people to each other, with respect to it, and with respect to other robots to decide and plan its respective navigation, while showing acceptable social behaviours in presence of humans. We describe our proposed approach and show how proxemics and the classical navigation algorithms are combined to provide an effective navigation, while respecting social human distances. To show the suitability of our approach, we simulate several situations of coexistence of robots and humans, demonstrating an effective social navigation." ItemEmotion detection for social robots based on nlp transformers and an emotion ontology(MDPI AG, 2021) Graterol, Wilfredo; Diaz-Amado, Jose; Cardinale, Yudith; Dongo, Irvin; Lopes-Silva, Edmundo; Santos-Libarino, CleiaFor social robots, knowledge regarding human emotional states is an essential part of adapting their behavior or associating emotions to other entities. Robots gather the information from which emotion detection is processed via different media, such as text, speech, images, or videos. The multimedia content is then properly processed to recognize emotions/sentiments, for example, by analyzing faces and postures in images/videos based on machine learning techniques or by converting speech into text to perform emotion detection with natural language processing (NLP) techniques. Keeping this information in semantic repositories offers a wide range of possibilities for implementing smart applications. We propose a framework to allow social robots to detect emotions and to store this information in a semantic repository, based on EMONTO (an EMotion ONTOlogy), and in the first figure or table caption. Please define if appropriate. an ontology to represent emotions. As a proof-of-concept, we develop a first version of this framework focused on emotion detection in text, which can be obtained directly as text or by converting speech to text. We tested the implementation with a case study of tour-guide robots for museums that rely on a speech-to-text converter based on the Google Application Programming Interface (API) and a Python library, a neural network to label the emotions in texts based on NLP transformers, and EMONTO integrated with an ontology for museums; thus, it is possible to register the emotions that artworks produce in visitors. We evaluate the classification model, obtaining equivalent results compared with a state-of-the-art transformer-based model and with a clear roadmap for improvement. ItemAn approach to improve simultaneous localization and mapping in human populated environments(IEEE, 2021) Inofuente Colque, Kevin Adier; Barrios Aranibar, DennisOne task that autonomous mobile robots have to perform in indoor spaces is to construct the map of their environment and report their location and orientation. This process is called Simultaneous Localization and Mapping (SLAM). To do so, robots extract data through their sensors. However, in dynamic indoor environments, moving objects induce the SLAM process to collapse or diverge. Moving objects should not be taken into account to generate the map and the occlusions that they generate should be solved. In this work, we propose a robust and flexible approach for SLAM algorithms to perform better in human populated environments; by integrating a filtering scheme that manages moving and static objects. To illustrate the suitability of our approach, we implement Gmapping, as the classical SLAM algorithm, and RANSAC as the filter. Nevertheless, any other SLAM algorithm and filter can be implemented. The simulation tests have been carried out using three museum environments, which the robot can face in real life. Through the results obtained, it is possible to conclude that the proposed approach is efficient in managing the sensor data, filtering the outliers, and thus removing dynamic objects from the map. ItemImplementation of an energy harvesting system by piezoelectric elements exploiting the human footsteps(IEEE, 2017) Savina Quispe, Johnny Nelson; Cartagena Gordillo, AlexThe fundamental idea of this research work is to present an approach to energy harvesting, which basically uses piezoelectric technology and is implemented in a shoe. It takes advantage of the energy that the user waste when walks and thus is able to convert it into electric energy and can be use in an electronic device that requires low power. ItemA method based on rf spectral featuresfor evaluating the porosity degree in ceramic materials(IEEE, 2018) Sanchez Suarez, Rudy Marcelino; Choquehuanca Zevallos, Juan JoséIn this paper, a classification system of the degree of porosity of ceramic materials based on a Radio Frequency system is presented. The system uses methods from the machine learning field to learn patterns from spectral features measured with a circular patch antenna. Experimental results show that it is possible to indirectly get an estimate of the degree of porosity of ceramic samples getting low classification error rates. ItemAn approach of social navigation based on proxemics for crowded environments of humans and robots(MDPI, 2021) Daza Guardamino, Marcos Julio; Barrios Aranibar, DennisNowadays, mobile robots are playing an important role in different areas of science, industry, academia and even in everyday life. In this sense, their abilities and behaviours become increasingly complex. In particular, in indoor environments, such as hospitals, schools, banks and museums, where the robot coincides with people and other robots, its movement and navigation must be programmed and adapted to robot–robot and human–robot interactions. However, existing approaches are focused either on multi-robot navigation (robot–robot interaction) or social navigation with human presence (human–robot interaction), neglecting the integration of both approaches. Proxemic interaction is recently being used in this domain of research, to improve Human–Robot Interaction (HRI). In this context, we propose an autonomous navigation approach for mobile robots in indoor environments, based on the principles of proxemic theory, integrated with classical navigation algorithms, such as ORCA, Social Momentum, and A*. With this novel approach, the mobile robot adapts its behaviour, by analysing the proximity of people to each other, with respect to it, and with respect to other robots to decide and plan its respective navigation, while showing acceptable social behaviours in presence of humans. We describe our proposed approach and show how proxemics and the classical navigation algorithms are combined to provide an effective navigation, while respecting social human distances. To show the suitability of our approach, we simulate several situations of coexistence of robots and humans, demonstrating an effective social navigation.