ABSTRACT. As Chile is located in the Pacific Ring of Fire, volcanological monitoring has a particular relevance, due to the existence of a large number of active volcanoes. The SERNAGEOMIN National Volcanic Surveillance Network (Red Nacional de Vigilancia Volcánica) is responsible of the Southern Andes Volcanological Observatory (OVDAS), the national entity in charge of the monitoring of more than 40 active volcanoes along the country. Monitoring consists of sensing a large number of variables such as the chemical composition, deformation, temperature, etc around the volcanoes. However, the seismicity is the variable that provides the most important information about the activity of the volcano. The volcanoes monitored by OVDAS have several seismic stations that send signals 24/7 to the observatory for analysis. The volume of information is enormous. For this reason and thanks to the development of pattern recognition algorithms that automate certain stages of signal processing, these techniques were integrated for the pattern recognition of the volcanic seismic signals, to support volcano monitoring.

ABSTRACT. This study investigates the effectiveness of various electrode shapes in the superficial and selective stimulation of adjacent nerves. A finite element method-based approach using COMSOL Multiphysics is employed to assess the generated electric fields. Results reveal that circular and square electrodes yield a relatively uniform distribution of the electric field, in contrast to concentric electrodes which concentrate their intensity at the center. Examining the activation function suggests that in all three scenarios, nerve stimulation is feasible; however, concentric electrodes demonstrate higher selectivity. In conclusion, concentric electrodes are preliminarily more promising for achieving superficial and selective nerve stimulation.

ABSTRACT. Human mobility involves the nervous and muscular systems, essential for the planning and execution of movements such as walking. According to the WHO, approximately 3.8% of the global population faces challenges in walking. This article presents the development of a human-machine interface with the goal of testing the system and validating user perception to make it more accessible, efficient, and enjoyable for patients. The integration of serious games into the system was chosen to establish an interactive environment that blends gait training, driving physical rehabilitation. This approach focuses on integrating technology into conventional therapy to offer a safer and more motivating environment. The system was validated with twelve volunteers in a series of tasks that offered different degrees of autonomy when interacting with the treadmill. The evaluation of the control strategy in the tasks used the SUS questionnaire, indicating an acceptability score above 70. The results demonstrate the adaptability of the treadmill to individuals’ speed due to the developed control model, promoting its use in applications combined with serious games, thus enhancing the user experience without increasing complexity.

ABSTRACT. This work addresses the design, development, application and evaluation, obtained by implementing an exoskeleton-type robotic system for the rehabilitation of the upper part of the body in pediatric patients, incorporating functional electrostimulation and haptic feedback to improve neuronal reconnection and facilitate rehabilitation. The technical and functional requirements to be satisfied are included. The main elements are described: the control system, the exoskeleton, functional electrostimulation, motor effort measurement and haptic feedback, with all the components and modules used. The results obtained from the trials with two pediatric patients showed a positive effect in the combined technique of electrostimulation and haptic feedback, evaluating performance in functional tasks.

ABSTRACT. In the field of upper limb rehabilitation, where the goal is to improve quality of life and independence in daily activities, technological initiatives in the healthcare setting have become more relevant. In this context, we present a physical simulator for rehabilitation devices, specifically in the hand and wrist, designed in CAD and manufactured by 3D printing. This simulator, consisting of a prosthetic hand, a wrist base and a mounting bracket, constitutes an effective tool for the evaluation and testing of various rehabilitation devices. The simulator provides a physical environment in which specific hand rehabilitation devices can be tested and adjusted. Its modular design allows for easy replacement and adaptation of different devices, streamlining the development and evaluation process. Manufacturing with 3D technology ensures the customization and precision needed to mimic the anatomical and functional conditions of the human hand. By allowing direct testing of rehabilitation devices in a controlled environment, this simulator provides a tool to evaluate the efficacy and functionality of devices prior to implantation in patients. This has the potential to reduce the time and costs associated with the development and refinement of hand rehabilitation devices, thus contributing to improving the quality of life of those who benefit from these technological advances.

ABSTRACT. Integrating social robotics into the construction industry, particularly in the context of Industry 5.0, faces several challenges in creating complex environments that seamlessly blend human and machine interactions. In this regard, the emergence of intelligent and expert systems holds promising technologies to enhance construction tasks focused on robots and workers. This work compares several convolutional neural network-based object detectors designed to identify distinct construction assets and workers within dynamic environments. To this end, different versions of the You Only Look Once v8 (YOLOv8) algorithm have been implemented, trained, and experimentally tested using several images captured within dynamic construction environments. Furthermore, we present an in-depth comparison between YOLO v8 and its preceding versions, namely YOLO v7 and YOLO v5. Experimental results disclosed the high performance of the proposed approach in effectively detecting three distinct entities (workers, robotic platforms, and building elements), achieving a precision rate of up to 98.8\%.

ABSTRACT. The integration of technologies like the Internet of Things (IoT), Big data, and Artificial Intelligence (AI) has empowered modern vehicles with the ability to communicate with one another for better cooperation on the roads. However, the communication between vehicles exposes the whole intelligent transportation system to new attack vectors. Malicious vehicles can spread misleading information, which, if acted upon, might result in traffic congestion, accidents, chaos, and even fatalities. As a countermeasure, ETSI proposes a framework, TR 103 460, for reporting abnormal behavior. However, there are many shortcomings, such as the absence of a peer-to-peer (P2P) misbehavior reporting (MR) service and the inability to secure the reporter's identity and reported information. To protect vehicles from abuse, we propose a P2P non-interactive zero-knowledge proof-based privacy-preserving MR framework. Upon testing, we found that the proposed framework prevented the disclosure of the reporter's identity and information and reduced the ITS-Stations' (ITS-Ss) exposure to misbehavior by 67.7% and 79.2% in suburban and highway traffic scenarios, respectively.

ABSTRACT. Cognitive effectiveness is related to the speed and accuracy of a representation to be processed by a human being. The speed is related to cultural and previous knowledge and accuracy to the non-ambiguity. Agent orientation is a strong stream in Software Engineering guiding the development process of complex and highly distributed engineering solutions. Thus, it should be used for modeling the distributed components of cyber-physical systems. In this paper, we propose a synthetic way of using agent orientation for modeling cyber-physical systems using a fusing agent proposal as graphic modeling, and we report the research conducted to assess its cognitive effectiveness in a cyber-physical context. The result shows promising results on using the notation in performance, understanding and usefulness, but also a high discrepancy in visual expressiveness.

ABSTRACT. In Flexible Manufacturing Systems (FMS) decision making plays an important role in optimizing production and operational efficiency. This decision making should be efficient and adaptive. Machine Learning (ML) has become a fundamental tool to improve decision making in FMS. This paper discusses the foundations of FMS, the importance of decision making and how ML can revolutionize this process. A review of the algorithms used in decision making using ML in FMS is presented. To illustrate this integration and present a case study of an FMS

ABSTRACT. This article comprehensively analyzes the technological adoption landscape among agricultural enterprises in the Maule Region, Chile. Drawing from an extensive survey conducted within the region, the study delves into the extent to which technology has been embraced by these enterprises. By examining the factors influencing their decisions, challenges faced, and opportunities identified, the article offers valuable insights into the current state of tech adoption within the local agricultural sector. The findings highlight adoption patterns across different types of enterprises, shedding light on successful implementations and areas where advancements are lagging. The study serves as a benchmark for the technological progression in the Maule Region and contributes to the broader conversation on digitization within the global agricultural industry. As agriculture continues to evolve in an increasingly digital age, this research underscores the significance of understanding the nuances of technology integration for the sustainable growth of agricultural enterprises.

ABSTRACT. One of the major challenges in contemporary agriculture is the precise management of irrigation water, closely tied to an accurate estimation of crop water status. Currently, the available methods for accomplishing this task are time-consuming, non-scalable to large areas, and incapable of providing real-time information to farmers. In this sense, the incorporation of remote sensing tools for the assessment of plant water status is of great importance. One of these tools is canopy-air temperature difference, which is a valuable tool for assessing plant water status given that it provides quick, non-invasive insights into plant condition. This method is cost-effective, scalable, and suitable for various crop types, aiding in efficient irrigation management, stress detection, and optimizing agricultural practices. Consequently, this research aims to design a low-cost, spatialized-capable device based on the canopy-air temperature difference for predicting the water status of lettuce crops in greenhouse environments. The development of this device considered the ensemble of the device, where a series of components were integrated into a low-cost sensor. Afterward, laboratory tests were carried out to assess the precision of the sensors. Finally, a test was carried out under greenhouse conditions, where the performance of the sensor was tested under real operation conditions, allowing to calculate the canopy-air temperature difference in order to assess an estimate of lettuce water status. The results of this study indicate that this device will generate a tool that can be used by farmers of any scale, ultimately enabling efficient management of water resources.

ABSTRACT. Climate changes and human factors have led to increased water restrictions and resource utilization. It is expected that in the coming years, there will be longer drought periods with reduced precipitation and decreased river water availability. In the context of limited water resources, where 87% of Chile's freshwater is consumed by the agroindustry sector, water use efficiency and Water Productivity (WP) become crucial concepts, particularly for public policy considerations. The objective of this article is to calculate a water productivity indicator for central Chile using a dynamic map of Reference Evapotranspiration and to assess the impact of water communities on water productivity. We analyzed a dataset comprising 352 observations from 19 water communities across four regions of Central Chile. Daily reference evapotranspiration values were obtained from the "ETo" web platform, supported by the Universidad de Talca. We measured WP in Chilean pesos per cubic meter as a dependent variable and conducted a multilevel model to determine the influence of various factors on WP at the farm level. The results indicate that annual crops exhibited the lowest water productivity, while vegetables and fruits performed better. Additionally, our findings highlight the significant impact of water communities on water productivity, with the irrigation system and crop type emerging as the primary variables affecting WP in Central Chile.

ABSTRACT. This article presents the development of the hardware structure of a platform for monitoring physical variables in a crop. It outlines the technical specifications of its components and their key features, which classify it as an innovative product with significant impact on improving agricultural processes. The portability of the implemented equipment enhances its usability in remote locations, and the real-time data generation that can be accessed from mobile devices further amplifies its potential use. It is anticipated that this equipment can be employed to enhance crops not only at a national level but also internationally, positively impacting crop productivity.

ABSTRACT. Marking the opportunity to renegotiate Annex C of Itaipu Treaty for 2023 as a milestone for Paraguay, various ideas emerge for the country's development. One of them is the commercialization of energy to neighboring countries. To achieve this, it is almost logical to make investments in the Transmission System, which plays a fundamental role for this purpose. In this context, this work analyzes the variants related to the execution of works at the 500 kV level provided for in the ANDE Master Plan, considering the hypothesis that in said renegotiation the terms of purchase and sale of energy are changed. The evaluation was carried out considering 54 energy marketing strategies and reliability criteria. For the marketing analysis, income from energy transfer, the assumption of energy sales and changes in terms in the Treaty were considered. Likewise, for the reliability analysis, the simple contingency criterion was applied. The results reveal that, by advancing the execution time of some works, the economic performance of the SIN can be improved by up to 2.57%, compared to what was planned by ANDE. Furthermore, from a reliability point of view, an increase in the security of electricity supply has been observed. Therefore, considering the proposed approach, the ANDE Master Plan can be optimized, in order to have greater flexibility for the 500 kV works and greater robustness for the SIN, in order to be able to comply with future energy transaction commitments and obtain greater economic benefits.

ABSTRACT. Planning the expansion of electric power systems, particularly the transmission system, represents a dynamic and continuous process that requires constant adaptation to the changes that the systems experiment in their environment, whether they are economic, social or technical. Considering that the economic factor is one of the most conditioning aspects in any expansion plan, together with the dynamics of the electricity markets, it is evident that planners face the growing challenge of optimizing the available financial resources, so that any investment decision made in the electricity system is carried out after seeking the maximum possible benefits in technical, social, environmental and even political aspects. In Paraguay, the National Electricity Administration, through its Transmission Master Plan (PMT) for the period 2021-2030, has presented a strategic set of projected works in the 220 and 500 kV transmission corridors, mainly with the objective of accompanying the marked growth in demand in recent years. In this paper, a methodology for the analysis and prioritization of transmission works is proposed, applied to a set of nine selected works of the PMT, based on the use of probabilistic indexes applied to the evaluation of the impact of these expansion projects on the reliability of the system during N-1 contingencies. The methodology is applied to equivalent models of the Paraguayan National Interconnected System and focuses on the impact on reliability at the end of the mentioned period, specifically for the years 2029 and 2030, in order to compare the impact on reliability of the works under study. Then, a prioritization tool is applied according to certain criteria, in order to finally determine the priority works of the set of works analyzed. In this way, the methodology presented becomes a useful tool when deciding on investments among a set of transmission works.

ABSTRACT. The objective of this work is to analyze the regulatory framework for renewable energy generators interconnection. This study investigates this situation, evaluating the Brazilian regulatory reform proposal and comparing it with the regulatory reforms in the United States about transmission access. Results show that the increase in renewable source power plants has brought significant challenges to planning the energy transmission system expansion. Due to particular circumstances and the natural characteristics of some locations, access to specific transmission system connection points has become the subject of fierce disputes among generators. It also has caused queue backlogs for access request analyses. Global regulatory bodies have been analyzing models and alternatives to address delays and access request queues. We conclude that the new American regulation has improved significantly, which might positively influence the Brazilian generator interconnection procedures regulatory framework.

ABSTRACT. This article presents a comprehensive literature review of existing methodologies for exploring the future and their potential application in the energy sector. It is found that methodologies related to future studies have diversified, allowing the integration of information about complex environments through the opinions of various stakeholders. The most well-known methodologies are foresight and future scenarios, which can be applied in various decision-making cases, including international negotiations. Specifically, the future negotiation between Paraguay and Brazil in 2023 is addressed, involving the binational hydroelectric power plant ITAIPU, jointly owned by both countries. The aim is to construct feasible scenarios after the review of ITAIPU's Annex C. A scenario tool is applied to prepare for eventualities, providing flexibility in decision-making. Three possible future scenarios for tariffs after the ITAIPU review are developed, based on the analysis of alternatives for the Cost of Electric Service (CSE) of ITAIPU. This tool can be used for the ITAIPU Annex C review.

ABSTRACT. In an electrical system, the transmission system is particularly a fundamental infrastructure as it plays an important role for the accessibility and development of the electrical market. In the present work, an optimal planning of the transmission expansion to the Paraguayan electrical system was carried out, minimizing the operation and investment costs. A reduced equivalent system of the Paraguayan electrical system at 500 kV was elaborated, in which certain candidate works of the Transmission Master Plan of the Paraguayan Electrical Market Administrator were analyzed, applying mathematical optimization methods, having represented the network by a DC model. The mixed integer nonlinear programming problem is solved by programming in GAMS. As a result, it was determined from a set of candidate circuits, which are necessary to build for a given time horizon, so that the operating restrictions are satisfied and the operation and investment costs together are the minimum to supply the future demand. It is demonstrated that the results provide valid technical support for the selection of 500 kV works to be prioritized, and that there are works that can be reconsidered as they do not provide a reduction in operating costs or in terms of energy not supplied. In addition, for the particular case studied, it was observed that a minimum investment can mean large reductions in the operating cost of the system.

ABSTRACT. Battery energy storage systems (BESS) have the potential to significantly enhance the efficiency, robustness, and resilience of a power electrical system. This work addresses the possibility of integrating battery banks as an energy storage system into the Paraguayan National Interconnected System (SIN), developing a model to simulate its operation at the power system level. The goal is to create a charge/discharge scheme that allows for flexibility according to load patterns that vary throughout the year, with temperature and the predominantly residential nature of electricity consumption representing 88% of total customers and 44.7% of national electricity consumption, being the crucial factors in Paraguay's electrical demand variation. The results show a reduction in the need for load dispatch and an improvement in the Load Factor at the Itaipú hydroelectric power plant, consequently enhancing the Load Factor of the SIN. Additionally, there is a reduction in the dispersion between the maximum and minimum power dispatch values in the system, offering greater predictability in generation plant dispatch requirements. Ultimately, we believe that this would enable the National Energy Administration (ANDE) to generate savings in terms of optimizing the process of contracting energy from Itaipú, which supplies approximately 88% of the energy consumed in the country.

ABSTRACT. We present a remote control operation system enhanced by sensor fusion applied to a newly developed skyline grapple carriage to improve the throughput, reliability, and efficiency of the timber harvesting process in very steep terrains in Chile. The skyline cable carriage CMG is used as a key part in a new mechanized harvesting method recently introduced in Chile. The CMG lowers itself from a standing skyline to pick logs from the ground with a grapple claw. The operation is done completely by remote control without line of sight and with no direct human intervention as opposed to the previous methods which required intensive manpower (timber faller operators and choke setters). The operation of the CMG is enhanced with real time information given to the operator from a set of sensors and by processing the measured data.

ABSTRACT. The modernization process of a CNC machine entails multifaceted and critical component selection. This study proposes a multicriteria model based on the Analytic Hierarchy Process (AHP) to address this challenge. It focuses on the selection of CNC software and MCU, considering factors such as quality, vendor support, and technical capability. The CNC machine EP2006 was taken as a case study due to issues related to PCAM software. AHP identified GRBLHAL as the best alternative for CNC software and Teensy 4.1 or T41U5XBB for the MCU. This robust approach takes into account technological evolution, ensuring that the machine remains up-to-date and competitive in an ever-changing environment.

ABSTRACT. As an emerging technology, the Internet of Things is still a challenge due to its type of structure, as well as its multidisciplinary nature, which involves a great effort in terms of knowledge and understanding of the different types of resources used for the development of this type of project. In the years 2020 to 2022, due to the pandemic, face-to-face classes were compromised, allowing the use of this type of emerging technology. This study presents the results of experiments carried out in virtual courses for the development of a project for the internet of things carried out at the Instituto Tecnológico y de Estudios Superiores de Monterrey. Opinion polls were carried out with students during virtual classes with the Wokwi Circuits tool, the results showed the feasibility of using this tool in an integrated way with others necessary for the construction of IoT projects, the contribution of these results should enable the development of new research applied in more robust and advanced solutions according to the need of the scientific research project, collaborating for the distribution of information and knowledge sharing between different areas of investigation.

ABSTRACT. During the pandemic period, which involved the years 2020 to 2022, many activities that were carried out in person were forced to adapt to the virtual model, providing a challenge for educational institutions and professionals from different areas. This study presents the results obtained from the experiments carried out during virtual classes for the Internet of Things in which the resources of the Arduino IoT Cloud platform were used, which allowed greater interaction and simulation of results, enabling the creation of integrated solutions with advanced interfaces, these results contributed to a better development of the project, adding functionalities and resources that allow its use in more advanced projects, this work presents the result of the entire organization, structure and examples of activities that can contribute to more advanced studies on the its use, the results are based on experiments in classes, with discussions about the authors' experience during its elaboration. Some characteristics identified during the study are its ease of use, possibilities to carry out simulations online and in real time, also because it is a free tool, it has viable resources for the construction of more complex solutions.

ABSTRACT. In this study, we delve into the intricate dynamics of agricultural practices in Chile, emphasizing the integration of satellite imagery, agroclimatic data, and spatial analysis techniques. Using the capabilities of the Landsat satellite, combined with data from the ”Red Agroclima ́tica Nacional (RAN),” we provide insights into instantaneous water consumption and its implications for food production. The Mora ́n Index’s spatial analysis further enhances our understanding of crop distribution and water usage patterns. Additionally, through a comprehensive literature analysis, we bridge the gap between primary data and existing research, offering a holistic view of Chile’s agricultural landscape. Our findings underscore the importance of diversifying agricultural production and highlight potential challenges and opportunities in ensuring sustainable food production in the face of evolving environmental and socio-economic challenges.

ABSTRACT. This work presents a new prototype for the automated root traits phenotyping using an array of cameras. The proposed pipeline involves the acquisition of a set of images of the root, then the generation of a 3D cloud point and model using these photos and finally the calculation of geometrical traits using the reconstructed 3D model of the root. The design, construction and preliminary results of the prototype are presented here.

ABSTRACT. En este trabajo, se describe la implementación de una plataforma de pruebas para un sistema de inspección de plantas de arándanos basado en un dron con cámaras multiespectrales. El objetivo principal es implementar, en un robot UR3e, el seguimiento dinámico de trayectorias comandadas por un sistema de visión incorporado en su efector final, que permita probar y evaluar diversas alternativas de escaneo, detección e inspección de los racimos de arándanos en las plantas, que serían implementadas posteriormente en el dron. Para realizar experimentos, se colocaron imágenes de racimos de arándanos, en pequeños postes de madera, que se ubicaron en el espacio accesible por el UR3e. Cuando el robot se acciona, comienza a mover la cámara hasta detectar los frutos, guarda un video de la inspección del racimo, y continúa su trayectoria en busca de más frutos. Los resultados de estas pruebas permitieron establecer el rango de movimientos necesarios para capturar imágenes representativas de las plantas de arándanos, establecer y validar la comunicación robusta entre los dispositivos involucrados en el sistema de inspección y corroborar la efectividad del modelo de detección de arándanos.

ABSTRACT. This work presents a comprehensive review of the current state of the use of deep learning in the analysis and interpretation of satellite and aerial images applied to smart agriculture. Various investigations that have applied techniques such as convolutional neural networks, generative adversarial networks, and visual transformers are analyzed to address various applications and specific challenges in this field. The advances achieved demonstrate the effectiveness of these techniques to extract relevant information in agricultural decision-making, such as seed counting, disease detection, soil mapping and plant classification. However, outstanding challenges related to the interpret-ability of the models and their adaptability to different agricultural contexts are also identified. Future trends are discussed, such as the integration of multi-modal data sources, the development of more interpretive and explainable models, and the improvement of data-efficient learning techniques. These innovations promise to further advance precision agriculture and contribute to sustainable agricultural practices.

ABSTRACT. Chile is one of the leading producers of sweet cherries worldwide, and the fruit sector is currently facing the challenge of adapting to climate changes. In the Maule region, which accounts for 43\% of national sweet cherry exports, innovative adaptation strategies are needed. Therefore, this study aims to digitize the phenology models of sweet cherries in the Maule region, Chile. Using field data, the construction and validation of these models are conducted. The approach relies on monomolecular biomathematical models, which are calibrated and validated using observations collected over multiple seasons (2017/2018, 2018/2019, 2019/2020, and 2020/2021). The focus is on eight sweet cherry varieties: Sam, Lapins, Rainier, Royal D, Santina, Regina, Kordia, and Sweet Heart. By digitizing the phenology models, the developmental rates for each variety are estimated, enabling the prediction of the budburst start date for each of them. This study on the digitization of sweet cherry phenology models not only contributes significant advances in optimizing the planning and management of the cherry season in the Maule region, Chile but also plays a crucial role in the education and training of 21st-century agronomists. Furthermore, the digitized phenology models will be incorporated into an RShiny application program, making them easily accessible through digital platforms. This will enhance their utility for training and scientific research purposes.

ABSTRACT. In this study, we address the significant issue of Energy Poverty (EP) in the context of the Republic of Paraguay, focusing on the Carmen Soler community in Limpio city. EP, a pivotal facet of poverty, intersects with multifaceted dimensions of development, demanding a comprehensive approach. Our objective is to construct a Multidimensional Energy Poverty Index (MEPI) for Carmen Soler, utilizing secondary data collected in 2018. This index enables the assessment of energy deprivations within households, offering insight into their multidimensional energy poverty status. Our mixed-method approach combines exploratory and descriptive methodologies to analyze the situation, revealing that while incidence rates are low, intensity levels are notably high. The MEPI score, around 9.085%, emphasizes the urban context's significance despite its modest value. This research contributes to a broader understanding of Energy Poverty in Paraguay and recommends further national-level studies and policy discussions to address its implications comprehensively.

ABSTRACT. Battery cycler or battery cyclic testers are wellknown devices available in the market for the study of the behavior of battery energy storage devices. In this work, an open-source battery-cycler design is proposed. The proposed design considers the generic addition of an arbitrary number of battery cells in series and in parallel to form the battery pack. In particular, it is especially conceived for evaluating the different behavior among individual cells. This feature is mainly considered to help, for instance, in the design of battery management systems with active equalizers. The system is implemented in the Electric Power and Energy Laboratory at the Universidad Austral de Chile. Experimental results show the versatility of the system. This versatility lies not only in its ability to cycle multiple cells simultaneously, but also in its ability to accurately and simultaneously monitor critical parameters such as temperature, voltage and current.

ABSTRACT. Amidst the pursuit of sustainable energy, photovoltaic generation plays a crucial role in the global energy landscape. The effectiveness of harnessing photovoltaic resources significantly relies on accurate measurement of global horizontal solar irradiation (GHI). However, in certain locations, the availability of suitable sensors for installation is limited. Nevertheless, other meteorological variables, such as temperature, are more easily accessible. These variables can be used in prediction models to estimate the solar resource. Thus, this work presents a training and validation based method to predict GHI, applying 14 prediction models: Thirteen empirical models based on maximum and minimum temperatures, along with one machine learning model based on temperatures, relative humidity, wind speed, and wind direction. Also, the obtained resource is used to forecast the daily electrical generation of a photovoltaic system. Data from a meteorological station and a 40 kW photovoltaic system located in Quito, Ecuador, are employed. A statistical evaluation was carried out to validate the models and the forecasted photovoltaic energy. The results show that models relying solely on temperatures did not exhibit strong fits, in contrast to the machine learning model that incorporated more meteorological parameters during its training. The Goodin model performs better in places where only temperature data is available. Likewise, when other parameters are accessible, the Random Forest model demonstrates a remarkable proficiency in predicting the available resource. Regarding the estimated energy, notable findings were identified, highlighting the fundamental role of solar resource within this intricate process.

ABSTRACT. The pressing need to decarbonize electricity generation has spurred the imperative integration of renewable energy sources. Among these, solar photovoltaic (PV) technology has emerged as a highly viable alternative. However, the limited flexibility in energy distribution to the grid presents a hurdle for increasing the share of photovoltaic energy in the power matrix. Consequently, developing inventive and adaptable ways to include PV in the grid becomes pivotal in expediting the transition toward a low-carbon power generation model. Notably, Chile plays a significant role in advancing solar energy integration. Nevertheless, curtailments have been increased in the final years, with diminished PV energy production. To tackle this challenge, the vertical bifacial photovoltaic (VBPV) configuration emerges as a groundbreaking approach. Its ability to stagger generation peaks across two distinct timeframes throughout the day introduces enhanced grid integration flexibility. This study presents a computational analysis of the potential of VBPV layouts within the Chilean context alongside an exploration of the associated opportunities and obstacles.

ABSTRACT. The move to sustainable energy is a global challenge that requires the advancement of renewable sources. Photovoltaic and solar thermal systems are promising clean energy technologies. Mathematical models crucially improve our understanding of the performance of these systems. This study focuses on the development of approximate models to estimate the performance of photovoltaic and solar thermal systems in different environments, improving their efficiency and reliability. The models are intended to approximate cost reduction through the promotion of renewable energy and the mitigation of climate change. Using Simulink®, these mathematical models are validated through comparisons with real equipment, showing a maximum error of 6.57%.

ABSTRACT. The objective of this work is to design and imple- ment two cosmic ray detection systems to analyze the impact of the South Atlantic Magnetic Anomaly on the observed in- coming particle rate. The implemented detection systems utilize scintillating materials to emit photons when ionizing particles pass through them. These photons are captured by silicon photomultiplier sensors (SiPM), generating signals that are then conditioned by an electronic board. The board can accommodate up to 16 sensors grouped in sets of 4. The signals are amplified, compared with a reference, and digitized using a hysteresis comparator and time stretcher. An FPGA device has been programmed to process the signals, control the duty point, and test the detector’s timing. The detection system consists of two independent configurations. The first configuration includes three stacked 50 cm x 50 cm scintillators that can be rotated with respect to the zenith angle. The second configuration consists of four 25 cm x 25 cm scintillators that can be used as two separate detectors. The measurements have been carefully adjusted to the expected muon distribution and exhibit similar behavior to other detectors in the Mechanics and Energy laboratory. Furthermore, the new architecture has successfully observed interesting space weather events, validating all detection systems.

ABSTRACT. The Internet of Things (IoT) has proven effective in automating various tasks and finding applications in real-world scenarios such as intelligent industries, smart agriculture, e-healthcare, and environment exploration. Nevertheless, their applications demand secure data transmission, as IoT devices remain susceptible to hacking, potentially leading to data breaches. Such breaches can disrupt device operations, posing risks such as fires, impacts on health, and even jeopardizing lives. These security issues are being addressed using blockchain, which has proven effective in classical computing architectures. However, the technology is gradually transitioning towards quantum computing, which has significant processing power that could easily compromise the algorithms employed by blockchain. Thus, there is a need to use quantum computing approaches. In this work, we propose a small IoT environment for bit encoding and decoding using quantum superdense coding in the data transmission for IoT devices to validate the feasibility of quantum algorithms in IoT. We tested sending integers through two emulated Raspberry Pi devices in VirtualBox. On each Raspberry Pi, we implemented superdense coding to encode and decode the integers sent by the neighbor device via MQTT. Comparing the source data with the target data, the results indicated zero errors in data transmission, confirming that superdense coding is feasible in the IoT context. The average execution time for data decoding was 0,39 seconds based on 50 tests.

ABSTRACT. Due to the massive increase in data sets in contemporary applications and the difficulty of their processs in various approaches, data fusion remains a predominant way to obtain outstanding results, in termin reliability, efficiency, and precision. The following document presents an overwiev data fusion in wireless sensor networks, in which, various concept to applications are considered to generate a base document for future research. This articles gives a comprehensive a current view of models of architectures, techniques, methodologies or algorithms, and a current review of applications in different areas.

ABSTRACT. Recently, many researchers have tried to answer a question regarding smart cities: how to connect a wide variety of sensors and aggregate the data collected by different technologies related to the Internet of Things (IoT)? Those data are usually gathered and transmitted through WAN (Wide Area Network) or private MPLS (Multi-Protocol Label Switching) connections. However, since WAN based solutions present different resources in terms of data, size, coverage area, latency and capacity requirements, they become inefficient or even prohibitive regarding operating costs on smart city applications. An alternative is the use of SD-WAN (Software-Defined Wide Area Network), which combines hardware and software appliances or is software based only, consisting of the virtualization of WAN connections. The main characteristics of SD-WAN are: the ability to do dynamic path selection, facilitating data flow and increasing system resilience; the support to multiple connection types (ADSL, VDSL, FTTH or 3G/4G), enlarging the coverage area when compared with traditional WAN; the employment of a simple interface (easy to configure and manage); the capital and operation expenditure reduction; the increase of service agility and flexibility; the implementation of a centralized control and monitoring with lower costs. In this sense, this paper proposes an SD-WAN embedded white-label solution, of low cost and low energy consumption for commercial and academic use employing Ubuntu Linux, Floodlight SDN Controller, Open vSwitch and Raspberry Pi 3b. Then, the Quality of Service (QoS) parameters obtained by the proposed SD-WAN solution are measured and evaluated, through network emulation tests performed with the aid of Distributed Internet Traffic Generator (D-ITG), with the purpose of verifying the applicability in smart cities.

ABSTRACT. Robust qualities make composite materials extremely valuable for the aerospace industry. However, some issues using these materials become apparent during production. Structures made from composite materials are still primarily produced manually, which often leads to increased variability in the quality of the final products. Self-manufactured, low-cost foil sensors can be employed to monitor the curing process of potting materials, particularly synthetic resins, during the production of composite structures for aerospace vehicles. Since these sensors remain integrated within the structures following the method developed here, they hold potential for subsequent utilization in monitoring structures during flight and under operational stresses. For this study, custom sensors were produced in-house using an economical method. These sensors were designed as interdigital electrodes and were coated with conductive ink onto a polyimide substrate. The ink's flexibility was sufficient to robustly and securely accommodate substrate deformations. The foil sensor was implemented and assessed using a model aircraft wing segment as an illustrative example. In this context, the foil sensor served as a measurement probe for capturing time-series impedance spectra. The results demonstrated the foil sensor's mechanical and chemical durability during the test preparation and execution phases on the model, alongside its electrical suitability for this intended purpose. The collected measurement curves underscore this method's efficacy for monitoring composite materials' curing process during production.

ABSTRACT. University Social Responsibility is an essential commitment for students when relating to the national and social environment, while software engineering projects, ranging from development to maintenance, underline the need to satisfy customer demands. In software engineering, the constant search for effective methodologies to promote significant skills and knowledge among students is analyzed. In this context, the Service-Learning method emerges as an innovation that transmits knowledge and establishes collaborative connections with the surrounding community. In this paper, we present a review of research focused on higher education students, especially computer engineering majors, who use the Service Learning methodology to address community challenges. The article is structured into sections that explore related work, the review methodology, a case study on an implementation project using Service Learning and Project Based Learning, and concludes with lessons learned from this review.

ABSTRACT. This paper uses a developed temperature control education system called TCLab to apply three different closed loop tuning methods. The TCLab system is an Arduino-based system used in several control system applications. The closed loop tuning methods are Ziegler-Nichlos, relay, and good gain.Furthermore, several tests were conducted to evaluate the performance of the tuning parameters obtained from the earlier methods. To our knowledge, this device has been used for this objective for the first time.

ABSTRACT. In recent years, Multimodal Learning Analytics (MMLA) has offered significant opportunities for improvement in education, student teaching, and learning processes. However, the recent explosive advancement of artificial intelligence technologies has strongly impacted the scenario of disciplines related to the use of information technologies. The scopes of these new technologies are still unknown. This article describes the potential for developing and researching Artificial Intelligence as a Service (AIaaS) to improve current applications and research in MMLA. We present eight types of analysis that can be enhanced by AIaaS, as well as a comparative analysis of the most well-known AIaaS currently on the market. The combination of AIaaS and MMLA tools is expected to provide a new impulse for improving teaching-learning processes, which could positively impact the overall quality of education methodologies.

ABSTRACT. In this study, we propose using feedback control techniques for learning and educative purposes on the line of Electronic Engineering for undergraduate degrees. The main objective is that the student manages to control the inverted double pendulum to leave it at a certain equilibrium point. The methods addressed are space state representations, linearization, control by LQR, Kalman observer, and discretization. As a case study for applying these methods, we choose the stabilization of an inverted double pendulum. The expected result is a discretized model with a sampling time able to stabilize the inverted double pendulum in the erect equilibrium state. Therefore, this result also shows the student’s understanding of control techniques.

ABSTRACT. Nowadays, the vast majority of university careers declare a competency-based curriculum. However, having concrete evidence to measure learning outcomes can be a complex problem in engineering. Academics make great efforts to design active learning experiences to stimulate skills development. However, more evidence is required to describe methodologies integrated with technological tools to evaluate learning outcomes. In this paper, we propose using the Lego Serious Play (LSP) methodology and Multimodal Learning Analytics (MMLA) techniques to assess learning outcomes in the Software Engineering I course. The results obtained are quite promising since it was possible to identify difficulties in acquiring and applying knowledge.

ABSTRACT. In recent years, rare-earth free machines have gained increased attention in low-speed high-torque (LSHT) applications considering rare-earth scarcity and price fluctuations. In this sense, matrix-rotor induction machines (MRIM) have shown promising results, but their suitability and competitivity when compared with the prominent permanent magnet synchronous machines (PMSM) have not been disclosed so far. This paper provides an electromagnetic analysis of MRIMs by means of 3D finite element simulations, comparing their performance to a PMSM in LSHT applications. Rated torque, efficiency and power factor of these machines are assessed and compared.

ABSTRACT. This paper presents a comprehensive analysis of the impact of harmonic-oriented step-skewing on the performance indices of a SynRM. A 36-slot, 6-pole, 3-barrier SynRM that has been previously optimized was chosen as the study case. The results verify that skewing can significantly decrease torque ripple at the cost of having a negative impact on the mean torque. More importantly, the saliency ratio and the current angle for MTPA are reduced, which penalizes power factor and efficiency. The findings of this research provide a deeper insight into the effect of various skewing steps on the performance indices of the machine.

ABSTRACT. In electromagnetic transients studies for conceptual design projects of transmission lines, electric arcs are commonly represented by a switch in series with a fixed-value resistance. Although valid, this simplification could lead to improper equipment sizing if not properly conducted. Using empirical models and taking into account the structural aspects of the transmission lines, a method was developed to size the resistance that represents electric arcs. With the aim of enhancing result accuracy, current and arc length parameters were considered and calculated using easily accessible or estimable information. A minimum arc length was defined based on the distance occupied by the lines insulator chain, allowing for extrapolation to a maximum length. In the analysis of a single-phase switching study, the observation of the lines structural profile and the application of the sizing method confirmed that a delayed current zero crossing previously encountered with the use of an initial conservative value was not real and the lines own dissipation capacity was sufficient to extinguish the phenomenon. Thus, it was demonstrated that a straightforward and effective representation of the electric arc is possible, by employing a resistance sizing approach that remains true to the actual conditions of the line which it was designed for.

ABSTRACT. This paper introduces a methodology for designing a dual-cage squirrel cage induction motor (IM) intended for electric vehicles. A 48-stator slot/40-rotor slot, 4-pole IM is selected as the study case to validate the proposed methodology. The validation was conducted thorough finite element (FE) simulation by ANSYS software package, with acceptable agreement. The findings of this research provide a quick tool to design dual-cage IM with low computational burden.

ABSTRACT. Electricity generation has evolved from conventional systems that use resources such as coal or oil, to renewable generation systems, using solar and wind energy. However, the variability of these resources can compromise the operational continuity of a system by making it difficult to assign secondary reserves necessary for the system, increasing the complexity in determining the flexibility recquired. The Renewable Energy FLEXibility (REFLEX) model, unlike others, internalizes the system's flexibility deficit as constraints in the unit commitment, allowing flexibility deficiencies to be economically valued when assigning reserves due to the high penetration of Variable Renewable Energy (VRE). Chilean electrical system is used as study case to verify the effectiveness of the model, finding an optimal economic relationship between the integration of VRE and the sizing of required reserves, allowing analysis on guidelines looking to keep systems flexible and reliable.

ABSTRACT. In this work, we design a parallel algorithm of the Block-InsertionSort (BiS) method by taking advantage of the high degree of parallelization that BiS offers, which performs multiple insertions of already sorted element blocks. As a result, we present a parallel implementation using OpenMP, evaluating its performance with different input sizes and data distributions. We also compared it against various parallel versions of classical sorting algorithms and state-of-the-art parallel sorting algorithms with available implementations. Our final version –which relies on multiway merge routines from libstdc++ parallel mode– was able to achieve significant performance improvements, close to 17× average speedup on 32 cores.

ABSTRACT. One of the largest biometric databases in Chile is fingerprints, which is also the most widely used biometric in the national context. In this sense, it is relevant to have efficient algorithms in execution time on this biometrics. In the current context of High Performance Computing, there are co-processors, such as GPUs (Graphic Processing Units) capable of accelerating algorithms efficiently with low monetary cost, low electrical cost and physical space. In this work, we propose the acceleration of a biometric fingerprint algorithm on a multi-GPU hardware platform.

ABSTRACT. This paper presents a performance analysis in software of the runtime cost of different algorithms proposed to accelerate scalar multiplication on elliptic curves. It employs double and triple base for the scalar $k$ representation. Furthermore, we implement the Joint Sparse Form algorithm with both double and triple base, and compare all these algorithms against NAF, Windows NAF, and Sliding Windows NAF. Our analysis allows us to establish that for double-base algorithms, the $2$-$3$ base is the most efficient, and for triple base, the $2$-$3$-$5$ base is the most efficient. The same holds true for multibase Joint Sparse Form algorithms. However, without a doubt, the most efficient algorithm is the Windows NAF method with a window size $w=5$. Our implementation was executed on GNU Linux and programmed in Python $2.7$. In an Intel Core i5 Processor 2.53 GHz.

ABSTRACT. A biometric identification system must answer the question: who is the person? It must recognize the individual with no other data than the digital representation of their biometric trait. Indexing significantly reduces the number of candidates to verify, however they depend entirely on the quality of the index and the features extracted from the fingerprint. This article presents a robust indexing scheme against rotations, translations and elastic deformations in the skin, based on Delaunay triangulation, maintaining acceptable response times and having a better penetration rate than the published works consulted. To determine these characteristics, a topological structure based on Delaunay triangulation will be associated, where the coordinates of the vertices of the generated triangles correspond to those of the minutiae extracted from the fingerprint.

ABSTRACT. For companies with interdisciplinary teams working on confidential projects, some restrictions and policies regarding information security may be raised. For example, the use of third-party clouds is a concern. This paper proposes a framework using a new open-source plugin, the Easy Design Handoff, for Adobe XD and GitHub Actions, aiming to achieve the following relevant contributions: An approach based on Continuous Integration and Continuous Deployment pipelines that may be used as an alternative to built-in handoff features like Adobe XD without relying on third-party clouds, and a new open-source plugin for Adobe XD that adds the functionality to export the wireframes without using any kind of third-party cloud. This case study was a real project, and it was found that Continuous Integration and Continuous Deployment pipelines can be used to do design handoff without relying on third-party clouds. The proposed framework and plugin raised the level of automation and standardization of the project without violating the company’s security policy, and improved the collaboration between teams during software development.

ABSTRACT. This paper conducts a comparative analysis of control strategies based on fuzzy logic for systems with inverse responses. The study evaluates two control approaches: a Fuzzy Logic PI controller and the Iinoya Fuzzy Logic compensator. The evaluation uses TCLab as the testbed, a benchmark device used in control engineering education. A comprehensive comparison is performed, considering performance metrics including ISE and ISCO indices, maximum overshoot, and settling time for each utilized controller.

ABSTRACT. This paper presents RUPU, a low-cost scaled-down experimental platform tailored for deployment and experimental testing of strategies to deal with the lateral and longitudinal control problems in path-following vehicle platooning. The platform specifically considers the problem of line-following platooning with agents traveling in string formation following a line in the path. This configuration captures the essence of the underlying control problems and can be implemented avoiding complex lane detection and path-planning algorithms, reducing the cost of sensors and processing hardware. The platform provides agents equipped with sensing, actuating, and computing hardware to perform autonomous navigation over a flat surface. They also possess wireless communication interfaces for cooperative platooning schemes, external monitoring, and basic user interaction. To illustrate the potential of RUPU, we perform a set of experiments and demostrate the capability to perform repetible and reproducible experiments to validate existing theoretical results and testing of new approaches for platooning control.

ABSTRACT. This work examines whether the resolution of a programming guide is related to academic success in the introductory programming course at the Andrés Bello University (Chile). We investigated whether the guide, which consists of 52 exercises which are not mandatory to solve, helps predict the failure of the first test of this course by first-year students. Furthermore, the use of the unified SHAP and XAI framework is proposed to analyze and understand how programming guides influence student performance. The study includes a literature review of previous related studies, a descriptive analysis of the data collected, and a discussion of the practical and theoretical implications of the study. The results obtained will be useful to improve student support strategies and decision making related to the use of guides as an educational tool.

ABSTRACT. We introduce CFV2, a robot controller board made to make it easier to create mobile robots for research and education. This card was developed in accordance with the open-source philosophy in an effort to democratize robotics research and promote collaboration in technical and engineering education. Through pulse width modulation (PWM) control, independent quadrature encoder and current sensor reading, a gyroscope, an accelerometer, and signaling accessories—all coupled with a microcontroller that adds connectivity for wireless and serial communication—CFV2 enables the kinematic and dynamic control of robots with up to four motors. For a small fraction of the cost of comparable commercial systems, the CFV2 open source software enables its various stages to be configured as Robot Operating System (ROS2) nodes, simplifying their integration into high-performance robotic systems for teaching and research. This paper describes the features of CFV2 and provides an illustration of its application.

ABSTRACT. In the course of recent years, industries have implemented new technologies, currently professionals who come from university centers have a serious deficiency in their practical skills, which forces universities to improve their laboratory spaces, which is where These skills are generated. To improve these qualities in the engineering student, modern teaching equipment must be acquired, with state-of-the-art technology, which implies that more economic resources must be spent to cover these deficiencies, of the teachinglearning process. Faced with this negative situation, there is also the limitation of money, most universities have limited resources to cover this demand, for this reason, a proposal arises to develop a system that connects to the equipment that educational institutions have, but in the line of automation, that has the technology of the moment, equipment that can be moved to different spaces, that is, that is portable, thus achieving lower costs, so many elements would not be needed in a laboratory In the development of the proposal, a didactic briefcase is presented, the same one that has as main element a PLC S7 - 1200, carries all the inputs and outputs passing through the corresponding protections with cables to: terminal blocks, potentiometers, pilots lights, correspondingly, which are located in the front part of the equipment. The system variables can be visualized through an HMI. With this research, the students can implement their automation applications, to check the operation of the equipment, the didactic module is taken to the electro-pneumatics laboratory, in the binodal logic, with which, the effectiveness of the operation of the didactic briefcase is checked.