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Predicting recreational water quality and public health safety in urban estuaries using Bayesian Networks
(Elsevier, 2024-05) Lloyd, S.; Carvajal, G.; Campey, M.; Taylor, N.; Osmond, P.; Roser, D.; Khan, S.
To support the reactivation of urban rivers and estuaries for bathing while ensuring public safety, it is critical to have access to real-time information on microbial water quality and associated health risks. Predictive modelling can provide this information, though challenges concerning the optimal size of training data, model transferability, and communication of uncertainty still need attention. Further, urban estuaries undergo distinctive hydrological variations requiring tailored modelling approaches. This study assessed the use of Bayesian Networks (BNs) for the prediction of enterococci exceedances and extrapolation of health risks at planned bathing sites in an urban estuary in Sydney, Australia. The transferability of network structures between sites was assessed. Models were validated using a novel application of the k-fold walk-forward validation procedure and further tested using independent compliance and event-based sampling datasets. Learning curves indicated the model's sensitivity reached a minimum performance threshold of 0.8 once training data included ≥ 400 observations. It was demonstrated that Semi-Naïve BN structures can be transferred while maintaining stable predictive performance. In all sites, salinity and solar exposure had the greatest influence on Posterior Probability Distributions (PPDs), when combined with antecedent rainfall. The BNs provided a novel and transparent framework to quantify and visualise enterococci, stormwater impact, health risks, and associated uncertainty under varying environmental conditions. This study has advanced the application of BNs in predicting recreational water quality and providing decision support in urban estuarine settings, proposed for bathing, where uncertainty is high.
Bibliometric analysis of energy management and efficiency in the maritime industry and port terminals: Trends
(Elsevier, 2024) Mojica, J.; Piñeres, A.; Cabello, J.; Salais, T.; Cantillo, J.; Gatica, G.
Energy management and efficiency in port terminals play a crucial role in addressing the environmental challenges of the maritime industry. This article presents a bibliometric review of the existing literature on the subject, focusing on trends in the field of energy management in port terminals. Through a systematic analysis of relevant academic articles, this study identifies key themes and emerging areas of interest. The findings highlight the growing attention to sustainable practices and energy optimization strategies in the maritime and port industry. The review reveals a growing body of research examining energy efficiency measures, renewable energy integration, and the application of advanced technologies. In addition, the analysis highlights the importance of stakeholder collaboration, policy frameworks and regulatory initiatives to promote sustainable energy management practices in port environments. This bibliometric review provides valuable information for researchers, practitioners and policy makers involved in the field of energy management in the maritime industry and port terminals. It provides a comprehensive overview of the current state of knowledge, identifies emerging trends, and points to possible areas for future research. The results of this study contribute to a better understanding of the current state of knowledge, identify emerging trends and point to possible areas for future research. The results of this study contribute to a better understanding of the challenges and opportunities associated with sustainable energy management in port terminals, facilitating the development of effective strategies to mitigate environmental impacts and optimize energy use in this critical sector.
Re-evaluating the link between the Ellsworth Mountains and East Antarctica in the Neoproterozoic: Implications for the breakup of Rodinia and the existence of Pannotia
(Elsevier, 2024-04) Castillo, P.; Poblete, F.; Fernández, R.; Bastías-Silva, J.; Fanning, M.
Our current understanding of the Ellsworth Mountains stratigraphy suggests the oldest sedimentary sequence (Heritage Group) was deposited in a Cambrian rift setting. This early Paleozoic age is then used as a key piercing point to help define Cambrian paleogeography for the southern paleo-Pacific margin of Gondwana, which places the Ellsworth Mountains between southern Africa and East Antarctica as part of West Gondwana. However, U-Pb zircon dating of a micro-diorite from the Heritage Group reveals a crystallization age of 682 ± 10 Ma, challenging chronostratigraphic and tectonic interpretations. Positive εHft and mantle-like δ18O values for these Cryogenian zircons suggest that the rifting, affecting Mesoproterozoic crust, occurred during the Cryogenian rather than in the Cambrian. This finding strongly supports a connection between the Ellsworth-Whitmore Mountain crustal block and the Transantarctic Mountains in East Antarctica prior to the amalgamation of Gondwana. It also facilitates its contextualization during the breakup of Rodinia, likely positioned close to the Shackleton Range as a continuation of the Australia-Antarctic plate, which separated from Laurentia to form the proto-Pacific Ocean in the late Neoproterozoic. This connection is supported by the U-Pb, Hf, and O data in detrital zircon grains from the lowermost units of the Heritage Group, which indicate local, East Antarctic Shield, and probable Laurentian sources. A second magmatic event in the Cambrian (516 ± 7 Ma) is recorded through zircons from a basaltic andesite within the Liberty Hills Formation, which provides an absolute depositional age for this unit. This magmatism is linked to an extensional setting, albeit distinct from that of the Cryogenian micro-diorite. The Cambrian zircons yield elevated δ18O values, indicating a strong sedimentary influence on the magma source and crustal recycling. We interpret this Cambrian extensional magmatism as a result of a tectonic escape following the collision between the East Antarctic Shield and West Gondwana/Indo-Antarctic plates, leading to the formation of Gondwana. This interpretation argues against the hypothetical Pannotia supercontinent and the proposed Cambrian rift between this sector of the paleo-Pacific margin of Gondwana and southern Laurentia.
Deep Learning based flower detection and counting in highly populated images: A peach grove case study
(Elsevier, 2024-03) Estrada, J.; Vasconez, J.; Fu, L.; Cheein, F.
Farmers and producers need to estimate crop yield in order to plan and allocate human and economic resources during the harvesting season. For many crops, such as peach groves, the number of fruits is correlated with the number of flowers produced by each tree. Therefore, estimating the number of flowers in peach groves can serve as a good indicator of crop yield, disregarding climate hazards. However, in peach groves, tree images present several challenges, including a high number of flowers, interference from distant trees, and occlusion between elements. These issues pose a difficult task for computer vision and machine learning techniques. In this study, we propose the utilization of state-of-the-art deep learning techniques for image detection purposes; namely the YOLO architectures on its versions 5, 7, and 8 and their different size models (n, s, m, l, x); as well as predicting object density using multi-column in densely populated images, using a multi-column deep neural network. The methodology was tested on a new dataset comprising 600 images of peach trees during the blooming season, in the region of Catalonia, Spain. Out of these, 400 images were used to train the model, while 100 were allocated for testing and another 100 for validation. The counting results were evaluated using metrics such as Mean Squared Error (MSE), Mean Absolute Error (MAE), and percentage error (%Err). For the detection algorithms, metrics such as accuracy, precision, recall, and mean average precision were utilized, alongside metrics for evaluating the counting process. The experiments demonstrated that predicting the density map yielded better results in the counting process, achieving an MAE of 39.13, RMSE of 69.69, and a percentage error of 9.98. The detection algorithm that exhibited superior performance was YOLOv7x, with metrics of MAE 152.7, RMSE 212.9, and a percentage error of 29.7 %. These results indicate that, for counting purposes, predicting the density map produced better overall outcomes.
Earthquake and tsunami preparedness between residents and tourists in coastal communities
(Elsevier, 2023-10) Cisternas, P.; Cifuentes, L.; Bronfman, N.; Repetto, P.; Castañeda, J.
Earthquakes and tsunamis are natural phenomena that trigger severe consequences for communities. Compared to residents, tourists are more vulnerable to natural hazards, mainly due to a lack of knowledge of the territory hazards, alert signs, and the local language. To encourage disaster preparedness behavior, this study explored the differences in risk perception, trust in authorities, and preparedness for earthquakes and tsunamis between residents and tourists in a coastal city highly exposed to seismic activity. A survey was implemented in a sample of residents (n = 548) and tourists (national n = 194; international n = 38) in a coastal city in Chile. The questionnaire evaluated perceived risk and perceived consequences, trust in authorities, and the participants' preparedness level against earthquakes and tsunamis. The findings reveal that international tourists perceived lower risk and consequences and higher trust in authorities than national tourists and residents. On the contrary, residents demonstrated higher levels of preparedness, reflecting their familiarity with the hazards and evacuation signage. The results highlight the importance of personalized strategies to increase tourist preparedness (both national and international). Implications and strategies are addressed in the study.
Accident Risk Detection in Urban Trees using Machine Learning and Fuzzy Logic
(Elsevier, 2022) Ramírez, G.; Salazar, K.; Barria, V.; Pinto, O.; San Martin, L.; Carrasco, R.; Fuentealba, D.; Gatica, G.
Knowing the state of trees and their associated risks contribute to the care of the population. Machine Learning, through supervised learning, has demonstrated its effectiveness in various areas of knowledge. The risk of accidents can be predicted by having different tree data, including height, species, condition, presence of pests, the area where it is planted, climatic events, and age. This work proposes a platform to register trees and predict their risk. The solution considers integrating technology and applications for those in charge of maintenance and changes in current procedures. The risk prediction process is carried out through a fuzzification process that contributes to the responsible entities’ decision-making. Preliminary results of this research are presented, and the capacity of the developed software architecture is demonstrated, where the scalability of the prediction algorithm stands out.
Bibliometric behavior of big data and digital marketing as real-time multimedia
(Elsevier, 2024) Ramírez, R.; Santamaria, M.; Monsalve, L.; Lay, N.; Hinojoza-Montañez, S.; García, M.
Technological trends such as big data have generated interest in its application in digital marketing, due to the ease of precision in business and in daily decision-making, where there is a need to respond to the needs of the market in real time and achieve competitiveness. We aim to describe the bibliometric behavior of big data and digital marketing as real-time multimedia applications during the period from 2012 to 2023. We based our methodology on the bibliometric analysis of statistical relationships using VOSviewer software. We employed the normalization technique and applied the association strength method for keyword co-occurrence analysis and author co-citation analysis. Additionally, we used the hermeneutic technique to interpret the results. The findings indicate that research trends are associated with social networks; data processing; machine learning techniques; real-time system; online system; data analysis; data management. The contributing authors were Wang Y.; Chen Y.; Liu Y.; Zhang X.; Wang X.; Wang J.; Zhang Y.; Li J. We concluded that the common software in the study includes Hadoop, Reduced Map, Apache Spark, Twitter, Apache Storm, Spark Transmission, Transformer, and Weibo.
Pricing for urban areas using queuing theory
(Elsevier, 2022) Rios, J.; Morillo-Torres, D.; Olmedo, A.; Coronado-Hernandez, J.; Gatica, G.
By reducing traffic congestion in large cities and providing a safe place to leave vehicles while their owners are doing their activities, parking facilities play an important role in society by reducing congestion and the negative externalities (e.g. CO2 generation, noise, congestion) caused by vehicular traffic, being this one detrimental to society. Additionally, parking lots must establish strategies that allow them to be profitable and remain competitive. We determined the rate of a parking lot with a 20% margin, considering the rate of actual arrivals and the lost arrivals rate when the parking lot is full and the time a vehicle spends in the parking lot. In the results we found the queuing theory is applied to a private parking lot, in addition to establishing an optimal pricing policy, operating policies are established that allow it to generate additional revenue.
A faster optimal model slotting in rack positions with mono SKU pallet
(Elsevier, 2022) Rios, J.; Morillo-Torres, D.; Olmedo, A.; Coronado-Hernandez, J.; Gatica, G.
The warehouse, with its racking positions, oversees regulate the flow of goods in the distribution center (DC). An adequate distribution of the products in the warehouse (slotting), reduces the operating picking times once is done by a full pallet. This paper presents a mathematical model that optimizes slotting times in a selective shelving and random storage warehouse. The model places the products with the highest turnover rate and ABC inventory valuation close to the dispatch area. In addition, it places high-value products on the upper shelf levels and heavy pallets on the lower levels. The results applied to a company dedicated to the manufacture of cellulose pulp and derivatives, obtained a 19.24% reduction in operating time.
Quantitative Estimation of Demand for Conveyor Belt Supplies
(Elsevier, 2022) Nuñez-Uribe, C.; Olmedo, A.; Ríos, J.; Coronado-Hernández, J.; Morillo, D.; Gatica, G.; Umaña-Ibáñez, S.; Cabrera, G.
Demand forecasts provides quantitative data to estimate, with a reasonable degree of certainty, customers’ requirements of a company. Applying this tool in manufacturing companies allows them to generate predictions for decision making. Forecasts have a transverse impact on finances, human resources, inventories, and production, among others. In Chile, qualitative models are used to make these estimates based on information from the sales force, customers, or group of experts. This article incorporates three exponential smoothing models into these estimates. Data is available from a manufacturing company (2016 to 2019); it is used to make comparisons and adjustments to select, the best model for each product. Also, a correlation and covariance analysis is carried out between the inputs, to determine the degree of relationship between the products and thus project their demand.
L-PECS: Application for Inclusive Work Environments
(Elsevier, 2021) Lagos, P.; Baeza, R.; Pinto, O.; Costa, G.; Ruete, D.; Fuentealba, D.; Gatica, G.
Children with ASD may show permanent communication problems due to a decline in the effectiveness of persistence of the information transacted. L-PECS is an application for Android smartphones that uses an alternative language called PECS, based on image exchange. L-PECS allows to improve the persistence of information in work contexts, generating effective communicational instances, task follow-up, and supporting the labor insertion of people with ASD. This work performed user interface tests, user action tests, usability, and accessibility tests on 20 users operating L-PECS to define and show possible behaviors. L-PECS can encourage the hiring of people with ASD.
Analysis of Self-efficacy and Attitude-mediated Inclusivity in Higher Education: A Case Study on the Colombian North Coast
(Elsevier, 2024) Quintero, R.; Pertuz, L.; Mosalvo, J.; Amador, E.; Portnoy, I.; Acuña-Rodríguez, M.; Córdova, A.
Inclusivity is a fundamental principle of education worldwide as it fosters the general well-being of students, educators, and other parties in the education sector. Moreover, inclusive education is a multidimensional phenomenon that many factors can influence. Thus, understanding the underlying interactions between those factors fostering inclusivity may help to inform decisions taken by the involved parties, such as education-related policymakers. This study examines the relationship between self-efficacy and the attitudes of higher education teachers toward inclusive education. We applied two psychometric survey-like instruments: the Self-Efficacy Scale for Inclusive Teaching Practices and the University and Disability Issues Scale. The study cohort comprised 68 higher education professors from universities in Barranquilla on the Colombian North Coast. We found that professors exhibiting favorable attitudes to adjusting the curricula, as well as higher sensitization and relationships with students in situations of disability, are prone to perceive higher self-efficacy and less extra burden arising from the tasks associated with inclusive education.
Test of Understanding Graphs in Calculus: Test of students' interpretation of calculus graphs
(Modestum LTD, 2017) Dominguez, Angeles; Barniol, Pablo; Zavala, Genaro
Studies show that students, within the context of mathematics and science, have difficulties understanding the concepts of the derivative as the slope and the concept of the antiderivative as the area under the curve. In this article, we present the Test of Understanding Graphs in Calculus (TUG-C), an assessment tool that will help to evaluate students' understanding of these two concepts by a graphical representation. Data from 144 students of introductory courses of physics and mathematics at a university was collected and analyzed. To evaluate the reliability and discriminatory power of this test, we used statistical techniques for individual items and the test as a whole, and proved that the test's results are satisfactory within the standard requirements. We present the design process in this paper and the test in the appendix. We discuss the findings of our research, students' understanding of the relations between these two concepts, using this new multiple-choice test. Finally, we outline specific recommendations. The analysis and recommendations can be used by mathematics or science education researchers, and by teachers that teach these concepts. © Authors.
Relationship between social vulnerability and community resilience: A geospatial study in the context of natural disasters
(Elsevier, 2024-10) Bronfman, N.; Guerrero, N.; Castañeda, J.; Cisternas, P.; Repetto, P.
Social vulnerability and resilience are critical factors for disaster risk management. Despite the significant progress in research on both concepts, only some studies have explored the empirical relationship between them. The relationship between community resilience and social vulnerability to natural disasters in Chile was studied using empirical and geospatial analysis. We used the Social Vulnerability Index (SoVI) and the Community Resilience Index (BRIC), previously calculated nationally for Chile. Based on these indicators, we constructed a matrix to classify the 3100 districts into high, medium, and low levels of vulnerability and resilience. In addition, we performed a spatial autocorrelation analysis using the Global Moran Index. Our results indicate that: Vulnerability and resilience are related concepts, but are not opposite within a continuum, (II) Rather than being randomly distributed, districts with higher (or lower) capacities to prepare for, respond to, and recover from a disaster tend to cluster geographically; (III) the districts with the highest levels of resilience and lowest levels of vulnerability were located in the main cities of the country. We expect that a better understanding of the relationship between vulnerability and resilience in each territory will help institutions in charge of disaster management to identify communities most susceptible to damage and least capable of recovering from a disaster. Consequently, it will facilitate the design and implementation of policies, programs, and plans best adapted to the needs of each community.
Maintenance Process Analysis in a Port Cargo Company through Discrete Event Simulation
(Elsevier, 2024) Corrotea, H.; Portales, H.; Amigo, L.; Gatica, G.; Troncoso-Palacio, A.; Mondragón, D.; Ramos, M.
Cargo transfer is a key procedure in port businesses; nevertheless, the electromechanical equipment employed for maintenance should adhere to a set of standards to ensure its proper operation all the time, which may raise production costs. Because of this, every improvement that enables minimizing production losses and expenses over the short, medium, and long time is a decisive choice that companies should consider becoming sustainable. Under this policy, the maintenance process has assumed a significant role as an integral part of the manufacturing process and not only as a dependency of the company. In this study, proposals for improving a port company's maintenance procedure will be analyzed using the discrete event simulation technique. The findings at the task execution stage reveal delays or queues that have a direct impact on the overall time necessary to accomplish maintenance. The reason that the equipment in the locations is not available on time could be due to a lack of supplies or replacement parts required to finish the repair. This has a negative impact on the scheduled maintenance times. Additionally, the simulation results show that incorporating one person into the process improves reaction times. However, the final recommendation is that a future role or workload study should be carried out instead of hiring other employees and, if possible, redistributing workloads among the people who are part of the company.
A preliminary risk assessment in naval Antarctic expeditions
(Elsevier, 2024) Coronado-Hernandez, J.; Rios-Angulo, W.; Ospino, M.; Tarra, P.; Costa, G.
In this work to implement the Risicar methodology and propose a risk overview to facilitate and encourage traveling in a Ship to the Antarctic continent to carry out scientific expeditions would use this method to treat possible risks to which they may be exposed. The results of this method were determinates the possible risks of these expeditions were identified and classified, evaluated, and treated, facilitating the risk management of the deck operations.
A Mixed Integer Programming optimization model for mining truck dispatch policies using traffic constraints: Case of a copper mine in northern Chile
(Elsevier, 2024) País, G.; Obredor-Baldovino, Th.
Productivity in open pit operations in the mining industry is conditioned by the manual assignment of trucks by the dispatcher, who does not have the ability to find the optimal policy by himself, having many variables that consider. To this end, an MIP optimization model is proposed that considers the scheduling of a discretized operating shift in smaller stages that consider positions and capacities of available trucks, and congestion based on a differential speed based on the number of trucks in different sections of the transport route. The model seeks to prioritize the transfer of material to crushers and meet material goals during the planning horizon. Preliminary results indicate that it is possible to reduce the violation of the production plan by destination by 12% and increase productivity by 46% with respect to the state of the art of similar solutions.
Predicting the concentration range of trace organic contaminants in recycled water using supervised classification
(Elsevier, 2024-02) Farzanehsa, M.; Carvajal, G.; McDonald, J.; Khan, S.
Trace Organic Contaminants (TrOCs) have evidence for many health and environmental issues. Frequent monitoring of TrOC concentration is a time-consuming and costly process, which cannot be achieved easily. Identifying surrogate markers for these contaminants is a practical solution to monitor and ensure water quality. However, this topic is seldom explored in previous literature. This study aimed to find surrogate markers to predict concentration class (i.e., three classes: low concentration, medium concentration, high concentration) for a set of widely used pharmaceutical and personal care product TrOCs (e.g., Fluoxetine, Primidone, Saccharin, Sucralose to name a few) in recycled water from Melbourne Eastern Treatment Plant (ETP), Melbourne, Australia. For this purpose, three popular supervised learning classification algorithms namely Naïve Bayes, Random Forest and Support Vector Machines were utilized. Physicochemical parameters colour, Chemical Oxygen Demand (COD) and Total Organic Carbon (TOC) were found to be the top three predictive features for the majority of the investigated TrOCs. UV Transmittance (UVT) and the total amount of suspended solids (TSS) were the next frequent features. The Random Forest model resulted in the highest classification accuracy (≥73 %) for the majority of compounds. This paper presents evidence that with the acquired intelligence of supervised machine learning, the concentration range of hard to measure TrOCs in water can be predicted from a handful of low-cost and easy-to-measure physicochemical parameters.
A CHASIDE Test-based Analysis for Identifying Adolescents Characteristics Impacting their Vocational Orientation: Case of private schools in the city Barranquilla, Colombia
(Elsevier, 2024) Acosta, C.; Acuña-Rodríguez, M.; Peñaranda-Osorio, E.; Gatica, G.; Córdova, A.
This research is oriented to the identification of characteristics in the choice of professional careers in adolescents in eleventh grade. A total of 270 young people between the ages of 15 and 20 years old, all students at private schools in the city of Barranquilla, Colombia, were surveyed. A test called CHASIDE was used, which is focused on the occupational environment. Among the results, we found career options chosen by the students, the different inclinations in the workplaces where they plan to work, competencies in adolescents regarding the choice of career, and the identification of learning channels according to areas of knowledge. In the future, we seek to analyze whether there is a relationship between learning channels, personality, and career choice, and thus develop technological tools and algorithms for career choice, in order to address career orientation as the main axis of success in higher education.
Modeling hospital logistics capacity through system dynamics during the COVID-19 pandemic: case of Pasco Healthcare Network in Peru
(Elsevier, 2024) Lock, R.; Benavente, Y.; Gatica, G.; Olivares, P.; Ramirez, J.; Gonzalez-Holgado, A.
The present investigation, whose main objective is based on modeling the hospital logistics capacity in the Pasco Healthcare Network (Peru) through Systems Dynamics during the first and second wave of the appearance of the SARS-COVid-2 virus, oriented towards a study in the capacity to respond to the most intense health emergency in recent decades. In the first instance, the reality of the studied system was made known, which was possible thanks to the information provided by the actors that make up the hospital logistics capacity, sources uploaded to the WHO worldwide. Afterwards, we proceeded to characterize the variables that make up the system, prioritizing each of these through the application of a structural analysis that measured the levels of influence between one variable and another. Because of this, we proceeded to create the causal diagram, and likewise facilitate the inclusion of the network model through the Stella software. Once the model has been simulated, the results obtained are reported.

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