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Green building's heat loss reduction analysis through two novel hybrid approaches
No full textOne of the key reasons for the performance discrepancy between a building's intended usage and the actual operation is Heat Loss, which describes a building's envelope efficiency during in-use circumstances. In this setting, the ANN models’ use for energy analysis of green buildings has become more established. This research aims to anticipate the heat loss of green buildings utilizing two artificial neural network-based methodologies (ANN). In particular, TLBO and BBO are used and contrasted. Additionally, RMSE, MAE, and R2 are used to calculate an absolute error for predicting heat loss to gauge the accuracy of the findings. The suggested TLBO-MLP standard is a reliable method with a positive outcome (RMSE = 0.01012 and 0.05216, and R2 = 0.99536 and 0.9651). Also, according to the training error ranges of [−0.0006078, 0.01133] and [−0.00040708, 0.010181] and testing error ranges of [0.0004724, 0.068666] and [0.0021984, 0.057688] for BBO-MLP and TLBO-MLP, respectively, shows that the TLBO-MLP reaches the lower range of error and can predict the heat loss with higher accuracy and it could properly forecast the heat loss of building technologies. Even so, the BBO-MLP standard provides this research with satisfactory performance (R2 = 0.9943 and 0.95175, and RMSE = 0.01122 and 0.06112). To increase the precision of calculating the heat loss of buildings, specifically integrating them with optimization algorithms, further study is required
Recommendations for coastal planning and beach management in Caribbean insular states during and after the COVID19 pandemic
Get PDFThe COVID-19 pandemic has implications for coastal planning and management. Rules for isolation and physical distancing, among other measures for human life protection, have led to the closure of most beaches around the world. The present critical situation has raised the following question: How can some recommendations be designed in sun, sea, and sand tourism-dependent-insular countries to face “the COVID-19 new normality?” We used the content analysis technique to analyze representative publications on a global level to ascertain information on best management practices. A survey of 58 experts provided additional information. We used inferential statistics for sample selection and produced a list of 43 practices and beach planning and management actions to face the COVID-19 pandemic. This led to 27 new recommendations designed for beach planning and management within insular contexts, some of which were tested in the Republic of Cuba. Recommendations aim to guarantee a culture of safety and improvement within the field of beach or coastal planning and management. These recommendations should prove useful for other insular countries, during the COVID-19 period, in the new normality that follows, and in other post-pandemic scenarios.Milanes, Celene B.-will be generated-orcid-0000-0003-2560-8859-600PÉREZ MONTERO, OFELIA-will be generated-orcid-0000-0002-3423-9744-600Cabrera, J. AlfredoCuker, Benjamin-will be generated-orcid-0000-0002-8024-9628-60
Composite carbon materials from winery composted waste for the treatment of effluents contaminated with ketoprofen and 2-nitrophenol
Get PDFThe present work consisted of preparing and characterizing composite carbon materials (WRCC) from raw winery residues (WR) activated with zinc chloride to produce a carbon adsorbent. The WRCC was used for the adsorption of emerging contaminants in aqueous media. The WRCC presented a morphology with favorable characteristics for the adsorption process, giving an abundant porous structure with pores of different sizes. The results show the WRCC’s effectiveness, presenting surface area values (227 m2 g−1) and total pore volume (0.175 cm3 g−1). The general order kinetic model predicted the experimental curves sufficiently. The Sips model better described the two adsorbates' equilibrium data, with maximum adsorption capacities of 376.0 and 119.6 mg g−1 for 2-nitrophenol and ketoprofen, respectively. The WRCC carbon material was also highly efficient, with maximum removal of 81.4% and 94% in 1000 mg L−1 of the compounds 2-nitrophenol and ketoprofen. Finally, the prepared material has essential characteristics that make it an efficient adsorbent in treating effluents with emerging contaminants.Silva, Nathália F.Netto, Matias S.Silva Oliveira, Luis FelipeMallmann, Evandro S.Lima, Eder Claudio-will be generated-orcid-0000-0002-8734-1208-600Ferrari, ValdecirDotto, Guilherme Luiz-will be generated-orcid-0000-0002-4413-8138-60
Ivermectin adsorption by commercial charcoal in batch and fixed-bed operations
No full textEmerging contaminants were used during the COVID-19 pandemic, including ivermectin. Studies that limit the optimal adsorption parameters of ivermectin are scarce in the literature. In this study, we analyzed the adsorption of ivermectin with a high surface area and porosity charcoal. Isotherms were better fitted to the Koble-Corrigan model. The maximum capacity was 203 μg g−1 at 328 K. Thermodynamics indicated a spontaneous and endothermic behavior. The equilibrium was quickly reached within the first few minutes regardless of the ivermectin concentration. The linear driving force (LDF) model fitted the kinetic data (qexp = 164.8 μg g−1; qpred = 148.1 μg g−1) at 100 μg L−1 of ivermectin. The model coefficient (KLDF) and diffusivity (Ds) increased with increasing drug concentration. Two sloped curves were obtained in the column experiments, with a breakthrough time of 415 min and 970 min. The capacity of the column (qeq) was 76 μg g−1. The length of the mass transfer zone was 9.04 and 14.13 cm. Therefore, it can be concluded that the adsorption of ivermectin is highly sensitive to changes in pH, being favored in conditions close to neutrality. Commercial activated charcoal was highly efficient in removing the studied compound showing high affinity with very fast kinetics and a good performance in continuous operation mod
Implementation of deep neural networks and statistical methods to predict the resilient modulus of soils
No full textThe Resilient Modulus (Mr) is perhaps the most relevant and widely used parameter to characterise the soil behaviour under repetitive loading for pavement applications. Accordingly, it is a crucial parameter controlling the mechanistic-empirical pavement design. Nonetheless, determining the Mr by laboratory tests is not always possible due to the high consumption of time and financial resources. Thus, developing new indirect approaches for estimating the MR is necessary. Precisely, this article investigates the application of Deep Neural Networks (DNNs) and statistical methods to predict the Mr of soils. For that purpose, the Long-Term Pavement Performance (LTPP) database was implemented. It includes 64 701 datasets resulting from coarse-grained and fine-grained soil samples considering a wide range of grain size distribution and subjected to different stress levels. The input parameters were the bulk stress, octahedral shear stress, and the percentage of soil particles passing through the different sieves (3”, 2”, 3/2”, 1”, 3/4”, 1/2”, 3/8”, No. 4, No. 10, No. 40, No. 80, and No. 200) and the output was the Mr. The results suggest that while conventional mathematical models are unable to predict the influence of the grain size distribution and stress level on the Mr, the proposed DNNs were able to reproduce very accurate predictions. Notably, the proposed computational models have been uploaded to a GitHub repository and have become a valuable tool for forecasting the Mr when experimental measurements are not feasibl
Intelligent multi-tariff payment collection system for inter-municipal buses in the department of Atlántico – Colombia
No full textIn the department of Atlántico-Colombia, inter-municipal transport companies operate that mobilize 325,000 people daily. The nature of inter-municipal transport makes it very difficult for companies and vehicle owners to have real control of the income of each bus because, unlike urban transport, the value of the ticket depends on the place of getting on and off each bus. One of the main motivations of this research is to help solve the problems associated with the management of drivers who usually hire assistants who manually and visually control each passenger’s entry and exit points and, according to this criterion, calculate the amount to be paid. Charge individually. Since there is no certainty of the actual monetary income from the buses, companies and owners charge drivers a fixed daily value (fee). The objective of the platform described in this article is to manage the analysis of economic resources generated in public transport activity. This form of work affects the formality of the transport sector and generates a loss of competitiveness in the department Atlántico – Colombia
Gait-Based biometrics system
No full textBehavioral biometrics is the field of study related to person identification based on the way an activity is performed. Despite the difficulties of implementation and achieving high recognition metrics, this field has advantages that attract the interest of the scientific community. In the case of gait analysis, active interaction between the user and the acquisition device is not required. This enables signals to be safely assessed remotely, that is important in the times of pandemic. Furthermore, it is not easy to deliberately mimic a person’s gait. The work concerns on the development of system that enables identifying individuals based on gait with the use of wearable sensors such as accelerometers or gyroscopes. The work describes the data preprocessing pipeline and the innovative data augmentation mechanism performed with the use of generative models. The validation of the system is carried out using three different datasets collected under laboratory, semi-laboratory and field conditions. This article focuses on presenting a comprehensive solution, with a special authors’ aspect of data augmentation
Using discrete event simulation to muck development planning in underground mining
No full textIn underground mining operations around the world, planning for muck removal has become a big problem. Therefore, it realizes a discrete event simulation analysis of a system of four interconnected mines that use the same routes between them. The results of the analysis make it possible to evaluate the congestion presented at specific points along an interconnection route between equipment and activities. Therefore, it is concluded that it is important to have specific places for the removal of debris because these can cause the completion date of the project to be delayed
Machine Learning techniques applied to the consumption of illegal psychoactive substances: A systematic mapping
No full textIntroducción— El consumo de sustancias psicoactivas ilícitas es una problemática que se vive a diario, donde personas de diferentes edades se han visto implicadas, resaltando que muchas de estas sustancias generan trastornos tales como, por ejemplo: la Marihuana o cannabis: su consumo afecta la función cerebral de manera directa, y particularmente las partes del cerebro responsables de la memoria, el aprendizaje, la atención, la toma de decisiones. El Bazuco: es una sustancia tóxica, cuyos principales riesgos de consumirla se reflejan en el deterioro neurológico y en el organismo, y es muy rápida su disolución en el torrente sanguíneo, aspecto que hace que sea muy adictiva. La Cocaína: su consumo afecta directamente el sistema nervioso y el resto del organismo de forma inmediata, en estas afectaciones se encuentran vasoconstricción, midriasis, hipertermia, taquicardia e hipertensión. La Heroína: es una sustancia altamente adictiva, inicialmente, sus efectos son muy placenteros, lo que propicia una conducta de consumo continuada y repetitiva, además, produce sensaciones de sequedad en la boca, enrojecimiento y acaloramiento de la piel, pesadez en brazos y piernas, náuseas y vómitos, comezón intensa y enturbiamiento de las facultades mentales.
Objetivo— Esta problemática es algo que resalta mucho y de gran impacto en los jóvenes de acuerdo al contexto en el que se encuentren ya que hoy en dia hay mucha facilidad para obtener este tipo de sustancias, por ende, se han planteado una serie de trabajos que abordan desde la inteligencia artificial esa problemática.
Metodología— El presente estudio realiza una revisión de 50 publicaciones relacionadas con el uso de métodos y técnicas de ML aplicadas al consumo de sustancias psicoactivas ilícitas.
Resultados— De las publicaciones incluidas se hallaron temáticas en común por lo que se hace un resumen de los artículos seleccionados por cada temática y se describen brevemente los métodos adoptados, así como también una comparativa entre ellos, anotando los métodos usados, sus resultados y demás factores importantes de la aplicación o modelo en distintas áreas y se concluye con una serie de propuestas sobre las líneas que a futuro podrían encaminar la investigación en este campo.Introduction— The consumption of illicit psychoactive substances is a problem experienced every day, by people of different ages who have been involved in it, highlighting that many of these substances generate disorders such as, for example: Marijuana or cannabis: its consumption affects brain function directly, and particularly the parts of the brain responsible for memory, learning, attention, decision making. Bazuco: it is a toxic substance, which main risks of consumption are reflected in the neurological deterioration and in the organism, and its dissolution in the bloodstream is very fast, an aspect that makes it very addictive. Cocaine: its consumption, directly affects the nervous system and the rest of the organism immediately, these affectations include vasoconstriction, mydriasis, hyperthermia, tachycardia and hypertension. Heroin: is a highly addictive substance, initially, its effects are very pleasant, which leads to a continuous and repetitive consumption behavior, in addition, it produces sensations of dry mouth, reddening and heating of the skin, heaviness in arms and legs, nausea and vomiting, intense itching and clouding of the mental faculties.
Objective— This problem is something that stands out a lot and has a great impact on young people according to the context they are in, since nowadays it is very easy to obtain this type of substances, therefore, a series of works have been proposed that address this problem from artificial intelligence.
Methodology— The current study is a review of 50 publications related to the use of ML methods and techniques applied to the consumption of illicit psychoactive substances.
Results— From the publications included, common themes were found, so a summary is made of the articles selected for each theme and the methods adopted are briefly described, as well as a comparison between them, noting the methods used, their results and other important factors of the application or model in different areas, and concluding with a series of proposals on the lines that could guide future research in this field
Impact of attention deficit hyperactivity disorder on entrepreneurial behavior: a neurobiological approach
No full textThe objective of this study is to determine the relationship between Attention Deficit Hyperactivity Disorder (ADHD) and entrepreneurial behavior, especially in
characteristics such as risk-taking, creativity, and decision-making. Three groups of ten individuals (5 women; age 36.3 ± 14.0) were selected using social media
platforms: one group with ADHD (four participants), one group of entrepreneurs (three participants), and one control group without ADHD or entrepreneurial experience (three participants). 10-question interviews, tailored to their respective profiles, were conducted individually via Zoom. After interviews transcriptions,
significant statements were extracted for data analysis. Participants were also instructed to play the Iowa Gambling Task (IGT) from an online platform to assess decision-making and risk-taking. Individual data were compiled, compared and statistically processed with Microsoft Excel. As results, comparing interview
statements between individuals with ADHD, entrepreneurs, and the control group, in terms of risk-taking, attention, and creativity showed that individuals with
ADHD can bring unique traits and skills to entrepreneurship, while entrepreneurs have specific strategies for managing distractions and maintaining focus. The
control group emphasizes organization and analysis rather than creativity. The findings from the IGT suggested that people with ADHD may exhibit impulsive
tendencies and difficulty evaluating the long-term consequences of their actions. Entrepreneurs were willing to take calculated risks to seize opportunities and
achieve their goals, and they were also aware of the need to limit risk and make prudent decisions to protect their investments. The control group highlighted the
individual differences in risk-taking in randomly selected individuals, without any special condition. They showed a certain caution in opting for low-risk choices.
In conclusion, the study underscores the importance of considering individual and contextual factors in decision-making processes, incorporating neurobiological
aspects of ADHD. Although available data did not directly examine the influence of these factors on entrepreneurship success, it highlights the significance of
understanding the complex influences involved in decision-making.El objetivo de este estudio es determinar la relación entre el Trastorno por Déficit de Atención con Hiperactividad (TDAH) y el comportamiento emprendedor, especialmente en características como la asunción de riesgos, la creatividad y la toma de decisiones. Se seleccionaron tres grupos de diez individuos (5 mujeres; edad 36,3 ± 14,0) utilizando plataformas de medios sociales: un grupo con TDAH (cuatro participantes), un grupo de emprendedores (tres participantes) y un grupo de control sin TDAH ni experiencia emprendedora (tres participantes). Las entrevistas de 10 preguntas, adaptadas a sus respectivos perfiles, se realizaron individualmente a través de Zoom. Tras la transcripción de las entrevistas, se extrajeron las afirmaciones significativas para el análisis de los datos. También se indicó a los participantes que jugaran a la Iowa Gambling Task (IGT) desde una plataforma en línea para evaluar la toma de decisiones y la asunción de riesgos. Los datos individuales se recopilaron, compararon y procesaron estadísticamente con Microsoft Excel. Como resultados, la comparación de las declaraciones de las entrevistas entre individuos con TDAH, emprendedores y el grupo de control, en términos de asunción de riesgos, atención y creatividad, mostró que los individuos con TDAH pueden aportar rasgos y habilidades únicos a la iniciativa empresarial, mientras que los emprendedores tienen estrategias específicas para gestionar las distracciones y mantener la concentración. El grupo de control pone más énfasis en la organización y el análisis que en la creatividad. Los resultados del IGT sugirieron que las personas con TDAH pueden mostrar tendencias impulsivas y dificultad para evaluar las consecuencias a largo plazo de sus acciones. Los empresarios estaban dispuestos a asumir riesgos calculados para aprovechar las oportunidades y alcanzar sus objetivos, y también eran conscientes de la necesidad de limitar el riesgo y tomar decisiones prudentes para proteger sus inversiones. El grupo de control puso de manifiesto las diferencias individuales en la asunción de riesgos en individuos seleccionados al azar, sin ninguna condición especial. Mostraron cierta cautela a la hora de optar por opciones de bajo riesgo. En conclusión, el estudio subraya la importancia de considerar los factores individuales y contextuales en los procesos de toma de decisiones, incorporando los aspectos neurobiológicos del TDAH. Aunque los datos disponibles no examinaron directamente la influencia de estos factores en el éxito empresarial, pone de relieve la importancia de comprender las complejas influencias que intervienen en la toma de decisiones