Search results for: Colombian Amazon

Authors: Andres Bautista, Alicia Porras, Juan P. Casas, Maribel Silva

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The Colombian aeronautical industry has stimulated research in the mechanical behavior of materials under different loading conditions aircrafts are generally exposed during its operation. The Calima T-90 is the first military aircraft built in the country, used for primary flight training of Colombian Air Force Pilots, therefore, it may be exposed to adverse operating situations such as hard landings which cause impact loads on the aircraft that might produce the impact fatigue phenomenon. The Calima T-90 structure is mainly manufactured by composites materials generating assemblies and subassemblies of different components of it. The main method of bonding these components is by using adhesive joints. Each type of adhesive bond must be studied on its own since its performance depends on the conditions of the manufacturing process and operating characteristics. This study aims to characterize the typical adhesive joints of the aircraft under usual loads. To this purpose, the evaluation of the effect of adhesive thickness on the mechanical performance of the joint under quasi-static loading conditions, constant amplitude fatigue and cyclic impact fatigue using single lap-joint specimens will be performed. Additionally, using a double cantilever beam specimen, the influence of the thickness of the adhesive on the crack growth rate for mode I delamination failure, as a function of the critical energy release rate will be determined. Finally, an analysis of the fracture surface of the test specimens considering the mechanical interaction between the substrate (composite) and the adhesive, provide insights into the magnitude of the damage, the type of failure mechanism that occurs and its correlation with the way crack propagates under the proposed loading conditions.

Keywords: adhesive, composites, crack propagation, fatigue

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Authors: Julian Dario Castro Cifuentes

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In Colombia, the armed conflict has lasted for more than sixty years bringing poverty, internal displacement of people, deaths from both government and insurgent forces and other violence-related problems that has damaged its social fabric. In 2016, the peace process between the Colombian government and the FARC rebels brought the possibility of ending this war and a new set of challenges to Colombian society in order to achieve pacific coexistence and reconciliation. In this scenario, there have been different efforts from diverse social actors in order to build peace and reconciliation mainly within the victims of the armed conflict. In the case of music, there have been multiple programs for social transformation through music and pedagogical experiences. Nevertheless, the need to strengthen this initiative by giving ‘peace building oriented’ pedagogical tools to the musicians that lead this experiences and understanding which aspects make this practices ‘musically meaningful’, has been recognized. For this reason, the purpose of this study is to discuss the convergences and divergences of music, and educational experiences applied to peacebuilding in the context of Colombia’s post-conflict. In this research, the hermeneutic phenomenology paradigm is applied in a case study of a peace building music education experience in the department of Nariño, Colombia articulated with the program ‘Manos a la Paz’. Two particular experiences, one on musical practice and another on music education are taken as a unit of analysis to understand its essence and structure in order to find ways to articulate efforts in peace building actions from music. This study shows how the existent gap between music experience and its subjacent pedagogical knowledge, can be reduced through deconstruction of the music and pedagogical experience. The ‘Manos a la Paz’ program showed how a peace building approach to music education can make major contributions to Pacific Coexistence and Reconciliation in Colombia’s Post-Conflict.

Keywords: music education, music for peace, music pedagogy, peace building, social fabric

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Authors: Elaine Lima Da Fonseca, Eliomar Pereira Da Silva Filho

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The modeling of areas susceptible to soil loss by hydro erosive processes consists of a simplified instrument of reality with the purpose of predicting future behaviors from the observation and interaction of a set of geoenvironmental factors. The models of potential areas for soil loss will be obtained through binary logistic regression, artificial neural networks, and support vector machines. The choice of the municipality of Colorado do Oeste in the south of the western Amazon is due to soil degradation due to anthropogenic activities, such as agriculture, road construction, overgrazing, deforestation, and environmental and socioeconomic configurations. Initially, a soil erosion inventory map constructed through various field investigations will be designed, including the use of remotely piloted aircraft, orbital imagery, and the PLANAFLORO/RO database. 100 sampling units with the presence of erosion will be selected based on the assumptions indicated in the literature, and, to complement the dichotomous analysis, 100 units with no erosion will be randomly designated. The next step will be the selection of the predictive parameters that exert, jointly, directly, or indirectly, some influence on the mechanism of occurrence of soil erosion events. The chosen predictors are altitude, declivity, aspect or orientation of the slope, curvature of the slope, composite topographic index, flow power index, lineament density, normalized difference vegetation index, drainage density, lithology, soil type, erosivity, and ground surface temperature. After evaluating the relative contribution of each predictor variable, the erosion susceptibility model will be applied to the municipality of Colorado do Oeste - Rondônia through the SPSS Statistic 26 software. Evaluation of the model will occur through the determination of the values of the R² of Cox & Snell and the R² of Nagelkerke, Hosmer and Lemeshow Test, Log Likelihood Value, and Wald Test, in addition to analysis of the Confounding Matrix, ROC Curve and Accumulated Gain according to the model specification. The validation of the synthesis map resulting from both models of the potential risk of soil erosion will occur by means of Kappa indices, accuracy, and sensitivity, as well as by field verification of the classes of susceptibility to erosion using drone photogrammetry. Thus, it is expected to obtain the mapping of the following classes of susceptibility to erosion very low, low, moderate, very high, and high, which may constitute a screening tool to identify areas where more detailed investigations need to be carried out, applying more efficient social resources.

Keywords: modeling, susceptibility to erosion, artificial intelligence, Amazon

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Authors: Rachel Danielson, Brendan Bohannan, S.M. Tsai, Kyle Meyer, Jorge L.M. Rodrigues

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The Amazon Rainforest is a global diversity hotspot and crucial carbon sink, but approximately 20% of its total extent has been deforested- primarily for the establishment of cattle pasture. Understanding the impact of this large-scale disturbance on soil microbial community composition and activity is crucial in understanding potentially consequential shifts in nutrient or greenhouse gas cycling, as well as adding to the body of knowledge concerning how these complex communities respond to human disturbance. In this study, surface soils (0-10cm) were collected from three forests and three 45-year-old pastures in Rondonia, Brazil (the Amazon state with the greatest rate of forest destruction) in order to determine the impact of forest conversion on microbial communities involved in nitrogen fixation. Soil chemical and physical parameters were paired with measurements of microbial activity and genetic profiles to determine how community composition and process rates relate to environmental conditions. Measuring both the natural abundance of 15N in total soil N, as well as incorporation of enriched 15N2 under incubation has revealed that conversion of primary forest to cattle pasture results in a significant increase in the rate of nitrogen fixation by free-living diazotrophs. Quantification of nifH gene copy numbers (an essential subunit encoding the nitrogenase enzyme) correspondingly reveals a significant increase of genes in pasture compared to forest soils. Additionally, genetic sequencing of both nifH genes and transcripts shows a significant increase in the diversity of the present and metabolically active diazotrophs within the soil community. Levels of both organic and inorganic nitrogen tend to be lower in pastures compared to forests, with ammonium rather than nitrate as the dominant inorganic form. However, no significant or consistent differences in total, extractable, permanganate-oxidizable, or loss-on-ignition carbon are present between the two land-use types. Forest conversion is associated with a 0.5- 1.0 unit pH increase, but concentrations of many biologically relevant nutrients such as phosphorus do not increase consistently. Increases in free-living diazotrophic community abundance and activity appear to be related to shifts in carbon to nitrogen pool ratios. Furthermore, there may be an important impact of transient, low molecular weight plant-root-derived organic carbon on free-living diazotroph communities not captured in this study. Preliminary analysis of nitrogenase gene variant composition using NovoSeq metagenomic sequencing indicates that conversion of forest to pasture may significantly enrich vanadium-based nitrogenases. This indication is complemented by a significant decrease in available soil molybdenum. Very little is known about the ecology of diazotrophs utilizing vanadium-based nitrogenases, so further analysis may reveal important environmental conditions favoring their abundance and diversity in soil systems. Taken together, the results of this study indicate a significant change in nitrogen cycling and diazotroph community composition with the conversion of the Amazon Rainforest. This may have important implications for the sustainability of cattle pastures once established since nitrogen is a crucial nutrient for forage grass productivity.

Keywords: free-living diazotrophs, land use change, metagenomic sequencing, nitrogen fixation

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Authors: Vishal Das, Tianyi Mao, Zhicheng Geng, Carmen Flores, Diego Pelloso, Fang Wang

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Accurate sell-in and sell-out forecasting is a ubiquitous problem in the retail industry. It is an important element of any demand planning activity. As a global food and beverage company, Nestlé has hundreds of products in each geographical location that they operate in. Each product has its sell-in and sell-out time series data, which are forecasted on a weekly and monthly scale for demand and financial planning. To address this challenge, Nestlé Chilein collaboration with Amazon Machine Learning Solutions Labhas developed their in-house solution of using machine learning models for forecasting. Similar products are combined together such that there is one model for each product category. In this way, the models learn from a larger set of data, and there are fewer models to maintain. The solution is scalable to all product categories and is developed to be flexible enough to include any new product or eliminate any existing product in a product category based on requirements. We show how we can use the machine learning development environment on Amazon Web Services (AWS) to explore a set of forecasting models and create business intelligence dashboards that can be used with the existing demand planning tools in Nestlé. We explored recent deep learning networks (DNN), which show promising results for a variety of time series forecasting problems. Specifically, we used a DeepAR autoregressive model that can group similar time series together and provide robust predictions. To further enhance the accuracy of the predictions and include domain-specific knowledge, we designed an ensemble approach using DeepAR and XGBoost regression model. As part of the ensemble approach, we interlinked the sell-out and sell-in information to ensure that a future sell-out influences the current sell-in predictions. Our approach outperforms the benchmark statistical models by more than 50%. The machine learning (ML) pipeline implemented in the cloud is currently being extended for other product categories and is getting adopted by other geomarkets.

Keywords: sell-in and sell-out forecasting, demand planning, DeepAR, retail, ensemble machine learning, time-series

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Authors: Wanderson Goncalves e Goncalves, José Alberto Silva de Sá

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Human actions are a threat to the balance and conservation of the Amazon forest. Therefore the environmental monitoring services play an important role as the preservation and maintenance of this environment. This study classified forest types using data from a forest inventory provided by the 'Florestal e da Biodiversidade do Estado do Pará' (IDEFLOR-BIO), located between the municipalities of Santarém, Juruti and Aveiro, in the state of Pará, Brazil, covering an area approximately of 600,000 hectares, Bands 3, 4 and 5 of the TM-Landsat satellite image, and Self - Organizing Maps. The information from the satellite images was extracted using QGIS software 2.8.1 Wien and was used as a database for training the neural network. The midpoints of each sample of forest inventory have been linked to images. Later the Digital Numbers of the pixels have been extracted, composing the database that fed the training process and testing of the classifier. The neural network was trained to classify two forest types: Rain Forest of Lowland Emerging Canopy (Dbe) and Rain Forest of Lowland Emerging Canopy plus Open with palm trees (Dbe + Abp) in the Mamuru Arapiuns glebes of Pará State, and the number of examples in the training data set was 400, 200 examples for each class (Dbe and Dbe + Abp), and the size of the test data set was 100, with 50 examples for each class (Dbe and Dbe + Abp). Therefore, total mass of data consisted of 500 examples. The classifier was compiled in Orange Data Mining 2.7 Software and was evaluated in terms of the confusion matrix indicators. The results of the classifier were considered satisfactory, and being obtained values of the global accuracy equal to 89% and Kappa coefficient equal to 78% and F1 score equal to 0,88. It evaluated also the efficiency of the classifier by the ROC plot (receiver operating characteristics), obtaining results close to ideal ratings, showing it to be a very good classifier, and demonstrating the potential of this methodology to provide ecosystem services, particularly in anthropogenic areas in the Amazon.

Keywords: artificial neural network, computational intelligence, pattern recognition, unsupervised learning

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Authors: Felipe Villegas-Velasquez, Harold Pantoja-Villota, Sergio Holguin-Cardona, Alejandro Osorio-Botero, Brayan Candamil-Arango

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Colombian electricity comes mainly from hydric resources, affected by environmental variations such as the El Niño phenomenon. That is why incorporating other types of resources is necessary to provide electricity constantly. This research seeks to fill the wind speed and global solar irradiance dataset for two years with the highest amount of information. A further result is the characterization of the data by region that led to infer which errors occurred and offered the incomplete dataset.

Keywords: energy, wind speed, global solar irradiance, Colombia, imputation

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Authors: Iris Maria Velez Osorio

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There has been in the last decade a concern about the environment, particularly about clean and enough water for human consumption but, some enterprises had some trouble to understand the limited resources in the environment. This research tries to understand how some industries are better oriented to the preservation of the environment through investment for strategic management of scarce resources and try in the best way possible, the contaminants. It was made an industry classification since four different group of theories for Corporate Social Responsibility agree with variables of: investment in environmental care, water protection, and residues treatment finding different levels of commitment with CSR.

Keywords: corporate social responsibility, environment, strategic management, water

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Authors: Gabriel Roveda-Hoyos, Margarita Ramirez-Gomez, Adrian Perez, Diana Paola Serralde

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The objective of this study was to determine the variability of arbuscular mycorrhizal fungi (HFMA) communities associated with wild agraz plants (Vaccinium meridionale Swartz) in the Colombian Andes. This species is one of the most promising fruits within the genus Vaccinium because of the high content of anthocyanins and antioxidants in its fruits, and like other species of the Ericaceae family, it depends on the association with HFM for its development in the natural environment. In this study, the presence of mycorrhizae in wild communities of V. meridionale was evaluated, and their relationship with the edaphic and climatic conditions of the study area was analyzed. Sampling was conducted in the rural area of the municipalities of Raquira, and Chiquinquira, Chia, and Tabio in the departments of Cundinamarca and Boyaca, Colombia. Seven sites were selected, and in each site, 5 plants were randomly selected, root and soil samples were taken from each plant in the rhizosphere zone for the quantification of colonization and the presence of spores. The samples were collected on different soils, taxonomic orders Entisols, Inceptisols, and Alfisols, located at altitudes between 2,600 and 3,000 above sea level in the Eastern Cordillera of Colombia. The physicochemical characteristics of the soil were compared with the density of spores and the percentage of presence of mycorrhizae in the roots and variables with the morphometric and physiological characteristics of the plants. Four types of mutual associations were found: arbuscular mycorrhizae, ectendomycorrhiza, ericoid mycorrhizae, and endophytic septate fungi. The main results obtained show a predominance of spores of the genera Glomus and Acaulsopora, in most of the soils analyzed. The spore density of Glomeromycete fungi in the soil varied considerably between the different sites; it was higher ( > 50 spores/g of dry soil) in soil samples with lower bulk density and higher content of organic matter; in these soils a higher cation exchange capacity was found, as well as of nitrogen, calcium, magnesium, manganese and zinc concentration. It can be concluded that Vaccinium meridionale is able to establish in a natural way, association with HFMA.

Keywords: Ericaceae, Arbuscular mycorrhizae, Andes, soils, Glomus sp.

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Authors: Magda Silva

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This paper presents the empirical and the theoretical principles associated with the Duke in Brazil Summer Program. Using a sociocultural model and critical theory, this study abroad maximizes students’ ability to enrich language competence, intercultural skills, and critical thinking. The fourteen-year implementation of this project demonstrates the global importance of foreign language teaching as the program unfolds into real life scenarios within the cultures of distinct regions of Brazil; Cosmopolitan Rio, in the southeast, and rural Belém, northern Amazon region.

Keywords: study abroad, critical thinking, sociocultural theory, foreign language, empirical, theoretical

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Authors: Ivan Stanev, Maria Koleva

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Automated software development issues are addressed in this paper. Layers and packages of a Common Platform for Automated Programming (CPAP) are defined based on Service Oriented Architecture, Cloud computing, Knowledge based automated software engineering (KBASE) and Method of automated programming. Tools of seven leading companies (AWS of Amazon, Azure of Microsoft, App Engine of Google, vCloud of VMWare, Bluemix of IBM, Helion of HP, OCPaaS of Oracle) are analyzed in the context of CPAP. Based on the results of the analysis CPAP requirements are formulated

Keywords: automated programming, cloud computing, knowledge based software engineering, service oriented architecture

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Authors: Mera-Martínez Daniela

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Dendropsophus minutus, is a species distributed in South America including the slopes of the Andes, the Amazon basin, forests of southeastern Brazil and in Guyana where tropical forests are characteristic. The relationship of amphibians found in this locality is evidenced by molecular markers, with the objective of analyzing if the geographic distance is influencing the structure of the populations of D. minutus in Guyana; we analyzed 65 sequences from the 3 localities of Guyana where haplotype networks, Mantel Test and phylogeny were realized to know the influence. It was evidenced that there is a haplotypic difference in the locality of Guyana compared to Suriname and French Guyana, but this does not have a correlation with the geographic distance, but this one can be influenced by the conditions of the places.

Keywords: phylogeography, Dendropsophus, geographic distance, molecular markers

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Authors: Qianjia Cheng, Hongquan Jiang

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Crowdsourcing solves the problems that computers can't handle by integrating computers and the Internet. Its extensive knowledge sources, high efficiency and high quality, make crowdsourcing attract wide attention in industry and academia in recent years. The development of online crowdsourcing platforms such as Clickworker and Amazon Mechanical Turk(Mturk) tend to mature gradually. This paper sorts out the concept of crowdsourcing, sorts out the workflow of competitive crowdsourcing, summarizes the related technologies of crowdsourcing based on the workflow, quality control, cost control and delay control, introduces the typical crowdsourcing platform. Finally, we highlight some open problems of the current crowdsourcing and present some future research direction in this area.

Keywords: application, crowdsourcing, crowdsourcing platform, system architecture

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Authors: Gabriel Fernando Talero Rojas, Vladimir Silva Leal, Camilo Bayona-Roa, Juan Pava, Mauricio Lopez Gomez

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The substitution of conventional aviation fuels with biomass-derived alternative fuels is an emerging field of study in the aviation transport, mainly due to its energy consumption, the contribution to the global Greenhouse Gas - GHG emissions and the fossil fuel price fluctuations. Nevertheless, several challenges remain as the biofuel production cost and its degradative effect over the fuel systems that alter the operating safety. Moreover, experimentation on full-scale aeronautic turbines are expensive and complex, leading to most of the research to the testing of small-size turbojets with a major absence of information regarding the effects in the energy performance and the emissions. The main purpose of the current study is to present the results of experimentation in a full-scale military turbojet engine J69-T-25A (presented in Fig. 1) with 640 kW of power rating and using blends of Jet A1 with oil palm biodiesel. The main findings are related to the thrust specific fuel consumption – TSFC, the engine global efficiency – η, the air/fuel ratio – AFR and the volume fractions of O2, CO2, CO, and HC. Two fuels are used in the present study: a commercial Jet A1 and a Colombian palm oil biodiesel. The experimental plan is conducted using the biodiesel volume contents - w_BD from 0 % (B0) to 50 % (B50). The engine operating regimes are set to Idle, Cruise, and Take-off conditions. The turbojet engine J69 is used by the Colombian Air Force and it is installed in a testing bench with the instrumentation that corresponds to the technical manual of the engine. The increment of w_BD from 0 % to 50 % reduces the η near 3,3 % and the thrust force in a 26,6 % at Idle regime. These variations are related to the reduction of the 〖HHV〗_ad of the fuel blend. The evolved CO and HC tend to be reduced in all the operating conditions when increasing w_BD. Furthermore, a reduction of the atomization angle is presented in Fig. 2, indicating a poor atomization in the fuel nozzle injectors when using a higher biodiesel content as the viscosity of fuel blend increases. An evolution of cloudiness is also observed during the shutdown procedure as presented in Fig. 3a, particularly after 20 % of biodiesel content in the fuel blend. This promotes the contamination of some components of the combustion chamber of the J69 engine with soot and unburned matter (Fig. 3). Thus, the substitution of biodiesel content above 20 % is not recommended in order to avoid a significant decrease of η and the thrust force. A more detail examination of the mechanical wearing of the main components of the engine is advised in further studies.

Keywords: aviation, air to fuel ratio, biodiesel, energy performance, fuel atomization, gas turbine

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Authors: Qianjia Cheng, Hongquan Jiang

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Crowdsourcing solves the problems that computers can't handle by integrating computers and the Internet. Its extensive knowledge sources, high efficiency, and high quality have made crowdsourcing attract wide attention in industry and academia in recent years. The development of online crowdsourcing platforms such as Clickworker, Amazon Mechanical Turk(Mturk) tends to mature gradually. This paper sorts out the concept of crowdsourcing, sorts out the workflow of competitive crowdsourcing, summarizes the related technologies of crowdsourcing based on workflow, quality control, cost control, and delay control, and introduces the typical crowdsourcing platform. Finally, we highlight some open problems of the current crowdsourcing and present some future research directions in this area.

Keywords: application, crowdsourcing, crowdsourcing platform, system architecture

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Authors: nafees mahbub, blake tindol, utkarsh shrivastava, kuanchin chen

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Online shopping has become an integral part of businesses today. Big players such as Amazon are setting the bar for delivery services, and many businesses are working towards meeting them. However, what happens if a seller underestimates or overestimates the delivery time? Does it translate to consumer comments, ratings, or lost sales? Although several prior studies have investigated the impact of poor logistics on customer satisfaction, that impact of under estimation of delivery times has been rarely considered. The study uses real-time customer online purchase data to study the impact of missed delivery times on satisfaction.

Keywords: LOST SALES, DELIVERY TIME, CUSTOMER SATISFACTION, CUSTOMER REVIEWS

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Authors: J. Berčík, A. Mravcová, A. Rusková, P. Jurčišin, R. Virágh

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The online world is changing every day. With this comes the emergence and development of new business models. One of them is the sale of several types of products in one place. This type of sales in the form of online marketplaces has undergone a positive development in recent years and represents a kind of alternative to brick-and-mortar shopping centres. The main philosophy is to buy several products under one roof. Examples of popular e-commerce marketplaces are Amazon, eBay, and Allegro. Their share of total e-commerce turnover is expected to even double in the coming years. The paper highlights possibilities for testing web applications and online marketplace using emerging methods like stationary eye cameras (eye tracking) and facial analysis (FaceReading).

Keywords: emerging methods, consumer neuroscience, e-commerce, marketplace, user experience, user interface

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Authors: Andrew Kurochkin, Kostiantyn Bokhan

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In this study, a new meme dataset of ~650K meme instances was created, a technology of meme generation based on the state of the art deep learning technique - GPT-2 model was researched, a comparative analysis of machine-generated memes and human-created was conducted. We justified that Amazon Mechanical Turk workers can be used for the approximate estimating of users' behavior in a social network, more precisely to measure engagement. It was shown that generated memes cause the same engagement as human memes that produced low engagement in the social network (historically). Thus, generated memes are less engaging than random memes created by humans.

Keywords: content generation, computational social science, memes generation, Reddit, social networks, social media interaction

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Authors: Cagri Baris Kasap

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In this study, how interface designers can be viewed as producers of culture in the current era will be interrogated from a critical theory perspective. Walter Benjamin was a German Jewish literary critical theorist who, during 1930s, was engaged in opposing and criticizing the Nazi use of art and media. ‘The Author as Producer’ is an essay that Benjamin has read at the Communist Institute for the Study of Fascism in Paris. In this article, Benjamin relates directly to the dialectics between base and superstructure and argues that authors, normally placed within the superstructure should consider how writing and publishing is production and directly related to the base. Through it, he discusses what it could mean to see author as producer of his own text, as a producer of writing, understood as an ideological construct that rests on the apparatus of production and distribution. So Benjamin concludes that the author must write in ways that relate to the conditions of production, he must do so in order to prepare his readers to become writers and even make this possible for them by engineering an ‘improved apparatus’ and must work toward turning consumers to producers and collaborators. In today’s world, it has become a leading business model within Web 2.0 services of multinational Internet technologies and culture industries like Amazon, Apple and Google, to transform readers, spectators, consumers or users into collaborators and co-producers through platforms such as Facebook, YouTube and Amazon’s CreateSpace Kindle Direct Publishing print-on-demand, e-book and publishing platforms. However, the way this transformation happens is tightly controlled and monitored by combinations of software and hardware. In these global-market monopolies, it has become increasingly difficult to get insight into how one’s writing and collaboration is used, captured, and capitalized as a user of Facebook or Google. In the lens of this study, it could be argued that this criticism could very well be considered by digital producers or even by the mass of collaborators in contemporary social networking software. How do software and design incorporate users and their collaboration? Are they truly empowered, are they put in a position where they are able to understand the apparatus and how their collaboration is part of it? Or has the apparatus become a means against the producers? Thus, when using corporate systems like Google and Facebook, iPhone and Kindle without any control over the means of production, which is closed off by opaque interfaces and licenses that limit our rights of use and ownership, we are already the collaborators that Benjamin calls for. For example, the iPhone and the Kindle combine a specific use of technology to distribute the relations between the ‘authors’ and the ‘prodUsers’ in ways that secure their monopolistic business models by limiting the potential of the technology.

Keywords: interface designer, cultural producer, Walter Benjamin, materialist aesthetics, dialectical thinking

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Authors: Luis Javier Serrano Tamayo

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This research on technology makes a first approach to the selection of an amphibious landing ship with strategic capabilities, through the implementation of a multi-criteria model using Analytical Hierarchical Process (AHP), in which a significant group of alternatives of latest technology has been considered. The variables were grouped at different levels to match design and performance characteristics, which affect the lifecycle as well as the acquisition, maintenance and operational costs. The model yielded an overall measure of effectiveness and an overall measure of cost of each kind of ship that was compared each other inside the model and showed in a Pareto chart. The modeling was developed using the Expert Choice software, based on AHP method.

Keywords: analytic hierarchy process, multi-criteria decision-making, Pareto analysis, Colombian Marine Corps, projection operations, expert choice, amphibious landing ship

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Authors: Mauricio Quintero Angel, Andrés A. Duque Nivia, Carlos H. Fajardo Toro

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This paper analyzes two approaches of sustainability, the weak and strong, considering a case of study of oil palm production for an industry of biodegradable detergent. In this case, a company demand the oil palm as the active element for washing and through its trademark aims to supply 10% of the Colombian market of washing powders. Under each approach the economic and ecological implications of the palm oil production and especially the implications for crop management are described. The crop production under the weak sustainability implies plantations, intensive use of agrochemicals and the inclusion of new areas of cultivation as the market grows. Under the strong sustainability the production system is limited by the productive vocation of the ecosystem, so that new approaches and creativity for making viable the nature conservancy and the business development are require.

Keywords: agriculture, environmental impacts, oil palm, strong sustainability, weak sustainability

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Authors: Sofia Stoica

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In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices in the past five years of ten major tech companies – Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We experimented with a variety of models– a linear regressor model, K nearest Neighbors (KNN), a sequential neural network – and algorithms - Multiplicative Weight Update, and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: finance, machine learning, opening price, stock market

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Authors: Shuai Zhao, Shalendra D. Sharma, Jin Xu

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This research uses advanced machine learning models to learn a number of hypotheses regarding political executives. Specifically, it analyses the impact these powerful leaders have on economic growth by using leaders’ data from the Archigos database from 1835 to the end of 2015. The data is processed by the AutoGluon, which was developed by Amazon. Automated Machine Learning (AutoML) and AutoGluon can automatically extract features from the data and then use multiple classifiers to train the data. Use a linear regression model and classification model to establish the relationship between leaders and economic growth (GDP per capita growth), and to clarify the relationship between their characteristics and economic growth from a machine learning perspective. Our work may show as a model or signal for collaboration between the fields of statistics and artificial intelligence (AI) that can light up the way for political researchers and economists.

Keywords: comparative politics, political executives, leaders’ characteristics, artificial intelligence

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Authors: Irlana C. do Mar, Thayna A. Ferreira, Dayane S. Rezende, Bruno A. M. Figueira, José M. R. Mercury

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This work presents a low-cost Mn starting material to synthesis manganese oxide octahedral molecular sieve with Mg²⁺ in the tunnel (Mg-OMS-1), based on the Mn residues from Carajás Mineral Province (Amazon, Brazil). After hydrothermal and cation exchange procedures, the Mn residues transformed to a single phase, Mg-OMS-1. The raw material and the synthesis processes were analyzed by means of X-ray diffraction (XRD), Scanning electron microscopy (SEM) and Infrared spectroscopy (FTIR). The tunnel structure was synthesized hydrothermally at 180 °C for three days without impurities. According to the XRD analysis, the formation of crystalline Mg-OMS-1 was identified through reflections at 9.8º, 12º and 18º (2θ), as well as a thermal stability around 300 ºC. The SEM analysis indicated that the final product presents good crystallinity with a homogeneous size. In addition, an intense and diagnostic FTIR band was identified at 515 cm⁻¹ related to the MnO₆ octahedral stretching vibrations.

Keywords: Mn residues , Octahedral Molecular Sieve, Synthesis, Characterization

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Authors: Clemencia Gomez

Abstract:

Geology is currently absent from Colombia's education system, leading to a lack of geological awareness that hinders essential scientific training about Earth and its spatial and temporal dimensions. Understanding geological concepts is crucial for tackling challenges like climate change, sustainable resource management, geological risk mitigation, and groundwater management. Citizens have the right to receive a comprehensive scientific education that enhances their critical thinking regarding social, environmental, and economic issues. Geological sciences are vital in this context, as they enable the sustainable use of the planet's resources and effective management of human impacts. Additionally, geoethics should be integral to every citizen's education, highlighting the necessity of responsibly utilizing natural resources found in the Earth's surface and subsurface, which are fundamental to many everyday products. The Colombian associations of Geology aims to address these gaps by advocating for the appointment of geologists in municipalities. These professionals would assist in reviewing technical aspects of urban planning, identifying geological risks, pinpointing water supply opportunities, supporting sustainable mineral-energy projects, and promoting geological education in schools. The role of a professional in Earth sciences is crucial for municipalities for several reasons: Natural Resource Management: Earth scientists help in managing and conserving natural resources such as water, minerals, and soil. Their expertise ensures sustainable use and helps prevent depletion. Environmental Protection: They assess environmental impacts and advise on policies to protect ecosystems and biodiversity. This is vital for maintaining the health of local environments. Disaster Preparedness and Response: Professionals in this field analyze geological hazards like earthquakes, floods, and landslides. They contribute to developing early warning systems and emergency response plans, which can save lives and property. Climate Change Mitigation: Earth scientists study climate patterns and contribute to strategies for mitigating climate change impacts. This includes advising on land use planning and developing resilience strategies for communities. Urban Planning and Development: Their expertise is essential in urban planning, ensuring that infrastructure development considers geological and environmental factors. This helps prevent construction in hazardous areas and promotes sustainable development. Public Education and Awareness: They play a vital role in educating the public about Earth-related issues, fostering greater community engagement in environmental conservation and disaster preparedness. In summary, professionals in Earth sciences significantly contribute to the sustainability, safety, and well-being of municipalities and their residents.

Keywords: social geology, safety, sustainability, municipalities

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Authors: Ribeiro Tiago Magalhães

Abstract:

Objective: The objective of this study was to evaluate the influence of a hydroelectric power plant in the state of Amapá, and to present the results obtained by dimensioning the diversity of the main mosquito vectors involved in the transmission of pathogens that cause diseases such as malaria, dengue and leishmaniasis. Methodology: The present study was conducted on the banks of the Araguari River, in the municipalities of Porto Grande and Ferreira Gomes in the southern region of Amapá State. Nine monitoring campaigns were conducted, the first in April 2014 and the last in March 2016. The selection of the catch sites was done in order to prioritize areas with possible occurrence of the species considered of greater importance for public health and areas of contact between the wild environment and humans. Sampling efforts aimed to identify the local vector fauna and to relate it to the transmission of diseases. In this way, three phases of collection were established, covering the schedules of greater hematophageal activity. Sampling was carried out using Shannon Shack and CDC types of light traps and by means of specimen collection with the hold method. This procedure was carried out during the morning (between 08:00 and 11:00), afternoon-twilight (between 15:30 and 18:30) and night (between 18:30 and 22:00). In the specific methodology of capture with the use of the CDC equipment, the delimited times were from 18:00 until 06:00 the following day. Results: A total of 32 species of mosquitoes was identified, and a total of 2,962 specimens was taxonomically subdivided into three genera (Culicidae, Psychodidae and Simuliidae) Psorophora, Sabethes, Simulium, Uranotaenia and Wyeomyia), besides those represented by the family Psychodidae that due to the morphological complexities, allows the safe identification (without the method of diaphanization and assembly of slides for microscopy), only at the taxonomic level of subfamily (Phlebotominae). Conclusion: The nine monitoring campaigns carried out provided the basis for the design of the possible epidemiological structure in the areas of influence of the Cachoeira Caldeirão HPP, in order to point out among the points established for sampling, which would represent greater possibilities, according to the group of identified mosquitoes, of disease acquisition. However, what should be mainly considered, are the future events arising from reservoir filling. This argument is based on the fact that the reproductive success of Culicidae is intrinsically related to the aquatic environment for the development of its larvae until adulthood. From the moment that the water mirror is expanded in new environments for the formation of the reservoir, a modification in the process of development and hatching of the eggs deposited in the substrate can occur, causing a sudden explosion in the abundance of some genera, in special Anopheles, which holds preferences for denser forest environments, close to the water portions.

Keywords: Amazon, hydroelectric, power, plants

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Authors: Maria Luisa Jaramillo, Alvaro Turriago Hoyos, Ulf Thoene

Abstract:

Financial inclusion has become a crucially important factor in debates on economic inequality posing challenges to the financial systems of countries around the world. Nowadays, governments and banks are concerned about creating products that allow access to wide sectors of the population. The creation of banking products by the financial sector for people with low incomes tends to lead to improvements in the quality of life of vulnerable parts of the population. In countries with notable social and economic inequalities financial inclusion is a key aspect for equitable economic growth. This study is based on the case of Colombia, which is a country with a strong record of economic growth over the past decade. Nevertheless, corruption, unemployment, and poverty contribute to uncertainty regarding the country’s future growth prospects. This study wants to explain the situation of financial exclusion and financial inclusion with respect to the Colombian case. Financial inclusion is going to be studied from the perspective of social innovation.

Keywords: Colombia, financial exclusion, financial inclusion, social innovation

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Authors: Maggie Shen

Abstract:

Ever since the late 20th century, business giants have been competing to provide better experiences for their users. One way they strive to do so is through more efficiently connecting users with their goals, with recommendation systems that filter out unnecessary or less relevant information. Today’s top online platforms such as Amazon, Netflix, Airbnb, Tiktok, Facebook, and Google all utilize algorithmic recommender systems for different purposes—Product recommendation, movie recommendation, travel recommendation, relationship recommendation, etc. However, while bringing unprecedented convenience and efficiency, the prevalence of algorithmic recommendation systems also influences society in many ways. In using a variety of primary, secondary, and social media sources, this paper explores the impacts of algorithms, particularly algorithmic recommender systems, on different sectors of society. Four fields of interest will be specifically addressed in this paper: economy, international relations, political ideologies, and education.

Keywords: algorithms, economy, international relations, political ideologies, education

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Authors: Eva Wagner, Lucely Vargas

Abstract:

Corporate Social Responsibility (CSR) plays an important role in (large-scale) enterprises’ business strategy in developed and emerging countries. This article approaches CSR in international comparison by examining the CSR reporting of 116 leading companies in Austria, Germany, Colombia and Chile from 2006 to 2010. We have used an independently developed scoring model which analyzes reported CSR-activities using seven dimensions to efficiently assess CSR. The study reveals that there are significant differences in CSR-commitment among countries and regions: German companies, as expected, lead most of the investigated CSR dimensions revealing stronger commitment to CSR than their Austrian, Colombian and Chilean counterparts. Even if Latin American companies lag behind their European counterparts, they exhibit high CSR-performance in the social dimension: corporate giving and philanthropic activities are firmly anchored in the tradition of Latin American companies. This indicates that particular CSR-emphases reflect the political and social circumstances of each individual country.

Keywords: corporate social responsibility, corporate social performance, international comparison

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Authors: Juan Heredia, Naci Dilekli

Abstract:

The Ecuadorian Rainforest has been polluted for almost 60 years with little to no regard to oversight, law, or regulations. The consequences have been vast environmental damage such as pollution and deforestation, as well as sickness and the death of many people and animals. The aim of this paper is to quantify and localize the polluted zones, which something that has not been conducted and is the first step for remediation. To approach this problem, multi-spectral Remote Sensing imagery was utilized using a novel algorithm developed for this study, based on four normalized indices available in the literature. The algorithm classifies the pixels in polluted or healthy ones. The results of this study include a new algorithm for pixel classification and quantification of the polluted area in the selected image. Those results were finally validated by ground control points found in the literature. The main conclusion of this work is that using hyperspectral images, it is possible to identify polluted vegetation. The future work is environmental remediation, in-situ tests, and more extensive results that would inform new policymaking.

Keywords: remote sensing, oil pollution quatification, amazon forest, hyperspectral remote sensing

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