Evaluation of the effectiveness of an organization in the field of brand perception using a computer agent-based simulation system

Este proyecto de investigación busca usar un sistema de cómputo basado en modelación por agentes para medir la percepción de marca de una organización en una población heterogénea. Se espera proporcionar información que permita dar soluciones a una organización acerca del comportamiento de sus consumidores y la asociada percepción de marca. El propósito de este sistema es el de modelar el proceso de percepción-razonamiento-acción para simular un proceso de razonamiento como el resultado de una acumulación de percepciones que resultan en las acciones del consumidor. Este resultado definirá la aceptación de marca o el rechazo del consumidor hacia la empresa. Se realizó un proceso de recolección información acerca de una organización específica en el campo de marketing. Después de compilar y procesar la información obtenida de la empresa, el análisis de la percepción de marca es aplicado mediante procesos de simulación. Los resultados del experimento son emitidos a la organización mediante un informe basado en conclusiones y recomendaciones a nivel de marketing para mejorar la percepción de marca por parte de los consumidores.

Application of agent-based modeling to the study of gender stereotypes

Gender stereotypes are sets of characteristics that people believe to be typically true of a man or woman. We report an agent-based model (ABM) that simulates how stereotypes disseminate in a group through associative mechanisms. The model consists of agents that carry one of several different versions of a stereotype, which share part of their conceptual content. When an agent acts according to his/her stereotype, and that stereotype is shared by an observer, then the latter’s stereotype strengthens. Contrarily, if the agent does not act according to his/ her stereotype, then the observer’s stereotype weakens. In successive interactions, agents develop preferences, such that there will be a higher probability of interaction with agents that confirm their stereotypes. Depending on the proportion of shared conceptual content in the stereotype’s different versions, three dynamics emerge: all stereotypes in the population strengthen, all weaken, or a bifurcation occurs, i.e., some strengthen and some weaken. Additionally, we discuss the use of agent-based modeling to study social phenomena and the practical consequences that the model’s results might have on stereotype research and their effects on a community

Characterization of resistance in vitro to different antimicrobial in strains of Staphylococcus spp. in a hospital of the city of Valledupar between January and July 2009

The Staphylococcus spp. they can cause a wide range of infections systemic and located in community and hospital patients. Its high pathogenicity and growing resistance to multiple antimicrobials including methicillin, causes high morbiditymortality rates, causing a high epidemiological impact. Objective: to determine the phenotypic profile of resistance to different antimicrobials in strains of the genus Staphylococcus spp. Materials and methods: collected 75 strains and determined them susceptibility to different antibiotics by the Kirby-Bauer method. The production of betalactamasecheck using the nitrocefin test. (Resistance to Methicillin in S. aureus was conductedusing Mueller Hinton with 4% NaCl and oxacillin 6 μg/mL). Inducible clindamycin resistance tamizo by D-Test test. Results: they were isolated by 38% of staphylococcus coagulase negative (SNA) and 62% of S. aureus. 53% were penicillin resistant staphylococci: S. aureus with 58% and 42% SNA. 47% of the strains showed resistance to methicillin: S. aureus with 61% and SNA with 39%. A strain of S. aureus showed inducible resistance to clindamycin (1.33%). Coagulase negative staphylococci were isolated mostly from blood samples (31%), blood (29%), tip of catheter (5%) and came mostly from neonatal ICU (25%), medical (21%) and surgery (16%).Conclusions: S. aureus and SNA were isolated with greater frequency in blood and wounds from surgery and neonatal ICU. The predominant resistance phenotypes were penicillin and oxacillin.

Comportamiento epidemiológico de la sepsis nosocomial en la Unidad de Recién Nacidos de la Fundación Cardioinfantil

Objetivo. Se realizó un estudio retrospectivo que describe las características demográficas, la etiología, los factores asociados, la mortalidad, la sensibilidad y la resistencia de los microorganismos a los antibióticos usados en sepsis nosocomial. Diseño del estudio. Se realizó la recolección de datos desde el 2004 hasta el primer trimestre del 2006. Se definió infección nosocomial probada como la infección diagnosticada después de 72 horas de hospitalización y que recibe manejo antibiótico mayor a 3 días. Resultados. Se revisaron 60 historias clínicas, en las cuales los gérmenes Gram negativos fueron los principales causantes de sepsis nosocomial, tanto intra como extrainstitucional; de ellos la k. pneumoniae fue el germen más frecuentemente encontrado. Conclusiones. Los gérmenes Gram negativos son los microorganismos predominantemente causantes de sepsis nosocomial en la Unidad de Recién Nacidos (URN) de la Fundación Cardioinfantil (FCI).

The High Education Teacher, an Agent of Moral Development

The article shows the classroom like an workplace to move moral development, from the relationship between students and professors in the university atmosphere. It proposes elements to take to the practice the ethics education a transverse curriculum line. It assumes the ethics, from a plural perspective, founded on the knowledge and the human action. It joins the integral formation with the conceptions of education, curriculum, pedagogical models and methodologies of education. It proposes actions to demonstrate the commitment of the professor with the integral formation. Finally, concludes that the professor is agent of moral development and that in the classroom is constructed: identity, autonomy and responsibility, from open and plural relation between professors and students and between these and the knowledge.

An artificial economy based on reinforcement learning and agent based modeling

In this paper, we employ techniques from artificial intelligence such as reinforcement learning and agent based modeling as building blocks of a computational model for an economy based on conventions. First we model the interaction among firms in the private sector. These firms behave in an information environment based on conventions, meaning that a firm is likely to behave as its neighbors if it observes that their actions lead to a good pay off. On the other hand, we propose the use of reinforcement learning as a computational model for the role of the government in the economy, as the agent that determines the fiscal policy, and whose objective is to maximize the growth of the economy. We present the implementation of a simulator of the proposed model based on SWARM, that employs the SARSA(λ) algorithm combined with a multilayer perceptron as the function approximation for the action value function.