Global Modeling and Prediction of Computer Network Traffic

We develop a probabilistic framework for global modeling of the traffic over a computer network. This model integrates existing single-link (-flow) traffic models with the routing over the network to capture the global traffic behavior. It arises from a limit approximation of the traffic fluctuations as the time--scale and the number of users sharing the network grow. The resulting probability model is comprised of a Gaussian and/or a stable, infinite variance components. They can be succinctly described and handled by certain 'space-time' random fields. The model is validated against simulated and real data. It is then applied to predict traffic fluctuations over unobserved links from a limited set of observed links. Further, applications to anomaly detection and network management are briefly discussed

Using Markov Boundary Approach for Interpretable and Generalizable Feature Selection

Predictive power and generalizability of models depend on the quality of features selected in the model. Machine learning (ML) models in banks consider a large number of features which are often correlated or dependent. Incorporation of these features may hinder model stability and prior feature screening can improve long term performance of the models. A Markov boundary (MB) of features is the minimum set of features that guarantee that other potential predictors do not affect the target given the boundary while ensuring maximal predictive accuracy. Identifying the Markov boundary is straightforward under assumptions of Gaussianity on the features and linear relationships between them. This paper outlines common problems associated with identifying the Markov boundary in structured data when relationships are non-linear, and predictors are of mixed data type. We have proposed a multi-group forward-backward selection strategy that not only handles the continuous features but addresses some of the issues with MB identification in a mixed data setup and demonstrated its capabilities on simulated and real datasets

Improving children’s and their visitors’ hand hygiene compliance

Background: Numerous interventions have tried to improve healthcare workers' hand hygiene compliance, however little attention has been paid to children's and their visitors’ compliance.Aim: To increase children’s and visitors’ compliance using interactive educational interventions. Methods: This was an observational study of hand hygiene compliance before and after the introduction of educational interventions. Qualitative data in the form of Questionnaires and interviews was obtained.Findings: Hand hygiene compliance increased by 21.4% (P [less than] 0.001) following the educational interventions, with children's compliance reaching 40.8% and visitors' being 50.8%. Compliance varied depending on which of the five moments of hygiene was observed (P [less than] 0.001), with the highest compliance was ‘after body fluid exposure’ (96%). Responses from questionnaires showed educational interventions raised awareness of the importance of hand hygiene (69%, 57%) compared to those who hadn't experienced the educational intervention (50%). Conclusion: Educational interventions may result in a significant increase in children's and visitors' hand hygiene (P [less than] 0.001)

Estudio de pre-factibilidad para la creación de una pequeña empresa procesadora y distribuidora de bebida en polvo a base de maní y leche en el casco urbano de Managua durante 2020-2024

Realiza un estudio de pre-factibilidad para la creación de una pequeña empresa productora y distribuidora de bebida en polvo a base de maní y leche, determina a partir de un análisis de mercado, las variables mercadológicas que influyen en la aceptación del producto de parte de los consumidores del casco urbano, define la viabilidad técnica del proyecto teniendo en cuenta el tamaño de la planta, localización, proceso productivo requerido para la bebida, estructura organizacional y procedimientos legales que condicionan la operatividad de este, evalúa la rentabilidad del proyecto a través de un análisis financiero utilizando las técnicas del VPN y TIR