Planeación estratégica

El envejecimiento poblacional es un fenómeno macrosocial que alude al cambio en la estructura por edades de la población, producto de la relativa disminución de las personas más jóvenes y el aumento de la proporción de adultos y, sobre todo, de personas de avanzada edad.

El presente trabajo tiene como finalidad contribuir al entendimiento del Plan estratégico aplicado y de los términos usados en su desarrollo, teniendo como soporte básico a los autores del modelo, Leonard D. Goodstein, Timothy Nolan y William Pfeiffer. A fin de poder implementar los conocimientos sobre este tema.

En los últimos tiempos las empresas han experimentado cambios dramáticos y discontinuos, que implican que las mismas deban adaptarse a estos para poder sobrevivir. El fenómeno de la globalización que actualmente nos invade para las empresas implica una mayor competencia.

Transferência de titularidade. Quem é o novo dono, quem é o novo possuidor. Sucessão é o ato pelo qual uma pessoa assume a titularidade de determinados bens e direitos pertencentes a outrem.

Electrum

This article examines defeats and losses as phenomena of an ‘expanded military history’ of Roman History from the Republic to the Principate. It adopts a cultural historical perspective of the military historical phenomenon. “Patterns”and “strategies”are defined, that appear in the sources when dealing with Roman defeats, losses and losers (in particular the commanders or even the emperor himself). Above, the historiography of the Roman imperial period is exemplary examined to see what reasons, interpretations or explanations are given there for suffering a defeat and whether and how these are part of narrative strategies. Sometimes military catastrophes simply were concealed, belittled or reinterpreted. How Rome dealt with defeat tells something about Rome’s society and especially the elite: “Roman culture”or “Rome’s political culture” shaped the way how the military phenomenon of defeat was dealt with. Defeats could also be seen as chances for future victories, they were good for ...

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2019

Stock price prediction is one of the most complex machine learning problems. It depends on a large number of factors which contribute to changes in the supply and demand. In this paper, we propose a stock prediction analysis using machine learning based on support vector machines (SVM), linear regression and reinforcement learning. SVM are favored in applications where text mining is used for market prediction. SVMs can be used for both linearly and non-linearly separable data sets. when the data is linearly separable, SVMs construct a hyperplane on the feature space to distinguish the training tuples in the data such that the margin between the support vectors is maximized. Correlation is used between stock prices of different companies to predict the price of a stock by using technical indicator of highly correlated stocks, not only stock to be predicted.