In this paper, the delay integral equations in population growth will be described,discussed , studied and transfered this model to integro-differential equation. At last,we will solve this problem by using variational approach.

Recently, the financial mathematics has been emerged to interpret and predict the underlying mechanism that generates an incident of concern. A system of differential equations can reveal a dynamical development of financial mechanism across time. Multivariate wiener process represents the stochastic term in a system of stochastic differential equations (SDE). The standard wiener process follows a Markov chain, and hence it is a martingale (kind of Markov chain), which is a good integrator. Though, the fractional Wiener process does not follow a Markov chain, hence it is not a good integrator. This problem will produce an Arbitrage (non-equilibrium in the market) in the predicted series. It is undesired property that leads to erroneous conc

Resumen

El trabajo se investiga en el realismo y la tradición social que incluye la tragedia Bodas de sangre, del autor español Federico García Lorca. A lo largo de estas páginas se da la luz sobre los temas, acciones, oraciones y palabras que pertenecen a la realidad de la vida española en general y sobre todo en territorio andaluz, en el que ocurren los sucesos de la obra.  Así como las tradiciones sociales que el dramaturgo español contemporáneo abundando a lo largo de su texto, y que han sido tomadas de la herencia popular.

    Literariamente, esta obra se clasifica como Tragedia Moderna, por la razón de que incorpora los elementos necesarios de d

Uno de los rasgos más interesantes sobre España es la diversidad de sus lenguas, y aunque la mayoría de los españoles hablan español, pero una gran parte de la población es bilingüe y en algunas ocasiones, trilingüe. Hoy en día estas lenguas se usan y conviven juntas sin grandes problemas, aunque durante mucho tiempo esta convivencia ha sido muy complicada. Asi que el propósito de nuestro trabajo es enfocar la luz sobre la situación linguística actual de España.
Al estudiar la situación linguística de España encontramos que las lenguas son instrumentos vivos y dinámicos, inseparables de su propia historia, dos realidades, su pasado y su presente, que van conformando su propia estructura y su propio dominio lingüísti

Polyacrylonitrile nanofiber (PANFS), a well-known polymers, has been extensively employed in the manufacturing of carbon nanofibers (CNFS), which have recently gained substantial attention due to their excellent features, such as spinnability, environmental friendliness, and commercial feasibility. Because of their high carbon yield and versatility in tailoring the final CNFS structure, In addition to the simple formation of ladder structures through nitrile polymerization to yield stable products, CNFS and PAN have been the focus of extensive research as potential production precursors. For instance, the development of biomedical and high-performance composites has now become achievable. PAN homopolymer or PAN-based precursor copolymer can

Sansevieriatrifasciata was studied as a potential biosorbent for chromium, copper and nickel removal in batch process from electroplating and tannery effluents. Different parameters influencing the biosorption process such as pH, contact time, and amount of biosorbent were optimized while using the 80 mm sized particles of the biosorbent. As high as 91.3 % Ni and 92.7 % Cu were removed at pH of 6 and 4.5 respectively, while optimum Cr removal of 91.34 % from electroplating and 94.6 % from tannery effluents was found at pH 6.0 and 4.0 respectively. Pseudo second order model was found to best fit the kinetic data for all the metals as evidenced by their greater R2 values. FTIR characterization of biosorbent revealed the presence of carboxyl a

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an