background at altnagelvin, a district general hospital in northern ireland, we have observed that a significant number of hip fracture admissions are later readmitted for treatment of other medical conditions. these readmissions place increasing stress on the already significant burden that orthopedic trauma poses on national health services. objectives the aim of this study was to review a ser...

in this study, liquid-liquid extraction process in a kuhni extraction column was modeled and simulated. a non-equilibrium dynamic model was developed for modeling liquid-liquid extraction processes based on a rate-based model. the model equations are inclusive of partial and ordinary differential equations which were discretized in column height direction. the population balance model was used ...

Estimate of sediment load is required in a wide spectrum of water resources engineering problems. The nonlinear nature of suspended sediment load series necessitates the utilization of nonlinear methods to simulate the suspended sediment load. In this study Artificial Neural Networks (ANNs) are employed to estimate daily suspended sediment load. Two different ANN algorithms, Multi Layer Perce...

A new method called C–C–1 method is suggested, which can improve some drawbacks of the original C–C method. Based on the theory of period N , a new quantity S(t) for estimating the delay time window of a chaotic time series is given via direct computing a time-series quantity S(m,N, r, t), from which the delay time window can be found. The optimal delay time window is taken as the first period ...

Most of the existing forecasting techniques give the basic idea of crop production per year. There are various forecasting techniques, we have worked on two techniques one is Fuzzy Time Series and another one is Diffusion of Innovation. Research paper will focus on (SAII) study, analyze, improve and implement strategies of forecasting techniques depending on nature of data and we have done SAII...

We propose a new time series model aimed at forecasting crude oil prices. The proposed specification is an unobserved components model with an asymmetric cyclical component. The asymmetric cycle is defined as a sine-cosine wave where the frequency of the cycle depends on past oil price observations. We show that oil price forecasts improve significantly when this asymmetry is explicitly modelled.

We describe a technique for fast compression of time series and indexing of compressed series. We have tested it on three data sets: stock prices, air and sea temperatures, and wind speeds.

This paper gives a tour through the empirical analysis of univariate GARCH models for financial time series with stops along the way to discuss various practical issues associated with model specification, estimation, diagnostic evaluation and forecasting.