Non-linear convergence in Asian interest rates and inflation rates

We examine the dynamics of convergence of the ASEAN5 plus the big three for nominal interest rates, inflation rates, and real interest rates. We test for convergence relative to the U.S and Japan, using monthly data over the period January 1990 - December 2010, using non-linear unit root tests. The results show strong evidence of stationary inflation and real interest rate differentials in all but China’s inflation differential relative to the U.S., and stationary nominal interest differentials in most of the cases. We interpret these results as convergence in inflation rates and real interest rates in all cases, and as nominal interest convergence in most of the cases. Moreover, examining the impact of the Asian crisis shows less number of convergences before the crisis and more convergences after the crisis. This suggests that convergence has increased after the 1997/98 Asian crisis, and that the crisis has pulled the economies together.interest rates convergence; inflation convergence; nonlinear unit root tests

Non-linearities in the dynamics of oil prices

We utilize non-linear models to examine the stationarity of oil prices (Brent, Dubai, WIT and World) over the period 1973:2-2011:2. Real oil prices are calculated and expressed in the domestic currencies of seven Asian countries (Indonesia, Japan, Korea, Malaysia, the Philippines, Singapore and Thailand) and in the U.S dollar. Applying linear unit root tests with and without structural breaks shows very limited evidence of stationarity. However, applying non-linear models shows evidence of non-linearity in all the cases. In most cases, we find significant evidence of exponential smooth transition autoregression (ESTAR) type non-linearity. Notably, the results for Japan suggest logistic (LSTAR) type non-linearity for the four oil prices. Applying unit root tests, which account for two types of non-linearities (smooth transition and nonlinear deterministic trends), reveals evidence of stationarity in all the cases.oil prices; nonlinear unit root tests; nonlinear deterministic trends; smooth transition autoregression

ANN for English Alphabet Prediction

Abstract: In this paper an Artificial Neural Network (ANN) model, for predicting the Letters from twenty dissimilar fonts for each letter. The character images were, initially, based on twenty dissimilar fonts and each letter inside these twenty fonts was arbitrarily distorted to yield a file of 20,000 distinctive stimuli. Every stimulus was transformed into 16 simple numerical attributes (arithmetical moments and edge amounts) which were then ascended to be suitable into a range of numeral values from 0 to 15. We naturally chose, arbitrarily, 1,000 distinctive stimuli for this research. We made certain that the scattering remnants the similar after selecting the one thousand stimuli. In this research, a neural network tool (Just NN) was used for the purpose of predicting to classify every of a huge number of black and white four-sided pixel displays as one of the 26 capital letters in the English language

Optical parameters of amorphous arsenic triselenide multilayers prepared by spin coating

Multilayer thin films of amorphous arsenic triselenide (As2Se3) were obtained by spin coating solution of an amine salt in amide on glass substrate.  The deposited multilayers in the range of 500 to 1000 nm were optically characterized by measuring the transmission spectra at room temperature.  All used samples were baked and annealed for different periods of times and temperatures.  The effect of layers number, baking times and temperatures on optical parameters were investigated.  The thickness of the prepared samples up to four layers was ranging between 0.1 µm to 0.2 µm