The cost of developing the software from scratch can be saved by identifying and extracting the reusable components from already developed and existing software systems or legacy systems [6]. But the issue of how to identify reusable components from existing systems has remained relatively unexplored. We have used metric based approach for characterizing a software module. In this present work,...

This paper compares the standard Bilateral Filter and its variants such as Modified Bilateral Filter(MBF), Joint Bilateral Filter(JBF), Fuzzy Bilateral Filter(FBF) and Switching Bilateral Filter(SBF). For comparison purpose various performance matrices such as: Peak Signal to Noise Ratio(PSNR), Mean Square Error(MSE), Mean Absolute Error(MAE), Normalized Color Difference(NCD), Perceptual Qualit...

This paper aims at evaluating volatility forecasts for the US Dollar/Mauritian Rupee exchange rate obtained via a GARCH (1,1) model under two distributional assumptions: the Generalized Error Distribution (GED) and the Student’s-t distribution. We make use of daily data to evaluate the parameters of each model and produce volatility estimates. The forecasting ability is subsequently assessed us...

soil hydraulic properties such as soil water characteristic curve are necessary prerequisite for modeling water movement and solute transport. direct methods of estimating these hydraulic properties are time consuming and costly. indirect methods, such as pedotransfer functions, estimate the hydraulic parameters using easy-to-measure soil properties like particle size distributions, bulk densit...

This paper proposes a hybrid forecasting model, which combines the seasonal time series ARIMA (SARIMA) and the neural network back propagation (BP) models, known as SARIMABP. This model was used to forecast two seasonal time series data of total production value for Taiwan machinery industry and the soft drink time series. The forecasting performance was compared among four models, i.e., the SA...

This paper presents a straight forward application of Layer Recurrent Neural Network (LRNN) to predict the load of a large distribution network. Short term load forecasting provides important information about the system’s load pattern, which is a premier requirement in planning periodical operations and facility expansion. Approximation of data patterns for forecasting is not an easy task to p...

Public health surveillance systems provide valuable data for reliable predication of future epidemic events. This paper describes a study that used nine types of infectious disease data collected through a national public health surveillance system in mainland China to evaluate and compare the performances of four time series methods, namely, two decomposition methods (regression and exponentia...

Saturated hydraulic conductivity of Soil is an important property in processes involving water and solute flow in soils. Saturated hydraulic conductivity of soil is difficult to measure and can be highly variable, requiring a large number of replicate samples. In this study, 60 sets of soil samples were collected at Saqhez region of Kurdistan province-IRAN. The statistics such as Correlation Co...

Accurate incidence forecasting of infectious disease is critical for early prevention and for better government strategic planning. In this paper, we present a comprehensive study of different forecasting methods based on the monthly incidence of typhoid fever. The seasonal autoregressive integrated moving average (SARIMA) model and three different models inspired by neural networks, namely, ba...