Different ANN architectures of MLP have been trained by BP and used to analyze Landsat TM images. Two different approaches have been applied for training: an ordinary approach (for one hidden layer M-H1-L & two hidden layers M-H1-H2-L) and one-against-all strategy (for one hidden layer (M-H1-1)xL, & two hidden layers (M-H1-H2-1)xL). Classification accuracy up to 90% has been achieved using one-against-all strategy with two hidden layers architecture. The performance of one-against-all approach is slightly better than the ordinary approach

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

Evaporation is one of the major components of the hydrological cycle in the nature, thus its accurate estimation is so important in the planning and management of the irrigation practices and to assess water availability and requirements. The aim of this study is to investigate the ability of fuzzy inference system for estimating monthly pan evaporation form meteorological data. The study has been carried out depending on 261 monthly measurements of each of temperature (T), relative humidity (RH), and wind speed (W) which have been available in Emara meteorological station, southern Iraq. Three different fuzzy models comprising various combinations of monthly climatic variables (temperature, wind speed, and relative humidity) were developed

Abstract: Narrow laser pulses have been essential sources in optical communication system. High data rate optical communication network system demands compressed laser source with unique optical property. In this work using pulsed duration (9) ns, peak power 1.2297mW, full width half maximum (FWHM) 286 pm, and wavelength center 1546.7 nm as compression laser source. Mach Zehnder interferometer (MZI) is built by considering two ways. First, polarization maintaining fiber (PMF) with 10 cm length is used to connect between laser source and fiber brag grating analysis (FBGA). Second, Nested Mach Zehnder interferometer (NMZI) was designed by using three PMFs with 10 cm length. These three Fibers are splicing to sing

objective: To evaluate the influence of monolithic zirconia brand, thickness, and substrate color on color matching accuracy when optically coupled to abutment substrates. Methods: A total of 180 samples of two brands of monolithic zirconia [Prettau Anterior (PA), Ceramill Zolid FX Multicolor (CZ)] were prepared in three different thicknesses (0.8 mm, 1.5 mm, and 2 mm) with a standardized 10 mm diameter. Color properties of the samples were assessed using spectrophotometry at baseline and after coupling to three substrate types: standard dentin, discolored dentin, and titanium. Color differences (ΔE) were calculated and statistically analyzed by 3-way ANOVA and pairwise comparison ( α=0.05). Results: The brand and material thickness, at