Long memory analysis is one of the most active areas in econometrics and time series where various methods have been introduced to identify and estimate the long memory parameter in partially integrated time series. One of the most common models used to represent time series that have a long memory is the ARFIMA (Auto Regressive Fractional Integration Moving Average Model) which diffs are a fractional number called the fractional parameter. To analyze and determine the ARFIMA model, the fractal parameter must be estimated. There are many methods for fractional parameter estimation. In this research, the estimation methods were divided into indirect methods, where the Hurst parameter is estimated fir

L1 adaptive controller has proven to provide fast adaptation with guaranteed transients in a large variety of systems. It is commonly used for controlling systems with uncertain time-varying unknown parameters. The effectiveness of  L1 adaptive controller for position control of single axis has been examined and compared with Model Reference Adaptive Controller (MRAC). The Linear servo motor is one of the main constituting elements of the x-y table which is mostly used in automation application. It is characterized by time-varying friction and disturbance.

    The tracking and steady state performances of both controllers have been assessed fo

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

Copper with different concentrations doped with zinc oxide nanoparticles were prepared from a mixture of zinc acetate and copper acetate with sodium hydroxide in aqueous solution. The structure of the prepared samples was done by X-ray diffraction, atomic force microscopy (AFM) and UV-VIS absorption spectrophotometer. Debye-Scherer formula was used to calculate the size of the prepared samples. The band gap of the nanoparticle ZnO was determined by using UV-VIS optical spectroscopy.

The study examined the assessment of raw water and drinking water projects of  Diyala Governorate for the year 2017, amounting to (24) projects, The average per capita supply of potable water (0.396 m3 / day/person), which is less than the global standard for the average per capita of drinking water, and constitute water rumors within the network of water transport in the province (3%), and the water of raw and drinking value within the limits allowed to be used by Iraq and the global indicators of {Total acidity, alkaline, acidic function, chlorides, magnesium, Electrical conductivity, total soluble salts, sodium, potassium, sulfates, turbidity other than (raw water)}. While the index of calcium only a value higher than the limits

The operating characteristics of optoelectronic devices depend critically on the properties physical of the constituent materials, interesting compound has been focused on this research formed from group III and V of the periodic table. Thin film n-InSb heterjuntion were successfully fabricated on p-Si substrates by thermal evaporation technique at different annealing temperature (as prepared, 400,500,600) °C. The effect of annealing temperature on the structural, surface morphology, optical and optoelectronic properties of InSb films were investigated and studied. The crystal structure of the film was characterized by X-ray diffraction and techniques. AFM techniques inspect the surface morphology of InSb films, the study presented the val