Background:Parkinson’disease(PD) is a neurodegenerative disorder of the central nervous system characterized by resting tremor, bradykinesia, cogwheel rigidity, and impairment of postural reflexes; the frequency of PD increases with aging.Clinically Parkinson's disease characterized by two groups of symptoms: motor and non-motor symptoms.Non-motor symptoms can be categorized as autonomic, cognitive/psychiatric (may include depression, dementia, anxiety, hallucinations), sensory and rapid eye movements (REM) sleep behavior disorder (RBD).

Objectives:The objectives of this study are to find out the frequency of the non-motor symptoms of idiopathic Parkinson disease in a group of patients in Baghd

In all applications and specially in real time applications, image processing and compression plays in modern life a very important part in both storage and transmission over internet for example, but finding orthogonal matrices as a filter or transform in different sizes is very complex and importance to using in different applications like image processing and communications systems, at present, new method to find orthogonal matrices as transform filter then used for Mixed Transforms Generated by using a technique so-called Tensor Product based for Data Processing, these techniques are developed and utilized. Our aims at this paper are to evaluate and analyze this new mixed technique in Image Compression using the Discrete Wavelet Transfo

Crystalline silicon (c-Si) has low optical absorption due to its high surface reflection of incident light. Nanotexturing of c-Si which produces black silicon (b-Si) offers a promising solution. In this work, effect of H₂O₂ concentrations towards surface morphological and optical properties of b-Si fabricated by two-step silver-assisted wet chemical etching (Ag-based two-step MACE) for potential photovoltaic (PV) applications is presented. The method involves a 30 s deposition of silver nanoparticles (Ag NPs) in an aqueous solution of AgNO₃:HF (5:6) and an optimized etching in HF:H₂O₂:DI H₂O solution under 0.62 M, 1.85 M, 2.47 M, and 3.7 M concentrations of H₂O<

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Estimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model  in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling  the Symmetric gray scale texture image and estimating by using

An experiment was conducted in pots under field conditions during fall seasons of 2017 and 2018. This study aimed to improve a weak growth of seedlings under salt stress in sorghum. Three factors were studied. 1st factor was three cultivars (Inqath, Rabeh, and Buhoth70). 2nd factor was seed priming (primed and unprimed seed). Seed were primed by soaking for 12 hours in a solution containing 300 + 70 mg L−1 of gibberellic (GA3) and salicylic (SA) acids, respectively. 3rd factor was irrigation with saline water (6, 9 and 12 dS m−1) resulting from dissolving sodium chloride in distilled water in addition to control treatment (distilled water). Randomized complete block design was used with four replications. In both seasons: the results sh

    Biomedical signal such as ECG is extremely important in the diagnosis of patients and is commonly recorded with a noise. Many different kinds of noise exist in biomedical environment such as Power Line Interference Noise (PLIN). Adaptive filtering is selected to contend with these defects, the adaptive filters can adjust the filter coefficient with the given filter order. The objectives of this paper are: first an application of the Least Mean Square (LMS) algorithm, Second is an application of the Recursive Least Square (RLS) algorithm to remove the PLIN. The LMS and RLS algorithms of the adaptive filter were proposed to adapt the filter order and the filter coefficients simultaneously, the performance of existing LMS

Abstracts:

The Central Bank is the backbone of the banking system as a whole, and in order to maintain the banking system, one of the most important functions that the Central Bank performs is the function of supervising and controlling banks, with several tools and methods, and one of the most important of these tools is its creation of the function of a compliance observer, which obligated commercial banks to appoint a person in A bank that performs this function according to certain conditions and granting it some powers that would build a sound and compliant banking system. The function of the compliance observer is to follow up on the bank’s compliance with the instructions and decisions issued by

The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.