Storing, transferring, and processing high-dimensional electroencephalogram (EGG) signals is a critical challenge. The goal of EEG compression is to remove redundant data in EEG signals. Medical signals like EEG must be of high quality for medical diagnosis. This paper uses a compression system with near-zero Mean Squared Error (MSE) based on Discrete Cosine Transform (DCT) and double shift coding for fast and efficient EEG data compression. This paper investigates and compares the use or non-use of delta modulation, which is applied to the transformed and quantized input signal. Double shift coding is applied after mapping the output to positive as a final step. The system performance is tested using EEG data files from the CHB-MIT Scalp EEG Database. Compression Ratio (CR) is used to evaluate the compression system performance. The results are encouraging when compared with previous works on the same data samples.
Load balancing in computer networks is one of the most subjects that has got researcher's attention in the last decade. Load balancing will lead to reduce processing time and memory usage that are the most two concerns of the network companies in now days, and they are the most two factors that determine if the approach is worthy applicable or not. There are two kinds of load balancing, distributing jobs among other servers before processing starts and stays at that server to the end of the process is called static load balancing, and moving jobs during processing is called dynamic load balancing. In this research, two algorithms are designed and implemented, the History Usage (HU) algorithm that statically balances the load of a Loaded
... Show MoreSeismic inversion technique is applied to 3D seismic data to predict porosity property for carbonate Yamama Formation (Early Cretaceous) in an area located in southern Iraq. A workflow is designed to guide the manual procedure of inversion process. The inversion use a Model Based Inversion technique to convert 3D seismic data into 3D acoustic impedance depending on low frequency model and well data is the first step in the inversion with statistical control for each inversion stage. Then, training the 3D acoustic impedance volume, seismic data and porosity wells data with multi attribute transforms to find the best statistical attribute that is suitable to invert the point direct measurement of porosity from well to 3D porosity distribut
... Show MoreIn real situations all observations and measurements are not exact numbers but more or less non-exact, also called fuzzy. So, in this paper, we use approximate non-Bayesian computational methods to estimate inverse Weibull parameters and reliability function with fuzzy data. The maximum likelihood and moment estimations are obtained as non-Bayesian estimation. The maximum likelihood estimators have been derived numerically based on two iterative techniques namely “Newton-Raphson†and the “Expectation-Maximization†techniques. In addition, we provide compared numerically through Monte-Carlo simulation study to obtained estimates of the parameters and reliability function i
... Show MoreOne of the most significant elements influencing weather, climate, and the environment is vegetation cover. Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) over the years 2019–2022 were estimated based on four Landsat 8 TIRS’s images covering Duhok City. Using the radiative transfer model, the city's land surface temperature (LST) during the next four years was calculated. The aim of this study is to compute the temperature at the land's surface (LST) from the years 2019-2022 and understand the link, between LST, NDVI, and NDBI and the capability for mapping by LANDSAT-8 TIRS's. The findings revealed that the NDBI and the NDVI had the strongest correlation with the
... Show MoreThe Compressional-wave (Vp) data are useful for reservoir exploration, drilling operations, stimulation, hydraulic fracturing employment, and development plans for a specific reservoir. Due to the different nature and behavior of the influencing parameters, more complex nonlinearity exists for Vp modeling purposes. In this study, a statistical relationship between compressional wave velocity and petrophysical parameters was developed from wireline log data for Jeribe formation in Fauqi oil field south Est Iraq, which is studied using single and multiple linear regressions. The model concentrated on predicting compressional wave velocity from petrophysical parameters and any pair of shear waves velocity, porosity, density, a
... Show MoreThe Compressional-wave (Vp) data are useful for reservoir exploration, drilling operations, stimulation, hydraulic fracturing employment, and development plans for a specific reservoir. Due to the different nature and behavior of the influencing parameters, more complex nonlinearity exists for Vp modeling purposes. In this study, a statistical relationship between compressional wave velocity and petrophysical parameters was developed from wireline log data for Jeribe formation in Fauqi oil field south Est Iraq, which is studied using single and multiple linear regressions. The model concentrated on predicting compressional wave velocity from petrophysical parameters and any pair of shear waves velocity, porosity, density, and
... Show MoreAbstract. This study presents experimental and numerical investigation on the effectiveness of electrode geometry on flushing and debris removal in Electrical Discharge Drilling (EDD) process. A new electrode geometry, namely side-cut electrode, was designed and manufactured based on circular electrode geometry. Several drilling operations were performed on stainless steel 304 using rotary tubular electrodes with circular and side-cut geometries. Drilling performance was characterized by Material Removal Rate (MRR), Electrode Wear Rate (EWR), and Tool Wear Ratio (TWR). Dimensional features and surface quality of drilled holes were evaluated based on Overcut (OC), Hole Depth (HD), and Surface Roughness (SR). Three-dimensional
... Show MoreIt is clear that correct application of antibiotic prophylaxis can reduce the incidence of infection resulting from the bacterial inoculation in a variety of clinical situations; it cannot prevent all infections any more than it can eliminate all established infections. Optimum antibiotic prophylaxis depends on: rational selection of the drug(s), adequate concentrations of the drug in the tissues that are at risk, and attention to timing of administration. Moreover, the risk of
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