Background: Multiple sclerosis is a chronic autoimmune inflammatory demyelinating disease of the central nervous system of unknown etiology. Different techniques and magnetic resonance image sequences are widely used and compared to each other to improve the detection of multiple sclerosis lesions in the spinal cord. Objective: To evaluate the ability of MRI short tau inversion recovery sequences in improvementof multiple sclerosis spinal cord lesion detection when compared to T2 weighted image sequences. Type of the study: A retrospective study. Methods: this study conducted from 15thAugust 2013 to 30thJune 2014 at Baghdad teaching hospital. 22 clinically definite MS patients with clinical features suggestive of spinal cord involvement, patients were imaged with sagittal short tau inversion recovery sequences and sagittal T2 weighted. Results: The mean age of the patients was 32.5 ± 6.7years; female to male ratio was 2.7:1. The total number of spinal cord MS lesions was 44 of them 86.4% in the cervical spine, 68.2%of the lesions had less than one vertebra extension,79.6% of the lesions did not show changes in the spinal cord morphology. There was a significant upgrading in the lesions conspicuity at short tau inversion recovery sequence comparing to T2 weighted image, P<0.001. A significant difference had been found in artifact grading between both sequences; P<0.001. Conclusions: short tau inversion recovery magnetic resonance image sequences improve detection of MS spinal cord plaques compared with T2 weighted image and itincreasesthe conspicuity of the visualized T2weighted image lesions, but also it accentuates theartifacts more than T2weighted image.
In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes
Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an
... Show MoreBackground: As the development of zirconia crown using CAD/CAM technology, the usage of full zirconia crown is gradually increased. The aim of this in-vitro study was to evaluate and contrast the vertical marginal fit of single all-ceramic translucent zirconia crowns constructed from different brands translucent zirconia blanks. Materials and Methods: An acrylic resin model of a left maxillary premolar was prepared all around the tooth with (1 mm) depth and 3D scanning to get fifteen STL files, then distributed into three groups (Imes-icor, Whitepeaks and Dental direct), 3D scanning and milling machine by Imes-icor CAD/CAM devise. Marginal gaps along vertical planes were measured at four indentations at the (mid mesial, mid distal, mid bucc
... Show MoreRNA Sequencing (RNA-Seq) is the sequencing and analysis of transcriptomes. The main purpose of RNA-Seq analysis is to find out the presence and quantity of RNA in an experimental sample under a specific condition. Essentially, RNA raw sequence data was massive. It can be as big as hundreds of Gigabytes (GB). This massive data always makes the processing time become longer and take several days. A multicore processor can speed up a program by separating the tasks and running the tasks’ errands concurrently. Hence, a multicore processor will be a suitable choice to overcome this problem. Therefore, this study aims to use an Intel multicore processor to improve the RNA-Seq speed and analyze RNA-Seq analysis's performance with a multiproce
... Show MoreA novel planar type antenna printed on a high permittivity Rogers’ substrate is proposed for early stage microwave breast cancer detection. The design is based on a p-shaped wide-slot structure with microstrip feeding circuit to eliminate losses of transmission. The design parameters are optimized resulting in a good reflection coefficient at −10 dB from 4.5 to 10.9 GHz. Imaging result using inhomogeneous breast phantom indicates that the proposed antenna is capable of detecting a 5 mm size cancerous tumor embedded inside the fibroglandular region with dielectric contrast between the target and the surrounding materials ranging from 1.7 : 1 to 3.6 : 1.
In this paper, some commonly used hierarchical cluster techniques have been compared. A comparison was made between the agglomerative hierarchical clustering technique and the k-means technique, which includes the k-mean technique, the variant K-means technique, and the bisecting K-means, although the hierarchical cluster technique is considered to be one of the best clustering methods. It has a limited usage due to the time complexity. The results, which are calculated based on the analysis of the characteristics of the cluster algorithms and the nature of the data, showed that the bisecting K-means technique is the best compared to the rest of the other methods used.
In recent years and decades, there is a great need for developing new alternative energy sources or renewable sustainable energy. On the other hand, new technology approaches are growing . towards benefits from the valuable nutrients in wastewater which are unrecoverable by traditional wastewater treatment processes. In the current study, a novel integrated system of microbial fuel cell and anoxic bioreactor (MFC-ANB) was designed and constructed to investigate its potential for slaughterhouses wastewater treatment, nitrogen recovery, and power generation. The system consisted of a double-chamber tubular type MFC with biocathode inoculated with freshly collected activated sludge. The MFC-ANB system was continuously fed with real-fi
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This study is concerned with the estimation of constant and time-varying parameters in non-linear ordinary differential equations, which do not have analytical solutions. The estimation is done in a multi-stage method where constant and time-varying parameters are estimated in a straight sequential way from several stages. In the first stage, the model of the differential equations is converted to a regression model that includes the state variables with their derivatives and then the estimation of the state variables and their derivatives in a penalized splines method and compensating the estimations in the regression model. In the second stage, the pseudo- least squares method was used to es
... Show MoreIn this work, copper substituted cobalt ferrite nanoparticles with
chemical formula Co1-xCuxFe2O4 (x=0, 0.3, and 0.7), has been
synthesized via hydrothermal preparation method. The structure of
the prepared materials was characterized by X-ray diffraction (XRD).
The (XRD) patterns showed single phase spinel ferrite structure.
Average crystallite size (D), lattice constant (a), and crystal density
(dx) have been calculated from the most intense peak (311).
Comparative standardization also performed using smaller average
particle size (D) on the XRD patterns of as-prepared ferrite samples
in order to select most convenient hydrothermal synthesis conditions
to get ferrite materials with smallest average particl