Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

A solid Phase Extraction (SPE) cartridges followed by HPLC-UV method is described for the simultaneous quantitative determination of benzidine (BZ) and its substituted 3, 3’-dichlorobenzidine (DCB) and 3, 3’-Dimethylbenzidine (DMB). The Benzidines were separated by liquid chromatography using a C-18 column with UV detector at wave length of 280nm. The mode of Flow was isocratic. The mobile phase was consisted of 75:25 methanol: water, column temperature 50C°, and Flow Rate 1.8ml/min. Calibration curves were linear (R2 = 0.9979-0.9995). LOD (26.36-33.67) µg/L, LOQ (109.98-186.11) µg/L, the Robustness (2.99-4.35), Ruggedness (2.93-3.65).Conditions of extraction by (SPE) cartridges were optimized, the resin used is Octadecyl silica (ODS

Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

Audio classification is the process to classify different audio types according to contents. It is implemented in a large variety of real world problems, all classification applications allowed the target subjects to be viewed as a specific type of audio and hence, there is a variety in the audio types and every type has to be treatedcarefully according to its significant properties.Feature extraction is an important process for audio classification. This workintroduces several sets of features according to the type, two types of audio (datasets) were studied. Two different features sets are proposed: (i) firstorder gradient feature vector, and (ii) Local roughness feature vector, the experimentsshowed that the results are competitive to

A number of aqueous samples were collected from river Tigris in Baghdad city, enriched ~1000 times using solid phase extraction (SPE), then extracted the trace concentrations of some polychlorinated biphenyls (PCB) using an aqueous two-phase system (ATPS) composed of 1Methylpyridinium chloride [MePy]Cl and KH2PO4 salt. High performance liquid chromatography technique coupled with ultraviolet (HPLC-UV) is used for the quantification. Extraction under the optimized conditions of pH, solvent composition, duration and temperature has given with a yield of PCB about 91%. The limit of detection (LOD) and limit of quantification (LOQ) for analyses are 0.11-0.62 µg.L−1 and 2.67–3.43 µg.L−1 respectively with relative stan

Information processing has an important application which is speech recognition. In this paper, a two hybrid techniques have been presented. The first one is a 3-level hybrid of Stationary Wavelet Transform (S) and Discrete Wavelet Transform (W) and the second one is a 3-level hybrid of Discrete Wavelet Transform (W) and Multi-wavelet Transforms (M). To choose the best 3-level hybrid in each technique, a comparison according to five factors has been implemented and the best results are WWS, WWW, and MWM. Speech recognition is performed on WWS, WWW, and MWM using Euclidean distance (Ecl) and Dynamic Time Warping (DTW). The match performance is (98%) using DTW in MWM, while in the WWS and WWW are (74%) and (78%) respectively, but when using (

The security of message information has drawn more attention nowadays, so; cryptography has been used extensively. This research aims to generate secured cipher keys from retina information to increase the level of security. The proposed technique utilizes cryptography based on retina information. The main contribution is the original procedure used to generate three types of keys in one system from the retina vessel's end position and improve the technique of three systems, each with one key. The distances between the center of the diagonals of the retina image and the retina vessel's end (diagonal center-end (DCE)) represent the first key. The distances between the center of the radius of the retina and the retina vessel's end (ra

According to the measuring the relationship between organizational loyalty and job satisfaction among staff members at one college in the higher education ministry in Iraq by using exploratory factor analysis methods to extraction the components which have the major effects on the variables related to organizational loyalty and job satisfaction .

The research contains four basic topics، the first section related to methodology and regarding the conceptual framework it is discussed in the second section، and the third section concentrated at the presentation and the analysis Scientific results and practical results are section presented in the fourth.